考虑水电调节费用补偿的风光水联盟优化调度策略

doi:10.11930/j.issn.1004-9649.202308001

中国电力 ›› 2024, Vol. 57 ›› Issue (5): 26-38.DOI: 10.11930/j.issn.1004-9649.202308001

• 新型电力系统源网荷储灵活资源运营及关键技术 • 上一篇下一篇

考虑水电调节费用补偿的风光水联盟优化调度策略

李咸善¹^,²(), 丁胜彪¹(), 李飞¹^,², 李欣¹^,²()

1. 三峡大学电气与新能源学院，湖北宜昌　443002
2. 梯级水电站运行与控制湖北省重点实验室（三峡大学），湖北宜昌　443002

收稿日期:2023-08-01 接受日期:2023-10-30 出版日期:2024-05-28 发布日期:2024-05-16
作者简介:李咸善（1964—），男，教授，博士生导师，从事新能源与梯级储能联合运行优化调度、微电网运行与调度、水电站仿真与控制等研究，E-mail：lixianshan@ctgu.edu.cn
丁胜彪（1999—），男，硕士研究生，从事新能源与梯级储能联合运行优化调度研究，E-mail：1226204438@qq.com
李欣（1986—），男，通信作者，博士，副教授，从事新型人工智能算法在大规模电力系统中的应用、深度学习技术在电力系统中的应用研究，E-mail：ctgulx@ctgu.edu.cn
基金资助:
国家自然科学基金资助项目（基于集成-深度学习的高比例新能源大规模电力系统动态安全评估研究，52107107）；梯级水电站运行与控制湖北省重点实验室（三峡大学）开放基金（基于灵活性资源调节的新能源区域电网风险协同优化调度，2022KJX07）。

Optimal Scheduling Strategy for Wind-Solar-Hydro Alliance Considering Compensation of Regulation by Hydropower

Xianshan LI¹^,²(), Shengbiao DING¹(), Fei LI¹^,², Xin LI¹^,²()

1. College of Electrical Engineering & New Energy, China Three Gorges University, Yichang 443002, China
2. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China

Received:2023-08-01 Accepted:2023-10-30 Online:2024-05-28 Published:2024-05-16
Supported by:
This work is supported by National Natural Science Foundation of China (Research on Dynamic Security Assessment of High Ratio New Energy Large Scale Power Systems Based on Integration Deep Learning, No.52107107), Open Fund of Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (Risk Collaborative Optimization Dispatching of New Energy Regional Power Grid Based on Flexible Resource Regulation, No.2022KJX07).

摘要/Abstract

摘要：

针对风光水综合能源跨区消纳调度中的梯级储能和梯级水电联合调节调度、水电调节费用公平疏导等关键问题，提出了考虑水电灵活调节费用疏导补偿的风光水联盟四阶段优化调度模型。首先，建立了基于梯级储能调节的入网前风光出力波动平抑模型，使平抑误差和平抑成本最小；提出了基于相对波动系数的梯级储能调节成本和调节功率的公平疏导方法。其次，基于梯级储能和梯级水电联合调节的风光水联盟联合出力对电网负荷的跟踪，构建了风光水联盟与区域电网的主从博弈模型，优化电网电价和联盟售电计划，达到双方利益最大。然后，构建了计及风光水不确定性的前两阶段调度模型的鲁棒优化模型，获得兼顾经济性和鲁棒性的联盟各主体能量调度策略。最后，构建了基于合作者边际贡献指数的非对称纳什谈判联盟效益分配模型，实现合作剩余的公平分配和水电调节费用的公平疏导。算例结果表明，该方法提升了各利益主体合作后的净利润，有利于维系联盟合作的稳定性，促进风光水综合能源跨区消纳。

关键词: 水电灵活调节, 新能源消纳, 主从博弈, 两阶段鲁棒优化, 非对称纳什谈判

Abstract:

Aiming at the key problems in cross-region consumption scheduling of the wind-solar-hydro integrated energy, such as the cascade energy storage, cascade hydropower joint regulation and scheduling methods, and fair allocation of hydropower regulation costs, a four-stage optimization scheduling model of wind-solar-hydro alliance is proposed with consideration of the compensation of hydropower flexible regulation costs. Firstly, a wind-solar power fluctuation suppression model based on cascade energy storage regulation is established to minimize the suppression error and cost. A fair allocation method for regulating cost and power of cascade energy storage based on wind-solar fluctuation coefficient is proposed. Secondly, based on the tracking of the power grid load by the joint output of the wind-solar-hydro alliance of the cascade energy storage and cascade hydropower joint regulation, a master-slave game model of wind-solar-hydro alliance and regional power grid is constructed to optimize the power grid price and alliance power sales plan, thus achieving the maximum benefit of both parties. Thirdly, a robust optimization model of the first two-stage scheduling model is constructed with consideration of the uncertainty of wind-solar-hydro, and a energy scheduling strategy is obtained for each entity of the alliance considering both economy and robustness. Finally, an asymmetric Nash negotiation model based on the partner's marginal contribution index is constructed to realize the fair distribution of cooperation surplus and the fair allocation of hydropower regulation costs. The case study results show that the proposed method can fairly improve the net profit of all stakeholders after cooperation, and is conducive to maintaining the stability of alliance cooperation and promoting the cross-regional consumption of wind-solar-hydro integrated energy.

Key words: flexible regulation of hydropower, new energy consumption, master-slave game, two-stage robust optimization, asymmetric Nash negotiation

李咸善, 丁胜彪, 李飞, 李欣. 考虑水电调节费用补偿的风光水联盟优化调度策略[J]. 中国电力, 2024, 57(5): 26-38.

Xianshan LI, Shengbiao DING, Fei LI, Xin LI. Optimal Scheduling Strategy for Wind-Solar-Hydro Alliance Considering Compensation of Regulation by Hydropower[J]. Electric Power, 2024, 57(5): 26-38.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202308001

https://www.electricpower.com.cn/CN/Y2024/V57/I5/26

图/表 14

图 1 区域电网与风光水联盟联合调度框架

Fig.1 Joint dispatching framework of regional power grid and wind-solar-hydro alliance

图 2 主从博弈模型框架

Fig.2 Framework of master-slave game model

图 3 总体模型优化求解流程

Fig.3 Overall model optimization solution flowchart

表 1 不同鲁棒调节参数下风光水联盟净利润

Table 1 Net profit of wind-solar-hydro alliance with different robust adjustment parameters

鲁棒参数设置		风光水联盟净利润/元
$\varGamma_{\rm WT}=0,\varGamma_{\rm PV}=0, \varGamma_{\rm I}=0$		167668
$\varGamma_{\rm WT}=12,\varGamma_{\rm PV}=6, \varGamma_{\rm I}=8 $		158102
$\varGamma_{\rm WT}=18,\varGamma_{\rm PV}=12, \varGamma_{\rm I}=16 $		152897
$\varGamma_{\rm WT}=24,\varGamma_{\rm PV}=24, \varGamma_{\rm I}=24 $		150048

图 4 预测场景与最恶劣场景对比

Fig.4 Comparison of predicted scenarios and worst scenarios

图 5 针对不同对象的平抑计划

Fig.5 Suppression plans for different objects

表 2 基于波动系数的成本疏导结果

Table 2 Allocation results based on Shapley value

	边际平抑量/（kW·h）	相对波动系数	分摊调节成本/元
风光集团1	7282.1	0.531	367.17
风光集团2	6432.2	0.469	314.29

图 6 双边交易出清电价

Fig.6 Clearing price for bilateral transactions

图 7 双边交易出清电力

Fig.7 Clearing energy for bilateral transactions

图 8 梯级储能两阶段运行出力计划

Fig.8 Cascade energy storage two-stage operation output plan

图 9 水电跟踪电网净负荷

Fig.9 Hydropower tracking the net load of the power grid

表 3 各成员合作前后的成本与收益分析

Table 3 Cost and benefit analysis of each member before and after cooperation

	合作前净利润/元	合作后净利润/元	合作后提升/元	净利润提升率/%
风光集团1	32575	56005	23430	171.9
风光集团2	21608	36467	14859	168.7
一级水电	23407	22936	–471	97.9
二级水电	33681	41474	7793	123.1
梯级储能	3605	1220	–2385	33.8

表 4 对称纳什谈判模型的分配

Table 4 Allocation of symmetric Nash negotiation model 单位：元

	边际贡献	需支付合作成本	所获剩余利润	最终净利润
风光集团1	56005	12621	10809	43384
风光集团2	36467	4060	10809	32417
上游水电站	32681	–13665	10809	37821
下游水电站	41730	–3016	10809	44490

表 5 非对称纳什谈判模型的分配

Table 5 Allocation of asymmetric Nash negotiation model

	边际贡献指数	需支付合作成本/元	所获剩余利润/元	最终净利润/元
风光集团1	1.425	11617	11813	44388
风光集团2	1.259	4432	10436	32044
上游水电站	1.230	–13052	10196	37208
下游水电站	1.302	–2997	10790	44471

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