Associate Professor Kulyos Audomvongseree, Ph.D.
รศ. ดร.กุลยศ อุดมวงศ์เสรี
Education
- Ph.D. Electrical Engineering, University of Tokyo, Japan, 2004
- M.Sc. Finance, Thammasat Business School (MIF Program), Thailand, 2010
- M.Eng. Electrical Engineering, Chulalongkorn University, Thailand, 2000
- B.Eng. Electrical Engineering, Chulalongkorn University, Thailand, 1998
Email: kulyos.a@chula.ac.th
Research Interest
- Energy Economics and Policy
- Power System Reliability Assessment
- Power Development Planning
- Generation and Transmission Expansion Planning
Research Cluster
Link to
1.
Pipattanasomporn, M; Chitalia, G; Songsiri, J; Aswakul, C; Pora, W; Suwankawin, S; Audomvongseree, K; Hoonchareon, N
CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets Journal Article
In: Scientific Data, vol. 7, no. 1, 2020, ISSN: 20524463, (cited By 2).
@article{Pipattanasomporn2020,
title = {CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets},
author = {M Pipattanasomporn and G Chitalia and J Songsiri and C Aswakul and W Pora and S Suwankawin and K Audomvongseree and N Hoonchareon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088245691&doi=10.1038%2fs41597-020-00582-3&partnerID=40&md5=f4429e29617970d1a17b92a27f26ec05},
doi = {10.1038/s41597-020-00582-3},
issn = {20524463},
year = {2020},
date = {2020-01-01},
journal = {Scientific Data},
volume = {7},
number = {1},
publisher = {Nature Research},
abstract = {This paper describes the release of the detailed building operation data, including electricity consumption and indoor environmental measurements, of the seven-story 11,700-m2 office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (°C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period of 18 months from July 1, 2018, to December 31, 2019. Such datasets can be used to support a wide range of applications, such as zone-level, floor-level, and building-level load forecasting, indoor thermal model development, validation of building simulation models, development of demand response algorithms by load type, anomaly detection methods, and reinforcement learning algorithms for control of multiple AC units. © 2020, The Author(s).},
note = {cited By 2},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper describes the release of the detailed building operation data, including electricity consumption and indoor environmental measurements, of the seven-story 11,700-m2 office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (°C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period of 18 months from July 1, 2018, to December 31, 2019. Such datasets can be used to support a wide range of applications, such as zone-level, floor-level, and building-level load forecasting, indoor thermal model development, validation of building simulation models, development of demand response algorithms by load type, anomaly detection methods, and reinforcement learning algorithms for control of multiple AC units. © 2020, The Author(s).
2.
Thongsawaeng, C; Audomvongseree, K
Determination of the optimal battery capacity of a grid-connected photovoltaic system with power and frequency fluctuations consideration Journal Article
In: ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 11, no. 2, pp. 28-37, 2013, ISSN: 16859545, (cited By 0).
@article{Thongsawaeng2013a,
title = {Determination of the optimal battery capacity of a grid-connected photovoltaic system with power and frequency fluctuations consideration},
author = {C Thongsawaeng and K Audomvongseree},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904820743&partnerID=40&md5=b36ed2f86df7453fc5114ead1b609f1d},
issn = {16859545},
year = {2013},
date = {2013-01-01},
journal = {ECTI Transactions on Electrical Engineering, Electronics, and Communications},
volume = {11},
number = {2},
pages = {28-37},
publisher = {ECTI Association},
abstract = {Power and frequency fluctuations are main problems of a grid-connected photovoltaic (PV) system. To effectively remedy this problem, appropriate size of battery should be installed into the PV system. In this paper, the dynamic model of the photovoltaic system and battery are discussed. The battery used in this analysis is lead-acid battery. In addition, the dependent structure of solar irradiance and ambient temperature are taken into account. The proposed algorithm begins with solar radiation-temperature model. Then, the output power of the PV system will be calculated based on the PV dynamic model. The rest of the interconnected power system is modeled as a small synchronous generator. The proposed algorithm has been tested with a 3-bus test system. Satisfactory results were obtained.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Power and frequency fluctuations are main problems of a grid-connected photovoltaic (PV) system. To effectively remedy this problem, appropriate size of battery should be installed into the PV system. In this paper, the dynamic model of the photovoltaic system and battery are discussed. The battery used in this analysis is lead-acid battery. In addition, the dependent structure of solar irradiance and ambient temperature are taken into account. The proposed algorithm begins with solar radiation-temperature model. Then, the output power of the PV system will be calculated based on the PV dynamic model. The rest of the interconnected power system is modeled as a small synchronous generator. The proposed algorithm has been tested with a 3-bus test system. Satisfactory results were obtained.
3.
Naksrisuk, C; Audomvongseree, K
Dependable capacity evaluation of wind power and solar power generation systems Journal Article
In: ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 11, no. 2, pp. 58-66, 2013, ISSN: 16859545, (cited By 1).
@article{Naksrisuk2013a,
title = {Dependable capacity evaluation of wind power and solar power generation systems},
author = {C Naksrisuk and K Audomvongseree},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904814109&partnerID=40&md5=3c28cd559f02bc8dbbbc1cf3448b9c79},
issn = {16859545},
year = {2013},
date = {2013-01-01},
journal = {ECTI Transactions on Electrical Engineering, Electronics, and Communications},
volume = {11},
number = {2},
pages = {58-66},
publisher = {ECTI Association},
abstract = {Integration of renewable energy sources, such as wind power and solar power, into the generation system can enhance country's energy security. These alternative energy help diversify sources of primary energy used to produce electricity. However, the biggest disadvantage of using these types of renewable energy power plants is that it might reduce power system reliability because these intermittent renewable energy sources have low dependable capacity. This paper aims to evaluate the dependable capacity of wind power and solar power generation systems. It considers uncertainties due to intermittent wind speed, solar irradiance, ambient temperature, and unavailability of their corresponding generators. Additionally, load uncertainty is also taken into account. The dependable capacity of the wind power and solar power generation systems are determined from the principle of generation system reliability evaluation. The reliability index such as Loss of Load Probability (LOLP) will be used as a key indicator to dene the dependable capacity.},
note = {cited By 1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Integration of renewable energy sources, such as wind power and solar power, into the generation system can enhance country's energy security. These alternative energy help diversify sources of primary energy used to produce electricity. However, the biggest disadvantage of using these types of renewable energy power plants is that it might reduce power system reliability because these intermittent renewable energy sources have low dependable capacity. This paper aims to evaluate the dependable capacity of wind power and solar power generation systems. It considers uncertainties due to intermittent wind speed, solar irradiance, ambient temperature, and unavailability of their corresponding generators. Additionally, load uncertainty is also taken into account. The dependable capacity of the wind power and solar power generation systems are determined from the principle of generation system reliability evaluation. The reliability index such as Loss of Load Probability (LOLP) will be used as a key indicator to dene the dependable capacity.