ICT plays an essential role in smart grid. It brings huge amount of measured values to data centers. The data are produced from millions of meters/sensors, installed at many locations. Then the data centers convert them to useful information with big data analysis. The collected data may include produced or consumed energy/power, temperatures, wind speed, cloud images, etc. And the information can be used to plan electricity production, transmission, O&M, asset management, etc.
SGRU aims to find efficient techniques for secure data transmission. It is also interested in algorithms for renewable energy/load forecast. In this area, SGRU’s researchers have collaborations with their counterparts from Japan, the USA, Germany and China. One of SGRU’s missions is to establish a center for RE & load forecast.
Research Team
- Wanchaleam Pora
- Jitkomut Songsiri
- Naebboon Hoonchareon
- Manisa Pipattanasomporn
- David Banjerdpongchai
Equipment and Testbed
Recent publication
- Metaheuristic optimization algorithms to estimate statistical distribution parameters for characterizing wind speeds, Alrashidi, M., Rahman, S., Pipattanasomporn, M., Renewable Energy 2020.
- Robust short-term electrical load forecasting framework for commercial buildings using deep recurrent neural networks, Chitalia, G., Pipattanasomporn, M., Garg, V., Rahman, S., Applied Energy 2020.
- CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets, Pipattanasomporn, M., Chitalia, G., Songsiri, J., Aswakul, C., Pora, W., Suwankawin, S., Audomvongseree, K., Hoonchareon, N., Scientific Data 2020.
- A transactive grid with microgrids using blockchain for the energy internet, 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, Dimobi, I, Pipattanasomporn, M., ISGT 2020.
- Realizing the potential of blockchain technology in smart grid applications, Kuzlu, M., Sarp, S., Pipattanasomporn, M., Cali, U., ISGT 2020.
- Occupancy Forecasting using LSTM Neural Network and Transfer Learning, Leeraksakiat, P., Pora, W., ECTI-CON 2020.
- New Rectification Technique for Cloud Base Height Estimation Base on Stereo Cameras, Prasertseree, C., Pora, W., ECTI-CON 2020.
- Power Baseline Modeling for Split-Type Air Conditioner in Building Energy Management Systems Using Deep Learning, Chumnanvanichkul, P., Chirapongsananurak P., Hoonchareon N., APCCAS 2019.
- Three-level Classification of Air Conditioning Energy Consumption for Building Energy Management System Using Data Mining Techniques, Chumnanvanichkul, P., Chirapongsananurak P., Hoonchareon N., IEEE PES GTD Asia 2019.
- Missing-data imputation for solar irradiance forecasting in Thailand, Layanun, V., Suksamosorn, S., Songsiri, J., SICE 2017.
- A study on the gustafson-kessel clustering algorithm in power system fault identification, Abdullah, A., Banmongkol, C., Hoonchareon, N., Hidaka, K., Journal of Electrical Engineering and Technology 2017.
- Implementation of adaptive neuro-fuzzy inference system in fault location estimation, Abdullah, A., Banmongkol, C., Hoonchareon, N., Hidaka, K., Lecture Notes in Electrical Engineering 2017.
- Classification of transmission line faults with waveform characterization, Hongdilokkul, R., Banmongkol, C., ECTI-CON 2016.
- A low-cost Wi-Fi smart plug with on-off and Energy Metering functions, Thongkhao, Y., Pora, W., ECTI-CON 2016.
- A development of IEC61850 monitoring system for distribution transformer, Srisodsai, S., Pora, W., ECTI-CON 2016.
- Parameter extraction for a solar cell model with three measured points only, Tong, N.T., Pora, W., ICEIC 2016.
- A parameter extraction technique exploiting intrinsic properties of solar cells, Tong, N.T., Pora, W., Applied Energy 2016.