Stochastic approach for optimal multi-objective energy management of multi-energy Microgrids incorporating a time-of-use-based demand response program

Articles in Press

Document Type : Research Paper

Authors
Gholamreza Salehi
Mir-Mohammad Mir-Mousavi
Afshin Mohseni Arasyeh
Hassan Feshki Farahani
Kamran Lari
Department of Mechanical Engineering, CT.C., Islamic Azad University, Tehran, Iran
10.22075/ijnaa.2026.40857.5669
Abstract
The growing adoption of distributed and renewable energies has significantly improved the sustainability of multi-energy microgrids (MEMGs). This research presents a novel stochastic model for optimal energy management of MEMGs featuring different energy sources, including electricity, heat and storage systems, by addressing uncertainties related to renewables and load in grid-connected and islanded modes while decreasing emissions and operational costs. The proposed optimal energy management system (EMS) incorporates a demand response program (DRP) along with a time-of-use (TOU) pricing model to enhance efficiency and reduce costs and emissions. Given the conflicting nature of the cost and emission minimization objectives, a multi-objective particle swarm optimization (MOPSO) algorithm is formulated to generate the Pareto optimal front. Furthermore, a fuzzy decision-making mechanism is applied to determine the best compromise solution. To achieve this goal, various scenarios are analyzed based on stochastic scheduling of thermal and power resources. However, due to the volume of simulation outputs, results are demonstrated for the most probable case. The total daily cost and emissions are presented for three case studies: (i) grid-connected case, (ii) islanded case, and (iii) time-of-use (TOU)--based DRP in the grid-connected case. The obtained results revealed that the minimization of operational cost and emission cost in Case B is improved by 9.7% and 15.3% compared to Case A. However, integrating TOU-DRP into EMS (i.e., Case C) has led to 3.25\% and 1.37% improvements in operational costs and emissions, respectively, compared to Case B without the inclusion of DRP.
Keywords
Multi-energy microgrid
CHP
emission reduction
operational cost reduction
renewable energy sources
uncertainties
MOPSO
TOU-DRP
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International Journal of Nonlinear Analysis and Applications

Articles in Press, Corrected Proof
Available Online from 13 November 2026

  • Receive Date 05 April 2026
  • Revise Date 11 May 2026
  • Accept Date 21 June 2026