Adaptive Electricity Control Using Pipeline Thermal Storage
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Solution Overview
Problem
Existing power grid systems lack the ability to efficiently manage electrical demand fluctuations, leading to increased costs due to the need for additional power at peak demand times, which is often more expensive than recently added power, and there is a need for consumers to optimize their energy consumption as an 'electrical reservoir' in a smart grid.
Innovation Solution
Adaptive control methods are employed to adjust control parameters based on time-related electrical demand data, including diurnal and seasonal variations, to maximize energy consumption during low-demand periods and minimize consumption during high-demand periods, utilizing a control algorithm that incorporates real-time data and historical demand curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If additional power is brought into the grid to meet increasing demand, then the power supply capacity is improved, but the cost per unit of power increases
Solution Approach 1:
The system performs preliminary action by pre-heating or pre-cooling the pipeline during periods of low electrical demand (off-peak hours) when power costs are lower. This stored thermal energy is then utilized during peak demand periods to reduce or eliminate the need for additional expensive power, thereby resolving the contradiction between maintaining power supply capacity and reducing per-unit power costs
Solution Approach 2:
The system changes the operational parameters of the pipeline temperature over time, allowing it to deviate from a constant setpoint. By dynamically adjusting the temperature based on electrical demand conditions and utilizing the pipeline's thermal mass, the system shifts energy consumption to lower-cost periods, effectively reducing the average cost per unit of power while maintaining adequate supply capacity
2Stability of the object's composition
If the pipeline temperature is maintained at a constant setpoint, then the temperature control stability is improved, but the energy consumption increases during high-demand periods
Solution Approach 1:
The system transitions from a static constant setpoint temperature control to a dynamic temperature profile that varies with electrical demand conditions. The pipeline temperature is allowed to fluctuate within acceptable ranges, being adjusted higher or lower depending on whether it is an off-peak or peak demand period, thereby reducing overall energy consumption while maintaining operational stability
Solution Approach 2:
The system implements periodic action by cycling the pipeline temperature control in response to diurnal and seasonal electrical demand patterns. During off-peak hours, the system applies heating or cooling to store thermal energy in the pipeline, then reduces or reverses the action during peak hours when electricity costs are higher, creating a periodic control pattern that reduces total energy consumption
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces overall energy costs by leveraging the pipeline as a thermal reservoir, optimizing energy use based on demand patterns, thereby reducing reliance on expensive peak power and enhancing the economic efficiency of electrical consumption.
Implementation Method 1
leveraging the pipeline as a thermal reservoir
Data Source
AI summary
Systems, methods, and controllers for controlling an adjustment process for a target system are provided. A central controller receives time-related electrical energy demand data, sensor data from controllers of devices which selectively apply electrical power to the target system, and commands the controllers to apply power to exceed a target control value up to a maximum control value where the electrical energy demand data remains below a threshold and only apply sufficient energy to reach the target control value, at least within a margin, where the electrical energy demand data remains above the threshold.