Multi-Objective Planning of Community Energy Storage Systems 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 probability density function. Then, the roulette wheel mechanism (RWM) is exploited to formulate a scenario-based stochastic program. The initial scenarios obtained from the RWM, are then reduced using the K-Means clustering algorithm, to make the problem tractable. Our experiments show that the ETS where the CES provider trades energy at the average grid energy trading price benefits prosumers and the CES provider more equitably than the other two ETSs.

Tasks

Reproductions