Perfectly Convergent Particle Swarm Optimization for Solving Combined Economic Emission Dispatch Problems with and without Valve Loading Effects

The bulk of power is produced by carbon-fuelled thermal power stations, which discharge emissions like SO2, CO2, and NOx further into environment. Academics began concentrating their research work on many-objective load allocation. In order to resolve combined economic and multiple emissions dispatch scenarios with max-max price penalty component, this research introduces perfectly convergent particle swarm optimization (PCPSO) for addressing using quadratic functions, while considering the implications of emissions. Implementing this method on three different standard test systems, like the IEEE six-committed test unit system, ten generating test system, and forty generating real test system, and comparing the outcomes with other bio inspired algorithms, for the evaluation of this algorithm’s effectiveness. To do this, we created a software in the MATLAB 2015a environment on hp lab-top with 4GB RAM. This technique has enhanced search tools with excellent convergence characteristics, optimizing the quadratic cost and quadratic emissions functions at diverse power demands with minimal transmission line losses. Various practical constraints are taken into account, like limits of ramp rate, restricted operating zone(s), power balancing restriction, and limits of committed system. Transmission losses taken into account when considering a multi - fuel system. This algorithm is quick, reliable, and efficient, and it requires less time to solve non-convex problems with excellent efficiency.