Service Control Apparatus Dynamic Load Adjustment
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Solution Overview
Problem
Data centers face challenges in precisely adjusting their load to minimize electricity expenses due to constant peak and trough periods of electricity consumption, which affects cost control and precision in load adjustment.
Innovation Solution
A service control method and apparatus that dynamically adjust the quantity of services to be executed based on real-time electricity grid prices and the quantity of to-be-executed services, using an electricity price threshold correlated with the quantity of services to optimize load adjustment and reduce costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If load is adjusted based on constant peak and trough periods, then electricity expense control is simplified, but load adjustment precision deteriorates
Solution Approach 1:
The patent transforms the static, fixed peak and trough periods into dynamic, real-time adjustable periods. The service control apparatus dynamically determines peak and trough periods based on real-time electricity prices and service quantities, allowing the system to adapt to changing conditions and achieve precise load adjustment while maintaining operational simplicity.
Solution Approach 2:
The patent changes the parameter of time period definition from fixed empirical values to dynamically calculated values based on electricity prices and service quantities. By introducing the service quantity as a variable parameter and calculating peak/trough periods in real-time, the system achieves both ease of operation and high precision in load adjustment.
2Device complexity
If load adjustment cycle is extended to cover constant peak and trough periods, then operation complexity is reduced, but adjustment precision deteriorates
Solution Approach 1:
The patent implements dynamic peak and trough period determination that adapts to real-time conditions. Instead of using fixed long-cycle periods, the system continuously updates peak and trough periods based on current electricity prices and service quantities, achieving high precision adjustment without excessive operational complexity.
Solution Approach 2:
The patent introduces feedback mechanisms where the service control apparatus monitors real-time electricity prices and service quantities, then adjusts peak and trough period definitions accordingly. This feedback loop enables precise load adjustment while maintaining manageable system complexity through automated real-time optimization.
3Device complexity
If fixed peak and trough periods are used, then system complexity is reduced, but real-time cost control capability deteriorates
Solution Approach 1:
The patent transforms fixed period determination into a dynamic process that responds to real-time electricity prices and service quantities. The service control apparatus continuously calculates optimal peak and trough periods, enabling real-time cost control while managing system complexity through automated algorithms.
Solution Approach 2:
The patent changes period determination from static fixed values to dynamic calculations based on electricity price and service quantity parameters. This allows the system to achieve real-time cost control capability by adapting period definitions to current operational conditions without excessive complexity.
Data Source
AI summary
A service control method and a service control apparatus, where the method includes obtaining, a current electricity grid electricity price and a quantity of to-be-executed services, determining an electricity price threshold according to the quantity of the to-be-executed services, decreasing, by the service control apparatus, a quantity of services that are about to be executed by a first quantity when the current electricity grid electricity price is greater than the electricity price threshold, and executing a service according to a reduced quantity of services that are about to be executed, or increasing, by the service control apparatus, a quantity of services that are about to be executed by a second quantity, and executing a service according to an increased quantity of services that are about to be executed when the current electricity grid electricity price is less than the electricity price threshold.