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1.沈阳工业大学电气工程学院,辽宁省沈阳市 110870
2.东北电力大学电气工程学院,吉林省吉林市 132012
Received:07 September 2022,
Revised:2022-12-09,
Published Online:13 February 2023,
Published:25 April 2023
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楚帅,葛维春,滕云等.海水淡化与电制热负荷联合消纳风电的多时间尺度调度策略[J].电力系统自动化,2023,47(8):120-131.
CHU Shuai,GE Weichun,TENG Yun,et al.Multi-time-scale Scheduling Strategy for Combined Accommodation of Wind Power by Seawater Desalination and Electric Heating Loads[J].Automation of Electric Power Systems,2023,47(8):120-131.
楚帅,葛维春,滕云等.海水淡化与电制热负荷联合消纳风电的多时间尺度调度策略[J].电力系统自动化,2023,47(8):120-131. DOI: 10.7500/AEPS20220907002.
CHU Shuai,GE Weichun,TENG Yun,et al.Multi-time-scale Scheduling Strategy for Combined Accommodation of Wind Power by Seawater Desalination and Electric Heating Loads[J].Automation of Electric Power Systems,2023,47(8):120-131. DOI: 10.7500/AEPS20220907002.
协调控制负荷侧灵活性资源消纳风电是构建新型电力系统的关键技术之一。考虑到风电预测精度随预测时间尺度缩短而提高,提出利用海水淡化、电制热等灵活性负荷消纳富余风电的多时间尺度优化调度策略。首先,分析多元协调消纳风电的电力电量平衡关系,建立海水淡化和电制热负荷的可调控支撑能力运行特性模型。其次,考虑负荷调度优势及运行边界,分析其在不同时间尺度下风电消纳调度需求的适应性,建立多时间尺度优化调度机制。在此基础上,建立日前、日内和实时优化调度模型,提出含电-水-热-储的多介质、多能源转换协调消纳风电的多时间尺度优化调度方法。最后,以中国北方某沿海城市冬季供暖期为例进行数值分析。结果表明,该方法在风电正调峰出力和反调峰出力时均表现出很强的跟随风电波动能力,能够有效提升风电利用率和运行经济性。
Coordinated control of load-side flexible resources to accommodate wind power is one of the key technologies for constructing a new power system. Considering that the forecast accuracy of wind power increases with the shortening of the forecast time scale
this paper proposes a multi-time-scale optimal scheduling strategy for flexible loads such as seawater desalination and electric heating to accommodate the redundant wind power. First
the power and electricity balance relationship of the coordinated accommodation of wind power by the multi-variable system is analyzed. A model of operating characteristics of adjustable support capacity of seawater desalination and electric heating loads is established. Then
considering the scheduling advantages and operation boundaries of load
the adaptability of scheduling demand of wind power accommodation at different time scales is analyzed and a multi-time-scale optimal scheduling mechanism is established. On this basis
the day-ahead
intra-day and real-time optimal scheduling models are established. A multi-time-scale optimal scheduling method is proposed for the coordinated accommodation of wind power in a multi-media and multi-energy flow system containing electricity-water-heat-storage. Finally
the numerical analysis is carried out by taking the winter heating period of a coastal city in northern China as an example. The results show that this method has a strong ability to follow the fluctuation of wind power in both positive and negative peak-shaving output of wind power. It can effectively improve the wind power utilization rate and operation economy.
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