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考虑置信容量和调峰能力的新能源基地光热电站配置方法

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光热电站具有清洁低碳、长时间储能的友好并网特性,能有效平抑新能源出力波动.相比于传统火电机组,光热电站的调节能力依然存在不足,可能会降低新能源基地外送能力.为此,基于光热电站接入前后外送可靠性不变原则,建立针对光热电站置信容量及调峰能力的评估方法和模型.在此基础上,以新能源基地综合发电经济性为目标,考虑机组约束、外送约束、光热电站置信容量和调峰能力约束建立模型.通过算例仿真,采用时序模拟技术,对光热电站的储热时长和容量优化配置模型进行求解,给出典型场景下的光热电站配置方案,得到风光容量配比最优的容量配置方案,并分析不同风光容量配比下的经济性情况.所提的光热电站储热时长和容量配置方法能够有效提升新能源基地的低碳性,优化光热电站的投资收益.
Concentrating Solar Power Plant Configuration Method of Renewable Energy Base with Consideration of Confidence Capacity and Peak Shaving Capcity
The concentrating solar power plant(CSPP)has the friendly grid-connected characteristics of clean,low carbon and long-term energy storage,which can effectively smooth the fluctuation of renewable energy output.Compared with the traditional thermal power unit,the adjustment ability of CSPP is still insufficient,which may reduce the delivery capacity of renewable energy base.Thus a confidence capacity and peak shaving capacity evaluation method and model based on equal power output reliability before and after CSPP access is proposed.On this basis,with the goal of power generation economy of the renewable energy base,the model considering the constraints of the unit,the delivery constraints,the confidence capacity and the peak load capacity of CSPP is also established.Based on the time series simulation technology,the optimal configuration model of heat storage duration and capacity of CSPP is solved.The configuration scheme of CSPP under typical scenarios is given,the economic comparisons under different wind and solar ratios are analyzed,and the optimal ratio scheme is obtained.The thermal storage duration and capacity allocation method proposed in this paper can effectively improve the low carbon nature of the renewable energy base and optimize the investment return of CSPP.

renewable energy baseconcentrating solar power plantconfidence capacitypeak shaving abilityheat storage time

丁坤、孙亚璐、王湘、杨昌海、李海波

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国网甘肃省电力公司经济技术研究院, 甘肃 兰州 730030

清华四川能源互联网研究院,四川 成都 610213

新能源基地 光热电站 置信容量 调峰能力 储热时长

国家电网科技项目

5108-202218280A-2-300-XG

2024

广东电力
广东电网公司电力科学研究院,广东省电机工程学会

广东电力

CSTPCD北大核心
影响因子:0.527
ISSN:1007-290X
年,卷(期):2024.37(3)
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