SCADA Office Building Implementation in the Context of an Aggregator

This paper at first presents an aggregation model including optimization tools for optimal resource scheduling and aggregating, and then, it proposes a real implemented SCADA system in an office building for decision support techniques and participating in demand response events. The aggregator model controls and manages the consumption and generation of customers by establishing contract with them. The SCADA based office building presented in this paper is considered as a customer of proposed aggregation model. In the case study, a distribution network with 21 buses, including 20 consumers and 26 distributed generations, is proposed for the aggregator network, and optimal resource scheduling of aggregator, and performance of implemented SCADA system for the office building, will be surveyed. The scientific contribution of this paper is to address from an optimization-based aggregator model to a SCADA based customer.This work has received funding from the Projects: NetEffiCity (ANI|P2020 18015); FEDER Funds through COMPETE program; National Funds through FCT under project UID/EEA/00760/2013; H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794).info:eu-repo/semantics/publishedVersio

Air conditioner consumption optimization in an office building considering user comfort

The rapid growth of energy consumption and its consequences in the last decades, made the world persuaded to energy optimization and energy management. Therefore, producers and prosumers should be equipped with the automation infrastructures to perform the management programs, such as demand response programs. Office buildings are considering as a proper case for implementing energy consumption minimization since they are responsible for a huge portion of total energy consumption in the world. This paper proposes a multi-period optimization algorithm implemented in Supervisory Control and Data Acquisition system of an office building. The developed optimization algorithm is an efficient solution considered for minimizing the power consumption of air conditioners by considering the user comfort constraints. Two determinative parameters are defined to prevent over-power reduction from certain devices. In order to respect to user preferences, priority numbers are dedicated to each air conditioner to present the importance of each device. A case study with several scenarios is implemented to verify the performance of the proposed algorithm in real life using real data of the building. The obtained results show the impacts of proposed parameters and different comfort constraints of algorithm while the main target of the optimization has been reached.The present work was done and funded in the scope of the following projects: MAS-Society Project PTDC/EEI-EEE/28954/2017 and UID/EEA/00760/2019 funded by FEDER, Spain Funds through COMPETE program and byNational Funds through FCT, Portugal.info:eu-repo/semantics/publishedVersio

Lighting Consumption Optimization in a SCADA Model of Office Building Considering User Comfort Level

Due to the high penetration of the buildings in energy consumption, the use of optimization algorithms plays a key role. Therefore, all the producers and prosumers should be equipped with the automation infrastructures as well as intelligent decision algorithms, in order to perform the management programs, like demand response. This paper proposes a multi-period optimization algorithm implemented in a multi-agent Supervisory Control and Data Acquisition system of an office building. The algorithm optimizes the lighting power consumption of the building considering the user comfort constraints. A case study is implemented in order to validate and survey the performance of the implemented optimization algorithm using real consumption data of the building. The outcomes of the case study show the great impact of the user comfort constraints in the optimization level by respect to the office user’s preferences.The present work was done and funded in the scope of the following projects: COLORS Project PTDC/EEI-EEE/28967/2017 and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Using a Specification-based Intrusion Detection System to Extend the DNP3 Protocol with Security Functionalities

Modern SCADA systems are increasingly adopting Internet technologies to control distributed industrial assets. As proprietary communication protocols are increasingly being used over public networks without efficient protection mechanisms, it is increasingly easier for attackers to penetrate into the communication networks of companies that operate electrical power grids, water plants, and other critical infrastructure systems. To provide protection against such attacks without changing legacy configurations, SCADA systems require an intrusion detection technique that can understand information carried by network traffic based on proprietary SCADA protocols. To achieve that goal, we adapted Bro, a specification-based intrusion detection system, for SCADA protocols in our previous work. In that work, we built into Bro a new parser to support DNP3, a complex proprietary network protocol that is widely used in SCADA systems for electrical power grids. The built-in parser provides clear visibility of network events related to SCADA systems. The semantics associated with the events provide us with a fine-grained operational context of the SCADA system, including types of operations and their parameters. Based on such information, we propose in this work two security policies to perform authentication and integrity checking on observed SCADA network traffic. To evaluate the proposed security policies, we simulated SCADA-specific attack scenarios in a test-bed, including real proprietary devices used in an electrical power grid. Experiments showed that the proposed intrusion detection system with the security policies can work efficiently in a large industry control environment that can include approximately 4000 devices.U.S. Department of Energy / DE-OE0000097National Science Foundation / OCI-1032889Infosys LimitedThe Boeing CompanyOpe

Power Systems Simulation Using Ontologies to Enable the Interoperability of Multi-Agent Systems

A key challenge in the power and energy field is the development of decision-support systems that enable studying big problems as a whole. The interoperability between systems that address specific parts of the global problem is essential. Ontologies ease the interoperability between heterogeneous systems providing semantic meaning to the information exchanged between the various parties. The use of ontologies within Smart Grids has been proposed based on the Common Information Model, which defines a common vocabulary describing the basic components used in electricity transportation and distribution. However, these ontologies are focused on utilities needs. The development of ontologies that allow the representation of diverse knowledge sources is essential, aiming at supporting the interaction between entities of different natures, facilitating the interoperability between these systems. This paper proposes a set of ontologies to enable the interoperability between different types of simulators, namely regarding electricity markets, the smart grid, and residential energy management. A case study based on real data shows the advantages of the proposed approach in enabling comprehensive power system simulation studies.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 703689 (project ADAPT), from the EUREKA - ITEA2 Project M2MGrids (ITEA-13011), Project SIMOCE (ANI—P2020 17690), and has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.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

Sequential Tasks Shifting for Participation in Demand Response Programs

In this paper, the proposed methodology minimizes the electricity cost of a laundry room by means of load shifting. The laundry room is equipped with washing machines, dryers, and irons. Additionally, the optimization model handles demand response signals, respecting user preferences while providing the required demand reduction. The sequence of devices operation is also modeled, ensuring correct operation cycles of different types of devices which are not allowed to overlap or have sequence rules. The implemented demand response program specifies a power consumption limit in each period and offers discounts for energy prices as incentives. In addition, users can define the required number of operations for each device in specific periods, and the preferences regarding the operation of consecutive days. In the case study, results have been obtained regarding six scenarios that have been defined to survey about effects of different energy tariffs, power limitations, and incentives, in a laundry room equipped with three washing machines, two dryers, and one iron. A sensitivity analysis of the power consumption limit is presented. The results show that the proposed methodology is able to accommodate the implemented scenario, respecting user preferences and demand response program, minimizing energy costs. The final electricity price has been calculated for all scenarios to discuss the more effective schedule in each scenario.This work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224), in the scope of ITEA 3 SPEAR Project 16001 and from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and CEECIND/02887/2017.info:eu-repo/semantics/publishedVersio

Application of demand response programs for peak reduction using load aggregator

O aumento do consumo de energia requer atenção. Os especialistas propuseram muitas soluções para otimizar o uso de energia e propõem um sistema de gestão de energia eficiente. No entanto, desenvolver um sistema de energia que contempla agregadores de carga é óbvio para aprimorar o processo de gestão de energia. Este trabalho discute um sistema de gestão de energia para implementar programas de Demand Response (DR) usando abordagens de agregação de carga. Neste trabalho, dois estudos de caso comparam as diferentes respostas do sistema. O objetivo principal é discutir o papel de diferentes modelos de agregador de carga no sistema de energia, implementando um programa de DR. Esses agregadores de carga controlam diferentes tipos de cargas. Neste contexto, vários tipos de cargas domésticas são consideradas cargas controláveis. No processo de agregação, o objetivo é agregar as cargas que possuem as mesmas características usando a análise de agrupamento das cargas. A contribuição científica desta dissertação está relacionada com a redução da ponta e a agregação de cargas, considerando as cargas controláveis e os recursos de geração no sistema. Para atingir o objetivo anterior, foram realizados dois estudos de caso. Cada estudo de caso consiste em três cenários baseados no modelo de agregação de carga. Os resultados dos estudos indicam as respostas do sistema aos diferentes cenários e ilustram os méritos do modelo de agregador de carga. Além disso, os resultados demonstram como o agrupamento dos dispositivos de carga no sistema pode efetivamente fornecer redução de pico com recurso a programas de DR.The increment of energy consumption takes a high level of attention. The experts have proposed many solutions to optimize energy use and propose an efficient energy management system. However, verifying the load aggregators' role energy system is obvious to enhance the energy management process. This work discusses an energy management system to implement DR programs using load aggregation approaches. In this work, two case studies compare the different responses of the system. The main goal is to discuss the role of different load aggregator models in the power system by implementing a DR program. Those load aggregators control different types of loads. In this context, various types of domestic loads are considered controllable loads. In the aggregation process, the goal is to aggregate the loads that have the same features using the clustering analysis of the loads. The scientific contribution of this thesis is related to the integration of providing the peak reduction and the clustered aggregation of loads, considering the controllable loads and generation resources in the system. To achieve the previous goal, two case studies have been done. Each case study consists of three scenarios based on the load aggregation model. The results of the case studies indicate the system responses to the different scenarios and illustrate the merits of the load aggregator model. Furthermore, the results demonstrate how clustering the load appliances in the system can effectively provide peak reduction due to the DR programs