Harnessing the value of distributed energy resources through analytics

1. Talking an energy
revolution: Analytics in
action for DER
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2. DER:
Dispatchable and
non-dispatchable resources on
the grid, including demand
response, distributed generation
(solar, CHP, wind), electric vehicles,
and storage technology. Energy
efficiency and micro grids can
also be considered to beDERs
Harnessing the value of
distributed energy resources
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Core distributed
energy resource
management

3. Integrating diverse energy systems into the main grid challenges operations
and existing solutions
Grid stability and reliability is under pressure
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Offshore wind parks
Bidirectional power flow
Unidirectional power flow
Hydrogen storage Biogas CHP
Small industrial gas
turbine
Pumped storage
power plant
Private solar
Smart street
Lighting
Electrical
vehicles
Diesel generator
Storage solutions
Large scale PV plant
Storage
solutions

4. DER analytics
DER Grid management analytics – analytics to
support the management of a grid with high
projected penetration of DERs
What challenges can analytics
address?
ManageDERasagenerationandmarketresource
Optimize dispatch of DER for reliability and
financial benefits
Maximize the leverage of existing assets Operate
a secure, resilient grid
Operate a resilient grid
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DER management analytics – analytics to assist
with planning, management and
operations of DERs on the grid
What data management
initiatives and tools can help?
Data integration: Multidimensional data enrichment
(assets,operations,weather,GIS,SCADA,customer,urban
developmentplans,demographics etc.)
Dataprocessing:in alarge-scale Hadoopenvironment
Analytics application framework: Technology agnostic
analytics application framework to enable evolving use
cases
Analytics integration framework: Standards-based
integrations to enable existing operational systems

5. DER analytics case study
Renewablesmetaforecasting
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Business situation and
objectives
Awindpowerplantoperator needed to:
Reducepenaltycostsbyreducing
forecastingerrors
Optimizetradingstrategybasedon
forecastconfidence
Alignmaintenanceschedulewith
productionforecast
Atransmissionsystemoperator(TSO)and
distribution system operator(DSO) needed to:
Preventcriticalsituationsin thegrid
Keepthenetworkbalanced
Manage congestion
Carry out reservemonitoring
How we helped
We undertook:
Time series analysis
Sequenceandpatternmining
Classification-based transferfunction
Betterdecisionmaking is enabled through
the combination of data frommultiple
forecastingengines to provide confidence
intervals
Forecasts are improved bysupplementing
production data with additional data for
example fromturbinesandweatherstations

6. DER analytics case study
Analysis of turbine performance and icing sensors
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Business situation and objectives
AEuropean utility wanted to limit the impact of blade
icingontheperformanceofitswindpark
How we helped
We conducted an initial field study on ice
detection
For better information on icing, two types of
sensors were installed on one windmill for
testing
In the future the better performing of these
sensors will be rolled out
We analyzed the data using scatter plotting,
box plotting and true/false, positive/negative
dynamic threshold categorization
The gained insight facilitates the evaluation
of the blade heating installation business
case and will help to improve preventative
shut down of turbines in case of icing

7. DER analytics case study
Extended low voltage analytics
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Business situation and objectives
For a European smart city joint venture project,
a European energy retailer and a European
DSO, we helped uncover newinsightsintolow
voltage networkstates and voltage/current
asymmetries
How we helped
We analyzed the voltage and current asymmetries,
as well as the power factor, of
41 grid monitoringdevices in varioussmart
citytestbeds
We compared twodatasetsbeforeandafter
adjustments ofgrid monitoringdevices
We conducted a collaborativefilteralgorithmfor
comparativeanalysis and networkgraphsfor
visualization
We provided a descriptive analysis using
histograms and bar charts

8. OMNETRIC
For more information contact: request@omnetric.com
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