• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.551-559
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• 2016

The present trend of increasing the penetration levels of Distributed Generator (DG) in the distribution network has made the issue of Islanding crucial for the reliable operation of the network. The islanding, if not detected early may lead to the collapse of the system as it can drive the distribution system to the cascaded failure. In this paper, an extensive study of the effect of DG placement and sizing is performed by dividing the system into different zones to obtain a reduced effect of islanding. The siting and sizing of DG is carried out to improve the overall voltage profile or/and reduction in active power loss using two stage Genetic Algorithm (GA). In the first stage a basic knockout selection is considered and the best population is taken for next stage, where roulette selection for crossover and mutation is performed for optimal placement and sizing of DGs. The effect of the islanding, due to load variations is reduced by optimal siting and sizing of DG. The effectiveness of the proposed scheme is tested on the IEEE 33 and 69 radial bus systems and the results obtained are promising.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.804-811
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• 2015

The presence of responsive loads in the promising active distribution networks (ADNs) would definitely affect the power system problems such as distributed generations (DGs) studies. Hence, an optimal procedure is proposed herein which takes into account the simultaneous placement of DGs and smart meters (SMs) in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Seeking to power loss minimization, the optimization procedure is tackled with genetic algorithm (GA) and tested thoroughly on 69-bus distribution test system. Different scenarios including variations in the number of DG units, adaptive power factor (APF) mode for DGs to support reactive power, and individual or simultaneous placing of DGs and SMs have been established and interrogated in depth. The obtained results certify the considerable effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the lowest value of power losses as well.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1240-1247
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• 2014

The applications of Distributed Generation (DG) in a smart distribution grid environment are widely employed especially for power balancing and supporting demand responses. Using these applications can have both positive and negative impacts on the distribution system. The sizing and location of their installations are the issues that should be taken into consideration to gain the maximum benefit from them when considering the economic aspects. This paper presents an application of the Bat Algorithm (BA) for the optimal sizing and siting of DG in a smart distribution power system in order to maximize the Benefit to Cost Ratio (BCR), subjected to system constraints including real and reactive power generation, line and transformer loading, voltage profile, energy losses, fault level as well as DG operating limits. To demonstrate the effectiveness of the proposed methodology and the impact of considering economic issues on DG placement, a simplify 9-bus radial distribution system of the Provincial Electricity Authority of Thailand (PEA) is selected for the computer simulation to explore the benefit of the optimal DG placement and the performance of the proposed approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2157-2164
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• 2010

Microgrid is generally defined as cluster of small distributed generators, energy storages and loads. Through monitoring and coordinated control, microgrid can provide various benefits such as reduction of energy cost, peak shaving and power quality improvement. In design stage of microgrid, system dynamic simulation is necessary for optimizing of sizing and siting of DER(distributed energy resources). As number of the system components increases, simulation time will be longer. This problem can restrict optimal design. So we used simplified modeling on energy sources and average switching model on power converters to reduce simulation time. The effectiveness of this method is verified by applying to prototype microgrid system, which is consist of photovoltaic, wind power, diesel engine generators, battery energy storage system and loads installed in laboratory. Simulation by Matlab/Simulink and measurements on prototype microgrid show that the proposed method can reduce simulation time not sacrificing dynamic characteristics.