A Multi-Agent NILM Architecture for Event Detection and Load Classification
André Eugenio Lazzaretti,
Douglas Paulo Bertrand Renaux,
Carlos Raimundo Erig Lima,
Bruna Machado Mulinari,
Hellen Cristina Ancelmo,
Elder Oroski,
Fabiana Pöttker,
Robson Ribeiro Linhares,
Lucas da Silva Nolasco,
Lucas Tokarski Lima,
Júlio Shigeaki Omori,
Rodrigo Braun dos Santos
Affiliations
André Eugenio Lazzaretti
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Douglas Paulo Bertrand Renaux
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Carlos Raimundo Erig Lima
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Bruna Machado Mulinari
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Hellen Cristina Ancelmo
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Elder Oroski
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Fabiana Pöttker
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Robson Ribeiro Linhares
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Lucas da Silva Nolasco
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Lucas Tokarski Lima
LIT—Laboratory of Innovation and Technology in Embedded Systems and Energy, Universidade Tecnológica Federal do Paraná—UTFPR, Sete de Setembro, 3165, Curitiba 80230-901, Brazil
Júlio Shigeaki Omori
COPEL—Companhia Paranaense de Energia, José Izidoro Biazetto, 158, Curitiba 82305-100, Brazil
Rodrigo Braun dos Santos
COPEL—Companhia Paranaense de Energia, José Izidoro Biazetto, 158, Curitiba 82305-100, Brazil
A multi-agent architecture for a Non-Intrusive Load Monitoring (NILM) solution is presented and evaluated. The underlying rationale for such an architecture is that each agent (load event detection, feature extraction, and classification) outperforms others of the same type in particular scenarios; hence, by combining the expertise of these agents, the system presents an improved performance. Known NILM algorithms, as well as new algorithms, proposed by the authors, were individually evaluated and compared. The proposed architecture considers a NILM system composed of Load Monitoring Modules (LMM) that report to a Center of Operations, required in larger facilities. For the purposed of evaluating and comparing performance, five load event detect agents, five feature extraction agents, and five classification agents were studied so that the best combinations of agents could be implemented in LMMs. To evaluate the proposed system, the COOLL and the LIT-Dataset were used. Performance improvements were detected in all scenarios, with power-ON and power-OFF detection improving up to 13%, while classification accuracy improved up to 9.4%.
