Integration of Legacy Appliances into Home Energy Management Systems

The progressive installation of renewable energy sources requires the coordination of energy consuming devices. At consumer level, this coordination can be done by a home energy management system (HEMS). Interoperability issues need to be solved among smart appliances as well as between smart and non-smart, i.e., legacy devices. We expect current standardization efforts to soon provide technologies to design smart appliances in order to cope with the current interoperability issues. Nevertheless, common electrical devices affect energy consumption significantly and therefore deserve consideration within energy management applications. This paper discusses the integration of smart and legacy devices into a generic system architecture and, subsequently, elaborates the requirements and components which are necessary to realize such an architecture including an application of load detection for the identification of running loads and their integration into existing HEM systems. We assess the feasibility of such an approach with a case study based on a measurement campaign on real households. We show how the information of detected appliances can be extracted in order to create device profiles allowing for their integration and management within a HEMS

Practical Application of a Multi-Agent Systems Society for Energy Management and Control

Power and energy systems lack decision-support systems that enable studying big problems as a whole. The interoperability between multi-agent systems that address specific parts of the global problem is essential. Ontologies ease interoperability between heterogeneous systems providing semantic meaning to the information exchanged between the various parties. This paper presents the practical application of a society of multi-agent systems, which uses ontologies to enable the interoperability between different types of agent-based simulators, directed to the simulation and operation of electricity markets, smart grids and residential energy management. Real data-based demonstration shows the proposed approach advantages in enabling comprehensive, autonomous and intelligent power system simulation studies.This work has been developed under the MAS-SOCIETY project - PTDC/EEI-EEE/28954/2017 and has received funding from UID/EEA/00760/2019, funded by FEDER Funds through COMPETE and by National Funds through FCTinfo:eu-repo/semantics/publishedVersio

Exploiting Semantic Technologies in Smart Environments and Grids: Emerging Roles and Case Studies

Semantic technologies are currently spreading across several application domains as a reliable and consistent mean to address challenges related to organization, manipulation, visualization and exchange of data and knowledge. Different roles are actually played by these techniques depending on the application domain, on the timing constraints, on the distributed nature of applications, and so on. This paper provides an overview of the roles played by semantic technologies in the domain of smart grids and smart environments, with a particular focus on changes brought by such technologies in the adopted architectures, programming techniques and tools. Motivations driving the adoption of semantics in these different, but strictly intertwined, fields are introduced using a strong application-driven perspective. Two real-world case studies in smart grids and smart environments are presented to exemplify the roles covered by such technologies and the changes they fostered in software engineering processes. Learned lessons are then distilled and future adoption scenarios discussed

TOOCC: Enabling heterogeneous systems interoperability in the study of energy systems

The environmental impact and the scarcity of limited fossil fuels led to the need of investment in energy based on renewable sources. This has driven Europe to implement several policies that changed the energy market's paradigm, namely the incentive to microgeneration. The penetration of energy sources from intermittent nature has increased the unpredictability of the system, which makes simulation and analysis tools essential in order to provide decision support to entities in this sector. This paper presents the Tools Control Center (TOOCC) as a solution to increase the interoperability between heterogeneous agent-based systems, in the energy field. The proposed approach acts as a facilitator in the interaction between different systems through the usage of ontologies, allowing them to communicate in the same language. To understand the real applicability of this tool, a case study is presented concerning the interaction between several systems, with the purpose of enabling the energy resource scheduling of a microgrid, and the reaction of a house managed by a house management system.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAM-GO) and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.info:eu-repo/semantics/publishedVersio

BRICKS: Building’s reasoning for intelligent control knowledge-based system

Building energy management systems have been largely implemented, focusing on specific domains. When installed together, they lack interoperability to make them work correctly and to achieve a centralized user interface. The Building's Reasoning for Intelligent Control Knowledge-based System (BRICKS) overcomes these issues by developing an interoperable building management system able to aggregate different interest domains. It is a context-aware semantic rule-based system for intelligent management of buildings' energy and security. Its output can be a set of alarms, notifications, or control actions to take. BRICKS itself, and its features are the innovative contribution of the present paper. It is very important for buildings' energy management, namely in the scope of demand response programs. In this paper, it is shown how semantics is used to enable the knowledge exchange between different devices, algorithms, and models, without the need for reprogramming the system. A scenario is deployed in a real building for demonstration.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066) and from FEDER Funds through COMPETE program and from National Funds through FCT under the projects UID/EEA/00760/2019, PTDC/EEI-EEE/28954/2017 (MAS-Society), and SFRH/BD/118487/2016.info:eu-repo/semantics/publishedVersio

Ontologies for the Interoperability of Heterogeneous Multi-Agent Systems in the scope of Energy and Power Systems

Tesis por compendio de publicaciones[ES]El sector eléctrico, tradicionalmente dirigido por monopolios y poderosas empresas de servicios públicos, ha experimentado cambios significativos en las últimas décadas. Los avances más notables son una mayor penetración de las fuentes de energía renovable (RES por sus siglas en inglés) y la generación distribuida, que han llevado a la adopción del paradigma de las redes inteligentes (SG por sus siglas en inglés) y a la introducción de enfoques competitivos en los mercados de electricidad (EMs por sus siglas en inglés) mayoristas y algunos minoristas. Las SG emergieron rápidamente de un concepto ampliamente aceptado en la realidad. La intermitencia de las fuentes de energía renovable y su integración a gran escala plantea nuevas limitaciones y desafíos que afectan en gran medida las operaciones de los EMs. El desafiante entorno de los sistemas de potencia y energía (PES por sus siglas en inglés) refuerza la necesidad de estudiar, experimentar y validar operaciones e interacciones competitivas, dinámicas y complejas. En este contexto, la simulación, el apoyo a la toma de decisiones, y las herramientas de gestión inteligente, se vuelven imprescindibles para estudiar los diferentes mecanismos del mercado y las relaciones entre los actores involucrados. Para ello, la nueva generación de herramientas debe ser capaz de hacer frente a la rápida evolución de los PES, proporcionando a los participantes los medios adecuados para adaptarse, abordando nuevos modelos y limitaciones, y su compleja relación con los desarrollos tecnológicos y de negocios. Las plataformas basadas en múltiples agentes son particularmente adecuadas para analizar interacciones complejas en sistemas dinámicos, como PES, debido a su naturaleza distribuida e independiente. La descomposición de tareas complejas en asignaciones simples y la fácil inclusión de nuevos datos y modelos de negocio, restricciones, tipos de actores y operadores, y sus interacciones, son algunas de las principales ventajas de los enfoques basados en agentes. En este dominio, han surgido varias herramientas de modelado para simular, estudiar y resolver problemas de subdominios específicos de PES. Sin embargo, existe una limitación generalizada referida a la importante falta de interoperabilidad entre sistemas heterogéneos, que impide abordar el problema de manera global, considerando todas las interrelaciones relevantes existentes. Esto es esencial para que los jugadores puedan aprovechar al máximo las oportunidades en evolución. Por lo tanto, para lograr un marco tan completo aprovechando las herramientas existentes que permiten el estudio de partes específicas del problema global, se requiere la interoperabilidad entre estos sistemas. Las ontologías facilitan la interoperabilidad entre sistemas heterogéneos al dar un significado semántico a la información intercambiada entre las distintas partes. La ventaja radica en el hecho de que todos los involucrados en un dominio particular los conocen, comprenden y están de acuerdo con la conceptualización allí definida. Existen, en la literatura, varias propuestas para el uso de ontologías dentro de PES, fomentando su reutilización y extensión. Sin embargo, la mayoría de las ontologías se centran en un escenario de aplicación específico o en una abstracción de alto nivel de un subdominio de los PES. Además, existe una considerable heterogeneidad entre estos modelos, lo que complica su integración y adopción. Es fundamental desarrollar ontologías que representen distintas fuentes de conocimiento para facilitar las interacciones entre entidades de diferente naturaleza, promoviendo la interoperabilidad entre sistemas heterogéneos basados en agentes que permitan resolver problemas específicos de PES. Estas brechas motivan el desarrollo del trabajo de investigación de este doctorado, que surge para brindar una solución a la interoperabilidad de sistemas heterogéneos dentro de los PES. Las diversas aportaciones de este trabajo dan como resultado una sociedad de sistemas multi-agente (MAS por sus siglas en inglés) para la simulación, estudio, soporte de decisiones, operación y gestión inteligente de PES. Esta sociedad de MAS aborda los PES desde el EM mayorista hasta el SG y la eficiencia energética del consumidor, aprovechando las herramientas de simulación y apoyo a la toma de decisiones existentes, complementadas con las desarrolladas recientemente, asegurando la interoperabilidad entre ellas. Utiliza ontologías para la representación del conocimiento en un vocabulario común, lo que facilita la interoperabilidad entre los distintos sistemas. Además, el uso de ontologías y tecnologías de web semántica permite el desarrollo de herramientas agnósticas de modelos para una adaptación flexible a nuevas reglas y restricciones, promoviendo el razonamiento semántico para sistemas sensibles al contexto

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements

Ontologies to Enable Interoperability of Multi-Agent Electricity Markets Simulation and Decision Support

This paper presents the AiD-EM Ontology, which provides a semantic representation of the concepts required to enable the interoperability between multi-agent-based decision support systems, namely AiD-EM, and the market agents that participate in electricity market simulations. Electricity markets’ constant changes, brought about by the increasing necessity for adequate integration of renewable energy sources, make them complex and dynamic environments with very particular characteristics. Several modeling tools directed at the study and decision support in the scope of the restructured wholesale electricity markets have emerged. However, a common limitation is identified: the lack of interoperability between the various systems. This gap makes it impossible to exchange information and knowledge between them, test different market models, enable players from heterogeneous systems to interact in common market environments, and take full advantage of decision support tools. To overcome this gap, this paper presents the AiD-EM Ontology, which includes the necessary concepts related to the AiD-EM multi-agent decision support system, to enable interoperability with easier cooperation and adequate communication between AiD-EM and simulated market agents wishing to take advantage of this decision support toolThis work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276), from FEDER Funds through COMPETE program and from National Funds through (FCT) under projects CEECIND/01811/2017 and UID/EEA/00760/2019. Gabriel Santos was supported by the PhD grant SFRH/BD/118487/2016 from National Funds through FCTinfo:eu-repo/semantics/publishedVersio

Smart City Ontologies and Their Applications: A Systematic Literature Review

The increasing interconnections of city services, the explosion of available urban data, and the need for multidisciplinary analysis and decision making for city sustainability require new technological solutions to cope with such complexity. Ontologies have become viable and effective tools to practitioners for developing applications requiring data and process interoperability, big data management, and automated reasoning on knowledge. We investigate how and to what extent ontologies have been used to support smart city services and we provide a comprehensive reference on what problems have been addressed and what has been achieved so far with ontology-based applications. To this purpose, we conducted a systematic literature review finalized to presenting the ontologies, and the methods and technological systems where ontologies play a relevant role in shaping current smart cities. Based on the result of the review process, we also propose a classification of the sub-domains of the city addressed by the ontologies we found, and the research issues that have been considered so far by the scientific community. We highlight those for which semantic technologies have been mostly demonstrated to be effective to enhance the smart city concept and, finally, discuss in more details about some open problems