The TM-EPSO for Solving the Unit Commitment Planning in the Day-ahead Power System

This paper simulates the unit commitment planning and ancillary services in the day-ahead power market of IEEE power system. The unit commitment of power and ancillary services to safe operation of the system planning for Power, Automatic Generation Control (AGC), Real-time Spinning Reserve (RSR) and Supplemental Reserve (SR). This thesis proposed the application of Taguchi Method (TM) for the discretization rule with Enhanced Particle Swarm Optimization (EPSO) to avoid the equality and Inequality of constraint, which can quickly reach the optimal solution with a better performance and accuracy of unit commitment problem for day-ahead power market. Using TM-EPSO algorithm to solve unit commitment and economic dispatch problem which can quickly reach the optimal solution and accuracy for day-ahead power system.