| Title | Medium- and long-term electric power demand forecasting based on the big data of smart city |
|---|---|
| ID_Doc | 38349 |
| Authors | Wei, ZM; Li, XY; Li, XZ; Hu, QH; Zhang, HY; Cui, PJ |
| Title | Medium- and long-term electric power demand forecasting based on the big data of smart city |
| Year | 2017 |
| Published | |
| Abstract | Based on the smart city, this paper proposed a new electric power demand forecasting model, which integrates external data such as meteorological information, geographic information, population information, enterprise information and economic information into the big database, and uses an improved algorithm to analyse the electric power demand and provide decision support for decision makers. The data mining technology is used to synthesize kinds of information, and the information of electric power customers is analysed optimally. The scientific forecasting is made based on the trend of electricity demand, and a smart city in north-eastern China is taken as a sample. |
| https://iopscience.iop.org/article/10.1088/1742-6596/887/1/012025/pdf |
Similar Articles
| ID | Score | Article |
|---|---|---|
41548
|
Wang, SR; Song, AF; Qian, YF Predicting Smart Cities? Electricity Demands Using K-Means Clustering Algorithm in Smart Grid(2023)Computer Science And Information Systems, 20, 2 | |
| 39821
|
Qiu, YF; Li, XZ; Zheng, W; Hu, QH; Wei, ZM; Yue, YQ The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city(2017) | |
| 39599
|
Shah, SSM; Meganathan, S Machine learning approach for power consumption model based on monsoon data for smart cities applications(2021)Computational Intelligence, 37, 3 | |
| 44368
|
Costa, C; Santos, MY Improving Cities Sustainability through the Use of Data Mining in a Context of Big City Data(2015) |