TODAY’S STUDY: The Value Of Distributed Energy
Expanding PV Value: Lessons Learned from Utility-led Distributed Energy Resource Aggregation in the United States
Jeffrey J. Cook, Kristen Ardani, Eric O’Shaughnessy, Brittany Smith, and Robert Margolis, November 2018 (National Renewable Energy Laboratory)
Distributed residential photovoltaic (PV) capacity in the United States increased from about 0.4 GW in 2010 to 10.5 GW in 2017 (GTM Research and SEIA 2018). Distributed PV and other emerging distributed energy resources (DERs) like battery storage and electric vehicles (EVs) may provide demand response, voltage regulation, and other grid services. When many DERs are aggregated and called upon to provide certain services simultaneously, they may provide the distribution grid with ancillary and other services that enhance reliability. These initiatives are often referred to as DER aggregation or virtual power plants. If nascent U.S. utility-led DER aggregation projects prove successful, new value streams could open for PV and other emerging DERs, thereby expanding deployment and transforming the energy market.
The literature on the scope, performance, and lessons learned from utility-led DER aggregation projects is limited. This report fills the research gap by surveying such programs nationwide and then analyzing five project case studies to compare lessons learned and identify common challenges and solutions that other utilities might consider when developing next-generation pilots and programs.
We identified 23 utility-led DER aggregation initiatives nationwide (Figure ES-1). The earliest project was launched by Bonneville Power Administration in 2009, while most were launched after 2014. There is significant geographic diversity in the programs; Arizona, California, and Hawaii are the only states with more than one utility-led DER aggregation program.
We selected the following five projects as case studies, because they incorporated PV, published data on DER performance, and had diverse characteristics such as project capacity and types of DERs involved:
• Green Mountain Power – McKnight Lane Redevelopment Project
• Maui Electric Company (MECO) – JumpSmart Maui Project
• Pacific Gas & Electric (PG&E) – San Jose EPIC
Distributed Energy Resource Demonstration Projects
• Southern California Edison (SCE) – Preferred Resources Pilot
• Sacramento Municipal Utility District (SMUD) – 2500 R Midtown Project
To analyze and compare the cases, we collected archival data and completed interviews with 27 subject-matter experts, including engineers, program managers, software developers, and other key partners. Overall, the unique design, scope, and timeline of each project complicates comparison of DER performance and related grid value across the projects. For example, project sizes vary from 0.04 MW of PV in the Green Mountain Power project to 51 MW in SCE’s. Even so, each project demonstrated that DER aggregation can provide grid benefits including frequency response, load shifting, and voltage regulation among others. As one example, SMUD found that controlling DERs at 10 homes provided an average load reduction of 2.66 kW per house and an aggregate 44 kW of load-shifting capability at peak.
Despite project design differences, there were commonalities in the lessons learned across each project that may be of interest to other utilities considering new aggregation programs. Across the cases, we identified five categories of challenges relating to distributed energy resource management system (DERMS) development and implementation, customer acquisition, DER deployment, communication with DERs, and DER performance. In some cases, the utilities faced similar issues within a given category. For example, three of the five utilities had challenges with developing DERMS software to control a disparate set of DER technologies and participants. In other cases, the utilities’ experiences and challenges varied substantially. For example, Green Mountain Power, PG&E, and SCE found that DERs performed as expected, whereas the other two utilities found that the performance of different technologies varied.
Based on this common set of challenges and the perspectives from interviewees, we offer considerations for next-generation DER aggregation programs, including the following:
• To scale DER aggregation programs, utilities likely need to develop a DERMS and find cost-effective pathways to integrate DERs with different communication protocols.
• To secure customer participation, utilities should consider how DER aggregation will impact or align with existing DER incentive structures so that potential customers see a net benefit of participation.
• To reduce deployment-related delays, utilities could work proactively with AHJs to resolve permitting issues particularly for batteries.
• To secure anticipated grid services from deployed DERs, utilities likely need to pursue methods to increase communication reliability between the utility, aggregators, and/or individual DERs.
• To more accurately predict DER performance, utilities should evaluate how technology mix, operation protocols, and consumer behavior may impact individual DER performance…
Despite the unique context of each DER aggregation project, the pilots shared common challenges relating to DERMS development and implementation, customer acquisition, DER deployment, communicating with DERs, and DER performance. This section summarizes those challenges, the key lessons learned, and considerations for resolving these issues in the next generation of programs.
Table 3 summarizes the challenges faced by each of the utilities in relation to five categories. In some cases, the utilities faced similar issues within a given category. For example, three of the five utilities had challenges with developing DERMS software to control a disparate set of DER technologies and participants. In other cases, the utilities’ experiences and challenges varied substantially. For example, Green Mountain Power, PG&E, and SCE found that DERs performed as expected, whereas the other two utilities found that the performance of different technologies varied. Though these challenges can be interrelated, the remainder of this section discusses each challenge separately with perspectives from interviewees on how utilities might resolve each challenge.
To scale DER aggregation programs, utilities likely need to develop a DERMS and find cost-effective pathways to integrate DERs with different communication protocols. In all five cases, the utility, or its partners, developed a temporary or permanent DERMS to aggregate and deploy DERs. A DERMS likely will be essential to scale aggregation programs given the need to develop situational awareness of DER performance, the ability to securely and reliably interact with those DERs, and optimally dispatch them to provide grid services autonomously. The cases demonstrate that developing a DERMS can be challenging, but Green Mountain Power and PG&E’s approach to phase in DERMS functionality may help mitigate some of these challenges. This approach could serve as a model for other utilities. Interviewees also offered some perspective on how utilities might address integration challenges, particularly when developing a program that includes DER aggregators. Ensuring the DERMS can interact with aggregator software adds complexity, costs, and cybersecurity concerns (Rodriguez Labastida and Asmus 2018). Interviewees suggested that aggregator software platforms are just emerging, so technology innovation may streamline the time and resources needed to develop, test, and integrate these systems. Several interviewees suggested that the use of open communication standards may also help developers and aggregators integrate disparate DER technologies regardless of their make and model. The IEEE 2030.5 Standard for Smart Energy Profile Application Protocol is one effort to standardize communication protocols between the utility, aggregators, and individual DERs. Widespread adoption of similar open or standardized communication protocols may reduce the time and resources needed to develop and implement a DER aggregation program.
To secure customer participation, utilities should consider how DER aggregation will impact or align with existing DER incentive structures so that potential customers see a net benefit of participation. The MECO and PG&E cases both demonstrate the potential challenges with acquiring customers. Location, availability, and concentration of DERs are essential considerations for assessing the role these resources can play in providing grid value. Utilities need to balance these considerations and related value, with existing DER incentive structures to gauge potential customer interest in DER aggregation. MECO’s project partner, Hitachi, and PG&E faced customer-acquisition challenges. In the case of Hitachi, these challenges stemmed in part from the poor economic value proposition of PV and batteries compared with net-metered PV on MECO’s grid. As a result, utilities may need to seek alternative rate or other compensation structures to foster customer interest in DER aggregation programs. If customers do not see a reasonable return, they will be unlikely to participate. Interviewees also suggested that utilities should adequately explain program design and requirements before signing up customers to ensure that the customers make informed choices. Other utilities might wish to evaluate these factors prior to program adoption and then adjust their customer-acquisition process or program design accordingly.
To reduce deployment-related delays, utilities could work proactively with AHJs to resolve permitting issues particularly for batteries. Hitachi did not deploy enough residential batteries to test this deployment challenge in the MECO pilot, while SMUD and PG&E faced AHJ permitting challenges. Battery permitting uncertainty can cause delays and additional costs as was the case for PG&E and SMUD. Though not evident in our cases, these challenges can also result in project termination. For example, Consolidated Edison’s (Con Ed’s) Clean Virtual Power Plant in New York was terminated after the utility could not secure approval from the New York City Department of Buildings and the New York Fire Department to install residential batteries. Con Ed remained committed to this concept and conducted a battery storage safety analysis to provide permitting authorities with more information on safe battery siting in New York City (Con Ed 2017). In addition, the New York State Energy Research and Development Authority (NYSERDA) has offered $8.1 million in technical assistance to support the development of energy storage permitting guidelines, model codes, and standards to streamline future permitting costs (NYSERDA 2016, NYSERDA 2018). These initiatives are similar to ongoing efforts to streamline PV permitting process and may help other utilities that are considering incorporating batteries in their DER aggregation programs. 19 Even so, utilities and other DER aggregation partners may wish to discuss battery storage deployment and permitting requirements with AHJs early in the process to address and resolve permitting issues.
To secure anticipated grid services from deployed DERs, utilities likely need to pursue methods to increase communication reliability between the utility, aggregators, and/or individual DERs. Four utilities faced communication challenges with deployed DERs. For example, Green Mountain Power encountered issues with faulty equipment, limited communication, and the need to reset equipment manually (Donalds, Galbraith, and OlinskyPaul 2018). In addition, interviewees from this case suggested that failures in the communication chain between the individual DER, the aggregator, and the utility also impacted DER performance. Ongoing efforts to streamline communication chains could help reduce the probability of failure. PG&E, SMUD and SCE also had issues with the data they received in response from DERs, even with consistent lines of communication as demonstrated by SMUD and SCE. Utilities may want to consider these types of challenges when determining which DERs to include in their programs and when developing data-communication requirements for DERs to receive compensation for grid services.
To more accurately predict DER performance, utilities should evaluate how technology mix, operation protocols, and consumer behavior may impact individual DER performance. Hitachi found that EV capacity varied depending on the time of day, which was due in part to the mobile nature of EVs and the MECO project’s focus on residential charging (Irie 2017). In comparison, SMUD found that smart thermostats in its program offered inconsistent demand response (ADM Associates Inc. 2014). The utility could not confirm what caused this variation, given the lack of data, and said more research was necessary to understand how reliable these resources could be (ADM Associates Inc. 2014). Thus, utilities may want to consider how DER technology performance may vary in their programs and adjust program design as necessary.