BTM Load Power Scheduling Under Fixed-Duration Power Options
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Generation stations, particularly wind and solar farms, face inefficiencies due to the inability to quickly adjust operations in response to fluctuating market prices, leading to power being sold at low or negative prices and curtailment, resulting in wasted energy and reduced operational efficiency.
Innovation Solution
Implementing a behind-the-meter (BTM) load, such as flexible datacenters, that can utilize power from generation stations without incurring traditional Transmission and Distribution (T&D) costs, allowing generation stations to selectively supply power to the grid or BTM loads based on market conditions, thereby optimizing revenue and reducing economic impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generation stations supply power to the grid continuously, then power generation operations are maintained, but power may be sold at low or negative prices during market fluctuations
Solution Approach 1:
The patent implements dynamic power supply adjustment by enabling generation stations to flexibly switch between grid supply and BTM load supply based on real-time market conditions. The system dynamically modifies power consumption targets for BTM loads to absorb excess generation when grid prices are unfavorable, eliminating the need for curtailment while maintaining operational continuity.
Solution Approach 2:
The system changes the operational parameters of power consumption by implementing time-varying power targets for BTM loads. These targets are adjusted based on market price signals, allowing the generation station to optimize the distribution of power between grid supply and local consumption, thereby avoiding negative pricing scenarios.
2Adaptability or versatility
If generation stations quickly adjust operations in response to market prices, then revenue is optimized, but operational complexity increases
Solution Approach 1:
The patent introduces a control system as an intermediary that automatically manages the complex decision-making process. This control system receives market price signals and autonomously adjusts power consumption targets for BTM loads, eliminating the need for manual operational adjustments while capturing revenue optimization opportunities.
Solution Approach 2:
The system implements a feedback mechanism where market price information continuously informs power consumption target adjustments. The control system monitors grid pricing conditions and automatically modifies BTM load power targets in response, creating a closed-loop system that adapts to market conditions without increasing operational complexity.
3Loss of energy
If power is diverted to BTM loads, then T&D costs are reduced and revenue is maximized, but power management complexity increases
Solution Approach 1:
The patent enables the generation station to serve its own power needs through BTM loads, eliminating the need to purchase power from the grid during high-cost periods. The system automatically manages power allocation between grid supply and local consumption, making the generation station self-sufficient and reducing T&D cost dependencies.
Data Source
AI summary
Examples relate to adjusting load power consumption based on a power option agreement. A computing system may receive power option data that is based on a power option agreement and specify minimum power thresholds associated with time intervals. The computing system may determine a performance strategy for a load (e.g., set of computing systems) based on a combination of the power option data and one or more monitored conditions. The performance strategy may specify a power consumption target for the load for each time interval such that each power consumption target is equal to or greater than the minimum power threshold associated with each time interval. The computing system may provide instructions the set of computing systems to perform one or more computational operations based on the performance strategy.