| 引用本文: | 田壁源,戚红艳,张新燕,等.基于MO-APSO的含风电场电力系统动态环境经济调度[J].电力系统保护与控制,2019,47(24):57-64.[点击复制] |
| TIAN Biyuan,QI Hongyan,ZHANG Xinyan,et al.Dynamic environmental economic dispatch of power system containing wind farms based on MO-APSO[J].Power System Protection and Control,2019,47(24):57-64[点击复制] |
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| 摘要: |
| 为综合考虑碳排放权交易对风火联供模式的影响，基于节能减排、发电效益、机组运行3个方面约束条件，引入碳排放权交易成本函数，构建了考虑发电成本、碳交易成本、环境成本的风火联供系统多目标动态环境经济调度(DEED)模型。提出一种多目标自适应粒子群优化(MO-APSO)算法求解该DEED问题。根据寻优过程中粒子当前的适应度函数值，对惯性权重及学习因子进行自适应修正，进一步改善早熟的缺陷，增强全局搜索能力。含风电场的10机电力系统仿真结果表明:所提方法能同时优化成本和排放这2个冲突的目标，且获得了比其他算法更为宽广和均匀的Pareto前沿，有效降低了联供系统的碳排放量及综合运行成本。 |
| 关键词: 风电 动态环境经济调度 多目标优化 调度模型 MO-APSO 最优折中解 |
| DOI：10.19783/j.cnki.pspc.190139 |
| 投稿时间：2019-01-29修订日期：2019-06-26 |
| 基金项目:国家自然科学基金项目资助(51667018, 51367015) |
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| Dynamic environmental economic dispatch of power system containing wind farms based on MO-APSO |
| TIAN Biyuan,QI Hongyan,ZHANG Xinyan,HE Feng,PENG Jian,CHANG Xiqiang |
| (State Grid Urumqi Power Supply Company, Urumqi 830011, China;College of Electrical Engineering, Xinjiang University, Urumqi 830049, China) |
| Abstract: |
| In order to comprehensively consider the impact of carbon emissions trading on wind-fire co-generation model, and based on the constraints of energy saving and emission reduction, power generation efficiency and unit operation, the carbon emission trading cost function is introduced. A multi-objective Dynamic Environmental Economic Dispatch (DEED) model of wind-fire combined power system considering generation cost, carbon trading cost and environmental cost is constructed. A multi-objective adaptive particle swarm optimization algorithm is proposed to solve the DEED problem. According to the current fitness function of particles in the optimization process, the inertia weight and learning factor are adaptively modified to further improve the premature defects and enhance the global search ability. The simulation results of 10-machine power systems with wind farms show that the proposed method can simultaneously optimize the two conflicting objectives of cost and emission, and obtain a wider and more uniform Pareto frontier than other algorithms, which can effectively reduce the carbon emissions and integrated operation costs of the combined generation system. This work is supported by National Natural Science Foundation of China (No. 51667018 and No. 51367015). |
| Key words: wind power dynamic environmental economic dispatch multi-objective optimization dispatching model MO-APSO optimal compromise solution |
