Interactive artificial ecosystem algorithm for solving power management optimizations

• Дата: 2022
• Автори: Mahdad, B., Srairi, K.
• Формат: Стаття
• Мова: English
• Опубліковано: National Technical University "Kharkiv Polytechnic Institute" and State Institution “Institute of Technical Problems of Magnetism of the National Academy of Sciences of Ukraine” 2022
• Теми: artificial ecosystem based optimization; power management; intensification and diversification; FACTS devices; оптимізація на основі штучної екосистеми; управління енергією; інтенсифікація та диверсифікація; пристрої FACTS (гнучка система передачі змінного струму)
• Онлайн доступ: http://eie.khpi.edu.ua/article/view/255850
• Назва журналу: Electrical Engineering & Electromechanics

Introduction. Power planning and management of practical power systems considering the integration and coordination of various FACTS devices is a vital research area. Recently, several metaheuristic methods have been developed and applied to solve various optimization problems. Among these methods, an artificial ecosystem based optimization has been successfully proposed and applied to solve various industrial and planning problems. The novelty of the work consists in creating an interactive process search between diversification and intensification within the standard artificial ecosystem based optimization. The concept of the introduced variant is based on creating dynamic interaction between production operator and consumer operator during search process. Purpose. This paper introduces an interactive artificial ecosystem based optimization to solve with accuracy the multi objective power management optimization problems. Methods. The solution of the problem was carried out using MATLAB program and the developed package is based on combining the proposed metaheuristic method and the power flow tool based Newton-Raphson algorithm. Results. Obtained results confirmed that the proposed optimizer tool may be suitable to solve individually and simultaneously various objective functions such as the total fuel cost, the power losses and the voltage deviation. Practical value. The efficiency of the proposed variant in terms of solution quality and convergence behavior has been validated on two practical electric test systems: the IEEE-30-bus, and the IEEE-57-bus. A statistical comparative study with critical review is elaborated and intensively compared to various recent metaheuristic techniques confirm the competitive aspect and particularity of the proposed optimizer tool in solving with accuracy the power management considering various objective functions.