His primary scientific interests are in Mathematical optimization, Electric power system, AC power, Wind power and Particle swarm optimization. Jamshid Aghaei has researched Mathematical optimization in several fields, including Electricity generation, Probabilistic logic, Power system simulation and Renewable energy. The concepts of his Renewable energy study are interwoven with issues in Pareto principle, Electricity and Electric power.
His work deals with themes such as Stochastic programming, Optimization problem, Demand response and Distributed generation, which intersect with Electric power system. His biological study spans a wide range of topics, including Load management and Operations research. His Wind power course of study focuses on Base load power plant and Dynamic demand, Peak demand, Environmental economics, Profit and Hybrid power.
His primary areas of study are Mathematical optimization, Electric power system, AC power, Wind power and Control theory. Mathematical optimization is represented through his Linear programming, Integer programming, Particle swarm optimization, Optimization problem and Stochastic programming research. Jamshid Aghaei interconnects Automotive engineering, Reliability engineering, Demand response and Renewable energy in the investigation of issues within Electric power system.
As part of one scientific family, he deals mainly with the area of Demand response, narrowing it down to issues related to the Smart grid, and often Electric vehicle. His study in AC power is interdisciplinary in nature, drawing from both Control engineering, Distributed generation, Stochastic optimization and Market clearing. His research integrates issues of Electricity generation, Probabilistic logic, Hybrid power and Energy storage in his study of Wind power.
Jamshid Aghaei mainly focuses on Mathematical optimization, Wind power, AC power, Electric power system and Robust optimization. Jamshid Aghaei works mostly in the field of Mathematical optimization, limiting it down to topics relating to Distribution networks and, in certain cases, Global optimal. His research investigates the connection between Wind power and topics such as Bidding that intersect with issues in Demand response, Electricity market and Hybrid power.
His research investigates the link between AC power and topics such as Integer programming that cross with problems in Distributed generation. His Electric power system research is multidisciplinary, incorporating perspectives in Automotive engineering, Reliability engineering and Renewable energy. His Renewable energy study combines topics in areas such as Wavelet transform, Energy management and Energy storage.
Jamshid Aghaei spends much of his time researching Mathematical optimization, Wind power, Linear programming, AC power and Variable renewable energy. Jamshid Aghaei integrates many fields in his works, including Mathematical optimization and Geographic information system. His Wind power research is multidisciplinary, incorporating elements of Stochastic programming, Renewable generation, Electricity and Bidding.
The Demand response research he does as part of his general Electricity study is frequently linked to other disciplines of science, such as News aggregator, therefore creating a link between diverse domains of science. His AC power research is within the category of Voltage. His studies deal with areas such as Robust optimization, Linearization and Benchmark as well as Variable renewable energy.
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Demand response in smart electricity grids equipped with renewable energy sources: A review
Jamshid Aghaei;Mohammad-Iman Alizadeh.
Renewable & Sustainable Energy Reviews (2013)
Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index
T. Niknam;M.R. Narimani;J. Aghaei;R. Azizipanah-Abarghooee.
Iet Generation Transmission & Distribution (2012)
Scenario-Based Multiobjective Volt/Var Control in Distribution Networks Including Renewable Energy Sources
T. Niknam;M. Zare;J. Aghaei.
IEEE Transactions on Power Delivery (2012)
Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)
Jamshid Aghaei;Mohammad-Iman Alizadeh.
Energy (2013)
Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security
N. Amjady;J. Aghaei;H.A. Shayanfar.
IEEE Transactions on Power Systems (2009)
A modified honey bee mating optimization algorithm for multiobjective placement of renewable energy resources
Taher Niknam;Seyed Iman Taheri;Jamshid Aghaei;Sajad Tabatabaei.
Applied Energy (2011)
Scenario-based dynamic economic emission dispatch considering load and wind power uncertainties
Jamshid Aghaei;Taher Niknam;Rasoul Azizipanah-Abarghooee;José M. Arroyo.
International Journal of Electrical Power & Energy Systems (2013)
A new modified teaching-learning algorithm for reserve constrained dynamic economic dispatch
Taher Niknam;Rasoul Azizipanah-Abarghooee;Jamshid Aghaei.
IEEE Transactions on Power Systems (2013)
Optimal Behavior of Electric Vehicle Parking Lots as Demand Response Aggregation Agents
M. Shafie-khah;E. Heydarian-Forushani;G.J. Osorio;F.A.S. Gil.
IEEE Transactions on Smart Grid (2016)
Generation and Transmission Expansion Planning: MILP–Based Probabilistic Model
Jamshid Aghaei;Nima Amjady;Amir Baharvandi;Mohammad-Amin Akbari.
IEEE Transactions on Power Systems (2014)
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