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ETPL
GC-001
Smart Grid Last-Mile Communications Model and Its Application to the Study of
Leased Broadband Wired-Access
Abstract: This paper addresses the modeling of specific Smart Grid (SG) communication requirements from
a data networking research perspective, as a general approach to the study of different access technologies
suitable for the last mile (LM). SGLM networks serve customers' Energy Services Interfaces. From
functional descriptions of SG, a traffic model is developed. It is then applied to the study of an access
architecture based on leased lines from local broadband access providers. This permits consideration of the
potential starvation of domestic traffic, which is avoided by applying well-known traffic management
techniques. From previous results obtained for a purpose-built WiMAX SGLM network, the intuition that a
leased broadband access yields lower latencies is verified. In general, the proposed traffic model simplifies
the design of benchmarks for the comparison of candidate access technologies.
ETPL
GC-002
Performance Analysis of Multiuser Selection Scheme in Dynamic Home Area Networks
for Smart Grid Communications
In this paper, multiuser selection scheme is employed in dynamic home area networks (HANs) for smart
grid communications, to reduce the effects of fading at the receiver part of smart meter. The performance of
multiuser selection scheme is evaluated in two cases: in the absence of interference and in the presence of
multiuser interference (MUI). In the former case, the closed-form capacity outage probability as well as the
numerical values of the bit error rate (BER) are obtained via the probability density function (PDF) of signal
to noise ratio (SNR) that is derived from the amplitude distribution property of the classic indoor Saleh-
Valenzuela (S-V) channel. In the latter case, the multiuser interference cancellation coefficient as a random
variable is added for the calculation of signal to interference noise ratio (SINR). In addition, due to free
space path loss and log-normal shadowing, the sum of MUI is treated as another log-normal-distributed
random variable by exploiting central limit theorem. Numerical results show that the performance of
multiuser selection scheme in HANs of smart grid is due to several factors, i.e., total number of devices in
HANs, traffic intensity, modulation scheme, and multiuser interference cancellation coefficient, etc.
ETPL
GC-003
Optimizations of Power Consumption and Supply in the Smart Grid: Analysis of the
Impact of Data Communication Reliability
Abstract: Data communications infrastructure will play an important role to transfer various information in
smart grid. In this paper, we consider the reliability of the smart grid data communications infrastructure and
its impact on the power consumption and supply optimizations. For optimizing the power consumption, we
consider a deferrable load scheduling method which is modeled by using a constrained Markov decision
process (CMDP) model, taking into account the unavailability of the home area network (HAN) and
neighborhood area network (NAN) gateways. For optimizing the power supply, we consider an economic
dispatch method which is modeled by using stochastic programming (SP), taking into account the
unavailability of the exact power demand and supply information. The power consumption and supply costs
are analyzed. In addition, we show how these costs can be reduced through the deployment of component
redundancy in the smart grid data communications infrastructure.
ETPL
GC-004
Smart Grid Communication: Its Challenges and Opportunities
The necessity to promote smart grid (SG) has been recognized with a strong consensus. The SG integrates
electrical grids and communication infrastructures and forms an intelligent electricity network working with

all connected components to deliver sustainable electricity supplies. Many advanced communication
technologies have been identified for SG applications with a potential to significantly enhance the overall
efficiency of power grids. In this paper, the challenges and applications of communication technologies in
SG are discussed. In particular, we identify three major challenges to implement SG communication
systems, including standards interoperability, cognitive access to unlicensed radio spectra, and cyber
security. The issues to implement SG communications on an evolutional path and its future trends are also
addressed. The aim of this paper is to offer a comprehensive review of state-of-the-art researches on SG
communications.
ETPL
GC-005
Scalable Solutions of Markov Games for Smart-Grid Infrastructure Protection
Abstract: The anticipated proliferation of cyber components for collecting information and controlling
operations of smart grids increases their vulnerability to a variety of cyber attacks. For instance, a large-scale
simultaneous attack on smart meters to destabilize the grid could be feasible via cyber means, which is not
viable via physical attacks alone. The interactions between the providers and attackers of the smart grid and
their optimal strategies can be modeled as a Markov game. However, the computational complexity of such
a game grows exponentially with the size of the infrastructure, making it impractical for smart grids of
reasonable sizes. In this paper, we show that when the players' current interest is a subset of the states only
and they are willing to accept small inaccuracies in the game solutions, many Markov game states can be
pruned. We present a pruning algorithm in which a threshold parameter is used to control qualitatively the
tradeoff between computation time and solution accuracy. The algorithm is iterative with decoupled state
values in each iteration, and we parallelize the state estimations to reduce the overall computation time. We
illustrate with examples that the pruning algorithm reduces the computation time greatly without losing
much precision in the game solutions, and that parallelization further reduces the computation time.
ETPL
GC-006
A Communication-Based Appliance Scheduling Scheme for Consumer-Premise Energy
Management Systems
Abstract: In this paper, a communication-based load scheduling protocol is proposed for in-home appliances
connected over a home area network. Specifically, a joint access and scheduling approach for appliances is
developed to enable in-home appliances to coordinate power usage so that the total energy demand for the
home is kept below a target value. The proposed protocol considers both “schedulable” appliances which
have delay flexibility, and “critical” appliances which consume power as they desire. An optimization
problem is formulated for the energy management controller to decide the target values for each time slot,
by incorporating the variation of electricity prices and distributed wind power uncertainty. We model the
evolution of the protocol as a two-dimensional Markov chain, and derive the steady-state distribution, by
which the average delay of an appliance is then obtained. Simulation results verify the analysis and show
cost saving to customers using the proposed scheme.
ETPL
GC-007
Decentralized Controls and Communications for Autonomous Distribution Networks
in Smart Grid
Abstract: The traditional power grid system was constructed in a centralized and radial topology where
power is generated and delivered from one end to the other. Conventional methods for unidirectional power
flow analysis will no longer be effective to control renewable energy sources implemented at the
consumption sector efficiently; new strategies are called for to facilitate the bidirectional flow incurred by

power production of the distributed energy resource units. The transformation will require intelligent
distribution automation by means of decentralized power management as well as information and
communications technologies to actualize smart grid modernization. In this paper, we design autonomous
distribution networks that take scalability into account by dividing the legacy distribution network into a set
of subnetworks. We tackle the power flow and power balance issues individually in parallel to optimize the
global distribution operation by our proposed power-control method. Meanwhile, we propose an overlay
multi-tier communications infrastructure for the underlying power network to analyze the traffic of data
information and control message required for associated power flow operation. Based on the proposed
schemes, we show that we can potentially improve the utilization of renewable energy production and
achieve data traffic reduction under decentralized operations as compared to legacy centralized management.
ETPL
GC-008
Priority-Based Traffic Scheduling and Utility Optimization for Cognitive Radio
Communication Infrastructure-Based Smart Grid
Abstract: Smart grid can be visualized as an intelligent control system over sensors and communication
platforms. Recently, wireless multimedia sensor networks (WMSNs) have shown its advantages for smart
grid by providing rich surveillance information for grid failure detection and recovery, energy source
monitoring, asset management, security, etc. On the other hand, cognitive radio (CR) networks have been
identified as a key wireless technology to reduce the communication interferences and improve the
bandwidth efficiency for smart grid communication. There is an essential need to use the CR communication
platform to support large-size and time-sensitive multimedia delivery for future smart grid system. In this
paper, we consider the heterogeneous characteristics of smart grid traffic including multimedia and propose
a priority-based traffic scheduling approach for CR communication infrastructure based smart grid system
according to the various traffic types of smart grid such as control commands, multimedia sensing data and
meter readings. Specifically, we develop CR channel allocation and traffic scheduling schemes taking into
consideration of channel switch and spectrum sensing errors, and solve a system utility optimization
problem for smart grid communication system. Our solutions are demonstrated through both analyzes and
simulations. This research opens a new vista of future smart grid communications.
ETPL
GC-009
Time Synchronization Attack in Smart Grid: Impact and Analysis
Abstract: Many operations in power grids, such as fault detection and event location estimation, depend on
precise timing information. In this paper, a novel Time Synchronization Attack (TSA) is proposed to attack
the timing information in smart grid. Since many applications in smart grid utilize synchronous
measurements and most of the measurement devices are equipped with global positioning system (GPS) for
precise timing, it is highly probable to attack the measurement system by spoofing the GPS. The
effectiveness of TSA is demonstrated for three applications of phasor measurement unit (PMU) in smart
grid, namely transmission line fault detection, voltage stability monitoring and event locationing. The
validity of TSA is demonstrated by numerical simulations.
ETPL
GC-010
Toward SWSs Discovery: Mapping from WSDL to OWL-S Based on Ontology Search
and Standardization Engine
Abstract: Semantic Web Services (SWSs) represent the most recent and revolutionary technology developed
for machine-to-machine interaction on the web 3.0. As for the conventional web services, the problem of
discovering and selecting the most suitable web service represents a challenge for SWSs to be widely used.

In this paper, we propose a mapping algorithm that facilitates the redefinition of the conventional web
services annotations (i.e., WSDL) using semantic annotations (i.e., OWL-S). This algorithm will be a part of
a new discovery mechanism that relies on the semantic annotations of the web services to perform its task.
The “local ontology repository” and “ontology search and standardization
engine” are the backbone of this algorithm. Both of them target to define any data type in the
system using a standard ontology-based concept. The originality of the proposed mapping algorithm is its
applicability and consideration of the standardization problem. The proposed algorithm is implemented and
its components are validated using some test collections and real examples. An experimental test of the
proposed techniques is reported, showing the impact of the proposed algorithm in decreasing the time and
the effort of the mapping process. Moreover, the experimental results promise that the proposed algorithm
will have a positive impact on the discovery process as a whole.
ETPL
GC-011
Battery Status-aware Authentication Scheme for V2G Networks in Smart Grid
Abstract: Vehicle-to-grid (V2G) is emerging as an attractive paradigm in smart grid, and provides power and
information services by periodically collecting power status of battery vehicles (BVs). During a BV's
interaction with power grid, it may be in one of the following states: charging, fully-charged (FC), and
discharging. In this paper, we identify that there are unique security challenges in a BV's different battery
states. Accordingly, we propose a battery status-aware authentication scheme (BASA) to address the issue
for V2G networks. In BASA, 1) an aggregated-identifier is proposed during the charging-to-FC state
transition to ensure that BVs can be authenticated without disclosing their real identities; 2) selective
disclosure based challenge-response authentication is presented during the FC-to-discharging phase to
realize anonymous data transmission; 3) an aggregated-status is reported during the discharging-to-charging
transition in order to hide a BV's power level from an aggregator. In addition, we perform comprehensive
security analysis, which shows that BASA achieves both privacy preservation and security protection during
battery state transitions. The analysis also indicates that battery status awareness is crucial for BVs' secure
operations for V2G networks in smart grid.
ETPL
GC-012
Dependable Demand Response Management in the Smart Grid: A Stackelberg Game
Approach
Abstract: Demand Response Management (DRM) is a key component in the smart grid to effectively reduce
power generation costs and user bills. However, it has been an open issue to address the DRM problem in a
network of multiple utility companies and consumers where every entity is concerned about maximizing its
own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to
maximize the revenue of each utility company and the payoff of each user. We derive analytical results for
the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed
algorithm which converges to the equilibrium with only local information available for both utility
companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can
be succeptible to privacy and security issues because of communication links between the utility companies
and the consumers. We study the impact of an attacker who can manipulate the price information from the
utility companies. We also propose a scheme based on the concept of shared reserve power to improve the
grid reliability and ensure its dependability

ETPL
GC-013
A Generic Query Model for the Unified Discovery of Heterogeneous Services
Abstract: In this paper, we propose Proteus, a generic query model for the discovery of operations offered by
heterogeneous services. We demonstrate the need for such a model, and show how it unifies the task of
service discovery through abstractions, which allow for the technology-independent formulation of service
advertisements, queries, and query responses. On top of these generic elements, we build an intuitive, fuzzy-
based query evaluation mechanism that supports the service matchmaking process by employing and
appropriately combining existing similarity metrics. Thanks to the generality of Proteus, it is possible to
seamlessly accommodate the discovery of operations provided by various types of services without the need
of changing the existing service infrastructure. Thus, our approach is applicable to a variety of settings
ranging from traditional web services to service-oriented grids, peer-to-peer networks, geospatial
information systems, and so on. Overall, compared to the existing query models supported by standard
service discovery technologies, our approach is marked by openness, flexibility, and improved performance
in terms of precision and recall. The feasibility and efficiency of Proteus are verified by a series of
experiments.
ETPL
GC-014
Reliable Wireless Communication Networks for Demand Response Control
Abstract: This paper presents methodologies for deriving reliability performance of wireless communication
networks to support demand response (DR) control. First, the impact of communication impairments on a
direct DR control program is investigated. Second, the outage probability of a wireless link is modelled and
quantified, considering the multipath fading, shadowing, and random path loss given the location
distribution of smart meters. Third, the distributions of packet delivery ratio are derived for two wireless
network architectures: the single-hop infrastructure-based network and the multi-hop mesh network.
Simulation results verify the above reliability models and provide important insights on the coverage of
wireless communication networks considering the reliability requirements of DR programs.
ETPL
GC-015
UDP: Usage-Based Dynamic Pricing With Privacy Preservation for Smart Grid
Abstract: Smart sensing and wireless communication technologies enable the electric power grid system to
deliver electricity more efficiently through the dynamic analysis of the electricity demand and supply. The
current solution is to extend the traditional static electricity pricing strategy to a time-based one where peak-
time prices are defined to influence electricity usage behavior of customers. However, the time-based
pricing strategy is not truly dynamic and the electricity resource cannot be optimally utilized in real time. In
this paper, we propose a usage-based dynamic pricing (UDP) scheme for smart grid in a community
environment, which enables the electricity price to correspond to the electricity usage in real time. In the
UDP scheme, to simplify price management and reduce communication overhead, we introduce distributed
community gateways as proxies of the utility company to timely respond to the price enquiries from the
community customers. We consider both community-wide electricity usage and individual electricity usage
as factors into price management: a customer gets higher electricity unit price if its own electricity usage
becomes larger under certain conditions of the community-wide collective electricity usage. Additionally,
we protect the privacy of the customers by restricting the disclosure of the individual electricity usage to the
community gateways. Lastly, we provide privacy and performance analysis to demonstrate that the UDP

scheme supports real-time dynamic pricing in an efficient and privacy-preserving manner.
ETPL
GC-016
Detecting Critical Nodes in Interdependent Power Networks for Vulnerability
Assessment
Abstract: Power networks and information systems become more and more interdependent to ensure better
supports for the functionality as well as improve the economy. However, power networks also tend to be
more vulnerable due to the cascading failures from their interdependent information systems, i.e., the
failures in the information systems can cause the failures of the coupled portion in power networks.
Therefore, the accurate vulnerability assessment of interdependent power networks is of great importance in
the presence of unexpected disruptive events or adversarial attacks targeting on critical network nodes. In
this paper, we study the Interdependent Power Network Disruptor (IPND) optimization problem to identify
critical nodes in an interdependent power network whose removals maximally destroy its functions due to
both malfunction of these nodes and the cascading failures of its interdependent communication network.
First, we show the IPND problem is NP-hard to be approximated within the factor of (2-ε) . Despite its
intractability, we propose a greedy framework with novel centrality functions based on the networks'
interdependencies, to efficiently solve this problem in a timely manner. An extensive experiment not only
illustrates the effectiveness of our approach on networks with different topologies and interdependencies,
but also highlights some important observations which help to sharpen the robustness of interdependent
networks in the future.
ETPL
GC-017
Proactive and Reactive Runtime Service Discovery: A Framework and Its Evaluation
Abstract: The identification of services during the execution of service-based applications to replace services
in them that are no longer available and/or fail to satisfy certain requirements is an important issue. In this
paper, we present a framework to support runtime service discovery. This framework can execute service
discovery queries in pull and push mode. In pull mode, it executes queries when a need for finding a
replacement service arises. In push mode, queries are subscribed to the framework to be executed
proactively and, in parallel with the operation of the application, to identify adequate services that could be
used if the need for replacing a service arises. Hence, the proactive (push) mode of query execution makes it
more likely to avoid interruptions in the operation of service-based applications when a service in them
needs to be replaced at runtime. In both modes of query execution, the identification of services relies on
distance-based matching of structural, behavioral, quality, and contextual characteristics of services and
applications. A prototype implementation of the framework has been developed and an evaluation was
carried out to assess the performance of the framework. This evaluation has shown positive results, which
are discussed in the paper.
ETPL
GC-018
Bad Data Injection Attack and Defense in Electricity Market Using Game Theory
Study
Abstract: Applications of cyber technologies improve the quality of monitoring and decision making in
smart grid. These cyber technologies are vulnerable to malicious attacks, and compromising them can have
serious technical and economical problems. This paper specifies the effect of compromising each
measurement on the price of electricity, so that the attacker is able to change the prices in the desired
direction (increasing or decreasing). Attacking and defending all measurements are impossible for the

attacker and defender, respectively. This situation is modeled as a zero-sum game between the attacker and
defender. The game defines the proportion of times that the attacker and defender like to attack and defend
different measurements, respectively. From the simulation results based on the PJM 5-Bus test system, we
can show the effectiveness and properties of the studied game.
ETPL
GC-019
An Empirical Study of Communication Infrastructures Towards the Smart Grid:
Design, Implementation, and Evaluation,
Abstract: The smart grid features ubiquitous interconnections of power equipments to enable two-way flows
of electricity and information for various intelligent power management applications, such as accurate relay
protection and timely demand response. To fulfill such pervasive equipment interconnects, a full-fledged
communication infrastructure is of great importance in the smart grid. There have been extensive works on
disparate layouts of communication infrastructures in the smart grid by surveying feasible wired or wireless
communication technologies, such as power line communications and cellular networks. Nevertheless,
towards an operable, cost-efficient and backward-compatible communication solution, more comprehensive
and practical understandings are still urgently needed regarding communication requirements, applicable
protocols, and system performance. Through such comprehensive understandings, we are prone to answer a
fundamental question, how to design, implement and integrate communication infrastructures with power
systems. In this paper, we address this issue in a case study of a smart grid demonstration project, the Future
Renewable Electric Energy Delivery and Management (FREEDM) systems. By investigating
communication scenarios, we first clarify communication requirements implied in FREEDM use cases.
Then, we adopt a predominant protocol framework, Distributed Network Protocol 3.0 over TCP/IP (DNP3
over TCP/IP), to practically establish connections between electric devices for data exchanges in a small-
scale FREEDM system setting, Green Hub. Within the real-setting testbed, we measure the message
delivery performance of the DNP3-based communication infrastructure. Our results reveal that diverse
timing requirements of message deliveries are arguably primary concerns in a way that dominates viabilities
of protocols or schemes in the communication infrastructure of the smart grid. Accordingly, although DNP3
over TCP/IP is widely considered as a smart grid co- munication solution, it cannot satisfy communication
requirements in some time-critical scenarios, such as relay protections, which claim a further optimization
on the protocol efficiency of DNP3.
ETPL
GC-020
Trust System Design Optimization in Smart Grid Network Infrastructure
Abstract: The imposed communication network brings more vulnerabilities to the evolving smart grid.
Therefore, defensive techniques such as intrusion detection will need to be deployed in this already
complicated system. Deployment and runtime cost due to the defensive trust systems will affect the original
function of smart grid system without careful planning and design. This paper is an effort to address this
important issue. In particular, the set packing algorithm is used to optimize the placement of the trust nodes
of the defensive system in the multiple layer architecture of the smart grid. After the trust nodes are placed, a
trust node aware optimal routing algorithm is used to find the least cost routing in the communications of the
nodes. Also, an algorithm to identify new trust node(s) is presented to address the fault tolerance
requirement of the smart grid system. Simulation results demonstrate that our approach is promising by
providing secure, efficient, and reliable communications in the smart grid network.

ETPL
GC-021
A Decentralized Security Framework for Data Aggregation and Access Control in
Smart Grids
Abstract: We propose a decentralized security framework for smart grids that supports data aggregation and
access control. Data can be aggregated by home area network (HAN), building area network (BAN), and
neighboring area network (NAN) in such a way that the privacy of customers is protected. We use
homomorphic encryption technique to achieve this. The consumer data that is collected is sent to the
substations where it is monitored by remote terminal units (RTU). The proposed access control mechanism
uses attribute-based encryption (ABE) which gives selective access to consumer data stored in data
repositories and used by different smart grid users. RTUs and users have attributes and cryptographic keys
distributed by several key distribution centers (KDC). RTUs send data encrypted under a set of attributes.
Since RTUs are maintained in the substations they are well protected in control rooms and are assumed to be
trusted. Users can decrypt information provided they have valid attributes. The access control scheme is
distributed in nature and does not rely on a single KDC to distribute the keys which makes the approach
robust. To the best of our knowledge, ours is the first work on smart grids, which integrates these two
important security components (privacy preserving data aggregation and access control) and the first paper
which addresses access control in smart grids.
ETPL
GC-022
Reliability Analysis of Substation Automation System Functions Using PRMs
Abstract: The current trend for building an ontology-based data management system (DMS) is to capitalize
on efforts made to design a preexisting well-established DMS (a reference system). The method amounts to
extracting from the reference DMS a piece of schema relevant to the new application needs-a module-,
possibly personalizing it with extra constraints w.r.t. the application under construction, and then managing
a data set using the resulting schema. In this paper, we extend the existing definitions of modules and we
introduce novel properties of robustness that provide means for checking easily that a robust module-based
DMS evolves safely w.r.t. both the schema and the data of the reference DMS. We carry out our
investigations in the setting of description logics which underlie modern ontology languages, like RDFS,
OWL, and OWL2 from W3C. Notably, we focus on the DL-liteA dialect of the DL-lite family, which
encompasses the foundations of the QL profile of OWL2 (i.e., DL-liteR): the W3C recommendation for
efficiently managing large data sets.
ETPL
GC-023
Efficient Service Skyline Computation for Composite Service Selection
Abstract: This paper presents the application of a framework for reliability analysis of substation automation
(SA) system functions. The framework is based on probabilistic relational models which combines
probabilistic reasoning offered by Bayesian networks together with architecture models in form of entity
relationship diagrams. In the analysis, both the physical infrastructure, and the logical structure of the
system, is regarded in terms of qualitative modeling and quantitative analysis. Moreover, the framework
treats the aspect of failures caused by software. An example is detailed with the framework applied to an
IEC 61850-based SA system. The logical structure, including functions and their relations, is modeled in
accordance with Pieces of Information for COMmunication (PICOM) defined in the IEC 61850 standard.
By applying PICOMs as frame of reference when modeling functions the model instantiation becomes more
standardized compared to subjectively defining functions. A quantitative reliability analysis is performed on

a function for tipping a circuit breaker in case of mismatch between currents. The result is presented both in
terms of a qualitative architecture model and a quantitative result showing the probability of successful
operation during a period of one year.
ETPL
GC-024
Exploring Malicious Meter Inspection in Neighborhood Area Smart Grids
Abstract: In smart grids, smart meters may potentially be attacked or compromised to cause certain security
risks. It is challenging to identify malicious meters when there are a large number of users. In this paper, we
explore the malicious meter inspection (MMI) problem in neighborhood area smart grids. We propose a
suite of inspection algorithms in a progressive manner. First, we present a basic scanning method, which
takes linear time to accomplish inspection. The scanning method is efficient when the malicious meter ratio
is high. Then, we propose a binary-tree-based inspection algorithm, which performs better than scanning
when the malicious meter ratio is low. Finally, we employ an adaptive-tree-based algorithm, which
leverages advantages of both the scanning and binary-tree inspections. Our approaches are tailored to fit
both static and dynamic situations. The theoretical and experimental results have shown the effectiveness of
the adaptive tree approach.
ETPL
GC-025
Real-Time Opportunistic Scheduling for Residential Demand Response
Abstract: Demand response is a key feature of the smart grid. The addition of bidirectional communication
to today's power grid can provide real-time pricing (RTP) to customers via smart meters. A growing number
of appliance companies have started to design and produce smart appliances which embed intelligent control
modules to implement residential demand response based on RTP. However, most of the current residential
load scheduling schemes is centralized and based on either day-ahead pricing (DAP) or predicted price,
which can deviate significantly from the RTP. In this paper, we propose an opportunistic scheduling scheme
based on the optimal stopping rule as a real-time distributed scheduling algorithm for smart appliances'
automation control. It determines the best time for appliances' operation to balance electricity bill reduction
and inconvenience resulting from the operation delay. It is shown that our scheme is a distributed threshold
policy when no constraint is considered. When a total power constraint exists, the proposed scheduling
algorithm can be implemented in either a centralized or distributed fashion. Our scheme has low complexity
and can be easily implemented. Simulation results validate proposed scheduling scheme shifts the operation
to off-peak times and consequently leads to significant electricity bill saving with reasonable waiting time.
ETPL
GC-026
Modeling Cyber-Physical Vulnerability of the Smart Grid With Incomplete
Information
Abstract: This paper addresses the attack modeling using vulnerability of information, communication and
electric grid network. Vulnerability of electric grid with incomplete information has been analyzed using
graph theory based approach. Vulnerability of information and communication (cyber) network has been
modeled utilizing concepts of discovery, access, feasibility, communication speed and detection threat.
Common attack vector based on vulnerability of cyber and physical system have been utilized to operate
breakers associated with generating resources to model aurora-like event. Real time simulations for modified
IEEE 14 bus test case system and graph theory analysis for IEEE 118 bus system have been presented. Test
case results show the possible impact on smart grid caused by integrated cyber-physical attack.

ETPL
GC-027
Outage-Storage Tradeoff in Frequency Regulation for Smart Grid With Renewables
Abstract: Future power grid systems are envisioned to be integrated with many distributed renewable energy
sources (DRES). Energy storage is a key technology to enable reliable and cost-effective renewable energy.
Given the fact that a large-scale energy storage device is usually costly to install and operate, we are
naturally led to the following question: How much storage is necessary to guarantee the stability of a power
grid network with DRESs? This paper represents a first step in systematically exploring the tradeoff between
the capacity of energy storage devices and the outage probability, i.e., the probability of the occurrence of
imbalance between the supply and demand. We first propose a secure scheduling and dispatch (SSD)
algorithm that is capable of maintaining the grid stability in the presence of volatility in the power
generation. We then derive a closed-form bound to quantify the tradeoff between the storage capacity and
the outage probability. Under mild assumptions, we show that the outage probability decreases
exponentially with respect to the square of the storage capacity. This finding implies that energy storage is
an effective and economically viable solution to maintain the stability of a smart grid network, even in the
presence of many volatile and intermittent renewable energy sources. The impact of correlation in energy
generation on the stability of a smart grid network is also investigated .
ETPL
GC-028
Multilayer Consensus ECC-Based Password Authenticated Key-Exchange (MCEPAK)
Protocol for Smart Grid System
Abstract: This paper aims at providing a key agreement protocol for smart grid to cope with access control
of appliances/devices located inside a Home Area Network (HAN) by a set of controllers outside the HAN.
The commands/packets initiated by the controllers in crisis cases should be delivered fast and immune from
any interruption. The HAN controller, which acts as a gateway, should not cause any delay by decrypting
and re-encrypting the packets, nor should it has any chance to modify them. Considering the required level
of security and quality of service, we design our protocol with an Elliptic Curve Cryptography (ECC)
approach. We improve and implement the Password Authenticated Key Exchange (PAKE) protocol in two
steps. First, we propose an auxiliary mechanism that is an ECC version of PAKE, and then extend it to a
multilayer consensus model. We reduce the number of hash functions to one, and utilize a primitive
password shared between an appliance and HAN controller to construct four valid individual consensus and
authenticated symmetric keys between the appliance and upstream controllers by exchanging only 12
packets. Security analysis presents that our protocol is resilient to various attacks. Furthermore, performance
analysis shows that the delay caused by the security process is reduced by more than one half.
ETPL
GC-029
Relay-Aided Amplify-and-Forward Powerline Communications
Abstract: Powerline communications (PLC) is a favorable technique for many smart grid applications. By
transmitting information over the existing powerline infrastructure, PLC has the benefit of low deployment
cost. However, due to low transmit power, limited bandwidth, and harsh channel conditions, reliable long-
distance and high-capacity PLC is challenging. Relay-aided (RA-) PLC is promising in addressing these
issues. In this paper, we investigate the performance of the amplify-and-forward (AF) RA-PLC system from
an information-theoretic perspective. The capacity of AF-based RA-PLC is analyzed for frequency-selective
PLC channels. The capacity bounds are derived, and the optimal power allocation between the transmitting
nodes and the optimal power distribution over the signal frequency band are obtained. The capacity benefits

and features of AF-based RA-PLC are evaluated with two prevalent powerline channel models. Based on the
signal attenuation model, the capacity of AF-based RA-PLC is compared with direct-link (DL-)PLC, and the
effect of relay location is revealed. In addition, based on the transmission line (TL) model, the effects of
branch density and load impedance on the capacity of AF-based RA-PLC are evaluated.
ETPL
GC-030
A Noninvasive Threat Analyzer for Advanced Metering Infrastructure in Smart Grid
Abstract: Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a
highly complex network configuration. AMI comprises heterogeneous cyber-physical components, which
are interconnected through different communication media, protocols, and security measures. They are
operated using different data delivery modes and security policies. The inherent complexity and
heterogeneity in AMI significantly increases the potential of security threats due to misconfiguration or
absence of defense, which may cause devastating damage to AMI. Therefore, there is a need for creating a
formal model that can represent the global behavior of AMI configuration in order to verify the potential
threats. In this paper, we present SmartAnalyzer, a security analysis tool, which offers manifold
contributions: (i) formal modeling of AMI configuration that includes device configurations, topology,
communication properties, interactions among the devices, data flows, and security properties; (ii) formal
modeling of AMI invariants and user-driven constraints based on the interdependencies among AMI device
configurations, security properties, and security control guidelines; (iii) verifying the AMI configuration's
compliance with security constraints using a Satisfiability Modulo Theory (SMT) solver; (iv) reporting of
potential security threats based on constraint violations, (v) analyzing the impact of potential threats on the
system; and (vi) systematic diagnosing of SMT unsatisfiable traces and providing necessary remediation
plans. The accuracy and scalability of the tool are evaluated on an AMI testbed and various synthetic test
networks.
ETPL
GC-031
Taming Uncertainties in Real-Time Routing for Wireless Networked Sensing and
Control
Abstract: Real-time routing is a basic element of closed-loop, real-time sensing and control, but it is
challenging due to dynamic, uncertain link/path delays. The probabilistic nature of link/path delays makes
the basic problem of computing the probabilistic distribution of path delays NP-hard, yet quantifying
probabilistic path delays is a basic element of real-time routing and may well have to be executed by
resource-constrained devices in a distributed manner; the highly varying nature of link/path delays makes it
necessary to adapt to in-situ delay conditions in real-time routing, but it has been observed that delay-based
routing can lead to instability, estimation error, and low data delivery performance in general. To address
these challenges, we propose the Multi-Timescale Estimation (MTE) method; by accurately estimating the
mean and variance of per-packet transmission time and by adapting to fast-varying queueing in an accurate,
agile manner, MTE enables accurate, agile, and efficient estimation of probabilistic path delay bounds in a
distributed manner. Based on MTE, we propose the Multi-Timescale Adaptation (MTA) routing protocol;
MTA integrates the stability of an ETX-based directed-acyclic-graph (DAG) with the agility of
spatiotemporal data flow control within the DAG to ensure real-time data delivery in the presence of
dynamics and uncertainties. We also address the challenges of implementing MTE and MTA in resource-
constrained devices such as TelosB motes. We evaluate the performance of MTA using the NetEye and

Indriya sensor network testbeds. We find that MTA significantly outperforms existing protocols, e.g.,
improving deadline success ratio by 89% and reducing transmission cost by a factor of 9.7 in the NetEye
testbed.
ETPL
GC-032
Sensing-Performance Tradeoff in Cognitive Radio Enabled Smart Grid
Abstract: Smart grid is widely considered to be the next generation of power grid, where power generation,
management, transmission, distribution, and utilization are fully upgraded to improve agility, reliability,
efficiency, security, economy, and environmental friendliness. Demand response management (DRM) is
recognized as a control unit of the smart grid, with the attempt to balance the real-time load as well as to
shift the peak-hour load. Communications are critical to the accuracy and optimality of DRM, and hence at
the core of the control performance of the smart grid. In this paper, we introduce cognitive radio into the
smart grid to improve the communication quality. By means of spectrum sensing and channel switching,
smart meters can decide to transmit data on either an original unlicensed channel or an additional licensed
channel, so as to reduce the communication outage. Considering the energy cost taxed by spectrum sensing
together with the control performance degradation incurred by imperfect communications, we formulate the
sensing-performance tradeoff problem between better control performance and lower communication cost,
paving the way towards a green smart grid. The impact of the communication outage on the control
performance of DRM is also analyzed, which reduces the profit of power provider and the social welfare of
the smart grid, although it may not always decrease the profit of power consumer. By employing the energy
detector, we prove that there exists a unique optimal sensing time which yields the maximum tradeoff
revenue, under the constraint that the licensed channel is sufficiently protected. Numerical results are
provided to validate our theoretical analysis.
ETPL
GC-033
Optimizing Electric Vehicle Charging With Energy Storage in the Electricity Market
The Information and Communication Technologies (ICT) that are currently under development for future
smart grid systems can enable load aggregators to have bidirectional communications with both the grid and
Electric Vehicles (EVs) to obtain real-time price and load information, and to adjust EV charging schedules
in real time. In addition, Energy Storage (ES) can be utilized by the aggregator to mitigate the impact of
uncertainty and inaccurate prediction. In this paper, we study a problem of scheduling EV charging with ES
from an electricity market perspective with joint consideration for the aggregator energy trading in the day-
ahead and real-time markets. We present a Mixed Integer Linear Programming (MILP) model to provide
optimal solutions as well as a simple polynomial-time heuristic algorithm based on LP rounding. In addition,
we present a communication protocol for interactions among the aggregator, the ES, the power grid, and
EVs, and demonstrate how to integrate the proposed scheduling approach in real-time charging operations.
Extensive simulation results based on real electricity price and load data have been presented to justify the
effectiveness of the proposed approach and to show how several key parameters affect its performance.
ETPL
GC-034
Stability Enhancement of Decentralized Inverter Control Through Wireless
Communications in Microgrids
Abstract: Decentralized inverter control is essential in distributed generation (DG) microgrids for low
deployment/operation cost and high reliability. However, decentralized inverter control suffers from a
limited system stability mainly because of the lack of communications among different inverters. In this

paper, we investigate stability enhancement of the droop based decentralized inverter control in microgrids.
Specifically, we propose a power sharing based control strategy which incorporates the information of the
total real and reactive power generation of all DG units. The information is acquired by a wireless network
(such as a WiFi, ZigBee, and/or cellular communication network) in a decentralized manner. Based on the
desired power sharing of each DG unit and the acquired information of total generation, additional control
terms are added to the traditional droop controller. We evaluate the performance of the proposed control
strategy based on small-signal stability analysis. As timely communication may not be established for a
microgrid with low-cost wireless communication devices, two kinds of analytical models are developed with
respect to negligible and nonnegligible communication delays, respectively. Extensive numerical results are
presented to demonstrate the system stability under the proposed control strategy with respect to different.
ETPL
GC-035
Privacy-Aware Profiling and Statistical Data Extraction for Smart Sustainable Energy
Systems
Abstract: The growing population and global warming have been calling for more effective energy usage,
which have stimulated the emergence of smart sustainable energy technology. The distinct feature of this
newly emerging technology is the incorporation of advanced information and communication technologies
(ICT), which collects more detailed information on how energy is generated, distributed, and consumed.
Various smart metering technologies have also been proposed to support the optimization on sustainable
energy usage. Despite the obvious benefits of these technologies, people may still hesitate to adopt them
because of possible privacy breach. On the other hand, we observe that the major target information for
making the sustainable energy system smart is the aggregated statistics of energy usage, not the full detailed
usage profiles which would compromise customers' privacy. Thus, how to design schemes to collect
aggregated statistics while preserving customers' privacy becomes an important research problem. In this
paper, we propose two schemes to deal with this problem. The first one can support dynamic profiling,
which can extract aggregated statistical information without compromising individual privacy. The second
one aims to extract correlation information among various factors for the smart system design and can also
be used as an underlying tool for baseline inference and association rule mining.
ETPL
GC-036
Multi-Objective Optimal Energy Consumption Scheduling in Smart Grids
Abstract: A major source of inefficiency in power grids is the underutilization of generation capacity. This
is mainly because load demand during peak hours is much larger than that during off-peak hours. Moreover,
extra generation capacity is needed to maintain a security margin above peak load demand. As load demand
keeps increasing and two-way communications are enabled by smart meters (SMs), demand response (DR)
has been proposed as an alternative to installing new power plants in smart grids. DR makes use of real-time
schemes to allow users to modify their load demand patterns according to their energy consumption costs. In
particular, when load demand is high, energy consumption cost will be high and users may decide to
postpone certain amount of their consumption needs. This strategy may effectively reduce the peak load
demand and increases the off-peak demand, and hence could increase existing generation capacity utilization
and reduce the need to install extra generation plants. In this paper, we consider a third-party managing the
energy consumption of a group of users, and formulate the load scheduling problem as a constrained multi-
objective optimization problem (CMOP). The optimization objectives are to minimize energy consumption
cost and to maximize a certain utility, which can be conflicting and non-commensurable. We then develop

two evolutionary algorithms (EAs) to obtain the Pareto-front solutions and the ε-Pareto front solutions to the
CMOP, respectively, which are validated by extensive simulation results.
ETPL
GC-037
Advanced Power Distribution System Configuration for Smart Grid
Abstract: Power distribution systems should meet demands such as high reliability, efficiency, and
penetration of renewable energy generators (REGs) in a smart grid. In general, power distribution systems
are radial in nature. One-way power flow is the advantage of a radial system. However, the introduction of
REGs causes bidirectional power flow. Furthermore, there are limits to improvements in reliability and
efficiency in a radial system. Therefore, the upgrading of primary feeders from a radial to a loop
configuration has been considered in the Korea Smart Distribution Project. An advanced power distribution
system (APDS), in which primary feeders operate in a loop configuration, has been explored in this paper.
First, the design scheme of a conventional power distribution system configuration that adopts distribution
automation is introduced. Subsequently, an upgrading scheme of loop configuration using normally opened
tie switches and a tie switch selection algorithm for loss minimization are described. Finally, the advantages
of the upgraded configuration are reported through case studies. It is observed that the APDS configuration
can integrate more REGs from the viewpoint of voltage regulation. An advanced distribution system
allowing greater use of REGs will be a major contribution to smart grid implementation.
ETPL
GC-038
Smart Operation of HVDC Systems for Large Penetration of Wind Energy Resources
Abstract: The target for South Korea's domestic energy consumption is to increase the proportion of the total
energy consumption supplied by renewable energy to 11% by 2030. Increasing renewable energy generation
has become a natural trend, thereby making it an essential factor to be considered in research for the
development of a smart grid. The power system of Jeju Island is connected to the mainland (the Korean
Peninsula) through HVDC #1, with another line, HVDC #2, presently under construction. The purpose of
the first HVDC construction was essentially to supply a portion of the power supply to the Jeju area.
However, if the construction of HVDC #2 is completed, the role of the Jeju HVDC system in the Jeju power
system will be changed significantly. If flexibility through the operation of an HVDC system is increased,
more wind farms can be built on Jeju Island. In addition, depending on the operation of HVDC #1 and #2,
the stability of the Jeju power system will be changed greatly. In this paper, the operation of the HVDC lines
and its impacts are analyzed.
ETPL
GC-039
Operation Schemes of Smart Distribution Networks With Distributed Energy
Resources for Loss Reduction and Service Restoration
Abstract: The integration of Distributed Energy Resources (DERs) into the future Smart Distribution
Network (SDN) has challenging issues regarding the successful development of smart grids. The SDN offers
new opportunities in the improvement of the efficiency of power distribution networks. The DERs will be
distributed in the existing distribution networks, interconnected in customer areas and operated on its own
schedule without communication to the control center of the existing distribution system. The DER units
have both positive and negative effects regarding SDN operations. With the appropriate operation of the
DER units in the SDN, losses can be reduced during normal operations and they can support local loads
during abnormal conditions. Thus, the positive effects of the DER units need to be enabled in the SDN by
adopting advanced operation schemes. In this paper, the smart control functions for the DER units in the

SDN are defined and classified. In addition, the integration schemes for the SDN with DER units are
introduced. The proposed operation strategies will be implemented into the Korean Smart Distribution
Management System (KSDMS) as operation schemes used for loss reduction and service restoration. A
sample case study shows the effectiveness of the proposed operation schemes to achieve smart operation
functions for the SDN with DER units.
ETPL
GC-040
Design of Smart Distribution Management System for Obtaining Real-Time Security
Analysis and Predictive Operation in Korea
Abstract: The Development of smart grids offers new opportunities to improve the efficiency of operating
and controlling distribution systems. It allows network operators to optimize the use of dispersed generation
resources and enables real-time communication between customers and utility service providers to allow
optimization and balancing of energy usage. Such an improvement in the flexibility and control of the
distribution network is only possible if the control center operator has more accurate knowledge of the real-
time situation of the network. The Korean Smart Distribution Management System (KSDMS) project was
started in 2009 to achieve advanced distribution operation for potential smart grid systems in Korea. In this
paper, we summarize two KSDMS design strategies for situational awareness in real-time distribution
operation. One is the preparation of standardized data acquisition networks. In the KSDMS, numerous data
related to the voltage, current, faults, power quality and load profiles of the network are gathered using a
standardized communication method based on IEC 61850. The other is a real-time security analysis tools for
smart distribution systems, designed to provide the distribution operator with accurate real-time situational
information and predictive operation. We present a database design which can be used commonly for all
security analysis programs in KSDMS.
ETPL
GC-041
Price Elasticity of Demand Modeling With Economic Effects on Electricity Markets
Using an Agent-Based Model
Abstract: Automated Metering Infrastructure (AMI) is a technology that would allow consumers to exhibit
price elasticity of demand under smart-grid environments. The market power of the generation and
transmission companies can be mitigated when consumers respond to price signals. Such responses by
consumers can also result in reductions in price spikes, consumer energy bills, and emissions of greenhouse
gases and other pollutants. In this paper, we use the Electricity Market Complex Adaptive System
(EMCAS), an agent-based model that simulates restructured electricity markets, to explore the impact of
consumers' price elasticity of demand on the performance of the electricity market. An 11-node test network
with eight generation companies and five aggregated consumers is simulated for a period of one month.
Results are provided and discussed for a case study based on the Korean power system.
ETPL
GC-042
Power Scheduling of Distributed Generators for Economic and Stable Operation of a
Microgrid
Abstract: This paper is concerned with the power dispatch problem of distributed generators (DGs) for
optimal operation of a microgrid. The objective is to minimize the fuel cost during the grid-connected
operation, while ensuring stable operation after islanding. To achieve this goal, the economic dispatch (ED)
problem and related constraints are formulated. The constraints considered in this study are: i) reserve for
variation in load demand, ii) reserve for variation in the power outputs of non-dispatchable DGs, iii) flow
limits between two adjacent areas, and iv) reserve for the stable islanded operation. The first three
constraints, which have been employed in ED problem for conventional power systems, are modified to

apply to Microgrids. We also provide a detailed formulation of the constraint for stable islanded operation in
accordance with two power-sharing principles: i) fixed droop and ii) adjustable droop. The problem is
solved using a modified direct search method, and the effect of the constraints on the operational cost is
investigated via numerical simulations.
ETPL
GC-043
State Estimation for Supervisory Monitoring of Substations
Abstract: This paper introduces the application of state estimation to double bus double breaker distribution
substations, which are typically used in the Korean power system, to improve the reliability of substation
automation systems. In spite of the recent remarkable progress in the field of sensors and equipments, it is
hard to detect device malfunctions or degraded devices automatically in the supervisory monitoring system.
The object of the proposed system is not the state estimation itself, but its application to the supervisory
detection of the malfunction or degradation of the devices. The supervisory monitoring process consists of a
two step procedure-topology processing and normal state estimation. In a substation, the on-off states of the
circuit breakers determine the topology. This paper mainly presents the topology processing expert system
including the knowledge representation. The expert system is operated with a predefined period to identify
and correct topological errors in the distribution substations. The proposed system is now in the field test
stage in the Sanchung pilot substation and it will be applied to the next generation substation automation
system in Korea.
ETPL
GC-044
Study of the Effectiveness of a Korean Smart Transmission Grid Based on Synchro-
Phasor Data of K-WAMS
Abstract: ecent technological achievement in areas of distributed computing, networking, high speed
communications and digital control, as well as the availability of accurate GPS time source, are rapidly
becoming the enabling factors for the development of a new generation of real time power grid monitoring
tools. KDN (Korea electric power Date Network Co.) R&D department with KERI, Korea University and
LSIS has embarked on long term research and development work in the field of wide area systems
specifically applied to the power transmission grid in Korea. Primary focus will be on wide area
measurement and monitoring, analysis, assessment technique and tools aimed at preventing the propagation
of power grid instabilities. Of special interest are voltage stability and small signal stability. This project
aligns with KEPCO (the Korea Electric Power Company). In this paper, case studies performed with the use
of the developed system are presented.
ETPL
GC-045
Modified Dynamic Phasor Estimation Algorithm for the Transient Signals of
Distributed Generators
Abstract: In this paper, a modified dynamic phasor estimation method for protection relays is proposed to
calculate the dynamic phasor of a fundamental frequency component with time-variant amplitude. The fault
current is assumed to be the combination of a decaying dc offset, a decaying fundamental frequency
component and harmonics with constant amplitude. The exponential functions of the decaying dc offset and
fundament frequency component are replaced by Taylor series. Then, the LS (Least Square) technique is
used to estimate the magnitudes and the time constants of decaying components. The performance of the
algorithm is evaluated by using computer-simulated signals based on simple equations and fault current
signals collected from DFIG wind farm model in MATLAB Simulink. The test results indicate that the
proposed algorithm can accurately estimate the decaying amplitude and the time constant of the fundamental

frequency component.
ETPL
GC-046
DSM Considered Probabilistic Reliability Evaluation and an Information System for
Power Systems Including Wind Turbine Generators
Abstract: This paper proposes a methodology for evaluating the probabilistic reliability, considering demand
side management (DSM) and Web based on a daily interval reliability information system for a grid
constrained composite power system including wind turbine generators(WTG). The proposed model can
consider capacity limitations and transmission line unavailabilities and the operation of WTG modeled by
multi-states. The importance of renewable energy sources is growing at a rapid rate due to environmental
concerns. A web based online daily time interval reliability integrated information system (WORRIS) is
applied using the methodology proposed in this paper. This paper describes the architecture of the WORRIS
Version 7.0 system.
ETPL
GC-047
A Quantitative Analysis on Future World Marketability of HTS Power Industry
Abstract: This study estimates total world market volumes of HTS power industry, one of the main smart
grid equipment in the future when the market penetration ratio reaches 100% in the future. The results of
this paper are based on the GOULDEN Report providing the total market volumes of conventional power
industry for the world market. This study determines the market penetration ratio using the judgment method
with market penetration S-curve induced from Delphi method and Product Life Cycle from 2011 (expected
to be a launching year, not the actual year) to 2050 (expected to be a final target year). For this purpose,
HTS market penetration ratio of each stage, so called innovation, early adapters, early/late majority and
laggard stage, is analyzed using S-curve and thus calculated the total future market volumes of HTS
equipment. In conclusion, this paper shows the quantitative analysis for HTS cable, FCL, transformer and
rotational machine in the world market.
ETPL
GC-048
An Information-Theoretic Approach to PMU Placement in Electric Power Systems
Abstract: This paper presents an information-theoretic approach to address the phasor measurement unit
(PMU) placement problem in electric power systems. Different from the conventional `topological
observability' based approaches, this paper advocates a much more refined, information-theoretic criterion,
namely the mutual information (MI) between PMU measurements and power system states. The proposed
MI criterion not only includes observability as a special case, but also rigorously models the uncertainty
reduction on power system states from PMU measurements. Thus, it can generate highly informative PMU
configurations. The MI criterion can also facilitate robust PMU placement by explicitly modeling
probabilistic PMU outages. We propose a greedy PMU placement algorithm, and show that it achieves an
approximation ratio of (1-1/e) for any PMU placement budget. We further show that the performance is the
best that one can achieve, in the sense that it is NP-hard to achieve any approximation ratio beyond (1-1/e) .
Such performance guarantee makes the greedy algorithm very attractive in the practical scenario of multi-
stage installations for utilities with limited budgets. Finally, simulation results demonstrate near-optimal
performance of the proposed PMU placement algorithm.
ETPL
GC-049
Analysis of Frequency Dynamics in Power Grid: A Bayesian Structure Learning
Approach

Abstract: The oscillation of frequency in power grid is studied in this paper. The possibility association of
frequencies measured at different locations are modeled by a Bayesian network with the logical structure
learned using Bayesian structure learning and real measurements in the U.S. power grid. Frequency data
analysis and the detection of incorrect frequency measurements (caused by equipment error or malicious
attack) are performed over the logical Bayesian network structure. Such application of Bayesian network is a
powerful mathematical tool in computational intelligence. Without the physical power network topology
information, a two-branch search-and-score structure learning algorithm with L -1 regulation is proposed to
learn the logical structure, achieving around 97% correct prediction rate for future frequency and 92%
detection rate for false frequency data with 2% false alarm rate. The tool of epidemic propagation over this
logical network is also exploited to analyze the propagation of frequency changes. Using the Kolmogorov-
Smirnov test, such logical structure is demonstrated to be well approximated by the Small World network
model. And the propagation of frequency changes is demonstrated to be described by the Susceptible-
Infectious-Susceptible (SIS) model quite well. The Bayesian structure obtained from the real measurement is
statistically validated using a 5-fold training data and the Pearson system.
ETPL
GC-050
Harmonic state estimation through optimal monitoring systems
Abstract: The present paper describes a methodology based on Evolutionary Algorithms (EAs) that defines
the configuration required for a monitoring system, in order to monitor voltage and current state variables
from a power network. The methodology defines not only the sites where the meters should be installed, but
also how their transducers (PTs and CTs) should be connected. The monitoring system's observability is
verified through three different rules based on Kirchhoff's laws. A branch-and-bound algorithm and a
modified Genetic Algorithm (GA) are used to solve the optimization problem. The objective is to reduce the
cost of the whole monitoring system. It is also shown why intelligent searching methods are required for
solving the optimization problem. Three different networks were used to assess the methodology's
performance: IEEE 14-bus system, IEEE 30-bus system and a real power distribution feeder. The results
were compared with the ones obtained through other methodologies that have already been published
before.
ETPL
GC-051
Fuzzy Control of Distributed PV Inverters/Energy Storage Systems/Electric Vehicles
for Frequency Regulation in a Large Power System
Abstract: Control is proposed from the view point of the frequency fluctuation problem produced by the
large penetration of PV power and sudden load variation. The fuzzy based frequency control has three
inputs: average insolation, change of insolation and frequency deviation. Following these three inputs, a
frequency control system for the distributed PV inverters is proposed. For the case of different insolations in
the different areas of the power system, a coordinated control method of the distributed PV inverters, energy
storage systems (ESSs) and EVs is presented. The proposed method is simulated by considering dual power
and information flows between supply and demand sides in a large power system and is found satisfactory to
provide frequency control and to reduce tie-line power fluctuations.
ETPL
GC-052
Reinforcement Learning Based Real-Time Wide-Area Stabilizing Control Agents to
Enhance Power System Stability
Abstract: In this paper, the design of a network of real-time close-loop wide-area decentralized power
system stabilizers (WD-PSSs) is investigated. In this approach, real-time wide-area measurement data are

processed and utilized to design a set of stability agents based on a Reinforcement Learning (RL) method.
Recent technological breakthroughs in wide-area measurement system (WAMS) make the use of the
system-wide signals possible in designing power system controllers. The main design objectives of these
controllers are to stabilize the system after severe disturbances and mitigate the oscillations afterward. The
proposed stability agents are decentralized and autonomous. The proposed method extends the stability
boundary of the system and achieves the above goals without losing any generator or load area and without
any knowledge of the disturbances causing the response. This paper describes the developed framework and
addresses different challenges in designing such a network. A case study is provided to illustrate and verify
the performance and robustness of the proposed approach.
ETPL
GC-053
Intelligent Local Area Signals Based Damping of Power System Oscillations Using
Virtual Generators and Approximate Dynamic Programming
Abstract: his paper illustrates the development of an intelligent local area signals based controller for
damping low-frequency oscillations in power systems. The controller is trained offline to perform well
under a wide variety of power system operating points, allowing it to handle the complex, stochastic, and
time-varying nature of power systems. Neural network based system identification eliminates the need to
develop accurate models from first principles for control design, resulting in a methodology that is
completely data driven. The virtual generator concept is used to generate simplified representations of the
power system online using time-synchronized signals from phasor measurement units at generating stations
within an area of the system. These representations improve scalability by reducing the complexity of the
system “seen” by the controller and by allowing it to treat a group of several synchronous machines at
distant locations from each other as a single unit for damping control purposes. A reinforcement learning
mechanism for approximate dynamic programming allows the controller to approach optimality as it gains
experience through interactions with simulations of the system. Results obtained on the 68-bus New
England/New York benchmark system demonstrate the effectiveness of the method in damping low-
frequency inter-area oscillations without additional control effort.
ETPL
GC-054
Optimized Control of DFIG-Based Wind Generation Using Sensitivity Analysis and
Particle Swarm Optimization
Abstract: Optimal control of large-scale wind farm has become a critical issue for the development of
renewable energy systems and their integration into the power grid to provide reliable, secure, and efficient
electricity. Among many enabling technologies, the latest research results from both the power and energy
community and computational intelligence (CI) community have demonstrated that CI research could
provide key technical innovations into this challenging problem. In this paper, we propose a sensitivity
analysis approach based on both trajectory and frequency domain information integrated with evolutionary
algorithm to achieve the optimal control of doubly-fed induction generators (DFIG) based wind generation.
Instead of optimizing all the control parameters, our key idea is to use the sensitivity analysis to first identify
the critical parameters, the unified dominate control parameters (UDCP), to reduce the optimization
complexity. Based on such selected parameters, we then use particle swarm optimization (PSO) to find the
optimal values to achieve the control objective. Simulation analysis and comparative studies demonstrate the
effectiveness of our approach.
ETPL
GC-055
A Multi-Timescale Scheduling Approach for Stochastic Reliability in Smart Grids
With Wind Generation and Opportunistic Demand

Abstract: In this study, we focus on the stochastic reliability of smart grids with two classes of energy users-
traditional energy users and opportunistic energy users (e.g., smart appliances or electric vehicles), and
investigate the procurement of energy supply from both conventional generation (base-load and fast-start)
and wind generation via multi-timescale scheduling. Specifically, in day-ahead scheduling, with the
distributional information of wind generation and demand, we characterize the optimal procurement of the
energy supply from base-load generation and the day-ahead price; in real-time scheduling, with the
realizations of wind generation and the demand of traditional energy users, we optimize real-time price to
manage opportunistic demand so as to achieve system-wise reliability and efficiency. More specifically, we
consider two different models for opportunistic energy users: non-persistent and persistent, and characterize
the optimal scheduling and pricing decisions for both models by exploiting various computational and
optimization tools. Numerical results demonstrate that the proposed scheduling and pricing schemes can
effectively manage opportunistic demand and enhance system reliability, thus have the potential to improve
the penetration of wind generation.
ETPL
GC-056
Hybrid Approach for Power System Operational Planning With Smart Grid and
Small-Signal Stability Enhancement Considerations
Abstract: Operational planning of power systems, especially in terms of overall reliability and security, is a
key issue in the smart grid development. Hence, it is necessary to develop new strategies to cope with
increasing uncertainties arising from the fast changing ways power systems are being operated. This paper
presents a comprehensive approach to determine an optimal transmission network expansion plan
considering the enhancement of small-signal stability through wide-scale deployment of the existing and
planned transmission system assets. The dynamic model of the transmission network operational planning
(TNOP) is solved based on a combination of the Mean-Variance Mapping Optimization (MVMO), and the
classic dynamic programming method embedded with a heuristic procedure. Besides, a probabilistic
eigenanalysis-based recursive method is proposed to determine the optimal control strategies that are highly
relevant to the enhancement of the system small-signal stability performance throughout the planning
horizon. Numerical results demonstrate the viewpoint and the effectiveness of the proposed approach in
providing optimal strategies of minimum cost while avoiding the instability risk associated to poorly
damped low-frequency electromechanical oscillations.
ETPL
GC-057
Contingency-Based Nodal Market Operation Using Intelligent Economic Alarm
Processor
Abstract: This paper focuses on system monitoring and alarm processing and the use of those alarms for
economic decision in the nodal electricity market. The task of an Intelligent Economic Alarm Processor
(IEAP) is to analyze thousands of alarm messages and extract useful information that explains cause-effect
sequences associated with the unexpected contingencies. A graphical Fuzzy Reasoning Petri-nets (FRPN)
model that uses fuzzy logic parameters to effectively tackle the uncertainties is built. The economic alarm
processor module then processes the fault event signal, analyzes the impact on the market operation
activities and different participants, and gives recommendations to optimize the total economic impact under
fault scenarios. A contingency-based strategic bidding model concept is proposed to help the market
participants take advantages of the latest system operation information and maximize their benefits over the
competitors.

ETPL
GC-058
Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector
Regression
Abstract: In this paper we focus our attention on the long-term load forecasting problem, that is the
prediction of energy consumption for several months ahead (up to one or more years), useful in order to ease
the proper scheduling of operative conditions (such as the planning of fuel supply). While several effective
techniques are available in the short-term framework, no reliable methods have been proposed for long-term
predictions. For this purpose, we describe in this work a new procedure, which exploits the Empirical Mode
Decomposition method to disaggregate a time series into two sets of components, respectively describing
the trend and the local oscillations of the energy consumption values. These sets are then used for training
Support Vector Regression models. The experimental results, obtained both on a public-domain and on an
office building dataset, allow to validate the effectiveness of the proposed method.
ETPL
GC-059
A Noninvasive Threat Analyzer for Advanced Metering Infrastructure in Smart Grid
Abstract: Advanced Metering Infrastructure (AMI) is the core component in a smart grid that exhibits a
highly complex network configuration. AMI comprises heterogeneous cyber-physical components, which
are interconnected through different communication media, protocols, and security measures. They are
operated using different data delivery modes and security policies. The inherent complexity and
heterogeneity in AMI significantly increases the potential of security threats due to misconfiguration or
absence of defense, which may cause devastating damage to AMI. Therefore, there is a need for creating a
formal model that can represent the global behavior of AMI configuration in order to verify the potential
threats. In this paper, we present SmartAnalyzer, a security analysis tool, which offers manifold
contributions: (i) formal modeling of AMI configuration that includes device configurations, topology,
communication properties, interactions among the devices, data flows, and security properties; (ii) formal
modeling of AMI invariants and user-driven constraints based on the interdependencies among AMI device
configurations, security properties, and security control guidelines; (iii) verifying the AMI configuration's
compliance with security constraints using a Satisfiability Modulo Theory (SMT) solver; (iv) reporting of
potential security threats based on constraint violations, (v) analyzing the impact of potential threats on the
system; and (vi) systematic diagnosing of SMT unsatisfiable traces and providing necessary remediation
plans. The accuracy and scalability of the tool are evaluated on an AMI testbed and various synthetic test
networks.
ETPL GC-
060
A Game Theory Strategy to Integrate Distributed Agent-Based Functions in Smart
Grids
Abstract: The increasing incorporation of renewable energy sources and the emergence of new forms and
patterns of electricity consumption are contributing to the upsurge in the complexity of power grids. A
bottom-up-agent-based approach is able to handle the new environment, such that the system reliability can
be maintained and costs reduced. However, this approach leads to possible conflicting interests between
maintaining secure grid operation and the market requirements. This paper proposes a strategy to solve the
conflicting interests in order to achieve overall optimal performance in the electricity supply system. The
method is based on a cooperative game theory to optimally allocate resources from all (local) actors, i.e.,

network operators, active producers, and consumers. Via this approach, agent-based functions, for
facilitating both network services and energy markets, can be integrated and coordinated. Simulations are
performed to verify the proposed concept on a medium voltage 30-bus test network. Results show the
effectiveness of the approach in optimally harmonizing functions of power routing and matching.
ETPL
GC-061
A SAX-Based Advanced Computational Tool for Assessment of Clustered Rooftop
Solar PV Impacts on LV and MV Networks in Smart Grid
Future distribution networks with increasing level of solar PV penetration will be managed using smart grid
technologies capable of producing appropriate and timely response during normal and abnormal operational
events. Distribution feeder loads vary throughout the day according to the trend of consumption of the
customers. Solar PV outputs fluctuate in proportion to irradiance level of sun. Simultaneous occurrence of
both of these variations would result in various operating conditions that may lead to unexpected events, and
would require a large amount of network data to be processed and analyzed for decision making. It is
envisaged that such data will be available in the future grids with the availability of smart technologies and
advanced communication in residential dwellings, commercial buildings and industrial complexes. In this
paper, an advanced intelligent computational tool is developed to characterize and analyze the large amount
of data associated with wide variations in network behavior using SAX (Symbolic Aggregate
Approximation) and pattern recognition. The proposed tool is capable of dealing with network asymmetry,
load unbalance, single-phase solar PV integration and their impacts on upstream networks and will assist in
making right and timely decision to mitigate adverse impacts of solar PV. The proposed tool has been tested
with a practical three-phase distribution system in Australia and can provide an extensive assessment with
less computational efforts and time.
ETPL
GC-062
On Improving Distortion Power Quality Index in Distributed Power Grids
Abstract: This paper presents the Euclidean norm based new power quality index (PQI), which is directly
related to the distortion power generated from nonlinear loads, to apply for a practical distribution power
network by improving the performance of the previous PQI proposed by the authors. The proposed PQI is
formed as a combination of two factors, which are the electrical load composition rate (LCR) and the
Euclidean norm of total harmonic distortions (THDs) in measured voltage and current waveforms. The
reduced multivariate polynomial (RMP) model with the one-shot training property is applied to estimate the
LCR. Based on the proposed PQI, the harmonic pollution ranking, which indicates how much negative
effect each nonlinear load has on the point of common coupling (PCC) with respect to distortion power, is
determined. Its effectiveness and validity are verified by the experimental results from its prototype's
implementation in a laboratory with a single-phase 3 kW photovoltaic (PV) grid-connected inverter, which
contributes to a small distortion in voltage at the PCC, and practical nonlinear loads. Then, the harmonic
current injection model based time-domain simulations are carried out to prove the effectiveness of the
proposed PQI under the other conditions with different nonlinear loads.
ETPL
GC-063
Smart Grid Communication: Its Challenges and Opportunities
The necessity to promote smart grid (SG) has been recognized with a strong consensus. The SG integrates
electrical grids and communication infrastructures and forms an intelligent electricity network working with
all connected components to deliver sustainable electricity supplies. Many advanced communication

technologies have been identified for SG applications with a potential to significantly enhance the overall
efficiency of power grids. In this paper, the challenges and applications of communication technologies in
SG are discussed. In particular, we identify three major challenges to implement SG communication
systems, including standards interoperability, cognitive access to unlicensed radio spectra, and cyber
security. The issues to implement SG communications on an evolutional path and its future trends are also
addressed. The aim of this paper is to offer a comprehensive review of state-of-the-art researches on SG
communications.
ETPL
GC-064
Day-Ahead Resource Scheduling Including Demand Response for Electric Vehicles
Abstract: The energy resource scheduling is becoming increasingly important, as the use of distributed
resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a
methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of
distributed generation and V2G. The main focus is the comparison of different EV management approaches
in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and
Demand Response (DR) programs in the V2G approach. Three different DR programs are designed and
tested (trip reduce, shifting reduce and reduce+shifting). Other important contribution of the paper is the
comparison between deterministic and computational intelligence techniques to reduce the execution time.
The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear
programming is also used for comparison purposes. Full ac power flow calculation is included to allow
taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G
resources is used to illustrate the performance of the proposed method.
ETPL
GC-065
Modified Particle Swarm Optimization Applied to Integrated Demand Response and
DG Resources Scheduling
Abstract: The elastic behavior of the demand consumption jointly used with other available resources such
as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of
Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non
linear optimization problems that require computational intelligence methods to be solved. This paper
proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the
operation costs of a virtual power player that manages the resources in a distribution network and the
network itself. Resources include the DER available in the considered time period and the energy that can be
bought from external energy suppliers. Network constraints are considered. The proposed approach uses
Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and
minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310
consumers and 548 distributed generators. The obtained solutions are compared with a deterministic
approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.
ETPL
GC-066
Comprehensive Real-Time Microgrid Power Management and Control With
Distributed Agents
Abstract: Advances in smart grid technology have yet to coalesce into a comprehensive solution integrating
the landscape of future power systems. The microgrid concept may offer a solution for combining advanced
components and enabling technologies within an infrastructure that must expand to meet emerging demands.
As autonomous power system entities, microgrids require robust real-time power management and control to

simultaneously operate jointly with the utility, provide reliable service, and help achieve customer-driven
objectives utilizing local power system assets. In this paper, a decentralized control architecture for
microgrids is presented, along with a simulation environment appropriate for on-going investigations into
real-time, agent-based decision-making. Challenges faced by operating self-organizing multi-agent system
(MAS) are presented, as well as results for a representative power management scenario for a multi-asset
microgrid capable of operating in grid-interconnected or islanded mode. The system and formulations
presented demonstrate the viability and capability of decentralized agent-based control for microgrids and
illustrate their potential towards achieving smart grid goals.
ETPL
GC-067
Biogeography Based Optimal State Feedback Controller for Frequency Regulation of a
Smart Microgrid
Abstract: Development of “Q” and “R” matrices for designing a Linear Quadratic Regulator (LQR) is still a
research challenge. The theory says they should belong to the group of positive definite matrices, so we need
to find out the most suitable amongst them in order to obtain the desired response. In this paper
biogeography based optimization (BBO) technique has been applied to come up with the best “Q” and “R”
matrices such that the frequency excursion following a disturbance in a microgrid is minimized. As all the
states in a practical system may not be measurable hence, we have used Kalman estimator to estimate them.
These estimated states along with other measured states are used by the LQR to produce the desired control
signal. The microgrid is made smarter by using the agent based scheme integrated with a master controller
and a proper communication protocol. The simulation results show that the proposed approach improves the
microgrid frequency response and also gives a new alternative method for frequency control of a smart
microgrid.
ETPL
GC-068
Economic Analysis and Power Management of a Small Autonomous Hybrid Power
System (SAHPS) Using Biogeography Based Optimization (BBO) Algorithm
Abstract: In this study, Biogeography Based Optimization (BBO) algorithm is developed for the prediction
of the optimal sizing coefficient of Small Autonomous Hybrid Power System (SAHPS) in remote areas.
BBO algorithm is used to evaluate optimal component sizing and operational strategy by minimizing the
total cost of SAHPS, while guaranteeing the availability of energy. Due to the complexity of the SAHPS
design with nonlinear integral planning, BBO algorithm is used to solve the problem. The developed BBO
Algorithm has been applied to design the wind/PV/hydro hybrid energy systems to supply a colony located
in the area of Jaipur, Rajasthan (India) during the period of January, 2010 to January 2011. It is clear from
the results that the proposed BBO method has excellent convergence property, requires less computational
time and can avoid the shortcoming of premature convergence of other optimization techniques to obtain a
better solution
ETPL
GC-069
Advanced Metering for Phase Identification, Transformer Identification, and
Secondary Modeling
Abstract: Advanced metering infrastructure (AMI) offers utilities new ways to model and analyze
distribution circuits. Results from two circuits introduce a new method to identify phasing of transformers
and single-phase taps using voltage and kilowatt-hour measurements from AMI. In addition to phase
identification, we show how to use the same approach to create or check meter-to-transformer mappings.
These algorithms are based on linear regression and basic voltage drop relationships. With this approach,
secondary connectivity and impedance models can be auto generated. In addition, detection of unmetered

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