A Motif-based Classification Algorithm for Identifying Solar Panel Installations

With increasing energy requirements and limitation of non-renewable resources for traditional electricity generation and transmission, many households and premises across the world have installed solar systems. Power companies require information about solar panel installations to regulate the whole power system. In this paper, we propose a motif-based classification algorithm for identifying whether a customer has installed the solar panels. Firstly, we symbolize our time-series data with alphabets and classify those data. Then we evaluate our method by checking error rates of different settings. Later, we test our algorithm with different training and testing datasets. The motif-based classification algorithm analyzes electricity consumption data of households. Results show that our motif-based classification algorithm for identifying solar panel installations have a very good accuracy.

• Publication year

  2020

• Venue

  International Conference on Industrial Technology

• Publication date

  2020-02-01

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1109/ICIT45562.2020.9067159
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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