The paper investigates how residential loads in India contribute to grid peak load and how to manage such peaks. Algorithms that process smart meter data from residential loads and compute attributes that capture their contribution to the system peak are devised and demonstrated in the paper. Specifically, a distribution system is considered based on a study on households in Pune, India. To enhance the household dataset for analysis, a synthetic data generation technique is employed. The algorithms developed here are applied to this system to showcase their capabilities. Results show how simple attributes such as peak amplitude and peak duration can extract sufficient information to ensure households that contribute to system peak are appropriately identified. Moreover, these attributes offer insights into appliance ownership, supporting the development of effective DR programs. A demonstration of how shifting of individual peaks can significantly impact system peak is also provided. The results lay the foundation for designing meaningful DR programs leveraging the smart meter data.
No takes yet. Share an insight, caveat, or question.
Vibhute et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: