Distributed Datacenter Power Control for Renewable Curtailment
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Solution Overview
Problem
The challenge lies in efficiently managing and utilizing 'behind-the-meter' power generated by local stations, particularly wind and solar sources, which often face curtailment due to grid stability issues and negative market pricing, leading to wasted energy and inefficiencies in renewable energy generation.
Innovation Solution
A distributed power control system that includes a flexible datacenter powered by behind-the-meter sources, allowing for dynamic power modulation based on operational directives from local station control systems or remote master control systems, enabling the datacenter to ramp up, down, or adjust power consumption to match available renewable energy, thereby avoiding curtailment and utilizing otherwise wasted energy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If local stations generate power continuously to maximize renewable energy output, then energy production increases, but grid stability deteriorates and curtailment occurs
Solution Approach 1:
The patent implements dynamic power modulation where the datacenter's power consumption is continuously adjusted based on real-time renewable energy availability and grid conditions. The system transitions from static power consumption to dynamic adjustment, allowing the datacenter to ramp up or down its power usage in response to changing wind and solar generation levels, thereby preventing curtailment while maintaining grid stability.
Solution Approach 2:
The system changes the power consumption parameter of the datacenter based on external conditions. By monitoring renewable energy generation levels and grid stability metrics, the control system adjusts the power consumption parameter dynamically, matching it to available renewable energy supply. This parameter adaptation allows the system to maximize renewable energy utilization without compromising grid reliability.
2Loss of energy
If behind-the-meter power is generated at local stations, then transmission losses are reduced, but power utilization efficiency deteriorates due to curtailment
Solution Approach 1:
The patent creates a self-service arrangement where the local station's behind-the-meter power supply serves the collocated datacenter directly. The datacenter consumes the renewable energy generated at the same location, eliminating the need for transmission to distant consumers. This local self-service model simultaneously reduces transmission losses and ensures high power utilization efficiency by matching supply and demand at the source.
Solution Approach 2:
The system merges the power generation function and power consumption function at the same location. By colocating the datacenter with the renewable energy generation facility and connecting it directly to behind-the-meter power, the patent combines production and consumption in one integrated system, eliminating transmission infrastructure and maximizing local energy utilization.
3Ease of operation
If datacenter power consumption is kept constant, then operational simplicity is maintained, but adaptability to renewable energy fluctuations deteriorates
Solution Approach 1:
The patent implements a feedback control system that continuously monitors renewable energy generation levels, grid stability metrics, and datacenter power consumption. Based on this feedback, the control system automatically adjusts the datacenter's power consumption to maintain optimal operation. This closed-loop feedback mechanism provides adaptability to fluctuations while keeping operational complexity manageable through automated control.
Solution Approach 2:
The control system acts as an intermediary between the variable renewable energy supply and the datacenter's power consumption. It mediates the relationship by translating fluctuating generation levels into appropriate power consumption adjustments, shielding the datacenter from direct exposure to volatility while maintaining operational simplicity through centralized control.
Data Source
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AI summary
In an example embodiment, a distributed power control system can include a datacenter and a remote master control system. The datacenter can include (i) computing systems, (ii) a behind-the-meter power input system configured to receive power from a behind-the-meter power source and deliver power to the computing systems, and (iii) a datacenter control system configured to control the computing systems and the behind-the-meter power input system. The remote master control system can be configured to issue instructions to the datacenter that affect an amount of behind-the-meter power consumed by the datacenter. The datacenter control system can receive, from a local station control system configured to at least partially control the behind-the-meter power source, a directive for the datacenter to ramp-down power consumption, and in response to receiving the directive, cause the computing systems to perform a set of predetermined operations correlated with the directive.