Scenario-based sensitivity-driven energy storage optimization for economic and carbon efficiency in multi-vector energy communities

• Integration of heat and power dispatch to balance economic and environmental objectives. • Addressing seasonal dynamics and enhancing the adaptability of LISEC with heat pumps and electric-thermal storage devices. • Demonstrating practical feasibility with a real-world LISEC system comprising renewable energy sources. • Conducting a scenario-based sensitivity analysis to evaluate the robustness of the optimization results. The pressure to decarbonize power systems is increasing. Nonetheless, there are serious challenges in performing economic analyses of zero-carbon power systems. The sustainable operation of integrated heat and power systems is vital to ensure economic efficiency in the heat generation sector and reduce carbon emissions in power system dispatch. A bi-objective mixed-integer linear programming approach with scenario-based sensitivity evaluation is proposed in this study to break the silo between heat and power dispatch in local integrated smart energy communities (LISEC). The approach uses a dual-objective optimization algorithm that minimizes carbon production while minimizing cost and balancing economic and emission objectives. Dispatch analysis has also considered the impact of heat pumps and electric-thermal storage devices. The proposed method is applied to a LISEC system that consists of a 33-bus distribution network and a 58-node heating network with 26 heating demands to validate the proposed method. It comprises the distribution network interacting with the main grid for power exchange, wind turbines, battery energy storage, and combined heat and power (CHP) units. On the other hand, the district heating network consists of heat pumps, CHP, a gas boiler, and thermal storage tanks. A wide-ranging scenario-based sensitivity evaluation assesses the stability of optimization outcomes, principal components that determine economic feasibility and carbon output, and the effects of changes in energy storage capability and demand variability. The results underline that energy storage systems have proved to be a key component in strengthening the adequacy and performance of the electricity grid in extreme weather conditions.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2025-08-18
DOI
https://doi.org/10.1016/j.ijepes.2025.111007
Citations
2
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
1.46

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article

Scenario-based sensitivity-driven energy storage optimization for economic and carbon efficiency in multi-vector energy communities

Hossein Shayeghi, Pierluigi Siano, Adriano Sciacovelli, Abdollah Younesi
2 citations
International Journal of Electrical Power & Energy Systems
Integrated Energy Systems Optimization
1.46
article

Scenario-based sensitivity-driven energy storage optimization for economic and carbon efficiency in multi-vector energy communities

Hossein Shayeghi, Pierluigi Siano, Adriano Sciacovelli, Abdollah Younesi
article en
2 citations

Abstract

• Integration of heat and power dispatch to balance economic and environmental objectives. • Addressing seasonal dynamics and enhancing the adaptability of LISEC with heat pumps and electric-thermal storage devices. • Demonstrating practical feasibility with a real-world LISEC system comprising renewable energy sources. • Conducting a scenario-based sensitivity analysis to evaluate the robustness of the optimization results. The pressure to decarbonize power systems is increasing. Nonetheless, there are serious challenges in performing economic analyses of zero-carbon power systems. The sustainable operation of integrated heat and power systems is vital to ensure economic efficiency in the heat generation sector and reduce carbon emissions in power system dispatch. A bi-objective mixed-integer linear programming approach with scenario-based sensitivity evaluation is proposed in this study to break the silo between heat and power dispatch in local integrated smart energy communities (LISEC). The approach uses a dual-objective optimization algorithm that minimizes carbon production while minimizing cost and balancing economic and emission objectives. Dispatch analysis has also considered the impact of heat pumps and electric-thermal storage devices. The proposed method is applied to a LISEC system that consists of a 33-bus distribution network and a 58-node heating network with 26 heating demands to validate the proposed method. It comprises the distribution network interacting with the main grid for power exchange, wind turbines, battery energy storage, and combined heat and power (CHP) units. On the other hand, the district heating network consists of heat pumps, CHP, a gas boiler, and thermal storage tanks. A wide-ranging scenario-based sensitivity evaluation assesses the stability of optimization outcomes, principal components that determine economic feasibility and carbon output, and the effects of changes in energy storage capability and demand variability. The results underline that energy storage systems have proved to be a key component in strengthening the adequacy and performance of the electricity grid in extreme weather conditions.

International Journal of Electrical Power & Energy SystemsVol. 171
University of Salerno (IT), Universitatea Națională de Știință și Tehnologie Politehnica București (RO), University of Mohaghegh Ardabili (IR), Technical University of Denmark (DK)
Ministerul Cercetării şi Inovării
Affordable and clean energy
Openalex Percentile: Top 16%
Integrated Energy Systems Optimization
1.46
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