Lemlab
From wiki.openmod-initiative.org
|
local energy market laboratory
by Technical University of Munich
Authors:
Sebastian Dirk Lumpp, Markus Doepfert, Michel Zade
Contact:
Sebastian Dirk Lumpp
|
An open-source tool for the agent-based development and testing of local energy market applications. lemlab allows the user to simulate a LEM using a full agent-based modelling (ABM) in either simulation (SIM) or real-time (RTS) modes. This allows the rapid testing of algorithms as well as the real-time integration of hardware and software components.
Based on Python, Pyomo. Using PostgreSQL, Ethereum for data processing.
Website / Documentation
Download
|
 Open Source
GNU General Public License version 3.0 (GPL-3.0)
Directly downloadable
Input data shipped
|
| Model Scope |
Model type and solution approach |
| Model class
|
agent-based simulation
|
| Sectors
|
local energy markets
|
| Technologies
|
Renewables, Conventional Generation, CHP
|
| Decisions
|
|
| Regions
|
|
| Geographic Resolution
|
|
| Time resolution
|
|
| Network coverage
|
|
|
| Model type
|
Simulation, Agent-based
|
|
|
Agents: intertemporal convex optimization
Markets: (iterative) double-sided auctions, p2p clearing
Forecasting: naive, deterministic forecasting, neural networks
|
| Variables
|
|
| Computation time
|
minutes
|
| Objective
|
|
| Uncertainty modeling
|
perfect forecast, deterministic, stochastic
|
| Suited for many scenarios / monte-carlo
|
No
|
|
References
Scientific references
◀ back to model list
Facts about "Lemlab"RDF feed
| Author institution | Technical University of Munich + |
| Authors | Sebastian Dirk Lumpp, Markus Doepfert, Michel Zade + |
| Contact email | sebastian.lumpp@tum.de + |
| Contact persons | Sebastian Dirk Lumpp + |
| Data availability | all + |
| Deterministic | perfect forecast, deterministic, stochastic + |
| Full Model Name | local energy market laboratory + |
| Is suited for many scenarios | false + |
| License | GNU General Public License version 3.0 (GPL-3.0) + |
| Math modeltype | Simulation + and Agent-based + |
| Math modeltype shortdesc | Agents: intertemporal convex optimization
Markets: (iterative) double-sided auctions, p2p clearing
Forecasting: naive, deterministic forecasting, neural networks + |
| Model class | agent-based simulation + |
| Model source public | true + |
| Modelling software | Python, Pyomo + |
| Open future | false + |
| Open source licensed | true + |
| Processing software | PostgreSQL, Ethereum + |
| Sectors | local energy markets + |
| Source download | https://github.com/tum-ewk/lemlab + |
| Technologies | Renewables +, Conventional Generation + and CHP + |
| Text description | An open-source tool for the agent-based de … An open-source tool for the agent-based development and testing of local energy market applications. lemlab allows the user to simulate a LEM using a full agent-based modelling (ABM) in either simulation (SIM) or real-time (RTS) modes. This allows the rapid testing of algorithms as well as the real-time integration of hardware and software components.ation of hardware and software components. |
| Website | https://github.com/tum-ewk/lemlab + |
