GA-BASED ENERGY MANAGEMENT OPTIMIZATION FOR GRID-CONNECTED PHOTOVOLTAIC SYSTEM WITHOUT BATTERY STORAGE
Published: 29 May 2015
Abstract: This paper presents genetic algorithm (GA) based optimization of energy management for grid connected photovoltaic (PV) systems without battery storage. The major objective of this work is to minimize energy cost by maximizing objective function of GA considering both energy consumption and generation. In objective function calculation, PV module output power obtained by model of PV modules and previous power recordings from the PV system were employed. In the system, some electrical appliances and lights are in the energy consumption side and photovoltaic energy source connected to the grid is in the energy generation side. A simulation study was implemented to obtain energy cost savings using GA optimization in a commercial building. Due to the cost of the batteries, PV system is implemented without battery storage. Therefore, by adapting fluctuating PV energy generation with the time-flexible loads, an effort was aimed to develop a smart-grid strategy.
Keywords: energy management, pv system, genetic algorithms, optimization, load scheduling
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