Automated Energy Management for Industrial Automation Systems
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Solution Overview
Problem
Complex industrial systems require manual startup and shutdown due to intricate component interactions, leading to significant energy wastage during downtimes, with no existing technical solution for automated energy-saving state management.
Innovation Solution
A method and device that automatically determine component parameters by measuring energy consumption across various states and transitions, allowing for systematic control and switching to energy-saving states based on dependencies between components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual startup and shutdown procedures are used to ensure proper sequencing of components, then system reliability is maintained, but energy consumption increases significantly during downtimes
Solution Approach 1:
The system performs self-characterization by automatically determining state transition times and energy consumptions without external intervention. The control device autonomously controls components through predefined state models and sequences, enabling the system to manage its own startup and shutdown processes while optimizing energy consumption.
Solution Approach 2:
The invention changes the operational parameters by introducing energy-saving states (standby, sleep modes) with different energy consumption levels and transition times. The system dynamically selects between multiple possible states and transitions based on energy optimization criteria while maintaining operational reliability.
2Productivity
If automated control is implemented to reduce manual effort, then productivity increases, but device complexity increases due to additional control mechanisms
Solution Approach 1:
The control device serves multiple functions: it characterizes the system by determining state transition parameters, stores characterization data, plans energy-saving states, and executes automated control sequences. This multi-functionality reduces the need for separate dedicated systems while maintaining automation capabilities.
Solution Approach 2:
The system performs preliminary characterization during initial operation to gather state transition data and energy consumption information. This pre-acquired knowledge is stored and used for subsequent automated control decisions, eliminating the need for complex real-time analysis during actual startup and shutdown operations.
3Loss of energy
If energy-saving states are introduced to reduce energy consumption, then energy efficiency improves, but system adaptability decreases due to limited state options
Solution Approach 1:
The system dynamically adapts between multiple energy-saving states (standby, sleep modes with different consumption levels) and operational states based on current requirements. The control device can select from various predefined sequences and states, providing flexibility while maintaining energy efficiency. The state model allows dynamic transitions tailored to specific operational contexts.
Data Source
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AI summary
Industrial systems, also known as automation systems are used for automatically producing products and for automatically carrying out processes. The starting up and shutting down of said type of complex system is a process which lasts for a long period of time and is preformed manually because the interaction of the components is too complex to explicitly program an execution sequence. In general it is not known how high the actual energy consumption of the individual components in different modes is. The aim of the invention is to provide a method by means of which it is possible to determine said values for the components, in particular in automations systems. For the modes and mode transitions of the components, operational scenarios adapted to the system structure are carried out and the energy consumption of the component(s) is measured. Said information which is later used when necessary for switching is input into the system model and is used for calculating suitable switching sequences, in particular for switching the system into an energy-saving mode. Said information contains, for example, the power consumptions of the individual components in different modes, and the times and the charge paths for respective mode transitions in the components.