GCA-BULF: A Bottom-Up Framework for Short-Term Load Forecasting Using Grouped Critical Appliances
A novel framework named GCA-BULF has been introduced by researchers for short-term load forecasting (STLF), which takes a bottom-up approach to overcome the shortcomings of conventional top-down methods by concentrating on essential grouped appliances. STLF estimates electricity usage from minutes to days by analyzing historical data, temporal trends, and contextual elements. Although bottom-up techniques enhance precision through appliance-specific data, monitoring every device can be expensive, and many do not significantly influence overall load predictions. GCA-BULF focuses on critical appliances, thereby cutting costs while ensuring reliable forecasts. This framework aids in implementing peak-shifting strategies for time-of-use and tiered pricing, assisting consumers in reducing energy expenses and improving grid stability. The research can be found on arXiv with the identifier 2604.24766.
Key facts
- GCA-BULF is a bottom-up short-term load forecasting framework.
- It uses grouped critical appliances to reduce monitoring costs.
- STLF predicts electricity consumption over minutes to days.
- Traditional top-down methods struggle with complex consumption patterns.
- Time-of-use and tiered pricing encourage peak-shifting strategies.
- The framework aims to lower energy costs and enhance grid stability.
- The paper is published on arXiv with ID 2604.24766.
- The approach selectively monitors only high-power appliances.
Entities
Institutions
- arXiv