TY - GEN
T1 - Rooftop Solar PV Hosting Capacity Analysis in MV-LV Distribution Networks Using Quasi-Static Time-Series Simulation
AU - Chitacapa, Cesar Andres Patino
AU - Asanza, Sergio Patricio Zambrano
AU - Guaman, Edwin Marcelo Lema
AU - Leon, Brian Daniel Jaramillo
AU - Leite, Jonatas Boas
AU - Baquero, John Fredy Franco
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The massive interconnection of rooftop solar photovoltaic (PV) generation to the distribution network constitutes a challenge for the operation and planning of distribution network. In this environment, the performance of the distribution network may be affected and a comprehensive analysis of the hosting capacity in the medium and low voltage network is necessary. A quasi-static time-series and short-circuit analysis considering scenarios of PV systems penetration is proposed to accurately capture the effects of resource intermittency and load dynamics. Six metrics are used: overvoltage, voltage unbalance, thermal loading, fault currents, reverse power flow, and network losses. To evaluate the performance of the method, a real distribution feeder is used, as well as characteristic data of the classes of consumers. Since the relevance of a metric in the impact of the operation depends on the particular characteristics of each case, it is convenient to quantify these different metrics.
AB - The massive interconnection of rooftop solar photovoltaic (PV) generation to the distribution network constitutes a challenge for the operation and planning of distribution network. In this environment, the performance of the distribution network may be affected and a comprehensive analysis of the hosting capacity in the medium and low voltage network is necessary. A quasi-static time-series and short-circuit analysis considering scenarios of PV systems penetration is proposed to accurately capture the effects of resource intermittency and load dynamics. Six metrics are used: overvoltage, voltage unbalance, thermal loading, fault currents, reverse power flow, and network losses. To evaluate the performance of the method, a real distribution feeder is used, as well as characteristic data of the classes of consumers. Since the relevance of a metric in the impact of the operation depends on the particular characteristics of each case, it is convenient to quantify these different metrics.
KW - Distribution Networks
KW - Hosting Capacity
KW - Integrated Distribution Planning
KW - PV Systems
KW - Quasi-Static Time-Series
UR - https://www.scopus.com/pages/publications/85180013498
U2 - 10.1109/ISGT-LA56058.2023.10328352
DO - 10.1109/ISGT-LA56058.2023.10328352
M3 - Contribución a la conferencia
AN - SCOPUS:85180013498
T3 - 2023 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT-LA 2023
SP - 80
EP - 84
BT - 2023 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT-LA 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE PES Innovative Smart Grid Technologies Latin America, ISGT-LA 2023
Y2 - 6 November 2023 through 9 November 2023
ER -