George Sideratos

Senior Researcher
+30 210 772 2875


The research interests of Dr. Sideratos focuses on two areas. The first area is related to optimal management of distributed production and renewable energies and the second area includes machine learning and artificial intelligence. Regarging the first area, Mr Sideratos has helped to create energy management tools under uncertainty. In particular, he developed models of short-term load demand forecasting for the Greek interconnected system, but also for autonomous power systems. he has developed forecasting models for solar and wind production as well as forecasting models for the HV or MV substation load with large RES penetration and for the secure operation of a power system. Tools also developed that improved the RES forecasting in extreme events when large changes in power penetration occurred. In addition, he has contributed to the development of tools for stochastic unit commitment and the probabilistic power flow in power systems with high RES penetration.



  • G. Sideratos, A. Ikonomopoulos, and N. Hatziargyriou, 'A committee of machine learning techniques for load forecasting in a smart grid environment', International Journal of Energy and Power, vol. 4, pp 98-105, 2015
  • G. Sideratos, N. Hatziargyriou, ‘Probabilistic wind power forecasting using radial basis neural networks’, , IEEE Transaction on Power Systems, Vol 27 , Issue 4, pp 1788 - 1796, Nov. 2012
  • G. Sideratos, N. Hatziargyriou, 'Wind power forecasting focused on extreme power system events', IEEE Transactions on Sustainable Energy, Vol. 3, Issue. 3 pp. 445 – 454, 2012
  • A. Togelou, G. N. Sideratos and Hatziargyriou, ‘Wind Power forecasting in the absence of historical data’, IEEE Transactions on Sustainable Energy, Vol. 3, Issue 3, pp 416 - 421, 2012
  • G. N. Sideratos and Hatziargyriou, ‘An Advanced Radial Base Structure for Wind Power Forecasting’, International journal on Power and Energy Systems, ACTA Press, Vol. 12, 2008
  • G. Sideratos, N. Hatziargyriou, ‘An Advanced Statistical Method for Wind Power Forecasting’, IEEE Transaction on Power Systems, Vol. 22, Issue 1, pp. 258-265, 2007.


  • T. Boutsika, G. Sideratos, A. Ikonomopoulos, 'An Expert Committee Evaluation for Load Forecasting in a Smart Grid Environment', ENEFM2015, pp 135-141, 2015
  • G. Sideratos N. Hatziargyriou, ‘Load Forecasting in an isolated system’, ISAP’11 conference, 2011, Crete
  • G. Sideratos, N.Hatziargyriou, ‘Using Radial Basis Neural Networks to Estimate Wind Power Production’, PES conference, 2008
  • G. Sideratos, N. Hatziargyriou, ‘Application of Radial Basis Function Networks for Wind Power Forecasting’, ICANN, Athens, 2006
  • G. Sideratos, N. Hatziargyriou, P. Georgilakis, 'State-of-the-art in wind power forecasting', Proc. Workshop on Operation and Control of RES, Belgrade, Serbia and Montenegro, 2005
  • X. Wang, G. Sideratos, N. Hatziargyriou, L. Tsoukalas, ‘Wind Power Forecasting for Operational Planning’, PMAPS 2004
  • Zbigniew Gontar, G. Sideratos, N. Hatziargyriou, ‘Short Term Load Forecasting with Radial Basis Function Network’, SETN Conference, pp. 432-438, Samos, Greece, 2004