Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation
Abstract This paper presents a structured approach for the efficient operation of multi-carrier energy systems under the uncertainty of renewable energy sources. As the penetration of wind and solar energy increases, managing the resulting variability becomes critical to maintaining both economic ef...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-10404-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849234643587432448 |
|---|---|
| author | Ankit Garg K. R. Niazi Shubham Tiwari Sachin Sharma Tanuj Rawat |
| author_facet | Ankit Garg K. R. Niazi Shubham Tiwari Sachin Sharma Tanuj Rawat |
| author_sort | Ankit Garg |
| collection | DOAJ |
| description | Abstract This paper presents a structured approach for the efficient operation of multi-carrier energy systems under the uncertainty of renewable energy sources. As the penetration of wind and solar energy increases, managing the resulting variability becomes critical to maintaining both economic efficiency and operational flexibility. To address this, a two-stage multi objective optimization framework is proposed. In the first stage, the objective is to minimize daily operational costs while incorporating the uncertain behavior of renewables using a scenario-based stochastic approach. The second stage focuses on simultaneously enhancing system flexibility by maximizing the available capacities for both electrical and thermal energy generation and improving green house emissions. To evaluate system adaptability, two performance indicators are introduced: the Average Energy Generation Flexibility Index (AEGFI) and the Average Thermal Generation Flexibility Index (ATGFI). The optimization model is solved using the Modified Water Evaporation algorithm. Sensitivity analyses are also conducted to explore the effects of fluctuations in gas and electricity prices on system performance. The proposed model is applied to a generalized multi-carrier energy system. Simulation results demonstrate significant improvements in flexibility, with AEGFI and ATGFI increasing by 27.43% and 39.91%, respectively. Overall, the framework offers a comprehensive solution to balance cost-effectiveness and flexibility in energy systems with high shares of renewables. |
| format | Article |
| id | doaj-art-abf939d772ca449eb0a0c01d659d7c94 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-abf939d772ca449eb0a0c01d659d7c942025-08-20T04:03:06ZengNature PortfolioScientific Reports2045-23222025-07-0115112010.1038/s41598-025-10404-4Optimal energy management of multi-carrier energy system considering uncertainty in renewable generationAnkit Garg0K. R. Niazi1Shubham Tiwari2Sachin Sharma3Tanuj Rawat4Department of Electrical Engineering, Malaviya National Institute of TechnologyDepartment of Electrical Engineering, Malaviya National Institute of TechnologyDepartment of AFE, IIASADepartment of Electrical and Electronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher EducationGE VernovaAbstract This paper presents a structured approach for the efficient operation of multi-carrier energy systems under the uncertainty of renewable energy sources. As the penetration of wind and solar energy increases, managing the resulting variability becomes critical to maintaining both economic efficiency and operational flexibility. To address this, a two-stage multi objective optimization framework is proposed. In the first stage, the objective is to minimize daily operational costs while incorporating the uncertain behavior of renewables using a scenario-based stochastic approach. The second stage focuses on simultaneously enhancing system flexibility by maximizing the available capacities for both electrical and thermal energy generation and improving green house emissions. To evaluate system adaptability, two performance indicators are introduced: the Average Energy Generation Flexibility Index (AEGFI) and the Average Thermal Generation Flexibility Index (ATGFI). The optimization model is solved using the Modified Water Evaporation algorithm. Sensitivity analyses are also conducted to explore the effects of fluctuations in gas and electricity prices on system performance. The proposed model is applied to a generalized multi-carrier energy system. Simulation results demonstrate significant improvements in flexibility, with AEGFI and ATGFI increasing by 27.43% and 39.91%, respectively. Overall, the framework offers a comprehensive solution to balance cost-effectiveness and flexibility in energy systems with high shares of renewables.https://doi.org/10.1038/s41598-025-10404-4Multi-carrier energy systemPEVOptimizationEconomicGeneration flexibilityDemand response |
| spellingShingle | Ankit Garg K. R. Niazi Shubham Tiwari Sachin Sharma Tanuj Rawat Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation Scientific Reports Multi-carrier energy system PEV Optimization Economic Generation flexibility Demand response |
| title | Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation |
| title_full | Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation |
| title_fullStr | Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation |
| title_full_unstemmed | Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation |
| title_short | Optimal energy management of multi-carrier energy system considering uncertainty in renewable generation |
| title_sort | optimal energy management of multi carrier energy system considering uncertainty in renewable generation |
| topic | Multi-carrier energy system PEV Optimization Economic Generation flexibility Demand response |
| url | https://doi.org/10.1038/s41598-025-10404-4 |
| work_keys_str_mv | AT ankitgarg optimalenergymanagementofmulticarrierenergysystemconsideringuncertaintyinrenewablegeneration AT krniazi optimalenergymanagementofmulticarrierenergysystemconsideringuncertaintyinrenewablegeneration AT shubhamtiwari optimalenergymanagementofmulticarrierenergysystemconsideringuncertaintyinrenewablegeneration AT sachinsharma optimalenergymanagementofmulticarrierenergysystemconsideringuncertaintyinrenewablegeneration AT tanujrawat optimalenergymanagementofmulticarrierenergysystemconsideringuncertaintyinrenewablegeneration |