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S. Gupta, D. A. Tirpak, N. Burger, J. Gupta, N. Hohne, A. I. Boncheva, G. M. Kanoan, C. Kolstad, J. A. Kruger, A. Michaelowa, S. Murase, J. Pershing, T. Saijo and A. Sari, “Policies, Instruments and Co-Operative Arrangements,” In: B. Metz, O. R. Davidson, P. R. Bosch, R. Dave and L. A. Meyer, Eds., Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, International Energy Agency (IEA), New York, 1998. Trends in Photovoltaic Applications—Survey Report of Selected IEA Countries between 1992 and 1997. IEAPVPS106: 1998.
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has been cited by the following article:

• TITLE: The Assessment of Localized Clustering of Photovoltaic Plants in Italy: The Role of Financial Incentives

  AUTHORS: Annalina Sarra, Eugenia Nissi

  KEYWORDS: Renewable Energy Sources; Photovoltaic Power System; Feed-in Tariff; Elliptic Scan Statistics; Localized Cluster

  JOURNAL NAME: Open Journal of Statistics, Vol.3 No.6A, December 27, 2013

  ABSTRACT: In recent years, the rapid growth of renewable energy sources (photovoltaic, biomass, geothermal, wind and hydroelectricity) constitutes a feasible solution for environmental problems created by the present production-consumption energy model. Photovoltaic (PV) is one of the most promising, renewable energy sources with great potential for development. Over the last decade, the diffusion of photovoltaic installations in Italy has recorded a considerable increase, displaying at the same time substantial regional dissimilarities. In this paper, we sustain the hypothesis that the installation of PV plants is first of all driven by the financial incentives granted. Using data for Italian provinces, derived under two different editions of the Energy Account, which represents the current Italian financing mechanism, we apply a statistical cluster detection method (the spatial elliptic scan statistics) to identify differences in the spatial distribution of PV plants, in terms of most concentration, throughout the Italian territory. The focus is on mapping the clusters and checking their spatial stability over time, when different subsidy schemes have been adopted. The evidence shows that in the latest detected clusters there are many Northern Italian provinces, with adverse climate conditions (low global irradiance level, low annual temperatures), which have rapidly taken advantage of incentives for solar energy installations.