Optimum community energy storage system for demand load shifting

Parra, David, Norman, Stuart A., Walker, Gavin S. and Gillott, Mark (2016) Optimum community energy storage system for demand load shifting. Applied Energy, 174 . pp. 130-143. ISSN 0306-2619

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Community energy storage (CES) is becoming an attractive technological option to facilitate the use of distributed renewable energy generation, manage demand loads and decarbonise the residential sector. There is strong interest in understanding the techno-economic benefits of using CES systems, which energy storage technology is more suitable and the optimum CES size. In this study, the performance including equivalent full cycles and round trip efficiency of lead-acid (PbA) and lithium-ion (Li-ion) batteries performing demand load shifting are quantified as a function of the size of the community using simulation-based optimisation. Two different retail tariffs are compared: a time-of-use tariff (Economy 7) and a real-time-pricing tariff including four periods based on the electricity prices on the wholesale market. Additionally, the economic benefits are quantified when projected to two different years: 2020 and a hypothetical zero carbon year.

The findings indicate that the optimum PbA capacity was approximately twice the optimum Li-ion capacity in the case of the real-time-pricing tariff and around 1.6 times for Economy 7 for any community size except a single home. The levelised cost followed a negative logarithmic trend while the internal rate of return followed a positive logarithmic trend as a function of the size of the community. PbA technology reduced the levelised cost down to 0.14 £/kW h when projected to the year 2020 for the retail tariff Economy 7. CES systems were sized according to the demand load and this approximated the performance of PbA and Li-ion batteries, the capital cost per unit energy storage (kW h) of the latter assumed to be the double.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/800875
Keywords: Community energy storage ; Load-shifting ; Battery ; Retail tariff ; Optimisation
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
Identification Number: https://doi.org/10.1016/j.apenergy.2016.04.082
Depositing User: Eprints, Support
Date Deposited: 22 Mar 2018 15:18
Last Modified: 04 May 2020 18:01
URI: https://eprints.nottingham.ac.uk/id/eprint/50611

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