A Review on Automatic Bi-directional Smart Meter along with a Proposed Model of Second Layer Grid Protection System Based on Solid State Relay

2020 ◽  
Author(s):  
Suvamoy Bhattacharyya ◽  
Parnab Saha ◽  
Ushnik Chakrabarti ◽  
Anindya Nag ◽  
Sudhangshu Sarkar
Author(s):  
Atalay Barkana ◽  
Gerald Cook ◽  
Eugene S. McVey
Keyword(s):  

2003 ◽  
Vol 30 (2) ◽  
pp. 92-94
Author(s):  
H. T. Sheppard ◽  
P. D. Blankenship

Abstract Peanuts are graded at farmer marketing for value determination. The grading procedure requires kernel sizing which is facilitated with perforated screens oscillated with a mechanical vibrator. The vibrator operates for 20-sec periods and is controlled by a hand-adjustable, mechanical timer. The durability of the timer is unsatisfactory and it frequently fails during a single grading season. Subsequent maintenance and replacement costs prompted the development of two more durable timing units. Solid state timers were utilized in both units. Construction of the two units was the same except a mechanical relay was used for switching in one but a solid state relay in the other. During durability testing, a prototype timing device with a mechanical relay switched on and off 11,020 times over an 8-d period before failing. A timing device with a solid state relay switched on and off 68,621 times over a 22-d period without failing. During field testing, six timing units with mechanical relays and five timing units with solid state relays operated an estimated 6000 cycles each at peanut buying points throughout a peanut harvest season without failure.


Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2235 ◽  
Author(s):  
Zigui Jiang ◽  
Rongheng Lin ◽  
Fangchun Yang

Time-series smart meter data can record precisely electricity consumption behaviors of every consumer in the smart grid system. A better understanding of consumption behaviors and an effective consumer categorization based on the similarity of these behaviors can be helpful for flexible demand management and effective energy control. In this paper, we propose a hybrid machine learning model including both unsupervised clustering and supervised classification for categorizing consumers based on the similarity of their typical electricity consumption behaviors. Unsupervised clustering algorithm is used to extract the typical electricity consumption behaviors and perform fuzzy consumer categorization, followed by a proposed novel algorithm to identify distinct consumer categories and their consumption characteristics. Supervised classification algorithm is used to classify new consumers and evaluate the validity of the identified categories. The proposed model is applied to a real dataset of U.S. non-residential consumers collected by smart meters over one year. The results indicate that large or special institutions usually have their distinct consumption characteristics while others such as some medium and small institutions or similar building types may have the same characteristics. Moreover, the comparison results with other methods show the improved performance of the proposed model in terms of category identification and classifying accuracy.


2013 ◽  
Vol 770 ◽  
pp. 241-244 ◽  
Author(s):  
Kitipun Boonin ◽  
Suparat Tuscharoen ◽  
Jakrapong Kaewkhao

This research is intended to study and construct a two doors electrical furnace. Two line of Kanthal AF wire were used as a heat source furnace. Insulator of furnace was constructed from light brick C-2. The volume of furnace was about 25x30x45 cm3. Quantity of current flow through heating element was controlled by solid state relay. Temperature of the furnace is measured by thermocouple type K. The result of test performance of the furnace show that the temperature of 1200 °C was obtained at 220 volt and current in heating elements of 15 A.


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