A low-cost, high-precision power grid frequency monitoring solution for the European power grid. Monitor grid stability with ±0.002Hz precision and get instant alerts for frequency deviations.
- 📊 Real-time frequency monitoring (±0.002Hz precision)
- 🔔 Local alerts via LCD display and buzzer
- 📡 MQTT data transmission
- 📱 20x4 LCD interface with button controls
- 🔋 Offline operation capability
- 📦 3D-printable case included
Frequency is the heartbeat of the electrical grid - it reflects the instantaneous balance between electricity generation and consumption across the entire Continental European network. When this balance shifts, frequency changes reveal:
- Supply-Demand Imbalances: Frequency drops when demand exceeds generation, rises when generation exceeds demand
Every frequency change tells a story about grid operations:
- Slow Drifts (minutes): Indicate systematic generation-load imbalances, economic dispatch changes
- Fast Changes (seconds): Reveal sudden events like generator trips, large load connections/disconnections
- Oscillations: Show control system interactions, potential stability issues
- Rate of Change: Indicates how rapidly the system is losing or gaining energy
By monitoring frequency, you gain insight into:
- Early Warning System: Detect grid disturbances before they escalate to blackouts
- Load-Generation Balance: Understand real-time supply and demand dynamics
Critical Thresholds (ENTSO-E Standards)
| Threshold | Value | Description |
|---|---|---|
| Standard Frequency Range | 49.95 - 50.05 Hz | Normal operating range |
| Alert Range | 49.8 - 50.2 Hz | Deviation monitoring required |
| Level 1 Emergency | 49.2 - 50.8 Hz | Emergency state |
| Level 2 Emergency | 47.5 - 51.5 Hz | Blackout risk |
| Rate of Change (RoCoF) | > ±0.5 Hz/s | Dynamic stability threshold |
Source: ENTSO-E Operation Handbook, Policy 1: Load-Frequency Control and Performance, Section A-S1: Standard Frequency Range Parameters. These are the official thresholds for the Continental Europe Synchronous Area.
View real-time frequency data from this sensor: Live Dashboard
For comprehensive grid analysis and historical data, visit Energy-Charts, maintained by Fraunhofer ISE.
- ESP32 development board Link
- 20x4 LCD display (I2C) Link
- Push buttons (3x) Link
- Buzzer Link
- ZMPT101B Active Single Phase Voltage Transformer LINK
- 5V USV Module LINK
- HDR-15 Power Supply LINK
The device housing consists of three parts that can be 3D printed:
Print Settings:
- Material: PETG or ABS recommended (better heat resistance than PLA)
- Layer Height: 0.2mm
- Infill: 25%
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Hardware Setup
- Follow the provided schematic
- Print the case using provided STL file
- Connect components according to pin configuration:
ADC Input: GPIO34 LCD: SDA -> GPIO21, SCL -> GPIO22 Buttons: Up -> GPIO23, Down -> GPIO19, Mute -> GPIO18 Buzzer: GPIO25
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Software Setup
# Clone the repository git clone https://github.com/calkoe/OpenFreqSensor # Install PlatformIO # Open project in PlatformIO # Configure wifi settings in config.h # Build and upload
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Configuration
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Copy
include/config.template.htoinclude/config.h -
Edit
config.hwith your settings:// Network settings #define WIFI_SSID "your_ssid" #define WIFI_PASSWORD "your_password" #define MQTT_SERVER "your_mqtt_server" #define MQTT_USERNAME "your_username" #define MQTT_PASSWORD "your_password" // Device identification #define SENSOR_ID "freqsensor/your_id"
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The template file contains all available configuration options
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config.his ignored by git to keep your private settings secure
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The sensor publishes JSON messages with the following structure:
{
"sensorId": "freqsensor/koecher1", // Unique sensor identifier
"time": 1761407894423, // UNIX timestamp in milliseconds
"freq": 49.964, // Current grid frequency in Hz
"amp": 167844.8, // Signal amplitude (ADC units)
"quality": 0.012, // Measurement quality (lower is better)
"alert": false, // Whether frequency exceeds thresholds
"alertType": "none", // Type of alert if triggered
"deviation": 0.036, // Deviation from 50 Hz
"ramp": 0.002990723, // Rate of change in Hz/s
"analyzingDelay": 250, // Processing time in ms
"freeHeap": 111228, // Available ESP32 memory in bytes
"heapUsage": 65.4, // Memory usage percentage
"cpuFreq": 240, // CPU frequency in MHz
"wifiRSSI": -60 // WiFi signal strength in dBm
}- Sampling Rate: 512 Hz
- FFT Analysis Size: 512 samples
- Gaussian interpolation for high precision
- Ring buffer size: 4096 samples
- Analysis interval: 250ms
- Assembled with ESP32 and components
- 3D printed case
- LCD display showing real-time frequency readings
- Frequency accuracy: ±0.002Hz verified against reference meter
- Response time: <250ms for frequency changes
- MQTT connectivity: Stable data transmission
- Battery backup: 4+ hours operation during power outages
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
This project is provided "AS IS", without warranty of any kind, express or implied. By using this project, you agree that:
- The authors and contributors are NOT LIABLE for any damages or injuries arising from the use of this project
- This project is for EDUCATIONAL AND RESEARCH PURPOSES ONLY
- Any use of this project is AT YOUR OWN RISK
- The accuracy and reliability of measurements cannot be guaranteed
- This is NOT a certified measurement device
This device:
- Connects to LETHAL MAINS VOLTAGE (230V AC)
- Should ONLY be built and installed by QUALIFIED PERSONNEL
- Requires proper electrical isolation and safety measures
- Must be properly enclosed in an insulated case
- Should never be operated without proper safety barriers
DO NOT attempt to build or use this device unless you:
- Are a qualified electrician or electrical engineer
- Fully understand the risks of working with mains voltage
- Know how to properly isolate high-voltage circuits
- Can implement proper safety measures
IMPROPER USE CAN RESULT IN:
- Electric shock
- Death
- Fire
- Property damage