首页|基于大语言模型绿电预测和绿电交易的园区综合能源系统集群多目标协同运行方法

基于大语言模型绿电预测和绿电交易的园区综合能源系统集群多目标协同运行方法

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为实现传统工业园区数字化和智能化升级,助力区域高质量发展,亟需园区智能化调度模型.为此,该文结合智慧园区管理系统和园区综合能源系统物理模型建立园区综合能源系统集群架构,提出了园区综合能源系统集群绿电交易三阶段协同运行方法,以解决多园区综合能源系统绿电交易的问题,实现分布式绿电的精准预测以及就地消纳.首先,基于大语言模型LLAMA-7B实现绿电预测,进一步以绿电功率划分购售电园区.其次,基于绿电价格配额曲线预测模型和动态绿电定价策略,制定园区间绿电交易差异价格.在此基础上,建立了多目标低碳经济优化运行模型,从而解决绿电交易所带来的经济因素和环境因素的矛盾问题.算例分析表明:所提出的模型可以统筹规划园区综合能源系统集群的经济成本、实际碳排放量和新能源利用率,对多园区综合能源系统的智能调度具有积极的推动作用.
Multi-objective Collaborative Operation Method for Park-level Integrated Energy System Cluster Based on Large Language Model for Green Electricity Prediction and Trading
In order to achieve digital and intelligent upgrading of traditional industrial parks,and to support high-quality regional development,there is an urgent need for intelligent dispatch models in parks.Therefore,this paper combines the smart park management system and the physical model of the park-level integrated energy system(PIES)to establish a cluster architecture of the PIES.A three-stage collaborative operation method for green electricity trading in the PIES cluster is proposed to solve the problem of green electricity trading in multiple PIES,and to achieve accurate prediction of distributed renewable energy and on-site consumption.Firstly,based on the large language model LLAMA-7B,green electricity prediction is achieved,and further green electricity power is divided into purchasing and selling electricity PIES.Secondly,based on the green electricity price quota curve prediction model and dynamic green electricity pricing strategy,the differential prices for green electricity trading between parks is established.On this basis,a multi-objective low-carbon economic optimization operation model is established to solve the contradiction between economic and envi-ronmental factors brought about by the green electricity exchange.The example analysis shows that the proposed model can comprehensively schedule the economic cost,actual carbon emissions,and renewable energy utilization rate of the PIES cluster,which has a positive promoting effect on the intelligent dispatch of multiple PIES.

park-level integrated energy systemgreen electricity tradinglarge language modeltime series data predic-tionmulti-object optimizationlow-carbon economic dispatch

陈艳波、方哲、张宁、强涂奔、张智、黄涛、徐子韬

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新能源电力系统全国重点实验室(华北电力大学),北京 102206

青海理工学院,西宁 810016

新能源电力系统智慧运行教育部重点实验室(青海大学),西宁 810016

园区综合能源系统 绿电交易 大语言模型 时序数据预测 多目标优化 低碳经济调度

青海省"帅才科学家负责制"项目中央高校基本科研业务费专项

2024MS009

2024

高电压技术
中国电力科学研究院 中国电机工程学会

高电压技术

CSTPCD北大核心
影响因子:2.32
ISSN:1003-6520
年,卷(期):2024.50(7)