基于字典优化法和ε-约束法的双目标热电调度

Double-objective heat and power dispatch based on lexicographic optimization method and ε-constraint technique

随着国家对环境保护的日益重视,热电联产区域调度时除了节约运营成本外,减少污染物排放也越来越受重视。对这种经济和环境的双目标最小化问题,采用传统ε-约束法求解时不能有效优化收益矩阵,确保得到非支配解。对此,本文提出采用字典优化法,根据ε-约束法迭代优化的初始过程中形成的ε期望值逐步识别字典的冗余区域,通过更新收益矩阵的对应元素,在已缩小的搜索范围内进一步搜索,提高了搜索效率。引入松弛变量将ε-子问题转化为线性规划标准形式,并采用原始-对偶内点法求解,提高了全局搜索能力。同时采用模糊决策确定满意解。最后采用本文方法和权重系数调节法对2个案例进行仿真分析,结果表明,本文方法从帕雷托解的质量和计算速度方面均优于权重系数调节法。

With the increasing attentions to environmental protection in China, during regional dispatch for thermal and power cogeneration, besides saving the operation costs, pollutant emission reduction has also drawn more and more attentions. Against this dual objective minimization problem of economy and environment, using the conventional 6-constraint method can not effectively optimize the revenue matrix, so the non-dominated solution can not be ensured. To solve this problem, this paper proposes to adopt the lexicographic optimization method, it updates the income matrix gradually based on the e expectations formed in the previous optimization process so as to reduce the search scope. By introducing slack variables, the c sub-problems are transformed into a standard linear programming model, and the primal-dual interior point algorithm is used to solve it to improve the global search ability. In addition, the fuzzy decision technique is used to provide a quantitative solution for determining satisfactory solutions. Finally, two examples are analyzed by the proposed method and the weighting coefficient adjustment method. The results verifies that, both the quality of pareto solution and the computational speed of the proposed method are better.