CROCS: A Two-Stage Clustering Framework for Behaviour-Centric Consumer Segmentation with Smart Meter Data
arXiv:2601.10494v2 Announce Type: replace-cross Abstract: With grid operators confronting rising uncertainty from renewable integration and a broader push toward electrification, Demand-Side Management (DSM) -- particularly Demand Response (DR) -- has attracted significant attention as a cost-effective mechanism for balancing modern electricity systems. Unprecedented volumes of consumption data from a continuing global deployment of smart meters enable consumer segmentation based on real usage behaviours, promising to inform the design of more effective DSM and DR programs. However, existing c
The increasing integration of renewables and the push for electrification are creating urgency for more effective demand-side management in electricity grids.
This research outlines a methodology that can significantly improve the efficiency and stability of modern electricity systems by enabling more precise and behavior-centric consumer segmentation.
The ability to categorize consumers based on real usage behaviors allows for the design of more targeted and effective Demand Response programs, moving beyond generic incentives.
- · Grid operators
- · Smart meter manufacturers
- · Energy analytics platforms
- · Consumers (through more stable grids)
- · Inefficient traditional energy providers
- · Outdated demand-side management approaches
Improved grid stability and reduced reliance on peak power plants due to better demand response.
Potential for new business models focusing on personalized energy services and dynamic pricing based on consumption patterns.
Accelerated adoption of smart home technologies and energy management systems as consumers engage more actively with their energy profiles.
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Read at arXiv cs.LG