A pipeflow calculation tool that complements pandapower in the simulation of multi energy grids
GeoJSON to Modelica Translator that is focused on district energy system design and analysis.
topotherm is a pyomo-based open-source optimization model for district heating network design.
A multi-country electricity market and district heating model
An Excel Add-In allowing calculations of the friction pressure loss (head loss) in circular pipes with full flow water in SI Units.
HeatPro Python Package: Generate Heat Demand Load Profile for District Heating
District heating system unit design and dispatch optimization dashboard using Mixed Integer Linear Programming (MILP).
Calculates the temperature drop through the single insulated steel pipe, buried (Steady-State).
A streamlit app based on heatpro to generate heat load profile
Simulations of hourly energy demand, capacity, storage, and CO2 for different expansion scenarios of District Heating (DH) network using EnergyPlus building energy demand .csv files and PVT generation input .csv file.
A black box data driven model that considers the characterization and prediction of heat load in buildings connected to District Heating by using smart heat meters
A VBA function calculating the return temperature from the radiator unit (hydronic space heating)
Modelica library for the modeling, simulation and control of District Heating Networks (DHN) & Gas Networks (GN) within multi-energy systems.
Heat loss, corrosion diagnostics, and predictive maintenance of pipeline systems. The package is designed for engineers who are involved in exploratory or routine calculations.
A Matlab tool calculating the friction pressure loss (head loss) in circular pipes with full flow water in SI Units.
This package contains all the Modelica components used for the SAMI Project, aiming to enhance the efficiency of a district heating network.
Simulations of 5th generation district heating and cooling grids using Julia
Neural networks based clusters aggregation for DHN
This repository contains some of the scripts and documentation from my PhD research on data-driven methodologies for building efficiency within the district heating sector. It includes R scripts for time series analysis, machine learning, and energy optimization using smart heat meter data.
Synthetic DHN generator model
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