Quoted from: https://www.usensys.org/docs/usensys-info/ 

United States Energy SYStem (USENSYS) model is flexible, scalable, open source energy system optimization model for US, based on energyRt package. The current state of the model, which is in development, covers electric power sector and has 49 regions (48 lower states and Washington DC), and two time-resolution versions:

• renewables balancing version with 1 year and 8760 hours, 49 regions;
• electric power system transition version with 1-300 sub-annual slices and 50-100 years of horizon.

The renewables balancing version is currently applied to evaluate wind and solar energy potential and electric power system structure based on historic weather data (40 years of NASA’s data, MERRA-2 project). The main features of the UNENSYS model and the energyRt software:

• Optimization of the full year (vs. sampling); the model’s code has been confirmed to be efficient enough to optimize energy systems with 50 regions and 100 endogenous routes for 8760 hours at once (without representative days sampling). This feature allows evaluate the optimal allocation or capacities, especially requirements for storage (intraday and seasonal) and long-distance grid more accurately.
• Endogenous bi-directional trade routes (rare feature in capacity optimization models).
• Flexible, sector independent definition of technologies and storages.
• Special “weather” classes to explicitly model intermittency of renewables.
• Flexible representation of demand for electricity (endogenous spatial location, time-shift).

Energy systems modeling R-toolbox (energyRt) is a reference energy system (RES) modeling software with R interface. The goal of the software is to minimize time of developing RES models and process results. Besides its primary purpose, the statistics, R language is known for its leading capacities in data handling and graphical representation, including GIS. Data preparation (fetching, validation and cleaning, aggregation and conversion) is a necessary and time-consuming step in energy modeling. Processing modeling results is another step of working with data, generating imagery, tables and reports. The energyRt package allows to combine all the steps from data preparation to a model design, solving, and processing the results without leaving R. The code of the model itself is formulated in several languages and can be solved with one of them: GAMS, GLPK, Julia (dev., testing), and Python (dev., testing). All of the languages and software except GAMS are open source. GAMS is a commercial option which provides better time performance.
The energyRt package provides a set of functions and methods to design RES models with multiple regions, different time horizon and sub-annual time resolution. The only limits on those dimensions is a computer memory and the ability of a solver to find the solution for the problem. The spatial and time resolutions, as well as included technologies can be easily swapped to get different aggregation of the model for different tasks. And since the data processing step is integrated with the model itself, the script can be designed to be independent of the model structure and aggregation. The package provides an opportunity to design technologies with multiple input and output commodities (substitutable or complementary, the main or auxiliary), storage technologies, endogenous or exogenous interregional or global trade, exogenous or endogenous demand.