Data Center Asset Reconciliation Using Energy Discrepancy Detection
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Solution Overview
Problem
Data centers face challenges in maintaining accurate asset inventories, leading to underutilization or overutilization of assets, which results in significant carbon emissions and hinder Environmental, Social, and Governance (ESG) compliance.
Innovation Solution
A computerized method that measures and compares energy consumption across data center assets, identifies discrepancies, and automatically performs actions such as decommissioning, virtualizing, or configuring assets to optimize energy efficiency and reduce carbon emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing asset management solutions are used to maintain an inventory of assets, then asset inventory tracking is improved, but assets may still not be accounted for, leading to underutilization or overutilization and significant carbon emissions
Solution Approach 1:
The system continuously compares the sum of individual asset energy consumptions against the total data center energy consumption and uses this feedback to identify unaccounted assets. This closed-loop monitoring enables dynamic adjustment of asset inventories and triggers automated actions to resolve discrepancies, thereby improving both inventory accuracy and energy efficiency.
Solution Approach 2:
The system automatically performs corrective actions such as decommissioning, virtualizing, or reconfiguring assets without requiring manual intervention. The automated workflow enables the system to self-correct inventory discrepancies and optimize energy consumption autonomously, reducing carbon emissions while maintaining accurate asset tracking.
2Measurement precision
If assets are manually managed and inventoried, then inventory accuracy can be maintained, but time consumption and operational complexity increase
Solution Approach 1:
The system automatically performs inventory reconciliation by comparing individual asset energy consumptions against total consumption data. It autonomously identifies unaccounted assets and executes corrective actions without manual intervention, significantly reducing the time and effort required for inventory management while maintaining high accuracy.
Solution Approach 2:
The patent replaces manual inventory management processes with an automated computerized system that uses energy consumption data to identify and correct asset inventory discrepancies. This substitution of mechanical/manual processes with automated digital systems eliminates time-consuming manual tasks while ensuring continuous inventory accuracy.
3Adaptability or versatility
If assets are not properly accounted for in the inventory, then operational flexibility is maintained, but energy waste and carbon emissions increase
Solution Approach 1:
The system continuously monitors energy consumption at both the data center and individual asset levels, using this feedback to identify unaccounted assets. This real-time monitoring enables the system to detect energy waste patterns and trigger automated corrective actions, thereby reducing energy waste while maintaining operational flexibility through automated rather than rigid manual processes.
Solution Approach 2:
The system dynamically adjusts asset status parameters based on energy consumption analysis. When unaccounted assets are identified, the system automatically changes their status parameters to reflect appropriate actions such as decommissioning, virtualization, or reconfiguration, thereby optimizing energy efficiency while preserving operational flexibility through automated parameter adjustments.
Data Source
AI summary
A computerized method for environmental, social, and governance (ESG) compliance of assets of a data center is provided. A list of assets of a data center is obtained and energy consumption by the assets during a time period is measured. Total energy consumption of the data center during the time period is received. The energy consumption by the assets is compared with the total energy consumption of the data center. Based on the comparison, if it is determined that the total energy consumption of the data center is more than the energy consumption by the assets in the list of assets, an asset of the data center not in the list of assets is identified. An action, comprising decommissioning the identified asset, virtualizing the identified asset, and/or configuring the identified asset in balanced mode, on the identified asset of the data center is automatically performed.