Data Center Power Load Balancing for Automated Outage Recovery
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Solution Overview
Problem
Conventional Tier 2 data centers lack the redundancy and automated disaster recovery capabilities of Tier 4 centers, making them inadequate for critical systems and increasing capital expenses, while also failing to efficiently manage power loads across data centers during utility outages.
Innovation Solution
A system and method for intelligent data center power management that continuously collects and analyzes data from infrastructure, application, power, and virtual machine elements, enabling automated operational state changes and dynamic load balancing across multiple data centers, and predictive analytics for energy market failures, allowing for Tier 4-like redundancy and disaster recovery without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Tier 4 data center design with 2N+1 redundancy is implemented, then reliability and disaster recovery capability are improved, but capital expenses and device complexity increase significantly
Solution Approach 1:
The system segments the data center into multiple independent zones or clusters, each with its own power distribution infrastructure. This allows redundancy to be implemented at the zone level rather than requiring complete 2N+1 redundancy across the entire data center, reducing overall complexity while maintaining reliability through geographic or functional separation of critical systems
Solution Approach 2:
The patent implements dynamic load balancing and automated failover mechanisms that allow the system to adapt power distribution in real-time based on actual workload and failure conditions. Instead of static redundant components sitting idle, the system dynamically activates backup paths only when needed, reducing the number of permanently deployed redundant components while maintaining Tier 4 reliability during failures
2Device complexity
If Tier 2 data center design with single power distribution path is used, then capital expenses are reduced, but reliability and disaster recovery capability deteriorate
Solution Approach 1:
The system pre-configures multiple power distribution paths and automated failover logic in advance, but only activates additional redundant components when failures are detected. This allows Tier 2 data centers to operate with minimal redundant infrastructure during normal operation while automatically transitioning to Tier 4-like redundancy when disasters occur, without permanently bearing the capital cost of full Tier 4 infrastructure
Solution Approach 2:
The patent implements self-healing and automated failover mechanisms that detect power distribution failures and automatically reroute loads through alternative paths without human intervention. This allows Tier 2 data centers to achieve Tier 4 reliability outcomes through automated response to failures, rather than requiring permanent Tier 4 hardware redundancy, thereby maintaining reliability while reducing device complexity
3Productivity
If automated data collection and analysis systems are deployed, then operational efficiency and disaster recovery speed are improved, but system complexity and initial investment increase
Solution Approach 1:
The system employs multi-functional data collection platforms that serve multiple purposes: monitoring power distribution, tracking workload performance, detecting failures, and triggering failover actions. By using universal sensors and analytics engines that perform several functions simultaneously rather than dedicated systems for each function, the patent reduces overall system complexity while maintaining high operational efficiency and automated disaster recovery capabilities
Data Source
AI summary
Systems and methods for intelligent data center power management and energy market disaster recovery comprised of data collection layer, infrastructure elements, application elements, power elements, virtual machine elements, analytics/automation/actions layer, analytics or predictive analytics engine, automation software, actions software, energy markets analysis layer and software and intelligent energy market analysis elements or software. Plurality of data centers employ the systems and methods comprised of a plurality of Tier 2 data centers that may be running applications, virtual machines and physical computer systems to enable data center and application disaster recovery from utility energy market outages. Systems and methods may be employed to enable application load balancing and data center power load balancing across a plurality of data centers and may lead to financial benefits when moving application and power loads from one data center location using power during peak energy hours to another data center location using power during off-peak hours.