Electric power amount reduction control device, electric power amount reduction control method, electric power amount reduction control system, and program
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Solution Overview
Problem
Existing data center power management techniques fail to optimize total power consumption, including server and air conditioning power, due to a lack of consideration for individual facility conditions such as air conditioning facility arrangement, air flow, server configuration, and thermal cooling efficiency.
Innovation Solution
A power amount reduction control device that acquires external factors like floor average temperature and outside temperature, determines situation classifications, calculates optimal air conditioning control values, and adjusts server and air conditioning power consumption patterns to minimize total power usage by strategically arranging virtual resources across servers and air conditioning sections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a general-purpose rule-based standard is adopted in the air conditioning power model, then the calculation is simplified and easier to implement, but the optimization accuracy for reducing total power consumption deteriorates because individual facility conditions are not considered
Solution Approach 1:
The patent applies local quality by transitioning from a general-purpose rule-based power model to a facility-specific power model that incorporates individual data center conditions such as air conditioning facility arrangement, air flow characteristics, server configuration, and thermal cooling efficiency. This allows each data center to have a customized power consumption calculation that reflects its unique operational characteristics, thereby improving optimization accuracy without sacrificing implementation feasibility through the systematic measurement and integration of specific facility parameters.
2Measurement precision
If individual facility conditions such as air conditioning arrangement, air flow, and server configuration are considered in the power model, then the optimization accuracy for reducing total power consumption is improved, but the system complexity and measurement requirements increase
Solution Approach 1:
The patent applies preliminary action by establishing a comprehensive measurement and data collection framework before implementing the optimization algorithm. Specific facility conditions such as air conditioning arrangement, air flow patterns, server configuration, and thermal cooling efficiency are measured and stored in advance as input parameters for the power consumption model. This preparatory data collection enables the subsequent optimization process to operate with high accuracy without requiring complex real-time measurements during optimization execution.
Solution Approach 2:
The patent introduces an intermediary power consumption model that acts as a bridge between physical facility conditions and optimization objectives. This model integrates multiple facility-specific parameters (air conditioning arrangement, air flow, server configuration, thermal cooling efficiency) into a unified computational framework that can be processed by the optimization algorithm, thereby managing system complexity while maintaining measurement precision.
3Use of energy by moving object
If the number of IT devices is reduced through load aggregation to minimize power consumption, then the server power consumption is reduced, but the air conditioning power consumption may increase due to less efficient thermal management
Solution Approach 1:
The patent applies feedback by incorporating the interrelationship between server load aggregation and air conditioning power consumption into the optimization model. The facility-specific power model captures how changes in server arrangement and load distribution affect thermal patterns and air conditioning requirements. The optimization algorithm uses this feedback to evaluate the total power consumption impact of load aggregation decisions, balancing server energy savings against potential air conditioning energy increases to achieve genuine total power reduction.
Data Source
AI summary
A power amount reduction control device (100) includes an external factor acquisition unit (211) that acquires an external factor of air conditioning control, a Situation determination unit (212) that determines a Situation classification based on the external factor, a control value search unit (220) that calculates an air conditioning control value for each Situation classification, an air conditioning control execution unit (230) that controls an air conditioner using the air conditioning control value, a correspondence information generation unit (250) that generates control value power amount correspondence information for each Situation classification, an arrangement pattern calculation unit (310) that calculates an arrangement pattern of virtual resources, a server power consumption amount estimation unit (320) that estimates a server power consumption amount for each arrangement pattern, and an arrangement pattern determination unit (330) that calculates a total amount of the server power consumption amount and the air conditioning power consumption amount in each arrangement pattern and determines an arrangement pattern having a smallest total amount.