Nowadays, the changes of economic, environment, and regulations are forcing the electric utilities to operate systems at maximum capacity. Therefore, the operation and control of power system to improve the system stability has been receiving a great deal of attention. This paper presents an approach for enhancing the static voltage stability margin and reducing the power losses of the system with voltage security-constrained optimal power flow (VSC-OPF) that is based on static line voltage stability indices. The control approaches incorporate the voltage stability criteria into the conventional OPF. The minimization of the summation of fast voltage stability index (FVSI), line stability index (Lmn), and line voltage stability index (LVSI) is used as the objective functions. The performance and effectiveness of the proposed control approaches are evaluated on the standard IEEE 30-bus, 57-bus, and 118-bus test systems under normal and contingency conditions. The comparison analysis is carried out with different cases including minimization of generation cost. The proposed control approaches indicate the promising results and offer efficient countermeasures against the voltage instability of the system.

Voltage stability is very important, as without it voltage collapse will occur. There is therefore a need to incorporate the consideration of voltage stability into the optimal power flow (OPF). This paper presents a comparison of the effectiveness of five voltage stability indices (VSIs) when incorporated in an OPF. The improved particle swarm optimization (IPSO) algorithm is used to solve the OPF problem. The five VSIs investigated are the L-index, fast voltage stability index (FVSI), line stability index (L mn ), online voltage stability index (LVSI), and voltage collapse proximity indicator (VCPI). The effectiveness of each VSI is considered in the terms of the generation cost, emission, transmission loss, and voltage stability. The IEEE standard 14-, 30-, 57-, and 118-bus test systems are used for the comparison. It is found that considering each voltage stability index as part of the objective function for the OPF provided different values of generation cost, emission, transmission loss, and maximum loadability. The results suggest that FVSI and L mn provide the minimum generation cost values for all test systems, while VCPI and LVSI provide lower emission values for most systems. VCPI gives the lowest transmission losses for all systems, and the L-index provides the maximum loadability for most systems. Incorporation of these indices into the OPF can provide the optimal values in different terms, and the most suitable voltage stability index will depend on the situation and size of the system, which needs to be judiciously chosen.

One of the challenges in academic counselling is to provide an automated service system for students. There several query questions asking the faculty staffs about related-academic services each semester. Offered the communication interface more convenience, the novel approach based on neural network model is introduced to investigate the automated conversational agent. The pre-defined dialogue sentences were collected manually from the student query questions and used as the training dataset. The questions have been varied and grouped by topic-categorizing queried from the registration help desk of the department. Artificial intelligence and machine learning have contributed each other to build the conversational agent so-call KUSE-ChatBOT plugged and used in the modern messenger application, LINE. The system is also included the dialogue backend management system to use in further deep learning model updating. Tensorflow, the machine learning development platform originated by Google, was performed and obtained the learning model using Python development kits. The LINE Messaging APIs is then contributed as the user interface where users could have FAQs' conversation via the LINE application. The KUSE-ChatBOT is outperformed and efficient by providing automated consultation to the students precisely with the accuracy rate over 75 percent. The system could assist the staffs to be able to lessen the workload of answering the same question repeatedly and give response to the student timely.

Indigo blue was discovered as a semiconductor material because of its organic semiconductor properties. This paper shows a primary study of the electrochemical properties of Sakon Nakhon-indigo strain used in the metal–semiconductor–metal (MSM) diode. The fermentation and extraction of our local indigo plant are explained. Indian indigo in the MSM diode is compared in the same conditions of preparation. The electrochemical properties, including the current–voltage (I–V) characteristic, static resistance, and rectification ratio, are discussed. The results show that the electron and hole characteristics and band gap energy of the indigo blue affects the electrochemical properties of the device. Our local MSM diode has a suitable operation between −1 and +3 VMSM with a knee voltage of 1.0 VMSM. Especially, it can produce the highest forward-bias current of about 3.19 mA at linear operation between +2 and +3 VMSM, whereas the review MSM diode is about 2–3 hundred times lower. This shows that this strain has more conductive properties because of its effective electron and hole characteristics obtained by an indigo yield concentration. Therefore, the MSM diode based on Sakon Nakhon-indigo strain is an important role in an electronic semiconductor device for low voltage consumption and high sensitivity. In the future, the molecular characteristics of local indigo may be deeply analyzed to be further developed into a thin-film form used as an organic semiconductor material in several electronic devices.