Micro Demand Response Control for Grid Buffer Reduction
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Solution Overview
Problem
Current power grid systems rely on large buffers to manage unexpected demand spikes, leading to wasted energy and increased operational costs, as they lack efficient real-time control mechanisms for demand adjustments across the grid.
Innovation Solution
A system and method that utilize network controls and signaling to manage electrical demand in real-time, allowing for automated micro-adjustments in power usage across the grid, thereby reducing the need for large buffers and minimizing waste.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large buffers are maintained to manage unexpected demand spikes, then reliability of power supply is improved, but energy waste and operational costs increase
Solution Approach 1:
The system dynamically adjusts power consumption of controllable loads in real-time based on actual grid demand conditions. Instead of maintaining a static large buffer, the system continuously monitors grid status and modulates load consumption to match actual demand, allowing the buffer to be small yet responsive to unexpected spikes.
Solution Approach 2:
The system implements real-time feedback loops where grid demand information is continuously monitored and fed back to control devices. This feedback mechanism enables the system to detect demand spikes immediately and adjust controllable loads accordingly, replacing the need for large static buffers with dynamic responsive control.
2Reliability
If large buffers are maintained to manage unexpected demand spikes, then reliability of power supply is improved, but operational costs increase
Solution Approach 1:
The system transitions from static buffer maintenance to dynamic load adjustment, where controllable loads are modulated in real-time based on actual grid conditions. This dynamic approach reduces the need for large buffered capacity and associated operational costs while maintaining reliability through responsive demand management.
Solution Approach 2:
The system changes operational parameters of controllable loads (power consumption levels) in real-time based on grid demand conditions. By adjusting these parameters dynamically rather than maintaining fixed high-capacity buffers, the system reduces operational costs while preserving reliability through adaptive response to demand spikes.
3Productivity
If manual demand response is implemented, then instantaneous demand is reduced, but response time is delayed
Solution Approach 1:
The system enables controllable loads to automatically adjust their own power consumption based on real-time grid demand signals. This self-service capability eliminates the manual intervention delay, as loads autonomously respond to grid conditions instantaneously, maintaining demand reduction effectiveness while achieving immediate response times.
Solution Approach 2:
The system replaces manual mechanical adjustment processes with automated electronic control mechanisms. Control devices electronically modulate load operation based on digital grid demand signals, substituting slow manual intervention with instantaneous automated response, thereby reducing response time while maintaining demand reduction capability.
4Reliability
If excess power is shunted through impedance to dissipate, then reliability is maintained, but energy efficiency deteriorates
Solution Approach 1:
The system converts the previously harmful practice of dissipating excess power through impedance into a beneficial process by redirecting that excess power to controllable loads. Instead of wasting energy as heat in impedance shunts, the system utilizes real-time demand management to allocate excess power productively to adjustable loads, transforming energy loss into useful work while maintaining grid stability.
Solution Approach 2:
The system recovers excess power that would otherwise be discarded through impedance dissipation. By implementing real-time demand response, the system captures and redirects this otherwise wasted energy to controllable loads, converting discarded energy into beneficial power delivery and improving overall energy efficiency while maintaining reliability.
Data Source
AI summary
A system and method for dynamically and automatically adjusting the load on a power grid through micro adjustments of equipment coupled to the consumer side of the power grid. The system allowing for the automatic adjustment of equipment to either decrease or increase instantaneous power demand on the grid in response to peak demands and demand valleys to smooth the demand curve on the power grid. The system able to balance demand within the grid to adjust demand within various different portions of the power grid and allowing for reducing the power buffer supplied by electric utilities to reduce waste and carbon emissions.