Energy Storage in the Western US Interconnection: Current Adoption, Trends and Modeling Challenges

By Konstantinos Oikonomou, Masood Parvania, and Vijay Satyal

Electric energy storage (EES) represents one of the major components of grid modernization that provides various services for the enhancement of the reliability and the resiliency of the power grid. In the U.S., the potential benefits of EES have attracted the interest of policy makers and regulators at both the state and federal levels. As of June 2016, EES capacity in the U.S. was over 23 GW, out of which, 94 percent was pumped hydro systems and the remaining 6 percent was of the electrochemical type (lithium–ion, Nickel cadmium, sodium sulfur batteries), the electro mechanical type (compressed air, flywheels) and thermal storage units. In the western interconnection (WI), EES is identified as an asset critical to the improvement of the reliability of the system and as a complementary technology in the attempts to increase penetrations of variable renewable energy resources. More specifically, the additional intra-hour balancing capacity (from generators) that will be required to accommodate the variability of an expected 14.4 GW of additional wind integration between 2011 and 2020 is estimated at 1.53 GW. However, if these additional balancing services are to be provided by new energy storage plants, instead, the energy capacity would be about 0.58 GWh, or storage capable of providing electricity at the rated power capacity for about 20 minutes.

Although, EES has demonstrated several reliability benefits for the bulk power systems, a number of barriers raise serious concerns. In detail, these barriers prevent (i) investors to capitalize on opportunities related to EES, (ii) electricity coordinators to fully evaluate EES impacts on system adequacy and reserves planning, and, (iii) local governments to assess EES contribution on the state renewable portfolio standards (RPS) and goals. These barriers are identified below as modeling, institutional and technology barriers.

1) Modeling Barriers: Modeling barriers are associated with the lack of software tools capable to fully evaluate EES impacts on system adequacy, reserves planning, and system stability. The main modeling barriers and their potential solution are presented below:

  • EES resources are well suited to provide grid services at finer time scales, due to their quick ramping capabilities. However, existing production cost models cannot capture this fine time resolution and, usually, underestimate the benefits and use of EES resources to address intra-hour or continuous-time grid variations. Although some models can simulate finer resolutions, they are still limited to the 5-minute optimization horizon, which undervalues the use of energy storage to address second-to-second and minute-to-minute generation and load variability.
    Potential Solution: Advancement in continuous-time resource scheduling models present a novel approach that can optimally schedule the continuous-time generation and ramping trajectories of the generating units and EES technologies.
  • The majority of the production cost models cannot capture the capacity value or cost effectiveness of building new storage resources, given assumptions about future electricity demand, reserves requirements, fuel prices, technology cost and performance, and policy and regulatory frameworks.
    Potential solution: The value of system capacity needs to be calculated separately via a capacity expansion model and combined with a production cost model to produce a more complete value of a storage device. Particularly, capacity expansion scenario outputs can be used to define the infrastructure for the production cost models and provide additional information in order to examine the impacts of power sector policies on the generation, storage and transmission capacity mix in the mid-to long-term periods (10-30 years).
  • Production cost models cannot adequately account for the total market value of EES for providing multiple services to the grid. Usually, the models can only capture the operational potential value for providing, (i) energy (electric energy time-shift), and (ii) ancillary services (regulation up/down, spinning, non-spinning and supplemental reserves). Consequently, utilities, developers and investors are unable to estimate the revenue stream of the EES facilities. As a result, the models will not materialize the EES values.
    Potential Solution: New tools need to be developed that can capture multiple benefits from storage units. These tools should be able to allocate storage power and energy to the service it values most at a specific time of the simulation period. In addition, these tools should be able to capture avoided cost benefits for generation and/or transmission and distribution lines capacity expansion, and a utility customer’s reduced cost for energy and demand charges.

2) Institutional Barriers: Institutional barriers are associated with the inability of EES developers, investors and utilities to quantify EES revenues, and to monetize EES resources operational value for their multiple grid services. The institutional barriers that prevent EES deployment and their potential solution are summarized below:

  • Regulatory restrictions prevent EES to obtain revenues for providing services under multiple classifications. Under current procedures, utilities cannot obtain cost-based rate recovery for transmission functions and, simultaneously, market based recovery for providing ancillary services, despite providing two independent services. Doing so would require approval from FERC and likely the public utility commission of the state in which the asset is located.
    Potential Solution: New regulatory policies need to be established, capable to form a transparent guide for EES participation rights and access to provide such diverse system services.
  • While in some organized markets, there is a compensation mechanism for storage resources when procuring energy or ancillary services, in “non-organized” market environments determining the value of these services can be a challenge.
    Potential Solution: Several utilities that operate under a “non-organized” market have started exploring alternative ways for identifying and quantifying EES benefits in their planning and procurement process. Washington state utilities have recently proposed a proxy value for EES based on the rates for those services in established ancillary service markets.
  • The lack of markets for voltage support, black start, and frequency response in most regions presents another barrier to the deployment of EES. Potential Solution: Some ISOs has recently proposed markets for these services. This would allow the market to drive the least cost technologies to meet requirements, whether or not this includes energy storage resources. Such market initiatives are still under discussion.

3) Technology Barriers: Despite the promising future of EES from a technical perspective, a main implementation barrier for EES is the high capital investment cost of available technologies. Achieving reduced EES costs requires attention to factors such as life-cycle cost and performance (efficiency, energy density, life cycle).

The landscape of the WI is changing with an increase in retirement of many base-load (coal-fired and nuclear) plants, resulting in a higher proportion of variable renewable energy resources in the WI energy portfolio. The utilization of EES has the potential to address this uncertainty by providing fast-responding services within small-time intervals (<5min, 10 min, 30min) and to act as a complementary technology for increasing penetrations of variable renewable energy resources in the WI. Though several reliability and resiliency opportunities exist for EES deployment, modeling, technology and institutional barriers prevent this potential. Therefore, the specific modeling and institutional recommendations for better treatment of EES in the case of the US WI are:

  • Developing advanced production cost models that can evaluate EES ramping in intra-hour resolutions or even in continuous-time trajectories.
  • Linking capacity expansion and production cost models, in order to allow a more concise assessment of the technical, regional, policy and operational aspects of storage deployment.
  • Engaging more actively with energy storage associations, utilities and other stakeholders to be informed of latest industry developments around EES modeling and reliability impact assessments. Doing so, would also allow for potential partnerships and/or refinement of future reliability assessment based study programs at western electricity coordinating council (WECC).
  • Encouraging WECC to monitor studies undertaken by balancing authorities and entities in the WI. This would significantly assist in maintaining a realistic understanding of the benefits and challenges of EES integration efforts.
For a downloadable copy of the June 2017 eNewsletterwhich includes this article, please visit the IEEE Smart Grid Resource Center




konstantinos oikonomou

Konstantinos Oikonomou is currently working toward a Ph.D. in electrical engineering from the University of Utah. His research interests include power system planning and reliability analysis as well as operation and planning of interdependent critical infrastructures, water-energy systems, and modeling and integration of distributed renewable energy resources. He received a B.Sc. in physics from the University of Patras in 2009, an M.Sc. degree in energy engineering from the University of Durham in 2011, and a second M.Sc. in electrical engineering from George Washington University in 2014. 

masood parvania

Masood Parvania is an assistant professor and the director of the U-Smart lab in the Department of Electrical and Computer Engineering at the University of Utah. Dr. Parvania is an associate editor of the IEEE Transactions on Smart Grid. He is Chair of the IEEE Power and Energy Society (PES) Utah Chapter, Chair of the IEEE PES Task Force on Reliability Impacts of Demand Response Integration, and Secretary of the IEEE PES Reliability, Risk and Probability Application (RRPA) Subcommittee. His research interests include the operation and planning of power and energy systems, modeling and integration of distributed energy resources, as well as sustainable renewable energy integration..

vijay satyal2

Vijay Satyal is the Senior Policy Analyst at Western Electricity Coordinating Council (WECC) and an adjunct faculty with the School of Public Policy at Oregon State University. In his prior role with Oregon Dept. of Energy, Dr. Satyal conducted policy analyses of renewable energy technologies (performance and transmission planning), review of tax credit programs, integrated resource planning efforts of Oregon utilities, and served on climate change-related state legislative initiatives. He received a master's degree in economics from the University of Bombay, a second master's in resource economics from Michigan State University, and a PhD in environmental sciences with an interdisciplinary (socio-economic-ecological) focus on public policy/regulatory impacts to natural resources from Oregon State University. 

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