A fuzzy optimization-based method for integrated power system scheduling and inter-utility power transaction with uncertainties

Electric utilities face many uncertainties in their daily scheduling and inter-utility transaction operations. The effects of these uncertainties can propagate through the time horizon, significantly affecting the economics of schedules and transactions. With deregulation in the utility industry and increasing competition in the electricity market, these uncertainties should be properly managed. In this paper, system demand, reserve requirements and prices of future purchase transactions are considered as uncertain, and the integrated scheduling and transaction problem is formulated as a fuzzy mixed integer programming problem for a power system consisting of thermal units and purchase transactions. Based on the symmetric approach of fuzzy optimization and the Lagrangian relaxation technique, a fuzzy optimization-based algorithm is developed. Testing results using fuzzy simulation show that the method produces robust scheduling and transaction decisions to hedge against uncertainties.