A Review of Fuzzy-Based Residential Grid-Connected Microgrid Energy Management Strategies for Grid Power Profile Smoothing

Residential grid-connected microgrids (MG) comprising renewable generation and storing capability are constrained to grid-operator requirements which include, among others, a smooth and bounded grid power profile. These requirements attempt to mitigate a high unpredictability on the electrical power exchanged between the grid and the MG and affect the design of the MG Energy Management System (EMS). This chapter reviews several energy management strategies based on Fuzzy-Logic Controllers (FLC) designed in the last years to smooth the grid power profile of a residential grid-connected MG. Two MG power architectures are considered. Both include wind and PV solar renewable generation and non-controllable domestic electrical loads. The first architecture assumes a battery charger/inverter as the only controllable element whereas the second one also considers a thermal load as an additional controllable element. The chapter presents a fuzzy logic approach to design the control strategies of the microgrid EMS. The strategies are designed under two scenarios, the first one assuming that forecast of generation and consumption is not available and the second one using MG forecasted data. Simulation and experimental results are provided to highlight and compare the features of all the strategies in terms of their power profile smoothing capability.

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