Multi-objective-based economic and emission dispatch with integration of wind energy sources using different optimization algorithms - Lalhmachhuana, R.; Deb, Subhasish; Datta, Subir; Singh, Ksh. Robert; Cali, Umit; Ustun, Taha Selim (Frontiers in Energy Research, 2024)
In this work, a study of economic and emission dispatch issues based on multi-objective optimization is solved, and generation cost and emission are reduced utilizing multi-objective optimization techniques. This optimization is carried out in an IEEE-30 bus system with and without integration of wind energy source, with equality and inequality constraints. Equality constraint is described as the power balance constraint, which stipulates that to have an optimal solution, the generated power needs to be adequate to satisfy the load demand plus losses. The inequality constraints are a collection of limitations for the active power generation, the reactive power generation, the generator bus voltage and the load bus voltage. To track hourly load demand, a daily load profile is established using the bus system. The generating cost and emission in the system are optimized using Multi-Objective Particle Swarm Optimization and Multi-Objective Ant-Lion Optimization approaches. In order to determine the goals' minimum values, a fuzzy min-max technique is applied. The values that have been minimized are then compared to determine how well wind energy integration has reduced the generation cost and emissions. Two case studies are performed in this work. For Case 1, the total generation cost and emission using MOPSO has lower total generation cost with a difference of 42.763, while, MOALO has the lower emission with a difference of 157.337 Tons. For Case 2, with implementation of wind energy, MOPSO has lower total generation cost with a difference of 51.678 and lower emission with a difference of 459.446 Tons.