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

Electronics

Randolph E. Collins¹  Harish Pulluri²  Chandan Kumar Shiva³  Vedik Basetti³  Ritesh Kumar³  Shriram S. Rangarajan³  Tomonobu Senjyu⁴ 

[1] Department of Electrical and Computer Engineering, Clemson University, Clemson, SC 29634, USA;Department of Electrical and Electronics Engineering, Anurag University, Hyderabad 500088, India;Department of Electrical and Electronics Engineering, SR University, Warangal 506371, India;Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan;

关键词: political optimizer;    economic load dispatch;    valve-point effect;    quasi-oppositional learning;   

DOI  :  10.3390/electronics10212596

来源: DOAJ

【 摘 要 】

In the present paper, a novel meta-heuristic algorithm, namely quasi-oppositional search-based 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.

【 授权许可】

Unknown