Economic Emission Load Dispatch Problem with Valve-Point Loading Using a Novel Quasi-Oppositional-Based Political Optimizer

In the present paper, a novel meta-heuristic algorithm, namely quasi-oppositional searchbased political optimizer (QOPO), is proposed to solve a non-convex single and bi-objective economic and emission load dispatch problem (EELDP). In the proposed QOPO technique, an opposite estimate candidate solution is performed simultaneously on each candidate solution of the political optimizer to find a better solution of EELDP. In the bi-objective EELDP, QOPSO is applied to simultaneously minimize fuel costs and emissions by considering various constraints such as the valve-point loading effect (VPLE) and generator limits for a generation. The effectiveness of the proposed QOPO technique has been applied on three units, six units, 10-units, 11-units, 13-units, and 40-unit systems by considering the VPLE, transmission line losses, and generator limits. The results obtained using the proposed QOPO are compared with those obtained by other techniques reported in the literature. The relative results divulge that the proposed QOPO technique has a good exploration and exploitation capability to determine the optimal global solution compared to the other methods provided in the literature without violation of any constraints and bounded limits.

Automated summary

In this paper, a novel meta-heuristic algorithm called QOPO is proposed to solve non-convex single and bi-objective economic and emission load dispatch problems. By simultaneously performing opposite estimate candidate solutions on each candidate solution, QOPO can find better solutions effectively. The results from applying QOPO on different systems and comparing with other techniques show that QOPO has good exploration and exploitation capabilities for determining optimal global solutions.