Abstract
Abstract This paper investigates the effects of uncertain renewable energy and loads on optimizing profit and cost in a microgrid power market. The optimal power scheduling problem is solved using interval arithmetic backward forward sweep (IA-BFS) and particle swarm optimization with time varying acceleration coefficients (PSO-TVAC) based optimal power flow (OPF). The effectiveness of the problem and the method is verified by studying the deviations in dispatch of conventional sources, operational cost and overall profit in residential feeder of the CIGRE LV benchmark microgrid with load curtailment, grid trade and wind, solar & conventional energy sources.
Published Version
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