Greece
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Experience & Education

  • Grafana Labs

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Projects

  • Diploma Thesis

    -

    Title: Real-Time Energy Disaggregation using Advanced Pattern Recognition Techniques

    Abstract:

    In recent years, the significant increase in the end use of electrical appliances, especially in urban societies, state the importance of controlling the overall electrical energy consumption, taking into consideration both the facilitation of financial control, and reinforcement of society's ecological profile. Up until now, small-scale consumers are informed about their consumption by…

    Title: Real-Time Energy Disaggregation using Advanced Pattern Recognition Techniques

    Abstract:

    In recent years, the significant increase in the end use of electrical appliances, especially in urban societies, state the importance of controlling the overall electrical energy consumption, taking into consideration both the facilitation of financial control, and reinforcement of society's ecological profile. Up until now, small-scale consumers are informed about their consumption by their electrical bills, making their notification partial and out of time. For this purpose, the "Real-Time Energy Data Disaggregation" term is introduced, which is associated with high energy consuming devices, namely, ovens, washing machines etc. Via this process, the consumers can be notified for their overall energy consumption, as well as the appliances' participation percentage. In the context of this thesis, a set of advanced pattern recognition techniques are used in order to achieve real-time energy data disaggregation, which is well-known as NIALM (Non-Intrusive Appliance Load Monitoring). To this end, two novel approaches are introduced (one containing a pre-training phase and one without), which are based on ANFIS (Adaptive Neuro-Fuzzy Inference System). Consequently, the experimental procedure is presented, where the results are assessed with the help of appropriate metrics. More specifically, the appliance end uses detected by the presented approaches are compared to the real data to show the appropriateness and correctness of the implemented system. These results are highlighting the ability of achieving the desired accuracy and validity, emphasizing the usefulness for the household consumer.

Languages

  • English

    Limited working proficiency

  • Greek

    Native or bilingual proficiency

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