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基于分散协同多阶段鲁棒调度的电热联合系统灵活性增强方法 被引量:5

Flexibility Reinforcement Method for Integrated Electricity and Heat System Based on Decentralized and Coordinated Multi-stage Robust Dispatching
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摘要 在“碳达峰”的背景下,新能源的渗透率将进一步增加,电热联合系统的灵活性欠缺难以满足日益增长的新能源消纳需求。文中提出了一种基于分散协同多阶段鲁棒调度的电热联合系统灵活性增强方法,相比传统调度方法,可充分发挥多能源储能、电热转换设备等灵活性资源应对风电出力波动的作用。首先,对含多种灵活性资源的电热联合系统进行建模,基于盒式不确定集的风电预测出力假设,并考虑到电、热系统分属于不同运营商的场景,建立了分散协同的多阶段鲁棒调度模型。为了衡量调度模型的灵活性,提出了基于线性规划灵敏度分析的多种灵活性指标。然后,提出了基于“预估-矫正”的储能状态转移方程,保证模型的凸性。接着,提出了分散协同鲁棒对偶动态规划算法,仅需较少的信息交换即可实现模型的快速求解。最后,通过算例验证了所提模型提升电热联合系统灵活性和保证风电消纳方面的有效性。 In the background of carbon peak, the penetration of renewable energy will further increase. The growing need for renewable energy accommodation can hardly be met due to the lack of flexibility of the current integrated electricity and heat system(IEHS). In this paper, a flexibility reinforcement method based on the decentralized and coordinated multi-stage robust dispatching is proposed. Compared to traditional dispatching methods, the proposed method can fully utilize the flexible resources such as multi-energy storages, electricity-to-heat converters to cope with fluctuations in wind power output. First, the IEHS with multiple flexible resources is modelled. Based on the assumption of wind power forecasting output for the box uncertainty set, and considering the scenarios where the electricity and thermal systems belong to different operators, a decentralized and coordinated multi-stage robust dispatching model is established. In order to measure the flexibility of the dispatching model, a variety of flexibility indicators based on linear programming sensitivity analysis are proposed. Then, a state transition equation of the energy storage based on predict-correction is proposed to ensure the convexity of the model. Furthermore, a decentralized and coordinated robust dual dynamic programming algorithm is proposed, which can quickly solve the model with less information exchange.Finally, an example is used to verify the effectiveness of the proposed model in improving the flexibility of the IEHS and ensuring wind power accommodation.
作者 施云辉 郭创新 SHI Yunhui;GUO Chuangxin(College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2022年第6期10-19,共10页 Automation of Electric Power Systems
关键词 鲁棒动态规划 电热联合系统 分布式优化 对偶动态规划 灵活性 robust dynamic programming integrated electricity and heat system(IEHS) decentralized optimization dual dynamic programming flexibility
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