• A Machine Learning Approach for NILM based on Odd Harmonic Current Vectors 

      Loukas E.P., Bodurri K., Evangelopoulos P., Bouhouras A.S., Poulakis N., Christoforidis G.C., Panapakidis I., Chatzisavvas K.C. (2019)
      This paper examines the application of machine learning techniques in NILM methodologies based on the first three odd harmonic order current vectors as the only attributes of the appliances. Proper formulation of the ...
    • Utilizing Harmonics in Sequential and Parallel Disaggregation Schemes 

      Skalidi I., Kothona D., Bouhouras A.S., Tsiggenopoulos D., Poulakis N., Vandikas I., Christoforidis G.C., Panapakidis I. (2019)
      Scope of this paper is to examine the performance of two disaggregation schemes for NILM algorithms based on the utilization of current harmonic vectors. The analysis is based on measurements performed on real residential ...