A Multi-Objective Planning and Scheduling Framework for Community Energy Storage Systems in Low Voltage Distribution Networks

TL;DR

This paper introduces a multi-objective optimization framework for planning and scheduling community energy storage systems in low voltage networks with solar PV, reducing power loss and trading costs effectively.

Contribution

It develops a novel multi-objective optimization approach that considers both planning and operational scheduling of CES in LV networks with PV integration.

Findings

Reduces real power loss by nearly 29%.

Decreases energy trading costs by about 16%.

Outperforms models focusing only on CES scheduling.

Abstract

This paper presents a methodology for optimizing the planning and scheduling aspects of a community energy storage (CES) system in the presence of solar photovoltaic (SPV) power in low voltage (LV) distribution networks. To this end, we develop a multi-objective optimization framework that minimizes the real power loss, the energy trading cost of LV customers and the CES provider with the grid, and the investment cost for the CES. Distribution network limits including the voltage constraint are also taken into account by combining the optimization problem with a linearized power flow model. Simulations for the proposed optimization framework with real power consumption and SPV generation data of the customers, highlight both real power loss and energy trading cost with the grid are reduced compared with the case without a CES by nearly 29% and 16%, respectively. Moreover, a case study justifies our methodology is competent in attaining the three objectives better than the optimization models which optimize only the CES scheduling.