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Demand response in electrical energy supply: An optimal real time pricing approach

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  1. Fotouhi Ghazvini, Mohammad Ali & Canizes, Bruno & Vale, Zita & Morais, Hugo, 2013. "Stochastic short-term maintenance scheduling of GENCOs in an oligopolistic electricity market," Applied Energy, Elsevier, vol. 101(C), pages 667-677.
  2. Li, Lanlan & Gong, Chengzhu & Wang, Deyun & Zhu, Kejun, 2013. "Multi-agent simulation of the time-of-use pricing policy in an urban natural gas pipeline network: A case study of Zhengzhou," Energy, Elsevier, vol. 52(C), pages 37-43.
  3. Fróes Lima, Carlos Alberto & Portillo Navas, José Ricardo, 2012. "Smart metering and systems to support a conscious use of water and electricity," Energy, Elsevier, vol. 45(1), pages 528-540.
  4. Soares, J. & Silva, M. & Sousa, T. & Vale, Z. & Morais, H., 2012. "Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization," Energy, Elsevier, vol. 42(1), pages 466-476.
  5. Chen, Yang & Hu, Mengqi & Zhou, Zhi, 2017. "A data-driven analytical approach to enable optimal emerging technologies integration in the co-optimized electricity and ancillary service markets," Energy, Elsevier, vol. 122(C), pages 613-626.
  6. Zhang, Qi & Mclellan, Benjamin C. & Tezuka, Tetsuo & Ishihara, Keiichi N., 2013. "A methodology for economic and environmental analysis of electric vehicles with different operational conditions," Energy, Elsevier, vol. 61(C), pages 118-127.
  7. Chou, Jui-Sheng & Tran, Duc-Son, 2018. "Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders," Energy, Elsevier, vol. 165(PB), pages 709-726.
  8. Dong, Jun & Xue, Guiyuan & Li, Rong, 2016. "Demand response in China: Regulations, pilot projects and recommendations – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 13-27.
  9. Fotouhi Ghazvini, Mohammad Ali & Faria, Pedro & Ramos, Sergio & Morais, Hugo & Vale, Zita, 2015. "Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market," Energy, Elsevier, vol. 82(C), pages 786-799.
  10. Pedro Faria & João Spínola & Zita Vale, 2018. "Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs," Energies, MDPI, vol. 11(8), pages 1-17, July.
  11. Pedro Faria & Zita Vale, 2019. "A Demand Response Approach to Scheduling Constrained Load Shifting," Energies, MDPI, vol. 12(9), pages 1-16, May.
  12. Adriano A. Santos & Filipe Pereira & António Ferreira da Silva & Nídia Caetano & Carlos Felgueiras & José Machado, 2023. "Electrification of a Remote Rural Farm with Solar Energy—Contribution to the Development of Smart Farming," Energies, MDPI, vol. 16(23), pages 1-17, November.
  13. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
  14. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
  15. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
  16. Wang, Huilong & Wang, Shengwei, 2021. "A hierarchical optimal control strategy for continuous demand response of building HVAC systems to provide frequency regulation service to smart power grids," Energy, Elsevier, vol. 230(C).
  17. Wang, Chen & Zhou, Kaile & Yang, Shanlin, 2017. "A review of residential tiered electricity pricing in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 533-543.
  18. Faber, Isaac & Lane, William & Pak, Wayne & Prakel, Mary & Rocha, Cheyne & Farr, John V., 2014. "Micro-energy markets: The role of a consumer preference pricing strategy on microgrid energy investment," Energy, Elsevier, vol. 74(C), pages 567-575.
  19. Hong, Seung Ho & Kim, Se Hwan & Kim, Gi Myung & Kim, Hyung Lae, 2014. "Experimental evaluation of BZ-GW (BACnet-ZigBee smart grid gateway) for demand response in buildings," Energy, Elsevier, vol. 65(C), pages 62-70.
  20. 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.
  21. He, Yongxiu & Wang, Bing & Wang, Jianhui & Xiong, Wei & Xia, Tian, 2012. "Residential demand response behavior analysis based on Monte Carlo simulation: The case of Yinchuan in China," Energy, Elsevier, vol. 47(1), pages 230-236.
  22. Jason Grant & Moataz Eltoukhy & Shihab Asfour, 2014. "Short-Term Electrical Peak Demand Forecasting in a Large Government Building Using Artificial Neural Networks," Energies, MDPI, vol. 7(4), pages 1-19, March.
  23. Chargui, Kaoutar & Zouadi, Tarik & Sreedharan, V. Raja & El Fallahi, Abdellah & Reghioui, Mohamed, 2023. "A novel robust exact decomposition algorithm for berth and quay crane allocation and scheduling problem considering uncertainty and energy efficiency," Omega, Elsevier, vol. 118(C).
  24. Sun, Zeyi & Li, Lin & Bego, Andres & Dababneh, Fadwa, 2015. "Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system," International Journal of Production Economics, Elsevier, vol. 165(C), pages 112-119.
  25. Luis Gomes & António Coelho & Zita Vale, 2022. "Assessment of Energy Customer Perception, Willingness, and Acceptance to Participate in Smart Grids—A Portuguese Survey," Energies, MDPI, vol. 16(1), pages 1-16, December.
  26. Ho-Sung Ryu & Mun-Kyeom Kim, 2020. "Two-Stage Optimal Microgrid Operation with a Risk-Based Hybrid Demand Response Program Considering Uncertainty," Energies, MDPI, vol. 13(22), pages 1-25, November.
  27. Daniel Icaza-Alvarez & Nestor Daniel Galan-Hernandez & Eber Enrique Orozco-Guillen & Francisco Jurado, 2023. "Smart Energy Planning in the Midst of a Technological and Political Change towards a 100% Renewable System in Mexico by 2050," Energies, MDPI, vol. 16(20), pages 1-26, October.
  28. Lu, Renzhi & Hong, Seung Ho & Zhang, Xiongfeng, 2018. "A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach," Applied Energy, Elsevier, vol. 220(C), pages 220-230.
  29. Faria, Pedro & Soares, Tiago & Vale, Zita & Morais, Hugo, 2014. "Distributed generation and demand response dispatch for a virtual power player energy and reserve provision," Renewable Energy, Elsevier, vol. 66(C), pages 686-695.
  30. Xue, Xue & Wang, Shengwei & Sun, Yongjun & Xiao, Fu, 2014. "An interactive building power demand management strategy for facilitating smart grid optimization," Applied Energy, Elsevier, vol. 116(C), pages 297-310.
  31. Aftab Ahmed Almani & Xueshan Han, 2023. "Real-Time Pricing-Enabled Demand Response Using Long Short-Time Memory Deep Learning," Energies, MDPI, vol. 16(5), pages 1-13, March.
  32. Boukettaya, Ghada & Krichen, Lotfi, 2014. "A dynamic power management strategy of a grid connected hybrid generation system using wind, photovoltaic and Flywheel Energy Storage System in residential applications," Energy, Elsevier, vol. 71(C), pages 148-159.
  33. Ahmed Ismail & Mustafa Baysal, 2023. "Dynamic Pricing Based on Demand Response Using Actor–Critic Agent Reinforcement Learning," Energies, MDPI, vol. 16(14), pages 1-19, July.
  34. Paulo Oliveira & Margarida Vaz Pato, 2014. "Time-Of-Use Electricity Tariffs With Smart Meters," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(2), pages 59-74.
  35. Sousa, Tiago & Morais, Hugo & Soares, João & Vale, Zita, 2012. "Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints," Applied Energy, Elsevier, vol. 96(C), pages 183-193.
  36. Woo, C.K. & Li, R. & Shiu, A. & Horowitz, I., 2013. "Residential winter kWh responsiveness under optional time-varying pricing in British Columbia," Applied Energy, Elsevier, vol. 108(C), pages 288-297.
  37. Tang, Rui & Wang, Shengwei & Shan, Kui & Cheung, Howard, 2018. "Optimal control strategy of central air-conditioning systems of buildings at morning start period for enhanced energy efficiency and peak demand limiting," Energy, Elsevier, vol. 151(C), pages 771-781.
  38. Frank Beckenbach & Maria Daskalakis & David Hofmann, 2018. "Agent-Based Analysis of Industrial Dynamics and Paths of Environmental Policy: The Case of Non-renewable Energy Production in Germany," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 953-994, October.
  39. Cruz, Marco R.M. & Fitiwi, Desta Z. & Santos, Sérgio F. & Catalão, João P.S., 2018. "A comprehensive survey of flexibility options for supporting the low-carbon energy future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 338-353.
  40. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
  41. Hong, Seung Ho & Yu, Mengmeng & Huang, Xuefei, 2015. "A real-time demand response algorithm for heterogeneous devices in buildings and homes," Energy, Elsevier, vol. 80(C), pages 123-132.
  42. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
  43. Kwon, Pil Seok & Østergaard, Poul, 2014. "Assessment and evaluation of flexible demand in a Danish future energy scenario," Applied Energy, Elsevier, vol. 134(C), pages 309-320.
  44. Numbi, B.P. & Zhang, J. & Xia, X., 2014. "Optimal energy management for a jaw crushing process in deep mines," Energy, Elsevier, vol. 68(C), pages 337-348.
  45. Zhang, Yunchao & Islam, Md Monirul & Sun, Zeyi & Yang, Sijia & Dagli, Cihan & Xiong, Haoyi, 2018. "Optimal sizing and planning of onsite generation system for manufacturing in Critical Peaking Pricing demand response program," International Journal of Production Economics, Elsevier, vol. 206(C), pages 261-267.
  46. Cortés-Arcos, Tomás & Bernal-Agustín, José L. & Dufo-López, Rodolfo & Lujano-Rojas, Juan M. & Contreras, Javier, 2017. "Multi-objective demand response to real-time prices (RTP) using a task scheduling methodology," Energy, Elsevier, vol. 138(C), pages 19-31.
  47. Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
  48. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.
  49. Khemakhem, Siwar & Rekik, Mouna & Krichen, Lotfi, 2017. "A flexible control strategy of plug-in electric vehicles operating in seven modes for smoothing load power curves in smart grid," Energy, Elsevier, vol. 118(C), pages 197-208.
  50. Gomes, A. & Antunes, C. Henggeler & Martinho, J., 2013. "A physically-based model for simulating inverter type air conditioners/heat pumps," Energy, Elsevier, vol. 50(C), pages 110-119.
  51. Juliano Camargo & Fred Spiessens & Chris Hermans, 2018. "A Network Flow Model for Price-Responsive Control of Deferrable Load Profiles," Energies, MDPI, vol. 11(3), pages 1-17, March.
  52. Soares, Ana & Antunes, Carlos Henggeler & Oliveira, Carlos & Gomes, Álvaro, 2014. "A multi-objective genetic approach to domestic load scheduling in an energy management system," Energy, Elsevier, vol. 77(C), pages 144-152.
  53. Marques, Vítor & Bento, Nuno & Costa, Paulo Moisés, 2014. "The “Smart Paradox”: Stimulate the deployment of smart grids with effective regulatory instruments," Energy, Elsevier, vol. 69(C), pages 96-103.
  54. Hovgaard, Tobias Gybel & Larsen, Lars F.S. & Edlund, Kristian & Jørgensen, John Bagterp, 2012. "Model predictive control technologies for efficient and flexible power consumption in refrigeration systems," Energy, Elsevier, vol. 44(1), pages 105-116.
  55. Campillo, Javier & Dahlquist, Erik & Wallin, Fredrik & Vassileva, Iana, 2016. "Is real-time electricity pricing suitable for residential users without demand-side management?," Energy, Elsevier, vol. 109(C), pages 310-325.
  56. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
  57. Ming, Zeng & Song, Xue & Mingjuan, Ma & Lingyun, Li & Min, Cheng & Yuejin, Wang, 2013. "Historical review of demand side management in China: Management content, operation mode, results assessment and relative incentives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 470-482.
  58. Dai, Yeming & Sun, Xilian & Qi, Yao & Leng, Mingming, 2021. "A real-time, personalized consumption-based pricing scheme for the consumptions of traditional and renewable energies," Renewable Energy, Elsevier, vol. 180(C), pages 452-466.
  59. Baratsas, Stefanos G. & Niziolek, Alexander M. & Onel, Onur & Matthews, Logan R. & Floudas, Christodoulos A. & Hallermann, Detlef R. & Sorescu, Sorin M. & Pistikopoulos, Efstratios N., 2022. "A novel quantitative forecasting framework in energy with applications in designing energy-intelligent tax policies," Applied Energy, Elsevier, vol. 305(C).
  60. Luis Gomes & Carlos Ramos & Aria Jozi & Bruno Serra & Lucas Paiva & Zita Vale, 2019. "IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach," Future Internet, MDPI, vol. 11(3), pages 1-21, March.
  61. Daniel Ramos & Pedro Faria & Zita Vale & João Mourinho & Regina Correia, 2020. "Industrial Facility Electricity Consumption Forecast Using Artificial Neural Networks and Incremental Learning," Energies, MDPI, vol. 13(18), pages 1-18, September.
  62. Kharrati, Saeed & Kazemi, Mostafa & Ehsan, Mehdi, 2016. "Equilibria in the competitive retail electricity market considering uncertainty and risk management," Energy, Elsevier, vol. 106(C), pages 315-328.
  63. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2016. "Power demand control scenarios for smart grid applications with finite number of appliances," Applied Energy, Elsevier, vol. 162(C), pages 83-98.
  64. Daniel Ramos & Mahsa Khorram & Pedro Faria & Zita Vale, 2021. "Load Forecasting in an Office Building with Different Data Structure and Learning Parameters," Forecasting, MDPI, vol. 3(1), pages 1-14, March.
  65. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2014. "Scheduling policies for two-state smart-home appliances in dynamic electricity pricing environments," Energy, Elsevier, vol. 69(C), pages 455-469.
  66. Alagoz, B. Baykant & Kaygusuz, Asim & Akcin, Murat & Alagoz, Serkan, 2013. "A closed-loop energy price controlling method for real-time energy balancing in a smart grid energy market," Energy, Elsevier, vol. 59(C), pages 95-104.
  67. Innocent Kamwa & Leila Bagherzadeh & Atieh Delavari, 2023. "Integrated Demand Response Programs in Energy Hubs: A Review of Applications, Classifications, Models and Future Directions," Energies, MDPI, vol. 16(11), pages 1-21, May.
  68. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
  69. Wei, Zhichen & Calautit, John, 2023. "Predictive control of low-temperature heating system with passive thermal mass energy storage and photovoltaic system: Impact of occupancy patterns and climate change," Energy, Elsevier, vol. 269(C).
  70. Sana Iqbal & Mohammad Sarfraz & Mohammad Ayyub & Mohd Tariq & Ripon K. Chakrabortty & Michael J. Ryan & Basem Alamri, 2021. "A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
  71. Pedro Faria & Zita Vale & José Baptista, 2015. "Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation," Energies, MDPI, vol. 8(6), pages 1-17, June.
  72. Fernando Lezama & Ricardo Faia & Pedro Faria & Zita Vale, 2020. "Demand Response of Residential Houses Equipped with PV-Battery Systems: An Application Study Using Evolutionary Algorithms," Energies, MDPI, vol. 13(10), pages 1-18, May.
  73. Li, Longxi, 2021. "Coordination between smart distribution networks and multi-microgrids considering demand side management: A trilevel framework," Omega, Elsevier, vol. 102(C).
  74. Ferrari, Lorenzo & Esposito, Fabio & Becciani, Michele & Ferrara, Giovanni & Magnani, Sandro & Andreini, Mirko & Bellissima, Alessandro & Cantù, Matteo & Petretto, Giacomo & Pentolini, Massimo, 2017. "Development of an optimization algorithm for the energy management of an industrial Smart User," Applied Energy, Elsevier, vol. 208(C), pages 1468-1486.
  75. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.
  76. Silva, Hendrigo Batista da & Santiago, Leonardo P., 2018. "On the trade-off between real-time pricing and the social acceptability costs of demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1513-1521.
  77. Numbi, B.P. & Xia, X., 2016. "Optimal energy control of a crushing process based on vertical shaft impactor," Applied Energy, Elsevier, vol. 162(C), pages 1653-1661.
  78. Omid Abrishambaf & Pedro Faria & Luis Gomes & João Spínola & Zita Vale & Juan M. Corchado, 2017. "Implementation of a Real-Time Microgrid Simulation Platform Based on Centralized and Distributed Management," Energies, MDPI, vol. 10(6), pages 1-14, June.
  79. Garnier, Ernesto & Madlener, Reinhard, 2014. "Day-Ahead versus Intraday Valuation of Demand-Side Flexibility for Photovoltaic and Wind Power Systems," FCN Working Papers 17/2014, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  80. Irina A. Firsova & Dinara G. Vasbieva & Andrey V. Losyakov & Viktoriia S. Arhipova & Andrey A. Pavlushin, 2018. "Development of Active Consumer Concept on Energy Market," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 8-13.
  81. Wang, Yong & Li, Lin, 2015. "Time-of-use electricity pricing for industrial customers: A survey of U.S. utilities," Applied Energy, Elsevier, vol. 149(C), pages 89-103.
  82. Zixu Liu & Xiaojun Zeng & Fanlin Meng, 2018. "An Integration Mechanism between Demand and Supply Side Management of Electricity Markets," Energies, MDPI, vol. 11(12), pages 1-23, November.
  83. Guo, Peiyang & Li, Victor O.K. & Lam, Jacqueline C.K., 2017. "Smart demand response in China: Challenges and drivers," Energy Policy, Elsevier, vol. 107(C), pages 1-10.
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