Distributed Software Infrastructure for Evaluating the Integration of Photovoltaic Systems in Urban Districts

Lorenzo Bottaccioli, Edoardo Patti, Michelangelo Grosso, Gaetano Rasconà, Angelo Marotta, Salvatore Rinaudo, Andrea Acquaviva, Enrico Macii

2016

Abstract

Nowadays, the adoption of renewable energy sources distributed across the city is crucial for planning and developing the future Smart City. An accurate simulation and modelling of energy sources, such as Photovoltaic Panels (PV), is necessary to evaluate both economical and environmental benefits. With the growth of renewable sources in the city simulations of energy production became crucial for the DSO for evaluating retrofits or for network balancing events. In this paper, we present a software infrastructure for simulating the solar radiation and estimating the energy production of a district. The infrastructure simulates the PV production and evaluates the integration of such systems considering real electricity consumption data. In its core, the proposed solution models the behaviours of PV systems taking into account the digital surface of rooftops and sub-hourly meteorological data (e.g. solar radiation and temperature) to compute real-sky conditions. Then, such information is used to feed a model of the hardware components of PV systems to gain more accurate estimations of energy production in the district in real-sky conditions.

References

  1. Boland, J., Huang, J., and Ridley, B. (2013). Decomposing global solar radiation into its direct and diffuse components. Renew. Sustainable Energy Rev., 28:749- 756.
  2. Bottaccioli, L., Patti, E., Acquaviva, A., Macii, E., Jarre, M., and Noussan, M. (2015). A tool-chain to foster a new business model for photovoltaic systems integration exploiting an energy community approach. In Proc. of IEEE ETFA2015. IEEE.
  3. Camargo, L. R., Zink, R., Dorner, W., and Stoeglehner, G. (2015). Spatio-temporal modeling of roof-top photovoltaic panels for improved technical potential assessment and electricity peak load offsetting at the municipal scale. Comput. Environ. Urban Syst., 52:58-69.
  4. De Amicis, R., Conti, G., Patti, D., Ford, M., and Elisei, P. (2012). I-Scope-Interoperable Smart City Services through an Open Platform for Urban Ecosystems. na.
  5. de Sousa, L., Eykamp, C., Leopold, U., Baume, O., and Braun, C. (2012). iguess-a web based system integrating urban energy planning and assessment modelling for multi-scale spatial decision making. In Porc. of iEMSs 2012.
  6. Erbs, D., Klein, S., and Duffie, J. (1982). Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation. Solar Energy, 28(4):293-302.
  7. Freitas, S., Catita, C., Redweik, P., and Brito, M. (2015). Modelling solar potential in the urban environment: State-of-the-art review. Renew. Sustainable Energy Rev., 41:915-931.
  8. Ganu, T., Seetharam, D. P., Arya, V., Kunnath, R., Hazra, J., Husain, S. A., De Silva, L. C., and Kalyanaraman, S. (2012). nplug: a smart plug for alleviating peak loads. In Proc. of e-Energy 2012, page 30. ACM.
  9. Jakubiec, J. A. and Reinhart, C. F. (2013). A method for predicting city-wide electricity gains from photovoltaic panels based on lidar and gis data combined with hourly daysim simulations. Solar Energy, 93:127- 143.
  10. Luka, N., Seme, S., laus, D., tumberger, G., and alik, B. (2014). Buildings roofs photovoltaic potential assessment based on lidar (light detection and ranging) data. Energy, 66:598-609.
  11. Marotta, A., Ciccazzo, A., and Rinaudo, S. (2011). Modeling of a smart photovoltaic panel integrated selfpowered and high efficiency DC-DC Boost converter . PCIM Europe 2011.
  12. Orgill, J. and Hollands, K. (1977). Correlation equation for hourly diffuse radiation on a horizontal surface. Solar Energy, 19(4):357-359.
  13. Patti, E., Pons, E., Martellacci, D., Castagnetti, F. B., Acquaviva, A., and Macii, E. (2015). multiflex: Flexible multi-utility, multi-service smart metering architecture for energy vectors with active prosumers. In Proc. of SMARTGREENS 2015, pages 288-293.
  14. Ronzino, A., Osello, A., Patti, E., Bottaccioli, L., Danna, C., Lingua, A. M., Acquaviva, A., Macii, E., Grosso, M., Messina, G., and Rascon, G. The energy efficiency management at urban scale by means of integrated modelling. In Proc.of SEB-15. Elsevier.
  15. Suri, M., Huld, T., Dunlop, E., and Cebecauer, T. (2008). Geographic aspects of photovoltaics in europe: contribution of the pvgis website. J-STARS, IEEE Journal of, 1(1):34-41.
  16. Zoha, A., Gluhak, A., Imran, M. A., and Rajasegarar, S. (2012). Non-intrusive load monitoring approaches for disaggregated energy sensing: A survey. Sensors, 12(12):16838-16866.
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Paper Citation


in Harvard Style

Bottaccioli L., Patti E., Grosso M., Rasconà G., Marotta A., Rinaudo S., Acquaviva A. and Macii E. (2016). Distributed Software Infrastructure for Evaluating the Integration of Photovoltaic Systems in Urban Districts . In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-184-7, pages 357-362. DOI: 10.5220/0005879403570362


in Bibtex Style

@conference{smartgreens16,
author={Lorenzo Bottaccioli and Edoardo Patti and Michelangelo Grosso and Gaetano Rasconà and Angelo Marotta and Salvatore Rinaudo and Andrea Acquaviva and Enrico Macii},
title={Distributed Software Infrastructure for Evaluating the Integration of Photovoltaic Systems in Urban Districts},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2016},
pages={357-362},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005879403570362},
isbn={978-989-758-184-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Distributed Software Infrastructure for Evaluating the Integration of Photovoltaic Systems in Urban Districts
SN - 978-989-758-184-7
AU - Bottaccioli L.
AU - Patti E.
AU - Grosso M.
AU - Rasconà G.
AU - Marotta A.
AU - Rinaudo S.
AU - Acquaviva A.
AU - Macii E.
PY - 2016
SP - 357
EP - 362
DO - 10.5220/0005879403570362