B. 1. Multinomial and . Logit, DESCRIPTIVE STATISTICS AND TABLES Variables Congestion from CNOR Congestion to CNOR Log-odds mfx Log-odds mfx CNOR Hydro 0

. Year5-0, 660*** -0.00262*** -1.531*** -0

B. Table, Estimations for CNOR-CSUD Variables Congestion from SARD Congestion to SARD Log-odds mfx Log-odds mfx SARD Hydro 0

. Year3-4, 018*** -0.00108*** -1.897*** -0

. Year4-8, 216*** -0.00254*** -1.873*** -0

B. Table, Estimations for CSUD-SUD Variables Congestion from SICI Congestion to SICI Log-odds mfx Log-odds mfx SICI Hydro 0

F. Ardian, S. Concettini, and A. Creti, Intermittent Renewable Generation and Network Congestion: An Empirical Analysis of Italian Power Market, SSRN working paper series, 2015.
DOI : 10.2139/ssrn.2677118

URL : https://hal.archives-ouvertes.fr/hal-01218543

J. Bai and P. Perron, Computation and analysis of multiple structural change models, Journal of Applied Econometrics, vol.6, issue.1, pp.72-78, 2003.
DOI : 10.7202/602236ar

B. H. Baltagi, Econometric Analysis of Panel Data, 1995.

M. Bessec and O. Bouabdallah, What causes the forecasting failure of Markovswitching models? A Monte Carlo study, Studies in Nonlinear Dynamics and Econometrics, vol.9, issue.2, 2005.

T. Bollerslev, Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, vol.31, issue.3, pp.307-327, 1986.
DOI : 10.1016/0304-4076(86)90063-1

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.7380

E. Bompard, E. Carpaneto, G. Ciwei, R. Napoli, M. Benini et al., A game theory simulator for assessing the performances of competitive electricity markets, Electric Power Systems Research, pp.217-227, 2008.

S. Bordignon, D. W. Bunn, F. Lisi, N. , and F. , Combining day-ahead forecasts for British electricity prices, Energy Economics, vol.35, pp.88-103, 2013.
DOI : 10.1016/j.eneco.2011.12.001

URL : http://paduaresearch.cab.unipd.it/8785/1/2011_1_20110110132225.pdf

B. Bosco, L. Parisio, and M. Pelagatti, Deregulated Wholesale Electricity Prices in Italy: An Empirical Analysis, International Advances in Economic Research, vol.15, issue.3, pp.415-432, 2007.
DOI : 10.1093/biomet/54.3-4.403

N. Bowden and J. E. Payne, Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models, Energy Economics, vol.30, issue.6, pp.3186-3197, 2008.
DOI : 10.1016/j.eneco.2008.06.003

R. Carmona, M. Coulon, and D. Schwarz, Electricity price modeling and asset valuation: a multi-fuel structural approach, Mathematics and Financial Economics, vol.46, issue.1, pp.167-202, 2013.
DOI : 10.1287/mnsc.46.7.893.12034

URL : http://arxiv.org/abs/1205.2299

K. C. Chatzidimitriou, A. C. Chrysopoulos, A. L. Symeonidis, and P. A. Mitkas, Enhancing Agent Intelligence through Evolving Reservoir Networks for Predictions in Power Stock Markets, Lecture Notes in Computer Science, vol.20, issue.8, pp.228-247, 2012.
DOI : 10.1109/IS.2006.348454

S. Clo, A. Cataldi, and P. Zoppoli, The merit-order effect in the Italian power market: The impact of solar and wind generation on national wholesale electricity prices, Energy Policy, vol.77, pp.79-88, 2015.
DOI : 10.1016/j.enpol.2014.11.038

J. Contreras, R. Esp?anolaesp?-esp?anola, F. J. Nogales, and A. J. Conejo, ARIMA models to predict next-day electricity prices, IEEE Transactions on Power Systems, vol.18, issue.3, pp.1014-1020, 2003.
DOI : 10.1109/TPWRS.2002.804943

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.198.2576

M. Coulon and S. Howison, Stochastic behavior of the electricity bid stack: from fundamental drivers to power prices, The Journal of Energy Markets, vol.2, issue.1, pp.29-69, 2009.
DOI : 10.21314/JEM.2009.032

J. C. Cuaresma, J. Hlouskova, S. Kossmeier, and M. Obersteiner, Forecasting electricity spot-prices using linear univariate time-series models, Applied Energy, vol.77, issue.1, pp.87-106, 2004.
DOI : 10.1016/S0306-2619(03)00096-5

N. J. Cutler, N. D. Boerema, I. F. Macgill, and H. G. Outhred, High penetration wind generation impacts on spot prices in the Australian national electricity market, Energy Policy, vol.39, issue.10, pp.5939-5949, 2011.
DOI : 10.1016/j.enpol.2011.06.053

R. Dacco and C. Satchell, Why do regime-switching models forecast so badly?, Journal of Forecasting, vol.37, issue.1, pp.1-16, 1999.
DOI : 10.1257/jep.4.1.117

G. Dempster, J. Isaacs, and N. Smith, Price discovery in restructured electricity markets, Resource and Energy Economics, vol.30, issue.2, 2008.
DOI : 10.1016/j.reseneeco.2007.08.001

D. Dickey and W. Fuller, Distribution of the estimators for autoregressive time series with a unit root, Journal of American Statistical Association, vol.55, pp.277-301, 1987.

F. X. Diebold and R. S. Mariano, Comparing Predictive Accuracy, Journal of Business and Economic Statistics, vol.13, pp.253-63, 1995.
DOI : 10.3386/t0169

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.9389

A. K. Diongue, D. Guegan, and B. Vignal, Forecasting electricity spot market prices with a k-factor GIGARCH process, Applied Energy, vol.86, issue.4, pp.505-510, 2009.
DOI : 10.1016/j.apenergy.2008.07.005

URL : https://hal.archives-ouvertes.fr/halshs-00188264

R. Engle, Dynamic Conditional Correlation, Journal of Business & Economic Statistics, vol.20, issue.3, pp.339-350, 2002.
DOI : 10.1198/073500102288618487

N. C. Figueiredoa, P. P. Da-silva, C. , and P. A. , Evaluating the market splitting determinants: evidence from the Iberian spot electricity prices, Energy Policy, vol.85, pp.218-234, 2015.
DOI : 10.1016/j.enpol.2015.06.013

F. R. Førsund, B. Singh, T. Jensen, and C. Larsen, Phasing in wind-power in Norway: Network congestion and crowding-out of hydropower, Energy Policy, vol.36, issue.9, pp.3514-3520, 2008.
DOI : 10.1016/j.enpol.2008.06.005

C. Gao, E. Bompard, R. Napoli, and J. Zhou, Design of the electricity market monitoring system, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, pp.99-106, 2008.
DOI : 10.1109/DRPT.2008.4523386

R. C. Garcia, J. Contreras, M. Van-akkeren, and J. B. Garcia, A GARCH Forecasting Model to Predict Day-Ahead Electricity Prices, IEEE Transactions on Power Systems, vol.20, issue.2, pp.867-874, 2005.
DOI : 10.1109/TPWRS.2005.846044

L. Gelabert, X. Labandeira, and P. Linares, An ex-post analysis of the effect of renewables and cogeneration on Spanish electricity prices, Energy Economics, vol.33, issue.S1, pp.33-59, 2011.
DOI : 10.1016/j.eneco.2011.07.027

A. Gianfreda and L. Grossi, Zonal price analysis of the Italian wholesale electricity market, 2009 6th International Conference on the European Energy Market, 2009.
DOI : 10.1109/EEM.2009.5207198

A. Gianfreda and L. Grossi, Forecasting Italian electricity zonal prices with exogenous variables, Energy Economics, vol.34, issue.6, pp.2228-2239, 2012.
DOI : 10.1016/j.eneco.2012.06.024

URL : http://cadmus.eui.eu//bitstream/1814/25076/2/2013_Gianfreda_et-all_ForecastingItalianElectricity.pdf

A. M. Gonzalez, A. M. San-roque, and J. Garcia-gonzalez, Modeling and forecasting electricity prices with input/output hidden Markov models, IEEE Transactions on Power Systems, vol.20, issue.1, pp.13-24, 2005.

C. W. Granger and P. Newbold, Spurious regressions in econometrics, Journal of Econometrics, vol.2, issue.2, pp.111-120, 1974.
DOI : 10.1016/0304-4076(74)90034-7

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.353.2946

W. Greene, Econometric Analysis, 2003.

E. Guerci, S. Ivaldi, C. , and S. , Learning Agents in an Artificial Power Exchange: Tacit Collusion, Market Power and Efficiency of Two Double-auction Mechanisms, Computational Economics, vol.8, issue.3???4, pp.73-98, 2008.
DOI : 10.5547/ISSN0195-6574-EJ-Vol27-No1-2

URL : https://hal.archives-ouvertes.fr/halshs-00871014

N. Haldrup and M. Nielsen, Directional congestion and regime switching in a long memory model for electricity prices, Stud. Nonlinear Dyn. Econom, vol.10, issue.3, 2006.

S. M. Harvey and W. W. Hogan, Nodal and zonal congestion management and the exercise of market power, 2000.

G. A. Hemdan, M. Kurrat, T. Schmedes, A. Voigt, and R. Busch, Integration of superconducting cables in distribution networks with high penetration of renewable energy resources: Techno-economic analysis, International Journal of Electrical Power & Energy Systems, vol.62, 2014.
DOI : 10.1016/j.ijepes.2014.04.021

S. Heydari and A. Siddiqui, Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility, Energy Economics, vol.32, issue.3, pp.709-725, 2010.
DOI : 10.1016/j.eneco.2009.10.001

E. Hickey, D. G. Loomis, and H. Mohammadi, Forecasting hourly electricity prices using ARMAX???GARCH models: An application to MISO hubs, Energy Economics, vol.34, issue.1, pp.307-315, 2012.
DOI : 10.1016/j.eneco.2011.11.011

H. Higgs, Modelling price and volatility inter-relationships in the Australian wholesale spot electricity markets, Energy Economics, vol.31, issue.5, pp.31-748, 2009.
DOI : 10.1016/j.eneco.2009.05.003

Y. Hong and C. Hsiao, Locational marginal price forecasting in deregulated electricity markets using artificial intelligence, textitIEE Proceedings: Generation , Transmission and Distribution, pp.621-626, 2002.
DOI : 10.1049/ip-gtd:20020371

R. Huisman, C. Huurman, and R. Mahieu, Hourly electricity prices in day-ahead markets, Energy Economics, vol.29, issue.2, pp.240-248, 2007.
DOI : 10.1016/j.eneco.2006.08.005

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.483.6766

K. Ignatieva and S. Trück, Modeling spot price dependence in Australian electricity markets with applications to risk management, Computers & Operations Research, vol.66, pp.415-433, 2016.
DOI : 10.1016/j.cor.2015.07.019

T. Jónsson, P. Pinson, and H. Madsen, On the market impact of wind energy forecasts, Energy Economics, vol.32, issue.2, pp.313-320, 2010.
DOI : 10.1016/j.eneco.2009.10.018

J. C. Ketterer, The impact of wind power generation on the electricity price in Germany, Energy Economics, vol.44, pp.270-280, 2014.
DOI : 10.1016/j.eneco.2014.04.003

C. R. Knittel and M. R. Roberts, An empirical examination of restructured electricity prices, Energy Economics, vol.27, issue.5, pp.791-817, 2005.
DOI : 10.1016/j.eneco.2004.11.005

F. Kunz, Improving Congestion Management: How to Facilitate the Integration of Renewable Generation in Germany, The Energy Journal, vol.34, issue.4, 2013.
DOI : 10.5547/01956574.34.4.4

D. Lien and Y. K. Tse, Evaluating the hedging performance of the constant-correlation GARCH model, Applied Financial Economics, vol.59, issue.11, pp.791-798, 2002.
DOI : 10.1016/S0304-4076(99)00080-9

H. Liu and J. Shi, Applying ARMA???GARCH approaches to forecasting short-term electricity prices, Energy Economics, vol.37, pp.152-166, 2013.
DOI : 10.1016/j.eneco.2013.02.006

J. J. Lucia and E. S. Schwartz, Electricity prices and power derivatives. -evidence from the nordic power exchange, Review of Derivatives Research, vol.5, issue.1, pp.5-50, 2000.
DOI : 10.1023/A:1013846631785

I. Milstein and A. Tishler, Intermittently renewable energy, optimal capacity mix and prices in a deregulated electricity market, Energy Policy, vol.39, issue.7, pp.3922-3927, 2011.
DOI : 10.1016/j.enpol.2010.11.008

S. Ck and R. Weron, Point and interval forecasting of spot electricity prices: Linear vs. non-linear time series models, Studies in Nonlinear Dynamics and Econometrics, vol.10, issue.3 2, 2006.

F. J. Nogales, J. Contreras, A. J. Conejo, and R. Espinola, Forecasting next-day electricity prices by time series models, IEEE Transactions on Power Systems, vol.17, issue.2, pp.342-348, 2002.
DOI : 10.1109/TPWRS.2002.1007902

O. Mahoney, A. Denny, and E. , The merit-order effect of wind generation in the Irish electricity market, Proceedings of the 30th USAEE/IAEEE North American Conference, 2011.

H. Park, J. Mjelde, and D. Bessler, Price dynamics among U.S. markets, Energy Economics, vol.28, issue.1, 2006.

A. Petrella and S. Sapio, No PUN Intended: A time series analysis of Italian Day-Ahead electricity price, EUI Working papers, 2006.

E. Raviv, K. E. Bouwman, and D. Van-dijk, Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices, Tinbergen Institute Discussion Paper, pp.2013-068, 2013.
DOI : 10.2139/ssrn.2266312

URL : https://www.econstor.eu/bitstream/10419/87547/1/13-068.pdf

A. Sapio, The effects of renewables in space and time: A regime switching model of the Italian power price, Energy Policy, vol.85, pp.487-499, 2015.
DOI : 10.1016/j.enpol.2015.07.025

G. Schwartz, Estimating the Dimension of a Model, The Annals of Statistics, vol.6, issue.2, pp.461-464, 1978.
DOI : 10.1214/aos/1176344136

A. Schröeder, P. Y. Oei, A. Sander, L. Hankel, and L. C. Laurisch, The integration of renewable energies into the German transmission grid???A scenario comparison, Energy Policy, vol.61, pp.140-150, 2013.
DOI : 10.1016/j.enpol.2013.06.006

. Schwert, Tests for Unit Roots, Journal of Business & Economic Statistics, vol.20, issue.1, 1989.
DOI : 10.1198/073500102753410354

F. Serinaldi, Distributional modeling and short-term forecasting of electricity prices by Generalized Additive Models for Location, Scale and Shape, Energy Economics, vol.33, issue.6, pp.1216-1226, 2011.
DOI : 10.1016/j.eneco.2011.05.001

R. H. Shumway and D. S. Stoffer, Time series analysis and its applications, 2011.

Y. K. Tse and A. K. Tsui, A Multivariate Generalized Autoregressive Conditional Heteroscedasticity Model With Time-Varying Correlations, Journal of Business & Economic Statistics, vol.20, issue.3, pp.351-362, 2002.
DOI : 10.1198/073500102288618496

I. Vahviläinen and T. Pyykkönen, Stochastic factor model for electricity spot price???the case of the Nordic market, Energy Economics, vol.27, issue.2, pp.351-367, 2005.
DOI : 10.1016/j.eneco.2005.01.002

R. Weron and A. Misiorek, Forecasting spot electricity prices with time series models, IEEE Conference Proceedings-EEM05, pp.133-141, 2005.

R. Weron and A. Misiorek, Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models, International Journal of Forecasting, vol.24, issue.4, pp.744-763, 2008.
DOI : 10.1016/j.ijforecast.2008.08.004

R. Weron, Electricity price forecasting: A review of the state-of-the-art with a look into the future, International Journal of Forecasting, vol.30, issue.4, pp.1030-1081, 2014.
DOI : 10.1016/j.ijforecast.2014.08.008

C. K. Woo, J. Zarnikau, J. Moore, and I. Horowitz, Wind generation and zonal-market price divergence: Evidence from Texas, Energy Policy, vol.39, issue.7, pp.39-3928, 2011.
DOI : 10.1016/j.enpol.2010.11.046

A. C. Worthington, A. Kay-spratley, and H. Higgs, Transmission of prices and price volatility in Australian electricity spot markets: a multivariate GARCH analysis, Energy Economics, vol.27, issue.2, pp.337-350, 2005.
DOI : 10.1016/j.eneco.2003.11.002

K. Wurzburg, X. Labandeira, and P. Linares, Renewable generation and electricity prices: Taking stock and new evidence for Germany and Austria, Energy Economics, vol.40, issue.1, pp.159-171, 2013.
DOI : 10.1016/j.eneco.2013.09.011

J. H. Zhao, Z. Y. Dong, Z. Xu, and K. P. Wong, A Statistical Approach for Interval Forecasting of the Electricity Price, IEEE Transactions on Power Systems, vol.23, issue.2, pp.267-276, 2008.
DOI : 10.1109/TPWRS.2008.919309