Numéro |
Sci. Tech. Energ. Transition
Volume 79, 2024
Emerging Advances in Hybrid Renewable Energy Systems and Integration
|
|
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Numéro d'article | 77 | |
Nombre de pages | 20 | |
DOI | https://doi.org/10.2516/stet/2024073 | |
Publié en ligne | 9 octobre 2024 |
- Mohammad Esmaeil H., Vahid H., Barry H., Miadreza S., Pierluigi S. (2021) An overview of demand response: from its origins to the smart energy community, IEEE Access 9, 96851–96876. [CrossRef] [Google Scholar]
- Zhou Y.K. (2023) Sustainable energy sharing districts with electrochemical battery degradation in design, planning, operation and multi-objective optimisation, Renew. Energy 202, 1324–1341. [CrossRef] [Google Scholar]
- Zhou Y.K., Lund P.D. (2023) Peer-to-peer energy sharing and trading of renewable energy in smart communities – trading pricing models, decision-making and agent-based collaboration, Renew. Energy 207, 177–193. [CrossRef] [Google Scholar]
- Tang D., Fang Y.P., Zio E. (2023) Vulnerability analysis of demand-response with renewable energy integration in smart grids to cyber attacks and online detection methods, Reliab. Eng. Syst. Saf. 235, 109212. [CrossRef] [Google Scholar]
- Jordehi A.R. (2019) Optimisation of demand response in electric power systems, a review, Renew. Sustain. Energy Rev. 103, 308–319. [CrossRef] [Google Scholar]
- Li Y.C., Wang J.K., Zhang Y., Han Y.H. (2022) Day-ahead scheduling strategy for integrated heating and power system with high wind power penetration and integrated demand response: a hybrid stochastic/interval approach, Energy 253, 124189. [CrossRef] [Google Scholar]
- Salehimehr S., Behrooz T., Mostafa S. (2022) Short-term load forecasting in smart grids using artificial intelligence methods: A survey, J. Eng. 12, 1133–1142. [Google Scholar]
- Norouzi F., Karimi H., Jadid S. (2023) Stochastic electrical, thermal, cooling, water, and hydrogen management of integrated energy systems considering energy storage systems and demand response programs, J. Energy Storage 72, 108310. [CrossRef] [Google Scholar]
- Guo Z., Li G.Y., Zhou M., Li Z.F. (2018) Optimal operation of energy hub in business park considering integrated demand response, Power Syst. Technol. 42, 8, 2439–2448. (In Chinese). [Google Scholar]
- Wang L.Y., Lin J.L., Dong H.Q., Wang Y.Q., Zeng M. (2023) Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system, Energy 270, 126893. [CrossRef] [Google Scholar]
- Singh B., Kumar A. (2023) Optimal energy management and feasibility analysis of hybrid renewable energy sources with BESS and impact of electric vehicle load with demand response program, Energy 278, 127867. [CrossRef] [Google Scholar]
- Zhou Y.K. (2022) Demand response flexibility with synergies on passive PCM walls, BIPVs, and active air-conditioning system in a subtropical climate, Renew. Energy 199, 204–225. [CrossRef] [Google Scholar]
- Zhou Y.K., Zheng S.Q. (2020) Machine-learning based hybrid demand-side controller for high-rise office buildings with high energy flexibilities, Appl. Energy 262, 114416. [CrossRef] [Google Scholar]
- Zhou Y.K. (2022) Ocean energy applications for coastal communities with artificial intelligence – a state-of-the-art review, Energy AI 10, 100189. [CrossRef] [Google Scholar]
- Liang W., Li H., Zhan S., Chong A., Hong T. (2024) Energy flexibility quantification of a tropical net-zero office building using physically consistent neural network-based model predictive control, Adv. Appl. Energy 14, 100167. [CrossRef] [Google Scholar]
- Zhou Y.K. (2022) Demand response flexibility with synergies on passive PCM walls, BIPVs, and active air-conditioning system in a subtropical climate, Renew. Energy 199, 204–225. [CrossRef] [Google Scholar]
- Zhou Y.K. (2022) Low-carbon transition in smart city with sustainable airport energy ecosystems and hydrogen-based renewable-grid-storage-flexibility, Energy Rev. 1, 1, 100001. [CrossRef] [Google Scholar]
- Ahmed H.Y., AboRas M.K., Kotb H. (2023) A novel ultra local based-fuzzy PIDF controller for frequency regulation of a hybrid microgrid system with high renewable energy penetration and storage devices, Processes 11, 4, 1093. [CrossRef] [Google Scholar]
- Mehdi N., Babak M. (2014) Reliability assessment of incentive- and priced-based demand response programs in restructured power systems, Int. J. Elect. Power Energy Syst. 56, 3, 83–96. [CrossRef] [Google Scholar]
- Zhu J. (2023) Capacity optimization method of electrochemical energy storage system based on demand side response improved particle swarm optimization algorithm, J. Phys. Conf. Ser. 2418, 1, 012099. [CrossRef] [Google Scholar]
- Li Y.T., Wang X.J. (2022) Community integrated energy system multi-energy transaction decision considering user interaction, Processes 10, 9, 1794. [CrossRef] [Google Scholar]
- Yang K., Zhao Z.Y., Yu Y.J. (2022) Comprehensive evaluation of power system flexible resource value based on typical application scenarios, in: Zhang X., Ren H., Lu Y., Wang C. (Eds.), Proc. GEESD, IOS Press, pp. 176–182. https://ebooks.iospress.nl/doi/10.3233/ATDE220279. [Google Scholar]
- Amirhos B., Hamidreza A., Somayeh M. (2022) Day-ahead optimal scheduling of microgrid with considering demand side management under uncertainty, Electr. Power Syst. Res. 209, 107965. [CrossRef] [Google Scholar]
- Shankar P., Maurya R. (2023) Integration of solar powered DC homes to DC microgrid using dual active bridge converter, Int. J. Power Electron. 18, 2, 163–175. [CrossRef] [Google Scholar]
- Zhou Y.K., Lund P.D. (2023) Peer-to-peer energy sharing and trading of renewable energy in smart communities – trading pricing models, decision-making and agent-based collaboration, Renew. Energy 207, 177–193. [CrossRef] [Google Scholar]
- Yang H.J., Liu Z.K., Xie Y.X. (2023) A probabilistic liquefaction reliability evaluation system based on CatBoost-Bayesian considering uncertainty using CPT and Vs measurements, Soil Dyn. Earthq. Eng. 173, 108101. [CrossRef] [Google Scholar]
- Pérez-Uresti S.I., Gallardo G., Varvarezos D.K. (2023) Strategic investment planning for the hydrogen economy – a mixed integer non-linear framework for the development and capacity expansion of hydrogen supply chain networks, Comput. Chem. Eng. 179, 108412. [CrossRef] [Google Scholar]
- Luis G., António C., Zita V. (2022) Assessment of energy customer perception, willingness, and acceptance to participate in smart grids – a Portuguese Survey, Energies 16, 1, 270–270. [CrossRef] [Google Scholar]
- Musa M.J., Hasan M.A., Sivaparthipan C. (2023) Future smart grids creation and dimensionality reduction with signal handling on smart grid using targeted projection, Sustain. Comput. Inform. Syst. 39, 100897. [Google Scholar]
- Hossein T., Mohammad Reza A., Luis B. (2022) Profit maximization for an electricity retailer using a novel customers’ behavior leaning in a smart grid environment, Energy Rep. 8, 908–915. [Google Scholar]
- Jiang Z.H., Peng J.Q., Yin R.X., Hu M.M., Cao J.Y., Zou B. (2022) Stochastic modelling of flexible load characteristics of split-type air conditioners using grey-box modeling and random forest method, Energy Build. 273, 112370. [CrossRef] [Google Scholar]
- Zhang Y., Luo B., Cheng H. (2023) A multi-loads capacitive power transfer system for railway intelligent monitoring systems based on single relay plate, Int. J. Circuit Theory Appl. 52, 1, 79–96. [Google Scholar]
- Costa Vinicius B.F., Bonatto Benedito D., Silva Patrícia F. (2022) Optimizing Brazil’s regulated electricity market in the context of time-of-use rates and prosumers with energy storage systems, Uti. Policy 79, 101441. [CrossRef] [Google Scholar]
- Penizzotto F., Pringles R., Coria G. (2024) Valuation of investments in energy aggregator and storage systems by compound options, Energy 291, 130458. [CrossRef] [Google Scholar]
- Zeng B., Wu G., Wang J.H., Zhang J.H., Zeng M. (2017) Impact of behavior-driven demand response on supply adequacy in smart distribution systems, Appl. Energy 202, 125–137. [CrossRef] [Google Scholar]
- Balasubramanian S., Balachandra P. (2021) Effectiveness of demand response in achieving supply-demand matching in a renewables-dominated electricity system: a modeling approach, Renew. Sustain. Energy Rev. 147, 111245. [CrossRef] [Google Scholar]
- Ontario Power Authority. OPA demand response program [Online]. Available at http://demand-response-shop.com/DR-brochure_Oct9.pdf (accessed: 2018.8.19). [Google Scholar]
- Lu J. (2013) Modern Consumer behavior, Peking University Press, Beijing, China. (In Chinese). [Google Scholar]
- Nolan S., Malley M.O. (2015) Challenges and barriers to demand response deployment and evaluation, Appl. Energy 152, 1–10. [CrossRef] [Google Scholar]
- Hart S., Mas-Colell A. (2001) A reinforcement procedure leading to correlated equilibrium, in: Debreu G., Neuefeind W., Trockel W. (Eds.),Economics essays, Springer, Heidelberg, Berlin, Germany, pp. 181–200. https://link.springer.com/chapter/10.1007/978-3-662-04623-4_12. [CrossRef] [Google Scholar]
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