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Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation
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Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation
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Journal Article
Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation
2019
Overview
The potential availability of renewable energy sources is unquestionable and the government is setting steep targets for renewable energy usage. Renewable‐based DGs, reduce dependence on fossil fuels, mitigate global climate change, ensure energy security, and reduce emissions of CO2 and other greenhouse gases. This study addresses microgrid system analysis with hybrid energy sources and reconfiguration simultaneously for efficient operation of the system. Microgrid zones are formulated categorically with the existing distribution system. In this study, wind, solar and small hydro‐based DGs are considered. Uncertainties of renewable power generation and load are also taken care in the optimization problem. A multi‐objective optimisation method proposed in this paper for optimal integration of renewable‐based DGs and reconfiguration of the network to minimise power loss and maximise annual cost savings. Optimal location and sizes of DG units are determined using gravitational search algorithm and general algebraic modelling system respectively. Optimal reconfiguration of the microgrid system is obtained using genetic algorithm. Simulation results are obtained for the IEEE 33‐bus system and compared with existing methods as available in the literature. Furthermore, this study has been carried out with a 24‐hr time‐varying distribution system. The simulation results show the efficiency and accuracy of the proposed technique.
Publisher
The Institution of Engineering and Technology,John Wiley & Sons, Inc,Wiley
Subject
/ B0260 Optimisation techniques
/ B8110B Power system management, operation and economics
/ B8120K Distributed power generation
/ C7410B Power engineering computing
/ CO2
/ DG units
/ distributed power generation
/ general algebraic modelling system
/ global climate change mitigation
/ gravitational search algorithm
/ maximise annual cost savings
/ multiobjective optimisation method
/ optimal network reconfiguration
/ power distribution economics
/ realistic time varying load model
/ renewable-based distribution generations
/ time varying distribution system
/ Turbines
