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emhass 0.17.6 documentation - Home emhass 0.17.6 documentation - Home
  • 🚀 Getting Started
  • ⚙️ Configuration
  • 🧠 Core Concepts
  • 🔥 Thermal Integration
  • 📁 Study Cases
  • Cookbook
  • 💻 Reference
  • GitHub
  • 🚀 Getting Started
  • ⚙️ Configuration
  • 🧠 Core Concepts
  • 🔥 Thermal Integration
  • 📁 Study Cases
  • Cookbook
  • 💻 Reference
  • GitHub

Section Navigation

  • Main Core Concepts: The Basics
  • An EMS based on Linear Programming
  • The forecast module
  • The machine learning forecaster
  • The machine learning regressor
  • 🧠 Core Concepts

🧠 Core Concepts#

  • Main Core Concepts: The Basics
    • 1. The Goal: Choosing a Cost Function
    • 2. The Timing: Optimization Types
    • 3. The Devices
    • Technical Reference
  • An EMS based on Linear Programming
    • Motivation
    • Linear programming
    • Household EMS with LP
    • The EMHASS optimizations
    • Time windows for deferrable loads
    • References
  • The forecast module
    • PV power production forecast
    • Load power forecast
    • Load cost forecast
    • PV production selling price forecast
    • Passing your own forecast data
    • Now/current values in forecasts
    • References
  • The machine learning forecaster
    • A basic model fit
    • The predict method
    • The tuning method with Bayesian hyperparameter optimization
    • How does this work?
    • Going further?
  • The machine learning regressor
    • A basic model fit
    • The predict method
    • Storing CSV files

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Using Commercial Solvers (CPLEX / Gurobi)

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Main Core Concepts: The Basics

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