PowerMeter v0.2.0-app

First packaged desktop release of PowerMeter for macOS.

This release introduces the application fork focused on local desktop use, Modbus/TCP device discovery, local SQLite storage, and a packaged FastAPI backend launched together with the desktop shell.

Highlights

• Added macOS desktop application packaging.
• Added FastAPI backend sidecar integration for the desktop app.
• Added local SQLite database storage in the user application data directory.
• Added desktop diagnostics endpoint and health check flow.
• Added Modbus/TCP network discovery workflow.
• Added configurable Unit ID discovery modes:
  • quick
  • extended
  • custom
  • guarded full scan mode
• Added scan job persistence and scan result storage.
• Added candidate device creation from discovered Modbus devices.
• Added frontend controls for scan mode, timeout, concurrency, and custom Unit IDs.
• Added safer Modbus detection strategy:
  • FC43/14 first
  • FC03 fallback
  • FC04 fallback
  • valid Modbus exception responses are treated as device responses.

Desktop runtime

The app stores its local data under the operating system application data directory.

On macOS:

~/Library/Application Support/PowerMeter/

Typical runtime files:

app.sqlite
logs/

Useful diagnostic endpoints:

http://127.0.0.1:8765/api/health
http://127.0.0.1:8765/api/desktop/diagnostics

Validation

The following check passed before release:

env PYTHONPYCACHEPREFIX=/tmp/powermeter_pycache .venv/bin/python -m compileall backend/app

Also verified:

• backend health endpoint returns OK;
• desktop diagnostics endpoint returns OK;
• SQLite database initialization works;
• desktop mode uses the expected application data directory;
• scan parameter validation works;
• quick, extended, custom, and guarded full scan plans were checked;
• custom Unit ID sorting and validation were checked;
• invalid custom Unit ID input is rejected.

Known limitations

• macOS build may be unsigned or not notarized.
• Gatekeeper may require manual approval on first launch.
• Discovery reliability depends on network access, firewall rules, reachable Modbus/TCP port 502, and device Unit ID configuration.
• Full Unit ID scanning is intentionally guarded to avoid unnecessarily aggressive scans.
• This is an early application release intended for testing and feedback.

Recommended installation

1. Download the attached macOS application archive or DMG.
2. Move PowerMeter to the Applications folder.
3. Launch the app.
4. If macOS blocks launch, allow it manually through System Settings → Privacy & Security.
5. Open diagnostics if the backend does not start.
6. Check that the health endpoint returns OK.

Notes for testers

Please report:

• macOS version;
• Apple Silicon or Intel CPU;
• whether the app launched successfully;
• whether backend diagnostics are healthy;
• whether discovery found expected Modbus/TCP devices;
• screenshots or logs from:

~/Library/Application Support/PowerMeter/logs/

v0.1.0 – Research Prototype Release

PowerMeter v0.1.0 — Research Prototype Release

We are pleased to announce the first public release of PowerMeter.

PowerMeter is an open-source platform for industrial energy monitoring, Modbus TCP data acquisition, demand response analytics, and electrical load pattern analysis. The project combines practical energy monitoring capabilities with research-oriented analytical tools, creating a foundation for both industrial deployments and smart-grid research.

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Highlights

Real-Time Energy Monitoring

PowerMeter provides continuous acquisition of electrical measurements from Modbus TCP-compatible meters and gateways.

Key capabilities:

• Modbus TCP communication
• Automated polling of connected devices
• Local data storage
• Historical measurement archive
• Web-based visualization

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Local-First Architecture

The platform is designed to operate entirely on local infrastructure without requiring cloud services.

Features include:

• SQLite-based storage
• Lightweight deployment
• Edge-computing compatibility
• Raspberry Pi support
• Low hardware requirements

This approach simplifies deployment in industrial environments and research laboratories where data privacy and network isolation are important.

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Demand Response Potential Index (DRPI)

One of the distinguishing features of PowerMeter is the implementation of a Demand Response Potential Index (DRPI).

The index is intended to support:

• flexibility assessment
• demand response studies
• smart-grid research
• load management investigations
• industrial energy optimization

The current implementation serves as a research-oriented analytical layer on top of traditional energy monitoring functions.

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Singular Spectrum Analysis (SSA)

PowerMeter includes experimental support for electrical load profile analysis using Singular Spectrum Analysis (SSA).

SSA enables:

• trend extraction
• noise reduction
• periodicity detection
• load pattern decomposition
• exploratory data analysis

This functionality is intended for researchers and engineers investigating consumption behavior and flexibility characteristics.

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REST API

The platform exposes functionality through a FastAPI-based backend.

Benefits:

• machine-readable interfaces
• integration with external applications
• future extensibility
• support for automation workflows

Interactive API documentation is available through Swagger/OpenAPI.

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Raspberry Pi Deployment

PowerMeter can be deployed on low-cost edge hardware such as Raspberry Pi devices.

The repository includes deployment instructions covering:

• installation
• configuration
• service management
• automatic startup

This enables cost-effective deployment in laboratories, pilot projects, and industrial environments.

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Current Scope

PowerMeter is currently positioned as a research prototype.

The project is suitable for:

• energy monitoring experiments
• smart-grid research
• demand response studies
• academic projects
• industrial proof-of-concept deployments

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Known Limitations

Current limitations include:

• limited device validation across meter manufacturers
• ongoing development of analytics modules
• absence of packaged installers
• limited automated testing coverage
• no official Docker deployment yet
• no built-in demo mode

These areas are planned for future development.

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Roadmap

Planned improvements include:

• expanded device compatibility
• improved visualization capabilities
• demo mode with synthetic datasets
• containerized deployment
• advanced demand response analytics
• NILM-related research functionality
• forecasting and predictive analytics
• enhanced documentation

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Scientific Use

PowerMeter is being developed as an open-source platform at the intersection of:

• energy informatics
• industrial IoT
• smart grids
• demand response
• energy flexibility assessment
• load analytics

Researchers are encouraged to evaluate, reproduce, and extend the analytical methods implemented within the project.

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Acknowledgements

The project has been developed as part of ongoing work in power systems engineering, energy analytics, and demand response research.

Contributions, feedback, issue reports, and collaboration proposals are welcome.

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License

Released under the MIT License.