Fast frequency response constrained electric vehicle scheduling for low inertia power systems

Rezaei, 2015, Smart microgrid hierarchical frequency control ancillary service provision based on virtual inertia concept: An integrated demand response and droop controlled distributed generation framework, Energy Convers. Manage., 92, 287, 10.1016/j.enconman.2014.12.049 Fernández-Muñoz, 2020, Fast frequency control ancillary services: An international review, Renew. Sustain. Energy Rev., 120, 10.1016/j.rser.2019.109662 Su, 2020, Fast frequency response of inverter-based resources and its impact on system frequency characteristics, Global Energy Interconnect., 3, 475, 10.1016/j.gloei.2020.11.007 Prakash, 2019, Modified interval-based generator scheduling for PFR adequacy under uncertain PV generation, IET Gener. Trans. Distrib., 13, 3725, 10.1049/iet-gtd.2018.6391 Bañol Arias, 2020, Assessment of economic benefits for EV owners participating in the primary frequency regulation markets, Int. J. Electr. Power Energy Syst., 120, 10.1016/j.ijepes.2020.105985 Khamesipour, 2022, Component sizing of a series hybrid electric vehicle through artificial neural network, Energy Convers. Manage., 254, 10.1016/j.enconman.2022.115300 Bhatt, 2022, Optimal techno-economic feasibility study of net-zero carbon emission microgrid integrating second-life battery energy storage system, Energy Convers. Manage., 266, 10.1016/j.enconman.2022.115825 Meng, 2019, Fast frequency response from energy storage systems— A review of grid standards, projects and technical issues, IEEE Trans. Smart Grid, 11, 1566, 10.1109/TSG.2019.2940173 Li, 2012, Modeling of plug-in hybrid electric vehicle charging demand in probabilistic power flow calculations, IEEE Trans. Smart Grid, 3, 492, 10.1109/TSG.2011.2172643 Tookanlou, 2021, A comprehensive day-ahead scheduling strategy for electric vehicles operation, Int. J. Electr. Power Energy Syst., 131, 10.1016/j.ijepes.2021.106912 İnci, 2022, Integrating electric vehicles as virtual power plants: A comprehensive review on vehicle-to-grid (V2G) concepts, interface topologies, marketing and future prospects, J. Energy Storage, 55, 10.1016/j.est.2022.105579 Mozafar, 2018, Innovative appraisement of smart grid operation considering large-scale integration of electric vehicles enabling V2G and G2V systems, Electr. Power Syst. Res., 154, 245, 10.1016/j.epsr.2017.08.024 Khooban, 2017, Secondary load frequency control of time-delay stand-alone microgrids with electric vehicles, IEEE Trans. Ind. Electron., 65, 7416, 10.1109/TIE.2017.2784385 Rezkalla, 2018, Comparison between synthetic inertia and fast frequency containment control based on single phase EVs in a microgrid, Appl. Energy, 210, 764, 10.1016/j.apenergy.2017.06.051 Marinelli, 2016, Validating a centralized approach to primary frequency control with series-produced electric vehicles, J. Energy Storage, 7, 63, 10.1016/j.est.2016.05.008 Teng, 2017, Challenges on primary frequency control and potential solution from EVs in the future GB electricity system, Appl. Energy, 194, 353, 10.1016/j.apenergy.2016.05.123 Wangsupphaphol, 2022, Design and development of auxiliary energy storage for battery hybrid electric vehicle, J. Energy Storage, 51, 10.1016/j.est.2022.104533 Liu, 2013, Decentralized vehicle-to-grid control for primary frequency regulation considering charging demands, IEEE Trans. Power Syst., 28, 3480, 10.1109/TPWRS.2013.2252029 Liu, 2016, EV dispatch control for supplementary frequency regulation considering the expectation of EV owners, IEEE Trans. Smart Grid, 9, 3763, 10.1109/TSG.2016.2641481 Karfopoulos, 2015, Distributed coordination of electric vehicles providing V2G regulation services, IEEE Trans. Power Syst., 31, 2834, 10.1109/TPWRS.2015.2472957 Liu, 2014, Vehicle-to-grid control for supplementary frequency regulation considering charging demands, IEEE Trans. Power Syst., 30, 3110, 10.1109/TPWRS.2014.2382979 Figgener, 2022, The influence of frequency containment reserve flexibilization on the economics of electric vehicle fleet operation, J. Energy Storage, 53, 10.1016/j.est.2022.105138 Sánchez, 2018, Impact of electric vehicle charging control on the frequency response: study of the GB system, 1 O’Malley, 2022, Frequency response from aggregated V2G chargers with uncertain EV connections, IEEE Trans. Power Syst., 10.1109/TPWRS.2022.3202607 Sanchez Gorostiza, 2020, Multi-objective optimal provision of fast frequency response from EV clusters, IET Gener. Trans. Distrib., 14, 5580, 10.1049/iet-gtd.2020.0717 Blatiak, 2022, Value of optimal trip and charging scheduling of commercial electric vehicle fleets with Vehicle-to-Grid in future low inertia systems, Sustain. Energy Grids Netw., 31 O’Malley, 2020, Value of fleet vehicle to grid in providing transmission system operator services, 1 Ela, 2012, Studying the variability and uncertainty impacts of variable generation at multiple timescales, IEEE Trans. Power Syst., 27, 1324, 10.1109/TPWRS.2012.2185816 Teng, 2016, Stochastic scheduling with inertia-dependent fast frequency response requirements, IEEE Trans. Power Syst., 31, 1557, 10.1109/TPWRS.2015.2434837 Pandžić, 2015, Toward cost-efficient and reliable unit commitment under uncertainty, IEEE Trans. Power Syst., 31, 970, 10.1109/TPWRS.2015.2434848 Nosair, 2016, Economic dispatch under uncertainty: The probabilistic envelopes approach, IEEE Trans. Power Syst., 32, 1701, 10.1109/TPWRS.2016.2602942 Zhang, 2014, A convex model of risk-based unit commitment for day-ahead market clearing considering wind power uncertainty, IEEE Trans. Power Syst., 30, 1582, 10.1109/TPWRS.2014.2357816 Kaur, 2016, Net load forecasting for high renewable energy penetration grids, Energy, 114, 1073, 10.1016/j.energy.2016.08.067 Sepasi, 2017, Very short term load forecasting of a distribution system with high PV penetration, Renew. Energy, 106, 142, 10.1016/j.renene.2017.01.019 Jin, 2014, Short-term net feeder load forecasting of microgrid considering weather conditions, 1205 Li, 2012, Applications of Bayesian methods in wind energy conversion systems, Renew. Energy, 43, 1, 10.1016/j.renene.2011.12.006 Loucks, 2017, An introduction to probability, statistics, and uncertainty, Water Resour. Syst. Plan. Manag., 213, 10.1007/978-3-319-44234-1_6 Martin, 2016 Kruschke, 2014 Shafie-khah, 2015, Optimal behavior of electric vehicle parking lots as demand response aggregation agents, IEEE Trans. Smart Grid, 7, 2654, 10.1109/TSG.2015.2496796 Kushwaha, 2020, PFR constrained energy storage and interruptible load scheduling under high RE penetration, IET Gener. Trans. Distrib., 14, 3070, 10.1049/iet-gtd.2019.1059 Krishnamurthy, 2016, An 8-zone test system based on ISO New England data: Development and application, IEEE Trans. Power Syst., 31, 234, 10.1109/TPWRS.2015.2399171 Wind speed and Solar irradiance data, [Online]. Available: http://www.soda-pro.com/. (Accessed 25 january 2022). Prakash, 2018, Frequency response constrained modified interval scheduling under wind uncertainty, IEEE Trans. Sustain. Energy, 9, 302, 10.1109/TSTE.2017.2731941 Wind turbine data for power calculation, URL https://www.suzlon.com/pdf/S111-product-brochure-May-2020.pdf. Trovato, 2019, Unit commitment with inertia-dependent and multispeed allocation of frequency response services, IEEE Trans. Power Syst., 34, 1537, 10.1109/TPWRS.2018.2870493 Bian, 2018, Demand side contributions for system inertia in the GB power system, IEEE Trans. Power Syst., 33, 3521, 10.1109/TPWRS.2017.2773531