Name
Abstract | ||
|---|---|---|
Forecasting of a single household electricity consumption (load) would be very useful for home energy management systems. However, the load forecasting of a single household is challenging due to the unpredictability of the individual household consumption behaviour. In this paper, a consumption scenario-based probabilistic load forecasting (PLF) method is developed. An energy consumption scenario analysis is proposed to compute the probability of occurrence of each consumption scenario of an individual household at any future time horizon. Then, the analysed results are integrated with PLF algorithms to provide the load forecasting of an individual household. Case studies are conducted to compare the performance of three conventional PLF algorithms and the performance of these three algorithms integrating with consumption scenario analysis. Results show that the proposed method outperforms the conventional PLF methods. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TSG.2021.3132039 | IEEE Transactions on Smart Grid |
Keywords | DocType | Volume |
Consumption scenario,Gaussian mixture distribution,individual residential consumer,probabilistic load forecasting | Journal | 13 |
Issue | ISSN | Citations |
2 | 1949-3053 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhong Xia | 1 | 0 | 0.34 |
| Hui Ma | 2 | 0 | 0.34 |
| Tapan Kumar Saha | 3 | 4 | 3.12 |
| Ruiyuan Zhang | 4 | 0 | 1.01 |