Fast and accurate power dispatch using a relaxed genetic algorithm and a local gradient technique

Abstract

A relaxed hybrid genetic algorithm (RHGA) and gradient technique (GT) is proposed to economically allocate power generation in a fast, accurate, and relaxed manner. The proposed hybrid scheme is constructed in such a way that a GA performs a base-level search, makes rapid decisions to direct the local GT to quickly climb the potential hill. The proposed method further ensures the dispatch quality as well as speed by allowing a loose match between the power generation and the load demand at the base search, and compensates for any mismatch at the beginning of the local search. Consequently, a GA is able to deliver equal effort to the search for the least cost and power balance without the risk of attaining infeasible solutions. The effectiveness of the proposed RHGA is verified on two test cases. The first is the static economic dispatch (SED) on a three-generator system, for which the near optimal solution is found within a comparable short time. The second is the dynamic economic dispatch (DED) problem on the practical Northern Ireland Electricity (NIE) system, which has a total of 25 generator units. The simulation results obtained are very encouraging with regard to the computational time and production cost.