Optimal energy management of residential PV/HESS using evolutionary fuzzy control

The adoption of residential photovoltaic power generators combined with energy storage system can reduce the energy dependency of individual households while alleviating the impact of intermittent solar energy on the electric power grid. However, to maximize the benefits, energy in such systems must be carefully managed. The first step towards development of such energy management system, described in our previous work, is determination of the optimal power flows that reflects the current and future solar energy availability and household load, as well as the state of the energy storage system. This paper builds on the optimal power flows to develop an advanced energy management system in form of a fuzzy rule base system. The time series of the optimal flows, determined using linear programming, are used to determine the parameters of a Takagi-Sugeno fuzzy controller through differential evolution. The resulting system can be implemented to control power flows in other systems composed of photovoltaic generation and energy storage. The results confirm the operational and economic benefits of using the optimal operational strategy, while allowing its in-depth analysis through the evolved fuzzy rule base.