INTELLIGENT LOAD CONTROL SYSTEM FOR 10 \ 0.4 KV TRANSFORMERS USING SCADA

Andriy Vidmysh, Oleksii Tokarchuk, Michael Karpiychuk, Maksym Paladii
2020 ENGINEERING, ENERGY, TRANSPORT AIC  
The article proposes a system of control of load of the power transformer on the basis of monitoring of the basic operating parameters of the distributive power transformer. Overloads, voltage fluctuations and heating create conditions for potential damage to transformers, which takes a long time to maintain and costly. The system is designed to provide basic information on DPT status. The system uses this data to optimize DPT performance and avoid possible emergencies. The monitoring system
more » ... vides a simple enough toolkit to overcome abnormal operating modes - from minor deviations to the most catastrophic failures. Load monitoring is carried out by the use of sensory devices in the power supply system. Methods of finding and equipment of monitoring points are proposed. SCADA data - load levels, temperature levels and voltages - are fed through a series of digital communication channels to the master controller for immediate action. A practical scheme has been developed that tracks and collects basic parameters such as winding current, oil level and DPT temperature. A topology has been developed, taking into account the expected loads to provide uninterrupted power to consumers. To ensure constant power supply to consumers, power transformers with a multi-winding configuration are used. Therefore, during the surges of consumer loads, constant supply is ensured without damaging the transformers. The distribution system is also open for diagnostic control. The scheme of the microcontroller interacting with a circle of the communication device is offered. Load monitoring is also a particular concern, as consuming excess power is an economic burden. Load imbalances, misuse of electricity, overloads or short circuits, harmonic problems, voltage profiles, power factor and minor problems can all be detected by this system.
doi:10.37128/2520-6168-2020-1-17 fatcat:paqofw4scbdtzcwuposw35b5zm