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Power quality is a critical concern for utilities and consumers alike, as modern industries increasingly rely on energy-efficient and electronically controlled equipment. To address this issue, we have developed a power quality monitoring system that can detect and analyze power quality disturbances in real-time. This project utilizes Arduino as the base software and focuses on monitoring four key parameters: harmonics, voltage sag, voltage swell, and power factor. We employ the mathematical Method of Fast Fourier Transform (FFT) to extract and localize voltage disturbances in recorded data, providing valuable insights into power quality issues affecting industries.
The extracted data is then uploaded to the internet using an ESP Module, allowing for data storage and in-depth analysis.
In the 21st century, industries have undergone a revolution with increased automation and the use of modern equipment. These advancements have made equipment more energy-efficient and electronically controlled, but also more sensitive to power supply deviations. Power quality has become a paramount concern for utilities striving to meet customer demands.
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As power quality issues continue to grow in significance, it is imperative to establish a power quality monitoring system capable of detecting and addressing these disturbances.
This project focuses on online monitoring of power quality issues in industrial settings, with a particular emphasis on four parameters: Voltage Swell, Voltage Sag, Harmonics, and Power Factor. To analyze these parameters, we employ the Method of Fast Fourier Transform (FFT), a mathematical technique capable of extracting and localizing voltage disturbances within recorded data. By understanding the magnitude and frequency components of these disturbances, we can gain valuable insights into power quality issues affecting industries.
The data extracted from our monitoring system is uploaded to the internet via an ESP Module, enabling us to store and analyze the data over an extended period.
This project aims to provide a comprehensive solution for monitoring and addressing power quality issues in industrial environments.
The main objective of our project is to develop a power quality monitoring system capable of analyzing the root mean square (rms) current and voltage signals. Based on this analysis, the system should identify factors affecting power quality, including harmonics, voltage sag, voltage swell, and power factor. The system will then upload the data to the internet using an ESP module, allowing for data storage and in-depth analysis of power quality issues.
Power quality is defined differently for manufacturers and consumers. For manufacturers, it is the power supply level necessary for the most efficient operation of their machines. For consumers, it is the assurance of continuous and uninterrupted power supply, vital for business operations and daily life. According to IEEE (Institute of Electrical and Electronics Engineers), power quality is defined as the concept of powering and grounding sensitive electronic equipment in a manner suitable for the equipment's performance and life expectancy.
In essence, power quality encompasses both performance and longevity considerations. Power quality issues can have significant consequences, including reduced capacity, production waste, equipment failure, utility penalties, and financial losses. Addressing these issues requires continuous monitoring and data storage to diagnose and rectify power quality problems effectively.
Monitoring power quality necessitates the detection of parameters that influence power quality. However, automatic detection is challenging due to the wide-ranging variations in disturbances in both time and frequency domains. Consequently, diagnosing power quality problems remains a complex task.
| Group ID | Date | Domain |
|---|---|---|
| 58042 | 05/07/2019 | Monitoring of Power Quality |
Empathy Mapping Canvas
Design For: Industries Design By: Group 58042
Date: 05/07/2019 Version: 1.0
| Users | Stakeholders |
|---|---|
| Energy Auditor | Government |
| Industries | Educational Institutions |
| Commercial Users |
Project: Online Monitoring of Power Team: 58042
| People | Activities | Situation/Context/Location | Props/Possible Solutions |
|---|---|---|---|
| Dealer | Harmonics | Small Scale Industries | Online Monitoring |
| Client | Power Factor | Medium Scale Industries | Data Storage |
| Admin | Voltage Sag | Substation | Continuous Monitoring |
Product Development Canvas Team/Date/Version: 58042/ 16/10/2019/ 1.0
Purpose
Product Experience
Customer Revalidation
Product Function
Components
Power quality is defined differently for different users. For manufacturers, it is the power supply level necessary for the most efficient operation of their machines. For consumers, it is the assurance of continuous and uninterrupted power supply, vital for business operations and daily life. According to IEEE, power quality can be defined as the concept of powering and grounding sensitive electronic equipment in a manner suitable for the equipment's performance and life expectancy.
In short, power quality encompasses both performance and longevity considerations, with the equation: Power Quality = Performance + Life Expectancy.
Voltage Sag is defined as the decrease in the RMS voltage level to 10% to 90% of nominal at the power frequency for durations of 0.5 cycles to 1 minute (IEEE-1159). It is also known as voltage dip and can be caused by natural events or human activities, such as the starting of large motors, lightning, or accidents. Voltage Sag can lead to system shutdown, reduced efficiency, and a shortened lifespan of equipment, resulting in significant losses.
Voltage Swell is defined as the increase in the RMS voltage level to 110% to 180% of nominal at the power frequency for durations of 0.5 cycles to 1 minute. It can be caused by de-energization of large loads or abrupt interruptions of current in a line.
Harmonics are sinusoidal components of a periodic wave having a frequency that is an integer multiple of the fundamental frequency. They can disrupt power quality and include frequency components such as the fundamental, 3rd order, and 5th order harmonics.
Power Factor is defined as the ratio between the active power of the fundamental wave to the apparent power of the fundamental wave. It is the cosine of the displacement angle between the voltage and current waveforms.
| Component | Description |
|---|---|
| Arduino Due | The Arduino Due is a microcontroller based on the Atmel SAM3X8E ARM Cortex-M3 CPU. It is the first Arduino board based on a 32-bit ARM core microcontroller and can be connected to a computer via USB cable. It communicates with a computer using the Arduino Software. |
| Current Sensor ACS-712 | The Current Sensor ACS-712 is used for current sensing and has three pins: Vcc, Ground, and Output. It offers a sensitivity of 185 mV/A. |
| Voltage Sensor ZMPT 101B | The Voltage Sensor ZMPT 101B is a sensor used to measure voltage. It is essential for monitoring voltage levels in the power quality monitoring system. This sensor is commonly used in various electronic applications to measure AC voltage accurately. |
| ESP 8266 | The ESP 8266 is a versatile Wi-Fi module that enables wireless communication in the power quality monitoring system. It allows the system to upload data to the internet for remote monitoring and analysis. The ESP 8266 is known for its reliability and ease of use in IoT (Internet of Things) applications. |
The Arduino Due is a microcontroller based on the Atmel SAM3X8E ARM Cortex-M3 CPU. It is the first Arduino board based on a 32-bit ARM core microcontroller and can be connected to a computer via USB cable. It communicates with a computer using the Arduino Software.
The Current Sensor ACS-712 is used for current sensing and has three pins: Vcc, Ground, and Output. It offers a sensitivity of 185 mV/A.
The Voltage Sensor ZMPT 101B is a sensor used to measure voltage. It is essential for monitoring voltage levels in the power quality monitoring system. This sensor is commonly used in various electronic applications to measure AC voltage accurately.
The ESP 8266 is a versatile Wi-Fi module that enables wireless communication in the power quality monitoring system. It allows the system to upload data to the internet for remote monitoring and analysis. The ESP 8266 is known for its reliability and ease of use in IoT (Internet of Things) applications.
```cpp
#include
const int sensorIn = A0;
int mVperAmp = 185; // use 100 for 20A Module & 66 for 30A Module
double Voltage = 0;
double VRMS = 0;
double AmpsRMS = 0;
void setup(){
Serial.begin(9600);
pinMode(13, OUTPUT);
}
void loop(){
Voltage = getVPP();
VRMS = (Voltage/2.0) *0.707; //root 2 is 0.707
AmpsRMS = (VRMS * 1000)/mVperAmp;
Serial.print(AmpsRMS);
Serial.println(" Amps RMS");
//Serial.println(VRMS, 0.00001);
if( AmpsRMS > 0.6 )
{
digitalWrite(13,HIGH);
}
else
{
digitalWrite(13,LOW);
}
}
float getVPP()
{
float result;
int readValue; //value read from the sensor
int maxValue = 0; // store max value
int minValue = 1024; // store min value
uint32_t start_time = millis();
while((millis()-start_time) < 1000) //sample for 1 Sec { readValue = analogRead(sensorIn); // see if you have a new maxValue if (readValue > maxValue)
{
/record the maximum sensor value/
maxValue = readValue;
}
if (readValue < minValue)
{
/record the minimum sensor value/
minValue = readValue;
}
}
// Subtract min from max
result = ((maxValue - minValue) * 5.0)/1024.0;
return result;
}
```cpp
#include "arduinoFFT.h"
#define SAMPLES 128 //Must be a power of 2
#define SAMPLING_FREQUENCY 1000 //Hz, must be less than 10000 due to ADC
arduinoFFT FFT = arduinoFFT();
unsigned int sampling_period_us;
unsigned long microseconds;
double SCL_FREQUENCY;
double vReal[SAMPLES];
double vImag[SAMPLES];
void setup() {
Serial.begin(115200);
sampling_period_us = round(1000000 * (1.0 / SAMPLING_FREQUENCY));
}
void loop()
{
/*SAMPLING*/
for (double i = 0; i < SAMPLES; i++)
{
microseconds = micros(); //Overflows after around 70 minutes!
vReal[i] = analogRead(0);
vImag[i] = 0;
while (micros() < (microseconds + sampling_period_us)) {
}
}
/*FFT*/
FFT.Windowing(vReal, SAMPLES, FFT_WIN_TYP_HAMMING, FFT_FORWARD);
FFT.Compute(vReal, vImag, SAMPLES, FFT_FORWARD);
FFT.ComplexToMagnitude(vReal, vImag, SAMPLES);
double peak = FFT.MajorPeak(vReal, SAMPLES, SAMPLING_FREQUENCY);
/*PRINT RESULTS*/
//Serial.println(peak); //Print out what frequency is the most dominant*/
for (int i = 0; i < (SAMPLES / 2); i++)
{
/*View all three lines in serial terminal to see which frequencies have which amplitudes*/
Serial.print((i * 1.0 * SAMPLING_FREQUENCY) / SAMPLES, 1);
Serial.print(" ");
Serial.println(vReal[i], 1); //View only this line in serial plotter to visualize the bins
}
delay(2000); //Repeat the process every second OR:
//while (1); //Run code once
}
Upon completion of this project, we have developed a comprehensive power quality monitoring system capable of online monitoring and analysis. This system can provide real-time data to users, allowing them to monitor and analyze power quality issues effectively. By addressing factors such as harmonics, voltage sag, voltage swell, and power factor, our project aims to enhance power quality in industrial settings.
Project Report: Online Monitoring of Power Quality. (2019, Dec 03). Retrieved from https://studymoose.com/document/report-sem-7-example
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