Wide-Area Energy Control for Data Center Source Coordination
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Solution Overview
Problem
Integrating diverse energy sources into data centers is challenging due to differing electrical properties and the need to coordinate low-level machine controls with high-level optimal dispatch algorithms, often lacking a standard agnostic interface for communication.
Innovation Solution
A wide-area energy control system that uses an agnostic communication interface to connect with diverse energy sources, allowing for real-time control based on power control information received from a remote data center control system, and enabling a plug-and-play architecture for easy installation and integration.
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 and integration difficulty increase
Solution Approach 1:
The patent implements a universal communication interface that enables a single control system to interface with multiple types of energy sources (solar panels, wind turbines, generators, batteries) through a standardized protocol. This universal interface eliminates the need for separate integration systems for each energy source type, thereby improving reliability through diverse energy supply while reducing system integration complexity.
Solution Approach 2:
The control system acts as an intermediary between diverse energy sources and the data center loads. It receives power control information from remote systems, processes it locally, and translates it into appropriate control signals for different energy source types. This intermediary function harmonizes the heterogeneous energy sources, managing their differing electrical properties and control requirements without increasing overall system complexity.
2Productivity
If low-level machine controls are coordinated with high-level optimal dispatch algorithms, then energy optimization and efficiency are improved, but control coordination difficulty increases
Solution Approach 1:
The control architecture is segmented into distinct hierarchical levels: high-level remote data center control systems that provide optimal dispatch algorithms and power control information, and local control systems that execute specific machine control functions. This segmentation allows each level to operate independently within its domain, optimizing energy allocation at the high level while managing device control at the low level, thereby improving overall efficiency without creating insurmountable coordination complexity.
Solution Approach 2:
The system implements feedback mechanisms where the local control system continuously monitors the actual performance of energy sources and loads, compares it with the optimal dispatch targets from the remote system, and adjusts control parameters accordingly. This feedback loop enables effective coordination between high-level optimization algorithms and low-level machine controls, improving energy efficiency while managing coordination complexity through iterative adjustment rather than complex upfront design.
3Ease of manufacture
If a standard agnostic interface is implemented, then ease of integration and installation are improved, but system adaptability requirements increase
Solution Approach 1:
The patent implements a standardized communication interface that copies or replicates the same protocol and data structure across all energy source connections. Instead of creating unique interfaces for each energy source type, the system uses a copied template interface that can be instantiated for any energy source. This approach dramatically simplifies integration and installation while the underlying adaptability is maintained through configuration parameters that allow the same interface structure to accommodate different energy source characteristics.
Data Source
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.