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

Tobi Michael Alabi, Lin Lu, Zaiyue Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

45 Citations (Scopus)

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.

Original languageEnglish
Article number120258
JournalEnergy
Volume226
DOIs
Publication statusPublished - 1 Jul 2021

Keywords

  • Battery ageing
  • Integrated demand response
  • Multi-energy system
  • Risk optimization
  • Stochastic optimization
  • Zero-carbon

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Modelling and Simulation
  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Pollution
  • General Energy
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Management, Monitoring, Policy and Law
  • Electrical and Electronic Engineering

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