Possibly in-house models (PiHM)

Name Possibly in-house models
Acronym PiHM
Methodical Focus -
Institution(s) Aalto University
Author(s) (institution, working field, active time period)
Current contact person Aira Hast
Contact (e-mail) aira.hast@aalto.fi
Primary Purpose Simulates the hourly district heat production in an open district heating market
Primary Outputs Marginal cost of heat production, which plants are running, produced heat by plant, heat production cost by plant
Support / Community / Forum
Link to User Documentation
Link to Developer/Code Documentation
Documentation quality expandable
Source of funding
Number of devolopers less than 10
Number of users -
Open Source
Planned to open up in the future
Modelling software Matlab
Internal data processing software Matlab
External optimizer
Additional software
Citation reference http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7216654&filter=AND%28p_Publication_Number:7169452%29
Citation DOI
Please list references to reports and studies which were produced using the model
Example research questions
Larger scale usage
Model validation -
Example research questions
further properties
Model specific properties
Modeled energy sectors (final energy) -
Modeled demand sectors -
Modelled energy carriers (primary energy carrier)
Gas -
Liquids -
Solid -
Renewables -
Modeled technologies: components for generation or conversion
Renewables -
Conventional -
Modeled technologies: components for transfer, infrastructure or grid
Electricity -
Gas -
Heat -
Properties electrical grid -
Modeled technologies: components for storage -
User behaviour and demand side management
Changes in efficiency
Market models -
Geographical coverage
Geographic (spatial) resolution One DH system
Time resolution hour
Comment on geographic (spatial) resolution
Observation period -
Additional dimensions (sector) -
Model class (optimisation) -
Model class (simulation) -
Short description of mathematical model class
Mathematical objective costs
Approach to uncertainty -
Suited for many scenarios / monte-carlo
typical computation time less than an hour
Typical computation hardware RAM, CPU
Technical data anchored in the model
Model file format .m
Input data file format text
Output data file format .csv
Integration with other models
Integration of other models

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