Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios
A deterministic Mixed-Integer Nonlinear Programming (MINLP) model for the Integrated Generation and Transmission Expansion Planning (IGTEP) problem is presented. The proposed framework is distinguished by its foundation on the complete AC power flow formulation, which is solved to global optimality...
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2025-07-01
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| author | Edison W. Intriago Ponce Alexander Aguila Téllez |
| author_facet | Edison W. Intriago Ponce Alexander Aguila Téllez |
| author_sort | Edison W. Intriago Ponce |
| collection | DOAJ |
| description | A deterministic Mixed-Integer Nonlinear Programming (MINLP) model for the Integrated Generation and Transmission Expansion Planning (IGTEP) problem is presented. The proposed framework is distinguished by its foundation on the complete AC power flow formulation, which is solved to global optimality using BARON, a deterministic MINLP solver, which ensures the identification of truly optimal expansion strategies, overcoming the limitations of heuristic approaches that may converge to local optima. This approach is employed to establish a definitive, high-fidelity economic and technical benchmark, addressing the limitations of commonly used DC approximations and metaheuristic methods that often fail to capture the nonlinearities and interdependencies inherent in power system planning. The co-optimization model is formulated to simultaneously minimize the total annualized costs, which include investment in new generation and transmission assets, the operating costs of the entire generator fleet, and the cost of unsupplied energy. The model’s effectiveness is demonstrated on the IEEE 14-bus system under various dynamic load growth scenarios and planning horizons. A key finding is the model’s ability to identify the most economic expansion pathway; for shorter horizons, the optimal solution prioritizes strategic transmission reinforcements to unlock existing generation capacity, thereby deferring capital-intensive generation investments. However, over longer horizons with higher demand growth, the model correctly identifies the necessity for combined investments in both significant new generation capacity and further network expansion. These results underscore the value of an integrated, AC-based approach, demonstrating its capacity to reveal non-intuitive, economically superior expansion strategies that would be missed by decoupled or simplified models. The framework thus provides a crucial, high-fidelity benchmark for the validation of more scalable planning tools. |
| format | Article |
| id | doaj-art-943a238a0ccd4df1844253ee0fe3f133 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Energies |
| spelling | doaj-art-943a238a0ccd4df1844253ee0fe3f1332025-08-20T03:02:48ZengMDPI AGEnergies1996-10732025-07-011815402710.3390/en18154027Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load ScenariosEdison W. Intriago Ponce0Alexander Aguila Téllez1GIREI Research Group, Electrical Engineering Department, Universidad Politécnica Salesiana, Quito 170146, Pichincha, EcuadorGIREI Research Group, Electrical Engineering Department, Universidad Politécnica Salesiana, Quito 170146, Pichincha, EcuadorA deterministic Mixed-Integer Nonlinear Programming (MINLP) model for the Integrated Generation and Transmission Expansion Planning (IGTEP) problem is presented. The proposed framework is distinguished by its foundation on the complete AC power flow formulation, which is solved to global optimality using BARON, a deterministic MINLP solver, which ensures the identification of truly optimal expansion strategies, overcoming the limitations of heuristic approaches that may converge to local optima. This approach is employed to establish a definitive, high-fidelity economic and technical benchmark, addressing the limitations of commonly used DC approximations and metaheuristic methods that often fail to capture the nonlinearities and interdependencies inherent in power system planning. The co-optimization model is formulated to simultaneously minimize the total annualized costs, which include investment in new generation and transmission assets, the operating costs of the entire generator fleet, and the cost of unsupplied energy. The model’s effectiveness is demonstrated on the IEEE 14-bus system under various dynamic load growth scenarios and planning horizons. A key finding is the model’s ability to identify the most economic expansion pathway; for shorter horizons, the optimal solution prioritizes strategic transmission reinforcements to unlock existing generation capacity, thereby deferring capital-intensive generation investments. However, over longer horizons with higher demand growth, the model correctly identifies the necessity for combined investments in both significant new generation capacity and further network expansion. These results underscore the value of an integrated, AC-based approach, demonstrating its capacity to reveal non-intuitive, economically superior expansion strategies that would be missed by decoupled or simplified models. The framework thus provides a crucial, high-fidelity benchmark for the validation of more scalable planning tools.https://www.mdpi.com/1996-1073/18/15/4027power system planninggeneration expansiontransmission network expansionsimultaneous expansion planningmixed-integer nonlinear programming (MINLP)dynamic load scenarios |
| spellingShingle | Edison W. Intriago Ponce Alexander Aguila Téllez Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios Energies power system planning generation expansion transmission network expansion simultaneous expansion planning mixed-integer nonlinear programming (MINLP) dynamic load scenarios |
| title | Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios |
| title_full | Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios |
| title_fullStr | Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios |
| title_full_unstemmed | Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios |
| title_short | Integrated Generation and Transmission Expansion Planning Through Mixed-Integer Nonlinear Programming in Dynamic Load Scenarios |
| title_sort | integrated generation and transmission expansion planning through mixed integer nonlinear programming in dynamic load scenarios |
| topic | power system planning generation expansion transmission network expansion simultaneous expansion planning mixed-integer nonlinear programming (MINLP) dynamic load scenarios |
| url | https://www.mdpi.com/1996-1073/18/15/4027 |
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