Open AccessResearch on Monthly Unified Scheduling Electricity Consumption Prediction Based on Temperature Gradient Change
Author(s) -
Junhui Liu,
Hongkun Bai,
Jiangbo Wang,
Hujun Li,
Meng Yang,
Shuo Yin,
Dan Song
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/782/3/032091
Subject(s) - electricity , scheduling (production processes) , power consumption , power grid , computer science , consumption (sociology) , environmental science , mathematical optimization , power (physics) , engineering , mathematics , electrical engineering , thermodynamics , social science , physics , sociology
With the improvement of residents’ living standards, the cooling and heating load are increasing rapidly, and the influence of temperature on the unified scheduling electricity consumption is increasing. Based on the temperature gradient change, the monthly unified scheduling electricity consumption prediction research is carried out to quantify the influence of temperature on the unified scheduling electricity consumption, and the unified scheduling electricity consumption prediction is performed for a provincial power grid. The example further proves the feasibility and effectiveness of the prediction method.