Gateway Policy Control for Privacy-Aware Demand Response
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Solution Overview
Problem
Conventional automated demand response systems lack customer control over energy management decisions, and interconnected devices and systems require improved data management and control to optimize energy consumption and pricing strategies.
Innovation Solution
A system and method for managing data generated by connected devices, allowing energy retailers to transmit pricing information to customers, enabling device-level control and automation, with data bifurcation techniques to ensure transparency, confidentiality, and privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional automated demand response systems are used to manage energy loads, then utility demand can be smoothed and pricing variability reduced, but customers lose control over energy management decisions
Solution Approach 1:
The system segments control authority between multiple entities: customers define their own policies and preferences for each connected device, the gateway executes these policies locally, and the ADR system provides automated responses to utility signals. This segmentation allows both automated demand management and customer control to coexist by distributing decision-making across different levels of the system hierarchy.
2Reliability
If discrete ADR systems are installed for single loads, then demand response control is achieved, but system complexity increases and scalability is limited
Solution Approach 1:
The gateway device serves multiple functions: it manages connected devices locally, executes customer-defined policies, communicates with utility ADR systems, and handles data logging. This multi-functional design consolidates what would otherwise require multiple discrete systems into a single universal platform, reducing overall system complexity while maintaining reliable demand response control across multiple loads.
3Loss of information
If connected devices collect and transmit detailed operational data, then energy consumption patterns can be analyzed for optimization, but data privacy and confidentiality concerns arise
Solution Approach 1:
The system applies different data handling approaches to different types of information. Detailed operational data and customer preferences remain stored locally in the gateway, providing only aggregated or anonymized data to utility systems. This local quality approach ensures that sensitive information stays confidential while still enabling energy consumption analysis for optimization purposes.
4Adaptability or versatility
If granular device-level control is implemented, then customer energy management flexibility increases, but data management and system coordination become more difficult
Solution Approach 1:
The gateway acts as an intermediary between connected devices and the ADR system. It translates utility demand signals into device-specific control actions based on customer policies, and aggregates device data into meaningful reports. This intermediary role simplifies data management by handling the complexity of coordinating multiple devices while maintaining granular control flexibility for customers.
Data Source
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AI summary
The disclosure relates to systems and methods for managing data generated by connected systems and/or devices in connection with energy usage and/or management decisions. In certain embodiments, a gateway device in communication with one or more connected devices may be configured to receive energy management signal information and apply one or more policies in connection with the management of the connected devices. Responses generated in connection with such energy management decisions may be reported securely in a manner that respects various stakeholder concerns relating to transparency, confidentiality, privacy, auditability, and/or affirmation of data provenance.