Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage
Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents. While battery and hydrogen storage are commonly used for peak s...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2025-06-01
|
| Series: | iEnergy |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.23919/IEN.2025.0013 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849426167191306240 |
|---|---|
| author | Vineeth Vijayan Ali Arzani Satish M. Mahajan |
| author_facet | Vineeth Vijayan Ali Arzani Satish M. Mahajan |
| author_sort | Vineeth Vijayan |
| collection | DOAJ |
| description | Grid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents. While battery and hydrogen storage are commonly used for peak shaving, ice-based thermal energy storage systems (TESSs) offer a direct way to reduce cooling loads without electrical conversion. This paper presents a multi-objective planning framework that optimizes TESS dispatch, network topology, and photovoltaic (PV) inverter reactive power support to address operational issues in active distribution networks. The objectives of the proposed scheme include minimizing peak demand, voltage deviations, and PV inverter VAr dependency. The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization (MOPSO) method. The MATLAB–OpenDSS simulations for a modified IEEE-123 bus system show a 7.1% reduction in peak demand, a 13% reduction in voltage deviation, and a 52% drop in PV inverter VAr usage. The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters. Thus, unlike earlier studies, this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network. |
| format | Article |
| id | doaj-art-efd0be20564d4a88a301debb0e88a5b5 |
| institution | Kabale University |
| issn | 2771-9197 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | iEnergy |
| spelling | doaj-art-efd0be20564d4a88a301debb0e88a5b52025-08-20T03:29:31ZengTsinghua University PressiEnergy2771-91972025-06-01429810610.23919/IEN.2025.0013Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storageVineeth Vijayan0Ali Arzani1Satish M. Mahajan2Center for Energy Systems Research (CESR), Tennessee Technological University, Cookeville, TN 38505, USACenter for Energy Systems Research (CESR), Tennessee Technological University, Cookeville, TN 38505, USACenter for Energy Systems Research (CESR), Tennessee Technological University, Cookeville, TN 38505, USAGrid-scale energy storage systems provide effective solutions to address challenges such as supply-load imbalances and voltage violations resulting from the non-coinciding nature of renewable energy generation and peak demand incidents. While battery and hydrogen storage are commonly used for peak shaving, ice-based thermal energy storage systems (TESSs) offer a direct way to reduce cooling loads without electrical conversion. This paper presents a multi-objective planning framework that optimizes TESS dispatch, network topology, and photovoltaic (PV) inverter reactive power support to address operational issues in active distribution networks. The objectives of the proposed scheme include minimizing peak demand, voltage deviations, and PV inverter VAr dependency. The mixed-integer nonlinear programming problem is solved using a Pareto-based multi-objective particle swarm optimization (MOPSO) method. The MATLAB–OpenDSS simulations for a modified IEEE-123 bus system show a 7.1% reduction in peak demand, a 13% reduction in voltage deviation, and a 52% drop in PV inverter VAr usage. The obtained solutions confirm minimal operational stress on control devices such as switches and PV inverters. Thus, unlike earlier studies, this work combines all three strategies to offer an effective solution for the operational planning of the active distribution network.https://www.sciopen.com/article/10.23919/IEN.2025.0013operational planningpower distribution networkpv invertersthermal energy storage systemstopology selection |
| spellingShingle | Vineeth Vijayan Ali Arzani Satish M. Mahajan Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage iEnergy operational planning power distribution network pv inverters thermal energy storage systems topology selection |
| title | Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage |
| title_full | Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage |
| title_fullStr | Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage |
| title_full_unstemmed | Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage |
| title_short | Enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage |
| title_sort | enhancing operational planning of active distribution networks considering effective topology selection and thermal energy storage |
| topic | operational planning power distribution network pv inverters thermal energy storage systems topology selection |
| url | https://www.sciopen.com/article/10.23919/IEN.2025.0013 |
| work_keys_str_mv | AT vineethvijayan enhancingoperationalplanningofactivedistributionnetworksconsideringeffectivetopologyselectionandthermalenergystorage AT aliarzani enhancingoperationalplanningofactivedistributionnetworksconsideringeffectivetopologyselectionandthermalenergystorage AT satishmmahajan enhancingoperationalplanningofactivedistributionnetworksconsideringeffectivetopologyselectionandthermalenergystorage |