基于约束进化算法的热电联供经济负荷分配问题研究

项目名称： 基于约束进化算法的热电联供经济负荷分配问题研究

项目编号： No.61503299

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 吴亚丽

作者单位： 西安理工大学

项目金额： 18万元

中文摘要： 目前，热电联供系统已成为众多分布式能源系统中提高能源效率、减少温室气体排放的有效解决方案。而经济负荷分配问题的合理解决是热电联系统高效运行的前提。本项目主要研究热电联供系统的经济负荷分配问题的建模及其优化策略。进化算法虽然以其特有的隐并行性为约束优化问题提供了一种新颖的求解思路,但现有的进化算法缺乏有效的约束处理机制，忽视了种群中个体有效信息的利用。为此，本项目拟针对热电联供经济负荷分配问题的模型特点，拟将基于邻域环境的知识学习和反馈机制用于改进传统算法的搜索效率；将基于决策空间与目标空间的知识的抽取与交互用于多种约束处理机制的有效融合，设计通用的高效率的约束进化算法，完善和发展约束进化算法的理论和方法。在此基础上，为热电联供经济负荷调度问题提供较完美的解决方案。该项目的实施不仅对热电联供系统经济负荷分配问题的解决提供重要的理论基础，而且为研究通用的约束进化算法框架提供良好的思路。

中文关键词： 规划与调度；热电联供系统；约束优化；进化算法；经济负荷分配

英文摘要： At present, the Combined Heat and Power(CHP) system has become an effective solution to improve energy efficiency and reduce greenhouse gas emissions. And the economic load dispatch problem is the prerequisite to operate CHP system effectively. The modeling and optimization problems of economic load dispatch problem in CHP system is studied in this project. Although Evolutionary Algorithm (EA) provides a novel solution for constrained optimization problem because of its unique implicit parallelism, the existing evolutionary At present, the Combined Heat and Power(CHP) system has become an effective solution to improve energy efficiency and reduce greenhouse gas emissions. The economic load dispatch problem is the prerequisite to operate CHP system effectively. So the modeling and optimization problems of economic load dispatch problem in CHP system is studied in this project. Although Evolutionary Algorithm (EA) provides a novel solution for constrained optimization problem because of its unique implicit parallelism, the existing evolutionary algorithms lacks of the effective constraint handling mechanism. And it also ignores the neighborhood information in the population. So our project intends to integrate learning and feedback mechanism of neighborhood knowledge into the original evolutionary algorithms to make it more efficient. And the abstraction and interaction of the knowledge in decision space and objective space is implemented to ensemble of the constraint handling mechanisms. All this can provide an novel evolutionary algorithm for complex constrained optimization problem, especially to economic load dispatch problem in CHP system. On this basis, the current common mechanism of swarm intelligence evolutionary search algorithms is analyzed and constraint handling mechanism is studied to improve and develop the theory and methods of constrained evolutionary algorithms. The implementation of this project not only provides an important theoretical basis for solving economic load dispatch problem if CHP system, but also a good idea for the study of a common constraints evolutionary algorithm framework.

英文关键词： planning and scheduling; combined heat and power (CHP) system ;constrained optimization;evolutionary algorithm;economic dispatch