scholarly journals Dynamic load modeling of some low voltage devices

2009 ◽  
Vol 22 (1) ◽  
pp. 61-70 ◽  
Author(s):  
Lidija Korunovic ◽  
Dobrivoje Stojanovic
Keyword(s):  
Induction Motor ◽  
Dynamic Load ◽  
Low Voltage ◽  
Supply Voltage ◽  
Incandescent Lamp ◽  
Mercury Lamp ◽  
Load Modeling ◽  
Load Model ◽  
Fluorescent Lamps

This paper presents the results of dynamic load modeling for some frequently used low voltage devices. The modeling of long-term dynamics is performed on the basis of step changes of supply voltage of the heater, incandescent lamp, mercury lamp, fluorescent lamps, refrigerator, TV set and induction motor. Parameters of dynamic exponential load model of these load devices are identified, analyzed and mutually compared.

scholarly journals A data-driven approach for online aggregated load modeling through intelligent terminals

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982599 ◽  
Author(s):  
Yi Tang ◽  
Liangliang Zhu ◽  
Jia Ning ◽  
Qi Wang
Keyword(s):  
Power System ◽  
Induction Motor ◽  
Power Distribution ◽  
Distribution Networks ◽  
Data Driven ◽  
Load Modeling ◽  
Load Model ◽  
Power Models ◽  
Data Driven Approach ◽  
Aggregated Load

Load model has significant impact on power system simulation. Current load modeling approaches are inadequate on revealing the accuracy and time-variation of load compositions. The application of wireless sensors dispersed in power distribution networks provides further opportunities for load modeling. In this article, a data-driven online aggregated load modeling approach is proposed systematically. First, all the electricity consumers are clustered according to big data of power consumption behaviors. In each cluster, typical users are designated to stand for the characteristics of the cluster, and intrusive measurement is adapted to capture these typical users’ time-varying information by employing wireless intelligent terminals, which can identify the composition of static load and induction motor load online. Second, the load models of other users in each cluster are assumed identical to typical users, including static impedance–current–power models and induction motor models. Finally, the composite load model is achieved by hierarchical aggregation and bottom-to-up stepwise equivalence. Simulations demonstrate that the load model built by proposed approach reflects higher accuracy and adaptability in power system.

Dynamic Load Modeling Based on Extreme Learning Machine

2012 ◽  
Vol 195-196 ◽  
pp. 1043-1048
Author(s):  
Zhong Hui Liu ◽  
Zhen Shu Wang ◽  
Mei Hua Su
Keyword(s):  
Power System ◽  
Extreme Learning Machine ◽  
Dynamic Simulation ◽  
Dynamic Load ◽  
Reactive Power ◽  
Power Model ◽  
Load Modeling ◽  
Load Model ◽  
Load Characteristics ◽  
Learning Machine

The dynamic load characteristics have significant impact on the power flow, transient stability computation, voltage stability calculation of the power system, and so on. Noticing that traditional mechanism loads model has difficulty in precisely describing the dynamic characteristics of synthetic load, this paper presents a non-mechanism dynamic load model based on Extreme Learning Machine (ELM). The Power Fault Recorder and Measurement System (PFRMS) is used to obtain data for load modeling. Take voltage and real/reactive power with different time delay as inputs, and take real/reactive power as output, train the ELM using the samples formed by fault data, the real power model and reactive power model are established respectively. The number of hidden layer nodes which has impact on the ELM model is also discussed. Dynamic simulation experiment is conducted at power system dynamic simulation laboratory. The simulation result shows that the ELM load model is simple and flexible, its parameters are easy to be identified. The ELM load model can describe the dynamic load characteristics accurately.

An Investigative Study on Impact of Frequency Dynamics in Load Modeling

2020 ◽  
Vol 01 (01) ◽  
Author(s):  
Musa Mohammed ◽  
◽  
Abubakar Abdulkarim ◽  
Adamu Sa’du Abubakar ◽  
Abdullahi Bala Kunya ◽  
...  
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Low Voltage ◽  
Model Performance ◽  
System Stability ◽  
Normal System ◽  
Area Network ◽  
Load Modeling ◽  
Feed Forward Neural Network ◽  
Load Model

Load modeling plays a significant impact in assessing power system stability margin, control, and protection. Frequency in the power system is desired to be kept constant, but in a real sense, it is not constant as loads continually change with time. In much literature, frequency dynamics are ignored in the formulation of load models for the basic assumption that it does not affect the models. In this paper, the composite load model was formulated with Voltage-Frequency Dependency (V-FD) on real and reactive powers and applied to estimate the load model. 2- Area network 4- machines Kundur test network was used for testing the developed model. The model was trained with measurements from a low voltage distribution network supplying the Electrical Engineering department at Ahmadu Bello University, Zaria. Both training and testing data were captured under normal system operation (dynamics). To evaluate the V-FD model performance, Voltage-Dependent (VD) model was examined on the same measured data. The work makes use of the Feed Forward Neural Network (FFNN) as a nonlinear estimator. Results obtained indicate that including frequency dynamics in modeling active power reduces the accuracy of the model. While in modeling reactive power the model performance improves. Hence, it can be said that including frequency dynamics in load modeling depends on the intended application of the model.

Dynamic Load Model using PSO-Based Parameter Estimation

2011 ◽  
Vol 131 (7) ◽  
pp. 557-566 ◽  
Author(s):  
Hisao Taoka ◽  
Junya Matsuki ◽  
Michiya Tomoda ◽  
Yasuhiro Hayashi ◽  
Yoshio Yamagishi ◽  
...  
Keyword(s):  
Parameter Estimation ◽  
Dynamic Load ◽  
Load Model ◽  
Dynamic Load Model

Supply voltage quality in low voltage industrial networks of Estonia

2011 ◽  
Vol 18 (2) ◽  
pp. 102 ◽  
Author(s):  
T Vinnal ◽  
K Janson ◽  
J Järvik ◽  
H Kalda ◽  
T Sakkos
Keyword(s):  
Low Voltage ◽  
Supply Voltage ◽  
Industrial Networks ◽  
Voltage Quality

COMPOSITE TRANSISTOR CELL USING DYNAMIC BODY BIAS FOR HIGH GAIN AND LOW-VOLTAGE APPLICATIONS

2014 ◽  
Vol 23 (08) ◽  
pp. 1450108 ◽  
Author(s):  
VANDANA NIRANJAN ◽  
ASHWANI KUMAR ◽  
SHAIL BALA JAIN
Keyword(s):  
Low Power ◽  
Large Scale ◽  
Low Voltage ◽  
Supply Voltage ◽  
High Gain ◽  
Signal Frequency ◽  
Output Impedance ◽  
Self Cascode ◽  
Intrinsic Gain ◽  
Body Bias

In this work, a new composite transistor cell using dynamic body bias technique is proposed. This cell is based on self cascode topology. The key attractive feature of the proposed cell is that body effect is utilized to realize asymmetric threshold voltage self cascode structure. The proposed cell has nearly four times higher output impedance than its conventional version. Dynamic body bias technique increases the intrinsic gain of the proposed cell by 11.17 dB. Analytical formulation for output impedance and intrinsic gain parameters of the proposed cell has been derived using small signal analysis. The proposed cell can operate at low power supply voltage of 1 V and consumes merely 43.1 nW. PSpice simulation results using 180 nm CMOS technology from Taiwan Semiconductor Manufacturing Company (TSMC) are included to prove the unique results. The proposed cell could constitute an efficient analog Very Large Scale Integration (VLSI) cell library in the design of high gain analog integrated circuits and is particularly interesting for biomedical and instrumentation applications requiring low-voltage low-power operation capability where the processing signal frequency is very low.

scholarly journals Design Strategies and Architectures for Ultra-Low-Voltage Delta-Sigma ADCs

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1156
Author(s):  
Lorenzo Benvenuti ◽  
Alessandro Catania ◽  
Giuseppe Manfredini ◽  
Andrea Ria ◽  
Massimo Piotto ◽  
...  
Keyword(s):  
Low Voltage ◽  
Flicker Noise ◽  
Supply Voltage ◽  
Cmos Process ◽  
Clock Frequency ◽  
Design Environment ◽  
Ultra Low Power ◽  
Analog Cmos ◽  
Gain Error ◽  
Dc Gain

The design of ultra-low voltage analog CMOS integrated circuits requires ad hoc solutions to counteract the severe limitations introduced by the reduced voltage headroom. A popular approach is represented by inverter-based topologies, which however may suffer from reduced finite DC gain, thus limiting the accuracy and the resolutions of pivotal circuits like analog-to-digital converters. In this work, we discuss the effects of finite DC gain on ultra-low voltage ΔΣ modulators, focusing on the converter gain error. We propose an ultra-low voltage, ultra-low power, inverter-based ΔΣ modulator with reduced finite-DC-gain sensitivity. The modulator employs a two-stage, high DC-gain, switched-capacitor integrator that applies a correlated double sampling technique for offset cancellation and flicker noise reduction; it also makes use of an amplifier that implements a novel common-mode stabilization loop. The modulator was designed with the UMC 0.18 μm CMOS process to operate with a supply voltage of 0.3 V. It was validated by means of electrical simulations using the CadenceTM design environment. The achieved SNDR was 73 dB, with a bandwidth of 640 Hz, and a clock frequency of 164 kHz, consuming only 200.5 nW. It achieves a Schreier Figure of Merit of 168.1 dB. The proposed modulator is also able to work with lower supply voltages down to 0.15 V with the same resolution and a lower power consumption despite of a lower bandwidth. These characteristics make this design very appealing in sensor interfaces powered by energy harvesting sources.

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