부산대학교 도서관

This paper presents a technique for determining the optimal sizing of a hybrid solar photovoltaic (PV) and battery energy storage (BES) system for grid-connected commercial buildings. The objective is to minimize the total net present cost (NPC), which includes the costs of the PV-BES system and electricity expenses. To achieve this, a rule-based energy management system with peak-shaving is implemented using the particle swarm optimization algorithm. The optimization process takes into account actual annual data on solar insolation, air temperature, load consumption, electricity net energy metering (NEM) prices, and the limitation of PV power exporting to the grid. The proposed technique is applied to the configuration of PV-BES systems in Malaysian commercial buildings. The optimization results are validated through uncertainty analysis using ten years of real data. A realistic cash flow analysis is presented, showing the customer's annual payments throughout the project's lifetime. The study focuses on a case study of a grid-connected commercial building (Fakulti Kejuruteraan Elektrik - FKE-2) at Universiti Teknikal Malaysia (UTeM) in Melaka. The results demonstrate reductions of 12.33% in the cost of electricity (COE), 22.62% in annual energy consumption, and 15.85% in peak demand. Furthermore, the proposed optimization technique is implemented and discussed in other states of Malaysia for comparison purposes.