In this paper, a new formulation for optimizing the design of a photovoltaic (PV)-wind hybrid energy home system, incorporating a storage battery, is developed. This formulation is carried out with the purpose of arriving at a selection of the system economical components that can reliably satisfy the load demand. Genetic algorithm (GA) optimization technique is utilized to satisfy two purposes. The first is to minimize the formulated objective function, which is the total cost of the proposed hybrid system. Whereas, the second is to ensure that the load is served according to certain reliability criteria, by maintaining the loss of power supply probability (LPSP) of the system lower than a certain predetermined value. Two computer programs are designed, using MATLAB code in a two M-files, to simulate the proposed hybrid system and to formulate the optimization problem by computing the coefficients of the objective function and the constraints. Also, these two programs are utilized together with the GA tool under MATLAB software to yield the optimum PV, wind, and battery ratings. The results verified that PV-wind hybrid systems feature lower system cost compared to the cases where either PV-alone or wind-alone systems are used.

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.

Design and Economic Analysis of a Stand-Alone PV System to Electrify a Remote Area Household in Egypt

This paper proposes a solution methodology for optimal allocation and sizing of renewable based DG units in radial distribution systems. The objectives are to minimize total power losses, to minimize system's investment cost and to improve voltage stability. The multi-objective genetic optimization algorithm is used to generate the optimal Pareto front and a fuzzy decision making function is used, as a hybrid function, to obtain the best compromise solution. The proposed technique is applied to typical IEEE bus systems including 33-bus system, 69-bus system and 119-bus system. This technique is implemented using different scenarios including all possible combinations of renewable DG units; to prove the effectiveness of the proposed methodology. The effect of DG based renewable energy allocation on the most sensitive buses to collapse is also carried out considering different load models. Copyright © 2016 John Wiley & Sons, Ltd.