Demand Coordination Network Control for Peak Demand Management
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Solution Overview
Problem
Conventional methods for managing peak demand of resources like electrical power and water impose discomfort and productivity losses by deferring or reducing device operation times, failing to consider acceptable operational margins and energy lag of buildings.
Innovation Solution
A demand coordination system with a network operations center and control nodes that determine energy lag from fine-grained data to generate schedules for devices, allowing for preemptive cycling and deferral to reduce peak demand while maintaining operational comfort zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If deferral or reduction of device operation times is used to manage peak demand, then resource consumption during peak periods is reduced, but operational comfort and productivity deteriorate
Solution Approach 1:
The system performs preliminary action by advancing device operation times before peak demand periods. The demand coordination system generates schedules that cause devices to operate earlier, storing energy or completing tasks in advance, thereby reducing peak demand without compromising operational comfort during critical periods.
Solution Approach 2:
The system applies dynamics by continuously adjusting device schedules based on real-time and historical data. The demand coordination system dynamically generates and modifies operation schedules, considering energy lag characteristics and acceptable operational margins, allowing flexible optimization between resource consumption and operational comfort.
2Loss of energy
If conventional demand management methods are applied, then peak demand charges are reduced, but productivity and operational performance deteriorate
Solution Approach 1:
The system implements feedback by continuously monitoring device performance, energy consumption patterns, and operational margins. The demand coordination system uses this feedback to refine schedules, ensuring that productivity requirements are met while optimizing peak demand management through iterative improvement.
Solution Approach 2:
The system applies parameter changes by modifying operation schedules based on energy lag characteristics and acceptable operational margins. The demand coordination system adjusts timing parameters and duty cycles within acceptable margins, maintaining productivity while reducing peak demand charges through optimized parameter selection.
3Power
If device operation times are staggered to mitigate peak demand, then instantaneous resource consumption is reduced, but total operational efficiency deteriorates
Solution Approach 1:
The system applies self-service by enabling devices to autonomously execute scheduled operations without continuous manual intervention. The demand coordination system establishes schedules that devices follow independently, maintaining operational efficiency while achieving peak demand mitigation through automated, coordinated operation timing.
Data Source
AI summary
An apparatus including devices, a network operations center (NOC), and control nodes. Each of the devices consumes a portion of a resource when turned on, and performs a corresponding function within an acceptable operational margin by cycling on and off. The NOC is disposed external to a facility, and determines an energy lag for the facility based upon fine-grained energy consumption baseline data. The NOC employs the energy lag to generate a plurality of run time schedules that coordinates run times for the each of the devices to control the peak demand of the resource. Each of the plurality of control nodes is coupled to a corresponding one of the plurality of devices. The plurality of control nodes transmits sensor data and device status to the NOC via the demand coordination network for generation of the plurality of run time schedules, and executes selected ones of the run time schedules to cycle the plurality of devices on and off.