Summary
In recent years, the global energy transition has led to a considerable increase in the integration of Distributed Energy Resources (DER) into modern power systems. This process has been driven by the urgent need to mitigate the environmental impacts associated with conventional energy generation and to meet the growing demand for cleaner, more sustainable energy solutions. Supported by favorable energy policies and continuous technological advancements, the deployment of DER, such as photovoltaic (PV) systems, wind turbines, diesel-based distributed generation, and controllable loads, continues to grow. However, the massive incorporation of these resources has introduced new challenges in the operation, control, and stability of electrical networks. Among the most significant issues are power quality fluctuations, increased complexity in power flow management, harmonic distortion caused by converter-based resources, and the need to modernize existing infrastructure to maintain the reliability and operational security of power systems.
Read more Read lessIn response to these challenges, this study proposes an innovative methodology for detecting the connection of Distributed Energy Resources in power systems, based on the analysis of electromagnetic transient (EMT) signals. The primary objective is to enhance the detection and understanding of the transient effects caused by the integration of these resources, thereby contributing to the operational stability and security of electrical grids. Early detection of these disturbances is essential to ensure the correct operation of protection systems, minimize the risk of faults, and strengthen the overall resilience of the power network.
The methodology was validated through simulations using the IEEE 14-bus standard system, modeled in PowerFactory software. The study considered various types of DER, including photovoltaic systems, wind turbines, diesel distributed generators, and resistive loads, varying both the connection times and the injected power levels. The electromagnetic transient signals generated by these connection events were analyzed using wavelet transforms to extract relevant features in the time-frequency domain. These features were then processed through a frequency-based spectral classification algorithm, designed to accurately identify the specific type of connected resource based on its distinctive transient signature.
The simulation results confirmed the effectiveness of the proposed methodology for characterizing and identifying the connection of the different analyzed resources, demonstrating that each type of distributed energy resource exhibits distinctive transient signatures that can be reliably detected and classified. This approach represents a significant advancement in enhancing the monitoring and management capabilities for the integration of DERs in power systems. Additionally, the implementation of this methodology in real networks, either at strategic nodes or through meters capable of performing event-triggered analyses, would provide valuable information for grid operators and protection schemes. This would enable a more efficient response to disturbances, help maintain operational stability, and optimize the management of networks with high penetration of distributed and renewable resources.
Additional informations
| Publication type | Session Materials |
|---|---|
| Reference | C6_12134_2026 |
| Publication year | |
| Publisher | CIGRE |
| Country | Colombia |
| Study committees | |
| File size | 780 KB |
| Price for non member | 30 € |
| Price for member | 30 € |
Authors
NIETO Julián - UNIVALLE; CEBALLOS Jacobo - Univalle; CASTRO Carlos - M&M Bobinados; GOMEZ Eduardo - univalle
