What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Electrical engineering
Miadreza Shafie-khah mostly deals with Demand response, Electricity market, Electric power system, Profit and Mathematical optimization.
His research integrates issues of Stochastic modelling, Telecommunications, Smart grid, Load management and Environmental economics in his study of Demand response.
His study in Electricity market is interdisciplinary in nature, drawing from both Control, Electric power industry and Data mining.
His work in Electric power system covers topics such as Operations research which are related to areas like Transport engineering.
He combines subjects such as Electric vehicle, Wind power, News aggregator and Perfect competition with his study of Profit.
His Mathematical optimization research focuses on subjects like Distributed generation, which are linked to Energy supply, Energy accounting and AC power.
His most cited work include:
- A Review of Smart Cities Based on the Internet of Things Concept (203 citations)
- Price forecasting of day-ahead electricity markets using a hybrid forecast method (171 citations)
- Iot-based smart cities: A survey (160 citations)
What are the main themes of his work throughout his whole career to date?
Miadreza Shafie-khah spends much of his time researching Demand response, Electric power system, Renewable energy, Mathematical optimization and Electricity market.
His work carried out in the field of Demand response brings together such families of science as Wind power, Load management, Smart grid and Operations research.
The Operations research study combines topics in areas such as Profit and News aggregator.
His study focuses on the intersection of Electric power system and fields such as Electric vehicle with connections in the field of Automotive engineering.
His studies in Renewable energy integrate themes in fields like Reliability engineering, Environmental economics and Energy storage.
His Electricity market study combines topics in areas such as Bidding and Microeconomics.
He most often published in these fields:
- Demand response (39.21%)
- Electric power system (28.31%)
- Renewable energy (23.90%)
What were the highlights of his more recent work (between 2019-2021)?
- Demand response (39.21%)
- Mathematical optimization (23.90%)
- Renewable energy (23.90%)
In recent papers he was focusing on the following fields of study:
Demand response, Mathematical optimization, Renewable energy, Distributed generation and Electric power system are his primary areas of study.
His Demand response research integrates issues from Wind power, Smart grid, Electricity market and Operations research.
His Electricity market research includes themes of Bidding and Photovoltaic system.
His Mathematical optimization research includes elements of Probability distribution and AC power.
Miadreza Shafie-khah has included themes like Reliability engineering, Automotive engineering, Energy storage, Electricity generation and Scheduling in his Renewable energy study.
In his study, which falls under the umbrella issue of Electric power system, Energy market and Battery is strongly linked to Electric vehicle.
Between 2019 and 2021, his most popular works were:
- Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model (44 citations)
- Co-optimized bidding strategy of an integrated wind-thermal-photovoltaic system in deregulated electricity market under uncertainties (43 citations)
- Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs (26 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Mathematical optimization
His primary scientific interests are in Mathematical optimization, Demand response, Renewable energy, Distributed generation and Electricity market.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Wind power and Monte Carlo method.
His Demand response study combines topics from a wide range of disciplines, such as Profit and Smart grid.
His studies deal with areas such as Energy management, Reliability engineering, Automotive engineering, Energy storage and Scheduling as well as Renewable energy.
In his study, Computation is inextricably linked to Integer programming, which falls within the broad field of Distributed generation.
The study incorporates disciplines such as Bidding, Photovoltaic system, Operations research and Dispatchable generation in addition to Electricity market.
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.
