Power Usage Estimation System for Grid Load Management
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Solution Overview
Problem
The increasing demand for power consumption approaches the limit of power generation capacity, leading to potential power outages and disruptions, and increasing generation capacity is expensive, necessitating a method to decrease consumption without adverse effects.
Innovation Solution
A system and method for estimating the effects of a request to change power usage by receiving device and user behavior data, estimating the impact on the power grid, and determining whether to send a request for reduced power consumption using various communication protocols, allowing for intelligent reduction in power usage through either directive or objective models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If power generation capacity is increased to meet growing demand, then power supply reliability is improved, but infrastructure cost increases
Solution Approach 1:
The system performs preliminary actions by predicting future power consumption before peak demand occurs. It analyzes historical usage patterns, weather forecasts, and scheduled events to anticipate power needs, allowing utility operators to prepare appropriate supply levels in advance, thereby maintaining reliability without requiring excessive generation capacity infrastructure
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual power consumption against predictions and adjusting forecasts in real-time. This feedback loop enables dynamic optimization of power generation scheduling, ensuring supply matches actual demand patterns while minimizing the need for oversized infrastructure capacity
2Reliability
If power consumption is decreased to avoid outages, then power supply stability is improved, but user convenience deteriorates
Solution Approach 1:
The system applies local quality by implementing differentiated power management strategies for different devices and locations based on user preferences and device criticality. Non-critical devices may have consumption reduced during peak periods, while critical devices maintain normal operation, thereby preserving user convenience for essential functions while achieving overall demand reduction
Solution Approach 2:
The system performs preliminary actions by pre-cooling or pre-heating spaces, pre-charging batteries, or pre-scheduling device operations during off-peak hours based on predicted peak demand periods. This allows power consumption to be shifted to off-peak times, maintaining user comfort and convenience while reducing peak demand stress on the power grid
Data Source
AI summary
Systems and methods for estimating the effects of a request to change power usage are described. Device data about one or more devices may be received. User behavior data about past and anticipated user behavior may be received. Effects of a request to change power usage on a power grid may be estimated using the device data and the user behavior data. Whether to send the request to change power usage may be determined based on the estimated effects.