IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i10p3594-d815460.html
   My bibliography  Save this article

A Mid/Long-Term Optimization Model of Power System Considering Cross-Regional Power Trade and Renewable Energy Absorption Interval

Author

Listed:
  • Xiaowei Ma

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
    Northwest Branch of State Grid Corporation of China, Xi’an 710000, China)

  • Zhiren Zhang

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China)

  • Hewen Bai

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China)

  • Jing Ren

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China
    Northwest Branch of State Grid Corporation of China, Xi’an 710000, China)

  • Song Cheng

    (Northwest Branch of State Grid Corporation of China, Xi’an 710000, China)

  • Xiaoning Kang

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710000, China)

Abstract

With the integration of large-scale renewable energy into the power grids, cross-regional power trade can play a major role in promoting renewable energy consumption, as it can effectively achieve the optimal allocation of interconnected power grid resources and ensure the safe and economic operation of the power grid. An optimization model on a mid/long-term scale is established, considering the relationship between the renewable energy absorption interval and the regulation of resources in the system. The model is based on the load block curve and the renewable energy power model, considering the maintenance constraints of conventional units, the operation constraints of conventional units and renewable energy units, cross-regional power trade constraints and system operation constraints. By analyzing the results of the adapted IEEE RELIABILITY TEST SYSTEM (IEEE-RTS), the validity of the model and method proposed in this paper is proven. The results show that the coordinated optimization of conventional energy and renewable energy in the system can be achieved, and the complementarity of power supply and load can be promoted.

Suggested Citation

  • Xiaowei Ma & Zhiren Zhang & Hewen Bai & Jing Ren & Song Cheng & Xiaoning Kang, 2022. "A Mid/Long-Term Optimization Model of Power System Considering Cross-Regional Power Trade and Renewable Energy Absorption Interval," Energies, MDPI, vol. 15(10), pages 1-15, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3594-:d:815460
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/10/3594/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/10/3594/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rahman, S. & Khallat, M.A. & Salameh, Z.M., 1988. "Characterization of insolation data for use in photovoltaic system analysis models," Energy, Elsevier, vol. 13(1), pages 63-72.
    2. Laslett, Dean & Creagh, Chris & Jennings, Philip, 2016. "A simple hourly wind power simulation for the South-West region of Western Australia using MERRA data," Renewable Energy, Elsevier, vol. 96(PA), pages 1003-1014.
    3. Li, Y.Z. & Wu, Q.H. & Li, M.S. & Zhan, J.P., 2014. "Mean-variance model for power system economic dispatch with wind power integrated," Energy, Elsevier, vol. 72(C), pages 510-520.
    4. Tiwari, G.N. & Mishra, R.K. & Solanki, S.C., 2011. "Photovoltaic modules and their applications: A review on thermal modelling," Applied Energy, Elsevier, vol. 88(7), pages 2287-2304, July.
    5. Sulaiman, M.Yusof & Hlaing Oo, W.M & Abd Wahab, Mahdi & Zakaria, Azmi, 1999. "Application of beta distribution model to Malaysian sunshine data," Renewable Energy, Elsevier, vol. 18(4), pages 573-579.
    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. Aleksandra V. Varganova & Vadim R. Khramshin & Andrey A. Radionov, 2022. "Improving Efficiency of Electric Energy System and Grid Operating Modes: Review of Optimization Techniques," Energies, MDPI, vol. 15(19), pages 1-16, September.

    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. Rehman, Shafiqur & El-Amin, Ibrahim, 2012. "Performance evaluation of an off-grid photovoltaic system in Saudi Arabia," Energy, Elsevier, vol. 46(1), pages 451-458.
    2. Eke, Rustu & Senturk, Ali, 2013. "Monitoring the performance of single and triple junction amorphous silicon modules in two building integrated photovoltaic (BIPV) installations," Applied Energy, Elsevier, vol. 109(C), pages 154-162.
    3. Li Xia, 2020. "Risk‐Sensitive Markov Decision Processes with Combined Metrics of Mean and Variance," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2808-2827, December.
    4. Rahmani, Shima & Amjady, Nima, 2017. "A new optimal power flow approach for wind energy integrated power systems," Energy, Elsevier, vol. 134(C), pages 349-359.
    5. Evangelisti, Luca & De Lieto Vollaro, Roberto & Asdrubali, Francesco, 2019. "Latest advances on solar thermal collectors: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    6. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D," Energy, Elsevier, vol. 141(C), pages 579-597.
    7. Laslett, Dean & Carter, Craig & Creagh, Chris & Jennings, Philip, 2017. "A large-scale renewable electricity supply system by 2030: Solar, wind, energy efficiency, storage and inertia for the South West Interconnected System (SWIS) in Western Australia," Renewable Energy, Elsevier, vol. 113(C), pages 713-731.
    8. Gaur, Ankita & Tiwari, G.N., 2014. "Performance of a-Si thin film PV modules with and without water flow: An experimental validation," Applied Energy, Elsevier, vol. 128(C), pages 184-191.
    9. Hu, Jianhui & Chen, Wujun & Yang, Deqing & Zhao, Bing & Song, Hao & Ge, Binbin, 2016. "Energy performance of ETFE cushion roof integrated photovoltaic/thermal system on hot and cold days," Applied Energy, Elsevier, vol. 173(C), pages 40-51.
    10. Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
    11. Rabbani, R. & Zeeshan, M., 2020. "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan," Renewable Energy, Elsevier, vol. 154(C), pages 1240-1251.
    12. Siddiqui, Osman K. & Zubair, Syed M., 2017. "Efficient energy utilization through proper design of microchannel heat exchanger manifolds: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 969-1002.
    13. Jiao, P.H. & Chen, J.J. & Peng, K. & Zhao, Y.L. & Xin, K.F., 2020. "Multi-objective mean-semi-entropy model for optimal standalone micro-grid planning with uncertain renewable energy resources," Energy, Elsevier, vol. 191(C).
    14. Jadidoleslam, Morteza & Ebrahimi, Akbar & Latify, Mohammad Amin, 2017. "Probabilistic transmission expansion planning to maximize the integration of wind power," Renewable Energy, Elsevier, vol. 114(PB), pages 866-878.
    15. Sousa, Tiago & Morais, Hugo & Vale, Zita & Castro, Rui, 2015. "A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context," Energy, Elsevier, vol. 85(C), pages 236-250.
    16. Hussain, F. & Othman, M.Y.H & Sopian, K. & Yatim, B. & Ruslan, H. & Othman, H., 2013. "Design development and performance evaluation of photovoltaic/thermal (PV/T) air base solar collector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 431-441.
    17. Chen, J.J. & Zhao, Y.L. & Peng, K. & Wu, P.Z., 2017. "Optimal trade-off planning for wind-solar power day-ahead scheduling under uncertainties," Energy, Elsevier, vol. 141(C), pages 1969-1981.
    18. Park, K.E. & Kang, G.H. & Kim, H.I. & Yu, G.J. & Kim, J.T., 2010. "Analysis of thermal and electrical performance of semi-transparent photovoltaic (PV) module," Energy, Elsevier, vol. 35(6), pages 2681-2687.
    19. Oruc, Muhammed E. & Desai, Amit V. & Kenis, Paul J.A. & Nuzzo, Ralph G., 2016. "Comprehensive energy analysis of a photovoltaic thermal water electrolyzer," Applied Energy, Elsevier, vol. 164(C), pages 294-302.
    20. Attila Kostyák & Csaba Béres & Szabolcs Szekeres & Imre Csáky, 2022. "Buffer Tank Discharge Strategies in the Case of a Centrifugal Water Chiller," Energies, MDPI, vol. 16(1), pages 1-15, December.

    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:gam:jeners:v:15:y:2022:i:10:p:3594-:d:815460. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.