40 lines
2.7 KiB
Markdown
40 lines
2.7 KiB
Markdown
# GridForge
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GridForge is a production-ready, low-code platform for composing cross-domain energy optimization applications. Utilities, SMEs, and communities can rapidly assemble multi-agent workflows that span electricity, water, heating, and edge devices. The platform exposes a visual DSL inspired by Object/Morphism/Functor/Limits/Colimits and a monoidal time model, enabling local problem definitions, data exchange channels, and global constraints.
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Key capabilities:
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- Visual DSL constructs: Objects (local optimization problems), Morphisms (data channels with schemas), Functors (problem transformers to a canonical representation), Limits/Colimits (global constraints and composition points), and TimeMonoid (rounds and async updates).
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- Auto-generated adapters and contract registry with versioning and conformance tests for plug-and-play deployment on DERs, meters, pumps, and controllable loads.
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- Integrated solver stack: optional ADMM-lite engine for distributed optimization with delta-sync and audit-ready reconciliation.
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- Simulation sandbox and hardware-in-the-loop templates to validate end-to-end workflows before field deployment.
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- Governance scaffold: RBAC, multi-tenant isolation, audit trails, and policy-driven exposure of shared signals.
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- Metrics: deployment time, adapter coverage, convergence speed, cross-domain performance, and governance/traceability KPIs.
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Getting started
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- Install: python -m pip install -e .
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- Run API server: uvicorn gridforge.server:app --reload
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- Run tests: pytest
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- Run packaging checks: bash test.sh (will build and run tests)
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Project structure (high level)
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- gridforge/
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- __init__.py: Package initialization
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- dsl.py: Core DSL data models (Object, Morphism, Functor, Limits, TimeMonoid)
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- core.py: Canonicalization and transformations of DSL into a canonical representation
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- adapters.py: Skeleton adapter generation and registry logic
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- contract.py: Versioned adapter contracts, conformance testing stubs
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- solver.py: ADMM-lite solver implementation for toy problems
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- simulation.py: Sandbox environment for end-to-end validation
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- governance.py: RBAC and policy scaffolding
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- server.py: FastAPI app exposing a basic API for prototyping
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tests/
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- test_basic.py: Basic DSL and adapter generation tests
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- test_solver.py: Simple solver behavior tests (toy problem)
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Roadmap
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- Expand DSL with richer validation, transformations, and cross-domain semantics.
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- Implement delta-sync runtime with robust reconciliation and audit logging.
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- Integrate with real-world backbones (Open-EnergyMesh, CatOpt) via adapters.
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- Harden the governance layer with policy engines and multi-tenant isolation.
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- Provide end-to-end demos and hardware-in-the-loop templates.
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