Newsletters

Developing Energy Storage Roadmap for Electric Utilities

Summary:

By Dr. Ralph Masiello Energy storage systems (ESS) are a new technology for electric utilities which offer great promise in assisting with renewable energy resources integration, and in reducing capital expenditures by increasing asset utilization. It also has potential for improving system reliability. Quanta Technology has developed a comprehensive tool set and the associated methodology for developing a strategy and roadmap for energy storage size/technology selection and deployment plans, including a quantitative business case analysis. Many utilities have begun pilot projects as they seek to learn about the technology and its applications. In California, especially, ESS has moved beyond the pilot stage; thanks to the CPUC deployment mandate (Rulemaking 10-12-007 pursuant to CA AB 2514) to achieve certain penetration levels by 2020 and 2030. For instance, large scale energy storage systems are playing a key role in mitigating the effects of the Alviso Canyon gas leaks. There are numerous other examples from smaller behind the meter installations to large grid scale applications. Turning ESS from the pilot phase to a technology that is at least considered in distribution planning on a routine basis is another thing altogether. And understanding just how much ESS a utility might plan to have system wide in a multi-year planning horizon is still more difficult. Quanta Technology has developed a roadmap approach that addresses these questions and is a big step forward in enabling distribution planners to exploit energy storage. A key question to address: why should a utility today develop a “roadmap” for ESS, if it is not imminently faced with regulatory pressure or with high renewables penetration? In short, it is primarily to be proactively ahead of the curve and prepared for the day when the issue comes to the table. Most importantly, many state commissions are not fully up to speed on energy storage yet, and may be getting information from the perspective of the energy storage industry or from developers that want to see energy storage classified as a “competitive” resource and utilities excluded from participation. A well-developed roadmap should include: clearly detailed benefits to the ratepayers, economics of different regulatory approaches, various energy storage business models and value streams, and deployment approaches that enable the utility to make a well-reasoned, technical, and economically robust argument. One important element in developing a roadmap is to understand the various ESS technologies commercially available in the market and/or under development in the laboratory today, as well as projections for their cost and performance for the next few years. Such information is readily available from multiple sources; but, they need to be processed and presented in the context of a utility environment. Quanta Technology has taken this common roadmap practice a step further by incorporating a detailed bottom-up probabilistic and futuristic cost model of energy storage turnkey costs for several leading electro-chemistries, based on the Argonne National Lab BatPac tools. (http://www.cse.anl.gov/batpac/). This novel approach allows the development and analysis of different planning scenarios as part of the roadmap based on possible future evolution paths. This method also allows utility managers and decision makers to monitor key flags in the energy storage development costs as new solutions or technology breakthroughs emerge in the market. This tool is getting constantly updated and extended to include additional technologies. We believe it will be useful in understanding the range of possibilities – after all, if ESS were already inexpensive and robust, it could be in widespread service today to bring capacity factors from the 40%’s to 80% or higher (defined as the average loading as a percentage of peak load allowed for the distribution circuit). One challenge for utility planners is that commonly used distribution planning software suites do not represent the ESS model properly, or fail to represent how ESS actually operates in various applications. Quanta Technology has developed a set of software that simulates the energy storage control algorithms and the physical storage system and also integrates with common planning software platforms such as CYME™. These control algorithms can work with “centralized” (deployed at the substation) or “distributed” (multiple storage systems along the feeder) projects. The enhanced planning models support analyses of major applications such as: capacity deferral, arbitrage, backfeed prevention, power factor control, production intermittency smoothing and voltage control applications. They can work on a balanced three phase basis or on a per phase basis. These algorithms are more sophisticated than those found in many published works. For instance, the capacity deferral algorithm acts to peak shave MW loads, but it can also take advantage of the reactive power compensation to exploit near-perfect power factor correction. This receives the last few pecentages of capacity out of a conductor. The application can also work on a phase amperage basis, instead of individually managing active and reactive power flows. Integrated with common power flow tools, they provide time-series quasi-steady state-type analysis by performing minute-by-minute simulations of the controls and the energy storage simulation (or even higher time-based resolution studies for managing voltage fluctuations). These applications and simulations are what is needed to perform the detailed engineering validation of energy storage projects, such as the evaluation of system configuration and the locations of a given circuit for chosen applications. The control algorithm for smoothing large and sudden voltage fluctuations (beyond the permissible ranges due to impact of high penetration of PV installations) on the grid is equally sophisticated. This modeling and simulation analysis can exploit “smart bi-directional inverter” capabilities to manage not only storage MW charge/discharge rates, but also to adjust inverter Mvar flows to regulate voltages at the ESS point of interconnection and on the nearby feeder sections. An example case of investigating the improving effect of the voltage smoothing application through an ESS for a circuit with large amount of solar PV systems is shown in Figure 1. The results of 60-minute time-series voltage analysis for the circuit for the case of no ESS (trend in blue), and after applying the ESS application (trend shown in red) are given in Figure 1. The before and after trends clearly show voltage spike mitigation and smooth transitions as the PV production changes due to cloud alternations.     But how do you know which circuit can benefit from an ESS, and how do you know what power and energy rating ESS to begin with when you perform the detailed engineering? Performing detailed time series simulations across a large number of circuits is tedious and unworkable for most utilities. A reasonably accurate method to assess a large population of feeders, and to determine where there is a viable business case for energy storage, the size of the system, and so on, is required. Quanta Technology has developed MATLAB analytics that can process a large population of feeders and to determine, for instance, the best configuration of energy storage for capacity deferral as well as the best deferral period economics compared to normal capacity upgrades. The economics are evaluated in terms of customary utility revenue requirements as well as cash flow. A key element in developing viable energy storage business cases is how the energy storage resource can passively or actively participate in energy markets for the benefit of the ratepayer. The Quanta Technology methodology is unique and powerful in that it can explore multiple alternative energy storage business models in parallel with “utility” applications and it can simultaneously analyze their combined economic benefits. The Figure 1 Feeder load and allowable rating simply shows the feeder loading curve-vs-rating throughout the day. A modest overload exists from hours 11 to 19. In Figure 2 the loading is reduced by the BESS dispatch. (BESS = “Battery Energy Storage System”) In figure 3, BESS dispatch – Capacity Deferral and Time Arbitrage – the BESS dispatch is refined to not only avoid the overload, but also to manage the BESS charging and discharging, so as to reduce energy costs at the substation (costed at Locational Marginal Price for that station hourly) via time arbitrage (it is technically arbitraging the hourly prices via time shifting energy demand, we use the term “time arbitrage” for this). Figures 4 and 5 compare the cases and show more detail of the BESS charging and discharging. The capacity deferral application is inherently a peak shaving application which shifts some wholesale or transmission-level energy draw from on-peak to off- peak, allowing the deferral of an upgrade required to meet just a few peak hours a year (see Figure 5 and 6). As load grows, the peak-shaving occurs more frequently. In any regulatory environment where the transmission energy carries a higher cost to the distribution utility and its ratepayers on-peak/off-peak (TOU pricing or dynamic hourly pricing, for example), the peak shaving automatically generates savings. The Quanta Technology analysis platform accurately computes these savings looking at the hourly profiles across a full year. When the energy storage is not needed for peak-shaving reliability purposes, it can still be used for time arbitrage or energy shifting. It can be done in a way that maximizes savings. Quanta Technology uses a sophisticated optimization scheme to compute the optimal scheduling of energy charging and discharging to maximize savings across the year (see Figure 7 and 8). Note, this can be done without active market participation in the bidding process. The storage is a “price taker” in the market environment. An valid application for a regulated or municipal utility is as well. Going a step further, the unneeded energy storage capacity can be used for participation in ancillary services markets. The energy storage economics can be further enhanced by using some of the capacity not for time shifting but for providing reserves and regulation. The Quanta Technologies optimization co-optimizes the allocation of capacity to energy-shifting/time-arbitrage. Delivery of the ancillary products reserves regulation, while meeting needs for reliability applications (See Figure 9 and 10). This could be done by the utility as a participant or as a “shared application”, where a 3rd party market-participant is paying for the use of the resources. Gaining the revenues from ancillaries requires an “active market participation” as a bidder, note. Figure 6 compares Capacity Deferral (“CD”), Capacity Deferral plus Arbitrage (“CDA”), and Capacity Deferral plus Arbitrage and Ancillaries (“CDAAM”) patterns the charging and discharging, as well as how the BESS capacity is allocated to the different applications. There is a “lot going on,” and depending upon the relative pricing of the energy and different ancillaries, BESS capacity, and overriding capacity deferral needs, the patterns can change dramatically from day-to-day, or as a function of BESS capacity. In the plots, the energy prices (only) are shown as Y axis, and the ancillaries prices will vary, more or less. Results from this overall roadmap are insightful and quite different than higher-level or spreadsheet approaches. Blanket assessments based on “typical” data that do not look at hourly details will either overstate the number of feeders that can benefit from storage – badly – or fail to identify those that can, due to pessimistic and simplistic assessments of benefits. Even more importantly, the roadmap process can be then transferred to real-world planning using the detailed engineering analytics now available. We then analyze how storage penetration develops under these three scenarios (CD, CDA, CDAAM per above). under “rules” for deployment based on utility economics as used in rate-case analysis. This includes the cost of storage, ratepayer benefits, and the utility ROI investment hurdles. Storage deployment on feeders in the population increases at different rates over time, based on how load growth and energy prices will affect the economic viability of BESS on a particular feeder. Figure 7 shows the total storage deployment over time for a large feeder population (> 1000 feeders). This allows analysis of the sensitivity of storage viability against parameters such as energy prices, interest rates, storage costs, storage efficiencies, and storage lifetime/depreciation charges. Figure 8 reduces all of this to cumulative ratepayer benefits – what matters at a day’s end. Furthermore, plots over time can be created to show the ratepayer cost accrued for each year of energy storage operation (Figure 9). These are shown for the cases of CD, CDA, and CDAAM operation for batteries. The benefit is the time value of the deferral plus the arbitrage while the battery remains to collect arbitrage / ancillary revenue after distribution station or feeder capacity upgrades. Generic data for capacity costs are used, but it is possible to instead use specific feeder costs if such analysis exists.. The orange line represents the benefit of the battery without any arbitrage. The red line represents the benefits of the battery with arbitrage. The yellow line represents benefit of the battery with inclusion of the ancillary services. Conclusion It is possible to develop an overall “roadmap” for BESS deployment in a distribution system that pragmatically assesses a large population of stations and feeders and which explores different storage applications/business models as well as the sensitivities to technology costs, energy prices, interest rates, and so on. The full roadmap development then becomes a good vehicle for communicating the utility perspective on storage to regulatory bodies, and for informing  the utility management. The roadmap is also an effective way to screen a large feeder population for storage viability after the detailed engineering analysis using specific BESS products and controllers against individual feeders has been performed. Energy Storage is “happening” today. Utilities are well advised to get ahead of the problem and have a roadmap ready at hand for the day when management asks for it! Quanta Technology can assist in the development and maintenance of that plan using proven methodologies.  

Newsletter Archives

2017

Developing Energy Storage Roadmap for Electric Utilities

Summary:

By Dr. Ralph Masiello Energy storage systems (ESS) are a new technology for electric utilities which offer great promise in assisting with renewable energy resources integration, and in reducing capital expenditures by increasing asset utilization. It also has potential for improving system reliability. Quanta Technology has developed a comprehensive tool set and the associated methodology for developing a strategy and roadmap for energy storage size/technology selection and deployment plans, including a quantitative business case analysis. Many utilities have begun pilot projects as they seek to learn about the technology and its applications. In California, especially, ESS has moved beyond the pilot stage; thanks to the CPUC deployment mandate (Rulemaking 10-12-007 pursuant to CA AB 2514) to achieve certain penetration levels by 2020 and 2030. For instance, large scale energy storage systems are playing a key role in mitigating the effects of the Alviso Canyon gas leaks. There are numerous other examples from smaller behind the meter installations to large grid scale applications. Turning ESS from the pilot phase to a technology that is at least considered in distribution planning on a routine basis is another thing altogether. And understanding just how much ESS a utility might plan to have system wide in a multi-year planning horizon is still more difficult. Quanta Technology has developed a roadmap approach that addresses these questions and is a big step forward in enabling distribution planners to exploit energy storage. A key question to address: why should a utility today develop a “roadmap” for ESS, if it is not imminently faced with regulatory pressure or with high renewables penetration? In short, it is primarily to be proactively ahead of the curve and prepared for the day when the issue comes to the table. Most importantly, many state commissions are not fully up to speed on energy storage yet, and may be getting information from the perspective of the energy storage industry or from developers that want to see energy storage classified as a “competitive” resource and utilities excluded from participation. A well-developed roadmap should include: clearly detailed benefits to the ratepayers, economics of different regulatory approaches, various energy storage business models and value streams, and deployment approaches that enable the utility to make a well-reasoned, technical, and economically robust argument. One important element in developing a roadmap is to understand the various ESS technologies commercially available in the market and/or under development in the laboratory today, as well as projections for their cost and performance for the next few years. Such information is readily available from multiple sources; but, they need to be processed and presented in the context of a utility environment. Quanta Technology has taken this common roadmap practice a step further by incorporating a detailed bottom-up probabilistic and futuristic cost model of energy storage turnkey costs for several leading electro-chemistries, based on the Argonne National Lab BatPac tools. (http://www.cse.anl.gov/batpac/). This novel approach allows the development and analysis of different planning scenarios as part of the roadmap based on possible future evolution paths. This method also allows utility managers and decision makers to monitor key flags in the energy storage development costs as new solutions or technology breakthroughs emerge in the market. This tool is getting constantly updated and extended to include additional technologies. We believe it will be useful in understanding the range of possibilities – after all, if ESS were already inexpensive and robust, it could be in widespread service today to bring capacity factors from the 40%’s to 80% or higher (defined as the average loading as a percentage of peak load allowed for the distribution circuit). One challenge for utility planners is that commonly used distribution planning software suites do not represent the ESS model properly, or fail to represent how ESS actually operates in various applications. Quanta Technology has developed a set of software that simulates the energy storage control algorithms and the physical storage system and also integrates with common planning software platforms such as CYME™. These control algorithms can work with “centralized” (deployed at the substation) or “distributed” (multiple storage systems along the feeder) projects. The enhanced planning models support analyses of major applications such as: capacity deferral, arbitrage, backfeed prevention, power factor control, production intermittency smoothing and voltage control applications. They can work on a balanced three phase basis or on a per phase basis. These algorithms are more sophisticated than those found in many published works. For instance, the capacity deferral algorithm acts to peak shave MW loads, but it can also take advantage of the reactive power compensation to exploit near-perfect power factor correction. This receives the last few pecentages of capacity out of a conductor. The application can also work on a phase amperage basis, instead of individually managing active and reactive power flows. Integrated with common power flow tools, they provide time-series quasi-steady state-type analysis by performing minute-by-minute simulations of the controls and the energy storage simulation (or even higher time-based resolution studies for managing voltage fluctuations). These applications and simulations are what is needed to perform the detailed engineering validation of energy storage projects, such as the evaluation of system configuration and the locations of a given circuit for chosen applications. The control algorithm for smoothing large and sudden voltage fluctuations (beyond the permissible ranges due to impact of high penetration of PV installations) on the grid is equally sophisticated. This modeling and simulation analysis can exploit “smart bi-directional inverter” capabilities to manage not only storage MW charge/discharge rates, but also to adjust inverter Mvar flows to regulate voltages at the ESS point of interconnection and on the nearby feeder sections. An example case of investigating the improving effect of the voltage smoothing application through an ESS for a circuit with large amount of solar PV systems is shown in Figure 1. The results of 60-minute time-series voltage analysis for the circuit for the case of no ESS (trend in blue), and after applying the ESS application (trend shown in red) are given in Figure 1. The before and after trends clearly show voltage spike mitigation and smooth transitions as the PV production changes due to cloud alternations.     But how do you know which circuit can benefit from an ESS, and how do you know what power and energy rating ESS to begin with when you perform the detailed engineering? Performing detailed time series simulations across a large number of circuits is tedious and unworkable for most utilities. A reasonably accurate method to assess a large population of feeders, and to determine where there is a viable business case for energy storage, the size of the system, and so on, is required. Quanta Technology has developed MATLAB analytics that can process a large population of feeders and to determine, for instance, the best configuration of energy storage for capacity deferral as well as the best deferral period economics compared to normal capacity upgrades. The economics are evaluated in terms of customary utility revenue requirements as well as cash flow. A key element in developing viable energy storage business cases is how the energy storage resource can passively or actively participate in energy markets for the benefit of the ratepayer. The Quanta Technology methodology is unique and powerful in that it can explore multiple alternative energy storage business models in parallel with “utility” applications and it can simultaneously analyze their combined economic benefits. The Figure 1 Feeder load and allowable rating simply shows the feeder loading curve-vs-rating throughout the day. A modest overload exists from hours 11 to 19. In Figure 2 the loading is reduced by the BESS dispatch. (BESS = “Battery Energy Storage System”) In figure 3, BESS dispatch – Capacity Deferral and Time Arbitrage – the BESS dispatch is refined to not only avoid the overload, but also to manage the BESS charging and discharging, so as to reduce energy costs at the substation (costed at Locational Marginal Price for that station hourly) via time arbitrage (it is technically arbitraging the hourly prices via time shifting energy demand, we use the term “time arbitrage” for this). Figures 4 and 5 compare the cases and show more detail of the BESS charging and discharging. The capacity deferral application is inherently a peak shaving application which shifts some wholesale or transmission-level energy draw from on-peak to off- peak, allowing the deferral of an upgrade required to meet just a few peak hours a year (see Figure 5 and 6). As load grows, the peak-shaving occurs more frequently. In any regulatory environment where the transmission energy carries a higher cost to the distribution utility and its ratepayers on-peak/off-peak (TOU pricing or dynamic hourly pricing, for example), the peak shaving automatically generates savings. The Quanta Technology analysis platform accurately computes these savings looking at the hourly profiles across a full year. When the energy storage is not needed for peak-shaving reliability purposes, it can still be used for time arbitrage or energy shifting. It can be done in a way that maximizes savings. Quanta Technology uses a sophisticated optimization scheme to compute the optimal scheduling of energy charging and discharging to maximize savings across the year (see Figure 7 and 8). Note, this can be done without active market participation in the bidding process. The storage is a “price taker” in the market environment. An valid application for a regulated or municipal utility is as well. Going a step further, the unneeded energy storage capacity can be used for participation in ancillary services markets. The energy storage economics can be further enhanced by using some of the capacity not for time shifting but for providing reserves and regulation. The Quanta Technologies optimization co-optimizes the allocation of capacity to energy-shifting/time-arbitrage. Delivery of the ancillary products reserves regulation, while meeting needs for reliability applications (See Figure 9 and 10). This could be done by the utility as a participant or as a “shared application”, where a 3rd party market-participant is paying for the use of the resources. Gaining the revenues from ancillaries requires an “active market participation” as a bidder, note. Figure 6 compares Capacity Deferral (“CD”), Capacity Deferral plus Arbitrage (“CDA”), and Capacity Deferral plus Arbitrage and Ancillaries (“CDAAM”) patterns the charging and discharging, as well as how the BESS capacity is allocated to the different applications. There is a “lot going on,” and depending upon the relative pricing of the energy and different ancillaries, BESS capacity, and overriding capacity deferral needs, the patterns can change dramatically from day-to-day, or as a function of BESS capacity. In the plots, the energy prices (only) are shown as Y axis, and the ancillaries prices will vary, more or less. Results from this overall roadmap are insightful and quite different than higher-level or spreadsheet approaches. Blanket assessments based on “typical” data that do not look at hourly details will either overstate the number of feeders that can benefit from storage – badly – or fail to identify those that can, due to pessimistic and simplistic assessments of benefits. Even more importantly, the roadmap process can be then transferred to real-world planning using the detailed engineering analytics now available. We then analyze how storage penetration develops under these three scenarios (CD, CDA, CDAAM per above). under “rules” for deployment based on utility economics as used in rate-case analysis. This includes the cost of storage, ratepayer benefits, and the utility ROI investment hurdles. Storage deployment on feeders in the population increases at different rates over time, based on how load growth and energy prices will affect the economic viability of BESS on a particular feeder. Figure 7 shows the total storage deployment over time for a large feeder population (> 1000 feeders). This allows analysis of the sensitivity of storage viability against parameters such as energy prices, interest rates, storage costs, storage efficiencies, and storage lifetime/depreciation charges. Figure 8 reduces all of this to cumulative ratepayer benefits – what matters at a day’s end. Furthermore, plots over time can be created to show the ratepayer cost accrued for each year of energy storage operation (Figure 9). These are shown for the cases of CD, CDA, and CDAAM operation for batteries. The benefit is the time value of the deferral plus the arbitrage while the battery remains to collect arbitrage / ancillary revenue after distribution station or feeder capacity upgrades. Generic data for capacity costs are used, but it is possible to instead use specific feeder costs if such analysis exists.. The orange line represents the benefit of the battery without any arbitrage. The red line represents the benefits of the battery with arbitrage. The yellow line represents benefit of the battery with inclusion of the ancillary services. Conclusion It is possible to develop an overall “roadmap” for BESS deployment in a distribution system that pragmatically assesses a large population of stations and feeders and which explores different storage applications/business models as well as the sensitivities to technology costs, energy prices, interest rates, and so on. The full roadmap development then becomes a good vehicle for communicating the utility perspective on storage to regulatory bodies, and for informing  the utility management. The roadmap is also an effective way to screen a large feeder population for storage viability after the detailed engineering analysis using specific BESS products and controllers against individual feeders has been performed. Energy Storage is “happening” today. Utilities are well advised to get ahead of the problem and have a roadmap ready at hand for the day when management asks for it! Quanta Technology can assist in the development and maintenance of that plan using proven methodologies.  

Grid Modernization - Challenges and Opportunities

Summary:

by Damir Novosel of Quanta Technology 1.     Introduction Modern society has reached a point where virtually every crucial, economic, and social function depends on the safe, secure, and reliable, operation of the electrical power and energy infrastructures. New technology trends include development of more efficient, reliable, and cost-effective renewable generation and Distributed Energy Resources (DER), energy storage technologies, Electric Vehicles (EV), monitoring, protection, automation, and control devices, and communications that offer significant opportunities for realizing a sustainable energy future. However, the electric power systems in the industrialized world, in addition to generally being quite old, particularly in large metropolitan areas, face challenges caused by physical and cyber security attacks, environmental concerns, new weather patterns, changing consumer needs, and regulatory requirements. While the electrical power system is becoming, and will continue to become, more distributed, it is important to note that today’s interconnected grid began as a distributed grid. Interconnected grids were created to improve grid cost-efficiency, reliability, service quality, and safety. As technology advancements made it easier to deploy renewable resources and, controllable, more efficient distributed grids, the fundamental benefits of a connected grid still hold and in fact, become more important. While the present grid is generally considered reliable, as dependency on the digital economy grows, users will demand even more reliability from the electric power delivery in the future, including resilience during major weather or security events. Transmission and distribution systems are an enabler to deployment of renewable resources, providing pathways for the transport of clean energy between production and consumption centers and a means for resource movement and delivery, while at the same time fortifying electric system efficiency, stability, and reliability of supply. Integration of DER and distributed grids can increase efficiencies in the use of the existing grid, as well as become part of the overall development strategy to balance the supply-and-demand uncertainties and risks in a variety of different resources. In cases where distributed grids become predominant (e.g. renewable intermittent DER plus energy storage), and grid usage becomes equally as variable, assuring a safe and reliable supply will require an intelligent, modern, resilient, flexible and safe grid. Several states in the USA, like California and New York, and countries such as Germany, Spain, and Australia have ambitious goals for achieving high penetration levels of renewable generation and DER in the electric power system in coming years. These goals are necessary if the energy infrastructure is to adapt to the transition away from carbon based fuels required to mitigate climate change. In achieving those goals, a key question is how much should be invested in the grid as more and more DER (e.g. microgrids or systems using PV plus energy storage) serve loads without utilizing the grid for the majority or extended periods of time. The follow up question is what the value of the grid is in presence of DER and energy storage. It is well understood by the industry as documented through independent and objective organizations such as IEEE (e.g. IEEE report on Quadrennial Energy Review per DOE request)[1] that the reliability and safety of serving electrical power load will be negatively affected if the T&D grid is not available to provide backup. Therefore, increasing the ability of the T&D system to host and enable the use of increasing penetration levels of DER is an essential step in achieving this medium and long-term vision. 2.     Modern Grid Ingredients Building this intelligent grid is a monumental task (particularly on the distribution and grid-edge sides, which are vast and heterogeneous) that has led to the emergence of new concepts, technologies, and paradigms. Examples of this include debates regarding future grid architecture (a distributed, hybrid, or centralized grid); advances in grid modeling, simulation, and analysis; the introduction of the microgrid concept as an alternative to enhance resiliency and facilitate DER integration; and the convergence of information and operations technologies (IT/OT). The idea of the utility of the future encompasses the need for all aspects pertaining to the utility industry to evolve and adapt to this new and dynamic customer-centric reality. This includes business and engineering processes, regulation, policies, rate design, asset ownership, service diversification, and relationships with customers. Furthermore, changing weather patterns are leading to increased frequency of severe events and associated risks for electric utilities, such as extreme temperatures accompanied by abnormal peak demands, severe droughts accompanied by wildfires and infrastructure damage, etc. Average temperature rise stresses grid equipment (e.g. transformers and T&D lines), including reducing its life-time. In addition to adapting planning and operations practices to this “new normal”, the above effects require updated equipment design, as well as different engineering and construction practices to counteract the impact of climate change and enable the adoption of new technologies. For instance, impacts caused by the adoption of inverter-based DER technologies such as voltage fluctuations, reverse flows, low fault currents affecting system protection performance, and potential loss of inertia (requiring frequency regulation) need to be addressed. Future grid capabilities could be divided into three broad categories: Technology and integration, processes and standards, and regulation and business models. Advanced monitoring, protection, automation, and control technologies, new tools for operations, planning, and communications, as well as robust and foundational infrastructure can facilitate the transition to a high renewables/high DER grid. Although grid technology related aspects are challenging and complex, changes and solutions in this area are at a more advanced stage than those needed to address emerging regulatory, policy, and business problems and needs (some of which are being triggered or enabled by technology developments). In summary, addressing the business, legal, regulatory, and policy side of the utility of the future is an area where significant work is required. Integration of high penetration levels of renewables, DER, energy storage, and EV in the electric power system requires increasing the ability of the T&D system to host and enable the use of these resources, while improving the reliability, resiliency, and safety of the electrical power supply. Grid modernization is key to realizing this potential. The traditional assumption that T&D systems could be analyzed separately is no longer valid, and joint modeling, simulation and analysis of T&D systems (and particularly sub-transmission and distribution systems) is gradually becoming a need that requires new modeling approaches and simulation tools. This interdependency is progressively increasing and starting to impact operations and planning of T&D systems. Utilities operating in states such as California (PG&E, SCE, and SDG&E) and Hawaii (HECO), where DER proliferation is already a reality and where aggressive DER adoption will continue to achieve to achieve renewables and environmental goals, continue this evolution toward a modernized distribution grid at a faster pace than utilities operating in emerging DER markets. Otherwise, DER proliferation will lead not only to significant operations, planning and engineering challenges and inefficiencies, but also will prevent utilities (and ultimately customers and society in general) to attain the potential benefits derived from the adoption of these technologies. Furthermore, since even larger-scale adoption of DER is inevitable, given the imminent (or existing) achievement of grid parity by PV-DG in these markets, additions in grid modernization infrastructures and systems should largely be considered “necessary” rather than “optional” investments to enable the normal operation of modern and future distribution systems. It is worth noting that utilities operating in states with incipient penetration levels of DER, recognize the imminence and urgency of preparing for the transition to this new paradigm, and are actively working on modernizing their distribution grids and overall practices so that they are suitable for operation in this new reality. An important point to emphasize is that the pace of the transition toward a modernized grid, particularly on the distribution side, is a function of the existing and expected system conditions and trends of every utility system and market. Grid modernization and DER proliferation are certainly interrelated, but the latter is not a requirement for the former. Utilities such as Commonwealth Edison (ComEd), Dominion, and CenterPoint, which operate in service territories with incipient penetration levels of DER, have successfully implemented grid modernization initiatives with the purpose of improving grid reliability, resiliency, and system efficiency, addressing growing expectations regarding customer service, and replacing foundational aging infrastructure. 3.     Grid Modernization Requirements and Smart Technologies The following are some of key areas for grid modernization. It is envisioned that further evolution and modernization in this areas is required to enable the T&D system of the future. DER technology - While vendor and developer information systems are certainly aware of new DER sales and installations, these sources of information need to be better integrated with utility systems, and privacy and cybersecurity issues should remain a high priority along with tackling consumer privacy and data ownership implications, especially for DER not owned and operated by utilities. The IOT promises low cost ubiquitous communications to DER which would facilitate incorporating them in advanced market and operations processes. However, distribution systems are expected to have a high level of reliability, security, and availability, even in catastrophic situations, requiring upgrades to improve the capacity and reliability with increased automation. Smart inverter technology are helpful technologies to facilitate DER integration and have voltage and frequency “ride-through” capabilities. However, the utilization of this technology introduces additional challenges such as a need to provide enough fault current to activate protection devices during fault conditions and address significant reduction in the system inertia affecting the system frequency. While smart inverters can regulate voltage, the mitigating impacts of reducing voltage may increase the reactive power requirements from the grid. Thus, close coordination with Volt/VAR control is required. Smart PV inverters require additional equipment upgrades, much improved grid monitoring and control systems, new planning methods and tools, grid management systems that feature more interaction with DER, and implementation of appropriate interconnection standards. Energy storage promises the ability to mitigate renewable DER variability and improve T&D utilization and economics, but technical, regulatory and economic barriers still impede its adoption even in states with aggressive programs for deployment. “Shared applications”, meaning multiple use of the same energy storage device, is a key to realizing the best economic potential from the technology. However, regulatory barriers and legacy paradigms are major obstacles to the rapid adoption of these technologies and their most effective uses. Energy storage is forced to fit into one of the generation, transmission, distribution or customer “buckets” and follow rules established for that asset class. Energy storage is in many viewpoints a new asset class of its own. Microgrids can serve as a scheduling /dispatch /control entity responsible for balancing load and generation, and in grid connected operations possibly serving as a point of aggregation up to higher level operations and even to wholesale markets. They enable resources, customer, and network to be islanded from the main power grid so as to allow continuity of service on some basis during contingencies with energy provided by local resources. Grid integrated microgrids require protection, sectionalizing, monitoring, automation, and – most importantly – control capabilities beyond those typically used in distribution systems today. Integrated, holistic T&D planning and operations – As the variability of distribution system net load increases, better coordination and information transfer is required. The ISO can no longer rely on simple load forecast bus allocation factors to forecast bus net loads but must be able to forecast PV production, as one example. More importantly, the use of DER to provide aggregated energy supply to the T&D system and ancillary services to the wholesale markets will be increasingly valuable. Better visibility and control is vital to the electrical system of the future - Advanced sensors, controls, and management systems are required to operate the distribution system in real-time to manage reliability and operational challenges derived from DER variability and load. Cost-effective monitoring of key electric variables, including bi-directional power flows, voltages, currents, equipment and DER status, etc., as well as fault information to circuit breakers and other protection devices is necessary to provide situational awareness. The ability to control DER on a five-minute basis will require overall bandwidth beyond the typical AMI network capacity. There is an increasing need for advanced sensors with higher resolution and GPS-based time-synchronization capabilities to accurately capture distribution system dynamics and address operational and power quality issues derived from DER variability. Furthermore, faster more intelligent, and flexible volt-VAR schemes (such as distribution-class power electronics-based static compensators) that work in coordination with smart inverters are required.  Advanced distribution and substation automation technologies enable enhanced grid flexibility as well as improved asset management that will increase asset lives, reduce costs, and improve reliability. However, only around 50% of US distribution substations are fully automated today. Digital relays, substation automation computers and data concentrators, and gateways to SCADA, DMS, and Energy Management Systems (EMS) systems – are fully commercial and proven technologies. They need to be implemented in large scale with full utilization of their key capabilities. Intelligent and adaptive reclosers and switches operating in Fault Location, Isolation and Service Restoration schemes can isolate faults in smaller sections to support increased flexibility and improve reliability with both traditional and distributed grids. Furthermore GPS based measurements may be able detect fault currents at a remote location or high impedance conditions not sufficient to trip the normal protection. Adaptive system protection will need to be widely used. DERs with inverter technology create various operating scenarios which are not presently addressed by existing protection schemes. Circuit power flows and fault current levels will change based on DER size, output, and location on the circuit. It is technically possible to set relays remotely or even to program adaptive settings from the DMS. The capabilities of digital relays to support adaptive protection settings (which may be determined at the substation or system level via new applications) will be needed to support protection under high penetration levels of DER and resolve issues such as insufficient fault current, island operation, etc. Electric transportation holds significant promise for reducing dependence on oil and carbon footprint. Electrical systems can help improve the livability, workability and sustainability of “Smart Cities”. Specifically addressing EVs, studies have shown that the first purchase of an EV is likely to inspire more in the same neighborhood, which can lead to the emergence of “clusters” and the overload of system components. Distribution system capacity upgrades in combination with solutions based on DER and intelligent load control could address these issues. The ideal scenario of the grid of the future of being able to achieve all the above is difficult to achieve in the short-term, given the monumental size and complexity of the distribution grid, and the large investments and required infrastructure (including communications systems) associated to this activity. However, a gradual transition toward this vision is possible and necessary to be able to provide a reliable, resilient, safe and secure service and operate the complex and highly dynamic distribution grid associated to high penetration of DER scenarios. There are some other necessary ingredients for successful grid modernization: Standards are more critical for both users and vendors to streamline deployment of both existing and new technologies and support interoperability among devices and systems as well as the use of best industry practices. For example, the IEEE 1547 Series of Interconnection Standards is critical for reliable and cost-effective DER deployment. Well-trained workforce, capable of dealing with grid changes, is necessary. A range of initiatives addressing grid modernization should be planned, including development of new curricula at universities, enhancement of secondary and post-secondary energy sector workforce training programs, attending tutorials, apprenticeships, and sharing and using best practices. This includes participation of individuals in standards development, professional activities and conferences, and continuous education. Furthermore, the ongoing evolution of the electric power industry also involves changes to existing electricity market and regulatory frameworks, which are aimed at satisfying the growing expectations of end users. The advanced monitoring, protection, automation and control infrastructures and capabilities introduced by grid modernization are vital enablers for the successful implementation of these initiatives. In the specific case of electricity markets, Transactive Energy (TE) and the DSO are two concepts widely discussed as being key elements in the Utility of the Future, in integrating DER with wholesale markets, and in applying market concepts to DER dispatching and operations on the distribution system. The spectrum of these discussions ranges from radically new paradigms to application of wholesale market design to the distribution system, including the introduction of Distribution Locational Marginal Pricing (DLMP). The TE advocates envision a future market where a “platform” allows buyers and sellers to find each other and where the energy markets are built around bilateral individual transactions ranging from real-time to months forward. These models have other commodities markets as their guiding light. However, the TE models have so far not shown how real world implementation including reliability and obligations with critical customers can be made to work, and are not “mainstream” today. The DSO or the Distribution System Platform (DSP) model is very much mainstream. Basically, wholesale concepts of day ahead, hourly, and real-time markets using locational pricing to manage congestion are the guiding principles. Considerable theoretical work as well as some rigorous cost-benefit studies have been done on this model. The undergoing Reforming the Energy Vision (REV) process in New York is definitely considering it seriously. However, as the DSO model is also based primarily on the wholesale model which relies on gross profits from dynamic energy market and ancillary prices to incent investments in generation as needed, more analysis is needed.  For example, any DER locational needs (in fact, one could argue most) will not be able to reduce congestion but will be able to avoid backfeed (curtailment or local energy storage) and to manage voltage and power fluctuations. These may turn out to be both “zero marginal cost” kinds of resources and also ones with significant capital costs – and where the relationship to the energy markets is tenuous, especially in the case of voltage support. So alternative schemes, such as distribution level capacity markets, may be called for. Furthermore advanced sensors and tools to enable are required to proper operate the distribution market. The conclusion is that initial DSO functionality and design should “keep things simple” to avoid error-prone complexity and to be robust against likely early stage data base and data errors. 4.     Recommendations We are at a crossroads of making business and technical decisions that will allow us to optimally and cost-effectively manage the electrical power delivery. The electrical power and energy sector will continue evolving as consumer expectations and options will change, technology breakthroughs will happen, and energy sources and their usage will be transformed. Use of electricity is expected to grow even with improvements in energy efficiency as it is expected that electrical energy will replace other forms of energy (e.g. transportation). As business models and technology are changing, the future grid is becoming a hybrid grid with distributed energy resources and microgrids integrated in traditional, but modernized, grid to fulfill all the consumer needs to balance the supply and demand uncertainties and risks with a variety of energy resources The following are overarching recommendations to achieve safe, resilient, reliable, and cost-effective delivery of electrical energy while supporting environmental targets for years to come: There is a need for grid modernization, with the speed of modernization adjusted to the pace of needed safety and reliability improvements, and the integration of clean DER and environmental and other regulatory targets. The architecture and design of the grid will have to be updated to accommodate very high penetration of DER and customer driven operations and planning. Enabling the transition to a modern grid requires changes in business models and regulatory policies, as well identification of the technical needs and development of new technologies. Continuous focus on improving safety, resiliency, reliability, cost-efficiency, and customer flexibility to choose.   In summary, Quanta Technology team has been very privileged to have continuous opportunities to work on the above topics either in partnership with a number of global utilities and IOU, supporting DOE and regulatory agencies, or through IEEE, CIGRE and other industry initiatives. We are proud to support and provide global leadership to our industry and the overall society on important grid modernization initiatives enabling safe, resilient, reliable, and cost-effective energy future.   [1] IEEE QER Report to DOE, http://www.ieee-pes.org/qer, September 2015 [2] http://grouper.ieee.org/groups/scc21/1547_series/1547_series_index.html

Quanta Technology Develops Synchrophasor Roadmaps and Benefits for Utilities

Summary:

By Dino Lelic, Ralph Masiello, Yi Hu, and Bryan Gwyn of Quanta Technology There are many identified potential benefits of synchrophasor technology.  However, implementation of the infrastructure and tools to realize these benefits is a work in process.  Building a business case for the needed investments has been a challenge up to now.  Quanta Technology has developed a methodology for quantifying the benefits of synchrophasor applications in a given environment and using that to develop a short, medium, and long-term roadmap for synchrophasor and applications deployment. Articulating those benefits is important in order to both assess the impact of past investments in the technology, and more importantly, to weigh investments in new projects. The Smart Grid Investment Grants (SGIG) and Smart Grid Demonstration Projects (SGDP) for synchrophasor and communications systems funded by the American Recovery and Reinvestment Act (ARRA) of 2009 helped many transmission utilities to procure and install modern, production-grade PMUs on an operational scale. Between 2009 and 2014, the federal grants and matching private investments (with 50% or more cost share provided by recipients) helped bring the technology into the mainstream of the electric utility industry across the North American grid, and motivated introduction of the technology worldwide. This increased the demand for production-grade PMUs and synchrophasor data applications. In this period most independent system operators and regional transmission operators for the first time considered the use of synchrophasor data applications. Initially, most of the benefits were based on qualitative, anecdotal evidence without developing specific numerical metrics for those benefits. As the SGIG programs approached their completion, many utilities started to look at options for the further advancement of the synchrophasor technology, and how to bring it into the control room. Without the discounts provided through DOE grants in the SGIG projects, a more critical business case approach was necessary, which resulted in a more quantifiable justification of the investment in the technology. In many regions, the generation mix is changing rapidly, where retirement of coal and nuclear plants gives way to renewables such as wind and solar power. These changes fundamentally affect how the future grid will be planed and operated, particularly since the issues need to be addressed, such as reduced system inertia, variability of wind and solar output, and the introduction of HVDC interconnections, to name a few. Many of the benefits are difficult to quantify economically, as they serve to mitigate high-impact/low-probability events such as major power system outages, or because the particular benefit is a “foundational” benefit or improvement in operations and planning processes, which contribute to more tangible benefits in market operations or asset management. The tangible benefits of synchrophasor technology applications can be grouped as follows: Reliability and Resiliency - Reduced number of outages and customers affected, primarily associated with the “low-probability/high-impact” event avoidance, reductions in unscheduled outages and faster restoration. Planning and Operations - Improvements due to more accurate models, better situational awareness and the use of grid resources (e.g., renewable and distributed), particularly during dynamic system conditions. Data Analysis - Faster and more accurate post-event analysis, more efficient use of resources to analyze data, faster restoration, and improved processes to avoid repeat events. Asset Utilization - Improved monitoring, maintenance, and availability of assets, such as transmission, distributed generation (e.g., inverters at wind farms and interconnectors), faster identification of asset failures. Markets - Improvement in congestion management and market costs for ancillary services (frequency response services and balancing energy services) and curtailment costs. Environmental and Policy Benefits - this includes increased delivery and use of renewable generation and a decrease in net carbon emissions. A less quantifiable benefit would be from the curtailment of costs, if synchrophasor technologies and fast energy storage could result in a new approach to provide relief from curtailment due to N-1 transmission contingencies. In developing the detailed roadmap, synchrophasor applications are selected based on the business drivers and needs. Applications in turn require a support of the appropriate infrastructure and the development of appropriate processes to enable their operational use.  Once all three areas are addressed, the applications will be able to address the drivers and needs, that will result in  improved reliability and operational efficiency. A typical process in preparation of the business case, specifically for addressing benefits, is shown in the following diagram. Once the benefits are quantified, they need to be prioritized, taking into account the level of importance to a specific utility (perhaps categorized as a "must-have", good-to-have and nice-to-have), the timeline of deployment (near-term, mid-term, long-term), and the level of cost/effort (low, medium, high). One example for prioritization would be a system with transient stability concerns to focus on applications relating to developing limits, determining operational regimes, and supporting special reliability functions in protection (special protection schemes). Another example, a system with long transmission lines, transmission boundaries, integration of HVDC lines, and with high level of wind integration may be vulnerable to oscillations, such as (inter-area oscillations), and subsynchronous resonance would need a different set of applications that could detect oscillations from very low frequency (0.005 – 0.1 Hz) to sub-synchronous oscillations (4-50 Hz), as well as to detect the locations of those oscillations. It is necessary to take into account the costs of deployment of the technology before further justifying the investment in the synchrophasor technology acquisition and installation. There are several cost components, and the major cost drivers as reported in [2] are, in order of impact to the total cost: communication infrastructure, security related costs, labor, and  equipment. Once the benefits and costs are identified, economic parameters such as benefits-to-costs ratio, net-present value, and payback can be calculated. A simple example is illustrated below.   LITERATURE: NASPI Technical Report, The Value Proposition for Synchrophasor Technology – Itemizing and Calculating the Benefits from Synchrophasor Technology, October 2015 “Factors Affecting PMU Installation Costs”, Smart Grid Investment Grant Program, US Department of Energy Report, October 2014 KEMA, Inc. 2010, Assessment of the Benefits and Costs of Seven PIER-Supported Projects. California Energy Commission. CEC-500-2009-014

2016

2016 Spring eNews

Summary:

Quanta Technology's Spring 2016 e-Newsletter focuses on Energy Storage.  It features links to presentations and published articles from Quanta experts and clients from the first quarter of 2016.

2015

2015 Summer/Fall e-News

Summary:

Dear Colleagues, As the electrical power system continues to be more complex, it is of utmost importance to address electric power system reliability as one of the most important objectives in our industry today. Under the best of operational circumstances, this is a formidable task, but add to that threats to critical infrastructure, physical and cyber security threats, changing weather patterns including events such as hurricanes, tornadoes and geomagnetic disturbances, it is essential to have a robust vulnerability management plan including risk assessment, probability analysis, grid hardening and response planning. Multiple layers of regulatory oversight are also in place to address the above. In the U.S., the Federal Energy Regulatory Commission (FERC) and the North American Electric Reliability Corporation (NERC) provide regulatory guidelines, mandates and standards that require electrical utilities to spend significant resources and efforts to comply. It is important to develop strategies and plans to efficiently address those requirements in conjunction with vulnerability management plans. This issue of our newsletter focuses on regulatory compliance topics. We share our experiences about how to: • Develop and implement a successful compliance documentation roadmap that includes best practices, ease of execution, program scope and Reliability Assurance Initiative attributes. • Navigate the evolution of NERC CIP Version 3 to Version 5 and the comprehensive requirements for physical and cyber security protection. • Address the new CIP-014-1 physical security standards for stations, substations and primary control centers. • Plan for the best outcome if 5,000 MW suddenly came through your system due to Geomagnetic Disturbance (GMD) from a sudden solar storm. Sincerely, Damir Novosel & the Quanta Technology Team

2015 Spring QT e-News

Summary:

The 2015 Spring edition of Quanta Technology's e-News quarterly newsletter is hot off the press, featuring articles about international clients and international projects: • Ecuador - Design & Implementation of Protection Systems for the National Transmission System • Netherlands - Enabling Energized Work Helps Maintain Electric Power Reliability • Colombia - Advancing Synchrophasor Applications • Malaysia - Line Protection Qualification by Real-Time Digital Simulation Testing

2015 Winter e-News Newsletter

2014

2014 Fall Newsletter

Summer QT e-News now available!

2014 Spring QT e-News newsletter

2013

2013 QT e-News Fall Winter Edition

2013 QT e-News - Summer Edition

Summary:

We are pleased to continue providing you with forward-thinking and timely articles in the QT e-News™ quarterly newsletter written by our industry experts. This issue discusses many of the topics that are trending in today’s energy market.

QT e-News - Spring 2013 Edition

Winter 2013 eNews Online Newsletter

Summary:

Quanta Technology's Winter 2013 edition of our e-News Online Newsletter highlights: * __Three External Trends will Affect Our Industry’s Future__ by Lee Willis * __Distribution Systems – Automation & Optimization__ by Nick Abi-Samra * __Power System Restoration After Blackouts__ by Anatoliy Meklin * __Methodology for Managing Stranded Assets__ by Farnoosh Rahmatian

2012

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Newsletter, Spring 2012 Edition

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2011

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2010

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