Andrew Lyden: Created page with "{{Model |Full_Model_Name=Python for Local Energy Systems Analysis |Acronym=PyLESA |author_institution=University of Strathclyde |authors=Andrew Lyden |contact_persons=Andrew L..."

2020-08-13T09:42:59Z

Created page with "{{Model |Full_Model_Name=Python for Local Energy Systems Analysis |Acronym=PyLESA |author_institution=University of Strathclyde |authors=Andrew Lyden |contact_persons=Andrew L..."

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{{Model
|Full_Model_Name=Python for Local Energy Systems Analysis
|Acronym=PyLESA
|author_institution=University of Strathclyde
|authors=Andrew Lyden
|contact_persons=Andrew Lyden
|contact_email=andrew.lyden@strath.ac.uk
|source_download=https://github.com/andrewlyden/PyLESA
|text_description=PyLESA is an open source tool capable of modelling local energy systems containing both electrical and thermal technologies. It was developed with the aim of aiding the design of local energy systems. The focus of the tool is on modelling systems with heat pumps and thermal storage alongside time-of-use electricity tariffs and predictive control strategies. It is anticipated that the tool provides a framework for future development including electrical battery studies and participation in grid balancing mechanisms.

This tool was developed as part of a PhD, "Modelling and Design of Local Energy Systems Incorporating Heat Pumps, Thermal Storage, Future Tariffs, and Model Predictive Control " by Andrew Lyden.
|Primary purpose=Design of local energy systems with heat pumps, thermal storage and MPC
|Primary outputs=Technical; economic
|open_source_licensed=Yes
|license=MIT license (MIT)
|model_source_public=Yes
|Link to source=https://github.com/andrewlyden/PyLESA
|data_availability=some
|open_future=No
|modelling_software=Python
|processing_software=Python
|External optimizer=APOPT
|Primary purpose=Design of local energy systems with heat pumps, thermal storage and MPC
|GUI=Yes
|model_class=Local energy systems
|sectors=electricity, heat
|technologies=Renewables, Conventional Generation
|Demand sectors=Households
|Energy carriers (Renewable)=Sun, Wind
|Transfer (Electricity)=Distribution
|Transfer (Heat)=Distribution, Transmission
|Storage (Electricity)=Battery
|Storage (Gas)=No
|Storage (Heat)=Yes
|Market models=Variety of exisitng and future electricity tariffs
|decisions=dispatch
|Changes in efficiency=State
|georesolution=Local/Community/District
|timeresolution=Hour
|network_coverage=AC load flow, DC load flow
|Observation period=More than one year
|math_modeltype=Simulation
|math_objective=Minimization of operational costs
|deterministic=perfect foresight
|is_suited_for_many_scenarios=No
|montecarlo=No
|computation_time_minutes=Minutes to Hours
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

PyLESA - Revision history

Andrew Lyden: Created page with "{{Model |Full_Model_Name=Python for Local Energy Systems Analysis |Acronym=PyLESA |author_institution=University of Strathclyde |authors=Andrew Lyden |contact_persons=Andrew L..."