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• W3112504322 abstract "In this manuscript, a hybrid approach for energy management in grid connected MG system is proposed. The grid connected MG system has photovoltaic (PV), wind turbine (WT), micro turbine (MT), battery. The proposed hybrid approach is the consolidation of both the Gradient Boosting Decision Trees (GBDT) and Sandpiper Optimization Algorithm (SOA) and this way the proposed technique is named as GBDT-SOA. Here, at grid connected micro-grid configuration the required load demand is ever monitored by the GBDT approach. The perfect combination of the MG is optimized by SOA considering the predicted load requirement. The fuel cost including grid power hourly power variation, operation and maintenance cost of the grid connected micro-grid system is defined as the objective of the proposed technique. The constraints are power demand, renewable energy sources, state of charge of storage elements. Batteries have been used as an energy source, to stabilize and allow the renewable power system units to maintain running in a steady, stable output power. At that point, the proposed model is executed in MATLAB/Simulink work site and the performance is analyzed with existing techniques, such as BFO, SOA and SSA. The efficiency of the sources like photovoltaic, wind turbine, micro turbine, and battery using proposed technique is 95.9375%, 92.113%, 94.387% and 93.7560%." @default.
• W3112504322 created "2020-12-21" @default.
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• W3112504322 date "2020-12-18" @default.
• W3112504322 modified "2023-09-25" @default.
• W3112504322 title "A <scp>GBDT‐SOA</scp> approach for the system modelling of optimal energy management in <scp>grid‐connected</scp> micro‐grid system" @default.
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• W3112504322 doi "https://doi.org/10.1002/er.6270" @default.
• W3112504322 hasPublicationYear "2020" @default.
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