Optimal design of wind energy generation in electricity distribution network based on technical-economic parameters

In order to satisfy electricity customers and avoid some environmental constraints and problems, the transition to renewable energy sources has become increasingly important given their advantages and benefits, such as reducing pollution and improving the reliability of the targeted distribution system. In this paper, several state-of-the-art metaheuristic optimisation algorithms are used to investigate the optimal setting and sizing of wind turbines (WTs) when connected to the electricity distribution network (EDN). The selected algorithms were implemented to optimise and minimise a multi-objective function (MOF) considered as the sum of the techno-economic parameters of total active power loss (TAPL), total voltage deviation (TVD) and investment cost of the WTG (ICWTG) when the daily uncertainties and variations of the load-source powers are taken into account. The effectiveness of the selected algorithms was validated on the two standard test systems IEEE 33-bus and 69-bus. The simulation results in this paper showed the superiority of the Gorilla Troops Optimizer (GTO) algorithm compared to other new metaheuristic optimisation algorithms in terms of providing the best optimised results. Accordingly, the GTO algorithm showed excellent effectiveness and robustness in determining the optimal setting and sizing of the WTG units in EDN. Thus, the daily active power losses were reduced to 1,415 MWh for the first test system and 1,072 MWh for the second test system, while also improving the bus voltage profiles and favouring the investment costs of the installed WTG units, all with daily uncertainties in terms of load demand and WTG power variations