NEMO |
University of New South Wales |
true |
true |
GNU General Public License version 3.0 (GPL-3.0) |
all |
|
true |
dispatch |
|
Australia |
Optimization Simulation |
Optimisations are carried out using a single-objective evaluation function (with penalties). The search space (of generator capacities) is searched using the CMA-ES algorithm. |
minimise average cost of electricity |
|
Python |
transmission |
|
Hour |
NEMO (SEI) |
Stockholm Environment Institute |
true |
false |
Apache License 2.0 (Apache-2.0) |
|
Full energy system optimization flexible geographic and sectoral scope |
true |
dispatch investment |
|
All |
Optimization |
Constrained cost optimization with perfect foresight |
Minimize total discounted costs |
Deterministic but can readily be applied in Monte Carlo analyses |
Julia |
transmission distribution DC load flow net transfer capacities |
SQLite |
Hour |
OMEGAlpes |
G2Elab |
true |
false |
Apache License 2.0 (Apache-2.0) |
some |
Production consumption conversion storage |
true |
|
|
|
Optimization |
|
|
|
OMEGAlpes, PuLP |
|
|
|
OSeMOSYS |
KTH Royal Institute of Technology |
true |
true |
Apache License 2.0 (Apache-2.0) |
all |
|
true |
investment |
|
Africa (all countries), Sweden, Baltic States, Nicaragua, Bolivia, South America, EU-27+3 |
Optimization |
Linear optimisation (with an option of mixed-integer programming) |
Minimise total discounted cost of system |
|
GNU MathProg |
transmission distribution |
Python |
Day |
Oemof |
Reiner Lemoine Institut / ZNES Flensburg |
true |
true |
GNU General Public License version 3.0 (GPL-3.0) |
some |
Energy Modelling Framework |
true |
dispatch investment |
|
Depends on user |
Optimization Simulation |
https://oemof.org/libraries/ |
costs, emissions |
Deterministic |
Python, Pyomo, Coin-OR |
transmission distribution net transfer capacities DC load flow |
PostgreSQL, PostGIS |
Hour |
OnSSET |
KTH Royal Institute of Technology |
true |
false |
MIT license (MIT) |
|
|
true |
|
|
Sub-Saharan Africa, developing Asia, Latin America |
Optimization |
|
Cost minimization |
|
Python |
|
Python |
Multi year |
OpenTUMFlex |
Technical University of Munich |
true |
false |
GNU General Public License version 3.0 (GPL-3.0) |
some |
Energy System Model urban energy systems load shifting optimisation Local energy systems |
true |
|
|
User dependent |
Optimization Simulation |
|
Cost optimal optimization and flexibility calculation |
|
Python (Pyomo) |
distribution |
|
15 Minute |
PLEXOS Open EU |
University College Cork |
false |
true |
|
all |
Market Model |
true |
dispatch |
|
North West Europe |
Optimization |
Least Cost Optimization, Can be run in MIP or linear relaxed mode |
Minimize total Generation cost |
None |
PLEXOS |
net transfer capacities |
MS Excel |
Hour |
POMATO |
TU Berlin |
true |
false |
GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0) |
some |
Network-constrained Unit Commitment and Economic Dispatch |
true |
dispatch |
|
User-dependent |
Optimization |
Linear Economic Dispatch. Linear Optimal Power Flow. Linear Security Constrained Optimal Power Flow |
Cost minimization |
Chance Constrained |
Julia/JuMP |
transmission DC load flow net transfer capacities |
Python |
Hour |
Pandapipes |
Fraunhofer IEE, Uni Kassel |
true |
true |
MIT license (MIT) |
|
|
false |
|
|
|
Simulation |
|
|
|
Python |
distribution |
|
|
Pandapower |
|
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
some |
Transmission Network Model |
true |
|
|
|
Simulation |
|
|
|
Python |
transmission distribution |
Pandas |
|
PowNet |
Singapore University of Technology and Design |
true |
false |
MIT license (MIT) |
all |
Network-constrained Unit Commitment and Economic Dispatch |
true |
dispatch |
|
Laos, Cambodia, Thailand, any user-defined country or region |
Optimization Simulation |
Mixed Integer Linear Program (MILP), DC Power Flow, Unit Commitment, Economic Dispatch |
Cost minimization |
Sensitivity analysis |
Python (Pyomo) |
transmission distribution DC load flow |
Python |
Hour |
PowerMatcher |
Flexiblepower Alliance Network |
true |
false |
Apache License 2.0 (Apache-2.0) |
|
|
true |
|
|
|
|
|
|
|
Java |
|
|
|
PowerSimulations.jl |
NREL |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
quasii-static sequential unit-commitment and economic dispatch problems |
true |
dispatch |
|
Any |
Optimization |
Principal application is sequential quasi-static system optimization problems (production cost modeling). |
Least Cost |
scenario analysis |
Julia |
transmission AC load flow DC load flow net transfer capacities |
Julia |
Second |
PowerSimulationsDynamics.jl |
NREL |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
Dynamic system simulation model library |
true |
|
|
|
Simulation |
PowerSimulationsDynamics.jl enables transient stability analysis of power systems through differential-algebraic equations and with forward differentiation to enable small-signal stability analysis. |
N/A |
scenario analysis |
Julia |
transmission AC load flow |
Julia |
Less than second |
PowerSystems.jl |
NREL |
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
|
Optimization Simulation |
true |
dispatch |
|
Any |
Simulation |
PowerSystems.jl includes basic power flow and network matrix calculation capabilities. |
|
scenario analysis |
Julia |
transmission AC load flow DC load flow net transfer capacities |
Julia |
Less than second |
Pvlib python |
|
true |
false |
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) |
some |
|
true |
|
|
|
Simulation |
|
|
|
Python |
|
NumPy, Pandas |
|
PyLESA |
University of Strathclyde |
true |
false |
MIT license (MIT) |
some |
Local energy systems |
true |
dispatch |
|
|
Simulation |
|
Minimization of operational costs |
perfect foresight |
Python |
AC load flow DC load flow |
Python |
Hour |
PyPSA |
FIAS |
true |
false |
GNU General Public License version 3.0 (GPL-3.0) |
all |
Energy System Model |
true |
dispatch investment |
|
Europe, China, South Africa |
Optimization Simulation |
Non-linear power flow; linear optimal power flow / investment optimisation |
Cost minimization |
Not explicitly covered, but stochastic optimisation possible |
Python, Pyomo |
transmission distribution AC load flow DC load flow net transfer capacities |
Pandas |
Hour |
QuaSi - GenSim |
Siz energieplus |
true |
false |
MIT license (MIT) |
all |
building energy demand |
true |
|
|
All |
Simulation |
EnergyPlus is used to perform a thermal building simulation |
|
|
EnergyPlus, OpenStudio, MS Excel, Ruby |
|
MS Excel |
15 Minute |