Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning
This paper presents a mathematical model to solve the multi-stage transmission network expansion planning (MTNEP) problem considering renewable energy sources (RES) and the allocation of energy storage systems (ESSs). Given the stochastic nature of both renewable energy sources and demand, the imple...
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2025-01-01
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| author | Mario D. Pastrana Juan Carlos Cortez Juan Camilo Lopez Marina Lavorato Marcos J. Rider |
| author_facet | Mario D. Pastrana Juan Carlos Cortez Juan Camilo Lopez Marina Lavorato Marcos J. Rider |
| author_sort | Mario D. Pastrana |
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| description | This paper presents a mathematical model to solve the multi-stage transmission network expansion planning (MTNEP) problem considering renewable energy sources (RES) and the allocation of energy storage systems (ESSs). Given the stochastic nature of both renewable energy sources and demand, the implementation of representative periods (RPs) is proposed. RPs represent the behavior of the electrical power system over time series, including short-term variations, demand and RES correlations, and geographic factors, offering feasible computational complexity to solve the MTNEP problem. The proposed model is formulated as a deterministic equivalent mixed-integer linear programming (MILP) model for a set of RPs. The MILP model optimizes investments in transmission lines (TLs) and ESSs. Furthermore, the MILP model incorporates active power losses through piecewise linearization and <inline-formula> <tex-math notation="LaTeX">$N-1$ </tex-math></inline-formula> security constraints. A method is developed to reduce the combinatorial search space to deal with high-dimensional problems. The Garver’s 6-bus system, a modified IEEE 24-bus test system, and the northern Colombian transmission system are used to validate the proposed model. An extensive analysis of the impact of RES and ESSs on MTNEP is presented. Simultaneous optimization of TLs and ESSs provides better and cheaper MTNEPs compared to traditional methods. The effectiveness of ESSs in integrating RES, shifting electricity, reducing/delaying investments (especially when considering <inline-formula> <tex-math notation="LaTeX">$N-1$ </tex-math></inline-formula> security constraints) and alleviating grid congestion is evidenced. This shows that ESSs have great potential as reinforcement and flexibility elements in the MTNEP problem. |
| format | Article |
| id | doaj-art-cb7d51b939e44f2dbe888e10985f5ce6 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-cb7d51b939e44f2dbe888e10985f5ce62025-08-20T02:43:10ZengIEEEIEEE Access2169-35362025-01-011311195311196810.1109/ACCESS.2025.358272911048777Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion PlanningMario D. Pastrana0https://orcid.org/0000-0002-6872-0827Juan Carlos Cortez1https://orcid.org/0000-0003-2080-2468Juan Camilo Lopez2https://orcid.org/0000-0001-5646-8612Marina Lavorato3https://orcid.org/0000-0003-1669-3334Marcos J. Rider4https://orcid.org/0000-0001-5484-1161Corporate Engineering Department, ISA Interconexión Eléctrica S.A. E.S.P., Medellín, ColombiaDepartment of Systems and Energy (DSE), School of Electrical and Computer Engineering (FEEC), Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, BrazilFaculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente, Enschede, Overijssel, The NetherlandsDepartment of Systems and Energy (DSE), School of Electrical and Computer Engineering (FEEC), Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, BrazilDepartment of Systems and Energy (DSE), School of Electrical and Computer Engineering (FEEC), Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, BrazilThis paper presents a mathematical model to solve the multi-stage transmission network expansion planning (MTNEP) problem considering renewable energy sources (RES) and the allocation of energy storage systems (ESSs). Given the stochastic nature of both renewable energy sources and demand, the implementation of representative periods (RPs) is proposed. RPs represent the behavior of the electrical power system over time series, including short-term variations, demand and RES correlations, and geographic factors, offering feasible computational complexity to solve the MTNEP problem. The proposed model is formulated as a deterministic equivalent mixed-integer linear programming (MILP) model for a set of RPs. The MILP model optimizes investments in transmission lines (TLs) and ESSs. Furthermore, the MILP model incorporates active power losses through piecewise linearization and <inline-formula> <tex-math notation="LaTeX">$N-1$ </tex-math></inline-formula> security constraints. A method is developed to reduce the combinatorial search space to deal with high-dimensional problems. The Garver’s 6-bus system, a modified IEEE 24-bus test system, and the northern Colombian transmission system are used to validate the proposed model. An extensive analysis of the impact of RES and ESSs on MTNEP is presented. Simultaneous optimization of TLs and ESSs provides better and cheaper MTNEPs compared to traditional methods. The effectiveness of ESSs in integrating RES, shifting electricity, reducing/delaying investments (especially when considering <inline-formula> <tex-math notation="LaTeX">$N-1$ </tex-math></inline-formula> security constraints) and alleviating grid congestion is evidenced. This shows that ESSs have great potential as reinforcement and flexibility elements in the MTNEP problem.https://ieeexplore.ieee.org/document/11048777/Energy storage systemcombinatorial search space reduction methodmixed-integer linear programmingmulti-stage transmission network expansion planningrenewable energy sourcesrepresentative periods |
| spellingShingle | Mario D. Pastrana Juan Carlos Cortez Juan Camilo Lopez Marina Lavorato Marcos J. Rider Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning IEEE Access Energy storage system combinatorial search space reduction method mixed-integer linear programming multi-stage transmission network expansion planning renewable energy sources representative periods |
| title | Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning |
| title_full | Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning |
| title_fullStr | Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning |
| title_full_unstemmed | Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning |
| title_short | Analysis of the Impact of Renewable Energy Sources and Energy Storage Systems on Multi-Stage Transmission Network Expansion Planning |
| title_sort | analysis of the impact of renewable energy sources and energy storage systems on multi stage transmission network expansion planning |
| topic | Energy storage system combinatorial search space reduction method mixed-integer linear programming multi-stage transmission network expansion planning renewable energy sources representative periods |
| url | https://ieeexplore.ieee.org/document/11048777/ |
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