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Multi-criteria optimization of multi-energy complementary systems considering reliability, economic and environmental effects

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  • Yang, Yu
  • Liu, Zhiqiang
  • Xie, Nan
  • Wang, Jiaqiang
  • Cui, Yanping
  • Agbodjan, Yawovi Souley

Abstract

Economic and environmental benefits of multi-energy complementary systems (MECSs) have become favorite topics. However, intermittent renewable energy and demand, as well as breakdown, may cause a failure of expected benefits or even supply shortages. This paper proposed an optimization method for MECSs that comprehensively considers reliability, economic and environmental performances. Markov Chain Monte Carlo (MCMC) method was adopted for reliability assessment. The multi-criteria optimization problem was solved using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and a decision-making method (TOPSIS). An actual indoor heated swimming pool with a MECS was conducted as a case study. Furthermore, the influences of scheduling strategy and power grid penetration (PGP) on MECSs were investigated. Compared with the case without considering reliability, the proposed optimization method exhibits more holistic performance, in terms of nearly 10 times lower expected energy supply shortage time (EESST) at the expense of 13.08% higher annual total cost (ATC) and 15.15% lower environmental performance coefficient (EPC). Additionally, the scheduling strategy greatly affects the performances, and a proposed scheduling strategy achieves 7.26% lower ATC, 7.69% higher EPC and about 40 times lower EESST. This study also reveals the necessity to focus on PGP as it significantly influences the strategy selection.

Suggested Citation

  • Yang, Yu & Liu, Zhiqiang & Xie, Nan & Wang, Jiaqiang & Cui, Yanping & Agbodjan, Yawovi Souley, 2023. "Multi-criteria optimization of multi-energy complementary systems considering reliability, economic and environmental effects," Energy, Elsevier, vol. 269(C).
    • Handle: RePEc:eee:energy:v:269:y:2023:i:c:s0360544223003274
    DOI: 10.1016/j.energy.2023.126933
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