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The uptake of solar power generation is on the rise. This necessitates more research into developing data-driven intelligent methods that can perform effective analytics over power generation data to inform strategies to improve solar power generation systems. In this paper, we consider the utility of time series representation learning for analytics over power generation data. WaRTEm, a representation learning method that focuses on learning time series representations that are invariant to local phase shifts, is the focus of our investigations in this paper. We identify two metadata attributes for power generation sequences, month and CellID, as attributes that embed useful notions of semantic similarity between time series sequences. We evaluate the effectiveness of WaRTEm representations, as against using the raw time series sequences, in alignment to the month and CellID labellings, using accuracy over 1NN retrieval as an evaluation framework. Through empirical evaluations, we identify that WaRTEm embeddings are consistently able to achieve better representations when evaluated on 1NN accuracy. We also identify some features of WaRTEm that are more suited for time series representation learning, which provides promising directions for future work.
|Number of pages||6|
|Publication status||Published - Dec 2019|
|Event||20th International Conference on Intelligent Systems Applications to Power Systems - Indian Institute of Technology Delhi (IIT Delhi), Delhi, India|
Duration: 10 Dec 2019 → 14 Dec 2019
|Conference||20th International Conference on Intelligent Systems Applications to Power Systems|
|Abbreviated title||ISAP 2019|
|Period||10/12/19 → 14/12/19|
Kiprakis, A., Ajay, C. K., Singh, S. N., Garg, D., Padmanabhan, D. & Thompson, J., 3 Jan 2019, 2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2018. Wada, T., Yadav, D., Tiwari, A. N. & Kumar, B. (eds.). Institute of Electrical and Electronics Engineers Inc., 8596979. (2018 5th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2018).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution