@article{Srisontisuk2021,

title = {On Determining Critical System Ramp Capability Requirement in High PV Penetration Network Using Graphical Method},

author = {S Srisontisuk and N Hoonchareon},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099853210&doi=10.1002%2ftee.23308&partnerID=40&md5=3847464422b738aa0cf5bde4e68b913d},

doi = {10.1002/tee.23308},

issn = {19314973},

year  = {2021},

date = {2021-01-01},

journal = {IEEJ Transactions on Electrical and Electronic Engineering},

volume = {16},

number = {3},

pages = {383-391},

publisher = {John Wiley and Sons Inc},

abstract = {Increasing effort of solar power integration to the grid could be accelerated towards sustainability goal. However, high PV penetration ratio (PVR) in turn critically reduces system frequency response performance of an existing power system due to reduction of on-line rotating generators. Besides intrinsic system inertia, system RC plays a vital role in dynamically securing the power system operation subject to large PV disturbances. This study proposes a graphical method to determine critical values of system RC requirement with respect to the anticipated PVR and PV ramp-down rate of disturbance; both of which should be forecastable, in practice, in each operating time interval. Impact of PVR on dynamic performance of a power system, through the effective time-varying of system inertia and governor response characteristic has been examined. The results of the analyses on graphical display will be useful for system operators to prepare enough system RC, economically well in-advance through Unit Commitment program, to ensure system dynamic security, complying with the N-1 contingency constraint. In addition, the proposed graphical display can reveal whether the curtailment of aggregated PV's output generation is necessary for that time interval. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.},

note = {cited By 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Srikranjanapert2021,

title = {How an integration of home energy management and battery system affects the economic benefits of residential pv system owners in Thailand},

author = {M Srikranjanapert and S Junlakarn and N Hoonchareon},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102493531&doi=10.3390%2fsu13052681&partnerID=40&md5=5e154c32ae066ce724d58e785a1f1072},

doi = {10.3390/su13052681},

issn = {20711050},

year  = {2021},

date = {2021-01-01},

journal = {Sustainability (Switzerland)},

volume = {13},

number = {5},

pages = {1-20},

publisher = {MDPI AG},

abstract = {Although home energy management systems (HEMS) and batteries are part of the Thailand Smart Grid Master Plan, the financial feasibility and attractiveness of installing residential solar rooftop photovoltaic (PV) systems with integration of the HEMS and battery have never been in-vestigated. This study develops three scenarios comprising of an installation of only solar PV sys-tem, solar PV system with the HEMS, and solar PV system with integration of the HEMS and battery under the current net billing solar program for households and analyzes their financial feasibility and attractiveness by using economic measures. In addition, sensitivity analysis is performed to analyze the impacts of critical parameters on the feasibility of these three scenarios. Findings indicate that the installation of a solar rooftop system with the HEMS provides the highest customer economics. Although the implementation of HEMs leads to an increase in energy exports, benefits from bill savings of lower electricity consumption by using the HEM are relatively high compared to the loss from energy exports. Therefore, in the short term, the government should promote the integration of HEMS with a PV system; however, the installation of a PV system with HEMS and battery in the residential sector should be promoted when battery cost decreases. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.},

note = {cited By 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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}

}

@article{Abdullah2018,

title = {Fault identification usingcombined adaptive neuro-fuzzy inference system and Gustafson-Kessel algorithm},

author = {A Abdullah and C Banmongkol and N Hoonchareon and K Hidaka},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074912603&partnerID=40&md5=d249ac0cb81434e9bc76d0b8f4dea265},

issn = {23071885},

year  = {2018},

date = {2018-01-01},

journal = {Journal of Engineering Research (Kuwait)},

volume = {6},

number = {1},

publisher = {University of Kuwait},

abstract = {Issueson detecting the occurrence of a fault, justifying the type, and estimating the exact location of the faultshould be resolved to eliminate faults promptly and restore power supply with minimum interruption. Conventional approaches have contributed toassisting power utility in overcomingthese issues. However, these approaches rely on line parameters and involve a few complex mathematical equations. In this paper, a new method for fault identification pertinent to classification and location is proposed by utilizing the combined adaptive neuro-fuzzy inference system (ANFIS) and Gustafson-Kessel (GK) clustering algorithm. The effectiveness and practicability of this method aredemonstrated by the simulation results. This method uses the GK fuzzy clustering algorithm to decide on the premise configuration and its parameter and identifies itssucceeding parameter usingthe orthogonal least square. The proposed method is independent of the line parameter information and obtains high accuracy on estimation of fault locations. © 2018 University of Kuwait. All rights reserved.},

note = {cited By 1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Abdullah2017,

title = {A study on the gustafson-kessel clustering algorithm in power system fault identification},

author = {A Abdullah and C Banmongkol and N Hoonchareon and K Hidaka},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027586677&doi=10.5370%2fJEET.2017.12.5.1798&partnerID=40&md5=7692e6f9d32c5878c2d43fe976dc90e5},

doi = {10.5370/JEET.2017.12.5.1798},

issn = {19750102},

year  = {2017},

date = {2017-01-01},

journal = {Journal of Electrical Engineering and Technology},

volume = {12},

number = {5},

pages = {1798-1804},

publisher = {Korean Institute of Electrical Engineers},

abstract = {This paper presents an approach of the Gustafson-Kessel (GK) clustering algorithm’s performance in fault identification on power transmission lines. The clustering algorithm is incorporated in a scheme that uses hybrid intelligent technique to combine artificial neural network and a fuzzy inference system, known as adaptive neuro-fuzzy inference system (ANFIS). The scheme is used to identify the type of fault that occurs on a power transmission line, either single line to ground, double line, double line to ground or three phase. The scheme is also capable an analyzing the fault location without information on line parameters. The range of error estimation is within 0.10 to 0.85 relative to five values of fault resistances. This paper also presents the performance of the GK clustering algorithm compared to fuzzy clustering means (FCM), which is particularly implemented in structuring a data. Results show that the GK algorithm may be implemented in fault identification on power system transmission and performs better than FCM. © The Korean Institute of Electrical Engineers.},

note = {cited By 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Abdullah2017a,

title = {Implementation of adaptive neuro-fuzzy inference system in fault location estimation},

author = {A Abdullah and C Banmongkol and N Hoonchareon and K Hidaka},

editor = {Teoh Mustaffa S S M T Ibrahim H. Iqbal S.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992754538&doi=10.1007%2f978-981-10-1721-6_80&partnerID=40&md5=2296ffc86e63869ddb0884cb96c1fa36},

doi = {10.1007/978-981-10-1721-6_80},

issn = {18761100},

year  = {2017},

date = {2017-01-01},

journal = {Lecture Notes in Electrical Engineering},

volume = {398},

pages = {737-748},

publisher = {Springer Verlag},

abstract = {This paper proposed a new scheme using hybrid intelligent technique that combines artificial neural network and fuzzy inference system. This technique, known as Adaptive Neuro-Fuzzy Inference System (ANFIS) has associated with the advantage of wavelet transform as a pattern recognition method. The algorithm used to identify the type of fault either single line to ground, double line, double line to ground or three phase occur on a power transmission line. Other than that, this scheme is capable to analyze the fault location without the knowledge of line parameters. A power clustering algorithm called Gustafson Kessel is implemented for better performance. Alternative Transient Program/Electromagnetic Transient Program (ATP/EMTP) is used for simulation purposes and Matlab for further analysis. Outcomes indicated that the scheme is efficient and has a high percentage of accuracy. © Springer Science+Business Media Singapore 2017.},

note = {cited By 0; Conference of 9th International Conference on Robotic, Vision, Signal Processing and Power Applications, RoViSP 2016 ; Conference Date: 2 February 2016 Through 3 February 2016; Conference Code:184869},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jakpattanajit2016,

title = {Enhancing small-signal and transient stability performances in power systems with integrated energy function and functional sensitivity},

author = {C Jakpattanajit and A Yokoyama and N Hoonchareon},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84955652672&doi=10.1002%2ftee.22183&partnerID=40&md5=68bba24521bd22ce33a7f78b824b430e},

doi = {10.1002/tee.22183},

issn = {19314973},

year  = {2016},

date = {2016-01-01},

journal = {IEEJ Transactions on Electrical and Electronic Engineering},

volume = {11},

number = {1},

pages = {15-22},

publisher = {John Wiley and Sons Inc.},

abstract = {Small-signal and transient stability of a power system can be improved by installing power system stabilizers (PSSs) inside the excitation controls of the generators. Nonetheless, designing and tuning the PSSs' parameters to suit all operating conditions is a complex and difficult task. Therefore, a new control scheme integrating the principles of the energy function and the functional sensitivity is proposed in this paper. The performance of this control scheme in terms of critical clearing time, simulated dynamic responses, and power oscillation damping was examined using the IEEJ West 10- machine test system. Test results reveal that the proposed scheme can improve both small-signal and transient stability performances under various operating conditions and contingencies. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.},

note = {cited By 1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Threevithayanon2013,

title = {Accurate one-terminal fault location algorithm based on the principle of short-circuit calculation},

author = {W Threevithayanon and N Hoonchareon},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871840824&doi=10.1002%2ftee.21787&partnerID=40&md5=0b354293c83b45508515ff08ec332831},

doi = {10.1002/tee.21787},

issn = {19314973},

year  = {2013},

date = {2013-01-01},

journal = {IEEJ Transactions on Electrical and Electronic Engineering},

volume = {8},

number = {1},

pages = {28-32},

publisher = {John Wiley and Sons Inc.},

abstract = {An alternative method to find the line fault distance in a transmission network employing only one-terminal measured data is presented. The proposed method applies Zbus for short-circuit calculation to find the fault location on a transmission line without the necessity to know the fault type a priori. The well-known drawback of the standard simple-reactance one-terminal algorithm, which neglects the effect of fault impedance, will be minimized by estimating the voltage drop at the fault location by employing the Zbus technique. Accuracy the proposed method is demonstrated using the short-circuit simulation of the modified IEEE-14 bus test system on MATLAB/Simulink and the Simpower Toolbox. Compared to the accuracy obtained from the standard one-terminal algorithm, test results confirm substantially improved accuracy of the proposed method in all cases of the four types of fault categories: single line-to-ground fault; double line-to-ground fault; line-to-line fault; and balance three-phase fault. While the accuracy has been significantly improved, especially for the case with a relatively high fault impedance, also the simplicity in the involved computation is well preserved when compared to other iterative-based techniques. © 2012 Institute of Electrical Engineers of Japan.},

note = {cited By 5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ChangChien2003,

title = {Estimation of β for adaptive frequency bias setting in load frequency control},

author = {L -R Chang-Chien and N -B Hoonchareon and C -M Ong and R A Kramer},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0038180640&doi=10.1109%2fTPWRS.2003.810996&partnerID=40&md5=1131f9caabee44bf593929f29829cd7b},

doi = {10.1109/TPWRS.2003.810996},

issn = {08858950},

year  = {2003},

date = {2003-01-01},

journal = {IEEE Transactions on Power Systems},

volume = {18},

number = {2},

pages = {904-911},

abstract = {Utilities in the U.S. use tie-line bias control to share generation and frequency support in the interconnection. To ensure that the reliability and the responsibility of frequency support are maintained, NERC guidelines specify that the frequency bias coefficient - 10 B that a control area uses in its tie-line control be set as close as practical to the area's frequency response characteristic β. This paper presents an algorithm to estimate β online using variables commonly available from existing AGC system. Results showing the algorithm's performance in simulated conditions and on actual field data are presented. Issues related to using the estimated β in an adaptive frequency bias-setting control are examined.},

note = {cited By 35},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hoonchareon2002,

title = {Implementation of an ACĒ 1 decomposition method},

author = {N -B Hoonchareon and C -M Ong and R A Kramer},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036699882&doi=10.1109%2fTPWRS.2002.801035&partnerID=40&md5=1204f63a6bd501db37deb1803d83c188},

doi = {10.1109/TPWRS.2002.801035},

issn = {08858950},

year  = {2002},

date = {2002-01-01},

journal = {IEEE Transactions on Power Systems},

volume = {17},

number = {3},

pages = {757-761},

abstract = {Having established feasibility and developed a method to decompose control area's ACĒ 1 into components attributable to load changes in subareas within the control area, this paper addresses some of the practical issues with an on-line implementation of the ACĒ 1 model and the decomposition method. Issues examined here include time-varying system conditions, nonlinearities in the governors' dead bands and AGC loop, and the impact of load disturbance external to the control area. An on-line recursive parameter estimation technique with adjustable forgetting factor to update the ACĒ 1 model parameters is proposed.},

note = {cited By 12},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Hoonchareon2002a,

title = {Feasibility of decomposing ACĒ 1 to identify the impact of selected loads on CPS1 and CPS2},

author = {N -B Hoonchareon and C -M Ong and R A Kramer},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036699881&doi=10.1109%2fTPWRS.2002.801034&partnerID=40&md5=a3e62c22416799675109ff731dfb8a0e},

doi = {10.1109/TPWRS.2002.801034},

issn = {08858950},

year  = {2002},

date = {2002-01-01},

journal = {IEEE Transactions on Power Systems},

volume = {17},

number = {3},

pages = {752-756},

abstract = {Control areas are held to the NERC's control performance standards (CPS), CPS1 and CPS2. A control area serving rapid and widely varying loads would like to know how load variations in certain subareas or zones affect its area's CPS1 and CPS2 measures. This paper addresses the question of decomposability of the 1-min average value of area control error (ACE) ACĒ 1, the primary variable in the computation of CPS1 and CPS2, into components attributable to load fluctuations within defined zones. It includes description of dynamic models of ACE and ACĒ 1, and simulated results confirming the decomposability of ACĒ 1.},

note = {cited By 17},

keywords = {},

pubstate = {published},

tppubtype = {article}

}