Reduced Data Modeling for Integrated Utility Network Control
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Solution Overview
Problem
Current measurement and regulation systems in energy, water, and gas management are designed for individual disciplines and lack integration with small renewable energy sources and consumers, leading to inefficiencies and high costs, with limited consideration for interconnectedness and environmental impact.
Innovation Solution
A system that reduces large-scale data to create digital reduced dynamic models, aggregating data from small sources and consumers to optimize energy production and consumption, using historical data to create behavioral scenarios and adjust operational parameters, with a control block, evaluation device, and decision-making block connected to a server for real-time management and regulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional measurement and regulation systems are used for individual disciplines, then system robustness is maintained, but energy efficiency and cost-effectiveness deteriorate due to lack of integration and interconnectedness
Solution Approach 1:
The patent combines multiple discipline-specific measurement and regulation systems (energy, water, gas) into an integrated digital platform that processes data from small renewable energy sources and consumers collectively. This merging enables shared infrastructure and coordinated control, improving energy efficiency while maintaining system reliability through unified monitoring and management.
Solution Approach 2:
The digital platform performs multiple functions across different utility sectors (energy production, water management, gas distribution) and serves diverse users (small RES sources, consumers, municipalities). This multi-functional approach allows a single system to address interconnectedness needs across disciplines, reducing overall energy consumption compared to separate specialized systems.
2Adaptability or versatility
If small renewable energy sources and consumers are connected to traditional systems, then energy production diversity increases, but system complexity and operational costs increase
Solution Approach 1:
The digital platform acts as an intermediary layer between small renewable energy sources/consumers and traditional utility infrastructure. It aggregates data from numerous small participants, processes it through digital twins and behavioral scenarios, and presents unified control signals to the grid. This intermediary approach enables diverse energy production without requiring complex individual connections for each small source.
Solution Approach 2:
The system creates digital twins (virtual copies) of physical energy systems, small RES sources, and consumer devices. These digital replicas enable simulation, prediction, and optimization of system behavior without physically modifying or complicating the actual infrastructure. Behavioral scenarios are generated from these copies to guide real-world operations, managing complexity through virtual modeling.
3Measurement precision
If comprehensive data collection from all system elements is performed, then measurement precision and control accuracy improve, but energy consumption and processing costs increase
Solution Approach 1:
The system extracts only the most relevant features and parameters from comprehensive raw data collected from sensors and system elements. Instead of processing all available data, the digital twin technology identifies and extracts key variables necessary for accurate modeling and control decisions. This extraction maintains measurement precision while significantly reducing computational energy consumption.
Solution Approach 2:
The system implements partial data processing by focusing computational resources on critical subsystems and time periods where precision is most needed. Behavioral scenarios are generated selectively based on system state and operational priorities rather than continuously processing all data. This partial action approach achieves sufficient measurement precision for effective control while minimizing energy consumption.
Data Source
Figure 1
AI summary
The invention relates to a system for reducing large-scale data in order to save energy and increase the efficiency of linear and non-linear operational parameter systems in network industries, including energy networks, that comprises a control block (11) for operational and design parameters of network industries, to which an evaluation device (1) interconnected with meters in a selected community or otherwise defined territory (6) and equipped with a decision block (10) to correct a numerical model from the evaluation device (1) is connected, which is connected with a server (5) to a database of values of 01-n events, provided with a procedure module (2) to which a control block (7), an evaluation local device (8) and a reduced procedure module (9) are connected, wherein the reduced procedure module (9) is connected via a reconstruction block (3) to the decision block (10), and the evaluation local device (8) is connected to the evaluation device (1) and the output to the control block (7). The network industry is generalized from the group of electricity network, water supply network, gas supply network, heat supply network, sewerage, transport, and lighting.