Capacity value of energy storage in distribution networks. (August 2018)

• Record Type: Journal Article
• Authors: Konstantelos, I.; Strbac, G.
• Is Part Of: Journal of energy storage. Volume 18(2018)
• Page Start: 389
• Page End: 401
• Publication Date: 2018-08
• Subjects: Capacity credit -- Expected Energy Not Served (EENS) -- Equivalent Load Carrying Capability (ELCC) -- Energy storage -- Monte Carlo methods -- Power system security; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2018.06.002
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: Capacity markets are uneven playing fields that ignore energy storage. A novel Monte Carlo method for calculating ELCC of energy storage is presented. Energy storage is shown to be fundamentally different to conventional assets. Beyond storage size, network reliability and demand shape are important factors. Development of new network standards considering these effects is a high priority. Abstract: Security of supply in electricity distribution networks has been traditionally delivered by conventional assets such as transformers and circuits to supply energy to consumers. Although non-network solutions, such as energy storage (ES), can also be used to provide security of supply by carrying out peak shaving and maintaining supply for the duration of a network outage, present network design standards do not provide a framework for quantifying their security contribution and corresponding capacity value. Given the fundamentally different operating principles of ES, it is imperative to develop novel methodologies for assessing its contribution to security of supply and enable a level playing field to be established for future network planning. To this end, a novel probabilistic methodology based on chronological Monte Carlo simulations is developed for computing the Effective Load Carrying Capability (ELCC) of an energy storage plant. Substantial computational speed-up is achieved through event-based modelling and decomposing between energy and power constraints. The paper undertakes, for the first time, the in-depth analysis of key factors that can affect ES security contribution; plant and network outage frequency and duration, network redundancy level, demand shape, islanding operation capability and ES availability. ES capacity value is shown to decrease in networks with an unreliable connection to the grid; time to restore supply is shown to be more important that frequency of faults. Capacity value increases in cases of peaky demand profiles, while the ability to operate in islanded conditions is shown to be a critical factor. These findings highlight the need for sophisticated network design standards. The proposed methodology enables planners to consider ES solutions and allows network and non-network assets to compete on an equal basis for security provision.