Scenario-based stochastic operation management of MicroGrid including Wind, Photovoltaic, Micro-Turbine, Fuel Cell and Energy Storage Devices

In this paper, an efficient stochastic framework is proposed to investigate the effect of uncertainty on the optimal operation management of MicroGrids (MGs). The proposed stochastic framework would concurrently consider the uncertainties of load forecast error, Wind Turbine (WT) generation, Photovoltaic (PV) generation and market price. The proposed stochastic method consists of two main phases. In the first phase, by the use of Probability Distribution Function (PDF) of each uncertain variable and roulette wheel mechanism, several scenarios are generated. Now by the use of scenario reduction process, the most probable and dissimilar scenarios are selected. By means of this strategy, the stochastic problem is converted to a number of deterministic problems with different probabilities. In this regard, the Weibull and normal PDFs are utilized to model the stochastic random variables. In the second phase, a new optimization strategy based on Adaptive Modified Firefly Algorithm (AMFA) is employed to solve each of the deterministic problems generated in the first phase. The stochastic optimization problem is investigated while meeting different equality and equality constraints. In order to see the efficiency and satisfying performance of the proposed method, a typical grid-connected MG including WT/PV/Micro-Turbine/Fuel Cell and Energy Storage Devices is studied as the test system. (C) 2013 Elsevier Ltd. All rights reserved.