Energy Load and Power Forecasting
Energy Load and Power Forecasting is a research topic within Electrical and Electronic Engineering. Science Explorer counts 39k research works in it since 1950. 21.0% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the methods and techniques for forecasting electricity prices and load demand, with an emphasis on short-term forecasting using neural networks, ARIMA models, and probabilistic approaches. The cluster also covers topics related to wind power generation, deep learning applications, and renewable energy forecasting.
- Electricity Price Forecasting
- Load Forecasting
- Short-Term Forecasting
- Neural Networks
- Wind Power Generation
- ARIMA Models
- Probabilistic Forecasting
- Deep Learning
- Renewable Energy
- Time Series Analysis
- Research works
- 39k fractional, since 1950
- In the world top 10%
- 8.3k per year above
- Top-10% rate
- 21.0% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +121% the tick is no change
Which countries lead Energy Load and Power Forecasting research?
By volume, China and India publish the most (6.1k and 2k works in 2022–2025).
By volume, 2022–2025
- 1 China 6.1k works
- 2 India 2k works
- 3 United States 967 works
- 4 Türkiye 425 works
- 5 Indonesia 377 works
- 6 United Kingdom 364 works
- 7 Iran 274 works
- 8 Germany 272 works
- 9 Italy 253 works
- 10 ?? 252 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Energy Load and Power Forecasting research?
By volume in 2022–2025, North China Electric Power University publishes the most Energy Load and Power Forecasting research, followed by State Grid Corporation of China (China) and China Southern Power Grid (China).
By volume, 2022–2025
- 1 North China Electric Power UniversityChina 268 works
- 2 State Grid Corporation of China (China)China 227 works
- 3 China Southern Power Grid (China)China 173 works
- 4 Shanghai Electric (China)China 155 works
- 5 Tsinghua UniversityChina 81 works
- 6 Hohai UniversityChina 74 works
- 7 Huazhong University of Science and TechnologyChina 68 works
- 8 Southeast UniversityChina 67 works
- 9 Zhejiang UniversityChina 63 works
- 10 Vellore Institute of Technology UniversityIndia 63 works
Who are the leading researchers in Energy Load and Power Forecasting?
The most-cited researchers publishing on Energy Load and Power Forecasting include Seyedali Mirjalili, Georgios B. Giannakis and Melinda Marquis.
- 1 Seyedali Mirjalili Australia 7.6k citations
- 2 Georgios B. Giannakis United States 4.6k citations
- 3 Melinda Marquis United States 4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Energy Load and Power Forecasting research done?
The largest centres of Energy Load and Power Forecasting research in 2022–2025 are Beijing (China), Shanghai (China), Nanjing (China) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Baishan, Yangpu and Jilin City.
Largest cities, 2022–2025
Where it is the local speciality
- BaishanCN · 21.8 works38×
- YangpuCN · 57.5 works20×
- Jilin CityCN · 67.5 works13×
- Beijing66.6 works10.0×
Location quotient: how much more of its research is in Energy Load and Power Forecasting than the world average.
Where is the best place to study Energy Load and Power Forecasting?
Among universities, judged by research, Dongbei University of Finance and Economics, Zhejiang University of Finance and Economics and Nanjing University of Information Science and Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Dongbei University of Finance and EconomicsChina | 70.4 | 51.4% | 19.6× | 19 | +1629.1% |
| 2 | Zhejiang University of Finance and EconomicsChina | 62.4 | 40.6% | 10.8× | 12 | +359.3% |
| 3 | Nanjing University of Information Science and TechnologyChina | 62.1 | 32.8% | 7.9× | 50 | +217.4% |
| 4 | Macau University of Science and TechnologyMacau | 61.0 | 47.3% | 7.6× | 26 | — |
| 5 | Huaiyin Institute of TechnologyChina | 60.2 | 66.8% | 13.7× | 15 | -46.1% |
| 6 | National Technical University of AthensGreece | 58.8 | 39.1% | 8.0× | 32 | +129.3% |
| 7 | North China Electric Power UniversityChina | 58.2 | 19.1% | 25.5× | 268 | +17.5% |
| 8 | Singidunum UniversitySerbia | 58.0 | 49.2% | 19.6× | 11 | — |
| 9 | Maulana Azad National Institute of TechnologyIndia | 55.8 | 23.3% | 9.8× | 22 | +336.2% |
| 10 | Shandong University of Finance and EconomicsChina | 54.5 | 42.6% | 10.4× | 13 | — |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Energy Load and Power Forecasting research growing?
Output in 2018–2022 was 121% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Energy Load and Power Forecasting.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.