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

Posted: May 21, 2014 - 15:00 / ESA / Reports

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.

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 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.