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Energies
Volume 12
Issue 23
10.3390/en12234500
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Article

Synthetic Models of Distribution Networks Based on Open Data and Georeferenced Information

by
Giuditta Pisano
1,*,
Nayeem Chowdhury
1,2,
Massimiliano Coppo
3,
Nicola Natale
1,
Giacomo Petretto
2,
Gian Giuseppe Soma
1,
Roberto Turri
3 and
Fabrizio Pilo
1
1
Department of Electrical and Electronic Engineering, University of Cagliari, 09100 Cagliari, Italy
2
Enel Produzione Società per Azioni (S.p.A), 56122 Pisa, Italy
3
Department of Industrial Engineering, University of Padova, 35131 Padova, Italy
*
Author to whom correspondence should be addressed.
Energies 2019, 12(23), 4500; https://doi.org/10.3390/en12234500
Received: 24 October 2019 / Revised: 16 November 2019 / Accepted: 18 November 2019 / Published: 26 November 2019
(This article belongs to the Special Issue Distribution System Optimization)
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Abstract

Many planning and operation studies that aim at fully assessing and optimizing the performance of the distribution grids, in response to the current trends, cannot ignore grid limitations. Modelling the distribution system, by including the electrical characteristics of the network (e.g., topology) and end user behaviors, has become complex, but essential, for all conventional and emerging actors/players of power systems (i.e., system and market operators, regulators, new market parties as service providers, aggregators, researchers, etc.). This paper deals with a methodology that, starting from publicly available open data on the energy consumption of a region or wider area, is capable to obtain reasonable load and generation profiles for the network supplied by each primary substation in the region/area. Furthermore, by combining these profiles with territorial and socio-economic information, the proposed methodology is able to model the network in terms of lines, conductors, loads and generators. The results of this procedure are the synthetic networks of the real distribution networks, that do not correspond exactly to the actual networks, but can characterize them in a realistic way. Such models can be used for all the kind of optimization studies that need to check the grid limitations. Results derived from Italian test cases are presented and discussed. View Full-Text
Keywords: modelling; synthetic networks; distribution networks; distributed generation; renewable energy sources; representative distribution networks; open data modelling; synthetic networks; distribution networks; distributed generation; renewable energy sources; representative distribution networks; open data
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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MDPI and ACS Style

Pisano, G.; Chowdhury, N.; Coppo, M.; Natale, N.; Petretto, G.; Soma, G.G.; Turri, R.; Pilo, F. Synthetic Models of Distribution Networks Based on Open Data and Georeferenced Information. Energies 2019, 12, 4500. https://doi.org/10.3390/en12234500

AMA Style

Pisano G, Chowdhury N, Coppo M, Natale N, Petretto G, Soma GG, Turri R, Pilo F. Synthetic Models of Distribution Networks Based on Open Data and Georeferenced Information. Energies. 2019; 12(23):4500. https://doi.org/10.3390/en12234500

Chicago/Turabian Style

Pisano, Giuditta, Nayeem Chowdhury, Massimiliano Coppo, Nicola Natale, Giacomo Petretto, Gian G. Soma, Roberto Turri, and Fabrizio Pilo. 2019. "Synthetic Models of Distribution Networks Based on Open Data and Georeferenced Information" Energies 12, no. 23: 4500. https://doi.org/10.3390/en12234500

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