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促进风电消纳的源-荷联合优化调度 被引量:4

Source-load joint optimization scheduling for promoting wind power accommodation
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摘要 针对我国弃风问题,将光热电站与风电联合运行,利用其出力的互补性以及储热装置的可调度性应对风电出力的波动性、反调峰性,平滑风电出力以及净负荷曲线,降低火电机组调峰的成本,提高风电利用率。但此方法受到储热装置容量的限制以及机组最小出力和旋转备用的约束,对弃风情况改善有限,因此在需求侧引入需求响应措施与光热-风电系统配合。以系统发电运行成本、弃风惩罚费用和需求响应成本为目标函数,考虑各种约束条件,建立了需求响应与光热-风电系统联合优化的两阶段调度模型,源荷侧配合促进风电最大化的消纳。设置4种情景进行算例分析,通过算例分析验证源荷联合优化策略的有效性。 In view of wind power curtailment,the concentrated solar power station and wind farm can be jointly operated to deal with the fluctuation and anti-peaking of wind power output,smooth the net load curve,reduce the peaking cost of thermal power units,and promote the consumption of wind power by using the complementarity of their output and the schedulability of heat storage devices.However,this method only has limited improvement on wind power curtailment due to the limited capacity of the heat storage devices and the constraints of the minimum unit output and rotating reserve.In this study,the demand response and the CSP-wind power systems were combined to promote the accommodation of wind power.By taking the operating cost of system power generation,curtailment cost and demand response cost as the objective function and taking various constraints into consideration,this study established a two-stage scheduling model of combined demand response and CSP-wind power system and achieved the source-load coordination to promote the maximum accommodation of wind power.Finally,four scenarios were set up for example analysis to verify the practicability and effectiveness of the source-load joint optimization strategy.
作者 李昱君 于永进 LI Yujun;YU Yongjin(College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, Shandong 266590, China)
出处 《山东科技大学学报(自然科学版)》 CAS 北大核心 2021年第4期118-126,共9页 Journal of Shandong University of Science and Technology(Natural Science)
基金 青岛西海岸新区2020年科技项目(源头创新专项)(2020-92)。
关键词 光热-风电系统 需求响应 风电消纳 蓄冷空调 源-荷联合优化 concentrated solar power-wind power system demand response accommodation of wind power cool storage air conditioning source-load joint optimization
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