A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema

This paper introduces a portable framework for developing, scaling and maintaining energy management and information systems (EMIS) applications using an ontology-based approach. Key contributions include an interoperable layer based on Brick schema, the formalization of application constraints pertaining metadata and data requirements, and a field demonstration. The framework allows for querying metadata models, fetching data, preprocessing, and analyzing data, thereby offering a modular and flexible workflow for application development. Its effectiveness is demonstrated through a case study involving the development and implementation of a data-driven anomaly detection tool for the photovoltaic systems installed at the Politecnico di Torino, Italy. During eight months of testing, the framework was used to tackle practical challenges including: (i) developing a machine learning-based anomaly detection pipeline, (ii) replacing data-driven models during operation, (iii) optimizing model deployment and retraining, (iv) handling critical changes in variable naming conventions and sensor availability (v) extending the pipeline from one system to additional ones. • A portable framework for EMIS applications development is proposed. • An interoperable layer using Brick metadata schema is exploited in the framework. • The framework was validated implementing an anomaly detection tool for PV systems. • Typical real-life EMIS implementation and deployment issues were addressed. • The framework was publicly shared as an open-source Python package.

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Publication Details

Journal
Energy and Buildings
Published
2024-09-13
DOI
https://doi.org/10.1016/j.enbuild.2024.114802
Citations
8
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
2.79

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article

A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema

Roberto Chiosa, Alfonso Capozzoli, Marco Savino Piscitelli, Marco Pritoni
8 citations
Energy and Buildings
Distributed and Parallel Computing Systems
2.79
article

A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema

Roberto Chiosa, Alfonso Capozzoli, Marco Savino Piscitelli, Marco Pritoni
article en
8 citations

Abstract

This paper introduces a portable framework for developing, scaling and maintaining energy management and information systems (EMIS) applications using an ontology-based approach. Key contributions include an interoperable layer based on Brick schema, the formalization of application constraints pertaining metadata and data requirements, and a field demonstration. The framework allows for querying metadata models, fetching data, preprocessing, and analyzing data, thereby offering a modular and flexible workflow for application development. Its effectiveness is demonstrated through a case study involving the development and implementation of a data-driven anomaly detection tool for the photovoltaic systems installed at the Politecnico di Torino, Italy. During eight months of testing, the framework was used to tackle practical challenges including: (i) developing a machine learning-based anomaly detection pipeline, (ii) replacing data-driven models during operation, (iii) optimizing model deployment and retraining, (iv) handling critical changes in variable naming conventions and sensor availability (v) extending the pipeline from one system to additional ones. • A portable framework for EMIS applications development is proposed. • An interoperable layer using Brick metadata schema is exploited in the framework. • The framework was validated implementing an anomaly detection tool for PV systems. • Typical real-life EMIS implementation and deployment issues were addressed. • The framework was publicly shared as an open-source Python package.

Energy and BuildingsVol. 323
Lawrence Berkeley National Laboratory (US), Politecnico di Torino (IT)
U.S. Department of Energy, Politecnico di Torino
Affordable and clean energy
Openalex Percentile: Top 9%
Distributed and Parallel Computing Systems
2.79
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