Real-Time Data Center Curtailment for Power Pricing Response
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Solution Overview
Problem
Non-critical data centers face challenges in timely and efficient reaction to real-time power pricing fluctuations and curtailment signals, leading to inefficiencies and potential financial losses due to unscheduled power curtailments.
Innovation Solution
A cloud-based computing platform that monitors real-time energy consumption and pricing, automatically sends curtailment signals to non-critical data centers, and provides operational alerts to ensure compliance with power agreements, enabling dynamic power modulation and efficient power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If non-critical data centers manually monitor and react to power pricing fluctuations, then operational flexibility is maintained, but response time is delayed and financial losses occur
Solution Approach 1:
The patent introduces a computing platform as an intermediary system that sits between power providers and non-critical data centers. This platform automatically receives real-time power pricing data, processes curtailment signals, and distributes them to data centers, eliminating the need for manual monitoring while managing the complexity of real-time operations.
Solution Approach 2:
The system enables non-critical data centers to automatically respond to power pricing signals without human intervention. The computing platform autonomously monitors power pricing, generates curtailment signals when prices exceed thresholds, and manages the entire process, allowing the system to serve itself in real-time power management.
2Loss of energy
If non-critical data centers implement real-time power management systems, then operational costs are reduced, but system complexity increases
Solution Approach 1:
The computing platform is designed to perform multiple functions: receiving power pricing data from power providers, monitoring it in real-time, comparing against thresholds, generating curtailment signals, and distributing them to multiple non-critical data centers. This multi-functional approach consolidates complexity into a single universal system rather than requiring separate systems at each data center.
Solution Approach 2:
The system implements feedback loops where power consumption data from non-critical data centers is continuously monitored and fed back to the computing platform. This feedback mechanism allows the system to dynamically adjust curtailment signals based on real-time consumption patterns, optimizing energy management while maintaining manageable system complexity through automated control.
3Productivity
If non-critical data centers rapidly curtail power consumption, then revenue is maximized, but coordination with power providers becomes more difficult
Solution Approach 1:
The system establishes pre-configured curtailment thresholds and response protocols in advance through agreements with power providers. When real-time power pricing exceeds these pre-set thresholds, the computing platform automatically executes curtailment actions without requiring real-time negotiation or coordination, thus maximizing revenue while simplifying ongoing operations.
Solution Approach 2:
The computing platform continuously monitors both power pricing signals from power providers and power consumption data from non-critical data centers, creating a feedback loop that enables rapid, coordinated responses. This real-time feedback mechanism ensures that curtailment actions are synchronized with power provider signals, facilitating easier coordination through automated communication and response tracking.
Data Source
AI summary
The present invention provides a system comprising a power grid operator, a power provider, one or more non-critical data centers configured to receive power from the power provider, and a computing platform in data communication with at least the power provider and the one or more non-critical data centers, wherein the computing platform is configured to at least: (1) receive real-time power consumption data from the one or more non-critical data centers; (2) receive real-time power pricing data from the power grid operator or the power provider; (3) automatically send a curtailment signal to each of the one or more non-critical data centers; and (4) automatically send an end curtailment signal to each of the one or more non-critical data centers. The one or more non-critical data centers may comprise at least one cryptocurrency mining data center, or, alternatively, may comprise at least one non-critical artificial intelligence data center.