| 引用本文: | 孟安波,李专.采用多目标纵横交叉算法的电力系统动态环境经济调度[J].电力系统保护与控制,2016,44(2):109-115. |
| MENG Anbo,LI Zhuan.Dynamic environmental economic dispatch of power system adopting multi-objective crisscross optimization algorithm[J].Power System Protection and Control,2016,44(2):109-115 |
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| 摘要: |
| 针对带非线性约束的电力系统动态环境经济调度问题，提出一种多目标纵横交叉算法。对动态调度中燃料费用和污染排放两个相互约束、冲突的目标同时进行优化。求解过程中，结合非约束支配策略，提出一种双交叉机制，增强粒子穿越非可行区域的能力，使得生成的帕累托最优解落在可行区域内。通过边缘探索，增强算法的全局搜索能力。同时，采用外部存档集合储存非劣解，并通过拥挤度对比，保持非劣解的多样性。最后，采用模糊决策理论获得最优折中解。对10机电力系统的仿真结果验证了所提方法的有效性与优越性。 |
| 关键词: 动态环境经济调度 多目标纵横交叉算法 双交叉机制 边缘探索 帕累托最优 多目标优化 |
| DOI：10.7667/j.issn.1674-3415.2016.02.015 |
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| Dynamic environmental economic dispatch of power system adopting multi-objective crisscross optimization algorithm |
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MENG Anbo, LI Zhuan
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Faculty of Automation, Guangdong University of Technology, Guangzhou 510006, China
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| Abstract: |
| For the constrained non-linear dynamic environmental economic power dispatch (DEED), a multi-objective crisscross optimization algorithm (MOCSO) is proposed. The two conflicting, constraining objective functions of fuel cost and pollutant emission in the process of dynamic dispatch are optimized simultaneously. In the optimization process, combined with non-constrained domination principle, this paper presents a new double cross mechanism to enhance the ability of crossing feasible regions, so that the Pareto optimal solution may falls within the feasible region. With searching on the periphery, the algorithm's ability of global searching is improved greatly. Meanwhile, the proposed approach adopts an external elitist archive to retain non-dominated solutions and maintain the diversity by using the crowded-comparison operator. Finally, fuzzy theory is used to obtained the best compromise solution. Simulation results of 10 generator test system validate the effectiveness and advantages of the proposed method. |
| Key words: dynamic environmental economic load dispatch multi-objective crisscross optimization algorithm double cross mechanism edge exploration Pareto optimality multi-objective optimization |
