189
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Scenario-Based Two-Stage Stochastic Scheduling of Microgrid Considered as the Responsible Load

& ORCID Icon
Pages 1614-1631 | Received 07 Nov 2019, Accepted 24 Mar 2020, Published online: 08 Jan 2021

References

  • F. Katiraei, R. Iravani, N. Hatziargyriou, and A. Dimeas, “Microgrids management,” IEEE Power Energy Mag., vol. 6, no. 3, pp. 54–65, May–Jun 2008. DOI: 10.1109/MPE.2008.918702.
  • C.-X. Dou, X.-B. Jia, H. Li and M.-F. Lv, “Multi-agent system based energy management of microgrid on day-ahead market transactions,” Elect Power Compon Syst., vol. 44, no. 12, pp. 1330–1344, May 2016. DOI: 10.1080/15325008.2016.1158216.
  • J. Jung and M. Villaran, “Optimal planning and design of hybrid renewable energy systems for microgrids,” Renew. Sust. Energy Rev, vol. 75, pp. 180–191, Aug. 2017. DOI: 10.1016/j.rser.2016.10.061.
  • S. Vachirasricirikul and I. Ngamroo, “Robust controller design of heat pump and plug-in hybrid electric vehicle for frequency control in a smart microgrid based on specified-structure mixed H2/H1 control technique,” Appl. Energy, vol. 88, no. 11, pp. 3860–3868, Nov. 2011. DOI: 10.1016/j.apenergy.2011.04.055.
  • A. Patel, H. S. V. S. Kumar Nunna and S. Doola, “Multi-agent-based forecast update methods for profit enhancement of intermittent distributed generators in a smart microgrid,” Elect Power Compon Syst., vol. 46, no. 16–17, pp. 1782–1794, Dec. 2018. DOI: 10.1080/15325008.2018.1517838.
  • A. Ghasemi and M. Enayatzare, “Optimal energy management of a renewable based isolated microgrid with pumped-storage unit and demand response,” Renew Energy, vol. 123, pp. 460–474, Aug. 2018. DOI: 10.1016/j.renene.2018.02.072.
  • A. G. Zamani, A. Zakariazadeh and S. Jadid, “Day-ahead resource scheduling of a renewable energy based virtual power plant,” Appl. Energy, vol. 169, pp. 324–340, May 2016. DOI: 10.1016/j.apenergy.2016.02.011.
  • L. Guo, W. Liu, B. Jiao, B. Hong and C. Wang, “Multi-objective stochastic optimal planning method for stand-alone microgrid system,” IET Gener. Transm. Distrib., vol. 8, no. 7, pp. 1263–1273, July 2014. DOI: 10.1049/iet-gtd.2013.0541.
  • S. Tabatabaee, S. S. Mortazavi and T. Niknam, “Stochastic energy management of renewable micro-grids in the correlated environment using unscented transformation,” Energy, vol. 109, pp. 365–377, Aug. 2016. DOI: 10.1016/j.energy.2016.04.067.
  • S. Parhoudeh, A. Baziar, A. Mazareie and A. Kavousi-Fard, “A novel stochastic framework based on fuzzy cloud theory for modeling uncertainty in the micro-grids,” Int. J. Elec. Power Energy Syst., vol. 80, pp. 73–80, Sep. 2016. DOI: 10.1016/j.ijepes.2016.01.033.
  • V. S. Pappala, I. Erlich, K. Rohrig and J. Dobschinski, “A stochastic model for the optimal operation of a wind-thermal power system,” IEEE Trans. Power Syst, vol. 24, no. 2, pp. 940–950, Apr. 2009. DOI: 10.1109/TPWRS.2009.2016504.
  • W. Su, J. Wang and J. Roh, “Stochastic energy scheduling in microgrids with intermittent renewable energy resources,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1876–1883, July 2014. DOI: 10.1109/TSG.2013.2280645.
  • G. Liu, Y. Xu and K. Tomsovic, “Bidding strategy for microgrid in day-ahead market based on hybrid stochastic/robust optimization,” IEEE Trans. Smart Grid, vol. 7, no. 1, pp. 227–237, Jan. 2016. DOI: 10.1109/TSG.2015.2476669.
  • H. Farzin, M. Fotuhi-Firuzabad and M. Moeini-Aghtaie, “A stochastic multi-objective framework for optimal scheduling of energy storage systems in microgrids,” IEEE Trans. Smart Grid, vol. 8, no. 1, pp. 117–127, Jan. 2017. DOI: 10.1109/TSG.2016.2598678.
  • S. Mohammadi, S. Soleyman and B. Mozafari, “Scenario-based stochastic operation management of MicroGrid including wind, photovoltaic, micro-turbine, fuel cell and energy storage devices,” Int. J. Elec. Power Energy Syst., vol. 54, pp. 525–535, Jan. 2014. DOI: 10.1016/j.ijepes.2013.08.004.
  • T. Niknam, R. Azizipanah-Abarghooee and M. R. Narimani, “An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation,” Appl. Energy, vol. 99, pp. 455–470, Nov. 2012. DOI: 10.1016/j.apenergy.2012.04.017.
  • F. Najibi and T. Niknam, “Stochastic scheduling of renewable micro-grids considering photovoltaic source uncertainties,” Energy Convers. Manage, vol. 98, pp. 484–499, July 2015. DOI: 10.1016/j.enconman.2015.03.037.
  • P. Li, D. Xu, Z. Zhou, W.-J. Lee and B. Zhao, “Stochastic optimal operation of microgrid based on chaotic binary particle swarm optimization,” IEEE Trans. Smart Grid, vol. 7, no. 1, pp. 66–73, Jan. 2016. DOI: 10.1109/TSG.2015.2431072.
  • A. Samimi, M. Nikzad and P. Siano, “Scenario-based framework for coupled active and reactive power market in smart distribution systems with demand response program,” Renew Energy, vol. 109, pp. 22–40, Aug. 2017. DOI: 10.1016/j.renene.2017.03.010.
  • M. Hosseinzadeh and F. R. Salmasi, “Robust optimal power management system for a hybrid AC/DC microgrid,” IEEE Trans. Sustain. Energy, vol. 6, no. 3, pp. 675–687, July 2015. DOI: 10.1109/TSTE.2015.2405935.
  • M. Bornapour, R.-A. Hooshmand and M. Parastegari, “An efficient scenario-based stochastic programming method for optimal scheduling of CHP-PEMFC, WT, PV and hydrogen storage units in micro grids,” Renew Energy, vol. 130, pp. 1049–1066, Jan. 2019. DOI: 10.1016/j.renene.2018.06.113.
  • Y. Zhang, N. Gatsis and G. B. Giannakis, “Robust energy management for microgrids with high-penetration renewables,” IEEE Trans. Sustain. Energy, vol. 4, no. 4, pp. 944–953, Oct. 2013. DOI: 10.1109/TSTE.2013.2255135.
  • M. Vahedipour-Dahraie, H. Rashidizadeh-Kermani, H. R. Najafi, A. Anvari-Moghaddam and J. M. Guerrero, “Stochastic security and risk-constrained scheduling for an autonomous microgrid with demand response and renewable energy resources,” IET Renew Power Gener., vol. 11, no. 14, pp. 1812–1821, Dec. 2017. DOI: 10.1049/iet-rpg.2017.0168.
  • M. Vahedipour-Dahraie, H. Rashidizadeh-Kermani, A. Anvari-Moghaddam and J. M. Guerrero, “Stochastic risk-constrained scheduling of renewable-powered autonomous microgrids with demand response actions: Reliability and economic implications,” IEEE Trans. Indus. Appl, vol. 56, no. 2, pp. 1882–1895, Mar.-Apr. 2020.
  • K. Masoudi and H. Abdi, “Multi-objective stochastic programming in microgrids considering environmental emissions,” J. Oper. Autom. Power Eng., vol. 8, no. 2, pp. 141–151, Aug. 2020.
  • P. Faria, T. Soares, Z. Vale and H. Morais, “Distributed generation and demand response dispatch for a virtual power player energy and reserve provision,” Renew Energy, vol. 66, pp. 686–695, June. 2014. DOI: 10.1016/j.renene.2014.01.019.
  • U.S. Department of Energy. Benefits of demand response in electricity markets and recommendations for achieving them: A report to the United States congress pursuant to section 1252 of the energy policy act of 2005. DOE EPAct Report, February, 2006.
  • S. M. Nosratabadi, R.-A. Hooshmand and E. Gholipour, “Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy,” Appl. Energy., vol. 164, pp. 590–606, Feb. 2016. DOI: 10.1016/j.apenergy.2015.12.024.
  • D. Neves, M. C. Brito and C. A. Silva, “Impact of solar and wind forecast uncertainties on demand response of isolated microgrids,” Renew Energy, vol. 87, no. 2, pp. 1003–1015, March 2016. DOI: 10.1016/j.renene.2015.08.075.
  • M. Sedighizadeh, M. Esmaili, A. Jamshidi and M. H. Ghaderi, “Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system,” Elect. Power Energy Syst., vol. 106, pp. 1–16, March 2019. DOI: 10.1016/j.ijepes.2018.09.037.
  • M. Vahedipour-Dahraie, H. Rashidizadeh-Kermani and A. Anvari-Moghaddam, “Risk-constrained stochastic scheduling of a grid-connected hybrid microgrid with variable wind power generation,” Electronics, vol. 8, no. 5, pp. 577–517, May 2019. DOI: 10.3390/electronics8050577.
  • S. Kumar Ja and D. Kumar, “Demand side management for stand-alone microgrid using coordinated control of battery energy storage system and hybrid renewable energy sources,” Elect Power Compon. Syst., vol. 47, no. 14–15, pp. 1261–1273, Sep. 2019.
  • J. Shen, C. Jiang, Y. Liu, and J. Qian, “A microgrid energy management system with demand response for providing grid peak shaving,” Elect Power Compon. Syst., vol. 44, no. 8, pp. 843–852, 2016. noApr. DOI: 10.1080/15325008.2016.1138344.
  • K. Neusser, Time Series Analysis in Economics. New York, US: Springer International Publishing, ISBN 978-3-319-32862-1, May, 2015,
  • J. Dupakova, N. Growe-Kuska, and W. Romish, “Scenario reduction in stochastic programming: An approach using probability metrics,” Mathemetical Programming, Series B, vol. 95, no. 3, pp. 493–511, 2003.
  • J. R. Birge and F. Louveaux, Introduction to Stochastic Programming; Springer Series in Operations Research and Financial Engineering. New York: Springer-Verlag, 1997.
  • A. J. Conejo, M. Carrion, and J. M. Morales, Decision Making under Uncertainty in Electricity Markets. New York, US: Springer, 2010.
  • M. Hosseinzadeh, E. Gareno and L. Schenato, “A distributed method for linear programming problems with box constraints and time-varying inequalities,” IEEE Control Syst. Lett., vol. 3, no. 2, pp. 404–409, April. 2019. DOI: 10.1109/LCSYS.2018.2889963.
  • L. Mellouk, M. Ghazi, A. Aaroud, M. Boulmalf, et al., “Design and energy management optimization for hybrid renewable energy system- case study: Laayoune region,” Renew Energy, vol. 139, pp. 621–634, Aug. 2019. DOI: 10.1016/j.renene.2019.02.066.
  • H. Brand, E. Thorin, and C. Weber, Scenario reduction algorithm and creation of multi-stage scenario trees; OSCOGEN, Discussion paper no. 7, Feb., 2002.
  • N. I. Nwulu and X. Xia, “Optimal dispatch for a microgrid incorporating renewable and demand response,” Renew Energy, vol. 101, pp. 16–28, Feb. 2017. DOI: 10.1016/j.renene.2016.08.026.
  • C. Mishra, S. P. Singh and J. Rokadia, “Optimal power flow in the presence of wind power using modified cuckoo search,” IET Gen. Transm. Distrib., vol. 9, no. 7, pp. 615–626, Apr. 2015. DOI: 10.1049/iet-gtd.2014.0285.
  • H. A. Aalami, M. P. Moghaddam and G. R. Yousefi, “Modeling and prioritizing demand response programs in power markets,” Elect. Power Syst. Res., vol. 80, no. 4, pp. 426–435, Apr. 2010. DOI: 10.1016/j.epsr.2009.10.007.
  • A. Ghasemi, S. S. Mortazavi and E. Mashhour, “Hourly demand response and battery energy storage for imbalance reduction of smart distribution company embedded with electric vehicles and wind farms,” Renew Energy, vol. 85, pp. 124–136, Jan. 2016. DOI: 10.1016/j.renene.2015.06.018.
  • H. A. Aalami, G. R. Yousefi and M. P. Moghaddam, “A MADM-based support system for DR programs,” 43rd International Universities Power Engineering Conference (UPEC), Padova; Italy, Sep 2008.
  • O. Hafez and K. Bhattacharya, “Optimal planning and design of a renewable energy based supply system for microgrids,” Renew Energy, vol. 45, pp. 7–15, Sep. 2012. DOI: 10.1016/j.renene.2012.01.087.
  • T. Madiba and R. C. Bansal, “Optimal load-shedding control of a microgrid power system,” Elect Power Compon. Syst., vol. 46, no. 7, pp. 768–787, Oct. 2018. DOI: 10.1080/15325008.2018.1501622.
  • M. Hosseinzadeh and F. R. Salmasi, “Power management of an isolated hybrid AC/DC micro-grid with fuzzy control of battery banks,” IET Renew. Power Gener, vol. 9, no. 5, pp. 484–493, June 2015. DOI: 10.1049/iet-rpg.2014.0271.
  • (Nov 2018) Enercon E-82 E2 2.300 turbine datasheet [Online], Available: http://en.wind-turbine-models.com/turbines/550-enercon-e-82-e2-2.300.
  • The ELIA, Belgiums electricity transmission system operator website [Online], Available: http://elia.be/en/grid-data/data-download/.
  • University of Massachusetts, Amherst, “Wind energy center”, [Online], Available: http://www.umass.edu/windenergy/resourcedata/Nantucket.
  • The NSRDB solar and filled meteorological fields data set, NCDC [Online], Available: ftp://ftp.ncdc.noaa.gov/pub/data/nsrdb-solar/solaronly. Site ID:725063, Nantucket Memorial AP, MA, US.
  • EPEX SPOT, https://www.epexspot.com/en/market-data/.
  • D. S. Kirschen and G. Strbac, Fundamentals of Power System Economics. Hoboken, NJ, US: John Wiley & Sons international publishing, 2004.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.