TY - GEN
T1 - AC Power Flow-Based Co-Optimization for Integrated Generation and Transmission Network Expansion Planning
AU - Chillogalli, José Eduardo
AU - Torres Contreras, Santiago Patricio
AU - Romero, Rubén R.
AU - Chumbi Quito, Wilson Enrique
AU - Ergun, Hakan
AU - Van Hertem, Dirk
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The integrated Generation and Transmission Network Expansion Planning (GTNEP) models have been developed to enable simultaneous investment decisions that consider both investment and operational components. In this research, a new methodology to assess the GTNEP is proposed, which takes into account the integrated planning of new generation power plants, transmission lines, reactive power allocation, and network power losses. To address the GTNEP, the operational problem is formulated using the AC optimal power flow, providing more realistic solutions. As a solution method, the Iterated Greedy Algorithm (IGA), and a hybridization of differential evolution with the tabu search (DE-TS) meta-heuristic were implemented. The proposed approach was tested using the 6-bus Garver test system. The results demonstrate that more cost-effective and realistic expansion plans are found with integrated AC-GTNEP compared to the sequential approach of first solving Generation Expansion Planning (GEP), and then Transmission Network Expansion Planning (TNEP).
AB - The integrated Generation and Transmission Network Expansion Planning (GTNEP) models have been developed to enable simultaneous investment decisions that consider both investment and operational components. In this research, a new methodology to assess the GTNEP is proposed, which takes into account the integrated planning of new generation power plants, transmission lines, reactive power allocation, and network power losses. To address the GTNEP, the operational problem is formulated using the AC optimal power flow, providing more realistic solutions. As a solution method, the Iterated Greedy Algorithm (IGA), and a hybridization of differential evolution with the tabu search (DE-TS) meta-heuristic were implemented. The proposed approach was tested using the 6-bus Garver test system. The results demonstrate that more cost-effective and realistic expansion plans are found with integrated AC-GTNEP compared to the sequential approach of first solving Generation Expansion Planning (GEP), and then Transmission Network Expansion Planning (TNEP).
KW - Co-optimization
KW - Generation Expansion Planning
KW - Integrated planning
KW - Transmission Expansion Planning
KW - Co-optimization
KW - Generation Expansion Planning
KW - Integrated planning
KW - Transmission Expansion Planning Indexed keywords
UR - https://www.scopus.com/pages/publications/85207440221
UR - https://ieeexplore.ieee.org/document/10689001
U2 - 10.1109/PESGM51994.2024.10689001
DO - 10.1109/PESGM51994.2024.10689001
M3 - Contribución a la conferencia
AN - SCOPUS:85207440221
SN - 979-8-3503-8184-9
T3 - IEEE Power and Energy Society General Meeting
SP - 1
EP - 5
BT - 2024 IEEE Power and Energy Society General Meeting, PESGM 2024
PB - IEEE Computer Society
CY - Seattle, Washington
T2 - 2024 IEEE Power and Energy Society General Meeting, PESGM 2024
Y2 - 21 July 2024 through 25 July 2024
ER -