摘要
可再生能源作为电力市场的主体,其消纳量的考核权重对电力市场交易产生着重要影响。在其影响下现有电力市场交易影响因素发生变化,导致现有预测模型的评估结果与实际市场交易结果之间产生较大差异,严重影响模型可信度的同时,不利于电力市场正常交易秩序的健康发展。因此,基于可再生能源消纳量考核权重特征,对预测模型进行影响因素的重构分析,具体实现通过可再生能源消纳量考核权重时间预测量计算。电力市场双边交易价格影响系数与数据整合下电力市场交易影响预测模型的构建与输出,为此分3个独立阶段完成,为了保证每个阶段的统一,模型构建过程中将上一阶段所得参量作为下一阶段的计算样本,以此建立每一阶段的联系。通过验证数据的对比表明,构建的预测模型具备良好分析能力、精准的预测能力、稳定的输出能力,其性能具有较高的可信度。
As the main body of the power market,the assessment weight of renewable energy consumption has an important impact on the electricity market transaction.Under its influence,the influencing factors of the existing power market transactions change,which leads to a larger difference between the evaluation results of the existing prediction model and the actual market trading results,seriously affects the credibility of the model,and is not conducive to the healthy development of the normal trading order of the power market.Therefore,based on the assessment weight characteristics of renewable energy consumption,this paper reconstructs and analyzes the influencing factors of the prediction model,realizes time forecast quantity calculation through the renewable energy consumption quantity assessment weight.The construction and output of a predictive model for the impact of electricity market transactions under the integration of bilateral transaction price coefficient and data in the electricity market are completed in three independent stages.To ensure the unity of each stage,the parameters obtained from the previous stage are used as the calculated sample of the next stage.It can establish connection of stages.A comparison of the validation data shows that the constructed prediction model has good analytical ability,accurate prediction ability,stable output ability.Its performance has a higher credibility.
作者
郑景立
喻芸
张建中
张继英
ZHENG Jingli;YU Yun;ZHANG Jianzhong;ZHANG Jiying(China Southern Power Grid Digital Grid Group Co.,Ltd.,Guangzhou 510663,China)
出处
《微型电脑应用》
2024年第11期157-161,共5页
Microcomputer Applications
关键词
可再生能源
消纳量
考核权重
电力市场
预测模型
renewable energy
consumption
assessment weight
power market
prediction model