Multi-Objective Planning of Community Energy Storage Systems Under Uncertainty
K. B. J. Anuradha, Jose Iria, Chathurika P. Mediwaththe

TL;DR
This paper presents a multi-objective stochastic optimization framework for planning community energy storage systems under uncertainty, comparing different energy trading schemes to improve equity among prosumers and providers.
Contribution
It introduces a novel multi-objective stochastic optimization model incorporating scenario reduction for community energy storage planning under various trading schemes.
Findings
Trading at the average grid price benefits prosumers and providers more equitably.
The scenario reduction improves computational tractability.
The proposed framework effectively balances costs and benefits under uncertainty.
Abstract
This paper evaluates how the planning of a community energy storage (CES) system under different energy trading schemes (ETSs) can benefit low voltage (LV) prosumers and the CES provider equitably. First, we consider an ETS where the CES provider trades energy with prosumers at the average grid energy trading price, second, an ETS where the CES provider trades energy at a higher price than the grid energy trading price, and third, an ETS where the CES provider trades energy at a lower price than the grid energy trading price. To this end, we present a multi-objective stochastic optimization framework to minimize the investment and annual operating costs of the CES provider and annual operating costs of prosumers, taking into account the uncertainties of real and reactive energy consumption and photovoltaic (PV) generation of prosumers. The uncertainties are modeled using the normal…
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Taxonomy
TopicsSmart Grid Energy Management · Electric Vehicles and Infrastructure · Microgrid Control and Optimization
Methodsk-Means Clustering
