Adaptive Energy Flow Control With Dynamic Model Updating
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Solution Overview
Problem
Existing energy management systems struggle to adapt dynamically to individual energy source and consumer conditions, leading to inefficiencies in energy flow regulation and increased costs.
Innovation Solution
A control system comprising a control unit, energy flow meters, and a modeling unit that adjusts energy flows based on real-time data, a predetermined control strategy, and a dynamic energy flow model, allowing for quick adaptation to changes and external influences, with the ability to set various objectives such as cost minimization or energy storage optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing energy management systems are used to regulate energy flows, then energy flow control is achieved, but the systems cannot adapt dynamically to individual energy source and consumer conditions
Solution Approach 1:
The energy flow model is designed to be dynamic and continuously adaptable. The modeling unit updates the energy flow model based on recorded data from energy flow meters, allowing the system to adapt to changing conditions of energy sources and consumers. This dynamic modeling approach enables the system to adjust to individual energy conditions without requiring complete system redesign.
Solution Approach 2:
The system performs self-adjustment through automated model updating. The modeling unit automatically compares recorded energy flow data with expected data from the current energy flow model, detects deviations, and determines updated models without manual intervention. This self-service capability enables dynamic adaptation while keeping operational complexity manageable.
2Adaptability or versatility
If a dynamic energy flow model with continuous data recording is implemented, then adaptability improves, but device complexity increases
Solution Approach 1:
The system implements continuous feedback loops where energy flow meters record actual energy flows, the control unit compares these with expected values from the energy flow model, and the modeling unit updates the model based on detected deviations. This structured feedback mechanism enables dynamic adaptation through systematic data processing rather than complex ad-hoc adjustments.
Solution Approach 2:
The energy flow model is prepared in advance with expected data patterns for different energy sources and consumers. By having pre-established model structures and comparison criteria ready before operation, the system reduces the complexity of real-time decision-making while maintaining high adaptability to changing conditions.
3Adaptability or versatility
If multiple control strategies are implemented for different objectives, then versatility improves, but ease of operation deteriorates
Solution Approach 1:
The control system is designed with a universal architecture that can accommodate multiple control strategies (cost minimization, energy independence, load balancing, etc.) through a single configurable framework. The modeling unit and control unit work together with a unified data processing approach that supports various objectives without requiring separate system instances, thereby maintaining ease of operation while providing versatility.
Data Source
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AI summary
The invention relates to a control system (100) for regulating energy flows (105) within an overall system (110) consisting of a plurality of energy sources (120) and a plurality of energy consumers (130). For this purpose, the control system comprises a control unit (140) with a plurality of AC/DC interfaces (142) for receiving and adjusting the energy flows within the overall system, and with a plurality of signal interfaces (144) for acquiring data (145) from the overall system. Furthermore, the control system comprises a plurality of energy flow meters (150) and a modeling unit (160). The modeling unit is connected to the control unit via data transmission and is configured to determine a number of adjustments (170) to be made to the energy flows, based on the acquired data from the overall system, a predetermined control strategy (162), and a current energy flow model (164), and to output these adjustments to the control unit.The modeling unit is designed to compare the recorded data at least partially with data previously expected according to the current energy flow model and, depending on this comparison, to determine a new current energy flow model (165) and apply it to the recorded data.