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A Methodology for Explicit Representation Of The Stochastic Demand Due To Electric Vehicles in Generation Expansion Planning Problems

Yıl 2021, Cilt 9, Sayı 2, 257 - 263, 28.05.2021
https://doi.org/10.21541/apjes.821861

Öz

Generation expansion planning (GEP) problems are solved to find the optimum investment decisions to satisfy the increasing electricity demand. Integration of electric vehicles (EVs) with the capability of charging from the grid will also increase the electricity demand of the grid. Depending on the charging/driving characteristics of users, demand curves for EVs will be shaped and it will be different on each day. Therefore, it is very crucial to represent this stochastic nature of EVs demand in the associated GEP problems. This paper is proposing a methodology to represent EVs demand realistically on GEP models. The proposed methodology starts with generating random demand patterns to demonstrate possibilities for the EVs demand patterns via Monte Carlo Simulation, then using an optimization-based model to select a representative set. Two stage stochastic programming model is proposed for GEP problems and solved to minimize the expected cost over the entire set, the representative set and the average EVs demand. The results show that GEP models with selected demand curves produce more realistic decisions (closer to the solutions obtained by using the entire demand patterns) than the decisions obtained by the models with average EVs demand. In most cases, the models using average EVs demand fail to capture the new peaks generated by EVs, therefore, they suggest less capacity expansion then the required amount. This results in more unmet demand in the system.

Kaynakça

  • IEA, World Energy Outlook, 2019. (Visited on December, 25 2019).
  • N.E. Koltsaklis and A.S. Dagoumas, “State-of-the-art generation expansion planning: A review”, Applied Energy, vol. 230, pp. 563–589, 2018.
  • A.S. Dagoumas and N.E. Koltsaklis, “Review of models for integrating renewable energy in the generation expansion planning”, Applied Energy, vol. 242, pp. 1573–1587, 2019.
  • J.C. Kelly, J.S. MacDonald and G.A. Keoleian, “Time-dependent plug-in hybrid electric vehicle charging based on national driving patterns and demographics”, Applied Energy, vol. 94, pp. 395-405, 2012.
  • S. Shafiee, M. Fotuhi-Firuzabad and M. Rastegar, “Investigating the impacts of plug-in hybrid electric vehicles on power distribution systems”, IEEE Transactions on Smart Grid, vol. 4, no 3, pp. 1351-1360, 2013.
  • J. Jung, Y. Cho, D. Cheng, A. Onen, R. Arghandeh, M. Dilek and R.P. Broadwater, “Monte Carlo analysis of plug-in hybrid vehicles and distributed energy resource growth with residential energy storage in Michigan”, Applied Energy, vol. 108, pp. 218-235, 2013.
  • B. Yagcitekin, M. Uzunoglu, A. Karakas and O. Erdinc, “Assessment of electrically-driven vehicles in terms of emission impacts and energy requirements: a case study for Istanbul, Turkey”, Journal of Cleaner Production, vol. 96, pp. 486-492, 2015.
  • R. Godina, E.M.G. Rodrigues, N.G. Paterakis,, O. Erdinc and J.P.S. Catalão, “Innovative impact assessment of electric vehicles charging loads on distribution transformers using real data”, Energy Conversion and Management, vol. 120, pp. 206-216, 2016.
  • J. Su, T.T. Lie and R. Zamora, “Modelling of large-scale electric vehicles charging demand: A New Zealand case study”, Electric Power Systems Research, vol. 167, pp. 171-182, 2019.
  • X. Yu, “Impacts assessment of PHEV charge profiles on generation expansion using national energy modeling system”, Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, IEEE, pp. 1-5, (2008).
  • M.D. Galus, M. Zima and G. Andersson, “On integration of plug-in hybrid electric vehicles into existing power system structures”, Energy Policy, vol. 38, no 11, pp. 6736-6745, 2010.
  • A.H. Hajimiragha, C.A. Cañizares, W. Michael, M.W. Fowler, S. Moazeni and A. Elkamel, “A Robust Optimization Approach for Planning the Transition to Plug-in Hybrid Electric Vehicles”, IEEE Transactions on Power Systems, vol. 26, no 4, pp. 2264 – 2274, 2011.
  • P. Vithayasrichareon, G. Mills and I.F. MacGill, “Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment”, IEEE Transactions on Sustainable Energy, vol. 6, no 3, pp. 899-908, 2015.
  • S.W. Hadley and A.A: Tsvetkova, “Potential impacts of plug-in hybrid electric vehicles on regional power generation”, The Electricity Journal, vol. 22, no 10, pp. 56-68, 2009.
  • P. Prebeg, G. Gasparovic, G.Krajacic and N. Duic, “Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles”, Applied Energy, vol. 184, pp. 1493–1507, 2016.
  • A. Hajebrahimi, I. Kaçwa and M. Huneault, “A novel approach for plug-in electric vehicle planning and electricity load management in presence of a clean disruptive technology”, Energy, vol. 158, pp. 975-985, 2018.
  • Y. Yua, P. Lib, B.G: Shand, G.H. Huangb and L.P. Xu, “A scenario-based interval-stochastic basic-possibilistic programming method for planning sustainable energy system under uncertainty: A case study of Beijing, China”, Journal of Cleaner Production, vol. 197, pp. 1454-1471, 2018.
  • P.J. Ramírez, D. Papadaskalopoulos and G. Strbac, “Co-Optimization of Generation Expansion Planning and Electric Vehicles Flexibility”, IEEE Transactions on Smart Grid, vol. 7, no 3, pp. 1609-1619, 2016.
  • A. Hajimiragha, C.A. Canizares, M.W. Fowler and A. Elkamel, “Optimal transition to plug-in hybrid electric vehicles in Ontario, Canada, considering the electricity-grid limitations”, IEEE Transactions on Industrial Electronics, vol. 57, no 2, pp. 690-701, 2010.
  • L. Ahmadi, A. Elkamel, S.A. Abdul-Wahab, M. Pan, E. Croiset, P.L. Douglas and E. Entchev, “Multi-Period Optimization Model for Electricity Generation Planning Considering Plug-in Hybrid Electric Vehicle Penetration”, Energies, vol. 8, no. 5, pp. 3978-4002, 2015.
  • G.H. Moon, S.B. Kong, S.K. Joo, H.S. Ryu, and T.H. Kim, “Stochastic integrated generation and transmission planning incorporating electric vehicle deployment”, Journal of Electrical Engineering and Technology, vol. 8, no 1, pp. 1-10, 2013.
  • P. Ramírez, D. Papadaskalopoulos and G. Strbac, “Impact of Electric Vehicles Flexibility on Generation Expansion Planning.” 4th IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), October 6-9, Copenhagen, pp. 1-5, (2013).
  • P.M. de Quevedo, G. Muñoz-Delgado and J. Contreras, “Impact of Electric Vehicles on the Expansion Planning of Distribution Systems Considering Renewable Energy, Storage, and Charging Stations”, IEEE Transactions on Smart Grid, vol. 10, no 1, pp. 794–804, 2019.
  • F. Manríquez, E. Saum, J. Aguado, S. de la Torre, and J. Contreras, “The impact of electric vehicle charging schemes in power system expansion planning”, Applied Energy, vol. 262, 2020
  • H. Mehrjerdi, “Dynamic and multi-stage capacity expansion planning in microgrid integrated with electric vehicle charging station”, Journal of Energy Storage, vol. 29, 2020
  • C. F. Heuberger, P. K. Bains, and N. M. Dowell, “The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment”, Applied Energy, vol. 257, 2020
  • Seda Ediz, “ Evaluation of the impacts of plug-in hybrid electric vehicles on electricity load curve for İstanbul”, Master's thesis, Istanbul Sehir University, Turkey, 2017.
  • www.teias.gov.tr, (Visited on February, 1 2020)

Yıl 2021, Cilt 9, Sayı 2, 257 - 263, 28.05.2021
https://doi.org/10.21541/apjes.821861

Öz

Kaynakça

  • IEA, World Energy Outlook, 2019. (Visited on December, 25 2019).
  • N.E. Koltsaklis and A.S. Dagoumas, “State-of-the-art generation expansion planning: A review”, Applied Energy, vol. 230, pp. 563–589, 2018.
  • A.S. Dagoumas and N.E. Koltsaklis, “Review of models for integrating renewable energy in the generation expansion planning”, Applied Energy, vol. 242, pp. 1573–1587, 2019.
  • J.C. Kelly, J.S. MacDonald and G.A. Keoleian, “Time-dependent plug-in hybrid electric vehicle charging based on national driving patterns and demographics”, Applied Energy, vol. 94, pp. 395-405, 2012.
  • S. Shafiee, M. Fotuhi-Firuzabad and M. Rastegar, “Investigating the impacts of plug-in hybrid electric vehicles on power distribution systems”, IEEE Transactions on Smart Grid, vol. 4, no 3, pp. 1351-1360, 2013.
  • J. Jung, Y. Cho, D. Cheng, A. Onen, R. Arghandeh, M. Dilek and R.P. Broadwater, “Monte Carlo analysis of plug-in hybrid vehicles and distributed energy resource growth with residential energy storage in Michigan”, Applied Energy, vol. 108, pp. 218-235, 2013.
  • B. Yagcitekin, M. Uzunoglu, A. Karakas and O. Erdinc, “Assessment of electrically-driven vehicles in terms of emission impacts and energy requirements: a case study for Istanbul, Turkey”, Journal of Cleaner Production, vol. 96, pp. 486-492, 2015.
  • R. Godina, E.M.G. Rodrigues, N.G. Paterakis,, O. Erdinc and J.P.S. Catalão, “Innovative impact assessment of electric vehicles charging loads on distribution transformers using real data”, Energy Conversion and Management, vol. 120, pp. 206-216, 2016.
  • J. Su, T.T. Lie and R. Zamora, “Modelling of large-scale electric vehicles charging demand: A New Zealand case study”, Electric Power Systems Research, vol. 167, pp. 171-182, 2019.
  • X. Yu, “Impacts assessment of PHEV charge profiles on generation expansion using national energy modeling system”, Power and Energy Society General Meeting-Conversion and Delivery of Electrical Energy in the 21st Century, IEEE, pp. 1-5, (2008).
  • M.D. Galus, M. Zima and G. Andersson, “On integration of plug-in hybrid electric vehicles into existing power system structures”, Energy Policy, vol. 38, no 11, pp. 6736-6745, 2010.
  • A.H. Hajimiragha, C.A. Cañizares, W. Michael, M.W. Fowler, S. Moazeni and A. Elkamel, “A Robust Optimization Approach for Planning the Transition to Plug-in Hybrid Electric Vehicles”, IEEE Transactions on Power Systems, vol. 26, no 4, pp. 2264 – 2274, 2011.
  • P. Vithayasrichareon, G. Mills and I.F. MacGill, “Impact of Electric Vehicles and Solar PV on Future Generation Portfolio Investment”, IEEE Transactions on Sustainable Energy, vol. 6, no 3, pp. 899-908, 2015.
  • S.W. Hadley and A.A: Tsvetkova, “Potential impacts of plug-in hybrid electric vehicles on regional power generation”, The Electricity Journal, vol. 22, no 10, pp. 56-68, 2009.
  • P. Prebeg, G. Gasparovic, G.Krajacic and N. Duic, “Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles”, Applied Energy, vol. 184, pp. 1493–1507, 2016.
  • A. Hajebrahimi, I. Kaçwa and M. Huneault, “A novel approach for plug-in electric vehicle planning and electricity load management in presence of a clean disruptive technology”, Energy, vol. 158, pp. 975-985, 2018.
  • Y. Yua, P. Lib, B.G: Shand, G.H. Huangb and L.P. Xu, “A scenario-based interval-stochastic basic-possibilistic programming method for planning sustainable energy system under uncertainty: A case study of Beijing, China”, Journal of Cleaner Production, vol. 197, pp. 1454-1471, 2018.
  • P.J. Ramírez, D. Papadaskalopoulos and G. Strbac, “Co-Optimization of Generation Expansion Planning and Electric Vehicles Flexibility”, IEEE Transactions on Smart Grid, vol. 7, no 3, pp. 1609-1619, 2016.
  • A. Hajimiragha, C.A. Canizares, M.W. Fowler and A. Elkamel, “Optimal transition to plug-in hybrid electric vehicles in Ontario, Canada, considering the electricity-grid limitations”, IEEE Transactions on Industrial Electronics, vol. 57, no 2, pp. 690-701, 2010.
  • L. Ahmadi, A. Elkamel, S.A. Abdul-Wahab, M. Pan, E. Croiset, P.L. Douglas and E. Entchev, “Multi-Period Optimization Model for Electricity Generation Planning Considering Plug-in Hybrid Electric Vehicle Penetration”, Energies, vol. 8, no. 5, pp. 3978-4002, 2015.
  • G.H. Moon, S.B. Kong, S.K. Joo, H.S. Ryu, and T.H. Kim, “Stochastic integrated generation and transmission planning incorporating electric vehicle deployment”, Journal of Electrical Engineering and Technology, vol. 8, no 1, pp. 1-10, 2013.
  • P. Ramírez, D. Papadaskalopoulos and G. Strbac, “Impact of Electric Vehicles Flexibility on Generation Expansion Planning.” 4th IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), October 6-9, Copenhagen, pp. 1-5, (2013).
  • P.M. de Quevedo, G. Muñoz-Delgado and J. Contreras, “Impact of Electric Vehicles on the Expansion Planning of Distribution Systems Considering Renewable Energy, Storage, and Charging Stations”, IEEE Transactions on Smart Grid, vol. 10, no 1, pp. 794–804, 2019.
  • F. Manríquez, E. Saum, J. Aguado, S. de la Torre, and J. Contreras, “The impact of electric vehicle charging schemes in power system expansion planning”, Applied Energy, vol. 262, 2020
  • H. Mehrjerdi, “Dynamic and multi-stage capacity expansion planning in microgrid integrated with electric vehicle charging station”, Journal of Energy Storage, vol. 29, 2020
  • C. F. Heuberger, P. K. Bains, and N. M. Dowell, “The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment”, Applied Energy, vol. 257, 2020
  • Seda Ediz, “ Evaluation of the impacts of plug-in hybrid electric vehicles on electricity load curve for İstanbul”, Master's thesis, Istanbul Sehir University, Turkey, 2017.
  • www.teias.gov.tr, (Visited on February, 1 2020)

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

Hatice TEKİNER MOGULKOC (Sorumlu Yazar)
Marmara University
0000-0002-1338-3368
Türkiye

Yayımlanma Tarihi 28 Mayıs 2021
Başvuru Tarihi 5 Kasım 2020
Kabul Tarihi 10 Nisan 2021
Yayınlandığı Sayı Yıl 2021, Cilt 9, Sayı 2

Kaynak Göster

IEEE H. Tekiner Mogulkoc , "A Methodology for Explicit Representation Of The Stochastic Demand Due To Electric Vehicles in Generation Expansion Planning Problems", Academic Platform - Journal of Engineering and Science, c. 9, sayı. 2, ss. 257-263, May. 2021, doi:10.21541/apjes.821861