Data Center Power Control Using a Vendor-Agnostic Energy Interface
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Solution Overview
Problem
Integrating diverse energy sources into data centers is challenging due to differing electrical properties and information technology/cooling loads, and existing systems lack a standard agnostic interface for efficient communication and control, leading to complex coordination and high latency.
Innovation Solution
A wide-area energy control system with a vendor-agnostic interface connects to various energy sources, receiving power control information from a remote data center control system to schedule and manage local energy sources, enabling real-time control and integration of diverse energy sources like solar, wind, and diesel generators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If diverse energy sources are integrated into data centers, then energy supply diversity and reliability are improved, but system complexity increases due to differing electrical properties and lack of standard interfaces
Solution Approach 1:
The patent implements a universal agnostic interface that can communicate with multiple types of energy sources (solar, wind, diesel generators, battery storage) through a single standardized communication protocol. This interface acts as a mediator that translates between different energy source control systems and the central wide-area energy controller, eliminating the need for separate integration systems for each energy type and thereby reducing overall system complexity while maintaining reliability
Solution Approach 2:
The agnostic interface serves as an intermediary layer between the diverse energy sources and the wide-area energy control system. It standardizes communication protocols and data formats, allowing the central controller to manage heterogeneous energy sources without direct complex point-to-point connections, thus reducing system complexity while ensuring reliable integration
2Productivity
If centralized control is implemented across multiple data centers, then energy optimization and workload balancing are improved, but communication latency increases
Solution Approach 1:
The control system is segmented into hierarchical levels: wide-area energy controllers at individual data centers handle local real-time control with low latency, while remote data center control systems perform strategic optimization across multiple facilities. This segmentation allows local autonomous decision-making for time-critical operations while maintaining centralized optimization capabilities for long-term energy efficiency
Solution Approach 2:
The system performs preliminary local processing and decision-making at wide-area energy controllers before transmitting commands to energy sources. By pre-processing control logic locally and only communicating essential commands rather than continuous data streams, the system reduces communication latency while maintaining optimization efficiency across the distributed network
Data Source
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AI summary
Systems and methods for managing power loads of one or more data centers using a wide-area energy controller to operate local energy resources of the data center based on power control information generated by a remote data center control system are described. In one aspect, a system includes a set of local energy sources configured to provide power to the loads of the energy system and a wide-area energy controller. The wide-area energy controller includes a first interface communicably coupled to an application programming interface (API) that connects a remote data center control system to respective wide-area energy controllers of multiple data centers, the first interface being configured to receive power control information from the remote data center control system via the API. The wide-area energy controller includes a control unit configured to schedule the local energy sources to provide power to the loads based on the power control information.