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Stochastic optimal planning scheme of a zero-carbon multi-energy system (ZC-MES) considering the uncertainties of individual energy demand and renewable resources: An integrated chance-constrained and decomposition algorithm (CC-DA) approach

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  • Alabi, Tobi Michael
  • Lu, Lin
  • Yang, Zaiyue

Abstract

Renewable resources stochasticity and energy demand variation are inevitable during the operation of energy systems. Thus, this paper presents novel stochastic planning and operation of a zero-carbon multi-energy system (ZC-MES) taking the uncertainties of individual energy demand and environmental conditions into consideration. The comprehensive mathematical model is developed as an optimization problem using Monte Carlo scenario generation, fast forward scenario reduction approach, chance-constrained programming, duality theory, and big-M linearization approach. Furthermore, benders decomposition is applied to split the large-scale optimization problem into an investment master problem (MP) and operation subproblem (SP), which are then solved iteratively. The obtained results indicate that by considering all the energy demand uncertainties as an individual entity in the model, the selected capacities of PV, AC, and HWS increase by 60%, 21%, and 10.6%, respectively, while, WT, WSHP, BES, and EC reduce by 14%, 15%, 11%, and 1.09%, respectively. Also, the optimal operation cost for the proposed model reduced by 5–10% compared to other scenarios, however, its annualized investment cost is 3–12% higher but the overall economic implication is optimal. In summary, the underlying reason for this optimal result is the combination of energy storage temporal arbitrage and energy output shifting technique that was implemented by the algorithm to maintain an optimal interrelationship balance and to favour the optimal sizing of the chosen technologies.

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  • Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2021. "Stochastic optimal planning scheme of a zero-carbon multi-energy system (ZC-MES) considering the uncertainties of individual energy demand and renewable resources: An integrated chance-constrained and," Energy, Elsevier, vol. 232(C).
  • Handle: RePEc:eee:energy:v:232:y:2021:i:c:s0360544221012482
    DOI: 10.1016/j.energy.2021.121000
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    References listed on IDEAS

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    1. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    2. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    3. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.
    4. Karasu, Seçkin & Altan, Aytaç & Bekiros, Stelios & Ahmad, Wasim, 2020. "A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series," Energy, Elsevier, vol. 212(C).
    5. Y. Zhang, 2007. "General Robust-Optimization Formulation for Nonlinear Programming," Journal of Optimization Theory and Applications, Springer, vol. 132(1), pages 111-124, January.
    6. Chen, Cong & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "Two-stage robust planning-operation co-optimization of energy hub considering precise energy storage economic model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.
    8. Mazzoni, Stefano & Ooi, Sean & Nastasi, Benedetto & Romagnoli, Alessandro, 2019. "Energy storage technologies as techno-economic parameters for master-planning and optimal dispatch in smart multi energy systems," Applied Energy, Elsevier, vol. 254(C).
    9. Wang, Yongli & Li, Ruiwen & Dong, Huanran & Ma, Yuze & Yang, Jiale & Zhang, Fuwei & Zhu, Jinrong & Li, Shuqing, 2019. "Capacity planning and optimization of business park-level integrated energy system based on investment constraints," Energy, Elsevier, vol. 189(C).
    10. Wang, Yongli & Li, Jiapu & Wang, Shuo & Yang, Jiale & Qi, Chengyuan & Guo, Hongzhen & Liu, Ximei & Zhang, Hongqing, 2020. "Operational optimization of wastewater reuse integrated energy system," Energy, Elsevier, vol. 200(C).
    11. Alabi, Tobi Michael & Lu, Lin & Yang, Zaiyue, 2021. "A novel multi-objective stochastic risk co-optimization model of a zero-carbon multi-energy system (ZCMES) incorporating energy storage aging model and integrated demand response," Energy, Elsevier, vol. 226(C).
    12. Correa-Florez, Carlos Adrian & Gerossier, Alexis & Michiorri, Andrea & Kariniotakis, Georges, 2018. "Stochastic operation of home energy management systems including battery cycling," Applied Energy, Elsevier, vol. 225(C), pages 1205-1218.
    13. Rahmaniani, Ragheb & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2017. "The Benders decomposition algorithm: A literature review," European Journal of Operational Research, Elsevier, vol. 259(3), pages 801-817.
    14. Zhou, Suyang & Sun, Kaiyu & Wu, Zhi & Gu, Wei & Wu, Gaoxiang & Li, Zhe & Li, Junjie, 2020. "Optimized operation method of small and medium-sized integrated energy system for P2G equipment under strong uncertainty," Energy, Elsevier, vol. 199(C).
    15. Comodi, Gabriele & Bartolini, Andrea & Carducci, Francesco & Nagaranjan, Balamurugan & Romagnoli, Alessandro, 2019. "Achieving low carbon local energy communities in hot climates by exploiting networks synergies in multi energy systems," Applied Energy, Elsevier, vol. 256(C).
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