Particle Swarm Optimization to Solve Economic Dispatch Considering Different Iterations of Loss Coefficient

Economic Dispatch (ED), a significant optimization issue in the power system, aims to guide the outputs of all available generating units in the power system in such a way that fuel costs are minimized while still meeting system constraints. Transmission losses are a significant component and have an impact on the most efficient dispatch of generation in a broad, linked network where electricity is carried over long distances and via low density regions. A standard approach for accounting for transmission losses is to express the loss coefficients or B-coefficients from Kron's loss formula. In this work, the ED issue in power systems is resolved using a particle swarm optimization (PSO) technique while also considering the effect of different iterations of loss coefficient that most other papers do not consider in an ED solution. The generator's various nonlinear characteristics, i.e. ramp rate limits, prohibited operating zone, and non-smooth cost functions are investigated in this proposed technique for practical generator operation. The proposed technique's suitability is demonstrated for two differing iterations of loss coefficients, and the technique is juxtaposed against the Genetic Algorithm (GA) technique in terms of cost minimization and computational efficiency. Results from experiments indicate that the PSO technique proposed has the capability to obtain superior solutions to ED issues using both iterations as compared to GA. From this study, it is proven that the loss coefficient for the second iteration provides preferable ED solution as compared to the first iteration. Therefore, it is important to use accurate loss coefficient values to obtain a preferable solution for the ED issue.