NOC-Based Peak Demand Control via Preliminary Scheduling
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Solution Overview
Problem
Current methods for managing peak demand of resources like electrical power and water often result in discomfort and reduced operational efficiency, as they primarily rely on deferral techniques that delay device start times and reduce duty cycles, rather than advancing or adjusting them to maintain acceptable operational margins.
Innovation Solution
A system comprising a monitor node, control nodes, and a network operations center (NOC) that coordinates the operation of devices by determining and broadcasting consumption data, generating run time schedules, and adjusting start times and duty cycles to optimize peak demand while maintaining acceptable operational conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If deferral techniques are used to manage peak demand by delaying device start times and reducing duty cycles, then peak demand is reduced, but device comfort and operational efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by advancing device start times before peak demand periods occur. Instead of merely delaying device operation, the controller proactively schedules devices to operate earlier, thereby reducing peak demand while ensuring devices complete their required operational cycles within acceptable timeframes, maintaining both comfort and efficiency.
Solution Approach 2:
The system dynamically adjusts device operation schedules based on real-time and historical demand patterns. The controller continuously optimizes start times, duty cycles, and operational parameters to balance peak demand reduction with maintaining acceptable device performance and comfort levels, rather than using static deferral approaches.
2Loss of energy
If deferral techniques are used to manage peak demand, then energy consumption during peak periods is reduced, but operational efficiency and productivity deteriorate
Solution Approach 1:
The system performs preliminary actions by advancing device start times before peak demand periods occur. Instead of merely delaying device operation, the controller proactively schedules devices to operate earlier, thereby reducing peak demand while ensuring devices complete their required operational cycles within acceptable timeframes, maintaining both comfort and efficiency.
Solution Approach 2:
The system changes operational parameters such as start times, duty cycles, and operational intensity to optimize the balance between energy consumption and productivity. By adjusting these parameters dynamically, the system reduces peak energy demand while ensuring that devices maintain sufficient operational efficiency to meet productivity requirements.
3Power
If a centralized system is used to coordinate device operation for peak demand management, then demand optimization is improved, but system complexity increases
Solution Approach 1:
The system enables devices to self-manage their operation schedules based on coordinated signals from the controller. Each device autonomously adjusts its start times and duty cycles according to the optimized schedule, reducing the need for complex centralized control mechanisms while still achieving demand optimization through distributed self-adjustment.
Solution Approach 2:
The controller performs preliminary calculations and schedule optimizations in advance, storing optimized schedules that devices can execute autonomously. This preliminary action reduces the need for complex real-time centralized control, as devices follow pre-computed schedules that balance demand optimization with operational simplicity.
Data Source
AI summary
Coupling a first and second nodes, and a monitor node together within a facility via network; via the monitor node, broadcasting whether a non-system device consumes a resource; via the first node, transmitting data and status via the network for generation of schedules, and operating a first device within an acceptable operating margin to maintain a first environment by cycling on and off according to the schedules; and via a network operations center external to the facility, generating the schedules to control peak demand of the resource, where one or more run times start prior to when otherwise required to maintain local environments, and coordinating run times for the first device and a second device, where coordination is based on a global schedule, an adjusted first descriptor set characterizing the first environment, and an adjusted second descriptor set characterizing a second environment, and data broadcast by the monitor node.