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Multi-objective stochastic economic dispatch with maximal renewable penetration under renewable obligation

Author

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  • Hlalele, Thabo G.
  • Naidoo, Raj M.
  • Bansal, Ramesh C.
  • Zhang, Jiangfeng

Abstract

In this paper, a stochastic multi-objective economic dispatch model is presented under renewable obligation policy framework. This proposed model minimises the total operating costs of generators and spinning reserves under renewable obligation while maximising renewable penetration. The intermittent nature of the wind and photovoltaic power plants is incorporated into the renewable obligation model. In order to minimise the cycling costs associated with ramping the thermal generators, the battery energy storage system units are included in the model to assist the system spinning reserves. Dynamic scenarios are created to deal with the intermittency of renewable energy sources. Due to the computational complexity of all possible scenarios, a scenario reduction method is applied to reduce the number of scenarios and solve the proposed stochastic renewable obligation model. A Pareto optimal solution is presented for the renewable obligation, and further decision making is conducted to assess the trade-offs associated with the Pareto front. To show the effectiveness of the proposed stochastic renewable obligation model, two IEEE test systems are used, i.e., the modified IEEE 30-bus and IEEE 118-bus system. In both test systems, the proposed model can attain high renewable penetration while minimising the expected operating cost. In the large IEEE 118-bus test system, the computational efficiency of the renewable obligation model is demonstrated by reducing the line constraints by 87% which minimises the computing time. A comparative study evaluates the impact of the stochastic model to the deterministic one, and it shows that the stochastic model can achieve high renewable penetration.

Suggested Citation

  • Hlalele, Thabo G. & Naidoo, Raj M. & Bansal, Ramesh C. & Zhang, Jiangfeng, 2020. "Multi-objective stochastic economic dispatch with maximal renewable penetration under renewable obligation," Applied Energy, Elsevier, vol. 270(C).
    • Handle: RePEc:eee:appene:v:270:y:2020:i:c:s0306261920306322
    DOI: 10.1016/j.apenergy.2020.115120
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    References listed on IDEAS

    as
    1. Wang, Sarah & Tarroja, Brian & Schell, Lori Smith & Shaffer, Brendan & Samuelsen, Scott, 2019. "Prioritizing among the end uses of excess renewable energy for cost-effective greenhouse gas emission reductions," Applied Energy, Elsevier, vol. 235(C), pages 284-298.
    2. Anthony Papavasiliou & Yuting Mou & Léopold Cambier & Damien Scieur, 2018. "Application of stochastic dual dynamic programming to the real-time dispatch of storage under renewable supply uncertainty," LIDAM Reprints CORE 2943, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Zhang, Menglin & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2018. "A systematic approach for the joint dispatch of energy and reserve incorporating demand response," Applied Energy, Elsevier, vol. 230(C), pages 1279-1291.
    4. Tan, Qinliang & Ding, Yihong & Ye, Qi & Mei, Shufan & Zhang, Yimei & Wei, Yongmei, 2019. "Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    6. Das, Ridoy & Wang, Yue & Putrus, Ghanim & Kotter, Richard & Marzband, Mousa & Herteleer, Bert & Warmerdam, Jos, 2020. "Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services," Applied Energy, Elsevier, vol. 257(C).
    7. Anthony Papavasiliou & Yuting Mou & Léopold Cambier & Damien Scieur, 2018. "Application of stochastic dual dynamic programming to the real-time dispatch of storage under renewable supply uncertainty," LIDAM Reprints CORE 3044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Vincenzo Bassi & Eduardo Pereira-Bonvallet & Md Abu Abdullah & Rodrigo Palma-Behnke, 2018. "Cycling Impact Assessment of Renewable Energy Generation in the Costs of Conventional Generators," Energies, MDPI, vol. 11(7), pages 1-17, June.
    9. Kabir, M.N. & Mishra, Y. & Bansal, R.C., 2016. "Probabilistic load flow for distribution systems with uncertain PV generation," Applied Energy, Elsevier, vol. 163(C), pages 343-351.
    10. Lin, Zhenjia & Chen, Haoyong & Wu, Qiuwei & Li, Weiwei & Li, Mengshi & Ji, Tianyao, 2020. "Mean-tracking model based stochastic economic dispatch for power systems with high penetration of wind power," Energy, Elsevier, vol. 193(C).
    11. Talari, Saber & Shafie-khah, Miadreza & Osório, Gerardo J. & Aghaei, Jamshid & Catalão, João P.S., 2018. "Stochastic modelling of renewable energy sources from operators' point-of-view: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1953-1965.
    12. Wang, Luhao & Zhang, Bingying & Li, Qiqiang & Song, Wen & Li, Guanguan, 2019. "Robust distributed optimization for energy dispatch of multi-stakeholder multiple microgrids under uncertainty," Applied Energy, Elsevier, vol. 255(C).
    13. Kumar, Abhishek & Meena, Nand K. & Singh, Arvind R. & Deng, Yan & He, Xiangning & Bansal, R.C. & Kumar, Praveen, 2019. "Strategic integration of battery energy storage systems with the provision of distributed ancillary services in active distribution systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    14. Moarefdoost, M. Mohsen & Lamadrid, Alberto J. & Zuluaga, Luis F., 2016. "A robust model for the ramp-constrained economic dispatch problem with uncertain renewable energy," Energy Economics, Elsevier, vol. 56(C), pages 310-325.
    15. Khaloie, Hooman & Abdollahi, Amir & Shafie-khah, Miadreza & Anvari-Moghaddam, Amjad & Nojavan, Sayyad & Siano, Pierluigi & Catalão, João P.S., 2020. "Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model," Applied Energy, Elsevier, vol. 259(C).
    16. Shaterabadi, Mohammad & Jirdehi, Mehdi Ahmadi, 2020. "Multi-objective stochastic programming energy management for integrated INVELOX turbines in microgrids: A new type of turbines," Renewable Energy, Elsevier, vol. 145(C), pages 2754-2769.
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    2. Mohammad Abdul Baseer & Venkatesan Vinoth Kumar & Ivan Izonin & Ivanna Dronyuk & Athyoor Kannan Velmurugan & Babu Swapna, 2023. "Novel Hybrid Optimization Techniques to Enhance Reliability from Reverse Osmosis Desalination Process," Energies, MDPI, vol. 16(2), pages 1-15, January.
    3. Fatemeh Marzbani & Akmal Abdelfatah, 2024. "Economic Dispatch Optimization Strategies and Problem Formulation: A Comprehensive Review," Energies, MDPI, vol. 17(3), pages 1-31, January.
    4. Yang, Wenqiang & Zhu, Xinxin & Xiao, Qinge & Yang, Zhile, 2023. "Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles," Energy, Elsevier, vol. 282(C).
    5. Yin, Linfei & Zhao, Lulin, 2021. "Rejectable deep differential dynamic programming for real-time integrated generation dispatch and control of micro-grids," Energy, Elsevier, vol. 225(C).
    6. Hlalele, Thabo G. & Zhang, Jiangfeng & Naidoo, Raj M. & Bansal, Ramesh C., 2021. "Multi-objective economic dispatch with residential demand response programme under renewable obligation," Energy, Elsevier, vol. 218(C).
    7. Mo, Qiu & Liu, Fang, 2020. "Modeling and optimization for distributed microgrid based on Modelica language," Applied Energy, Elsevier, vol. 279(C).

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