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Low-Impact Current-Based Distributed Monitoring System for Medium Voltage Networks
- Source :
- Energies, Vol 14, Iss 17, p 5308 (2021)
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- Distribution networks are currently subject to a huge revolution in terms of assets being installed. In particular, the massive spread of renewable energy sources has drastically changed the way of approaching the grid. For example, renewables affected (i) the production of the legacy power plants, (ii) the quality of the supplied energy, decreasing it, (iii) the fault detection and location, etc. To mitigate the significant drawbacks of the renewables’ presence, several intelligent electronic devices have been (and are being) developed and installed among the grid. The aim is to increase grid monitoring and knowledge of its status. However, considering the significant number of nodes of the distribution network, compared to the transmission one, the process of installing new equipment is not effortless and is also quite expensive. This work aims at emphasizing a new concept of distributed monitoring systems, based on the phasor measurement unit’s current measurements, and a controlling algorithm to exploit it. The idea underneath the work is to avoid the out-of-service time needed and the costs associated with the installation of voltage sensors. Therefore, this paper describes an algorithm that exploits measurements from existing equipment and current measurements from PMUs to obtain information on the load and the node voltages. The algorithm is then tested on simulated power networks of increasing complexity and verified with an uncertainty evaluation. The results obtained from the simulation confirm the applicability and effectiveness of the algorithm and the benefits of a current-based monitoring system.
Details
- Language :
- English
- ISSN :
- 19961073
- Volume :
- 14
- Issue :
- 17
- Database :
- Directory of Open Access Journals
- Journal :
- Energies
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.64ec9a8e134269a5f8857a8637b4e4
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/en14175308