Polar Bear Optimization Algorithm deployed for Multi-Area Economic Dispatch incorporating Tie-Line Constraint

• Published in: 2020 International Conference on Engineering and Emerging Technologies (ICEET) pp. 1 - 6
• Main Authors: Ikram, Faiza, Ahmad, Aftab, Haq, Syed Sadam ul, Majeed, Ayesha, Nawaz, Tooba
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.02.2020
• Subjects: Costs; Dynamic Population Control; Heuristic algorithms; Multi-Area Economic Dispatch; Polar Bear Optimization; Programming; Propagation losses; Robustness; Sociology; Statistical analysis; Tie-Line Power; Transmission Losses
• ISBN: 1728145791; 9781728145792
• ISSN: 2409-2983
• DOI: 10.1109/ICEET48479.2020.9048223

Power system consists of large dispersed generating units, resulting in many dis-continuity and non-linearity problems. This paper emphasizes on one of the key operational optimization problem "Multi-Area Economic Dispatch (MAED)" and address the remedy using a very rigorous technique known as Polar Bear Optimization Algorithm (PBOA). MAED's main objective is to reduce the total fuel cost by evaluating the optimum dispatch strategy of generating machine in each area by justifying their predicted demand loads. The system and operational constraints reflected in the proposed approach are defined namely as area power balance, tie-line power sharing capacity, generation operating boundaries and as well as transmission line losses. The main advantage of employing PBOA is its feature of balancing the search agent size by kill and growth mechanism simply known as dynamic population control. The performance and robustness of the proposed algorithm is assessed by implementing it on the IEEE standard test system of 2 Area-6 units with fuel cost convex in nature. The computational results and comparative appraisal with other available literature methods dictate the strength and effectiveness of PBOA over others.