| 引用本文: | 霍 巍,张 耀,赵寒亭,等.基于联盟合作博弈的风电数据定价方法[J].电力系统保护与控制,2024,52(19):97-107.[点击复制] |
| HUO Wei,ZHANG Yao,ZHAO Hanting,et al.Wind power data pricing method based on an alliance cooperation game[J].Power System Protection and Control,2024,52(19):97-107[点击复制] |
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| 摘要: |
| 为发挥风电数据价值并给企业带来额外收益，提出一种基于联盟合作博弈模型的风电数据定价方法。首先，提出一种考虑第三方监管的风电数据交易流程与风电数据定价思路。其次，通过数据交易获取邻近场站数据，使用向量自回归模型提高风电预测精度，从而在电力市场交易中降低不平衡成本，提高风电场整体发电利润，体现所交易数据的整体价值。然后，将数据交易前后产生的超额利润(即使用交易数据后的发电利润增加值)，以联盟合作博弈的方式分配给数据售卖方作为交易数据的定价结果，实现数据价值的定量衡量。最后，考虑风电时空特性通过最大化数据价值确定数据交易对象，实现风电数据的合理定价。算例分析结果表明，所提方法能够提升风电预测精度、增加风场发电利润，并实现风电数据定价的公平性与合理性。 |
| 关键词: 电力数据交易 数据定价 风电预测 电力市场 合作博弈 |
| DOI：10.19783/j.cnki.pspc.231594 |
| 投稿时间：2023-12-14修订日期：2024-04-03 |
| 基金项目:国家重点研发计划项目资助“支撑20%新能源电量占比场景下的电网智能调度关键技术”(2022YFB2403500) |
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| Wind power data pricing method based on an alliance cooperation game |
| HUO Wei,ZHANG Yao,ZHAO Hanting,WANG Jianxue |
| (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China) |
| Abstract: |
| To give full play to the value of wind power data and bring extra profit to a wind farm, this paper proposes a wind power data pricing method based on alliance cooperation game theory. First, a wind power data trading process and pricing approach considering third-party supervision are proposed. Secondly, adjacent station data is obtained through data trading, and a vector autoregressive model is used to improve wind power forecasting accuracy, thereby reducing imbalance costs in electricity market transactions, increasing the overall generation profit of wind power plants, and reflecting the value of the traded data. Then, the excess profit generated before and after data trading (i.e., the increase in generation profit using traded data) is distributed to the data sellers as the pricing of the traded data using an alliance cooperation game, quantitatively measuring the value of the data. Finally, considering the spatio-temporal characteristics of wind power, the data trading parties are determined by maximizing the data value, achieving fair and reasonable data pricing. The case analysis results demonstrate that the proposed method can enhance wind power forecasting accuracy, increase wind farm generation profits, and achieve fairness and rationality in wind power data pricing. |
| Key words: electric data trading data pricing wind power forecasting electricity market cooperative game |
