Optimal Configuration Design of Gas Turbine Cogeneration Plants by a MILP Decomposition Approach

Abstract

To attain the highest economic and energy saving characteristics of gas turbine cogeneration plants, it is necessary to rationally determine capacities and numbers of gas turbines and auxiliary equipment in consideration of their operational strategies corresponding to seasonal and hourly variations in energy demands. Some optimization approaches based on the mixed-integer linear programming (MILP) have been proposed to such configuration design problems of energy supply plants. However, with increases in the numbers of the equipment which must be considered as candidates as well as the periods which must be set for variations in energy demands, the optimal configuration design problems become too large-scale and complex to solve. The author has proposed a MILP decomposition approach to obtain quasi-optimal solutions of the optimal configuration design problems in reasonable computation times. However, this approach has been limited to the optimal configuration design problems where equipment capacities are treated continuously. In this paper, the MILP decomposition approach is extended to the optimal configuration design problems where equipment capacities are treated discretely. The effectiveness of this extended approach is investigated through a numerical study on a gas turbine cogeneration plant.