Demand Response Load Estimation via Energy Rebound Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Power utilities face challenges in managing peak energy demand effectively, as existing systems lack accurate methods for estimating energy usage changes during demand events, leading to inefficiencies in load reduction and increased costs.
Innovation Solution
A system and method for estimating energy usage changes associated with demand events, involving determining energy potential changes, pre- and post-event energy rebounds, and creating an energy change profile using advanced metering infrastructure, processors, and algorithms to manage energy consumption and peak demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If utilities manipulate energy usage to avoid peak load conditions, then peak demand management is improved, but accurate estimation of energy usage changes during demand events is insufficient
Solution Approach 1:
The system performs preliminary estimation of energy usage patterns during demand events by analyzing historical data and device characteristics before implementing demand response actions. This allows utilities to predict energy usage changes and optimize peak demand management strategies in advance
Solution Approach 2:
The system continuously monitors actual energy usage during and after demand events, compares it with estimated patterns, and uses this feedback to refine future estimations. The energy change profile generation incorporates both pre-event predictions and post-event actual measurements to improve accuracy over time
2Productivity
If utilities implement demand response programs, then load reduction is achieved, but energy rebound effects increase overall energy consumption
Solution Approach 1:
The system estimates pre-demand event energy rebound by analyzing historical usage patterns before demand events. This preliminary estimation allows utilities to account for anticipated rebound effects when designing demand response programs, adjusting strategies to minimize overall energy consumption increases
Solution Approach 2:
The system monitors post-demand event energy consumption to measure actual rebound effects. This feedback is incorporated into the energy change profile and used to refine future demand response strategies, helping to optimize load reduction while minimizing rebound-related energy losses
3Measurement precision
If utilities track detailed energy usage patterns, then demand event analysis is improved, but system complexity increases
Solution Approach 1:
The system segments energy usage analysis by device type, location, and time period, processing different data segments through specialized algorithms. This segmentation allows detailed analysis of demand events while managing system complexity through modular data handling and focused processing for each segment
Data Source
AI summary
Certain embodiments of the invention may include systems, methods, and apparatus for estimating demand response load change. According to an example embodiment of the invention, a method is provided for estimating energy usage change associated with a demand event. The method may include determining energy potential change during a demand event for one or more devices associated with a location; estimating energy usage patterns for the location over predefined time periods before and after the demand event; determining pre-demand event and post-demand event energy rebounds based at least in part on the estimated energy usage patterns; determining an energy change profile associated with the location based at least in part on the determined energy potential change, and the pre-demand event and post-demand event energy rebounds.