A Solution to Unit Commitment Problem via Dynamic Programming and Particle Swarm Optimization

The optimization problem while committing the units is minimizing the entire production cost, at the same time meeting the demand and fulfilling the equality and inequality limits. In order to supply adequate power to the consumers in a cost-effective and secured way the commitment of thermal units is the best option available. The commitment of generating units is done depending upon the prediction of upcoming demand. For getting a way out to the unit commitment problem there are numerous conventional and advanced programming practices used. For solving the deterministic problem the conventional dynamic programming algorithm is employed. In this paper DP is used to solve the unit commitment problem. In this paper Particle swarm optimization technique is used which is population based global searching optimization technique to solve the unit commitment problem, for committing the units optimally. It is arrived from the exploration on the bird and fish flocking movement behavior. For the straightforward implementation of the algorithm it is extensively used and rapidly developed and few particles are needed to be attuned. An algorithm was developed to attain a way out to the unit commitment problem using Particle Swarm Optimization technique. The effectiveness of the algorithm was tested on two test systems. The first system comprising of three units and the second system is an IEEE 30-bus system and the attained results using the two methods are compared for total operating cost.