Welcome to the PREP-SHOT Documentation¶
- Author
Zhanwei Liu (Mr), <liuzhanwei@u.nus.edu> and Xiaogang He (Dr), <hexg@nus.edu.sg>
- Organization
- Version
latest
- Date
Oct 15, 2023
- Copyright
The model code is licensed under the GNU General Public License 3.0. This documentation is licensed under a Creative Commons Attribution 4.0 International license.
Overview¶
PREP-SHOT (Pathways for Renewable Energy Planning coupling Short-term Hydropower OperaTion) is a transparent, modular, and open-source energy expansion model hosted on GitHub. Offering advanced solutions for multi-scale, intertemporal, and cost-effective expansion of energy systems and transmission lines. PREP-SHOT was orginally developed to study the nexus between water and energy systems. The development started in 2021, and in 2022, it was released as an open-source model.
The model sets itself apart from existing energy expansion models through its deeper consideration of hydropower processes. While models such as urbs might treat hydropower as fixed processes, and others like GenX and PLEXOS may not fully capture the dynamic nature of water heads or consolidate multiple hydropower stations into a single unit, PREP-SHOT is uniquely designed to address these oversights.
Our model explicitly considers the plant-level water head dynamics (i.e., time-varying water head and storage) and the system-level network topology of all hydropower stations within a regional grid. This results in a more accurate reflection of the multi-scale dynamic feedbacks between hydropower operation and energy system expansion. Furthermore, it enables the realistic simulation of the magnitude and spatial-temporal variability of hydropower output, particularly in regions with a large number of cascade hydropower stations.
With PREP-SHOT, we aim to answer key questions related to the future of energy planning and utilization:
How can we effectively plan an energy portfolio and new transmission capacity under deep uncertainty?
How can we quantify the impacts of variable hydropower on the generation and capacity of future energy portfolios?
How It Works¶
![overview of PREP-SHOT](_images/overview.png)
Source: Liu and He (2023).
Key Features¶
PREP-SHOT is an optimization model based on linear programming for energy systems with multiple zones.
It aims to minimize costs while meeting the given demand time series.
By default, it operates on hourly-spaced time steps, but this can be adjusted.
The input data is in Excel format, while output data is generated in a NetCDF format using
Xarray
.It supports multiple types of solvers such as Gurobi, CPLEX, MOSEK, and GLPK via Pyomo.
It allows input of multiple scenarios for specific parameters.
As a pure Python program, it benefits from the use of
pandas
andXarray
, simplifying complex data analysis and promoting extensibility.
Offline documentation¶
To browse the documentation offline, you can download an PDF copy for offline reading (Synchronize updates with online documentation).