摘要
电力市场交易运营过程中,电力系统发电侧、售电侧和用户侧等环节中数据繁多,为此提出一种新型的数据管理方案。该方案融合了数据关联算法和模糊综合评价法,实现了影响电力市场交易运营大数据因素分析。通过关联分析模型实现影响电力市场交易的因素分析,通过模糊数学的隶属度理论,将电力市场交易运营数据的定量分析转换为定量评价,将复杂的宏观数据转换为能够直接为用户识别的数据信息,大大降低了数据维度。试验表明,所提研究方法的数据误差分析率低于2%左右,提高了数据管理能力。
In the process of power market trading and operation, there are a lot of data in the power generation side, power sales side and user side of the power system. This study proposes a new data management scheme. The program integrates the data association algorithm and the fuzzy comprehensive evaluation method, and realizes the analysis of the big data factors that affect the power market transaction operation. Realize the analysis of factors affecting electricity market transactions through the correlation analysis model, and use the membership theory of fuzzy mathematics to transform the quantitative analysis of electricity market transaction operation data into quantitative evaluation, and transform complex macro data into data information that can be directly identified, which greatly reduces the data dimension. Experiments show that the data error analysis rate of this research method is less than about 2%, which improves the data management ability.
作者
郭俊宏
薛晓强
李玲
牛家强
Guo Junhong;Xue Xiaoqiang;Li Ling;Niu Jiaqiang(Jibei Electric Power Exchange Center Company LTD,Beijing 100000,China;Aostar Information Technologies Co.,Ltd.,Chengdu 610000,China)
出处
《电子测量技术》
2020年第23期172-177,共6页
Electronic Measurement Technology
关键词
电力市场交易
数据关联算法
模糊综合评价法
运营数据
数据关联
electricity market transactions
data association algorithm
fuzzy comprehensive evaluation method
operation data
data association
