计及风-光-水-火多能协同的电网可再生能源消纳能力评估

doi:10.11930/j.issn.1004-9649.202305105

摘要/Abstract

摘要：

针对电网消纳能力评估问题进行研究，提出一种计及风-光-水-火多能协同的电网可再生能源消纳能力评估方法。首先，构建风-光-水-火多能协同系统框架；其次，给出可再生能源接纳运行风险的定义，并建立可再生能源运行风险模型；最后，基于两阶段鲁棒优化理论提出计及风-光-水-火多能协同的电网可再生能源消纳能力评估模型，并采用列和约束生成（column and constraint generation，C&CG）算法求解。算例结果表明：所提模型可有效控制可再生能源出力不确定集及评估电网可再生能源消纳能力。

关键词: 消纳能力评估, 多能协同, 运行风险

Abstract:

This paper studies the problem of power grid absorption capacity evaluation, and an evaluation method of renewable energy consumption capacity of power grid considering wind-photovoltaic-hydro-thermal power multi-energy coordination is proposed. Firstly, the framework of wind-photovoltaic-hydro-thermal power multi-energy cooperative system is constructed. Then, the definition of the operational risk of renewable energy acceptance is given, and the operational risk model of renewable energy is established. Finally, based on the two-stage robust optimization theory, the evaluation model of renewable energy consumption capacity of power grid considering wind-photovoltaic-hydro-thermal power multi-energy cooperation is proposed, and the column and constraint generation (C&CG) algorithm is used to solve the problem. The results of example show that the proposed model can control the uncertainty set of renewable energy output and assess the renewable energy consumption capacity of power grid effectively.

Key words: assessment of absorptive capacity, multi energy collaborative system, operational risks

郑伟民, 但扬清, 王晨轩, 武佳卉, 朱云峰. 计及风-光-水-火多能协同的电网可再生能源消纳能力评估[J]. 中国电力, 2023, 56(12): 248-254.

Weimin ZHENG, Yangqing DAN, Chenxuan WANG, Jiahui WU, Yunfeng ZHU. Evaluation of Renewable Energy Consumption Capacity in Power Grid Considering the Synergistic Effect of Wind-Photovoltaic- Hydro-Thermal Power[J]. Electric Power, 2023, 56(12): 248-254.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202305105

https://www.electricpower.com.cn/CN/Y2023/V56/I12/248

图/表 11

图 1 风-光-水-火多能协同系统框架

Fig.1 Framework of wind-photovoltaic-hydropower-thermal power multi energy collaborative system

图 2 可再生能源出力预测误差正态分布

Fig.2 Normal distribution of prediction error of renewable energy output

表 1 常规发电机组参数

Table 1 Parameters of conventional generator units

机组	${{{P_{\max }}} \mathord{\left/ {\vphantom {{{P_{\max }}} {{\text{MW}}}}} \right. } {{\text{MW}}}} $	${{{P_{\min }}} / {( {{\text{MW}} \cdot {{\text{h}}^{ - 1}}})}} $	${{{R_ + }} / {( {{\text{MW}} \cdot {{\text{h}}^{ - 1}}})}} $	${{R_ - }}/{( {{\text{MW}} \cdot {{\text{h}}^{ - 1}}})} $
G₁	155	30	50	50
G₂	130	20	30	30
W₃	120	10	20	20

图 3 风-光-负荷预测数据

Fig.3 Forecast data of wind power-photovoltaic-load

表 2 弃风、弃光和甩负荷成本参数

Table 2 Cost parameters for wind-photovoltaic-load shedding 单位：元/(MW·h)

时段	弃风成本	弃光成本	甩负荷成本
01:00—06:00	40	0	400
07:00—18:00	60	60	600
19:00—24:00	50	0	500

表 3 3组模型计算结果对比

Table 3 Comparison of calculation results of 3 sets of models 单位：万元

模型	运行成本	风险成本	总成本
DS	133.21	50.32	183.53
RS	143.56	20.26	163.82
RRS	137.35	15.78	153.28

图 4 不同模型风电机组出力范围对比

Fig.4 Comparison of output ranges of Wind units in different models

图 5 不同模型光伏机组出力范围对比

Fig.5 Comparison of output ranges of photovoltaic units in different models

表 4 不同风电和光伏不确定集参数的对比

Table 4 Comparison of uncertain set parameters for different wind and photovoltaic systems

${\varOmega _{{\text{pw}}}}$	${\varOmega _{{\text{pv}}}}$	运行成本/万元	运行风险成本/万元	总成本/万元
4	4	134.59	12.30	146.89
8	8	137.35	15.78	153.28
8	12	139.11	15.84	154.95
12	8	139.25	16.04	155.29
12	12	139.49	15.91	155.40

图 6 不同S下风电机组出力范围

Fig.6 Wind units output range under different S conditions

图 7 不同S下光伏机组出力范围

Fig.7 Photovoltaic units output range under different S conditions

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