Content area

Abstract

This paper presents a stochastic optimization model for integrated energy management in electrical and thermal microgrids, addressing uncertainties in renewable energy resources. The model optimizes the placement of combined heat and power (CHP) systems, energy storage, and demand-side management for both islanded and grid-connected operations. A multi-objective function is formulated to minimize energy losses, voltage deviations, costs, and renewable supply interruptions. The Large-Scale Two-Population Algorithm (LSTPA) is employed to solve the problem, with the IEEE 69-bus network as a case study. Results indicate that the proposed approach reduces energy losses to 3634 kWh, improves voltage stability to 0.9828 p.u., and lowers operational costs to $2845 in islanded mode. The findings demonstrate that increasing CHP units enhances system performance, reducing losses from 4280 kWh to 3634 kWh. This study offers valuable insights for policymakers and system operators in optimizing microgrid energy management while balancing efficiency, cost, and reliability. Future work will explore grid integration challenges and advanced control techniques to further optimize microgrid performance.

Details

Title
A novel LSTPA methodology for managing energy in electrical/thermal microgrids through CHP, battery resources, thermal storage, and demand-side strategies
Pages
42
Publication year
2025
Publication date
Dec 2025
Publisher
Springer Nature B.V.
e-ISSN
25208942
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3180789053
Copyright
Copyright Springer Nature B.V. Dec 2025