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Multi-Dimensional Energy Management based on an Optimal Allocation of Hybrid Wind Turbine Distributed Generation and Battery Energy Storage System in Flexible Interconnected Distribution Network Considering Seasonal Uncertainties
* 1 , 2 , 3
1  Department of Electrical Engineering, Faculty of Technology, University of Mostaganem, Mostaganem, 27000, Algeria
2  Department of Electrical Engineering, Faculty of Technology, University of Batna 2, Batna, 05078, Algeria
3  Department of Electrical Engineering, Faculty of Engineering, Aswan University, Aswan, 81542, Egypt
Academic Editor: Nunzio Cennamo


In recent years, the incorporation of wind turbine distributed generation (WTDG) in addition to battery energy storage system (BESS) into an electrical distribution network (EDN) has grown into a beneficial solution for ensuring a satisfying balance between energy generation and consumption. The principal approaches used to locate and size multiple WTDG and BESS units inside EDS are described in this article. To optimize overall multi-objective functions, this research investigates the optimal planning of multiple hybrid WTDG and BESS units in EDN. In the first scenario, injecting active power to the EDN is accomplished by installing WTDG. In contrast, in the second scenario, hybrid WTDG and BESS units are deployed concurrently to provide the EDN, taking into consideration the seasonal uncertainty of load-source powers variation, for a reason to approach to the practical case, where there are many parameters to be optimized, considering different constraints, during the uncertain time and variable data of load and power generator. The suggested work's originality is to completely design a novel multi-objective function (MOF) based on the sum of three technical metrics of active power loss (APL), voltage deviation (VD), and overcurrent relay operating time (OTR). The proposed MOF is tested and validated on the standard IEEE 69-bus distribution network by applying a new, recently published meta-heuristic algorithm called the Light Spectrum Optimizer (LSO) algorithm. The optimized outcomes revealed that the LSO showed good behavior in minimizing each parameter included in the MOF during the year

Keywords: optimal allocation; seasonal uncertainties; wind turbine distributed generation; battery energy storage system; electrical distribution network; multi-objective functions.