MATRYCS Toolbox is a cloud-based data analytics platform revolutionising building data management. It enables reliable policymaking, innovative data analytics services, and safe operations. Utilising AI-driven ML/DL algorithms, it analyzes diverse data sources for statistical insights and predictive modeling. A game-changing solution for energy efficiency and sustainability for the energy and building sector.
Key Features:
S1.1 Energy Prediction: The Energy Prediction service (S1.1) leverages predictive algorithms to monitor and forecast the energy performance of buildings and photovoltaic plants. By processing time series data from various sources, the service provides accurate predictions using ML/DL models, ensuring optimal algorithm selection for maximum accuracy. S1.1 can be used independently or as input for advanced applications like Building Automation and Control and Network Optimization.
S1.2 Building Automation and Control: The Building Automation and Control (BAC) service (S1.2) offers centralized and automated monitoring and control of a building's subsystems. This includes heating, cooling, ventilation, lighting, and more, optimizing energy performance while maintaining thermal comfort. The service provides energy efficiency indicators and identifies anomalies, enabling effective energy management and suggesting action plans for enhanced efficiency.
S1.3 KPIs Calculation: S1.3 estimates energy demand, consumption and CO2 emissions for buildings based on simplified models and various data sources. It uses geometric parameters, climate data and building characteristics to provide KPIs at different scales: building, district, municipality and province.
S1.4 TBM Services: The Technical Building Management service supports preventive and predictive maintenance at building and district levels. It detects anomalies, performs cross-correlation based diagnostics, and ensures efficient system maintenance, including PV plants and DHN systems.
S1.5 Optimisation for Network Operation: This service focuses on district heating and local electricity network optimization. It uses neural networks to simulate district heating network operation based on demand forecasts. For the local electricity network, a user-friendly application schedules electrical loads based on predicted energy production and consumption balances using a parameterized genetic algorithm.
S2.1 Technologies Catalogues: The service provides standardized technology catalogues for optimal building and zone-level solutions. It allows users to select potential replacements or new technologies based on energy systems and technologies installed in buildings or districts.
S3.1 SECAPs Decision Making Support: This service aids policymakers in climate change initiatives and action plans. It offers data visualization tools and insights on cities' emissions, energy consumption, and mitigation actions, helping identify areas for improvement.
S3.2 EPC Harmonization and Compliance: The service combines Energy Performance Certificates (EPCs) with open data to estimate energy demand/consumption and detect deviations in EPC parameters. It also provides a search engine for suggested energy conservation measures.
S3.3 National and EU Policy Impacts Assessment and Support: Using ML, this service estimates energy savings and provides optimal budget allocation proposals based on portfolio optimization, supporting data-driven policy making and impact assessment for energy-efficient buildings.
S4.1 Measurement and Verification of Energy Savings: Compliant with the International Performance Measurement and Verification Protocol (IPMVP), this service calculates energy and cost savings after energy efficiency measures are implemented in buildings.
S4.2 Financing of Energy Efficiency Refurbishments: This web-based platform bridges the gap between building owners seeking energy efficiency upgrades and investors looking to support such projects. It uses blockchain technology for data validation and trustworthiness.
Additional Functionalities:
- Digital Twin: Offers 3D digital models of buildings at different scales to support the implementation of energy services.
- Geoclustering Tool: Enables building stock performance evaluation and analysis using cluster techniques.
- Reasoning Engine: Extracts logical consequences from asserted facts and axioms to provide standardized physical, virtual, and logical asset information.
- Visualisation Engine: Empowers users with advanced visualizations and reports on flexible dashboards to analyze and optimize building data.
Please contact us and meet MATRYCS toolbox potential!