Forecast-Based Load Shedding for Resource Distribution Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing load shedding methods in resource distribution networks fail to effectively respond to variations in demand, leading to potential network collapse due to overconsumption.
Innovation Solution
A method for managing load shedding in a resource distribution network that involves forecasting overall consumption, determining load-shedding periods, estimating load-shedding gains for meters, selecting meters for load shedding, and sending load-shedding commands to achieve a target gain and maintain network stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load shedding is applied to control demand and avoid network collapse, then network stability is improved, but customer consumption is reduced
Solution Approach 1:
The system performs preliminary forecasting of overall consumption over a time range and determines load-shedding periods in advance by comparing forecasted consumption with predefined thresholds. Load-shedding commands are sent for future occurrences of time ranges, allowing the network to proactively prepare for and prevent overconsumption events before they cause network collapse.
Solution Approach 2:
The system dynamically adjusts load-shedding parameters including selecting specific meters based on estimated load-shedding gains, determining optimal load-shedding periods within time ranges, and setting target gains to compensate for differences between maximum forecasted consumption and predefined thresholds. These parameter changes optimize the balance between network stability and customer consumption.
2Reliability
If load shedding is applied to prevent network collapse, then network reliability is improved, but demand response capability deteriorates
Solution Approach 1:
The system dynamically adapts load-shedding strategies by forecasting consumption patterns over time ranges and determining optimal load-shedding periods based on varying demand conditions. The selection of meters for load shedding and the determination of target gains are adjusted according to estimated load-shedding gains, enabling the system to respond flexibly to changing demand while maintaining network reliability.
Solution Approach 2:
The system uses feedback from consumption data to improve its load-shedding decisions. By analyzing information representative of customer consumption and comparing actual consumption patterns with forecasts, the system refines its determination of load-shedding periods and target gains, enhancing both network reliability and demand response capability over time.
3Quantity of substance
If load shedding commands are sent to multiple meters, then overall consumption control is improved, but system complexity increases
Solution Approach 1:
The system applies load shedding selectively to specific meters rather than uniformly across all meters. By estimating load-shedding gains for individual meters and selecting meters based on these estimates, the system targets load-shedding actions to locations where they will be most effective, improving overall consumption control while minimizing the number of meters affected and reducing system complexity.
Solution Approach 2:
The system segments the time range into specific load-shedding periods and segments the meters into groups based on their load-shedding gain estimates. This segmentation allows the system to manage load shedding in controlled, manageable units rather than attempting to control all meters simultaneously across all time periods, thereby reducing system complexity while maintaining effective consumption control.
Data Source
AI summary
Load shedding is implemented in a resource distribution network to avoid overconsumption. The network comprises at least one network head and a plurality of meters configured to measure consumption of said resource by a customer and to transmit to the network head customer information representative of the customer's consumption over a given time range. Based on the customer information transmitted by the meters, a overall forecast consumption is determined for all meters for the specified time period. One or more load-shedding periods are determined by comparing the overall forecast consumption with a predefined overall threshold. For each one, the meters to be load-shed are selected according to the expected load-shedding gains for the meters in question. Furthermore, a load-shedding command is sent to them, concerning one or more future occurrences within the specified time range.