An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System

Soetedjo, Aryuanto; Nakhoda, Yusuf Ismail; Saleh, Choirul

doi:10.3390/en12193655

Cited by 9 publications

(4 citation statements)

References 45 publications

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“…For this, the actuators usually require consumption data and status of the loads. If there are a large number of sensors in a house, separate sensor sets will be controlled by varying other actuators [24][25][26]. The actuators may be a flush-mounted device, plugs or an in-built device.…”

Section: Communications Controllers and Actuatorsmentioning

confidence: 99%

P2P, CSC and TE: A Survey on Hardware, Software and Data

et al. 2021

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Peer-to-Peer (P2P), Transactive Energy (TE) and Community Self-Consumption (CSC) are exciting energy generation and use models, offering several opportunities for prosumers, micro-grids and services to the grid; however, they require numerous components to function efficiently. Various hardware devices are required to transmit data and control the generation and consumption equipment, whereas software is needed to use the gathered information to monitor and manage the hardware and energy trading. Data can be gathered from a variety of origins from within the grid and external sources; however, these data must be well-structured and consistent to be useful. This paper sets out to gather information regarding the hardware, software and data from the several archetypes available, focusing on existing projects and trials in these areas to see what the most-common hardware, software and data components are. The result presents a concise overview of the hardware, software and data-related topics and structures within the P2P, TE and CSC energy generation and use models.

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Section: Communications Controllers and Actuatorsmentioning

confidence: 99%

P2P, CSC and TE: A Survey on Hardware, Software and Data

et al. 2021

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“…These works aim to decrease the grid working cost and maximize the real-time response in the network. (Soetedjo et al , 2019) Presented a hardware testbed for testing the building energy management system (BEMS) using MAS. Indeed, they employ both a genetic algorithm to find the optimal power required and the fuzzy logic controller to monitor the building devices.…”

Section: Related Workmentioning

confidence: 99%

An intelligent system for energy management in smart cities based on big data and ontology

Sayah

Kazar

Lejdel³

et al. 2020

SASBE

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PurposeThis research paper aims at proposing a framework based on semantic integration in Big Data for saving energy in smart cities. The presented approach highlights the potential opportunities offered by Big Data and ontologies to reduce energy consumption in smart cities.Design/methodology/approachThis study provides an overview of semantics in Big Data and reviews various works that investigate energy saving in smart homes and cities. To reach this end, we propose an efficient architecture based on the cooperation between ontology, Big Data, and Multi-Agent Systems. Furthermore, the proposed approach shows the strength of these technologies to reduce energy consumption in smart cities.FindingsThrough this research, we seek to clarify and explain both the role of Multi-Agent System and ontology paradigms to improve systems interoperability. Indeed, it is useful to develop the proposed architecture based on Big Data. This study highlights the opportunities offered when they are combined together to provide a reliable system for saving energy in smart cities.Practical implicationsThe significant advancement of contemporary applications (smart cities, social networks, health care, IoT, etc.) requires a vast emergence of Big Data and semantics technologies in these fields. The obtained results provide an improved vision of energy-saving and environmental protection while keeping the inhabitants’ comfort.Originality/valueThis work is an efficient contribution that provides more comprehensive solutions to ontology integration in the Big Data environment. We have used all available data to reduce energy consumption, promote the change of inhabitant’s behavior, offer the required comfort, and implement an effective long-term energy policy in a smart and sustainable environment.

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“…While the essence and definitions of resilience in power systems [17,18] and interdependent infrastructure systems [19] are still under development, the resilience benefits of such AI-based BMS architectures can be foreseen. The platforms that host the implementations of such multi-agent systems can vary from industrial ones to embedded devices [20]. These agent-based approaches often implement transactive energy manage-ment system concepts, where consumers are actively participating in the operation of the grid, often referred to as prosumers [21].…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of an Interoperable Architecture for Integrating Building Legacy Systems into Scalable Energy Management Systems

Ntafalias¹,

Tsakanikas²,

Skarvelis‐Kazakos

et al. 2022

Smart Cities

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The building sector is responsible for a significant amount of energy consumption and greenhouse gas (GHG) emissions. Thus, the monitoring, control and optimization of energy consumption in buildings will play a critical role in the coming years in improving energy efficiency in the building sector and in reducing greenhouse gas emissions. However, while there are a significant number of studies on how to make buildings smarter and manage energy through smart devices, there is a need for more research on integrating buildings with legacy equipment and systems. It is therefore vital to define mechanisms to improve the use of energy efficiency in existing buildings. This study proposes a new architecture (PHOENIX architecture) for integrating legacy building systems into scalable energy management systems with focus also on user comfort in the concept of interoperability layers. This interoperable and intelligent architecture relies on Artificial Intelligence/Machine Learning (AI/ML) and Internet of Things (IoT) technologies to increase building efficiency, grid flexibility and occupant well-being. To validate the architecture and demonstrate the impact and replication potential of the proposed solution, five demonstration pilots have been utilized across Europe. As a result, by implementing the proposed architecture in the pilot sites, 30 apartments and four commercial buildings with more than 400 devices have been integrated into the architecture and have been communicating successfully. In addition, six Trials were performed in a commercial building and five key performance indicators (KPIs) were measured in order to evaluate the robust operation of the architecture. Work is still ongoing for the trials and the KPIs’ analysis after the implementation of PHOENIX architecture at the rest of the pilot sites.

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An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System

Cited by 9 publications

References 45 publications

P2P, CSC and TE: A Survey on Hardware, Software and Data

P2P, CSC and TE: A Survey on Hardware, Software and Data

An intelligent system for energy management in smart cities based on big data and ontology

Design and Implementation of an Interoperable Architecture for Integrating Building Legacy Systems into Scalable Energy Management Systems

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