S
Sayyad Nojavan
Researcher at University of Bonab
Publications - 174
Citations - 5970
Sayyad Nojavan is an academic researcher from University of Bonab. The author has contributed to research in topics: Demand response & Renewable energy. The author has an hindex of 42, co-authored 153 publications receiving 4085 citations. Previous affiliations of Sayyad Nojavan include University of Tabriz.
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Stochastic optimization of energy hub operation with consideration of thermal energy market and demand response
TL;DR: It is shown that adding new source of heat energy for providing demand of consumers with market mechanism changes the optimal operation point of multi carrier energy system.
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A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism
TL;DR: In this article, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed.
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Optimal bidding strategy of electricity retailers using robust optimisation approach considering time-of-use rate demand response programs under market price uncertainties
TL;DR: In this article, a robust optimisation approach is proposed for decision making of electricity retailers, considering the effect of DRP on total procurement cost, an optimal bidding strategy is proposed of electricity retailer with the time-based model of demand response programs (DRP) in the electricity market.
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Energy management of wind-PV-storage-grid based large electricity consumer using robust optimization technique
Dongmin Yu,Dongmin Yu,Tao Zhang,Tao Zhang,Guixiong He,Sayyad Nojavan,Kittisak Jermsittiparsert,Noradin Ghadimi +7 more
TL;DR: The robust optimization (RO) technique is provided to investigate the uncertainty of the pool market price in the presented problem and the purchased cost to the LEC is reduced 8.2% and 6.5% in risk-neutral and robust strategies, respectively.
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Optimal allocation of capacitors in radial/mesh distribution systems using mixed integer nonlinear programming approach
TL;DR: In this paper, a new mixed integer nonlinear programming approach for capacitor placement in radial/mesh distribution systems that determine the optimal sitting and sizing of capacitors with an objective of reduction power loss and investment capacitor costs is presented.