QuESt 2.0 User Feedback

Already downloaded QuESt 2.0? Already using the tool and have feedback? Submit this form to share your thoughts.

See what other users have to say about QuESt 2.0:

Harvey Rambarath –
Seminole Tribe of Florida
Applications Used: QuESt Behind-The-Meter
Use:

Analyzing the monetary benefits of integrating energy storage systems with onsite photovoltaic (PV) installations, aiming to reduce electricity bills for large buildings.

Feedback:

“The results generated by the tool have enabled us to make informed decisions in specifying the energy storage system designs for our projects. The free access to QuESt 2.0 is particularly beneficial for budget-constrained communities. This accessibility supports our energy storage and microgrid development projects, promoting energy resilience and sustainability not only for our tribe but for many others.”


Hung Dinh Nguyen
Nanyang Technological University Singapore
Applications Used: QuESt GPT
Use:

Analyzing battery testing data

Feedback:

“QuESt was extremely useful and allowed my research team efficiently to characterize a large amount of testing data, which significantly streamlined the analysis process. The ability of QuESt GPT to interactively guide users through complex data sets is a testament to the sophisticated capabilities of QuESt 2.0.”


Reinaldo Tonkoski
Technical University of Munich
Applications Used: QuESt App Hub, QuESt Workspace, and QuESt GPT
Use:

Educational Resource

Feedback:

“The recent upgrade to QuESt v2.0 has further enhanced its capabilities, making it an indispensable tool for researchers, educators, and industry professionals alike. The three main components of QuESt v2.0—QuESt App Hub, QuESt Workspace, and QuESt GPT—collectively provide a comprehensive and integrated platform unparalleled in the open-source domain.


Tony Sparks
HVAC & Energy Efficiency
Applications Used: QuESt Behind-The-Meter
Use:

Reducing High Utility Peak Demand Charges

Feedback:

“The tool takes the many complex variables/data points pertaining to system size (kW), discharge duration (kWH), time frames, and respective utility schedules, and distills them into sortable tables that ultimately allow comprehensive comparison and payback analysis for various system configurations. Without this data-driven decision model, our system considerations would have been primarily guesswork.”