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.

Summary 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.

This paper presents a study and design of a complete stand-alone photovoltaic (PV) system for providing the electrical loads in an emergency health clinic according to their energy requirements. Typical energy consumption daily profiles for the four seasons are assumed. The PV system is optimally sized to be an optimal economic system. Homer software is used as the sizing and optimization tool to determine the size and specifications of photovoltaic system components, system cost and estimation of corresponding produced electrical energy. The results show that the sizing of PV stand-alone system depends on the load data, the solar resource data and the investment cost of system components. Also it is found that providing electricity to the emergency health clinic using PV system is very beneficial and economical, especially considering the decreasing prices of PV systems and their increasing efficiencies and reliability. They have also the advantage of maintaining a clean environment.

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The intermittent nature of photovoltaic (PV) generation causes the voltage to fluctuate and may lead to instability, especially, in case of high penetration. In this paper, a methodology is proposed to control the reactive power generation of PV-inverters. The objective is to mitigate the voltage fluctuations at the point of common coupling (PCC) resulted from increasing or decreasing the active power output of PV plants which is dependent on solar radiation level. The generic PV-inverter models developed and recommended by the Renewable Energy Modeling Task Force (REMTF) of the Western Electricity Coordinating Council (WECC) is used to analyze the effect of high PV penetration on the dynamic voltage stability of distribution networks. Then, the tested distribution network with the embedded PV plants is modeled and simulated using PSS/E software. Levels of control that are built-in PV-inverters are tested in the case of normal operation and during disturbances. Comparison results show that the most suitable control methodology in case of disturbances and after fault clearance is the local voltage control. While the plant voltage control with coordinated V/Q control is the most preferable control methodology during normal operation.