Multi-objective optimization;
Combined heat and power production;
Mixed integer linear programming;
Two phase method;
EVOLUTIONARY ALGORITHMS;
COGENERATION SYSTEMS;
BOUND ALGORITHM;
INTEGER;
OPTIMIZATION;
DISPATCH;
MODEL;
MANAGEMENT;
SET;
D O I:
10.1016/j.ejor.2015.02.037
中图分类号:
C93 [管理学];
学科分类号:
12 ;
1201 ;
1202 ;
120202 ;
摘要:
In this paper, we deal-with the bi-objective non-convex combined heat and power (CHP) planning problem. A medium and long term planning problem decomposes into thousands of single period (hourly) subproblems and dynamic constraints can usually be ignored in this context. The hourly subproblem can be formulated as a mixed integer linear programming (MILP) model. First, an efficient two phase approach for constructing the Pareto Frontier (PF) of the hourly subproblem is presented. Then a merging algorithm is developed to approximate the PF for the multi-period planning problem. Numerical results with real CHP plants demonstrate the effectiveness and efficiency of the solution approach using the CPLEX based epsilon-constraint method as benchmark. (C) 2015 Elsevier B.V. All rights reserved.