基于混合推荐算法的电力用户交易最优方案研究
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广州电力交易中心有限责任公司

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基于SaaS多租户模式的电力交易平台运营管控机制及相关运营支撑技术研究项目ZBKJXM20180983


Research on Optimal Trading Scheme of power users based on hybrid recommendation algorithm
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    摘要:

    目的 针对目前电力交易时零售电价套餐种类繁多,形式复杂,用户很难找到最适合自己用电需求的电价套餐等问题,在研究了电力用户特征矩阵、以及用户特征相似性开展分析之后,提炼出一种混合电力套餐推荐模型。主要方法 引入多属性效用理论,并据此来实现电价套餐场景下的用户综合效用模型。最后,创造性引入了混合推荐算法,以给出最佳的电价套餐,从而提高电力系统整体运行效率,优化电力资源配置。仿真阶段,以某电力公司提供的50个典型用户的电力数据为案例进行分析。结果 结果表明,经混合推荐方案,电力成本降低1.47%。结论 所提模型为智能电网电力交易提供了一定借鉴作用。

    Abstract:

    At present, there are many kinds and complex forms of retail electricity price packages in power transaction, and it is difficult for users to find the most suitable electricity price package for their own electricity demand. Based on the study of the similarity analysis of power user characteristic matrix and power user characteristic, a hybrid electricity package recommendation model is proposed. The model constructs the comprehensive utility function of electricity price package to users based on multi-attribute utility theory. Finally, the optimal price package is recommended based on the hybrid recommendation algorithm, so as to improve the overall operation efficiency of the power system and optimize the allocation of power resources. In the simulation stage, the power data of 50 typical users provided by a power company are analyzed as a case. The results show that the power cost is reduced by 1.47% through the hybrid recommended scheme. The proposed model provides a reference for smart grid power trading.

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  • 收稿日期:2023-01-10
  • 最后修改日期:2023-03-10
  • 录用日期:2023-01-18
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