IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v72y2017icp385-398.html
   My bibliography  Save this article

Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies

Author

Listed:
  • Sharifzadeh, Mahdi
  • Lubiano-Walochik, Helena
  • Shah, Nilay

Abstract

Renewable energies can play an important role in mitigating the emissions associated with electricity power generation and diversification of the energy supply. The challenge is that renewable resources such as wind and solar have intermittent production patterns and their incorporation into conventional electricity grids will increase the degree of uncertainty. The present research proposes a comprehensive framework in which design and operation of the electricity grid are considered simultaneously and the uncertainties in the wind and solar generation as well as demand are systematically taken into account. The case of retrofitting the current UK electricity grid to include 50% renewable power generation by 2030 was posed as the demonstrating example. The research problem was formulated as a piece-wise linear mixed integer optimization under uncertainty and solved using CPLEX v12.0 in GAMS. The results suggested that it is possible to retrofit the electricity grid using renewable generators while optimizing the overall profitability and ensuring the secure supply of electricity. It was also observed that at the price of higher computational costs, stochastic optimization generates more realistic and robust solutions for the design and operation of the smart electricity grid.

Suggested Citation

  • Sharifzadeh, Mahdi & Lubiano-Walochik, Helena & Shah, Nilay, 2017. "Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 385-398.
    • Handle: RePEc:eee:rensus:v:72:y:2017:i:c:p:385-398
    DOI: 10.1016/j.rser.2017.01.069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032117300795
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2017.01.069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Türkay, Belgin Emre & Telli, Ali Yasin, 2011. "Economic analysis of standalone and grid connected hybrid energy systems," Renewable Energy, Elsevier, vol. 36(7), pages 1931-1943.
    2. Quan, Hao & Srinivasan, Dipti & Khosravi, Abbas, 2016. "Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study," Energy, Elsevier, vol. 103(C), pages 735-745.
    3. Kayal, Partha & Chanda, C.K., 2015. "Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network," Renewable Energy, Elsevier, vol. 75(C), pages 173-186.
    4. Pineda, Salvador & Morales, Juan M. & Boomsma, Trine K., 2016. "Impact of forecast errors on expansion planning of power systems with a renewables target," European Journal of Operational Research, Elsevier, vol. 248(3), pages 1113-1122.
    5. Sharifzadeh, Mahdi & Bumb, Prateek & Shah, Nilay, 2016. "Carbon capture from pulverized coal power plant (PCPP): Solvent performance comparison at an industrial scale," Applied Energy, Elsevier, vol. 163(C), pages 423-435.
    6. Torrent-Fontbona, F. & López, B., 2016. "Decision support for grid-connected renewable energy generators planning," Energy, Elsevier, vol. 115(P1), pages 577-590.
    7. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Mendoza, Franklin, 2009. "Design and economical analysis of hybrid PV-wind systems connected to the grid for the intermittent production of hydrogen," Energy Policy, Elsevier, vol. 37(8), pages 3082-3095, August.
    8. Ji, Bin & Yuan, Xiaohui & Chen, Zhihuan & Tian, Hao, 2014. "Improved gravitational search algorithm for unit commitment considering uncertainty of wind power," Energy, Elsevier, vol. 67(C), pages 52-62.
    9. Cetinay, Hale & Kuipers, Fernando A. & Guven, A. Nezih, 2017. "Optimal siting and sizing of wind farms," Renewable Energy, Elsevier, vol. 101(C), pages 51-58.
    10. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
    11. Wang, J. & Botterud, A. & Bessa, R. & Keko, H. & Carvalho, L. & Issicaba, D. & Sumaili, J. & Miranda, V., 2011. "Wind power forecasting uncertainty and unit commitment," Applied Energy, Elsevier, vol. 88(11), pages 4014-4023.
    12. Lamy, Julian V. & Jaramillo, Paulina & Azevedo, Inês L. & Wiser, Ryan, 2016. "Should we build wind farms close to load or invest in transmission to access better wind resources in remote areas? A case study in the MISO region," Energy Policy, Elsevier, vol. 96(C), pages 341-350.
    13. Pereira, Sérgio & Ferreira, Paula & Vaz, A.I.F., 2016. "Optimization modeling to support renewables integration in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 316-325.
    14. Carapellucci, Roberto & Giordano, Lorena, 2013. "The effect of diurnal profile and seasonal wind regime on sizing grid-connected and off-grid wind power plants," Applied Energy, Elsevier, vol. 107(C), pages 364-376.
    15. Arnau González & Jordi-Roger Riba & Antoni Rius, 2015. "Optimal Sizing of a Hybrid Grid-Connected Photovoltaic–Wind–Biomass Power System," Sustainability, MDPI, vol. 7(9), pages 1-20, September.
    16. Mondol, Jayanta Deb & Yohanis, Yigzaw G & Norton, Brian, 2009. "Optimising the economic viability of grid-connected photovoltaic systems," Applied Energy, Elsevier, vol. 86(7-8), pages 985-999, July.
    17. Hernández, J.C. & Medina, A. & Jurado, F., 2007. "Optimal allocation and sizing for profitability and voltage enhancement of PV systems on feeders," Renewable Energy, Elsevier, vol. 32(10), pages 1768-1789.
    18. PAPAVASILIOU, Anthony & OREN, Shmuel & ROUNTREE, Barry, 2015. "Applying high performance computing to transmissions-consstrained stochastic unit commitment for renewable energy integration," LIDAM Reprints CORE 2679, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. González, Arnau & Riba, Jordi-Roger & Rius, Antoni & Puig, Rita, 2015. "Optimal sizing of a hybrid grid-connected photovoltaic and wind power system," Applied Energy, Elsevier, vol. 154(C), pages 752-762.
    20. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Keck, Felix & Jütte, Silke & Lenzen, Manfred & Li, Mengyu, 2022. "Assessment of two optimisation methods for renewable energy capacity expansion planning," Applied Energy, Elsevier, vol. 306(PA).
    2. Koltsaklis, Nikolaos E. & Nazos, Konstantinos, 2017. "A stochastic MILP energy planning model incorporating power market dynamics," Applied Energy, Elsevier, vol. 205(C), pages 1364-1383.
    3. Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
    4. Dagoumas, Athanasios S. & Koltsaklis, Nikolaos E., 2019. "Review of models for integrating renewable energy in the generation expansion planning," Applied Energy, Elsevier, vol. 242(C), pages 1573-1587.
    5. Rajaeifar, Mohammad Ali & Sadeghzadeh Hemayati, Saeed & Tabatabaei, Meisam & Aghbashlo, Mortaza & Mahmoudi, Seyed Bagher, 2019. "A review on beet sugar industry with a focus on implementation of waste-to-energy strategy for power supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 423-442.
    6. Chen, Honglin & Liu, Mingbo & Liu, Yingqi & Lin, Shunjiang & Yang, Zhibin, 2020. "Partial surrogate cuts method for network-constrained optimal scheduling of multi-carrier energy systems with demand response," Energy, Elsevier, vol. 196(C).
    7. Konečná, Eva & Teng, Sin Yong & Máša, Vítězslav, 2020. "New insights into the potential of the gas microturbine in microgrids and industrial applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    8. Sharifzadeh, Mahdi & Hien, Raymond Khoo Teck & Shah, Nilay, 2019. "China’s roadmap to low-carbon electricity and water: Disentangling greenhouse gas (GHG) emissions from electricity-water nexus via renewable wind and solar power generation, and carbon capture and sto," Applied Energy, Elsevier, vol. 235(C), pages 31-42.
    9. Wang, Meng & Yu, Hang & Lin, Xiaoyu & Jing, Rui & He, Fangjun & Li, Chaoen, 2020. "Comparing stochastic programming with posteriori approach for multi-objective optimization of distributed energy systems under uncertainty," Energy, Elsevier, vol. 210(C).
    10. Cui, Yuanlong & Zhu, Jie & Meng, Fanran & Zoras, Stamatis & McKechnie, Jon & Chu, Junze, 2020. "Energy assessment and economic sensitivity analysis of a grid-connected photovoltaic system," Renewable Energy, Elsevier, vol. 150(C), pages 101-115.
    11. Heuberger, Clara F. & Bains, Praveen K. & Mac Dowell, Niall, 2020. "The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment," Applied Energy, Elsevier, vol. 257(C).
    12. Pilpola, Sannamari & Lund, Peter D., 2020. "Analyzing the effects of uncertainties on the modelling of low-carbon energy system pathways," Energy, Elsevier, vol. 201(C).
    13. Jing, Rui & Kuriyan, Kamal & Lin, Jian & Shah, Nilay & Zhao, Yingru, 2020. "Quantifying the contribution of individual technologies in integrated urban energy systems – A system value approach," Applied Energy, Elsevier, vol. 266(C).
    14. Jing, Rui & Wang, Meng & Zhang, Zhihui & Wang, Xiaonan & Li, Ning & Shah, Nilay & Zhao, Yingru, 2019. "Distributed or centralized? Designing district-level urban energy systems by a hierarchical approach considering demand uncertainties," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    15. Horia Andrei & Cristian Andrei Badea & Paul Andrei & Filippo Spertino, 2020. "Energetic-Environmental-Economic Feasibility and Impact Assessment of Grid-Connected Photovoltaic System in Wastewater Treatment Plant: Case Study," Energies, MDPI, vol. 14(1), pages 1-22, December.
    16. Qiu, Dawei & Dong, Zihang & Zhang, Xi & Wang, Yi & Strbac, Goran, 2022. "Safe reinforcement learning for real-time automatic control in a smart energy-hub," Applied Energy, Elsevier, vol. 309(C).
    17. Zanjirchi, Seyed Mahmoud & Shojaei, Sara & Naser Sadrabadi, Alireza & Jalilian, Negar, 2020. "Promotion of solar energies usage in Iran: A scenario-based road map," Renewable Energy, Elsevier, vol. 150(C), pages 278-292.
    18. Ghaemi, Zahra & Tran, Thomas T.D. & Smith, Amanda D., 2022. "Comparing classical and metaheuristic methods to optimize multi-objective operation planning of district energy systems considering uncertainties," Applied Energy, Elsevier, vol. 321(C).
    19. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    20. Yao, Huizong & Zang, Chuanfu, 2021. "The spatiotemporal characteristics of electrical energy supply-demand and the green economy outlook of Guangdong Province, China," Energy, Elsevier, vol. 214(C).
    21. Zhang, Zhihui & Jing, Rui & Lin, Jian & Wang, Xiaonan & van Dam, Koen H. & Wang, Meng & Meng, Chao & Xie, Shan & Zhao, Yingru, 2020. "Combining agent-based residential demand modeling with design optimization for integrated energy systems planning and operation," Applied Energy, Elsevier, vol. 263(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Wenxiao & Li, Chaoshun & Liao, Xiang & Qin, Hui, 2017. "Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm," Applied Energy, Elsevier, vol. 187(C), pages 612-626.
    2. Rajbongshi, Rumi & Borgohain, Devashree & Mahapatra, Sadhan, 2017. "Optimization of PV-biomass-diesel and grid base hybrid energy systems for rural electrification by using HOMER," Energy, Elsevier, vol. 126(C), pages 461-474.
    3. González, Arnau & Riba, Jordi-Roger & Rius, Antoni, 2016. "Combined heat and power design based on environmental and cost criteria," Energy, Elsevier, vol. 116(P1), pages 922-932.
    4. Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.
    5. Yang, Zhile & Li, Kang & Guo, Yuanjun & Feng, Shengzhong & Niu, Qun & Xue, Yusheng & Foley, Aoife, 2019. "A binary symmetric based hybrid meta-heuristic method for solving mixed integer unit commitment problem integrating with significant plug-in electric vehicles," Energy, Elsevier, vol. 170(C), pages 889-905.
    6. Zhang, Yang & Campana, Pietro Elia & Lundblad, Anders & Yan, Jinyue, 2017. "Comparative study of hydrogen storage and battery storage in grid connected photovoltaic system: Storage sizing and rule-based operation," Applied Energy, Elsevier, vol. 201(C), pages 397-411.
    7. Akikur, R.K. & Saidur, R. & Ping, H.W. & Ullah, K.R., 2013. "Comparative study of stand-alone and hybrid solar energy systems suitable for off-grid rural electrification: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 738-752.
    8. Luís A. C. Roque & Dalila B. M. M. Fontes & Fernando A. C. C. Fontes, 2017. "A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria," Energies, MDPI, vol. 10(12), pages 1-25, December.
    9. Li, Chaoshun & Wang, Wenxiao & Wang, Jinwen & Chen, Deshu, 2019. "Network-constrained unit commitment with RE uncertainty and PHES by using a binary artificial sheep algorithm," Energy, Elsevier, vol. 189(C).
    10. Bhatt, Ankit & Sharma, M.P. & Saini, R.P., 2016. "Feasibility and sensitivity analysis of an off-grid micro hydro–photovoltaic–biomass and biogas–diesel–battery hybrid energy system for a remote area in Uttarakhand state, India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 53-69.
    11. Sun, Wei & Harrison, Gareth P., 2019. "Wind-solar complementarity and effective use of distribution network capacity," Applied Energy, Elsevier, vol. 247(C), pages 89-101.
    12. Talaat, M. & Farahat, M.A. & Elkholy, M.H., 2019. "Renewable power integration: Experimental and simulation study to investigate the ability of integrating wave, solar and wind energies," Energy, Elsevier, vol. 170(C), pages 668-682.
    13. Xie, Kaigui & Dong, Jizhe & Singh, Chanan & Hu, Bo, 2016. "Optimal capacity and type planning of generating units in a bundled wind–thermal generation system," Applied Energy, Elsevier, vol. 164(C), pages 200-210.
    14. Wen, Shuli & Lan, Hai & Hong, Ying-Yi & Yu, David C. & Zhang, Lijun & Cheng, Peng, 2016. "Allocation of ESS by interval optimization method considering impact of ship swinging on hybrid PV/diesel ship power system," Applied Energy, Elsevier, vol. 175(C), pages 158-167.
    15. Mohseni, Soheil & Brent, Alan C. & Burmester, Daniel, 2020. "A comparison of metaheuristics for the optimal capacity planning of an isolated, battery-less, hydrogen-based micro-grid," Applied Energy, Elsevier, vol. 259(C).
    16. Mohammad Masih Sediqi & Mohammed Elsayed Lotfy & Abdul Matin Ibrahimi & Tomonobu Senjyu & Narayanan. K, 2019. "Stochastic Unit Commitment and Optimal Power Trading Incorporating PV Uncertainty," Sustainability, MDPI, vol. 11(16), pages 1-16, August.
    17. Duchaud, Jean-Laurent & Notton, Gilles & Darras, Christophe & Voyant, Cyril, 2019. "Multi-Objective Particle Swarm optimal sizing of a renewable hybrid power plant with storage," Renewable Energy, Elsevier, vol. 131(C), pages 1156-1167.
    18. 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.
    19. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    20. Ihsan, Abbas & Jeppesen, Matthew & Brear, Michael J., 2019. "Impact of demand response on the optimal, techno-economic performance of a hybrid, renewable energy power plant," Applied Energy, Elsevier, vol. 238(C), pages 972-984.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:72:y:2017:i:c:p:385-398. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.