Operation planning of district heating and cooling plants using genetic algorithms for mixed integer programming

In recent years, an operation planning of a district heating and cooling (DHC) plant has been arousing interest as a result of development of cooling load or heat demand prediction methods for district heating and cooling systems. In this paper, we formulate an operation planning of a district heating and cooling plant as a mixed integer linear programming problem. Since the formulated problem involves hundreds of variables, we anticipate that it is difficult to strictly solve it by enumeration-based methods. Thereby, we propose an approximate solution method based on genetic algorithms for mixed integer programming problems. Furthermore, we show the feasibility and effectiveness of the proposed method by comparison with the branch-and-bound method through numerical experiments using actual plant data.