Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation. Issue 2 (20th February 2019)

• Record Type: Journal Article
• Authors: Murty, Vallem Veera Venkata Satya Narayana; Kumar, Ashwani
• Is Part Of: IET smart grid. Volume 2:Issue 2(2019)
• Page Start: 192
• Page End: 202
• Publication Date: 2019-02-20
• Subjects: distribution networks -- renewable energy sources -- distributed power generation -- genetic algorithms -- power generation economics -- power distribution economics -- power engineering computing; DG units -- general algebraic modelling system -- optimal network reconfiguration -- IEEE 33‐bus test system -- optimal DG integration -- hybrid optimisation -- renewable energy sources -- renewable energy usage -- renewable‐based distribution generations -- fossil fuels -- energy security -- greenhouse gases -- microgrid system analysis -- hybrid energy sources -- microgrid zones -- small hydro‐based DGs -- renewable power generation -- optimisation problem -- multiobjective optimisation method -- optimal integration -- renewable‐based DGs -- power loss -- maximise annual cost savings -- global climate change mitigation -- distribution system -- solar‐based DG -- realistic time varying load model -- hydro‐based DG -- gravitational search algorithm -- algebraic modelling system -- time varying distribution system -- CO2; B0260 Optimisation techniques -- B8110B Power system management, operation and economics -- C7410B Power engineering computing -- B8120K Distributed power generation; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2018.0146
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : 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.