A new strategy based on ANN for controlling the electronic on‐load tap changer

Abstract

Summary On‐load tap changer (OLTC) is utilized in regulating the voltage in electric systems. Recently, electronic on‐load tap changer (EOLTC) has been presented to eliminate the OLTC limitations and drawbacks. This paper presents an intelligent controller for EOLTC. The proposed controller aims to regulate the load voltage via fast and accurate adjusting the EOLTC when load voltage or power system voltage is changed. A multilayer feed forward neural network (MFFNN) controller is used in this proposal. The designing, training, and testing of the proposed intelligent controller are done in a MATLAB/Simulink environment. The performance of the EOLTC with the proposed MFFNN controller is achieved using two test distribution systems. The first one consists of a 220‐V source installed with a 50‐kW electrical load during a 220/210 V transformer and a transmission of short line. The second test system consists of an 11‐kV source connected to a (500 kW + 300 kVAR) industrial load through a 11/0.4‐kV, 800‐kVA transformer. This test system is a part of a real distribution feeder picked from North Delta Electric Distribution Company in Egypt. Several cases for the load voltage decreasing and increasing are used to verify the effectiveness of the proposed intelligent controller. The proposed controller shows fast and accurate response.

Impact and assessment of the overvoltage mitigation methods in low‐voltage distribution networks with excessive penetration of PV systems: A review

“…The ETC is effective more than MTC as the MTC has a delayed operating time to adjust the system voltage and needs a high maintenance cost. Also, the ETC can change the voltage for every cycle; hence it is a fast type for voltage measurement 26,146 . This method can coordinate with controlling strategies to improve its flexibility 146 .…”

“…Also, the ETC can change the voltage for every cycle; hence it is a fast type for voltage measurement. 26,146 This method can coordinate with controlling strategies to improve its flexibility. 146 While strategy's disadvantages are frequent switching of OLTC leads to generate arc, 146 and it depends on collecting data from the specified feeders.…”

“…26,146 This method can coordinate with controlling strategies to improve its flexibility. 146 While strategy's disadvantages are frequent switching of OLTC leads to generate arc, 146 and it depends on collecting data from the specified feeders. Hence, information and communication technology (ICT) was needed; therefore, costs are high.…”

Review on voltage‐violation mitigation techniques of distribution networks with distributed rooftop PV systems

“…Examples of conventional control are line drop compensation [26], source drop compensation, and pre‐emptive tap changer [27]. The conventional control methods are not efficient for mitigating voltage rise, which is caused by DG in the distribution network [28]. The alternative control method is an intelligent control such as artificial neural network [28], fuzzy logic (FL) [29], and state estimation [30].…”

Centralized Control Method for Voltage Coordination Challenges With OLTC and D-STATCOM in Smart Distribution Networks Based IoT Communication Protocol

“…The electronic OLTC was utilized to maintain the load voltages within the permissible limits by simulating it using the MATLAB program [16]. The artificial neural network was used to control the electronic OLTC to maintain the voltage magnitudes at the load buses [17]. The OLTC and demand response (DR) were integrated to control the voltage in the unbalance DNs [18].…”