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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

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

Abstract

To model a realistic and highly flexible zero-carbon multi-energy system (ZCMES), a novel modelling strategy for ZCMES incorporating energy storage aging influence and integrated demand response (IDR) is proposed. Firstly, an integrated clustering-scenario generation and reduction approach (IC-SGRA) is developed to quantify the datasets uncertainties while selecting a representative day for the model. Secondly, the model is formulated as a multi-objective optimization problem to evaluate the influence of decision-maker preference concerning investment cost and operation cost on the optimal planning, and then weighting sum method is adopted to solve the problem. Finally, a Markowitz portfolio risk theory approach is adopted to mitigate the risk associated with uncertainties during decision-making, then an illustrative case study is used to analyse the proposed model. The simulation results reveal that the energy storage is overdesigned when aging effects are not considered, and the proposed approach can reduce the investment cost and the operation cost by 10.86% and 80.66% respectively, while the overall expenditure is reduced by 23.09%. Moreover, it was observed that the optimal total economic cost is obtained when high preference is given to the operation expenditure by the decision-makers while an equal preference resulted in a 0.24% reduction in investment cost and a 0.49% increase in total expenditure. Furthermore, the effect of BES lifetime and IDR load factors are also examined on ZCMES optimal planning. This study concluded that IDR is a promising strategy to encourage adopting zero-carbon policies flexibly and economically while choosing BES with high lifetime and tolerable capacity loss contribute to optimal planning.

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  • 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).
    • Handle: RePEc:eee:energy:v:226:y:2021:i:c:s0360544221005077
    DOI: 10.1016/j.energy.2021.120258
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    7. Li, Ye & Liu, Zihan & Sang, Yufeng & Hu, Jingfan & Li, Bojia & Zhang, Xinyu & Jurasz, Jakub & Zheng, Wandong, 2023. "Optimization of integrated energy system for low-carbon community considering the feasibility and application limitation," Applied Energy, Elsevier, vol. 348(C).
    8. Markus Fleschutz & Markus Bohlayer & Marco Braun & Michael D. Murphy, 2023. "From prosumer to flexumer: Case study on the value of flexibility in decarbonizing the multi-energy system of a manufacturing company," Papers 2301.07997, arXiv.org.
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    15. Tan, Caixia & Wang, Jing & Geng, Shiping & Pu, Lei & Tan, Zhongfu, 2021. "Three-level market optimization model of virtual power plant with carbon capture equipment considering copula–CVaR theory," Energy, Elsevier, vol. 237(C).
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    17. Mardan Dezfouli, Amir Hossein & Niroozadeh, Narjes & Jahangiri, Ali, 2023. "Energy, exergy, and exergoeconomic analysis and multi-objective optimization of a novel geothermal driven power generation system of combined transcritical CO2 and C5H12 ORCs coupled with LNG stream i," Energy, Elsevier, vol. 262(PB).
    18. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Gao, Chong & Ma, Zeyang, 2023. "A novel two-layer nested optimization method for a zero-carbon island integrated energy system, incorporating tidal current power generation," Renewable Energy, Elsevier, vol. 218(C).
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