Resource Management Device and Method for Managing or Distributing a Physical Resource

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This invention describes a resource management device and method that automates the management and distribution of physical resources (such as energy, water, gas, or oil) in an industrial setup with multiple participants (like machines, sources, and storage units). The system utilizes self-descriptions from each participant, prioritizes various optimization targets (e.g., cost, limits, profiles), selects an optimal management strategy (including learning-based methods), and dynamically configures itself with minimal manual intervention. It can adapt to changes in participants or optimization targets, automatically updating strategies using machine learning and hierarchical modular agents to maximize efficiency and flexibility.

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• Energy management systems in industrial plants to optimize electricity, heat, or gas usage.
• Smart grid control for balancing energy from diverse and fluctuating sources (like solar, wind, traditional generators, batteries).
• Automated building management systems adjusting power and water consumption according to usage patterns or price signals.
• Water distribution networks optimizing flow and storage according to demand and supply fluctuations.
• Manufacturing plants coordinating machines, energy sources, and storage for cost and production optimization.
• Industrial Internet of Things (IIoT) implementations managing connected resources with minimal human configuration.
• Facilities with frequent equipment changes or reconfigurations needing automatic integration and optimization of new devices.

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• Significantly reduces manual configuration effort by automatically integrating new participants and updating system configurations as needed.
• Increases operational flexibility and scalability, enabling rapid adaptation to changing requirements, constraints, or market signals.
• Reduces error rates as less manual intervention is required, lowering risk of human-induced mistakes.
• Supports both real and simulated (virtual) environments, allowing for safe testing and optimization before deploying changes to live systems.
• Leverages machine learning (including reinforcement learning) to continually improve performance and adapt strategies for optimal resource usage.
• Provides modular and hierarchical architecture, enhancing transparency, maintainability, and integration with existing or legacy systems.
• Enables cost savings by identifying and applying optimal resource allocation strategies (such as peak load management, price-based operation, or adherence to specific contractual models).
• Does not require deep expert knowledge for day-to-day operations, democratizing advanced resource management for a wider range of users.

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Patent Abstract

Es wird eine Ressourcenmanagementvorrichtung zum Verwalten oder Verteilen einer physikalischen Ressource in einer Anlage mit mehreren Teilnehmern vorgeschlagen, wobei jeder Teilnehmer eingerichtet ist, mit der physikalischen Ressource zu wechselwirken oder die physikalische Ressource zu verändern. Die Ressourcenmanagementvorrichtung umfasst:eine Konfigurationseinheit, die eingerichtet ist, auf Basis mehrerer teilnehmer-spezifischen Selbstbeschreibungen, Konfigurationsinformationen bereitzustellen,eine Priorisierungseinheit, die eingerichtet ist, auf Basis mehrerer Optimierungsvorgaben zumindest eine bestimmte Optimierungsvorgabe auszuwählen,eine Strategieeinheit, die eingerichtet ist, aus mehreren bereitgestellten Optimierungsstrategien eine bestimmte Optimierungsstrategie festzulegen, wobei die Festlegung auf Basis der Konfigurationsinformationen sowie der bestimmten Optimierungsvorgabe erfolgt,eine Optimierungseinheit, die eingerichtet ist, die Anlage unter Verwendung der festgelegten Optimierungsstrategie unter Ausführung einer Aktion an der Anlage anzusteuern und eine Belohnungsfunktion als Ergebnis der Ansteuerung der Anlage zu ermitteln, wobei die Aktion eine veränderte Ansteuerung und/oder eine Veränderung der Konfiguration der Anlage umfasst.