Profit Based Unit Commitment Problems with Emission Constraints Using Swarm Intelligence Technique

Unit Commitment (UC) problem is a significant optimizing task in daily operational planning of power systems which can be mathematically expressed as a large scale nonlinear mixed integer minimization problem for which there is no particular solution technique. The solution for the problem can be gained only by complete enumeration, often at a prohibitively computation time requirement for realistic power systems. This optimization involves many constraints such as system power and reserve, unit generation limit, unit minimum ON/OFF duration and ramping constraints. In this paper, the particle swarm optimization is proposed to solve the Profit Based Unit Commitment problem below deregulated environment with emission limitation. The bi-objective function optimization problem is expressed as a maximization of the Generation Companies profit and a minimization of the emission output of the thermal units, while all of the constrains should be fulfilled. This work, considers the new softer demand constraint to allocate fixed and transitional cost to the scheduled hours. The IEEE 10 unit 39 bus system with 24h data is engaged as the input for simulation using MATLAB software. From the results obtained, it is observed that the proposed system achieves maximum profit and minimum emission level with less computational time compared to other techniques.