Optimal design of wind energy generation in electricity distribution network based on technical-economic parameters
AbstractTo satisfy the electricity customers and avoid some environmental constraints and issues, the transition towards renewable energy sources became more crucial, given its merits and advantages, such as mitigating pollution and enhancing the reliability of the targeted distribution system. This paper uses different recent metaheuristic optimization algorithms to address the optimal setting and sizing of Wind Turbine Generator (WTG) units when connecting to Electricity Distribution Network (EDN). The chosen algorithms have been implemented to optimize and minimize a Multiple-Objective Function (MOF), which is considered the sum of the techno-economic parameters of the Total Active Power Loss (TAPL), the Total Voltage Deviation (TVD), and the Investment Cost of WTG (ICWTG), when taking into consideration the daily uncertainties and variations of the load-sources powers. The effectiveness of the selected algorithms was validated on the two standard test systems of IEEE 33-bus and 69-bus. The simulation results in this paper revealed the superiority of the Gorilla Troops Optimizer (GTO) algorithm compared with other new metaheuristic optimization algorithms in terms of providing the best-optimized results. Accordingly, the GTO algorithm showed excellent effectiveness and robustness in identifying the optimal setting and sizing of the WTG units into EDN. Hence, mitigating the daily active power losses until 1.415 MWh for the first test system and 1.072 MWh for the second one, also improving the bus voltage profiles while providing a favourable investment cost of the installed WTG units, all simultaneously with daily uncertainties for load demand and WTG power variation.
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