Property:Required software

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A

Arc-gis to geo-dependent-energy-web-service +Geo dependent energy demand and suppy WebService using VIsualStudio as client  +

C

Curve extraction and fitting of energy conversion systems +MATLAB, YALMIP, MILP solver such as CPLEX  +

D

Demand management of random consumption profiles +MATLAB, YALMIP, CPLEX or other MILP solver  +
Dynamic carbon factor tool +R  +

E

Edit AIMMS model +AIMMS Matlab  +
Energy hub server +Docker PyEHub library  +
EnergyPlus batch run module +EnergyPlus Matlab  +
EnergyPlus: Typical Residential Buildings in a Swiss Alpine Village +EnergyPlus  +
Execute AIMMS sequence +AIMMS Matlab  +

F

Fast Fluid Dynamics Processing +Processing: https://processing.org/  +

G

GUI-GIS +This project is based on the open-source GIS application QGIS. This project exists as a QGIS Plugin that can be installed on the QGIS Desktop application. The core of QGIS is written in Cpp whereas the plugins are written in Python. The plugin is written in python and makes use of several python libraries. The GUI of Python plugin is developed by making use of PyQt (Python library for Qt GUI framework in Cpp). • PyQt4 • QGIS 2.18.7 (http://download.osgeo.org/qgis/windows/) The plugin makes use of the QGIS APIs (PyQGIS) to interact with the QGIS Desktop, more specifically the canvas as well as the QGIS Utilities. • qgis.core • qgis.gui The plugin performs basic vector network analysis in form of routing algorithms. For this purpose, it uses the grass library which is a part of QGIS as a part of the processing toolbox. • grass7 (7.2) • Processing toolbox (need to be enabled) Following are the python libraries on which the plugin depends (some need to be installed beforehand). • os: Reading/Writing data and creating paths relative to the script’s location • csv: Reading/Writing CSV files. • json: Reading/Writing JSON files. • math: calculation of complex data items to fill-up attribute tables. • processing: qgis processing python library for grass library. • xlsxwriter: Writing data into excel files. (need to be Installed) • xlrd: Reading data from Excel files. (need to be Installed) • pandas: Reading/Writing data and dealing with input and output. (need to be Installed) Note: These libraries can be installed using “pip”, but in case of Windows this needs to be done from the OSGeo Shell (as Admin) and not the usual command shell. The python libraries can be of the latest version. (using pip install.)  +
Generic Energy Hub YALMIP +MATLAB, YALMIP  +
Generic energy hub (AIMMS) +AIMMS  +
Generic energy hub (Pyomo) +Python 3.4 Pyomo (python package) MILP solver as Gurobi, Cplex or CBC solver  +
GrasshopperSolarPotentials +https://www.rhino3d.com/ http://www.grasshopper3d.com/  +

M

Mechanism design for the energy hub dispatch: case study +MATLAB, YALMIP, LP solver such as CPLEX  +
Modular Energy Hub Modeling Framework +Python, Oemof (https://github.com/oemof)  +
Multi-agent reinforcement learning-based energy hub model +Python 3  +

N

Nonlinear powerflow constraints +AIMMS, Matpower (http://www.pserc.cornell.edu/matpower)  +

P

Parse XML +Matlab  +
Profile shifting optimization model +AIMMS  +
PyEHub +Python 3.6.1 pip for Python 3.6.1 An MILP solver (e.g. CPlex or GLPK)  +

R

Read AIMMS data +AIMMS Matlab  +
Read AIMMS solution header +AIMMS Matlab  +
Read AIMMS variable names +AIMMS Matlab  +
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