The optimal design of renewable-based distributed generations (DGs) is a challenging issue in order to maximise their benefits and to overcome power quality problems. Therefore, this paper proposes a methodology for optimal allocation and sizing of renewable DG units to minimise total power losses over radial distribution systems. The planning problem is formulated as a single objective nonlinear mixed integer-constrained optimisation problem and is solved by using the augmented Lagrangian genetic algorithm (ALGA) by combining the objective function and the nonlinear constraints. In that case, the ALGA solves a sequence of sub-problems where the objective function penalises the constraints violation in order to obtain the best solution. The proposed technique is applied to IEEE radial test systems including 33-bus, 69-bus and 119-bus and is implemented with different scenarios including all possible combinations and various types of renewable DG units to prove the effectiveness of the proposed methodology.
The main objective of this work is to design an optimal—efficient economic power renewable energy system that feeds the required electric load of a small scale brackish reverse osmosis desalination unit and a tourism motel located in Hurghada, Egypt. Four renewable energy power systems are presented in this paper to select the most optimum one of them. These suggested renewable energy systems are PV-wind hybrid system, stand-alone wind system, stand-alone photovoltaic system and PV-wind-fuel cell hybrid system. The sizing, optimization and economic estimation of the proposed systems were performed using HOMER software. HOMER solves the optimization problem to minimize the global cost and provides the optimum wind turbine, PV, battery and fuel cell ratings. In addition, a comparison between the four different suggested power system configurations is illustrated in details. PV-wind hybrid system realized the lowest net present cost and levelized cost of energy. Also, this system was able to provide energy approximately all the day. The battery state of charge varies between 83% and 99% and it was found that, the PV-wind hybrid system is more suitable than the others for the selected site and the suggested electrical load
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