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| | + | {{Model |
| | + | |Full_Model_Name=Simulator of System of Electrical Energy. |
| | + | |Acronym=SimSEE |
| | + | |author_institution=Institute of Electrical Engineering |
| | + | |authors=Ruben Chaer, Pablo Alfaro y Gonzalo Casaravilla |
| | + | |contact_persons=Ruben Chaer |
| | + | |contact_email=rchaer@simsee.org |
| | + | |website=https://simsee.org/index_en.html |
| | + | |source_download=https://sourceforge.net/projects/simsee/ |
| | + | |logo=Logosimseesinmarco 02.jpg |
| | + | |text_description=SimSEE is a platform for the Simulation of Systems of Electrical Energy. As such, it allows creating simulators tailored to a generation system, simply by adding the different types of Actors (thermal, wind, solar and hydraulic generators, demand, interconnections, etc.) to a Play-Room (simulation environment). These Actors behave in the Room according to their type. |
| | + | |
| | + | It is 100% programmed with Object Oriented technology which makes it easy to incorporate new models (types of Actors). |
| | + | |
| | + | To simulate the optimal operation of an Electric Power System, SimSEE solves a Dynamic Stochastic Programming problem, obtaining as a result an Optimal Operation Policy. Using this Policy, different realizations of the stochastic processes (chronicles or possible histories of the future of the system) are simulated. |
| | + | |
| | + | Since 2010, SimSEE has become the tool commonly used in Uruguay to simulate the operation of the energy system, mainly due to the good stochastic models developed for the modeling of wind and solar energy. |
| | + | These models achieve an adequate representation, both in the long term (Investment Planning) and in the short term (System Operation). |
| | + | |Primary outputs=Optimal energy dispatch of the energy resources. |
| | + | |Support=https://simsee.org/contacto_en.php |
| | + | |Framework=freepascal |
| | + | |User documentation=https://simsee.org/simsee/verdoc/vol1_en.php |
| | + | |Code documentation=https://sourceforge.net/p/simsee/src/HEAD/tree/ |
| | + | |Source of funding=academic projects |
| | + | |Number of developers=more than 10 |
| | + | |Number of users=more than 100 |
| | + | |open_source_licensed=Yes |
| | + | |license=GNU General Public License version 3.0 (GPL-3.0) |
| | + | |model_source_public=Yes |
| | + | |Link to source=https://sourceforge.net/p/simsee/src/HEAD/tree/ |
| | + | |data_availability=some |
| | + | |open_future=No |
| | + | |modelling_software=freepascal |
| | + | |processing_software=freepascal |
| | + | |GUI=Yes |
| | + | |model_class=Optimal energy dispatch |
| | + | |sectors=Electricity Market, |
| | + | |technologies=Renewables, Conventional Generation, CHP |
| | + | |Demand sectors=Industry |
| | + | |Transfer (Electricity)=Transmission |
| | + | |Storage (Electricity)=Battery, PHS |
| | + | |Storage (Gas)=No |
| | + | |Storage (Heat)=No |
| | + | |decisions=dispatch, investment |
| | + | |Changes in efficiency=Can be affected by the temperature |
| | + | |timeresolution=Hour |
| | + | |network_coverage=net transfer capacities |
| | + | |Observation period=Less than one month, Less than one year, More than one year |
| | + | |Additional dimensions (Ecological)=compute greenhouse emissions |
| | + | |Additional dimensions (Economical)=sopo prices, marginal costs, time-series |
| | + | |math_modeltype=Optimization, Simulation |
| | + | |math_modeltype_shortdesc=Optimal Stochastic Dynamic Programming solver for computation of the operational Policy and a Monte Carlo style simulator of the system using the computed Policy |
| | + | |math_objective=minimization of the future operational cost. |
| | + | |deterministic=stochastic, hydro inflows, wind velocity, solar radiation, temerature an Demand. |
| | + | |is_suited_for_many_scenarios=Yes |
| | + | |number_of_variables=1000 |
| | + | |montecarlo=Yes |
| | + | |computation_time_minutes=15 |
| | + | |computation_time_hardware=desktop with 8 cpus |
| | + | |computation_time_comments=the 15 min with 8 cpus is for a optimizaion/simulation of the uruguayan system over 10 years horizon with a daily time-step |
| | + | |citation_references= Chaer, R. (2008.). Simulación de sistemas de energía eléctrica. Tesis de maestría. Universidad de la Republica (Uruguay). Facultad de Ingenieria. |
| | + | |report_references=Chaer R. (2018) Handling the Intermittence of Wind and Solar Energy Resources, from Planning to Operation. Uruguay’s Success. September 2018 Conference: 36th USAEE/IAEE NORTH AMERICAN CONFERENCEAt: Washington DC USA |
| | + | |Larger scale usage=long term investment planning (typically 20 years) |
| | + | |Model validation=The model was tested using a set of configurations of the Uruguayan electrical system. For example, conditions of drought or abundance of the hydroelectric resource and starting the simulations with the lakes full or empty and comparing the results with the result of the expert operators. |
| | + | |Comment on model validation=Once this series of tests was carried out, the model began to be used for the programming of the operation on all time scales by the ISO of Uruguay |
| | + | |Specific properties=It uses its own stochastic modeling technique which facilitates the assimilation of forecasts |
| | + | |Model input file format=No |
| | + | |Model file format=No |
| | + | |Model output file format=No |
| | + | }} |
| | #REDIRECT [[SimSES]] | | #REDIRECT [[SimSES]] |
Chaer, R. (2008.). Simulación de sistemas de energía eléctrica. Tesis de maestría. Universidad de la Republica (Uruguay). Facultad de Ingenieria.
Chaer R. (2018) Handling the Intermittence of Wind and Solar Energy Resources, from Planning to Operation. Uruguay’s Success. September 2018 Conference: 36th USAEE/IAEE NORTH AMERICAN CONFERENCEAt: Washington DC USA
