2023 - Research.com Electronics and Electrical Engineering in Iran Leader Award
2022 - Research.com Electronics and Electrical Engineering in Iran Leader Award
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.
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
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.
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.
Short-term hourly load forecasting using time-series modeling with peak load estimation capability
IEEE Transactions on Power Systems (2001)
Day-ahead price forecasting of electricity markets by a new fuzzy neural network
IEEE Transactions on Power Systems (2006)
Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm
N. Amjady;F. Keynia.
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)
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)
Short-Term Load Forecast of Microgrids by a New Bilevel Prediction Strategy
Nima Amjady;Farshid Keynia;Hamidreza Zareipour.
IEEE Transactions on Smart Grid (2010)
Short-Term Bus Load Forecasting of Power Systems by a New Hybrid Method
IEEE Transactions on Power Systems (2007)
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)
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)
Wind power forecast using wavelet neural network trained by improved Clonal selection algorithm
Hamed Chitsaz;Nima Amjady;Hamidreza Zareipour.
Energy Conversion and Management (2015)
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