Evolutionary computation based wind energy integrated multi-objective optimal reactive power dispatch and economic load dispatch problem

The study explores power loss and voltage fluctuations in transmission networks, integrating them with the economic load dispatch problem (ELD) to create a new multi-objective optimization framework, aiming to minimize these issues while reducing generation costs. The multi-objective function combines three goals: minimizing ELD-related generation costs, power loss, and total voltage deviation (TVD) associated with optimal reactive power dispatch (ORPD). The framework also includes a renewable energy source (RES) optimally positioned to assess its impact on the system and the specific objectives of the multi-objective (MO)-ELD-ORPD problem. The variability of wind energy is considered, with optimal wind power output determined using the Weibull distribution function (WPDF). The analysis is conducted for the IEEE 30 bus system using the JAYA algorithm, while a fuzzy-based Pareto optimality method identifies the best solutions. Additionally, a special case for the larger IEEE 118 bus system is examined, accounting for uncertain power contributions from photovoltaic (PV) and wind sources, using a realistic RES model based on Srinagar, India. The JAYA algorithm has successfully provided optimal solutions for the MO-ELD-ORPD, resulting in significant reductions in generation costs, power losses, and TVD compared to other evaluated algorithms. Utilizing overestimated wind power led to decreases of approximately 4.97 %, 23.7 %, and 31.38 % in generation costs, power losses, and TVD, respectively, in the IEEE 30 bus system. Additionally, incorporating PV and wind energy in the IEEE 118 bus system significantly improved the proposed case study results compared to scenarios without RES, thus validating the effectiveness of this method.