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Topic · Electrical and Electronic Engineering

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. 9.9% 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%
3.9k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+80%
the tick is no change
Largest producer
China
55% of the 10 largest, 2022-now
Energy Load and Power Forecasting

Which countries lead Energy Load and Power Forecasting research?

By volume, China and India publish the most (6.8k and 2.2k works in 2022-now).

By volume, 2022-now

  1. 1 China 6.8k works
  2. 2 India 2.2k works
  3. 3 United States 1.1k works
  4. 4 Türkiye 469 works
  5. 5 Indonesia 405 works
  6. 6 United Kingdom 395 works
  7. 7 Germany 306 works
  8. 8 Iran 288 works
  9. 9 South Korea 276 works
  10. 10 Italy 269 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.

China: 54.8%India: 17.5%United States: 8.5%Türkiye: 3.8%6 others listed: 15.5%55%largest
China6,835 · 54.8%India2,179 · 17.5%United States1,062 · 8.5%Türkiye469 · 3.8%6 others listed1,939 · 15.5%

Shares of the rows listed above, not of the whole node.

Which institutions lead Energy Load and Power Forecasting research?

By volume in 2022-now, State Grid Corporation of China (China) publishes the most Energy Load and Power Forecasting research, followed by North China Electric Power University and China Southern Power Grid (China).

By volume, 2022-now

  1. 1 State Grid Corporation of China (China)China 316 works
  2. 2 North China Electric Power UniversityChina 298 works
  3. 3 China Southern Power Grid (China)China 186 works
  4. 4 Shanghai Electric (China)China 171 works
  5. 5 Tsinghua UniversityChina 90 works
  6. 6 Chinese Academy of SciencesChina 90 works
  7. 7 Hohai UniversityChina 83 works
  8. 8 Zhejiang UniversityChina 76 works
  9. 9 Southeast UniversityChina 74 works
  10. 10 Huazhong University of Science and TechnologyChina 73 works

Who are the leading researchers in Energy Load and Power Forecasting?

The most-cited researchers publishing on Energy Load and Power Forecasting include Yoshua Bengio, Robert John Tibshirani and Wei Huang.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Robert John Tibshirani United States 396k citations
  3. 3 Wei Huang China 267k citations
  4. 4 Yi Ping Cui United States 261k citations
  5. 5 Philippe Ciais France 237k citations
  6. 6 Kai You Wang China 224k citations
  7. 7 Frede Blaabjerg Denmark 203k citations
  8. 8 Seeram Ramakrishna Singapore 186k citations
  9. 9 Qiang Zhang China 184k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Energy Load and Power Forecasting?

The most cited paper in Energy Load and Power Forecasting is "Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting" (Haoyi Zhou, Shanghang Zhang, Jieqi Peng et al., 2021), with 6,999 citations. Next come "Forecasting with artificial neural networks:" (4,238) and "Linear system theory and design" (3,686).

Most cited papers
#PaperReleasedCitations
1 Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou, Shanghang Zhang, Jieqi Peng et al. · Proceedings of the AAAI Conference on Artificial Intelligence Conference paperOpen access 18 May 2021 6,999
2 Forecasting with artificial neural networks: Guoqiang Zhang, B. Eddy Patuwo, Michael Y. Hu · International Journal of Forecasting Mar 1998 4,238
3 Linear system theory and design Stephen Mark Barnett · Automatica May 1986 3,686
4 Doubly fed induction generator usingback-to-back PWM convertersand its application to variable-speed wind-energy generation Ruben S. Pena, John Clare, Greg M Asher · IEE Proceedings - Electric Power Applications 10 May 1996 2,766
5 Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network Weicong Kong, Zhao Yang Dong, Youwei Jia et al. · IEEE Transactions on Smart Grid 18 Sep 2017 2,652
All 99 most cited papers, with filters and sorting

Where is Energy Load and Power Forecasting research done?

The largest centres of Energy Load and Power Forecasting research in 2022-now 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-now

  1. 1 BeijingChina 1.3k works
  2. 2 ShanghaiChina 485 works
  3. 3 NanjingChina 449 works
  4. 4 GuangzhouChina 402 works
  5. 5 WuhanChina 302 works
  6. 6 Xi'anChina 230 works
  7. 7 ChennaiIndia 212 works
  8. 8 ChengduChina 202 works
  9. 9 HangzhouChina 199 works
  10. 10 TianjinChina 178 works

Where it is the local speciality

  1. BaishanCN · 24.2 works39×
  2. YangpuCN · 63.0 works20×
  3. Jilin CityCN · 72.3 works13×
  4. Beijing69.8 works10×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Energy Load and Power Forecasting than the world average.

See Energy Load and Power Forecasting on the map

Where is the best place to study Energy Load and Power Forecasting?

Among universities, judged by research, Macau University of Science and Technology, Huaiyin Institute of Technology and Sejong University score highest, combining citation excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 27.1%fractional works in this field (log) →share of work in the world top 10% →North Carolina State…Huaiyin Institute of…Sejong UniversityMacau University of …
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Citation excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Macau University of Science and TechnologyChina 70.130.4%8.5×28 +398.2%
2Huaiyin Institute of TechnologyChina 66.341.6%15.1×16 +312.1%
3Sejong UniversitySouth Korea 62.531.8%4.4×12 +29.4%
4North Carolina State UniversityUnited States 62.344.2%2.1×18 +108.5%
5North China Electric Power UniversityChina 57.912.3%29.1×298 +7.2%
6Hong Kong Polytechnic UniversityChina 57.620.9%2.5×34 +126.3%
7City University of Hong KongChina 57.627.3%1.8×16 +9.0%
8Nanjing University of Information Science and TechnologyChina 56.618.0%9.5×58 +181.6%
9Dongbei University of Finance and EconomicsChina 55.527.3%22.3×20 -31.1%
10Huazhong University of Science and TechnologyChina 55.417.2%2.6×73 +27.2%

Universities only. The score blends citation excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Energy Load and Power Forecasting, country by country

Is Energy Load and Power Forecasting research growing?

Output in 2022-2025 was 80% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Energy Load and Power Forecasting.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Energy Load and Power Forecasting as a percentage of every work published that year, 0.079% in 2024.

still counting0.050%0.10%Energy Load and Power Forecasting0.082% in 202519801990200020102020

Fractional works of Energy Load and Power Forecasting over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Energy Load and Power Forecasting9.9% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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