The STorage RequirEmEnts and dispatch Model (STREEM) is a high resolution energy model, which (i) simulates the operation of electricity storage systems, aiming at improving the matching of renewable energy generation and electricity demand, and (ii) identifies the storage capacity requirements of a region, towards maximization of renewable energy integration.
Key Features
The novelty of STREEM lies in its capability of simulating multiple storage technologies with simple parameterization of its input parameters. That way, it is capable of simulating the simultaneous operation of short-term (e.g., batteries) and long-term storage (e.g., pumped hydro storage), applying priority rules. Furthermore, STREEM can provide economic outputs of examined renewable plus storage configurations, such as the levelized cost of energy of residential PV generation coupled with the appropriate level of storage capacity, or the levelized cost of storage of multiple battery storage technologies. The applicability of STREEM ranges from local energy communities, to national or international scale.
STREEM is developed using the Python language.
Main Functionalities
- Storage dispatch algorithm: The storage dispatch algorithm of STREEM runs in an hourly resolution, and uses storage to transfer RES generation to the periods more needed (i.e., when RES generation is low and demand is high). If multiple storage technologies are used, the algorithm prioritizes short-term storage (e.g., battery energy storage systems) and uses the medium-/long-term storage technologies (e.g., pumped-hydro storage) after the short-term options have reached their storage capacity or depth-of-discharge. Excess generation that cannot be stored is curtailed. The hourly demand that can not be met either by directly feeding RES electricity to the grid or by discharging the storage systems, is saved as a residual demand timeseries. The residual demand timeseries that results from the storage dispatch algorithm can be fed in a unit-commitment and economic dispatch model, such as BSAM, to calculate the optimal dispatch of thermal units, imports, or other dispatchable units, for the demand not covered by RES.
- Required storage capacity algorithm: The algorithm investigating the storage capacity requirements, identifies the correlation between storage volume and curtailment decrease. It applies an iterative process of calculating the instantaneous slope of curtailment decrease with storage capacity increase. With this process, the actual curve of storage/curtailment correlation is approximated, regardless of the storage technology or specifications simulated, while ensuring fast convergence. Furthermore, with this process, storage capacity overshooting, which would lead to underutilised storage systems, is avoided.
Impact
The STREEM model has been developed and applied in the context of the following projects funded by the European Commission:
STREEM has been applied in the national context of Greece, in order to explore how much storage is needed in order to minimize electricity curtailment, under different combinations of wind turbines and solar photovoltaics capacity combinations. Apart from storage requirements, with the analysis with STREEM we were able to identify which renewables plus storage combinations perform best in terms of cost of renewable energy integration.
At the municipal level, STREEM has been applied to explore the storage requirements to supply a former lignite region with 90% PV-generated electricity. The analysis was made both in island mode and interconnected with the grid, highlighting the importance of battery-grid cooperation in the proper sizing of battery energy storage systems.
Scientific Articles and Other Relevant Publications
- Michas, S., & Flamos, A. (2023). Are there preferable capacity combinations of renewables and storage? Exploratory quantifications along various technology deployment pathways. Energy Policy, 174, 113455. https://doi.org/10.1016/j.enpol.2023.113455
- Michas, S., & Flamos, A.. Least-cost or sustainable? Exploring power sector transition pathways. (forthcoming)
Video Presentation
A study performed with STREEM, soft-linked with the AIM and BSAM models, is presented in the video below.