Grid Control Method Using Consumption Forecasting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current control methods for electric power distribution grids are inadequate in managing consumption behavior, leading to uncontrolled peaks in electric consumption, potential grid malfunctions, and costly penalty fees, especially when dealing with variable loads and generators like batteries and renewable energy systems.
Innovation Solution
A method that dynamically adjusts the set-points of grid devices within an observation time window to achieve consumption targets by analyzing consumption data, forecasting future usage, and adjusting priorities based on available power variations and device characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If instantaneous measurements are used as a basis for load disconnection, then the response speed to power consumption peaks is improved, but unnecessary disconnections occur during transients such as motor starting
Solution Approach 1:
The system performs preliminary actions by forecasting future consumption values before the actual peak occurs. The forecasting module predicts consumption at future time points based on historical and current data, allowing the control system to prepare load disconnection decisions in advance. This prevents reactive disconnections during transients while maintaining rapid response to actual peaks.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring actual consumption values and comparing them with forecasted values. The control module adjusts disconnection decisions based on this feedback, validating whether predicted peaks materialize and learning from past disconnection outcomes to improve future forecasting accuracy and reduce false disconnections.
2Ease of operation
If predefined load shedding schemes are adopted, then the control implementation is simplified, but the system cannot adapt to dynamic consumption patterns and local generators
Solution Approach 1:
The system transitions from static predefined shedding schemes to dynamic load management. The forecasting module continuously updates consumption predictions based on real-time data, and the control module dynamically adjusts which loads to disconnect and when. This dynamic approach adapts to changing consumption patterns and the presence of local generators while maintaining systematic control through automated decision-making algorithms.
Solution Approach 2:
The system changes key parameters including forecasting time horizons, consumption threshold levels, and load priority classifications. These parameter adjustments allow the system to adapt to different operational conditions, seasonal variations, and the integration of renewable energy sources, transforming a rigid predefined scheme into a flexible adaptive control system.
3Power
If load disconnection is performed immediately when power consumption exceeds a fixed threshold, then the peak consumption is reduced quickly, but user discomfort increases and productivity is affected
Solution Approach 1:
The system performs preliminary load disconnection based on forecasted consumption values before actual peaks occur. By predicting future consumption exceeding thresholds and pre-disconnecting appropriate non-critical loads, the system prevents peak formation without causing user discomfort from sudden disconnections during critical operations.
Solution Approach 2:
The system applies different disconnection strategies to different loads based on their criticality. Non-critical loads are disconnected preferentially while critical loads maintaining user operations are protected. This localized quality approach ensures peak reduction is achieved through selective disconnection rather than blanket load shedding, preserving productivity for essential functions.
4Reliability
If more control interventions are performed to manage consumption, then the consumption target compliance is improved, but the system complexity and intervention frequency increase
Solution Approach 1:
The forecasting module performs preliminary analysis of future consumption trends, allowing the control system to make informed decisions about necessary interventions. By predicting which consumption targets will be missed, the system only intervenes when and where needed, reducing unnecessary control actions and simplifying the overall control logic while maintaining high compliance rates.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The invention relates to a method for controlling an electric power distribution grid (100), which comprises one or more first grid devices (CD1...CDn) having changeable set-points. The method comprising the following steps: determining a consumption value at a check instant in an observation time window, in which consumption of said electric power distribution grid at a given observation electric node (Pcc) of said electric power distribution grid is observed, determining a consumption forecast value for said electric power distribution grid, said consumption forecast value being determined with reference to at an end instant of the observation time window, executing a control procedure for controlling the set-points of said first grid devices depending on the consumption forecast value at the check instant.