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Energy Industry Trends by Jonathan Tan, GZZ Cleantech Consulting

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Smart Grid, Big Data Management and Analytics Trends for the Energy Sector

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Energy Industry Trends by Jonathan Tan, GZZ Cleantech Consulting

  1. 1. Energy Industry Trends: Smart Grid, Big Data Management, and Analytics By Jonathan L. Tan August 15, 2016
  2. 2. U.S. Energy Industry • The energy industry is the totality of all of the industries involved in the production and sale of energy, including fuel extraction, manufacturing, refining and distribution. • The energy industry is the third largest industry in the United States. • U.S. energy companies produce oil, natural gas, coal, nuclear power, renewable energy and fuels, as well as electricity, smart grid, and demand response technologies. • Growing consumer demand and world class innovation – combined with a competitive workforce and supply chain capable of building, installing, and servicing all energy technologies – make the United States the world’s most attractive market in the $6 trillion global energy market.
  3. 3. U.S. Energy Industry Energy Industry Subsectors (Source: Select USA) • Renewable Energy - Bloomberg New Energy Finance (BNEF) expects that by 2030 the share of renewables in U.S. power generation mix to reach 27 percent. BNEF projects that just under $700 billion will be invested in the U.S. renewable energy sector during the next two decades. • Renewable Fuels - US’s Ethanol market is largest in world • Oil & Gas -The United States is undergoing a revolution in oil and natural gas production from shale. • Coal The United States holds the world’s largest estimated recoverable reserves of coal and is a net exporter of coal. Approximately 72 percent of coal production originated in five states: Wyoming, West Virginia, Kentucky, Pennsylvania, and Texas. • Nuclear Energy - The United States operates the most nuclear reactors, has the largest installed nuclear power capacity, and generates the most nuclear power in the world. Nearly 20 percent of U.S. electricity is produced at 100 nuclear reactors in 31 states. • Energy Efficiency - The market for achieving greater energy efficiency in the United States is large and growing. Combined financing and investment in building, industrial, and supply side energy efficiency doubled in 2012, exceeding $15 billion in funds due to an Executive Order from the Obama Administration in 2012 • Smart Grid -The United States is an international leader in the development and deployment of smart grid technologies and services. The smart grid subsector is defined by the electric grid equipment and services required for the modernization of distribution and transmission systems, as well as the Information and Communication Technologies (ICT) that support a fully networked grid and enable two-way communications and electric flows. Overall grid modernization investments are projected to achieve $130 billion in annual benefits for the U.S. economy by 2019, and the smart grid deployment by utilities in the United States is expected to create $15 billion to $31 billion annually by 2014 in potential sales for the ICT industry.
  4. 4. Energy Trends 1. The transition towards more renewable energy and diversified supplies is creating opportunities and challenges for the security of the global energy infrastructure. • As renewables are now part of the energy portfolio and are rapidly gaining market share, they bring along benefits such as energy mix diversification, with distributed generation growing at a fast pace worldwide and its installed capacity expected to more than double in the next decade. • At the same time, as the energy generation portfolio transitions and diversifies further, new challenges are emerging, which require changes to the electric utility business model and regulatory policies to ensure secure and reliable supply.
  5. 5. 2. Digital disruption is creating new opportunities – but also threats. • On the one hand, technology is instrumental for realizing intelligent grids and interconnected assets; • On the other hand, it introduces new threats such as the possibility of cyber attacks. • The increasing interconnectivity and proximity of energy systems means that conflicts can have ripple effects on energy markets and prices. • New technologies, such as batteries and grid-embedded generation, are making the cybersecurity of grid systems more vulnerable. • Global inexperience in handling large-scale cyberattacks, combined with the greater capabilities of state and non-state actors, has increased the likelihood that future wars and attacks will have a larger cyber component. Energy Trends
  6. 6. 3. The rebalancing of energy supply and demand is leading to a new global energy security order. • Recent drops in oil prices have led to a significant shift in wealth from net oil exporters to oil importers. • At the same time, the development of unconventional sources of oil and gas, as well as the recent economic slowdown in emerging markets such as China and India, have contributed to price readjustments against the backdrop of a general shift in energy supply patterns. • Geopolitical shifts, the new distribution of powers and energy trade flows will create challenges and opportunities for energy security in the new energy architecture. Energy Trends
  7. 7. WHAT IS U.S. ELECTRICITY GENERATION BY ENERGY SOURCE? • In 2015, the United States generated about 4 trillion kilowatt hours of electricity. About 67% of the electricity generated was from fossil fuels (coal, natural gas, and petroleum). • Major energy sources and percent share of total U.S. electricity generation in 2015: – Coal = 33% – Natural Gas = 33% – Nuclear = 20% – Hydropower = 6% – Other renewables = 7% – Biomass = 1.6% – Geothermal = 0.4% – Solar = 0.6% – Wind = 4.7% – Petroleum = 1% – Other gases = <1% 2016 will be the first year that Coal will overtaken by Natural Gas
  9. 9. Total US energy production increases for the sixth year in a row Source: U.S. Energy Information Administration
  10. 10. • Smart City Market - will grow to $3.3 Trillion by 2025 –with $100 billion investment projected for Infrastructure technologies in the next ten years with annual spend projected to $16 billion per year by 2020 • Internet of Things – 7 billion mobile devices in 2014, 25 billion connected devices by 2015 and 50 Billion by 2020. • IoT solutions will grow from $1.9 trillion in 2013 to $7.1 trillion in 2020 • Investment by in Analytics is accelerating: For instance, IBM has spent $6 billion in analytics R&D and $14 billion in analytics acquisitions and now has 8000 consultants dedicated to analytics and 200 mathematicians developing algorithms RELATED MARKET TRENDS
  11. 11. • The global Energy Analytics and Utility Analytics market is estimated to grow from $1.42 billion in 2013 to $4.74 billion in 2018. This represents a Compound Annual Growth Rate (CAGR) of 27.3% from 2013 to 2018. • In terms of regions, North America is expected to be the biggest market. Utility Companies that use analytics get $10.66 for every $1 they spend on Analytics. Source: Oracle RELATED MARKET TRENDS
  12. 12. • At nearly $1.3 trillion in estimated global revenue for 2014, the market for advanced energy products and services is as large as apparel and fashion and almost four times the size of the semiconductor industry worldwide, according to a report commissioned by Advanced Energy Economy (AEE). • In the United States, advanced energy market revenue grew 14% last year – five times the rate of the U.S. economy overall – to just under $200 billion, making it bigger than the airline industry, equal to pharmaceuticals, and nearly equal to consumer electronics in this country. • The study, conducted by Navigant Research, found that advanced energy in the United States was an estimated $199.5 billion market in 2014, up 14% from 2013 ($169 billion), and five times the rate of growth of the U.S. economy overall. • Areas of growth included: • Solar energy (up 39%) and • Natural gas generating equipment (48%), in long-anticipated response to lower-priced natural gas supplies. • Wind power, which suffered a severe setback in 2013 due to the on- again, off-again federal production tax credit (PTC), rebounded in 2014 with four-fold growth, to $8.2 billion, and a pipeline of projects that could result in revenue rivaling the $25 billion realized in 2012, its biggest year to date. ADVANCED ENERGY MARKET FACTS (Navigant)
  13. 13. • With global revenue up 12% over 2013, 2014 was the biggest growth year for advanced energy worldwide since AEE began tracking these markets in 2011. • U.S. advanced energy revenue has grown 38% over the four years from 2011 to 2014. U.S. advanced energy represents 15% of the world market. • With the addition of new revenue data on residential energy efficient lighting, Building Efficiency is now the largest segment of the U.S. advanced energy market, with revenue of $60.1 billion in 2014. • Counting only those products for which AEE has four years of data, revenue growth in Building Efficiency is 43% over four years. • In 2013, the severe downturn in wind energy due to uncertainty over the federal production tax credit (PTC), with revenue dropping to $2.1 billion from $25.5 billion in 2012, was enough to offset growth in other segments of U.S. advanced energy to show an overall decline of 4% year over year. But wind bounced back in 2014, to $8.2 billion, nearly four times 2013 revenue. ADVANCED ENERGY MARKET FACTS (Navigant)
  14. 14. • Including wind, the Electricity Generation segment of advanced energy grew 47% overall in the U.S., to $45.8 billion in 2014. • Solar photovoltaic (PV) revenue was up 39%, to $22.5 billion, capping four-year growth of 173%. • Natural gas generating equipment (combined cycle and simple cycle gas turbines) saw an increase for the first time in four years, with U.S. revenue up 48% to $6.4 billion – a sign that the natural gas revolution is now translating into new orders, not just higher utilization of existing natural gas power plants. • The U.S. Fuel Production segment reached $49 billion in 2014, up from a revised 2013 total of $48.4 billion, with $39.1 billion of that total from sales of ethanol. • In Transportation, U.S. revenue for hybrid vehicles was down 19% but up 34% for plug-in electric vehicles, while natural gas-powered vehicles jumped 26% in revenue. • Revenue from electric vehicle charging stations was up 31% in the U.S., to $201.5 million, up seven-fold from 2011. ADVANCED ENERGY MARKET FACTS (Navigant)
  15. 15. UTILITY 2.0 Utility 2.0 Problems Greatest earnings pressure in recent memory  Recession has led to unprecedented decline in load and revenues (sales volume)  Margins down in deregulated markets due to supply/demand imbalance Operational challenges  Antiquated systems and tools  Aging infrastructure  Rising costs  Aging work force  Data Deluge from AMI – 2.0 Lack of clarity in regulatory and legislative direction  Increasingly hostile rate environment—necessary upward adjustments on hold  Large variance in state regulatory direction  Regulatory developments that reward energy efficiency and GHG reduction yet to materialize  Federal energy policy mired in politics Viability of status quo approach to business in question  “Load destruction” threatens 100 yr old cents/kwh revenue model  Returns to current and future investments in low carbon generation unclear  Pressure to move forward with Smart Grid and energy efficiency remains high, but incentives/returns are contingent on new rate model (decoupling) Utility 2.0 Roadmap Grow the traditional business  Stay on message: reliable and affordable  Continue to invest in renewables, clean coal, nuclear as an “act of faith” Reduce costs  Process design  Sourcing models  Capital and O&M prioritization and “re-casing”  Data Analytics & Technology enablement Redefine boundaries  Legislative solutions—e.g., decoupling, save-a-watt, etc.  Smart Grid-enabled products and services—energy management, distributed gen, PHEV, AMI 2.0 Pursue acquisitions  In core business—regulated and unregulated generation, T&D  Along value chain—upstream, downstream  In crucial IP—low-carbon, renewables, energy technology Evolve customer relationships  Increased control of usage, load and spend  Redefined view of role relative to utility  Better understanding of segment-specific needs  Better Power Control, Load Management, Reliability, Cost, Clean
  16. 16. ELECTRIC UTILITY 2.0 or UTILITY OF THE FUTURE • Manage Carbon across the enterprise • Pursue all cost-effective energy efficiency • Integrate Cost Effective Renewable Energy Resources into the Power Generation Mix • Incorporate Smart Grid Technologies for Consumer and Environmental benefit • Conduct Robust and Transparent Resource Planning Performance parameters are: • Cost • Reliability • Customer service • Adoption of smart grid technologies and services and support for alternate energy The utility of the future leverages core competencies and builds adjacent core competencies, and develops these new models to scale, as the organization learns to become customer focused, providing efficient, reliable and resilient clean energy. This is achieved by data systems that allow for optimal life-cycle asset management and operating intelligence. Distributed generation resources integrated in the generation mix, allow for automated load management through connected data with customers (demand) and power generation (supply) to be fully aligned in real-time.
  17. 17. U.S. IOU CAPEX 2000 – 2010: T $69B D $160B THE CLASSIC ELECTRIC GRID 18 1. Generation Sources 2. Transmission Lines 3. Substations (Ex: PG&E has 900) 4. Distribution Feeders (1,500+) 5. Power Poles (millions) 6. Fuses (50,000) 7. Tap Lines 8. Transformers (1,000,000) 9. Service Lines (4,500,000)
  18. 18. DISTRIBUTION SYSTEMS NEED TO GET SMART 19 • Large – 50% to 100% of a utility’s assets • Old – Typically 40 to 60 years • Invisible – Little monitoring below the substation • Unreliable – Costs $3M per outage; regulators penalizing − System Average Interruption Duration Index (SAIDI) 2 hrs/year − Worst U.S. utilities have SAIDI of 6 to 7 hours − Best are 1 hour or less − Japan averages 3 minutes . . . Tokyo was 29 seconds!!! . . . • Stressed – the “Edge” − Demand Response − Solar PV & other variable and distributed generation − Storage − Plug-in Vehicles
  19. 19. Smart Grid Essentials 1. All power generation, distributed energy assets (smart grid), including DER assets, data systems, are integrated and connected ( via ICT) 2. System of system (SoS) interoperability model -nexus of energy with water/waste, transportation, industry, education, health, government, and the public (citizens, visitors, vendors, etc.) Fully integrated data systems (meter, IoT, weather, OEM, remote sensing, legacy, billing, CIM, GIS, SCADA, etc.) 3. Leveraging IoT –sensors, oem, meters, smart phones/mobile devices, etc. 4. Leveraging analytics – fully deployed (descriptive, predictive & prescriptive) through IoT, legacy systems, real-time data, etc. 5. Big data management standards met 6. Sustainability and removal of carbon fuels from power generation 7. Intelligent real-time applications leveraging customer usage and DR 8. Distributed grid optimization (DGO) integration of renewables, micro- grids, smart buildings, water/waste water systems, etc. 9. Adaptive planning applications and adaptive management systems 10. Distributed grid optimization (DGO) including renewables (carbon zero)
  20. 20. SMART GRID
  22. 22. SMART GRID CAPEX INVESTMENT TRENDS World Energy Investment Outlook 2014 Factsheet Overview Https://Www.Iea.Org/Media/140603_weoinvestment_factsheets.Pdf
  23. 23. Smart Grid Technology Investment: Forecasts for 2012-2030 • Smart meters • Communications systems • Distribution automation • Substation automation • IT systems – Infrastructure management systems (including distribution management, outage management, MDMS, demand response) – Billing and customer care (and web sites) – Storage, servers, hardware, etc. – Other IT (including workforce management, SOA) • Home area networking (HAN) • Consulting and systems integration • Other (including project management and customer communications)
  24. 24. SMART GRID INVESTMENT MIX SA = Substation Automation DA = Distribution Automation HANs = Home area networks SI = Systems Integration . Through 2030, the top spending countries will be: China (US$99 billion by 2030), United States (US$60 billion by 2030), India, France, Germany, Brazil, Spain, United Kingdom, Japan and Korea.
  25. 25. UTILITY DATA MANAGEMENT: MARKET OVERVIEW Why are utilities turning to Big Data solutions? • Before smart grids, the data that a utility would collect from its customers frequently amounted to little more than a monthly meter reading: one data point a month per customer. • The advent of AMI has increased the level of data collection dramatically. The Columbia Water and Light Department, for example, has a pilot where meters provide data on around half a dozen household circuits every minute. That is more than 43,000 data points per customer per month. • Even if, as is often the case, readings are taken at more infrequent intervals, say every five, 10 or 15 minutes, the increase is very significant. And this is just one element of what is currently termed ‘Big Data’, data sets that are terabytes to exabytes in size and come from a range of sources, which puts their management and analysis beyond the scope of traditional IT tools
  26. 26. MARKET DRIVERS (BIG DATA AND ANALYTICS) • The key driver for the adoption of data management strategies is clearly the need to handle and analyze the large amounts of information utilities are now faced with. • Utilities are entering a new era of customer expectation and technological innovation, and analytics is a core requirement for the truly modern digital utility. Those with pervasive analytic adoption will be able to internally comprehend and act upon inefficiencies and operational pain points to not only maximize existing assets but provide the best service possible to their customers. • For retailers in unregulated markets, analytics can be the differentiating factor for top-line growth through enhanced service and higher margins. And for both regulated and unregulated markets, analytics also enables a level of transparency that will enable each utility to respond to changes and issues faster and delivery services with fewer incidents
  27. 27. OTHER PROCESSES THAT UTILITIES HOPE TO ENHANCE THROUGH BETTER ANALYSIS OF DATA INCLUDE: -Business operation efficiency. Data analytics will allow utilities to see where consumers may be stealing electricity and will allow for better asset management as well as better system planning. -Implementing efficiency measures. Data allows for time-of-use rates which in turn allow customers to monitor their consumption and save money by shifting use away from times when rates are higher, while also reducing the need for more expensive forms of peak generation to be built. -Developing new business models. By adding intelligence to the grid operators can offer new services, such as energy management, engineering, high-speed Internet services, cable TV and private network links. -Improving grid resilience and load management. Distribution companies must reduce power demand to prevent outages, for example installing energy load management systems to help retailers and customers manage their energy use. Better data will also allow utilities to identify and rectify problems with the grid more quickly, in some cases even before the customer has a chance to report the issue or outage. -Engaging customers. Having more information about customers and their usage patterns is generally considered important in helping deliver a better, more
  28. 28. Big Data Infrastructure Essentials Typical Big Data Management Infrastructure Architecture
  29. 29. BIG DATA INFRASTRUCTURE ESSENTIALS DATA SYSTEM INTEGRATION Point to Point systems architecture System of Systems via Hub and Spoke architecture
  30. 30. BIG DATA INFRASTRUCTURE ESSENTIALS CLOUD COMPUTING Data Management in the cloud is essential for scalability, security, technology investment CAPEX mitigation, economic adaptability, and ease of use
  33. 33. Data type Technology involved Notes AMI Smart meters Increased sampling frequency leads to 1,000 to 10,000- fold increase in data levels Distribution Grid equipment Real-time monitoring and control requires Automation many more granular readings than those taken by smart meters. The GridSim simulation package described by Anderson et al (2011), for example, uses a default sample rate of 30 samples per second, per sensor. Third-party Off-grid data sets Utilities are increasingly also having to integrate and handle highly granular data from other sources, such as pricing details for demand response or forecasting information for renewable energy Asset Mgmt Firmware for all Maintaining smart grid technology once it smart devices and has been rolled out requires frequent associated operating firmware upgrades and the like, which systems equates to a considerable amount of asset management data Sources of Big Data in Utilities
  34. 34. BROADLY SPEAKING THERE ARE FIVE OPTIONS FOR DEALING WITH UTILITY DATA ANALYTICS: 1. Develop the systems in house. 2. Buy systems from an established operational technology (OT) vendor. 3. Buy systems from an established Information Technology (IT) vendor. 4. Buy and integrate point products from specialist vendors. 5. Outsource data analytics to a third party.
  35. 35. Data analytics option Benefits Disadvantages Develop systems in house Highly tailored to the Lack of development skills utility’s requirements and resources Rely on OT vendor system Close alignment with Analytics and IT integration operational processes capabilities might not be and requirements; good as good as for IT vendors integration with OT Rely on IT vendor system Good integration with IT May include unnecessary systems; robust design and support features that support increase cost: lack of alignment with operational processes Rely on point product or pure-play vendor system Close alignment with Potential lack of operational processes cross-product and IT system and good integration integration; lifetime support with OT concerns Rely on third-party service provider system Reduced cost, improved Evolving concept with analytics limited track record; data sharing may require culture shift PROS AND CONS OF DIFFERENT DATA ANALYTICS OPTIONS FOR UTILITIES
  36. 36. IDEAL UTILITY ANALYTICS VENDOR • Data Analytics expertise • OT/IT experience • Deep subject matter expertise (SME)
  37. 37. LEADING UTILITY ANALYTICS VENDORS ARE FOUND IN THESE CATEGORIES 1. Analytics and Applications (Real-Time Intelligence) 2. Data Management + Movement – Platforms 3. Data Infrastructure + Storage – Private/Public Clouds
  38. 38. • As in most nascent technology sectors, the smart grid data analytics market can be characterized as a rather fragmented marketplace with a mix of large, established players and smaller, specialized firms that come from many different industries. While the majority of the vendors, both large and small, come from the information technology (IT) sector, others may come from the telecom or even the automobile sector. • Among the large group of IT players, there are the big, established companies like Accenture, Capgemini, HP, IBM, Microsoft, Oracle, SAIC, SAP, Siemens, and Teradata. Another large technology group is represented by the Indian service companies such as Infosys and the “pure plays” – mostly with meter data management (MDM) expertise – like Aclara Software, Ecologic Analytics, eMeter, Itron, Olameter, and NorthStar Utilities. Telvent is a relatively large IT provider that offers a portfolio of MDM software, as well as distribution management system (DMS) and outage management system (OMS) solutions with data analytics capability. Competitive Landscape (from Navigant Research)
  39. 39. • Interestingly, there is no pure niche smart grid data analytics vendor in the marketplace. However, there is a small group of software companies that have developed a special niche area that they have found can be leveraged in the smart grid data analytics market. OPOWER and OSIsoft represent this market segment. • Although telecom companies play a fairly large role in the smart grid market, they do not appear to be prominent players with respect to smart grid data analytics – at least at this time. However, it would not surprise Pike Research if they soon make inroads into this particular sub-segment of the smart grid market since they can leverage a long history of managing and analyzing reams of data. AT&T is a good example of such a vendor. Competitive Landscape (from Navigant Research)
  40. 40. • The auto companies, offering plug-in hybrid and electric vehicles, could also become serious competitors in the smart grid data analytics marketplace. For example, Toyota launched a home energy system in 2012 to help individuals monitor and manage (even remotely) their energy use. • Pike Research believes that when the vendors begin to face the issue of scale, this competitive landscape will shift. The increasing need for scalability to handle ever-increasing amounts and complexity of data will provide a major advantage to those vendors that have the current software and other resource capabilities to handle the explosion of data. • Once scale and scalability become the key issue for utilities, many smaller vendors could lose their competitive advantage. To compete effectively in this marketplace, vendors must demonstrate that they possess deep utility industry know-how and understanding of the different technological and data analytics challenges that utilities face when transitioning to a smart grid operation. Competitive Landscape (from Navigant Research)
  41. 41. • A solid background in managing and interpreting data for other industry clients, especially in the telecom, banking, or retail sectors – be it in the area of business intelligence, information management, data correlation and modeling techniques, data mining, database/data warehousing, or predictive analytics and forecasting – will be considered an advantage by potential utility clients as they try to address their smart grid data analytics issues. • Moreover, in this early adoption phase, vendors need to be sensitive to the fact that many utilities are not ready and willing to handle too much change at once, preferring instead a more cautious, incremental approach. The ability to integrate data and the results of analytics into business processes is another key competitive factor. Competitive Landscape (from Navigant Research)
  42. 42. • Similarly, it is important that vendors can offer visualization along with location and geospatial enablement of data sets. • Since data security and privacy is of such a significant concern among utility companies when deploying smart grid technology, vendors with a strong background in dealing with these issues tend to enjoy a competitive edge. • As the volume of data escalates, scalability and speed of analysis through in-memory analytics will also matter a great deal to utility clients. • When the quantity of data becomes overwhelming for utilities to handle, outsourcing will become an attractive option. Utilities will be inclined to contract out the management of their data, including data analytics, on an ongoing basis to a vendor. • In such a case, the outsourcers, especially those with cloud computing capabilities, will have a competitive advantage. Smart Grid Data Analytics © 2013 Pike Research LLC. All Rights Reserved. This publication may be used only as expressly permitted by license from Pike Research LLC and may not otherwise be accessed or used, without the express written permission of Pike Research LLC. 4 Competitive Landscape (from Navigant Research)
  43. 43. By 2020, the deployment of smart technologies in the electric grid, transport, buildings, logistics, and industrial motors will save 15% of global emissions and almost a $1 trillion in savings per year in energy savings to global industry. Source: The Climate Group (Accenture)
  44. 44. Conclusions • The energy industry is diverse, complex and growing rapidly. • Shale energy is driving oil and gas production and providing energy independence from foreign sources. • The digital revolution is also impacting the energy industry with IoT, and data management and analytics. • The Clean Revolution is providing new regulatory mandates for clean energy and innovation in Renewables energy resources (Solar, Wind, Energy Storage, etc.) which are further driving states, utilities and industry from fossil fuels. • Global urbanization and smarter cities are also driving demand in the future for more efficient, resilient and reliable clean energy.
  45. 45. • Successful Investor Owned Utilities (IOU’s) and some Muni’s (like SMUD) will transform into hybrid companies providing more than just energy. • They first need to decide whether they will build centralized power plants or distributed generation resources through solar, wind, energy storage, microgrids, etc. • IOU’s will also provide network and data content through their connected network in the form of energy conservation services, allowing consumers control over their own energy usage through demand response, and services derived by distributed generation optimization (DGO). Conclusions
  46. 46. • Utilities that rightly leverage and integrate their big data, technology, and analytics will be most likely to manage the complexities of the future state where energy markets and the regulatory environment continue to be unpredictable, and consumers become more sophisticated about their energy options and demand more cost /energy efficient, reliable, and resilient grid. • Fully interoperable Data Management Systems will enable the optimization of the lifecycle management of both data and physical infrastructure assets that will enable adaptability in planning, management and real- time business mobile operating intelligence. • Optimized management of integrated enterprise data will ultimately improve growth and profits and provide enterprise value for investors. Conclusions
  47. 47. • Tomorrow’s winners will be those who successfully manage two key transitions: – from a technology standpoint, their operators must be able to benefit from digital innovation while at the same time building up a solid defense to cyber attacks. – From a legal framework standpoint, their structures will have the necessary flexibility to adapt to an ever- changing environment. • Tomorrow’s challenge for the energy sector will be to achieve effective collaboration between all stakeholders involved, for the world to meet its future energy needs in a sustainable way. Conclusions
  48. 48. Thank you for your time Jonathan L. Tan CEO gzz cleantech consulting LinkedIn Twitter 847-636-3578 Mobile