1. Modeling and Simulation of Distribution Networks with High Renewable Penetration in Open-Source Software: QGIS and OpenDSS.
- Author
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De-Jesús-Grullón, Ramón E., Batista Jorge, Rafael Omar, Espinal Serrata, Abraham, Bueno Díaz, Justin Eladio, Pichardo Estévez, Juan José, and Guerrero-Rodríguez, Nestor Francisco
- Subjects
DISTRIBUTED power generation ,GEOGRAPHIC information systems ,ELECTRIC circuits ,POWER resources ,RENEWABLE energy sources - Abstract
There are important challenges in modeling large electrical distribution circuits, especially with the presence of distributed renewable generation. Constructing simulations to assess the effect of the penetration of distributed generation on electrical distribution networks has become of great importance for Distribution Network Operators (DNOs). This paper proposes a simulation strategy based on open-source platforms and the integration of scripting tools for the rapid modeling of large-scale electrical distribution circuits with distributed renewable generation. The implementation is based on the adaptation of a tool called QGIS2OpenDSS, which creates OpenDSS distribution network models directly from an open-source geographic information system, QGIS. The plugin's capabilities are demonstrated using a real distribution feeder with more than 60% penetration of renewable generation based on photovoltaic systems. These simulations are carried out using real data from a circuit provided by a DNO in the Dominican Republic, which is used to demonstrate how this approach provides a more accessible and flexible way to simulate and assess the effect of Distributed Energy Resources (DERs) in medium voltage (MV) and low voltage (LV) networks, enabling utilities to evaluate system performance and identify potential issues. The integration of this open-source tool within the DNO software stack enables users to apply it according to specific project needs, enhancing their capability to analyze and manage high DER penetration levels, aiding in better planning, operation, and decision-making processes related to renewable energy projects. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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