Operational planning of district heating and cooling plants through genetic algorithms for mixed 0–1 linear programming

A district heating and cooling system supplies cold water and/or steam produced in the corresponding district heating and cooling plant to each of facilities in a certain district. In recent years, the operational planning of district heating and cooling plants has been arousing interest as a result of development of cooling load prediction methods for district heating and cooling systems. In this paper, we formulate operational planning problems of district heating and cooling plants as mixed 0–1 linear programming problems, which involve hundreds of variables in real instances. Realizing that it is difficult to obtain exact optimal solutions to the formulated problems, an approximate solution method using genetic algorithms for mixed 0–1 linear programming is proposed. The comparative numerical experiments with the branch-and-bound method using an operational planning problem of an actual district heating and cooling plant demonstrate the feasibility and efficiency of the proposed method.