D-Index & Metrics Best Publications
Electronics and Electrical Engineering
Iran
2023

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 61 Citations 11,268 206 World Ranking 929 National Ranking 3

Research.com Recognitions

Awards & Achievements

2023 - Research.com Electronics and Electrical Engineering in Iran Leader Award

2022 - Research.com Electronics and Electrical Engineering in Iran Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Mathematical optimization
  • Artificial intelligence
  • Electrical engineering

Nima Amjady focuses on Mathematical optimization, Electric power system, Artificial neural network, Electricity and Electricity market. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Economic dispatch and Robustness. His study in the field of Load forecasting also crosses realms of Function.

His research in Artificial neural network intersects with topics in Control engineering and Economic forecasting. Nima Amjady has included themes like Smart grid and Renewable energy in his Electricity study. His Electricity market research integrates issues from Market price and Econometrics.

His most cited work include:

  • Short-term hourly load forecasting using time-series modeling with peak load estimation capability (385 citations)
  • Day-ahead price forecasting of electricity markets by a new fuzzy neural network (306 citations)
  • Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm (234 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Electric power system, Mathematical optimization, Control theory, Electricity market and Electricity. His Electric power system research is multidisciplinary, incorporating elements of Artificial neural network, Reliability engineering, Control engineering and Voltage. He has researched Artificial neural network in several fields, including Evolutionary algorithm and Feature selection.

His research in Mathematical optimization is mostly focused on Optimization problem. His Control theory research is multidisciplinary, relying on both Islanding and Computation. His Electricity market research also works with subjects such as

  • Operations research that intertwine with fields like Volatility,
  • Econometrics, which have a strong connection to Electricity price forecasting.

He most often published in these fields:

  • Electric power system (46.70%)
  • Mathematical optimization (45.81%)
  • Control theory (19.38%)

What were the highlights of his more recent work (between 2016-2021)?

  • Mathematical optimization (45.81%)
  • Electric power system (46.70%)
  • Control theory (19.38%)

In recent papers he was focusing on the following fields of study:

Nima Amjady mainly investigates Mathematical optimization, Electric power system, Control theory, Wind power and Robustness. His studies deal with areas such as AC power, Microgrid and Power flow as well as Mathematical optimization. His work carried out in the field of Electric power system brings together such families of science as Reliability engineering, Transmission, Electric power transmission, Voltage and Linear programming.

His work on Frequency response as part of general Control theory research is frequently linked to Decomposition, bridging the gap between disciplines. His Wind power research includes themes of Unavailability, Computation and Cluster analysis. His study in Robustness is interdisciplinary in nature, drawing from both Distribution networks, Nondeterministic algorithm and Linear decision rules.

Between 2016 and 2021, his most popular works were:

  • Solar energy forecasting based on hybrid neural network and improved metaheuristic algorithm (130 citations)
  • A New Feature Selection Technique for Load and Price Forecast of Electrical Power Systems (119 citations)
  • Operation Scheduling of Battery Storage Systems in Joint Energy and Ancillary Services Markets (93 citations)

In his most recent research, the most cited papers focused on:

  • Electrical engineering
  • Artificial intelligence
  • Mathematical optimization

His primary areas of study are Mathematical optimization, Robustness, Wind power, Electricity and AC power. His research integrates issues of Bounded function, Power system simulation and Solar power in his study of Mathematical optimization. His work focuses on many connections between Solar power and other disciplines, such as Metaheuristic, that overlap with his field of interest in Artificial neural network.

His Wind power research incorporates themes from Electric power system, Profit, Electricity market and Compressed air energy storage, Energy storage. Nima Amjady mostly deals with Power flow in his studies of Electric power system. Within one scientific family, Nima Amjady focuses on topics pertaining to Bidding under Electricity, and may sometimes address concerns connected to Reliability engineering, Arbitrage and Operations research.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Short-term hourly load forecasting using time-series modeling with peak load estimation capability

N. Amjady.
IEEE Transactions on Power Systems (2001)

677 Citations

Day-ahead price forecasting of electricity markets by a new fuzzy neural network

N. Amjady.
IEEE Transactions on Power Systems (2006)

490 Citations

Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm

N. Amjady;F. Keynia.
Energy (2009)

367 Citations

Flexibility in future power systems with high renewable penetration: A review

M.I. Alizadeh;M. Parsa Moghaddam;N. Amjady;P. Siano.
Renewable & Sustainable Energy Reviews (2016)

319 Citations

Day-Ahead Price Forecasting of Electricity Markets by Mutual Information Technique and Cascaded Neuro-Evolutionary Algorithm

N. Amjady;F. Keynia.
IEEE Transactions on Power Systems (2009)

293 Citations

Short-Term Load Forecast of Microgrids by a New Bilevel Prediction Strategy

Nima Amjady;Farshid Keynia;Hamidreza Zareipour.
IEEE Transactions on Smart Grid (2010)

280 Citations

Short-Term Bus Load Forecasting of Power Systems by a New Hybrid Method

N. Amjady.
IEEE Transactions on Power Systems (2007)

262 Citations

A New Feature Selection Technique for Load and Price Forecast of Electrical Power Systems

Oveis Abedinia;Nima Amjady;Hamidreza Zareipour.
IEEE Transactions on Power Systems (2017)

244 Citations

Wind Power Prediction by a New Forecast Engine Composed of Modified Hybrid Neural Network and Enhanced Particle Swarm Optimization

N Amjady;F Keynia;H Zareipour.
IEEE Transactions on Sustainable Energy (2011)

240 Citations

Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm

Hamed Chitsaz;Nima Amjady;Hamidreza Zareipour.
Energy Conversion and Management (2015)

232 Citations

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