Affiliation:
1. Department of Engineering, University of Almeria, ceiA3, 04120 Almeria, Spain
Abstract
In the context of the global energy sector’s increasing reliance on fossil fuels and escalating environmental concerns, there is an urgent need for advancements in energy monitoring and optimization. Addressing this challenge, the present study introduces the Open Multi Power Meter, a novel open hardware solution designed for efficient and precise electrical measurements. This device is engineered around a single microcontroller architecture, featuring a comprehensive suite of measurement modules interconnected via an RS485 bus, which ensures high accuracy and scalability. A significant aspect of this development is the integration with the Non-Intrusive Load Monitoring Toolkit, which utilizes advanced algorithms for energy disaggregation, including Combinatorial Optimization and the Finite Hidden Markov Model. Comparative analyses were performed using public datasets alongside commercial and open hardware monitors to validate the design and capabilities of this device. These studies demonstrate the device’s notable effectiveness, characterized by its simplicity, flexibility, and adaptability in various energy monitoring scenarios. The introduction of this cost-effective and scalable tool marks a contribution to the field of energy research, enhancing energy efficiency practices. This research provides a practical solution for energy management and opens advancements in the field, highlighting its potential impact on academic research and real-world applications.
Reference54 articles.
1. A review on recent sizing methodologies of hybrid renewable energy systems;Lian;Energy Convers. Manag.,2019
2. Urban Design to Achieving the Sustainable Energy of Residential Neighbourhoods in Arid Climate;Juaidi;J. Clean. Prod.,2019
3. Alcayde, A., Robalo, I., Montoya, F.G., and Manzano-Agugliaro, F. (2022). SCADA System for Online Electrical Engineering Education. Inventions, 7.
4. Energy Management in the Smart Grid: State-of-the-Art and Future Trends;Meliani;Int. J. Eng. Bus. Manag.,2021
5. MO-NILM: A Multi-Objective Evolutionary Algorithm for NILM Classification;Machlev;Energy Build.,2019
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