Maximum demand flexibility from the demand response of a big group of residential homes

Jiexiang Wu1, Li Li1, Jiangfeng Zhang2
1School of Electrical and Data Engineering, University of Technology Sydney, Ultimo, 2007, NSW, Australia
2Department of Automotive Engineering, Clemson University, Greenville 29607, SC, USA

Tài liệu tham khảo

TRANSPORT, 2011 Australia, 2021 Action, 2015 Söder, 2018, A review of demand side flexibility potential in northern Europe, Renew Sustain Energy Rev, 91, 654, 10.1016/j.rser.2018.03.104 Freire-Barceló, 2022, A literature review of explicit demand flexibility providing energy services, Electr Power Syst Res, 209, 10.1016/j.epsr.2022.107953 Elghitani, 2017, Aggregating a large number of residential appliances for demand response applications, IEEE Trans Smart Grid, 9, 5092, 10.1109/TSG.2017.2679702 Duman, 2021, A home energy management system with an integrated smart thermostat for demand response in smart grids, Sustainable Cities Soc, 65, 10.1016/j.scs.2020.102639 Erdinc, 2016, End-user comfort oriented day-ahead planning for responsive residential HVAC demand aggregation considering weather forecasts, IEEE Trans Smart Grid, 8, 362, 10.1109/TSG.2016.2556619 Shao, 2012, Development of physical-based demand response-enabled residential load models, IEEE Trans Power Syst, 28, 607, 10.1109/TPWRS.2012.2208232 Pipattanasomporn, 2012, An algorithm for intelligent home energy management and demand response analysis, IEEE Trans Smart Grid, 3, 2166, 10.1109/TSG.2012.2201182 Zehir, 2012, Demand side management by controlling refrigerators and its effects on consumers, Energy Convers Manage, 64, 238, 10.1016/j.enconman.2012.05.012 Goldsworthy, 2018, The off-grid PV-battery powered home revisited; the effects of high efficiency air-conditioning and load shifting, Sol Energy, 172, 69, 10.1016/j.solener.2018.02.051 Wang, 2019, Dynamic control strategy of residential air conditionings considering environmental and behavioral uncertainties, Appl Energy, 250, 1312, 10.1016/j.apenergy.2019.04.184 Zhang, 2021, An optimal scheduling scheme for smart home electricity considering demand response and privacy protection, Int J Electr Power Energy Syst, 132, 10.1016/j.ijepes.2021.107159 Mohsenian-Rad, 2010, Optimal residential load control with price prediction in real-time electricity pricing environments, IEEE Trans Smart Grid, 1, 120, 10.1109/TSG.2010.2055903 Chen, 2012, Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization, IEEE Trans Smart Grid, 3, 1822, 10.1109/TSG.2012.2212729 Tang, 2018, Hierarchical control strategy for residential demand response considering time-varying aggregated capacity, Int J Electr Power Energy Syst, 97, 165, 10.1016/j.ijepes.2017.11.001 Gomez-Herrera, 2019, Optimization-based estimation of power capacity profiles for activity-based residential loads, Int J Electr Power Energy Syst, 104, 664, 10.1016/j.ijepes.2018.07.023 Conejo, 2010, Real-time demand response model, IEEE Trans Smart Grid, 1, 236, 10.1109/TSG.2010.2078843 Shirazi, 2015, Optimal residential appliance scheduling under dynamic pricing scheme via HEMDAS, Energy Build, 93, 40, 10.1016/j.enbuild.2015.01.061 Zhang, 2020, Survey-based air-conditioning demand response for critical peak reduction considering residential consumption behaviors, Energy Rep, 6, 3303, 10.1016/j.egyr.2020.11.242 Logenthiran, 2012, Demand side management in smart grid using heuristic optimization, IEEE Trans Smart Grid, 3, 1244, 10.1109/TSG.2012.2195686 Jiang, 2020, A residential load scheduling based on cost efficiency and consumer’s preference for demand response in smart grid, Electr Power Syst Res, 186, 10.1016/j.epsr.2020.106410 Setlhaolo, 2014, Optimal scheduling of household appliances for demand response, Electr Power Syst Res, 116, 24, 10.1016/j.epsr.2014.04.012 Clot, 2015, Compensation and rewards for environmental services (CRES) and efficient design of contracts in developing countries. Behavioral insights from a natural field experiment, Ecol Econom, 113, 85, 10.1016/j.ecolecon.2015.02.021 Fehr, 2002, Psychological foundations of incentives, Eur Econ Rev, 46, 687, 10.1016/S0014-2921(01)00208-2 Wolak, 2007 Vivekananthan, 2014, Demand response for residential appliances via customer reward scheme, IEEE Trans Smart Grid, 5, 809, 10.1109/TSG.2014.2298514 Balliet, 2011, Reward, punishment, and cooperation: a meta-analysis., Psychol Bull, 137, 594, 10.1037/a0023489 Asadinejad, 2018, Evaluation of residential customer elasticity for incentive based demand response programs, Electr Power Syst Res, 158, 26, 10.1016/j.epsr.2017.12.017 Liu, 2015, A collaborative design of aggregated residential appliances and renewable energy for demand response participation, IEEE Trans Ind Appl, 51, 3561, 10.1109/TIA.2015.2427286 Pecan. Street, 2018 Austin Energy, 2021 Shi, 2019, Estimating the profile of incentive-based demand response (IBDR) by integrating technical models and social-behavioral factors, IEEE Trans Smart Grid, 11, 171, 10.1109/TSG.2019.2919601 Time and date, 2021 Endeavour Energy, 2018 Energex, 2021