Grid Load Control via Appliance Time Windows
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Solution Overview
Problem
Existing methods for load distribution in electricity networks struggle to efficiently manage peak loads and oversupply due to reliance on forecasts and indirect control over household appliances, leading to inefficiencies and high costs, particularly in stabilizing the grid and preventing blackouts.
Innovation Solution
The energy supplier gains direct and flexible control over household appliances by specifying a time window for operation, allowing remote switching on and off based on current network conditions, enabling precise management of load fluctuations and optimizing the use of energy resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If energy suppliers use forecasts and indirect control to manage household appliances, then load distribution can be influenced to some extent, but the control is limited and does not take current conditions into account
Solution Approach 1:
The system performs preliminary actions by having users pre-define time windows during which appliances may operate, and by having the energy supplier pre-establish control parameters and thresholds. This allows the system to be prepared for real-time decision-making without requiring complex runtime negotiations or adjustments, thereby enabling adaptive control while maintaining operational simplicity.
Solution Approach 2:
The system implements dynamic control by allowing the energy supplier to switch appliances on or off within user-defined time windows based on real-time network conditions. The control is not static but adapts continuously to changing load situations, enabling the system to respond flexibly to current conditions while respecting user-specified operational boundaries.
2Speed
If energy suppliers implement direct control over household appliances, then rapid response to load fluctuations is achieved, but user acceptance may be reduced due to perceived loss of control
Solution Approach 1:
Users perform preliminary actions by defining time windows and operational parameters for their appliances before the load balancing situation arises. This advance preparation allows the energy supplier to exercise direct control within these pre-agreed boundaries without needing to consult users in real-time, achieving rapid response while maintaining user acceptance through prior consent.
Solution Approach 2:
The system introduces an intermediary layer of user-defined time windows that mediates between user autonomy and supplier control. These time windows act as a negotiated compromise, allowing the energy supplier to exercise direct control for rapid response while ensuring that control is exercised only within user-acceptable boundaries, thus maintaining user acceptance.
3Reliability
If peak load power plants are used to cope with demand peaks, then grid stability is maintained, but the regulation is technically complicated and expensive
Solution Approach 1:
The system implements continuous feedback by monitoring network utilization in real-time and using this information to control appliance operation. The energy supplier receives feedback on current load conditions and adjusts appliance switching decisions accordingly, creating a closed-loop control system that maintains grid stability through simple, automated decisions rather than complex regulation mechanisms.
Solution Approach 2:
The system enables self-service load balancing by allowing the energy supplier's control system to automatically make switching decisions based on predefined criteria and real-time network conditions. This automated self-service approach eliminates the need for technically complicated manual regulation and reduces operational complexity while maintaining grid stability.
4Ease of operation
If consumer load is controlled within user-defined time windows, then user acceptance is maintained, but the flexibility of load management is limited compared to unrestricted control
Solution Approach 1:
The system achieves dynamic load management within user-defined time windows by allowing the energy supplier to make real-time switching decisions based on current network conditions. While the time windows provide structure for user acceptance, the actual control actions are dynamic and adaptable to changing conditions, maximizing flexibility within the acceptable boundaries.
Solution Approach 2:
The system optimizes load management by changing operational parameters such as switching timing and duration within the user-defined time windows. Rather than being restricted to fixed schedules, the system adjusts these parameters dynamically based on network conditions, achieving both user acceptance through adherence to time windows and flexibility through parameter optimization.
Data Source
Figure 1
AI summary
Method and system for controlling load distribution in an electricity grid used by an energy supplier, which supplies a large number of households, wherein the energy supplier determines the current load of the grid and, depending on the current grid load, transmits switch-on information to electricity-consuming household appliances in the households via a data line network, wherein a household specifies a time window for the switch-on time of a household appliance to the energy supplier and wherein, depending on the currently determined grid load in the time window, the energy supplier transmits a switching command with which the household appliance is directly controlled.