The Application Of Intellegent Algorithms In Economic Dispatch

Economic dispatch is to schedule the online generator outputs such that the generation cost is minimized while satisfying all units and system's constraints. It is a typical optimization problem in a power system. Nowadays, the competition in power market is severe. It is necessary for many power plants to improve the efficiency of units and reduce the cost of generation. Economic dispatch is an efficient way to achieve the above goal. In this dissertation, we investigate three economic dispatch models whose cost functions are defined according to burning characteristic of coal. Also, the constraints of these cost functions are analyzed. Intelligent algorithms such as particle swarm optimization and differential evolution are used to optimize these models to get the optimal dispatch results. Specifically, we do the following research works in this dissertation:First, the economic dispatch problem with valve effect is considered. Since the existence of valve effect, the cost function is discontinue, nonlinear and non-differential. Such cost function is difficult to be solved using classic optimization methods. A hybrid algorithm, which combined simplex search and particle swarm optimization, is proposed to solve this problem. The hybrid algorithm inherits the global search ability of particle swarm optimization and the fast local search of simplex. It can obtain better solution with faster convergent speed.Second, we investigate the combined heat and power economic dispatch problem. The combined heat and power economic dispatch considers both the power and heat load. The dependence between power and heat makes the problem more complex to be solved. In this dissertation, a self-adjusted particle swarm optimization is proposed to solve this problem. In the proposed method, the equality constrains are handled using self adjusted scheme while the inequality constraints are handled using a penalty function method called external point method. In such a way, the feasibility of particles in the swarm is improved. The chances of finding optimal result increased.Finally, economic dispatch with multi-fuel is considered. Differential evolution is proposed to solve the economic dispatch with multi-fuel and valve effect. The obtained dispatch result is more attractive than those in existing literatures.