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Available onlineKeywords: Micro-gird Renewable energy resources Multi-objective mathematical programming Short term environmental/economical scheduling Normal boundary intersection method a b s t r a c t In recent years due to the decreasing fossil fuel reserves and the increasing social stress, complex power networks have no other choices except to seek for alternative energy sources to eliminate the environmental issues caused by the traditional power systems. Thus, the scheduling of energy sources in a complex Micro-Grid (MG) comprising Micro Turbine (MT), Photo Voltaic (PV), Fuel Cell (FC), battery units and Wind Turbine (WT) has been investigated in this paper. Furthermore, a multi-objective framework is presented to simultaneously handle the two objective functions including minimization of total operation cost and minimization of emission. In this regard, Normal Boundary intersection (NBI) technique is employed to solve the proposed multi-objective problem and generate the Pareto set. Besides, a fuzzy satisfying method is used for decision making process. Afterward, the results obtained from the presented method are compared to the ones derived from other methods. Finally, it is verified that the proposed solution method results in better solutions for operation cost, emission and the execution time.

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The microgrid (MG) is described as an electrical network of small modular distributed generation, energy storage devices and controllable loads. In order to maximize the output of solar arrays, maximum power point tracking (MPPT) technique is used by artificial neural network (ANN), and also, control of turbine output power in high wind speeds is proposed using pitch angle control technic by fuzzy logic. To track the maximum power point (MPP) in the photovoltaic (PV), the proposed ANN is trained by the genetic algorithm (GA). In other word, the data are optimized by GA, and then these optimum values are used in ANN. The simulation results show that the ANN‐GA in comparison with the conventional algorithms with high accuracy can track the peak power point under different insolation conditions and meet the load demand with less fluctuation around the MPP; also it can increase convergence speed to achieve MPP. Moreover, pitch angle controller based on fuzzy logic with wind speed and active power as inputs that have faster responses which leads to have flatter power curves enhances the dynamic responses of wind turbine. The models are developed and applied in Matlab/Simulink. Copyright © 2015 John Wiley & Sons, Ltd.