TY - GEN
T1 - Transmission Expansion Planning Considering the Impact of Distributed Generation
AU - Matute, Nelson E.
AU - Torres, Santiago P.
AU - Castro, Carlos A.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Distributed Generation (DG) is a very important alternative to the traditional approach of centralized generation and plays a major role not only in electric distribution systems but also in transmission systems. The incidence of DG in the electrical system (sub-transmission and/or distribution) could defer the addition of new transmission circuits and reduce transmission network losses, representing potential economical savings. This paper studies the economic impact of DG on the Transmission Expansion Planning (TEP) problem including also the cost of transmission network losses. A long-term deterministic static transmission expansion planning using the mathematical AC model is presented. DG is modeled as the summation of each type of small-scale generation technology concentrated in the load node. The proposed TEP approach provides information on the optimal combination of transmission circuits and DG in load nodes. The problem, formulated using the AC model, corresponds to a full non convex, non-linear mixed-integer programming (MINLP) problem. Performance comparisons between Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA), to solve the problem, are shown. Garver 6 - bus and IEEE 24 - bus test systems are used to evaluate this TEP approach.
AB - Distributed Generation (DG) is a very important alternative to the traditional approach of centralized generation and plays a major role not only in electric distribution systems but also in transmission systems. The incidence of DG in the electrical system (sub-transmission and/or distribution) could defer the addition of new transmission circuits and reduce transmission network losses, representing potential economical savings. This paper studies the economic impact of DG on the Transmission Expansion Planning (TEP) problem including also the cost of transmission network losses. A long-term deterministic static transmission expansion planning using the mathematical AC model is presented. DG is modeled as the summation of each type of small-scale generation technology concentrated in the load node. The proposed TEP approach provides information on the optimal combination of transmission circuits and DG in load nodes. The problem, formulated using the AC model, corresponds to a full non convex, non-linear mixed-integer programming (MINLP) problem. Performance comparisons between Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA), to solve the problem, are shown. Garver 6 - bus and IEEE 24 - bus test systems are used to evaluate this TEP approach.
KW - AC model
KW - artificial fish swarm algorithm
KW - distributed generation
KW - electric power systems
KW - expansion planning
KW - particle swarm
KW - transmission
UR - https://www.scopus.com/pages/publications/85075859324
U2 - 10.1109/ISGTEurope.2019.8905460
DO - 10.1109/ISGTEurope.2019.8905460
M3 - Contribución a la conferencia
AN - SCOPUS:85075859324
T3 - Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
BT - Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
Y2 - 29 September 2019 through 2 October 2019
ER -