Household Appliance Controller for Dynamic Tariff Process Continuity
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Solution Overview
Problem
Household appliances face challenges in operating efficiently on intelligent energy supply networks with dynamic and time-variable electricity tariffs, requiring adaptive control to minimize energy consumption and manage power limitations without interrupting processes.
Innovation Solution
Implementing a computer-like control part with a graph algorithm that integrates data from the energy supply network, allowing for conditional and modified process sequences, and parameterizing actuators to manage energy consumption and recovery, enabling continuous operation even during tariff changes and power restrictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If household appliances operate on traditional energy supply networks with fixed tariffs, then operation simplicity is maintained, but adaptability to dynamic energy pricing and load management is lost
Solution Approach 1:
The controller dynamically adapts its operation based on real-time energy pricing signals and load management requirements from the intelligent energy supply network. The system modifies its behavior patterns, scheduling, and power consumption profiles in response to changing network conditions, transforming a static appliance into a dynamic system that continuously optimizes its operation.
Solution Approach 2:
The controller receives feedback signals from the intelligent energy supply network including dynamic pricing information and load management commands. This feedback loop enables the controller to adjust its operation, scheduling, and power consumption in real-time, creating a closed-loop control system that responds to network conditions.
2Adaptability or versatility
If household appliances preselect start times to use lower electricity tariffs, then energy cost is reduced, but flexibility in responding to rapid tariff changes and power restrictions is lost
Solution Approach 1:
The controller performs preliminary actions by preplanning multiple alternative process sequences and scheduling options before execution. It prepares contingency plans that can be rapidly activated when dynamic pricing signals or load management restrictions are received, allowing the system to respond quickly without interrupting the actual appliance operation.
Solution Approach 2:
The system dynamically adjusts its scheduling and operation in real-time based on incoming pricing signals and network conditions. Rather than following a fixed preselected schedule, the controller continuously modifies the operation timing and sequence to exploit lower tariffs and avoid restrictions, maintaining flexibility throughout the appliance's operation.
3Productivity
If household appliances operate during high electricity tariffs to maintain process continuity, then productivity is maintained, but energy consumption cost increases
Solution Approach 1:
The controller dynamically balances process continuity requirements against energy cost considerations by adjusting operation timing, power levels, and process sequences in real-time. It can maintain productivity during high-tariff periods when necessary while optimizing to minimize energy costs through intelligent scheduling and alternative process paths.
Solution Approach 2:
The system changes operational parameters such as power consumption levels, process speed, and sequencing to optimize the balance between maintaining productivity and reducing energy costs during high-tariff periods. It can operate at reduced power levels or use alternative processes that achieve the same output with lower energy consumption.
4Use of energy by moving object
If household appliances implement intelligent control with graph algorithms for dynamic energy management, then energy optimization is improved, but device complexity increases
Solution Approach 1:
The controller acts as an intermediary between the household appliance and the intelligent energy supply network. It implements the complex graph algorithm-based optimization logic while shielding the appliance's core functions from this complexity. The controller translates network signals into optimized operation commands, managing the computational complexity internally.
Solution Approach 2:
The controller autonomously performs energy optimization calculations and decision-making using graph algorithms, eliminating the need for user intervention or external control systems. It self-manages the complexity of dynamic energy management by independently analyzing pricing signals, evaluating alternative sequences, and executing optimized operation patterns.
Data Source
Figure 1~2
Figure 3
AI summary
The invention relates to a household appliance having a controller 1, 11, which has the following components: a computer-like control part 2, 12, a control part for settings data 3, 13, a control part for operating data 4, 14, and actuators 8.1 to 8.n; 18.1 to 18.n, which are actuated via amplifiers 7, 7.1 to 7.n, 17, 17.1 to 17.n, wherein data for actuating the actuators are determined from the settings data and from the operating data by the computer-like control part 2, 12, with the development that, in order to operate the controller 11 on a novel energy supply network EVN' having a data network for exchanging data via said energy supply network EVN', the computer-like control part 12 is connected to a control part 1 in that a graph algorithm is implemented, wherein it can be made possible, by means of the interaction of the control parts 12, 19, for data of the data network of the energy supply network EVN' which are present for the household appliance to be taken into account in such a manner that operation of the household appliance can be continuously operated. The invention further relates to a method for operating a controller 11 of a household appliance on a novel energy supply network EVN' with data transmission of data via said energy supply network, wherein settings data of the controller, operating data from the process of the household appliance and data from the energy supply network pass through a computer for processing in order to be able to determine control variables for actuators of the household appliance, wherein it is further provided for the computer to take into account a graph algorithm when executing the processing steps thereof, such that modified process sequences of the household appliance, which are brought about when data of the data network of the energy supply network EVN' are taken into account, can be linked to each other in such a manner that operation of the household appliance can be continuously operated.