Search Results - MICROGRIDS

1

Dissertation/ Thesis

Stochastic Methods for the Evolving Electrical Distribution System

Contributors: Su, Wencong, Hong, Junho, Nudell, Thomas R., Wang, Mengqi (Maggie)

Subject Terms: Clustering Methods, Load Forcasting, Microgrid, Neural Networks, Smart Meters, Monte Carlo Simulations, Transformer Failures, Power Quality, Engineering

File Description: application/pdf

Relation: https://hdl.handle.net/2027.42/192515; jodonnel; https://dx.doi.org/10.7302/22420; orcid:0000-0001-5749-2585; ODonnell, John; 0000-0001-5749-2585

Availability: https://doi.org/10.7302/22420
https://hdl.handle.net/2027.42/192515

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2

Academic Journal

Distributed charging management of multi‐class electric vehicles with different charging priorities

Authors: Alsabbagh, Amro, Yin, He, Ma, Chengbin

Subject Terms: B8520 Transportation, B8120K Distributed power generation, B8110B Power system management, operation and economics, energy management approach, multiclass electric vehicles, distributed charging management, iterative methods, electric vehicle charging, battery powered vehicles, energy management systems, game theory, distributed power generation, B0290F Interpolation and function approximation (numerical analysis), B0240E Game theory, charging priorities, predefined charging priorities, consensus‐based distributed algorithm, EV utility, priority factor, total charging power, charging power distribution, battery energy storage system, noncooperative Stackelberg game, energy management problem, community microgrids, Electrical Engineering, Engineering

File Description: application/pdf

Relation: Alsabbagh, Amro; Yin, He; Ma, Chengbin (2019). "Distributed charging management of multi‐class electric vehicles with different charging priorities." IET Generation, Transmission & Distribution 13(22): 5257-5264.; https://hdl.handle.net/2027.42/166242; https://dx.doi.org/10.7302/165; IET Generation, Transmission & Distribution; Yoldaş, Y., Önen, A., Muyeen, S., et al.: ‘ Enhancing smart grid with microgrids: challenges and opportunities ’, Renw. Sust. Energy Rev., 2017, 72, pp. 205 – 214; Ravichandran, A., Sirouspour, S., Malysz, P., et al.: ‘ A chance‐constraints‐based control strategy for microgrids with energy storage and integrated electric vehicles ’, IEEE Trans. Smart Grid, 2018, 9, ( 1 ), pp. 346 – 359; Fletcher, R., Bomze, I.M., Demyanov, V.F., et al.: ‘ The sequential quadratic programming method ’ in ‘ Nonlinear optimization ’ ( Springer, Berlin, Germany, 2010 ); Rahmani‐Andebili, M., Mahmud, F.F.: ‘ An adaptive approach for PEVs charging management and reconfiguration of electrical distribution system penetrated by renewables ’, IEEE Trans. Ind. Inf., 2018, 14, ( 5 ), pp. 2001 – 2010; Zhang, T., Chen, X., Yu, Z., et al.: ‘ A monte carlo simulation approach to evaluate service capacities of EV charging and battery swapping stations ’, IEEE Trans. Ind. Inf., 2018, 14, ( 9 ), pp. 3914 – 3923; Kisacikoglu, M.C., Erden, F., Erdogan, N.: ‘ Distributed control of PEV charging based on energy demand forecast ’, IEEE Trans. Ind. Inf., 2018, 14, ( 1 ), pp. 332 – 341; Rahbari‐Asr, N., Chow, M.Y.: ‘ Cooperative distributed demand management for community charging of PHEV/PEVs based on KKT conditions and consensus networks ’, IEEE Trans. Ind. Inf., 2014, 10, ( 3 ), pp. 1907 – 1916; ‘Renewable resource data center, national renewable energy laboratory’, ( http://www.nrel.gov/rredc/ ), accessed 27 March 2019; ‘Commercial load datasets’, ( http://en.openei.org/datasets/files/961/pub/ ), accessed 27 March 2019; Piller, S., Perrin, M., Jossen, A.: ‘ Method for state of charge determination and their applications ’, J. Power Sources, 2001, 96, pp. 113 – 120; Zhang, J., Li, K.J., Wang, M., et al.: ‘ A bi‐level program for the planning of an islanded microgrid including caes ’, IEEE Trans. Ind. Appl., 2016, 52, ( 4 ), pp. 2768 – 2777; Kumar, K.N., Sivaneasan, B., So, P.L.: ‘ Impact of priority criteria on electric vehicle charge scheduling ’, IEEE Trans. Transp. Electrif., 2015, 1, ( 3 ), pp. 200 – 210; Eldjalil, C.D.A., Lyes, K.: ‘ Optimal priority‐queuing for EV charging‐discharging service based on cloud computing ’. 2017 IEEE Int. Conf. on Communications (ICC), Paris, France, 2017, pp. 1 – 6; Li, J., Li, C., Xu, Y., et al.: ‘ Noncooperative game‐based distributed charging control for plug‐in electric vehicles in distribution networks ’, IEEE Trans. Ind. Inf., 2018, 14, pp. 301 – 310; Yang, H., Xie, X., Vasilakos, A.V.: ‘ Noncooperative and cooperative optimization of electric vehicle charging under demand uncertainty: a robust Stackelberg game ’, IEEE Trans. Veh. Technol., 2016, 65, ( 3 ), pp. 1043 – 1058; Tushar, W., Saad, W., Poor, H.V., et al.: ‘ Economics of electric vehicle charging: a game theoretic approach ’, IEEE Trans. Smart Grid, 2012, 3, ( 4 ), pp. 1767 – 1778; Kikusato, H., Fujimoto, Y., Hanada, S., et al.: ‘ Electric vehicle charging management using auction mechanism for reducing PV curtailment in distribution systems ’, IEEET Sustain. Energy, 2019, doi:10.1109/TSTE.2019.2926998; Zhao, Y., He, X., Yao, Y., et al.: ‘ Plug‐in electric vehicle charging management via a distributed neurodynamic algorithm ’, Appl. Soft. Comput., 2019, 80, pp. 557 – 566; Liu, Y., Deng, R., Liang, H.: ‘ A stochastic game approach for PEV charging station operation in smart grid ’, IEEE Trans. Ind. Inf., 2018, 14, ( 3 ), pp. 969 – 979; Garcia‐Trivino, P., Torreglosa, J.P., Fernandez‐Ramirez, L.M., et al.: ‘ Decentralized fuzzy logic control of microgrid for electric vehicle charging station ’, IEEE J. Emerg. Sel. Top. Power Electron., 2018, 6, ( 2 ), pp. 726 – 737; Zhao, T., Li, Y., Pan, X., et al.: ‘ Real‐time optimal energy and reserve management of electric vehicle fast charging station: hierarchical game approach ’, IEEE Trans. Smart Grid, 2018, 9, ( 5 ), pp. 5357 – 5370; Wu, Y., Ravey, A., Chrenko, D., et al.: ‘ Demand side energy management of EV charging stations by approximate dynamic programming ’, Energy Convers. Manage., 2019, 196, pp. 878 – 890; Qi, J., Lai, C., Xu, B., et al.: ‘ Collaborative energy management optimization toward a green energy local area network ’, IEEE Trans. Ind. Inf., 2018, 14, ( 12 ), pp. 5410 – 5418; Yan, Q., Zhang, B., Kezunovic, M.: ‘ Optimized operational cost reduction for an EV charging station integrated with battery energy storage and PV generation ’, IEEE Trans. Smart Grid, 2019, 10, ( 2 ), pp. 2096 – 2106; Yao, L., Lim, W.H., Tsai, T.S.: ‘ A real‐time charging scheme for demand response in electric vehicle parking station ’, IEEE Trans. Smart Grid, 2017, 8, ( 1 ), pp. 52 – 62

Availability: https://doi.org/10.1049/iet-gtd.2019.0511
https://doi.org/10.7302/165
https://doi.org/10.1109/TSTE.2019.2926998
https://hdl.handle.net/2027.42/166242

Zugang prüfen (DOI)