Abstract
Abstract In this paper, an online power management (OPM) problem is proposed using measured/short term forecasted data. It improves the cost and dynamic performance of microgrid along with the consideration of interval uncertainties in renewable energy and loads. Additional options of grid power trade and demand response (DR) are provided for operational cost reduction, consumer participation and enhanced network performance. A combination of stochastic weight tradeoff particle swarm optimization (SWT-PSO) and interval arithmetic (IA) is proposed to analyze the effects of interval uncertainties of nodal power injections (due to renewable energy sources (RES) and loads) on microgrid cost and power flow variables. The effectiveness of the proposed approach is investigated by adding different power balancing resources one by one, to the residential feeder of CIGRE LV benchmark microgrid. The results are found to be improved in terms of reduction in fuel and emission costs, improved nodal voltages and network feasible OPF solution in interval forms corresponding to system volatilities. Moreover, settling time of online dispatch is reduced, thereby improving the dynamic response of distributed energy resources (DERs). In addition, the paper justifies the use of RES, DR, grid power trade (over islanded mode) and SWT-PSO (over priority listing).
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