Affine-arithmetic-based microgrid interval optimization considering uncertainty and battery energy storage system degradation

Xuehan Zhang, Yongju Son, Taesu Cheong, Sungyun Choi

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


Microgrids can effectively integrate renewable energy sources (RESs) and provide power for local customers. However, uncertainties of RESs and loads pose challenges to microgrid operation. The traditional point optimization method is unrealistic, and the widely used stochastic optimization (SO) method is time-consuming. Besides, battery energy storage systems (BESSs) are critical dispatchable devices to alleviate adverse effects of uncertainty, so an accurate nonlinear degradation cost model of BESSs should also be proposed. To handle such problems, the paper proposes an affine–arithmetic (AA)-based microgrid interval optimization (IO) method considering uncertainty and BESS degradation. First, the AA theory is introduced to model the RES and load variation ranges as intervals and calculate the interval uncertainty. Then, a nonlinear BESS degradation cost model is proposed, which can assess battery degradation costs considering different charging and discharging behaviors. The nondominated sorting genetic algorithm-II (NSGA-II) is employed to solve the proposed microgrid IO framework. For validation, the proposed IO method was compared with the point optimization method and SO method under various uncertainty realizations in a modified IEEE 33 bus system. The simulation results indicated the effectiveness of the proposed IO method in terms of an equilibrium between the simulation time and optimization performance.

Original languageEnglish
Article number123015
Publication statusPublished - 2022 Mar 1

Bibliographical note

Funding Information:
This research was supported in part by the Basic Research Program through the National Research Foundation of Korea (NRF) funded by the MSIT (No. 2020R1A4A1019405 ) and in part by Korea Electric Power Corporation . (Grant number: R20XO02-19 ).

Publisher Copyright:
© 2021 Elsevier Ltd


  • Affine arithmetic
  • Battery energy storage system degradation
  • Interval optimization
  • Microgrid
  • Uncertainty

ASJC Scopus subject areas

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


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