Capturing the Impact of Storage and Other Flexible Technologies on Electric System Planning

Hale, Elaine¹  Stoll, Brady¹  Mai, Trieu¹ 

[1] National Renewable Energy Lab. (NREL), Golden, CO (United States)

关键词: power systems;    power system planning;    flexibility;    storage;    demand response;   

DOI  :  10.2172/1253712
RP-ID  :  NREL/TP--6A20-65726
PID  :  OSTI ID: 1253712

美国|英语

来源: SciTech Connect

【 摘 要 】

Power systems of the future are likely to require additional flexibility. This has been well studied from an operational perspective, but has been more difficult to incorporate into capacity expansion models (CEMs) that study investment decisions on the decadal scale. There are two primary reasons for this. First, the necessary input data, including cost and resource projections, for flexibility options like demand response and storage are significantly uncertain. Second, it is computationally difficult to represent both investment and operational decisions in detail, the latter being necessary to properly value system flexibility, in CEMs for realistically sized systems. In this work, we extend a particular CEM, NREL's Resource Planning Model (RPM), to address the latter issue by better representing variable generation impacts on operations, and then adding two flexible technologies to RPM's suite of investment decisions: interruptible load and utility-scale storage. This work does not develop full suites of input data for these technologies, but is rather methodological and exploratory in nature. We thus exercise these new investment decisions in the context of exploring price points and value streams needed for significant deployment in the Western Interconnection by 2030. Our study of interruptible load finds significant variation by location, year, and overall system conditions. Some locations find no system need for interruptible load even with low costs, while others build the most expensive resources offered. System needs can include planning reserve capacity needs to ensure resource adequacy, but there are also particular cases in which spinning reserve requirements drive deployment. Utility-scale storage is found to require deep cost reductions to achieve wide deployment and is found to be more valuable in some locations with greater renewable deployment. Differences between more solar- and wind-reliant regions are also found: Storage technologies with lower energy capacities are deployed to support solar deployment, and higher energy capacity technologies support wind. Finally, we identify potential future research and areas of improvement to build on this initial analysis.