Journal ArticleDOI
Optimal scheduling of plug-in electric vehicles and renewable micro-grid in energy and reserve markets considering demand response program
TLDR
This paper investigates the optimal energy management problem of the RMG with the presence of PEVs to minimize the cost through generating power with its local generators and trading energy with the power market considering the market price.About:
This article is published in Journal of Cleaner Production.The article was published on 2018-06-10. It has received 153 citations till now. The article focuses on the topics: Demand response & Energy management.read more
Citations
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Journal ArticleDOI
Review on Scheduling, Clustering, and Forecasting Strategies for Controlling Electric Vehicle Charging: Challenges and Recommendations
Ali Saadon Al-Ogaili,Tengku Juhana Tengku Hashim,N. A. Rahmat,Agileswari K. Ramasamy,Marayati Binti Marsadek,M. Faisal,Mahammad A. Hannan +6 more
TL;DR: This manuscript comprehensively reviews EV control charging strategies using real-world data and classifies them into scheduling, clustering, and forecasting strategies, and provides potential recommendations.
Multi-sources model and control algorithm of an energy management system
TL;DR: In this article, the authors presented the multi-sources energy models and ruled based feedback control algorithm of an energy management system (EMS) for light electric vehicle (LEV), i.e., scooters.
Journal ArticleDOI
Optimal operation of an energy hub considering the uncertainty associated with the power consumption of plug-in hybrid electric vehicles using information gap decision theory
TL;DR: A novel model is developed to estimate the uncertainty associated with the power consumption of PHEVs during trips using information gap decision theory (IGDT) under risk-averse and risk-seeking strategies, and simulation results demonstrate that the proposed method maximizes the objective function under the risk-neutral and risk
Journal ArticleDOI
Charging demand of Plug-in Electric Vehicles: Forecasting travel behavior based on a novel Rough Artificial Neural Network approach
Hamidreza Jahangir,Hanif Tayarani,Ali Ahmadian,Masoud Aliakbar Golkar,Jaume Miret,Mohammad Tayarani,H. Oliver Gao,H. Oliver Gao +7 more
TL;DR: To forecast PEV-TB an artificial intelligence-based method -feedforward and recurrent Artificial Neural Networks (ANN) with Levenberg Marquardt (LM) training method based on Rough structure - is developed and reduces the aggregators’ financial loss approximately by 16 $/PEV per year compared to the conventional methods.
Journal ArticleDOI
Co-optimized bidding strategy of an integrated wind-thermal-photovoltaic system in deregulated electricity market under uncertainties
Hooman Khaloie,Amir Abdollahi,Miadreza Shafie-khah,Pierluigi Siano,Sayyad Nojavan,Amjad Anvari-Moghaddam,Joao P. S. Catalao +6 more
TL;DR: Simulation results illustrate that not only the integrated participation of wind-thermal-photovoltaic resources increases the producer's expected profit, but also decreases the amount of the produced pollution by the thermal units.
References
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Journal ArticleDOI
Optimal Charging Strategies for Unidirectional Vehicle-to-Grid
TL;DR: Simulations on a hypothetical group of 10 000 commuter EVs in the Pacific Northwest verify that the optimal algorithms increase aggregator profits while reducing system load impacts and customer costs.
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Demand response modeling considering Interruptible/Curtailable loads and capacity market programs
TL;DR: In this paper, the authors proposed an economic model of incentive-based and time-based demand response (DR) programs for the Iranian power system, and evaluated the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption.
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Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services
TL;DR: A V2G algorithm is developed to optimize energy and ancillary services scheduling that maximizes profits to the aggregator while providing additional system flexibility and peak load shaving to the utility and low costs of EV charging to the customer.
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Advances and trends of energy storage technology in Microgrid
Xingguo Tan,Qingmin Li,Hui Wang +2 more
TL;DR: In this paper, a full scope review of the principal energy storage technologies being developed so far, and the features and benefits of energy storage systems (ESSs) within the MG are analyzed in details including ESS configuration and topologies, power electronics interfaces, ESS control schemes for charging/discharging, control strategy of hybrid ESS as well as optimization of the renewable sources and ESS.
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Optimal planning and design of a renewable energy based supply system for microgrids
Omar Hafez,Kankar Bhattacharya +1 more
TL;DR: In this article, the optimal design, planning, sizing and operation of a hybrid, renewable energy based microgrid with the goal of minimizing the lifecycle cost, while taking into account environmental emissions is discussed.