An integrated optimal operating strategy for a grid-connected AC microgrid under load and renewable generation uncertainty considering demand response

The challenge of a modern energy system is to be reliable, robust, easily accessible, economically viable, and environment-friendly. This paper addresses the above issue by proposing a novel integrated optimal energy management scheme for a grid-connected AC microgrid. The objectives of the energy management scheme are to minimize the cost of operation and reduce the emission. A group of measures like incentive-based demand response (DR) program economic-emission load dispatch, optimal battery scheduling, and network reconfiguration is simultaneously implemented in the energy management scheme to enhance the steady-state performance of the microgrid. Uncertainties are modeled using a stochastic approach in this work. The bi-objective optimization is carried out in the fuzzy domain employing the fuzzy max-min satisfaction criterion. Further, the incentive value of the DR program is optimized, and a sensitivity analysis is carried out to investigate the impact of the incentive value on the operating cost. Simulation studies on a thirty-three node test system demonstrate that the operating cost can be reduced by 18.90%, and emission by 45.44% for the given test system. If both cost and emission are to be reduced simultaneously, then the operating cost and emission are reduced by 9.08% and 34.85%, respectively.

Automated summary

This paper proposes an integrated optimal energy management scheme for AC microgrids, which aims to enhance the steady-state performance of the microgrid by minimizing the operating cost and reducing emissions through various measures. Uncertainties are modeled using a stochastic approach, and bi-objective optimization is carried out in the fuzzy domain.