Developement of Optimal Planning Method Using a Genetic Algorithm for District Heating and Cooling Plants with Heat Storage Tanks

Recently, district heating and cooling (DHC) plants with heat storage tanks have become common. But the optimization of the operational planning for these systems requires much computation time. In this paper, an optimal planning method for operation of these systems using a genetic algorithm (GA) was proposed. The proposed method has three new characteristics. Firstly, the optimization of DHC plant operation schedule to minimize both running costs and the dynamic load variation can be obtained. Secondly, it makes the search for optimal value more effective to use operator's know-how. Lastly, the probabilities of “crossover” and “mutation” can be changed dynamically to avoid converging to a local minimum value. Simulations demonstrated that the proposed method gives ten times faster computation time of dynamic programing needed to obtain the minimum operation cost and small load variation.