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| | |author_institution=Université de Liège, Politecnico di Milano | | |author_institution=Université de Liège, Politecnico di Milano |
| | |authors=Sergio Balderrama, Sylvain Quoilin, Francesco Lombardi, Giulia Guidicini, Lorenzo Rinaldi, Emanuela Colombo, Riccardo Mereu, Nicolò Stevanato, Ivan Sangiorgio, Gianluca Pellecchia | | |authors=Sergio Balderrama, Sylvain Quoilin, Francesco Lombardi, Giulia Guidicini, Lorenzo Rinaldi, Emanuela Colombo, Riccardo Mereu, Nicolò Stevanato, Ivan Sangiorgio, Gianluca Pellecchia |
| − | |contact_persons=Gianluca Pellecchia | + | |contact_persons=gianluca.pellecchia@polimi.it |
| − | |contact_email=gianluca.pellecchia@ | + | |contact_email=gianluca.pellecchia@polimi.it |
| | |website=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM | | |website=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM |
| | |source_download=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM.git | | |source_download=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM.git |
| | |logo=MGpy.png | | |logo=MGpy.png |
| | |text_description=The MicroGridsPy model main objective is to provide an open-source alternative to the problem of sizing and dispatch of energy in micro-grids in isolated places. It’s written in python(pyomo) and use excel and text files as input and output data handling and visualisation. | | |text_description=The MicroGridsPy model main objective is to provide an open-source alternative to the problem of sizing and dispatch of energy in micro-grids in isolated places. It’s written in python(pyomo) and use excel and text files as input and output data handling and visualisation. |
| − | |open_source_licensed=No | + | |Primary purpose=Sizing and dispatch of energy in micro-grids in isolated places |
| − | |model_source_public=No | + | |Primary outputs=Optimal sizing of PV panels, wind turbines, other renewable technologies, back-up genset and electrochemical storage system for least cost electricity supply in rural isolated areas; Optimal dispatch from the identified supply systems; Possibility to optimize on NPC or operation costs; LCOE evaluation for the identified system. |
| | + | |User documentation=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM/blob/MicroGridsPy-2.0/README.md |
| | + | |Code documentation=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM/blob/MicroGridsPy-2.0/Code/_README.txt |
| | + | |open_source_licensed=Yes |
| | + | |license=European Union Public Licence Version 1.1 (EUPL-1.1) |
| | + | |model_source_public=Yes |
| | + | |Link to source=https://github.com/SESAM-Polimi/MicroGridsPy-SESAM |
| | + | |data_availability=all |
| | |open_future=No | | |open_future=No |
| | + | |modelling_software=Python (Pyomo) |
| | + | |processing_software=Excel |
| | + | |External optimizer=Gurobi, CPLEX, cbc, glpk |
| | + | |Primary purpose=Sizing and dispatch of energy in micro-grids in isolated places |
| | |GUI=No | | |GUI=No |
| | + | |model_class=Energy Modeling Framework, energy system optimization model |
| | + | |sectors=Electric power, micro-grids design |
| | + | |technologies=Renewables, Conventional Generation |
| | + | |Demand sectors=Households, Industry, Commercial sector |
| | + | |Energy carrier (Liquid)=Diesel |
| | + | |Energy carriers (Renewable)=Sun, Wind |
| | + | |Transfer (Electricity)=Distribution |
| | + | |Storage (Electricity)=Battery |
| | |Storage (Gas)=No | | |Storage (Gas)=No |
| | |Storage (Heat)=No | | |Storage (Heat)=No |
| − | |is_suited_for_many_scenarios=No | + | |User behaviour=Archetypes |
| | + | |decisions=dispatch, investment |
| | + | |Changes in efficiency=No |
| | + | |georesolution=Village-scale |
| | + | |timeresolution=Hour |
| | + | |Observation period=More than one year |
| | + | |Additional dimensions (Ecological)=Greenhouse gas emissions |
| | + | |math_modeltype=Optimization |
| | + | |math_modeltype_shortdesc=The model is based on two-stage stochastic optimisation, where the main |
| | + | optimization variables are divided into first-stage variables (rated capacities of each |
| | + | energy source) and second-stage variables (energy flows from the different |
| | + | components), to deal with the parametric uncertainty, while LP or MILP |
| | + | formulation can be used to tackle the structural uncertainty mainly related to the |
| | + | modelling of non-linear behaviour. The optimization is performed in Python using |
| | + | Pyomo Library. Energy balance, VRES generation constrains, Battery |
| | + | charge/discharge constrains, Genset generation constrains are the main constrains |
| | + | of the model while regarding the objective function, it’s possible switch between |
| | + | NPC and Operation Cost minimization. |
| | + | |math_objective=Single objective optimization: NPC or operation costs |
| | + | |deterministic=Two-stage stochastic optimization |
| | + | |is_suited_for_many_scenarios=Yes |
| | |montecarlo=No | | |montecarlo=No |
| | + | |citation_references=Sergio Balderrama, Francesco Lombardi, Fabio Riva, Walter Canedo, Emanuela Colombo, Sylvain Quoilin, A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community, Energy (2019), 188, |
| | + | |citation_doi=https://doi.org/10.1016/j.energy.2019.116073 |
| | + | |report_references=-Sergio Balderrama, Francesco Lombardi, Fabio Riva, Walter Canedo, Emanuela Colombo, Sylvain Quoilin, A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community, Energy (2019), 188, https://doi.org/10.1016/j.energy.2019.116073 |
| | + | -Nicolò Stevanato, Francesco Lombardi, Emanuela Colombo, Sergio Balderrama, Sylvain Quoilin, Two-Stage Stochastic Sizing of a Rural Micro-Grid Based on Stochastic Load Generation, 2019 IEEE Milan PowerTech, Milan, Italy, 2019, pp. 1-6. https://doi.org/10.1109/PTC.2019.8810571 |
| | + | -Nicolò Stevanato, Francesco Lombardi, Giulia Guidicini, Lorenzo Rinaldi, Sergio Balderrama, Matija Pavičević, Sylvain Quoilin, Emanuela Colombo, Long-term sizing of rural microgrids: Accounting for load evolution through multi-step investment plan and stochastic optimization, Energy for Sustainable Development (2020), 58, pp. 16-29, https://doi.org/10.1016/j.esd.2020.07.002 |
| | + | -Nicolò Stevanato, Lorenzo Rinaldi, Stefano Pistolese, Sergio Balderrama, Sylvain Quoilin, Emanuela Colombo, Modeling of a Village-Scale Multi-Energy System for the Integrated Supply of Electric and Thermal Energy, Applied Sciences (2020), https://doi.org/10.3390/app10217445 |
| | + | |
| | + | |
| | + | |example_research_questions=-Long-term sizing of rural microgrids |
| | + | -Load evolution |
| | |Model input file format=No | | |Model input file format=No |
| | |Model file format=No | | |Model file format=No |
| | |Model output file format=No | | |Model output file format=No |
| | }} | | }} |
Sergio Balderrama, Francesco Lombardi, Fabio Riva, Walter Canedo, Emanuela Colombo, Sylvain Quoilin, A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community, Energy (2019), 188,
https://dx.doi.org/https://doi.org/10.1016/j.energy.2019.116073
-Sergio Balderrama, Francesco Lombardi, Fabio Riva, Walter Canedo, Emanuela Colombo, Sylvain Quoilin, A two-stage linear programming optimization framework for isolated hybrid microgrids in a rural context: The case study of the “El Espino” community, Energy (2019), 188, https://doi.org/10.1016/j.energy.2019.116073
-Nicolò Stevanato, Francesco Lombardi, Emanuela Colombo, Sergio Balderrama, Sylvain Quoilin, Two-Stage Stochastic Sizing of a Rural Micro-Grid Based on Stochastic Load Generation, 2019 IEEE Milan PowerTech, Milan, Italy, 2019, pp. 1-6. https://doi.org/10.1109/PTC.2019.8810571
-Nicolò Stevanato, Francesco Lombardi, Giulia Guidicini, Lorenzo Rinaldi, Sergio Balderrama, Matija Pavičević, Sylvain Quoilin, Emanuela Colombo, Long-term sizing of rural microgrids: Accounting for load evolution through multi-step investment plan and stochastic optimization, Energy for Sustainable Development (2020), 58, pp. 16-29, https://doi.org/10.1016/j.esd.2020.07.002
-Nicolò Stevanato, Lorenzo Rinaldi, Stefano Pistolese, Sergio Balderrama, Sylvain Quoilin, Emanuela Colombo, Modeling of a Village-Scale Multi-Energy System for the Integrated Supply of Electric and Thermal Energy, Applied Sciences (2020), https://doi.org/10.3390/app10217445
