Abstract
The regulation of the grid voltage within operational limits becomes increasingly challenging as residential photovoltaic (PV) adoption rises. Therefore, this study proposes a method for the efficient planning of multiple community battery energy storage systems (BESS) in low voltage distribution systems embedded with high residential rooftop PV units. A bi-level optimization method based on a Neural Network Optimization Algorithm is developed to regulate the voltage in grid-connected solar PV. Since BESS characteristics are crucial for the reliable operation of the distribution networks, the objective of the bi-level optimization problem is to optimally place and operate BESS collectively at a distributed system level. The charging/discharging protocol of the batteries management system is obtained utilizing linear programming that minimizes the daily voltage signal. Simulations were carried out on a modified IEEE low voltage test feeder to examine the impact of PV integration and BESS installation on the voltage profile. Experimental results show the efficacy of the proposed method in enabling the utility to determine the optimal location, capacity, and number of BESS in the distribution system to keep the network voltage magnitude within acceptable bounds. In addition, results demonstrate that the network topology, load profiles, and amount of PV power highly influence the BESS characteristics.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
8 articles.
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