Residential loads flexibility potential for demand response using energy consumption patterns and user segments

Citations

Cited by:

1. Luo, Xi & Liu, Yanfeng & Feng, Pingan & Gao, Yuan & Guo, Zhenxiang, 2021. "Optimization of a solar-based integrated energy system considering interaction between generation, network, and demand side," Applied Energy, Elsevier, vol. 294(C).
2. Bruno Mota & Luis Gomes & Pedro Faria & Carlos Ramos & Zita Vale & Regina Correia, 2021. "Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events," Energies, MDPI, vol. 14(2), pages 1-14, January.
3. Beccali, Marco & Bellia, Laura & Fragliasso, Francesca & Bonomolo, Marina & Zizzo, Gaetano & Spada, Gennaro, 2020. "Assessing the lighting systems flexibility for reducing and managing the power peaks in smart grids," Applied Energy, Elsevier, vol. 268(C).
4. Zhang, Yuanshi & Qian, Wenyan & Ye, Yujian & Li, Yang & Tang, Yi & Long, Yu & Duan, Meimei, 2023. "A novel non-intrusive load monitoring method based on ResNet-seq2seq networks for energy disaggregation of distributed energy resources integrated with residential houses," Applied Energy, Elsevier, vol. 349(C).
5. Jaka Rober & Leon Maruša & Miloš Beković, 2023. "A Machine Learning Application for the Energy Flexibility Assessment of a Distribution Network for Consumers," Energies, MDPI, vol. 16(17), pages 1-20, August.
6. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.
7. Song, Yuguang & Chen, Fangjian & Xia, Mingchao & Chen, Qifang, 2022. "The interactive dispatch strategy for thermostatically controlled loads based on the source–load collaborative evolution," Applied Energy, Elsevier, vol. 309(C).
8. Naderi, Shayan & Heslop, Simon & Chen, Dong & Watts, Scott & MacGill, Iain & Pignatta, Gloria & Sproul, Alistair, 2023. "Clustering based analysis of residential duck curve mitigation through solar pre-cooling: A case study of Australian housing stock," Renewable Energy, Elsevier, vol. 216(C).
9. Chen, Xiao & Zanocco, Chad & Flora, June & Rajagopal, Ram, 2022. "Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation," Applied Energy, Elsevier, vol. 318(C).
10. O'Connell, Sarah & Reynders, Glenn & Keane, Marcus M., 2021. "Impact of source variability on flexibility for demand response," Energy, Elsevier, vol. 237(C).
11. Liu, Yinyan & Ma, Jin & Xing, Xinjie & Liu, Xinglu & Wang, Wei, 2022. "A home energy management system incorporating data-driven uncertainty-aware user preference," Applied Energy, Elsevier, vol. 326(C).
12. Eunjung Lee & Keon Baek & Jinho Kim, 2020. "Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach," Energies, MDPI, vol. 13(23), pages 1-12, December.
13. Liu, Hong & Zhao, Yue & Gu, Chenghong & Ge, Shaoyun & Yang, Zan, 2021. "Adjustable capability of the distributed energy system: Definition, framework, and evaluation model," Energy, Elsevier, vol. 222(C).
14. Song, Kwonsik & Anderson, Kyle & Lee, SangHyun, 2020. "An energy-cyber-physical system for personalized normative messaging interventions: Identification and classification of behavioral reference groups," Applied Energy, Elsevier, vol. 260(C).
15. Zhao, Pengxiang & Dong, Zhao Yang & Meng, Ke & Kong, Weicong & Yang, Jiajia, 2021. "Household power usage pattern filtering-based residential electricity plan recommender system," Applied Energy, Elsevier, vol. 298(C).
16. Etxandi-Santolaya, Maite & Colet-Subirachs, Alba & Barbero, Mattia & Corchero, Cristina, 2023. "Development of a platform for the assessment of demand-side flexibility in a microgrid laboratory," Applied Energy, Elsevier, vol. 331(C).
17. Kong, Xiangyu & Wang, Zhengtao & Liu, Chao & Zhang, Delong & Gao, Hongchao, 2023. "Refined peak shaving potential assessment and differentiated decision-making method for user load in virtual power plants," Applied Energy, Elsevier, vol. 334(C).
18. Jung, Wooyoung & Jazizadeh, Farrokh, 2020. "Energy saving potentials of integrating personal thermal comfort models for control of building systems: Comprehensive quantification through combinatorial consideration of influential parameters," Applied Energy, Elsevier, vol. 268(C).
19. Kang, J. & Reiner, D., 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Cambridge Working Papers in Economics 2143, Faculty of Economics, University of Cambridge.
    • Jieyi Kang & David Reiner, 2021. "Identifying residential consumption patterns using data-mining techniques: A large-scale study of smart meter data in Chengdu, China," Working Papers EPRG2114, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
20. Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
21. Ku, Arthur Lin & Qiu, Yueming (Lucy) & Lou, Jiehong & Nock, Destenie & Xing, Bo, 2022. "Changes in hourly electricity consumption under COVID mandates: A glance to future hourly residential power consumption pattern with remote work in Arizona," Applied Energy, Elsevier, vol. 310(C).
22. Yang, Wangwang & Shi, Jing & Li, Shujian & Song, Zhaofang & Zhang, Zitong & Chen, Zexu, 2022. "A combined deep learning load forecasting model of single household resident user considering multi-time scale electricity consumption behavior," Applied Energy, Elsevier, vol. 307(C).
23. Song, Zhaofang & Shi, Jing & Li, Shujian & Chen, Zexu & Jiao, Fengshun & Yang, Wangwang & Zhang, Zitong, 2022. "Data-driven and physical model-based evaluation method for the achievable demand response potential of residential consumers' air conditioning loads," Applied Energy, Elsevier, vol. 307(C).
24. Luo, Na & Langevin, Jared & Chandra-Putra, Handi & Lee, Sang Hoon, 2022. "Quantifying the effect of multiple load flexibility strategies on commercial building electricity demand and services via surrogate modeling," Applied Energy, Elsevier, vol. 309(C).
25. Mishra, Kakuli & Basu, Srinka & Maulik, Ujjwal, 2022. "Load profile mining using directed weighted graphs with application towards demand response management," Applied Energy, Elsevier, vol. 311(C).
26. Troy Malatesta & Jessica K. Breadsell, 2022. "Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
27. Francesco Mancini & Jacopo Cimaglia & Gianluigi Lo Basso & Sabrina Romano, 2021. "Implementation and Simulation of Real Load Shifting Scenarios Based on a Flexibility Price Market Strategy—The Italian Residential Sector as a Case Study," Energies, MDPI, vol. 14(11), pages 1-21, May.
28. Kanakadhurga, Dharmaraj & Prabaharan, Natarajan, 2022. "Peer-to-Peer trading with Demand Response using proposed smart bidding strategy," Applied Energy, Elsevier, vol. 327(C).
29. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).
30. Hlalele, Thabo G. & Zhang, Jiangfeng & Naidoo, Raj M. & Bansal, Ramesh C., 2021. "Multi-objective economic dispatch with residential demand response programme under renewable obligation," Energy, Elsevier, vol. 218(C).
31. Felix Heider & Amra Jahic & Maik Plenz & Detlef Schulz, 2022. "Extended Residential Power Management Interface for Flexibility Communication and Uncertainty Reduction for Flexibility System Operators," Energies, MDPI, vol. 15(4), pages 1-23, February.
32. Olivella, Jordi & Domenech, Bruno & Calleja, Gema, 2021. "Potential of implementation of residential photovoltaics at city level: The case of London," Renewable Energy, Elsevier, vol. 180(C), pages 577-585.
33. Junker, Rune Grønborg & Kallesøe, Carsten Skovmose & Real, Jaume Palmer & Howard, Bianca & Lopes, Rui Amaral & Madsen, Henrik, 2020. "Stochastic nonlinear modelling and application of price-based energy flexibility," Applied Energy, Elsevier, vol. 275(C).
34. Bampoulas, Adamantios & Pallonetto, Fabiano & Mangina, Eleni & Finn, Donal P., 2022. "An ensemble learning-based framework for assessing the energy flexibility of residential buildings with multicomponent energy systems," Applied Energy, Elsevier, vol. 315(C).
35. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
36. Chen, Yongbao & Zhang, Lixin & Xu, Peng & Di Gangi, Alessandra, 2021. "Electricity demand response schemes in China: Pilot study and future outlook," Energy, Elsevier, vol. 224(C).
37. Milad Afzalan & Farrokh Jazizadeh, 2021. "Quantification of Demand-Supply Balancing Capacity among Prosumers and Consumers: Community Self-Sufficiency Assessment for Energy Trading," Energies, MDPI, vol. 14(14), pages 1-21, July.
38. Qingyang Wu, 2023. "Sustainable growth through industrial robot diffusion: Quasi‐experimental evidence from a Bartik shift‐share design," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 31(4), pages 1107-1133, October.
39. Kamalanathan Ganesan & Jo~ao Tom'e Saraiva & Ricardo J. Bessa, 2021. "Functional Model of Residential Consumption Elasticity under Dynamic Tariffs," Papers 2111.11875, arXiv.org.