刘旭, 杨德友, 刘铖, 张旺, 郑天宇. 考虑用户满意度的含风电场多目标环境经济调度[J]. 现代电力, 2017, 34(3): 44-51.
引用本文: 刘旭, 杨德友, 刘铖, 张旺, 郑天宇. 考虑用户满意度的含风电场多目标环境经济调度[J]. 现代电力, 2017, 34(3): 44-51.
LIU Xu, YANG Deyou, LIU Cheng, ZHANG Wang, ZHENG Tianyu. Multi-objective Economic Emission Dispatching for Power Grid Integrated with Wind Farms by Considering Customers Satisfaction[J]. Modern Electric Power, 2017, 34(3): 44-51.
Citation: LIU Xu, YANG Deyou, LIU Cheng, ZHANG Wang, ZHENG Tianyu. Multi-objective Economic Emission Dispatching for Power Grid Integrated with Wind Farms by Considering Customers Satisfaction[J]. Modern Electric Power, 2017, 34(3): 44-51.

考虑用户满意度的含风电场多目标环境经济调度

Multi-objective Economic Emission Dispatching for Power Grid Integrated with Wind Farms by Considering Customers Satisfaction

  • 摘要: 在分析发电侧与需求侧的互动原理基础上,建立基于分时电价的需求响应模型,并将其融入环境经济调度中,联合优化调度风电、火电和需求响应(虚拟发电资源)3种发电资源,以提高风电消纳能力和实现节能减排的目的,改变传统一味优化发电侧资源的调度模式。综合考虑用户满意度、污染气体排放和发电成本3个优化目标,在保证系统运行环保性和经济性的同时使求得的调度方案令用户满意。将禁忌搜索思想融入万有引力算法寻优过程中,结合多目标搜索理论,提出一种多目标禁忌搜索万有引力算法对模型进行求解。算例仿真结果验证了所提模型的合理性及算法的有效性。

     

    Abstract: The demand response model is established based on time-of-use price by analyzing the interaction between generation side and demand side, and it is applied in the economic emission dispatch. Proposed model combines such power sources as optimal scheduling wind power, thermal power and demand response (virtual generation resources) to improve wind power accommodation capacity and achieve purposes of energy saving, and changes traditional resource scheduling mode that blindly optimizes power sources at generation side. By comprehensive considering the customers' satisfaction, polluted gas emissions and generation cost, proposed model can ensure system to run in environmental protecting and economic status, and make the scheduling scheme meet the requirement of customers. Through introducing tabu search into the optimized search process of gravitational search algorithm, a multi-objective tabu search-gravitational search algorithm is proposed to solve this model by combing more targeted search mechanism. Simulation results verify the rationality of proposed model and the validity of algorithm.

     

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