20,640 research outputs found
Connecting office buildings to the smart grid:harvesting flexibility
Traditionally, the electricity system is oriented top- down and buildings are just energy consumers. Since electricity is expensive to store, supply and demand have to be balanced at all times. In the nearby future, the electricity system must be able to cope with an increase in intermittent decentralized energy production. Also, ongoing electrification is expected to contribute to an increase in demand. Demand side management and control is needed to ensure reliability of supply at acceptable costs. Buildings can be a part of the solution as they can offer flexibility in energy consumption and/or production. By enabling flexible control of processes on the building premises, the building can provide balancing services and respond to congestion problems in the power system, while user comfort can be guaranteed. For the engineering company BAM Techniek, it is of importance to know how the integration of such smart grid technologies in buildings can contribute to (energy) service provision. This study focusses on the enabling of flexibility in energy consumption and generation, while comfort is guaranteed. The project aims to create a framework that enables flexible control of building processes, and analyses of the potential value of flexibility in office buildings. The proposed framework consists of a technical solution, and an analysis of the economical benefits. Priority based control is introduced to enable flexible control of building processes. The concept is capable of prioritizing the energy consumption of processes, and controlling the consumption depending on the needs of the electricity market. An empty office has for instance, a low priority to consume energy. User needs are integrated in the prioritization mechanisms. This mechanism ensures that processes stay within the allowed bandwidth, while providing flexibility to the power system. Since the priority based control connects the end user needs to the market needs, a bi-directional flow of information is required. The Eneco World Office is used to perform a building case study to test the technological framework. Three sources of flexibility are investigated: decentralized climate systems, electric vehicles, and a sensible heat buffer. Results show that the amount of available flexibility depends mainly on load profiles and comfort settings. Electric vehicles and the sensible heat buffer provide significant amounts of flexibility. The flexibility in decentralized climate systems is limited since the room air temperature responds relatively fast to changes in settings and comfort boundaries are quickly met. The long term effect of storage in the building inertia should however be investigated further. Economical benefits can be created by using the variation in costs on the wholesale market caused by market volatility. When flexibility is used to contribute to the balance in a portfolio of buildings, the imbalance can be reduced, which leads to a reduction in costs. Finally, flexibility can contribute to a reduction in peak demand of buildings, leading to cost savings in the network connection. The need for smart grids is growing, while energy services are becoming more important in the built environment. Considering the potential value of smart grid services in the built environment and the market size, it is evident that the developing smart grid market presents opportunities for BAM Techniek. The provision of flexibility services can be a valuable addition to the energy services portfolio
Recommended from our members
Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California
This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World
This report documents the program and the outcomes of GI-Dagstuhl Seminar
16394 "Software Performance Engineering in the DevOps World".
The seminar addressed the problem of performance-aware DevOps. Both, DevOps
and performance engineering have been growing trends over the past one to two
years, in no small part due to the rise in importance of identifying
performance anomalies in the operations (Ops) of cloud and big data systems and
feeding these back to the development (Dev). However, so far, the research
community has treated software engineering, performance engineering, and cloud
computing mostly as individual research areas. We aimed to identify
cross-community collaboration, and to set the path for long-lasting
collaborations towards performance-aware DevOps.
The main goal of the seminar was to bring together young researchers (PhD
students in a later stage of their PhD, as well as PostDocs or Junior
Professors) in the areas of (i) software engineering, (ii) performance
engineering, and (iii) cloud computing and big data to present their current
research projects, to exchange experience and expertise, to discuss research
challenges, and to develop ideas for future collaborations
Effective demand response gathering and deployment in smart grids for intensive renewable integration using aggregation and machine learning
Tesis por compendio de publicaciones.[EN] Distributed generation, namely renewables-based technologies, have
emerged as a crucial component in the transition to mitigate the effects of climate
change, providing a decentralized approach to electricity production. However,
the volatile behavior of distributed generation has created new challenges in
maintaining system balance and reliability. In this context, the demand response
concept and corresponding programs arise giving the local energy communities
prominence.
In demand response concept, it is expected an empowerment of the
consumer in the electricity sector. This has a significant impact on grid operations
and brings complex interactions due to the volatile behavior, privacy concerns,
and lack of consumer knowledge in the energy market context. For this,
aggregators play a crucial role addressing these challenges. It is crucial to develop
tools that allow the aggregators helping consumers to make informed decisions,
maximize the benefits of their flexibility resources, and contribute to the overall
success of grid operations. This thesis, through innovative solutions and
resorting to artificial intelligence models, addresses the integration of
renewables, promoting fair participation among all demand response providers.
The thesis ultimately results in an innovative decision support system -
MAESTRO, the Machine learning Assisted Energy System management Tool for
Renewable integration using demand respOnse. MAESTRO is composed by a set
of diversified models that together contribute for handling the complexity of
managing energy communities with distributed generation resources, demand
response providers, energy storage systems and electric vehicles.
This PhD thesis comprises a comprehensive analysis of state-of-the-art
techniques, system design and development, experimental results, and key
findings. In this research were published twenty-six scientific papers, in both
international journals and conference proceedings. Contributions to international
projects and Portuguese projects was accomplished.
[ES] La generación distribuida, en particular las tecnologías basadas en energías
renovables, se ha convertido en un componente crucial en la transición para
mitigar los efectos del cambio climático, al proporcionar un enfoque
descentralizado para la producción de electricidad. Sin embargo, el
comportamiento volátil de la generación distribuida ha generado nuevos
desafíos para mantener el equilibrio y la confiabilidad del sistema. En este
contexto, surge el concepto de respuesta de la demanda y los programas
correspondientes, otorgando prominencia a las comunidades energéticas locales.
En el concepto de "respuesta a la demanda" (DR por sus siglas en inglés), se
espera un empoderamiento del consumidor en el sector eléctrico. Esto tiene un
impacto significativo en la operación de la red y genera interacciones complejas
debido al comportamiento volátil, las preocupaciones de privacidad y la falta de
conocimiento del consumidor en el contexto del mercado energético. Para esto,
los agregadores desempeñan un papel crucial al abordar estos desafíos. Es
fundamental desarrollar herramientas que permitan a los agregadores ayudar a
los consumidores a tomar decisiones informadas, maximizar los beneficios de sus
recursos de flexibilidad y contribuir al éxito general de las operaciones de la red.
Esta tesis, a través de soluciones innovadoras y utilizando modelos de
inteligencia artificial, aborda la integración de energías renovables, promoviendo
una participación justa entre todos los proveedores de respuesta de la demanda.
La tesis resulta en última instancia en un sistema de apoyo a la toma de decisiones
innovador: MAESTRO, Machine learning Assisted Energy System management Tool
for Renewable integration using demand respOnse. MAESTRO está compuesto por
un conjunto de modelos diversificados que contribuyen juntos para manejar la
complejidad de la gestión de comunidades energéticas con recursos de
generación distribuida, proveedores de respuesta de la demanda, sistemas de
almacenamiento de energía y vehículos eléctricos.
Esta tesis de doctorado comprende un análisis exhaustivo de las técnicas de
vanguardia, el diseño y desarrollo del sistema, los resultados experimentales y
los hallazgos clave. En esta investigación se publicaron veintiséis artículos
científicos, tanto en revistas internacionales como en actas de conferencias. Se
lograron contribuciones a proyectos internacionales y proyectos portugueses.
[POR] A produção distribuída, nomeadamente as tecnologias baseadas em
energias renováveis, emergiram como um componente crucial na transição para
mitigar os efeitos das alterações climáticas, proporcionando uma abordagem
descentralizada à produção de eletricidade. No entanto, o comportamento volátil
da geração distribuída criou desafios na manutenção do equilíbrio e da
fiabilidade do sistema. Nesse contexto, surge o conceito de resposta à procura e
os programas correspondentes, conferindo proeminência às comunidades
energéticas locais.
No conceito de resposta à procura, espera-se um empoderamento do
consumidor no setor elétrico. Isso tem um impacto significativo nas operações da
rede e gera interações complexas devido ao comportamento volátil,
preocupações com a privacidade e falta de conhecimento dos consumidores no
contexto do mercado energético. Para isso, os agregadores desempenham um
papel crucial ao lidar com esses desafios. É fundamental desenvolver ferramentas
que permitam aos agregadores ajudar os consumidores a tomar decisões
informadas, maximizar os benefícios de seus recursos de flexibilidade e
contribuir para o sucesso global das operações da rede.
Esta tese de doutoramento, através de soluções inovadoras e recorrendo a
modelos de inteligência artificial, aborda a integração de energias renováveis,
promovendo uma participação justa entre todos os fornecedores de resposta à
procura. A tese resulta, em última instância, num sistema inovador de apoio à
tomada de decisões - MAESTRO, Machine learning Assisted Energy System
management Tool for Renewable integration using demand respOnse. A ferramenta
MAESTRO é composta por um conjunto de modelos diversificados que, em
conjunto, contribuem para lidar com a complexidade da gestão de comunidades
energéticas com recursos de geração distribuída, fornecedores de resposta à
procura, sistemas de armazenamento de energia e veículos elétricos.
Esta tese de doutoramento abrange uma análise abrangente de técnicas de
ponta, design e desenvolvimento do sistema, resultados experimentais e
descobertas-chave. Nesta pesquisa, foram publicados vinte e seis artigos
científicos, tanto em revistas internacionais como em atas de conferências. Foram
realizadas contribuições para projetos internacionais e projetos portugueses
Spatial flexibility options in electricity market simulation tools: Deliverable D4.3
Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: Deliverable D4.3 addresses the spatial flexibility options that are being considered by TradeRES models. D4.3 presents a report describing the spatial flexibility-related modelling components that are already implemented and those that are being designed for integration in TradeRES agent-based models. This report includes the main definitions, concepts and terminology related to spatial flexibility, as means to support the presentation of the specific models that are being developed by the project, namely about flow based market coupling, market spliting, nodal pricing, dynamic line rating, cross border intraday market, cross border reserve market, cross border capacity market, consumer flexibility aggregation, renewable energy aggregation, storage aggregation, electric vehicle aggregation and grid capacity.N/
Demand response approaches in a research project versus a real business
© 2023 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Demand response through Demand Aggregation is part of the energy transition towards a green and distributed system. Although the market is open in most European countries, its practical implementation is not much successful yet. In the last decade, research presented different options to deal with demand response and aggregation. This paper compares the benefits and limitations of strategies implemented from a research perspective and the strategy followed by a recently created company to see which of the advances in research are currently useful from a business perspective. The study presents a novel decision matrix to evaluate demand response strategies. Results show that there are technical limitations in current Energy Management Systems that need to be taken into account when developing demand aggregation platforms. In addition, the study highlights the importance to propose a simple and scalable solution to allow consumers to participate actively in electricity markets and create a success business model.This research has been supported by the research and innovation programme Horizon 2020 of the European Union under
the grant agreement nr. 731211 SABINA. C. Corchero work is
supported by the grant IJCI-2015-26650 (MICINN). All researchers
have been partially supported by the Generalitat de Catalunya,
Spain (2017 SGR 1219). L. Canals Casals thanks the national
project IAQ4EDU (PID2020-117366RB-100) for giving the opportunity to continue his work in this field.Peer ReviewedObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantPostprint (published version
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
- …