基于双碳目标的大数据能源调度博弈管理算法研究

辛锐; 姜丹; 郑焕坤; 刘宏; 陈曦

辛锐,姜丹,郑焕坤,刘宏,陈曦.基于双碳目标的大数据能源调度博弈管理算法研究[J].电测与仪表,2022,59(4):55-65.
Xinrui,jiangdan,zhanghuankun,liuhong,chenxi.Research on Big Data Energy Dispatching Game Management Algorithm Based on Double Carbon Goals[J].Electrical Measurement & Instrumentation,2022,59(4):55-65.

基于双碳目标的大数据能源调度博弈管理算法研究

Research on Big Data Energy Dispatching Game Management Algorithm Based on Double Carbon Goals

DOI：10.19753/j.issn1001-1390.2020.04.009

中文关键词: 大数据能源互联网预测博弈论管理分析

英文关键词:big data energy internet forecast game theory management analysis

基金项目:中央高校基本科研业务费专项资金资助项目（2014MS87）；基于大云物移智新技术应用的电网企业“三流合一”体系研究（kj2019-043）；国家自然科学基金资助项目(61501185)

作者中文名	作者英文名	单位
辛锐	Xinrui	国网河北省电力有限公司信息通信分公司
姜丹	jiangdan	国网河北省电力有限公司信息通信分公司
郑焕坤	zhanghuankun	华北电力大学
刘宏	liuhong	国网河北省电力有限公司信息通信分公司
陈曦	chenxi	国网河北省电力有限公司信息通信分公司

摘要点击次数: 1525

中文摘要:

随着“碳中和”和“碳达峰”建设目标的不断推进，能源互联网作为实现“双碳”目标的主要驱动力，可以为能源的产生、传输、存储、消耗等设备的集成提供开放的网络框架，基于现有信息和通信技术能够有效提高能源管控水平。本文针对可再生能源与传统能源的协调管理问题，构建基于电网企业、储能公司、微电网和电力用户组成的常规电力系统模型。首先，将能源管理问题转化为三阶段的Stackelberg博弈，在满足系统可靠运行和用户用电需求的条件下最大化个人收益为。基于反向引导法解决三阶段非合作博弈问题，从而获得每一阶段最优策略的闭合表达式。研究了基于大数据的发电预测技术，并提出了一种电能预测方法可有效为微网用能进行指导。仿真结果表明本文所提的基于大数据可再生能源管理模型的有效性，验证了准确的风电功率预测结果有利于更好的能源管理的理论分析。

英文摘要:

With the continuous advancement of the construction goals of “carbon neutrality” and “carbon peaking”, the energy Internet, as the main driving force for achieving the “dual carbon” goal, can provide openness for the integration of equipment for energy generation, transmission, storage, and consumption. Based on the existing information and communication technology, it can effectively improve the level of energy management and control. This paper aims at the coordination and management of renewable energy and traditional energy, and constructs a conventional power system model based on grid companies, energy storage companies, microgrids and power users. First of all, the problem of energy management is transformed into a three-stage Stackelberg game, which maximizes personal income while meeting the reliable operation of the system and the power demand of users. The three-stage non-cooperative game problem is solved based on the reverse guidance method, so as to obtain the closed expression of the optimal strategy at each stage. The power generation forecasting technology based on big data is studied, and an electric energy forecasting method is proposed that can effectively guide the energy consumption of microgrids. The simulation results show the validity of the big data-based renewable energy management model proposed in this paper, and verify that the accurate wind power prediction results are conducive to the theoretical analysis of better energy management.

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