A Data-driven approach to renewable energy source planning at regional level

ABSTRACT

A correlation analysis based on Markowitz Portfolio Theory and data from meteorological station are used to develop a decision-making tool for the optimal spatial installation of renewable energy sources from Wind turbines and PV panels. A case study involving power generation plants and weather stations in the region of Tuscany in Italy is developed. The results show that temporal correlations of solar and wind generation profiles are characterized by correlation and anticorrelation. This feature is used for supporting decision-making on investments in renewable energy at the territorial level.

KEYWORDS:

• Renewable energy sources
• regional planning
• Markowitz portfolio

Acknowledgments

AS thanks CNR-PNR National Project DFM.AD004.027” Crisis-Lab” and P0000326 project AMOFI for support. AF is supported by SoBigData++ (H2020 framework grant n. 871042). Weather data have been provided by the Servizio Idrico Regionale of the Tuscany Region.

Notes

¹ Directorate-General for Energy (European Commission), Clean energy for all Europeans package, (2019) https://ec.europa.eu/energy/en/topics/energy-strategy-and-energy-union/clean-energy-all-europeans..

² According to the 2019 Ministerial Decree 4/7/2019 (the so called “RES1”).

³ Memoria per la 10a Commissione Industria, commercio, turismo, 5a Bilancio e 14° Politiche dell’Unione europea del Senato della Repubblica – Memoir of the Regulatory Authority for Energy Networks and Environment on the proposal for a National Recovery and Resilience Plan (Doc. XXVII, n. 18), available here: https://www.arera.it/it/docs/21/086-21.htm (In Italian only).

Additional information

Funding

This work was supported by the Consiglio Nazionale delle Ricerche; H2020 Research Infrastructures [871042].