Survey of Modeling Capabilities and Needs for the Stationary Energy Storage Industry

Transcription

1 Survey of Modeling Capabilities and Needs for the Stationary Energy Storage Industry Prepared for: Energy Storage Association th Street, NW Suite 500 Washington, DC energystorage.org Prepared by: Navigant Consulting, Inc th Street, NW Suite 700 Washington, DC May 2014

2 Table of Contents Acknowledgements... iv Executive Summary... v Study Objectives and Value... v Study Findings... vi System Planning... vi Real-Time Grid Operation... vii Energy Storage Systems... vii Additional Gaps... viii 1 Introduction Study Overview Approach Characterize Existing Models and Tools Define Stakeholder Needs Identify Gaps Characterization of Existing Models and Tools System Planning Portfolio Planning Energy Production Cost Simulation Transmission System Planning Distribution System Modeling Real-Time Grid Operation Energy Storage Systems Definition of Stakeholder Needs Identification of Gaps System Planning Portfolio Planning Energy Production Cost Simulation Transmission System Planning Distribution System Planning Real-Time Grid Operation Energy Storage Systems Additional Gaps and Improvements Energy Storage System Performance Renewable Plant Data Engineering Standards Page i

3 Appendix A Contributing Companies/Entities Appendix B Descriptions of Software Products B.1 Portfolio Planning B.2 Energy Production Cost Simulation B.3 Transmission System Planning B.4 Distribution System Planning B.5 Real-Time Grid Operation B.6 Energy Storage Systems Page ii

4 List of Figures and Tables Figures: Figure 1. Study Objectives... 1 Figure 2. Categories of Models and Tools Surveyed... 4 Figure 3. North American Interconnections Tables: Table 1. Modeling Tools Reviewed by Category... 2 Table 2. Portfolio Planning Models... 5 Table 3. Production Cost Models... 7 Table 4. Transmission Planning Models Table 5. Distribution Planning Models Matrix Table 6. Primary Real Time Grid Operation Vendors Table 7. Energy Storage-Specific Applications Matrix Table 8. Energy Storage Industry Stakeholder and Analysis Needs Page iii

5 Acknowledgements Navigant would like to thank the Energy Storage Association (ESA) for funding this important study. In addition, we would like to express our thanks to the ESA Tools Task Force for their insight, guidance, and review of this study. Members of the Task Force included:» Eva Gardow, FirstEnergy Service Company» Udi Helman, Independent consultant» Praveen Kathpal, AES Energy Storage» Ben Kaun, Electric Power Research Institute» Jim McDowall, Saft» Ali Nourai, DNV GL We also would like to acknowledge the input we received from the individuals who participated in our survey. A full list of contributing organizations is presented in Appendix A. Page iv

6 Executive Summary Study Objectives and Value Energy Storage (ES) can be used to enhance and support the electric distribution and transmission network, and support the integration and operation of intermittent electric generating resources. The first pumped storage hydroelectric project in the United States was developed nearly a century ago. Compressed air energy storage (CAES) plants have been operated commercially for a few decades. Thermal storage integrated with concentrating solar plants has been operated at utility-scale for about eight years. Ice storage is also being used to shift electrical demand and consumption to off-peak periods in commercial deployments. More recently, battery and flywheel based systems have begun commercial operations on the grid to provide ancillary services, and have met performance requirements. Building on this commercial experience as well as technical studies and demonstration projects on these and other storage technologies, such as flow batteries and ultracapacitors, interest in the grid support and transformative potential for these technologies has led to a renewed interest in both distributed and bulk scale ES. An example of this trend is the first U.S. ES mandate resulting from the 2013 California Public Utility Commission (CPUC) Decision requiring the state s three major utilities (Pacific Gas & Electric, Southern California Edison, and San Diego Gas & Electric) to procure a total of 1,325 megawatts of ES capacity by A significant driver for ES is the increasing deployment of solar photovoltaic and wind resources, where the rapid response of ES can mitigate output variability. Even more important is the flexible operating range of ES, ramping from full charge to full discharge during the increasingly severe late afternoon system ramp as the output of solar resources wanes and loads increase. The increasing interest in ES highlights the urgent need to properly value, integrate, and operate ES systems. However, given the limited role that ES historically has played in the electric system, many of the traditional utility planning models were not designed to fully assess ES alternatives. For ES to become widely and cost-effectively adopted, it is critical that stakeholders have the tools and models needed to make informed ES decisions. The Energy Storage Association (ESA) recognized this need and contracted with Navigant Consulting, Inc. (Navigant) to assess the current ES modeling capabilities in the industry. Based on Navigant s investigation, while there has been substantial model development related to ES, there are still a number of key gaps, including: 1) incomplete representation of ES characteristics in many models; 2) stand-alone ES planning tools that are not fully integrated with other utility planning models; 3) a lack of standardization among tools used to evaluate ES; and 4) limits on the data available on ES technologies. Each of these shortcomings will need to be addressed to improve the analysis of ES applications and their associated costs and benefits. This study describes each of the models currently used in the industry to evaluate ES technologies. This study does not evaluate the quality or performance of the specific models and tools but rather describes their current capabilities and future development plans, as expressed by the software developers surveyed and other industry experts. The results will help ES industry stakeholders assess whether a Page v

7 particular model can fulfill their needs. The study also highlights shortcomings in current ES modeling to potentially spur the development of new features and software packages to meet the growing demand. Study Findings Outside of large pumped hydroelectric facilities, ES is an emerging technology and has historically had a limited role in the operation of the bulk power grid. As a result, the widely used system planning models have generally neglected to account for the complex and variable operations of ES systems. Most planning software programs do not concentrate on the unique modeling required to represent ES accurately. The few models that do have the flexibility to incorporate the various characteristics of an ES system are complex and require very long computational runtimes. Importantly, the need to appropriately represent ES technologies and systems coincides with the need to model rapidly changing system operations and reliability due to increasing penetration of variable wind and solar generation, which in itself has presented challenges. Since ES can aid in the reliable operation of generation, transmission, and distribution, particularly under the conditions emerging with growing interconnection of variable energy technologies, further developments are necessary in the existing utility procurement and planning models to properly represent the value of ES. Additionally, the real-time operation of the grid requires software that will fully incorporate ES system operating parameters and dispatch units accordingly. Finally, ES-specific tools are needed to assess and inform the optimal ES system size and control algorithms to maximize economic, reliability, and environmental benefits. The following sections provide an overview of the different categories of planning and operations and their relevance to ES. System Planning Portfolio planning models are used to determine the optimal set of least-cost resources to meet the needs of a utility system or region. Currently, conventional commercially available portfolio planning models are unable to fully co-optimize between the energy and ancillary service markets, where the operational capabilities of ES are particularly valuable. Additionally, these models do not account for the ability of energy storage to minimize ramping constraints compared to traditional technologies. Energy production cost simulation models are used to perform long-term assessments of system and market operations, including forecasts of generation, wholesale electric costs, and locational marginal prices. Energy production cost simulation models incorporate significant system operational detail, but currently have difficulty capturing the comprehensive value of ES systems. Moreover, due to long runtimes, there may be limits to the number of production cost simulations used to evaluate alternative portfolios, including those with different specifications on storage. These models are primarily intended to simulate the hourly level of system operations assuming perfect foresight. On the other hand, ES Page vi

8 provides significant benefits within very short time-frames and by flexibly responding to unexpected occurrences. While sub-hourly dispatch is available or is being developed in many of these models, the capability to model ES operations at the 5-minute level and in response to regulation signals is still in the early stages. Some vendors have developed system models that can simulate frequency response, and use these in conjunction with production cost models, but for limited time-frames. For those models that do have sub-hourly dispatch capability and options for creating specific ES unit parameters, long modeling run times become an issue. Despite longer run times, there are a number of storage valuation studies that conduct sufficient numbers of storage scenarios using production simulation to inform longterm ES planning purposes on the grid by extrapolating representative day s results. Further progress is still needed. Transmission system planning models are used to assess large transmission networks. These software packages help evaluate the operations and reliability of the transmission network under various system conditions. Transmission system planning models have the ability to incorporate ES and quantify the associated contribution to system reliability. However, doing so often requires the user to create ESspecific individualized models, which can be a time-consuming process. It is recommended that the transmission system planning software vendors invest in creating and including ES-specific models in their annual updates. Distribution system models are often used by utilities for short- and long-term distribution planning. The largest gap in modeling ES on distribution systems is that there isn t a tool that can handle optimum dispatch plans for different applications. It s also important to note that the necessary inputs are not available within the model itself and therefore, ES components often have to be designed outside of the model. Also, tools to evaluate the impacts of transmission support applications on distribution circuits are not yet available. Real-Time Grid Operation Real-time grid operation includes software used by independent system operators/regional transmission organizations (ISOs/RTOs) and utilities to develop day-ahead and hour-ahead schedules and market prices for energy and ancillary services, and to operate the grid and markets in real time. Increasingly, conventional grid operational tools and market solutions have been supplemented with tools to forecast ancillary service and ramping needs due to variable energy resources. Many of these tools will affect ES operations, although their details are often not available to ES developers. With respect to transmission level operations, energy management systems (EMS) and market management systems (MMS) may need to be modified to accommodate ES in applications such as frequency regulation. These modifications are achievable and have already been implemented in certain ISOs/RTOs. The industry should press for additional specifications and transparency on these tools. While utility distribution management systems (DMS) offer a potential platform for integrating the results from various system planning software, advanced DMS systems are still evolving to incorporate these capabilities. Energy Storage Systems ES system tools are developed for specific industry needs such as estimating and demonstrating the value of ES, calculating optimal system size, controlling ES systems, and optimizing ES system Page vii

9 performance. These types of models allow for much greater detail in operational specifications, but use fixed historical or simulated data on market prices and system conditions as inputs. The major shortcomings with these tools are the lack of available data on ES system operations and the proprietary nature of many of the existing tools. Shared knowledge would allow developers to create more robust tools that could then be customized for specific needs. An additional linkage is between simulated data on future system conditions to be used as inputs to these types of models, to allow for further analysis of changing system conditions. Additional Gaps The most common gap highlighted by stakeholders is the lack of a single ES tool to integrate the inputs and results of various system planning tools. While an integrated tool may not be feasible due to computational limits and complexity, a standardized approach on how to value ES using available tools is also lacking. The development of such a standardized approach would aid the proper application and value-assessment of ES when compared to traditional resources. Page viii