Best Compromised Schedule for Multi-Objective Unit Commitment Problems

The paper attempts to develop a methodology to obtain Best Compromised Schedule (BCS) of Multi-Objective Unit Commitment (UC) Problem. The UC Problem is formulated to minimize both the fuel cost and Emission. The traditional weight method may not offer equal significance to both the Fuel Cost and Emission. The proposed methodology was a normalized objective function with a view of providing equal significance to both the objectives there by obtaining BCS. The solution methodology use the recently suggested Teaching Learning Based Optimization Algorithms (TLBO) and is tested on various test system ranging upto 100 units. The results on six tests system have clearly illustrated that the proposed method is better than weight method. The performance can be improved by combining the algorithms with Classical Legrangian Relaxations Method.