Multiobjective generation scheduling using fuzzy optimal search technique

A novel multiobjective optimisation technique for dynamic generation scheduling in an interconnected system is presented. In contrast to existing generator scheduling methods, the proposed approach treats economy, security, emission and reliability as competing objectives for optimal dispatch of the local system generating units. Fuzzy logic techniques are incorporated in a knowledge based system to solve this difficult multicriteria problem involving multiple conflicting objectives. Using fuzzy logic, the multiobjective problem is transformed into one with a single objective and is solved by maximising this function. A pattern recognition technique is used for assessing the stability of the interconnected system at each load level, and for evaluating the security transfer limits between neighbouring systems. Simulations carried out on a moderately sized interconnected system, containing 19 generating units in the local system, show that this technique is effective in determining the optimal dispatch of generation units, ensuring an appropriate balance between generation and predicted load demand and at the same time improving the stability of the interconnected system. Comparison of results with a classical generation scheduling method shows that use of the proposed fuzzy approach, which includes a larger number of constraints and objectives, results in a much shorter time.<>