# 42: Understanding of Patterns in Electricity Usage and Market Data Towards Facilitating Demand Response with Dynamic Pricing
Project ID:
42
Team Members:
Devon Stapleton, Anjal Parikh, Syeda Hasan
Faculty Advisor(s):
Shouyi Wang
Department:
Industrial, Manufacturing & Systems Engineering
Project Type:
REU
Title:
Understanding of Patterns in Electricity Usage and Market Data Towards Facilitating Demand Response with Dynamic Pricing
Abstract:
The renewable energy revolution will substantially alter the future energy. With increasing penetration of stochastic renewable energies, power distributors must respond to an extremely dynamic, complex, and challenging real-time supply-demand balancing problem. A promising solution is demand response (DR) with time-varying electricity price signals. The REU team will work with high-resolution IOT electricity usage data from an actual Arlington, Texas, household, and Texas market price data from the Electric Reliability Council of Texas (ERCOT). Identified patterns in these data will inform the development of state transition modeling within a large-scale DR management optimization funded by NSF Award ECCS-1938895.