Supervisor: Sina Hajikazemi
Earliest start: immediately
Type: Master Thesis
This master's thesis explores the potential of harnessing Large Language Models (LLMs) to transform user interactions with energy system models, with a focus on developing a Textual User Interface (TUI). The study investigates the interconnection between LLMs and Application Programming Interfaces (APIs) in order to facilitate a more intuitive and user-friendly means of engaging with complex energy system models. The research aims to bridge the gap between energy system model developers, decision-makers, and the public by providing a user-friendly TUI that enhances transparency and decision-making processes.
1. Examine the emerging role of LLMs in the future of user interfaces and their potential to transition from graphical to textual interfaces.
2. Develop a TUI that interfaces with Energy System Models (ESMs) via well-documented APIs.
1. Investigate and select appropriate tools and frameworks for integrating LLMs with APIs, drawing on existing examples and technologies, such as LangChain's Python Library for Use Cases with APIs (https://python.langchain.com/docs/use_cases/apis) and OpenAI's GPT Function Calling (https://platform.openai.com/docs/guides/gpt/function-calling).
2. Define use cases and questions that the LLM-based TUI can address to enhance understanding and decision-making in the context of energy system models.
3. Create well-documented API specifications using standard formats (e.g., OpenAPI) for a reputable energy planning model, such as "Open and Compact Model for the German Energy Transition," (available on GitHub: https://github.com/OCGModel/OCGModel).
4. Establish a functional connection between the API and LLM to develop a working prototype of the LLM-based TUI.
Significance and Contributions:
This research contributes to the evolving field of human-computer interaction by demonstrating how Large Language Models (LLMs) can be integrated with energy system models, providing an innovative approach to user interfaces in the context of energy planning and governance. The development of a TUI for ESMs enhances transparency and public engagement, while also encouraging model developers to improve precision and openness in their assumptions and methods.
By addressing these objectives, this master's thesis aims to facilitate better-informed decision-making in the energy sector, foster transparency in energy model development, and contribute to the broader discourse on the role of LLMs in future user interfaces and decision support systems.
Keywords: Large Language Models (LLMs), Textual User Interface (TUI), Energy System Models (ESMs), Application Programming Interfaces (APIs), User Experience, Transparency, Decision Support, Energy Planning, Human-Computer Interaction