In this paper, we propose a novel approach that makes use of a GPT model and of prompt engineering to build a proper input to GPT, given a domestic energy dataset. Specifically, given a residential energy consumption dataset, we ask a GPT model - in order to reduce the cost of energy - for planning the timing usage of house appliances, while preserving the same utilization of each appliance on a daily basis. To the best of our knowledge, this is the first attempt to schedule appliances usage taking advantage of the planning ability of a GPT model. Thanks to this preliminary study, we highlight interesting results to be further investigated and enabling certain room for improvements in this domain.

GPT Prompt Engineering for Scheduling Appliances Usage for Energy Cost Optimization

Siino M.
Primo
;
2024-01-01

Abstract

In this paper, we propose a novel approach that makes use of a GPT model and of prompt engineering to build a proper input to GPT, given a domestic energy dataset. Specifically, given a residential energy consumption dataset, we ask a GPT model - in order to reduce the cost of energy - for planning the timing usage of house appliances, while preserving the same utilization of each appliance on a daily basis. To the best of our knowledge, this is the first attempt to schedule appliances usage taking advantage of the planning ability of a GPT model. Thanks to this preliminary study, we highlight interesting results to be further investigated and enabling certain room for improvements in this domain.
2024
domestic appliances
energy cost
GPT
LLMs
Mistral 7B
scheduling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/650269
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