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Abstract
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The inherent intermittency and variability of load demand and renewable energy resources present an ongoing problem for power scheduling of microgrids. To address the operational challenges associated with uncertainty of load and energy resources, this paper proposed a stochastic based optimal day ahead power scheduling of microgrids considering economic and reliability aspects. The proposed problem formulation minimizes the expected operational cost, the pollutants emission cost, power losses cost and energy not supplied (ENS) cost of the microgrids while accommodating the intermittent nature of load demand and renewable power generation. The system uncertainties are considered using a set of scenarios and a scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Grey wolf optimization (GWO) algorithm is implemented to minimize the objective function as an optimization algorithm. Case studies are performed on a modified IEEE 33-bus distribution network. The simulation results demonstrate the effectiveness and accuracy of the proposed stochastic based microgrid power scheduling model.
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