Operation planning of district heating and cooling plants through genetic algorithms for nonlinear 0–1 programming

In recent years, the operation 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 an operation planning problem of a district heating and cooling plant as a nonlinear 0–1 programming problem. Realizing that there does not exist an efficient exact solution method and the problem involves hundreds of variables, we propose an approximate solution method using genetic algorithms for the formulated nonlinear 0–1 programming problem. Furthermore, we investigate the feasibility and effectiveness of the proposed method for an operation planning problem of an actual district heating and cooling plant.