A Novel Model of Emergency Demand Response Program for Optimal Aggregators’ Strategy

References

• Electric Power Research Institute (EPRI) – Definition of Demand-Side Management. http://www.epri.com. Accessed: June 2, 2015.
   Google Scholar
• W. Huang, N. Zhang, C. Kang, M. Li and M. Huo, “From demand response to integrated demand response: Review and prospect of research and application,” Prot Control Mod Power Syst., vol. 4, no. 1, pp. 12, 2019. DOI: 10.1186/s41601-019-0126-4.
   Google Scholar
• S. Borlease, Smart Grids: Infrastructure, Technology and Solutions. Boca Raton: CRC Press, 2013.
   Google Scholar
• M. Muratori, B.-A. Schuelke-Leech and G. Rizzoni, “Role of residential demand response in modern electricity markets,” Renew. Sustain. Energy Rev., vol. 33, pp. 546–553, 2014. DOI: 10.1016/j.rser.2014.02.027.
   Web of Science ®Google Scholar
• H. Aalami, M. P. Moghaddam and G. Yousefi, “Evaluation of nonlinear models for time-based rates demand response programs,” Int. J. Elect. Power Energy Syst., vol. 65, pp. 282–290, 2015. DOI: 10.1016/j.ijepes.2014.10.021.
   Web of Science ®Google Scholar
• N. Venkatesan, J. Solanki and S. K. Solanki, “Demand response model and its effects on voltage profile of a distribution system,” Paper Presented at the 2011 IEEE Power and Energy Society General Meeting, 2011.
   Google Scholar
• S. Zhao and Z. Ming, “Modeling demand response under time-of-use pricing,” Paper Presented at the 2014 International Conference on Power System Technology, 2014.
   Google Scholar
• M. H. Imani, M. J. Ghadi, S. Ghavidel and L. Li, “Demand response modeling in microgrid operation: A review and application for incentive-based and time-based programs,” Renew Sustain Energy Rev., vol. 94, pp. 486–499, 2018. DOI: 10.1016/j.rser.2018.06.017.
   Web of Science ®Google Scholar
• S. Mohajeryami, IN. Moghaddam, M. Doostan, B. Vatani and P. Schwarz, “A novel economic model for price-based demand response,” Electric Power Syst. Res., vol. 135, pp. 1–9, 2016. DOI: 10.1016/j.epsr.2016.03.026.
   Web of Science ®Google Scholar
• R. Sharifi, S. H. Fathi, A. Anvari-Moghaddam, J. M. Guerrero and V. Vahidinasab, “An economic customer-oriented demand response model in electricity markets,” Paper Presented at the 2018 IEEE International Conference on Industrial Technology (ICIT), 2018. DOI: 10.1109/ICIT.2018.8352340.
   Google Scholar
• R. Sharifi, A. Anvari-Moghaddam, S. H. Fathi, J. M. Guerrero and V. Vahidinasab, “An optimal market-oriented demand response model for price-responsive residential consumers,” Energy Efficien., vol. 12, no. 3, pp. 803–815, 2019. DOI: 10.1007/s12053-018-9713-x.
   Web of Science ®Google Scholar
• A. Badri and H. Kashefi, “Optimal bidding strategy of retailers in a mixed pool-bilateral market considering demand response programs,” Paper Presented at the 2013 Smart Grid Conference (SGC), 2013. DOI: 10.1109/SGC.2013.6733825.
   Google Scholar
• V.-H. Bui, H.-M. Kim and N.-O. Song, “Applying demand response based on TOU and EDRP to optimal microgrid operation,” IJSH, vol. 9, no. 5, pp. 41–50, 2015. DOI: 10.14257/ijsh.2015.9.5.05.
   Google Scholar
• M. F. Ribeiro, M. Shafie-khah, G. J. Osório, N. Hajibandeh and J. P. Catalão, Optimal demand response scheme for power systems including renewable energy resources considering system reliability and air pollution. Paper Presented at the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe, 2017).
   Google Scholar
• N. Hajibandeh, M. Shafie-Khah, G. J. Osório, J. Aghaei and J. P. Catalão, “A heuristic multi-objective multi-criteria demand response planning in a system with high penetration of wind power generators,” APPl. Energy, vol. 212, pp. 721–732, 2018. DOI: 10.1016/j.apenergy.2017.12.076.
   Web of Science ®Google Scholar
• M. Shafie-Khah, M. Ribeiro, N. Hajibandeh, G. J. Osório and J. P. Catalão, “A multi-objective method to design demand response strategies for power systems including wind power generation,” Paper Presented at the 2018 Power Systems Computation Conference (PSCC), 2018. DOI: 10.23919/PSCC.2018.8442739.
   Google Scholar
• N. Hajibandeh, M. Ehsan, S. Soleymani, M. Shafie-Khah and J. P. Catalão, “Prioritizing the effectiveness of a comprehensive set of demand response programs on wind power integration,” Int. J. Elect. Power & Energy Systems, vol. 107, pp. 149–158, 2019. DOI: 10.1016/j.ijepes.2018.11.024.
   Web of Science ®Google Scholar
• NYISO Auxiliary Market Operations. Demand response manual. New York Independent System Operator. Available: http://www.nyso.com; May, 2019.
   Google Scholar
• M. Vahedipour-Dahraie, A. Anvari-Moghaddam and J. M. Guerrero, “Evaluation of reliability in risk-constrained scheduling of autonomous microgrids with demand response and renewable resources,” IET Renew. Power Generat., vol. 12, no. 6, pp. 657–667, 2018. DOI: 10.1049/iet-rpg.2017.0720.
   Web of Science ®Google Scholar
• M. H. Imani, K. Yousefpour, M. T. Andani and M. J. Ghadi, “Effect of changes in incentives and penalties on interruptible/curtailable demand response program in microgrid operation,” Paper Presented at the 2019 IEEE Texas Power and Energy Conference (TPEC), 2019. DOI: 10.1109/TPEC.2019.8662184.
   Google Scholar
• M. H. Imani, P. Niknejad and M. Barzegaran, “The impact of customers’ participation level and various incentive values on implementing emergency demand response program in microgrid operation,” Int. J. Elect. Power Energy Syst., vol. 96, pp. 114–125, 2018. DOI: 10.1016/j.ijepes.2017.09.038.
   Web of Science ®Google Scholar
• E. Dehnavi and H. Abdi, “Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem,” Energy, vol. 109, pp. 1086–1094, 2016. DOI: 10.1016/j.energy.2016.05.024.
   Web of Science ®Google Scholar
• G. Derakhshan, H. A. Shayanfar and A. Kazemi, “The optimization of demand response programs in smart grids,” Energy Policy, vol. 94, pp. 295–306, 2016. DOI: 10.1016/j.enpol.2016.04.009.
   Web of Science ®Google Scholar
• N. Kampelis, et al., “HVAC optimization genetic algorithm for industrial near-zero-energy building demand response,” Energies, vol. 12, no. 11, pp. 2177, 2019. DOI: 10.3390/en12112177.
   Web of Science ®Google Scholar
• P. A. Diamond, “National debt in a neoclassical growth model,” Amer. Econ. Rev., vol. 55, no. 5, pp. 1126–1150, 1965.
   Web of Science ®Google Scholar
• H. Aalami, M. P. Moghaddam and G. R. Yousefi, “Demand response modeling considering interruptible/curtailable loads and capacity market programs,” Appl. Energy, vol. 87, no. 1, pp. 243–250, 2010. DOI: 10.1016/j.apenergy.2009.05.041.
   Web of Science ®Google Scholar
• H. Abdi, E. Dehnavi and F. Mohammadi, “Dynamic economic dispatch problem integrated with demand response (DEDDR) considering non-linear responsive load models,” IEEE Trans. Smart Grid, vol. 7, no. 6, pp. 2586–2595, 2016. DOI: 10.1109/TSG.2015.2508779.
   Web of Science ®Google Scholar
• FERC. Staff Report, Assessment of demand response and advanced metering. [Online] Available: http://www.FERC.gov; 2008.
   Google Scholar
• H. Aalami, M. P. Moghaddam and G. Yousefi, “Modeling and prioritizing demand response programs in power markets,” Electric Power Syst. Res., vol. 80, no. 4, pp. 426–435, 2010. DOI: 10.1016/j.epsr.2009.10.007.
   Web of Science ®Google Scholar
• R. Oran’s, 2006, “Phase I results: Incentives and rate design for energy efficiency and demand response,” Lbnl-60133. Energy and Environmental Economics Inc, Carson City, NV, Google Scholar.
   Google Scholar
• R. V. Rao, V. J. Savsani and D. Vakharia, “Teaching–learning-based optimization: An optimization method for continuous non-linear large scale problems,” Inform. Sci., vol. 183, no. 1, pp. 1–15, 2012. DOI: 10.1016/j.ins.2011.08.006.
   Web of Science ®Google Scholar