Le informazioni meteoclimatiche. energetico. Matteo De Felice ENEA, Climate Modeling Laboratory

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1 Le informazioni meteoclimatiche nel settore energetico Matteo De Felice ENEA, Climate Modeling Laboratory

2 Clima o meteo? Meteo: la temperatura media a Padova l 8 Ottobre 2011 era di 11 C Clima: la temperatura media in Ottobre a Padova è di 20 C (calcolo ) E le previsioni?

3 Previsioni meteo e previsioni climatiche Previsioni short-range Previsioni stagionali L M M G JJA JAS ASO OND Previsioni decadali meteo previsioni climatiche Proiezioni multi-decadali (climate change)

4 Informazioni o dati climatici? I dati climatici a disposizione sono molti e continuano a crescere (ad es. maggiore risoluzione) Ma i dati possono divenire informazioni utili?

5 Servizi climatici Global Framework on Climate Services (GFCS), WMO 2009 Produzione e traduzione delle informazioni climatiche per contesti specifici In Europa? Progetti (FP7 CLIM-RUN, EUPORIAS, SPECS), iniziative comunitarie (COPERNICUS), iniziative e mercati nazionali

6 Copernicus Iniziativa coordinata e gestita dalla Commissione Europea Sistemi di monitoraggio e uso dei dati per servizi e applicazioni

7 Clima & Energia Supply Market Demand Renewable Energies Thermal Power

8 Energy Sector Vulnerability E.g. During European 2003 heat-wave France reduced electricity export in August of 50% (EDF) [ ] a summer average decrease in capacity of power plants of % in Europe and % in the United States depending on cooling system type and climate scenario for In addition, probabilities of extreme (>90%) reductions in thermoelectric power production will on average increase by a factor of three. (van Vliet et al., Vulnerability of US and European electricity supply to climate change, Nature Climate Change 2(9), 2012)

9 Un esempio di servizio - Collaborazione tra ENEA e TERNA dal Obiettivi specifici - con processi iterativi: nuove risponde hanno sempre portato a nuove domande - Due argomenti: energie rinnovabili e fabbisogno elettrico

10 Electricity Demand Electricity demand sensitive to weather conditions Currently only climatological data are used for time-scales >14 days Demand affected by human activities (calendar effects) and economic trends

11 Electricity Demand Electricity Demand and how it is affected by temperature and its predictability at short-time scales M. De Felice, A. Alessandri, and P. M. Ruti, Electricity Demand Forecasting over Italy: Potential Benefits using Numerical Weather Prediction models, Electric Power Systems Research, vol. 104, pp , 2013.

12 What has happened? A question

13 Observe

14 Electricity Demand

15 E nei prossimi mesi?

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17 Going seasonal What will be the probability of having the demand above/below the normal? Use of statistical downscaling of seasonal forecasts Interesting result: significant skill on some Italian regions with one-month of lead time De Felice M., Alessandri A., and F. Catalano, Seasonal climate forecasts for medium-term electricity demand forecasting, Applied Energy, vol. 137, pp , 2015

18 A possible approach Find the relationship between seasonal forecast patterns and observed demand Principal Component Analysis (PCA)

19 Seasonal Forecast VAR1 MEM1 PC1 VAR1 MEM1 PC2 ML Method VAR1 MEM1 PC3 Target (predictand) VAR_X MEM_Y PC_Z

20 A possible product

21 Next steps Extending to Europe (ENTSO-E)

22 Electricity Exchange European electricity flows for Jan-Feb (left) and June-July (right) red nodes are the main exporters and blue the main importers Data from ENTSO-E ( )

23 Flows

24 Supply: solar power Photovoltaics: estimate & predict How much are we producing now? How much we will produce tomorrow? How much we will produce next summer? M. De Felice, M. Petitta, and P. M. Ruti, Short-term predictability of photovoltaic production over Italy, Renewable Energy, vol. 80, pp , 2015.

25 E nei prossimi mesi? Work in progress Analisi dei dataset e dei forecast disponibili

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