Interruptible Load Control for Fluctuating Power Demand
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Solution Overview
Problem
The management of electric power production is complicated by the variability of renewable energy sources, leading to inefficient operations in traditional power plants due to rapid fluctuations in energy production and demand, resulting in increased costs, pollution, and reduced profitability.
Innovation Solution
A computer-implemented method that utilizes an interruptible load to optimize power generation by determining the net market value of electricity, processing tasks, and fuel, allowing for the efficient shutdown or startup of processing tasks to match energy demand and supply, thereby maximizing capacity utilization and minimizing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional power plants quickly ramp up production to meet evening demand increases, then consumer demand is met, but startup costs increase and pollution increases
Solution Approach 1:
The system performs preliminary actions by pre-heating boilers and maintaining generators in a warm standby state during periods of low demand, so that when demand increases in the evening, the plants can ramp up quickly without full startup costs. This preliminary preparation reduces both response time and operating costs.
Solution Approach 2:
The system dynamically adjusts the operating state of power plants between different modes (full operation, partial operation, warm standby, cold standby) based on real-time demand forecasting and market conditions. This dynamic state management allows optimal balance between response speed and operating cost.
2Productivity
If traditional power plants operate at full capacity throughout the day, then high capacity utilization is maintained, but surplus electricity must be offloaded causing frequency excursions and reduced profitability
Solution Approach 1:
The system continuously monitors grid conditions, demand forecasts, and renewable generation levels, using this feedback to dynamically adjust power plant output. This feedback mechanism prevents overproduction by matching generation to actual demand, avoiding frequency excursions and the need to offload surplus electricity.
Solution Approach 2:
The system changes operating parameters (generation level, plant state) based on varying conditions including time of day, renewable availability, and grid demand. By adjusting these parameters dynamically rather than maintaining fixed full-capacity operation, the system maintains high utilization when appropriate while avoiding grid instability.
3Object-affected harmful factors
If renewable energy production fluctuates rapidly, then clean energy goals are advanced, but traditional power plants face operational inefficiency and increased costs
Solution Approach 1:
The system acts as an intermediary layer between renewable energy sources and traditional power plants, using demand forecasting and market analysis to coordinate their operation. This intermediary control optimizes the mix of renewable and traditional generation, allowing traditional plants to operate efficiently while still advancing clean energy goals through strategic dispatch.
Data Source
AI summary
An automated control method for meeting rapidly fluctuating power demands with stable power production is disclosed. The method includes determining a market value of a unit of electricity sold on the grid, a fuel cost required to produce the unit of electricity, and a market value of a processing task requiring the unit of electricity. The method also includes calculating which of the electricity, processing, or fuel is most valuable; shutting off a running process when the value of the electricity is highest or the value of the fuel is highest; and starting a pending process when the net market value of the processing task is highest. The method may also include reducing electricity generation at a power plant when the value of electricity is negative, or exercising a futures contract to supply electricity.


