Short term energy arbitrage in PV-battery grid-connected systems

Abstract

In this work, we show the optimization of the daily arbitrage operation of a PV-battery power generating system. Genetic algorithms (GA) metaheuristic technique is used for the optimization. A new arbitrage method is applied. An integer variable which can take one of three values (-1, 0 or 1) for each hour of the day decides the operation of the battery (charge/inactive/discharge), considering as inputs the average hourly irradiance, temperature and electricity price forecast for the day-ahead, and the state of charge (SOC) at the first hour of the day-ahead. The optimal arbitrage operation obtains the maximum net incomes, that is, incomes of selling electricity minus cost of purchasing electricity and degradation cost of the battery. The method is applied to a PV-battery power generating system near Zaragoza (Spain) for a specific day, obtaining net incomes 7% higher than using a previously published optimization method.