Demand Response System for Energy Grid Stability
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Solution Overview
Problem
Conventional energy grids face challenges in managing volatile energy demand from individual consumers, making it difficult to handle fluctuations in power consumption, and utility companies are hesitant to invest in upgrading technologies without assurance of improvement.
Innovation Solution
A computer-implemented method that sets a target power demand for consumers based on a reward table, adjusts actual power demand to reduce errors, and modifies the target demand when adjustments are not possible, using IoT devices and independent energy sources to stabilize energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If utility companies invest in upgrading technologies to handle volatile energy demand, then the ability to manage volatile demand improves, but the investment cost increases significantly
Solution Approach 1:
Instead of having the utility company invest in complex infrastructure to handle demand volatility, the patent inverts the approach by implementing demand response programs that incentivize consumers to actively manage and reduce their own demand. This shifts the burden from utility infrastructure upgrades to consumer-side behavioral changes, resolving the contradiction between reliability improvement and investment cost.
Solution Approach 2:
The patent enables consumers to self-manage their energy demand through automated demand response systems that adjust consumption based on grid conditions and incentive signals. This self-service approach eliminates the need for utility companies to invest in expensive infrastructure while still achieving volatile demand management, as consumers autonomously adjust their usage patterns.
2Loss of information
If conventional analytics are used to forecast power consumption, then information for consumers and utilities is provided, but the volatility of demand from individual consumers remains unaddressed
Solution Approach 1:
The patent implements closed-loop feedback mechanisms where real-time demand response signals are sent to consumers based on grid conditions, and consumer responses are monitored and fed back into the system. This feedback loop actively stabilizes demand by continuously adjusting consumer behavior in response to grid needs, going beyond conventional one-way analytics to create dynamic demand management.
Solution Approach 2:
The patent transitions from static conventional analytics to dynamic demand response systems that continuously adapt to changing grid conditions. The system dynamically adjusts target demand levels, incentive signals, and consumer targets in real-time, enabling the system to respond to volatility rather than merely forecast it, thus addressing the stability issue.
3Stability of the object's composition
If target power demand is set for consumers, then energy demand stability improves, but the complexity of monitoring and adjusting actual demand increases
Solution Approach 1:
The patent creates a universal demand response platform that serves multiple functions: setting target demand, monitoring actual consumption, calculating deviations, generating incentive signals, and adjusting consumer targets. This multi-functional system consolidates what would otherwise require separate complex subsystems, achieving demand stability while managing complexity through integration.
Data Source
AI summary
A computer-implemented method, according to one embodiment, includes: setting a target power demand corresponding to a consumer, and performing a process. The process includes: determining an actual power demand presented to a utility by the consumer, and determining a current error. The current error is the difference between the actual power demand and the target power demand. A determination is also made as to whether the actual power demand is adjustable in a direction that reduces the current error. In response to determining that the actual power demand is adjustable in the direction that reduces the current error, the current error is reduced by adjusting the actual power demand. Moreover, in response to determining that the actual power demand is not adjustable in the direction that reduces the current error, the target power demand is modified.