Enhanced energy management in smart microgrids using hybrid optimization and demand response strategies

• Industry changes reshape structure and competition in advanced economies. • Renewables improve reliability, efficiency, and flexibility in networks. • Decentralized production poses microgrid management challenges. • A novel optimization model enhances smart microgrid resilience. • Hybrid DRPs and IBT tackle renewable resource uncertainties. This paper presents a groundbreaking optimization model for efficient and resilient energy management in smart microgrids, particularly addressing challenges posed by decentralized renewable energy sources (RES) integration. The proposed model advances microgrid performance by minimizing operational costs, reducing pollution emissions, and maximizing RES utilization. A distinctive feature of this model is its hybrid strategy, which combines Demand Response Plans (DRPs) with an Incline Block Tariff (IBT). This approach engages industrial, commercial, and residential consumers to manage the inherent uncertainty and non-linearity of RES, thereby enhancing operational flexibility and reliability. In addition, a two-stage adjustable robust optimization model is introduced, supporting day-ahead planning that ensures secure and cost-effective energy management even under significant uncertainties in renewable energy production. The model is evaluated through two scenarios—operational cost and pollution emissions, and operational cost and availability—both with and without the DRPS and IBT scheme. Simulation results demonstrate that the model achieves substantial reductions in both costs and emissions while significantly improving system reliability and availability. The hybrid optimization model significantly enhances smart microgrid management. With the combined DRPS and IBT scheme, operational costs dropped by 23.21%, and emissions from wind and solar power decreased by 7.7% and 3.7%, respectively. This model improves cost-effectiveness and availability, optimizing renewable energy integration in microgrids.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2024-12-24
DOI
https://doi.org/10.1016/j.ijepes.2024.110421
Citations
21
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
4.38
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article

Enhanced energy management in smart microgrids using hybrid optimization and demand response strategies

Genzhu Li, Lei Yang, L. H. Wu
21 citations
International Journal of Electrical Power & Energy Systems
Smart Grid Energy Management
4.38
article

Enhanced energy management in smart microgrids using hybrid optimization and demand response strategies

Genzhu Li, Lei Yang, L. H. Wu
article en
21 citations

Abstract

• Industry changes reshape structure and competition in advanced economies. • Renewables improve reliability, efficiency, and flexibility in networks. • Decentralized production poses microgrid management challenges. • A novel optimization model enhances smart microgrid resilience. • Hybrid DRPs and IBT tackle renewable resource uncertainties. This paper presents a groundbreaking optimization model for efficient and resilient energy management in smart microgrids, particularly addressing challenges posed by decentralized renewable energy sources (RES) integration. The proposed model advances microgrid performance by minimizing operational costs, reducing pollution emissions, and maximizing RES utilization. A distinctive feature of this model is its hybrid strategy, which combines Demand Response Plans (DRPs) with an Incline Block Tariff (IBT). This approach engages industrial, commercial, and residential consumers to manage the inherent uncertainty and non-linearity of RES, thereby enhancing operational flexibility and reliability. In addition, a two-stage adjustable robust optimization model is introduced, supporting day-ahead planning that ensures secure and cost-effective energy management even under significant uncertainties in renewable energy production. The model is evaluated through two scenarios—operational cost and pollution emissions, and operational cost and availability—both with and without the DRPS and IBT scheme. Simulation results demonstrate that the model achieves substantial reductions in both costs and emissions while significantly improving system reliability and availability. The hybrid optimization model significantly enhances smart microgrid management. With the combined DRPS and IBT scheme, operational costs dropped by 23.21%, and emissions from wind and solar power decreased by 7.7% and 3.7%, respectively. This model improves cost-effectiveness and availability, optimizing renewable energy integration in microgrids.

International Journal of Electrical Power & Energy SystemsVol. 164
North China Electric Power University (CN), North China University of Water Resources and Electric Power (CN), PowerChina (China) (CN), Xi'an Jiaotong University (CN)
Affordable and clean energy
Openalex Percentile: Top 5%
Smart Grid Energy Management
4.38
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