Title :
Multi-objective daily operation management of distribution network considering fuel cell power plants
Author :
Niknam, Taher ; Meymand, H.Z. ; Mojarrad, H.D. ; Aghaei, Jamshid
Author_Institution :
Dept. of Electr. & Electron. Eng., Shiraz Univ. of Technol., Shiraz, Iran
fDate :
9/1/2011 12:00:00 AM
Abstract :
Fuel cells are environmentally clean, have low emission of oxides of nitrogen and sulfur and, at the same time, they can operate with a very low level of noise. In addition, they can provide energy in a controlled way with higher efficiency compared to conventional power plants. This study presents an efficient multi-objective new fuzzy self adaptive particle swarm optimisation evolutionary algorithm to solve the multi-objective optimal operation management considering fuel cell power plants in the distribution network. The objective functions of the problem are to decrease the total electrical energy losses, the total electrical energy cost, the total pollutant emission and deviation of bus voltages. The proposed algorithm is tested on a real distribution test feeder and the results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal non-dominated solutions.
Keywords :
Pareto optimisation; distribution networks; evolutionary computation; fuel cell power plants; fuzzy systems; particle swarm optimisation; Pareto-optimal nondominated solutions; bus voltages; distribution network; electrical energy cost; electrical energy losses; evolutionary algorithm; fuel cell power plants; fuzzy self adaptive system; multiobjective daily operation management; particle swarm optimisation; pollutant emission;
Journal_Title :
Renewable Power Generation, IET
DOI :
10.1049/iet-rpg.2010.0190