Automated Demand Response System for Grid Frequency Regulation
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Solution Overview
Problem
Current energy demand curtailment methods rely heavily on human involvement, which is inefficient and prone to errors, especially during critical and time-sensitive 'demand response' events, leading to inadequate demand reduction and increased operational costs for utilities.
Innovation Solution
A fully automated system that adapts power grid usage by controlling internal and external assets in response to power regulation and frequency regulation functions, using a demand reduction server to transmit commands to users for automated demand response without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human involvement is used in energy demand curtailment, then operational flexibility and decision-making capability are maintained, but response time is delayed and errors increase during critical demand response events
Solution Approach 1:
The system performs preliminary actions by pre-configuring demand response parameters, setting thresholds, and establishing control rules before demand response events occur. This allows the automated system to immediately execute appropriate demand reduction actions when events are detected, eliminating human response delays while maintaining decision-making quality through pre-planned strategies.
Solution Approach 2:
The system enables self-service by allowing demand response actions to be automatically executed without human intervention. The automated system monitors grid conditions, detects demand response events, and implements demand reduction measures independently, thereby eliminating human response time delays and errors while maintaining operational flexibility through programmable control logic.
2Productivity
If human involvement is used in energy demand curtailment, then complex decision-making can be performed, but operational costs and error rates increase
Solution Approach 1:
The system replaces the mechanical human decision-making process with an automated electronic control system. The automated system uses sensors, processors, and communication networks to monitor grid conditions and execute demand response actions, thereby eliminating human errors and operational costs while maintaining complex decision-making capabilities through programmable control logic and algorithms.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring grid conditions, demand response event status, and demand reduction effectiveness. This real-time feedback enables the automated system to adjust its control actions dynamically, maintaining high productivity while reducing operational complexity through closed-loop control that automatically corrects deviations without human intervention.
3Reliability
If automated demand response is implemented, then response time and accuracy are improved, but system complexity and initial costs increase
Solution Approach 1:
The system applies segmentation by dividing the demand response functionality into separate modular components: event detection modules, control rule engines, execution modules, and monitoring modules. This modular architecture reduces overall system complexity by allowing each component to be independently developed, tested, and maintained, while the integrated system achieves high response accuracy through coordinated operation of these specialized modules.
Solution Approach 2:
The system implements universality by designing a multi-functional automated demand response platform that can handle various types of demand response events, different control strategies, and multiple utility company requirements through a single integrated system. This universal design reduces complexity by avoiding the need for separate specialized systems for each function while maintaining high accuracy through configurable parameters and adaptable control logic.
Data Source
AI summary
A system, method and apparatus for automatically adapting power grid usage by controlling internal and/or external power-related assets of one or more users in response to power regulation and/or frequency regulation functions in a manner beneficial to both the power grid itself and the users of the power grid.