Peak Resource Scheduling for Equitable Grid Load Control
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Solution Overview
Problem
Resource distribution systems face challenges during extreme weather or critical peak demand periods where consumer demand outpaces production capabilities, leading to rolling outages that are difficult to manage and inequitable across all premises.
Innovation Solution
Implementing a peak resource management schedule that assigns staggered peak and limited consumption periods to premises, controlled by metering devices to manage consumption levels, utilizing communication interfaces and incentives for energy export during peak times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If resource allocation is delayed until peak demand periods, then response time to user requests increases, but system load and infrastructure costs increase exponentially
Solution Approach 1:
The system performs preliminary resource allocation by predicting future resource demands using machine learning models and allocating resources in advance before peak demand occurs. This proactive approach reduces response time during actual demand while avoiding the exponential load increase of reactive allocation.
Solution Approach 2:
The resource allocation system dynamically adjusts resource distribution based on real-time demand signals and predictive analytics. Rather than static allocation, the system continuously adapts resource allocation decisions to current and forecasted conditions, optimizing both response time and system load.
2Reliability
If more infrastructure resources are allocated to handle peak demand, then service reliability improves, but operational costs increase significantly
Solution Approach 1:
The system changes the parameter of resource allocation timing and quantity based on predictive demand signals. By adjusting allocation parameters proactively rather than reactively, the system maintains service reliability during peak demand without requiring permanently over-provisioned infrastructure, thus reducing operational costs.
Solution Approach 2:
The system implements feedback loops where resource allocation decisions are continuously refined based on actual demand patterns and predictive model performance. This feedback mechanism enables the system to maintain reliability while optimizing resource utilization and reducing unnecessary infrastructure costs.
3Device complexity
If reactive resource allocation is used, then infrastructure investment is reduced, but user experience deteriorates during peak periods
Solution Approach 1:
The system takes preliminary action by allocating resources before peak demand occurs, based on predictive analytics. This approach maintains good user experience during peak periods without requiring the heavy infrastructure investment that would be needed for purely reactive allocation with guarantees.
4Measurement precision
If manual resource management is implemented, then control precision improves, but operational complexity and time consumption increase
Solution Approach 1:
The system enables self-service automated resource allocation using machine learning models that autonomously predict demand and allocate resources without manual intervention. This maintains high control precision through sophisticated algorithms while reducing operational complexity and time consumption compared to manual management.
Data Source
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AI summary
A computer-implemented method includes assigning, by a peak management system, a peak resource management schedule to a first premises and a second premises within a resource distribution network. The peak resource management schedule includes a first peak consumption period and a first limited resource consumption period for the first premises and a second peak consumption period and a second limited resource consumption period for the second premises, where the first peak consumption period and the second peak consumption period are different. The method also includes transmitting, by the peak management system, a peak resource management signal to the first premises and the second premises. The peak resource management signal includes instructions to commence execution of the peak resource management schedule at the first premises and the second premises.