| 含大规模储热的光热电站—风电联合系统多日自调度方法 |
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| 引用本文： | 晋宏杨,孙宏斌,郭庆来,陈润泽,李正烁. 含大规模储热的光热电站—风电联合系统多日自调度方法[J]. 电力系统自动化, 2016, 40(11): 17-23 |
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| 作者姓名： | 晋宏杨 孙宏斌 郭庆来 陈润泽 李正烁 |
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| 作者单位： | 清华大学电机工程与应用电子技术系, 北京市 100084; 电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084,清华大学电机工程与应用电子技术系, 北京市 100084; 电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084,清华大学电机工程与应用电子技术系, 北京市 100084; 电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084,清华大学电机工程与应用电子技术系, 北京市 100084; 电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084,清华大学电机工程与应用电子技术系, 北京市 100084; 电力系统及发电设备控制和仿真国家重点实验室, 清华大学, 北京市 100084 |
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| 基金项目： | 国家重点基础研究发展计划(973计划)资助项目(2013CB228201)；国家自然科学基金资助项目(51361135703) |
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| 摘 要： | 含储热的光热电站具有良好的可调度性,其可调度能力与实时光照功率和储热装置内存储的能量有关。当光热电站与风电组成联合系统发电时,光热电站可以削减风电的不确定性,但由于风、光功率情况在不同调度日间具有波动性,因此联合系统需要的光热电站的可调度能力和光热电站的实际可调度能力每天均不相同。文中建立了基于场景方法的光热电站与风电联合系统的多日随机调度模型。该模型充分考虑多日风、光功率预测的不确定性,进行联合系统日前自调度。最后,通过算例分析,讨论了不同预测时间尺度、储能参数取值对自调度结果的影响。
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| 关 键 词： | 光热电站；储热装置；风电；多日自调度；经济调度 |
| 收稿时间： | 2015-08-26 |
| 修稿时间： | 2016-04-27 |
Multi-day Self-scheduling Method for Combined System of CSP Plants and Wind Power with Large-scale Thermal Energy Storage Contained |
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| JIN Hongyang,SUN Hongbin,GUO Qinglai,CHEN Runze and LI Zhengshuo. Multi-day Self-scheduling Method for Combined System of CSP Plants and Wind Power with Large-scale Thermal Energy Storage Contained[J]. Automation of Electric Power Systems, 2016, 40(11): 17-23 |
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| Authors: | JIN Hongyang SUN Hongbin GUO Qinglai CHEN Runze LI Zhengshuo |
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| Affiliation: | Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing 100084, China,Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing 100084, China,Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing 100084, China,Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing 100084, China and Department of Electrical Engineering, Tsinghua University, Beijing 100084, China; State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University, Beijing 100084, China |
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| Abstract: | The concentrating solar power (CSP) plants with thermal energy storage (TES) has good schedulability, which is decided by real time solar power input and energy stored in TES. The CSP plant combined with wind farms can reduce the uncertainty of wind power. The uncertainty and variability of wind and solar in different days result in the changes of CSP''s schedulability and the need of it. By using scenario set to represent uncertainty of wind and solar, a stochastic model of the combined system is established. The day-ahead schedule of the system and the power dispatched in real time is optimized considering the uncertainty of multi-day wind and solar power forecast. By case study, the advantage of self-scheduling considering multi-day wind and solar uncertainty is verified, and the impact of different forecast horizon, TES''s capacity and self-discharging rate is investigated. This work is supported by National Basic Research Program of China (973 Program) (No. 2013CB228201) and National Natural Science Foundation of China (No. 51361135703). |
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| Keywords: | concentrating solar power(CSP)plant thermal energy storage device wind power multi-day self-scheduling economic dispatch |
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