李伟, 周云海, 宋德璟, 石亮波, 陈奥洁. 蓄热式电采暖参与消纳受阻风光的源荷协调滚动调度[J]. 现代电力, 2024, 41(1): 116-123. DOI: 10.19725/j.cnki.1007-2322.2022.0164
引用本文: 李伟, 周云海, 宋德璟, 石亮波, 陈奥洁. 蓄热式电采暖参与消纳受阻风光的源荷协调滚动调度[J]. 现代电力, 2024, 41(1): 116-123. DOI: 10.19725/j.cnki.1007-2322.2022.0164
LI Wei, ZHOU Yunhai, SONG Dejing, SHI Liangbo, CHEN Aojie. Coordinated Rolling Scheduling of Source and Load for Regenerative Electric Heating in Accommodating Obstacled Wind and Solar Energy[J]. Modern Electric Power, 2024, 41(1): 116-123. DOI: 10.19725/j.cnki.1007-2322.2022.0164
Citation: LI Wei, ZHOU Yunhai, SONG Dejing, SHI Liangbo, CHEN Aojie. Coordinated Rolling Scheduling of Source and Load for Regenerative Electric Heating in Accommodating Obstacled Wind and Solar Energy[J]. Modern Electric Power, 2024, 41(1): 116-123. DOI: 10.19725/j.cnki.1007-2322.2022.0164

蓄热式电采暖参与消纳受阻风光的源荷协调滚动调度

Coordinated Rolling Scheduling of Source and Load for Regenerative Electric Heating in Accommodating Obstacled Wind and Solar Energy

  • 摘要: 蓄热式电采暖负荷具有时移性和连续可调性,可作为需求侧资源解决乡村地区新能源消纳困难与清洁供暖问题。当前实施的峰谷分时电价,不能根据源荷变化有效引导电采暖运行以消纳受阻风光。因此提出采用场景法描述风光荷的不确定性,根据源荷峰谷时段变化确定分时电价。并且考虑电采暖响应分时电价时出现用电同时率高问题,引入需求价格弹性系数,建立以蓄热式电采暖运行成本和系统负荷峰谷差期望最小的日前日内源荷协调优化模型,滚动调整每时段各灵活资源出力。最后,通过仿真验证模型的有效性。

     

    Abstract: The regenerative electric heating load has time shifts and continuous adjustability, which can be used as a demand-side resource to solve the problem of renewable energy consumption and clean heating in rural areas. The current peak-valley time-of-use electricity price cannot effectively guide the operation of electric heating to absorb the blocked scenery according to the change of source and load. Therefore, the scenario method is proposed to describe the uncertainty of wind-solar-load, and the time-of-use electricity price is determined according to the change of peak-valley period of source-load. Considering the problem of a high simultaneous rate of electricity consumption when the electric heating responds to the time-of-use electricity price, the demand-price elasticity coefficient is introduced. A day-ahead and daily endogenous load coordination optimization model with the minimum expectation of the operating cost of regenerative electric heating and the peak-valley difference of the system load is established, and the flexible resource output of each period is adjusted rollingly. Finally, the validity of the model is verified by simulation.

     

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