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Power generation mix evolution based on rolling horizon optimal approach: A system dynamics analysis

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  • Tang, Lei
  • Guo, Jue
  • Zhao, Boyang
  • Wang, Xiuli
  • Shao, Chengcheng
  • Wang, Yifei

Abstract

System dynamics is a well-established methodology to analyze the behavior of complex systems through computer simulation. Different from the traditional system dynamics, in this paper, the peak shaving and frequency control reserve constraints are incorporated into power generation mix planning to ensure system security and efficiency. However, it is an intractable task to consider this multi-market equilibrium and multi-period coupling planning problem in system dynamics. To ameliorate this inherent drawback, a novel planning model based on the rolling horizon optimal approach is proposed. First, by adding the constraints to the objective function, the Hamilton function is constructed to calculate the optimality conditions, and then the primal planning problem can be converted to a capital recovery problem. Considering the stochastic characteristics in the future market, a rolling horizon approach is adopted to update the planning information and optimize the power mix continuously. Next, an approximate gradient based on Pontryagin’s minimum principle is developed to simplify the optimal iteration processes. To demonstrate its feasibility, the sensitivity analysis suggests that the reduction of renewable energy cost and the wide allocation of flexible resources are two major factors to achieve a high-level penetration of renewable energy.

Suggested Citation

  • Tang, Lei & Guo, Jue & Zhao, Boyang & Wang, Xiuli & Shao, Chengcheng & Wang, Yifei, 2021. "Power generation mix evolution based on rolling horizon optimal approach: A system dynamics analysis," Energy, Elsevier, vol. 224(C).
    • Handle: RePEc:eee:energy:v:224:y:2021:i:c:s0360544221003248
    DOI: 10.1016/j.energy.2021.120075
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    as
    1. Shahmohammadi, M. Sadegh & Mohd. Yusuff, Rosnah & Keyhanian, Sina & Shakouri G., Hamed, 2015. "A decision support system for evaluating effects of Feed-in Tariff mechanism: Dynamic modeling of Malaysia’s electricity generation mix," Applied Energy, Elsevier, vol. 146(C), pages 217-229.
    2. Zapata, Sebastian & Castaneda, Monica & Franco, Carlos Jaime & Dyner, Isaac, 2019. "Clean and secure power supply: A system dynamics based appraisal," Energy Policy, Elsevier, vol. 131(C), pages 9-21.
    3. Mostashari-Rad, Fatemeh & Nabavi-Pelesaraei, Ashkan & Soheilifard, Farshad & Hosseini-Fashami, Fatemeh & Chau, Kwok-wing, 2019. "Energy optimization and greenhouse gas emissions mitigation for agricultural and horticultural systems in Northern Iran," Energy, Elsevier, vol. 186(C).
    4. Su, Jun & Lie, T.T. & Zamora, Ramon, 2020. "A rolling horizon scheduling of aggregated electric vehicles charging under the electricity exchange market," Applied Energy, Elsevier, vol. 275(C).
    5. Li, Qiang & Zhang, Wenjuan & Li, Huiquan & He, Peng, 2017. "CO2 emission trends of China's primary aluminum industry: A scenario analysis using system dynamics model," Energy Policy, Elsevier, vol. 105(C), pages 225-235.
    6. Wu, Zhibin & Xu, Jiuping, 2013. "Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas," Energy, Elsevier, vol. 49(C), pages 19-31.
    7. Pereira, Adelino J.C. & Saraiva, João Tomé, 2011. "Generation expansion planning (GEP) – A long-term approach using system dynamics and genetic algorithms (GAs)," Energy, Elsevier, vol. 36(8), pages 5180-5199.
    8. Ryan Wiser & Karen Jenni & Joachim Seel & Erin Baker & Maureen Hand & Eric Lantz & Aaron Smith, 2016. "Expert elicitation survey on future wind energy costs," Nature Energy, Nature, vol. 1(10), pages 1-8, October.
    9. Sithole, H. & Cockerill, T.T. & Hughes, K.J. & Ingham, D.B. & Ma, L. & Porter, R.T.J. & Pourkashanian, M., 2016. "Developing an optimal electricity generation mix for the UK 2050 future," Energy, Elsevier, vol. 100(C), pages 363-373.
    10. Tang, Lei & Wang, Xifan & Wang, Xiuli & Shao, Chengcheng & Liu, Shiyu & Tian, Shijun, 2019. "Long-term electricity consumption forecasting based on expert prediction and fuzzy Bayesian theory," Energy, Elsevier, vol. 167(C), pages 1144-1154.
    11. Morcillo, José D. & Franco, Carlos J. & Angulo, Fabiola, 2018. "Simulation of demand growth scenarios in the Colombian electricity market: An integration of system dynamics and dynamic systems," Applied Energy, Elsevier, vol. 216(C), pages 504-520.
    12. Cardoso, G. & Stadler, M. & Mashayekh, S. & Hartvigsson, E., 2017. "The impact of ancillary services in optimal DER investment decisions," Energy, Elsevier, vol. 130(C), pages 99-112.
    13. Ghasemi-Mobtaker, Hassan & Mostashari-Rad, Fatemeh & Saber, Zahra & Chau, Kwok-wing & Nabavi-Pelesaraei, Ashkan, 2020. "Application of photovoltaic system to modify energy use, environmental damages and cumulative exergy demand of two irrigation systems-A case study: Barley production of Iran," Renewable Energy, Elsevier, vol. 160(C), pages 1316-1334.
    14. Jeon, Chanwoong & Shin, Juneseuk, 2014. "Long-term renewable energy technology valuation using system dynamics and Monte Carlo simulation: Photovoltaic technology case," Energy, Elsevier, vol. 66(C), pages 447-457.
    15. Mendes, Carla & Soares, Isabel, 2014. "Renewable energies impacting the optimal generation mix: The case of the Iberian Electricity Market," Energy, Elsevier, vol. 69(C), pages 23-33.
    16. Ahmad, Salman & Mat Tahar, Razman & Muhammad-Sukki, Firdaus & Munir, Abu Bakar & Abdul Rahim, Ruzairi, 2016. "Application of system dynamics approach in electricity sector modelling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 29-37.
    17. Aslani, Alireza & Helo, Petri & Naaranoja, Marja, 2014. "Role of renewable energy policies in energy dependency in Finland: System dynamics approach," Applied Energy, Elsevier, vol. 113(C), pages 758-765.
    18. Rios, Daniel & Blanco, Gerardo & Olsina, Fernando, 2019. "Integrating Real Options Analysis with long-term electricity market models," Energy Economics, Elsevier, vol. 80(C), pages 188-205.
    19. Guo, Xiaodan & Guo, Xiaopeng, 2015. "China's photovoltaic power development under policy incentives: A system dynamics analysis," Energy, Elsevier, vol. 93(P1), pages 589-598.
    20. Zappa, William & Junginger, Martin & van den Broek, Machteld, 2019. "Is a 100% renewable European power system feasible by 2050?," Applied Energy, Elsevier, vol. 233, pages 1027-1050.
    21. de Oliveira, Erick Meira & Cyrino Oliveira, Fernando Luiz, 2018. "Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods," Energy, Elsevier, vol. 144(C), pages 776-788.
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    4. Luo, Yilun & Ahmadi, Esmaeil & McLellan, Benjamin Craig & Tezuka, Tetsuo, 2024. "A hybrid system dynamics model for power mix trajectory simulation in liberalized electricity markets considering carbon and capacity policy," Renewable Energy, Elsevier, vol. 233(C).
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    6. Doroodi, Maryam & Ostadi, Bakhtiar & Husseinzadeh Kashan, Ali & Zegordi, Seyed Hessameddin, 2024. "An integrated system dynamics model of electricity production, consumption, and export policy in Iran considering carbon emissions," Utilities Policy, Elsevier, vol. 90(C).
    7. Zhao, Jing & Zhang, Qin & Zhou, Dequn, 2023. "Can marketed on-grid price drive the realization of energy transition in China’s power industry under the background of carbon neutrality?," Energy, Elsevier, vol. 276(C).
    8. Brumana, Giovanni & Franchini, Giuseppe & Ghirardi, Elisa & Perdichizzi, Antonio, 2022. "Techno-economic optimization of hybrid power generation systems: A renewables community case study," Energy, Elsevier, vol. 246(C).

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