179 research outputs found

    Load Shifting Versus Manual Frequency Reserve: Which One is More Appealing to Flexible Loads?

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    This paper investigates how a thermostatically controlled load can deliver flexibility either in form of manual frequency restoration reserves (mFRR) or load shifting, and which one is financially more appealing to such a load. A supermarket freezer is considered as a representative flexible load, and a grey-box model describing its temperature dynamics is developed using real data from a supermarket in Denmark. Taking into account price and activation uncertainties, a two-stage stochastic mixed-integer linear program is formulated to maximize the flexibility value from the freezer. For practical reasons, we propose a linear policy to determine regulating power bids, and then linearize the mFRR activation conditions through the McCormick relaxation approach. For computational ease, we develop a decomposition technique, splitting the problem to a set of smaller subproblems, one per scenario. Examined on an out-of-sample simulation based on real Danish spot and balancing market prices in 2022, load shifting shows to be more profitable than mFRR provision, but is also more consequential for temperature deviations in the freezer

    Scaling energy management in buildings with artificial intelligence

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Estudio del rol de las Plantas Virtuales de Producción en la gestión de las redes de generación y distribución eléctrica

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    141 p.El objetivo principal de las Planta Virtuales de Producción Eléctrica o Virtual Power Plants (VPPs) es darle cumplimiento a los requerimientos de sus Stakeholders dentro de las redes de generación y distribución eléctrica que gestionan, así como aprovechar eficientemente los elementos y recursos que tienen a su disposición. Uno de los desafíos más importantes de las VPPs es satisfacer los requerimientos de sus Stakeholders optimizando el uso de la electricidad generada en sus sistemas de manera sostenible, minimizando los costes de operación y maximizando los beneficios comerciales. En esta tesis se presenta la información clave, recopilada a partir de más de 160 artículos científicos, para dar apoyo en el conocimiento de conceptos infraestructurales, tecnológicos y de desarrollo sostenible que involucran la gestión de las VPPs en las redes de generación y distribución eléctrica. De esta manera, se analiza, selecciona y organiza la información suministrada por los investigadores a través de sus artículos científicos, identificándose las distintas interacciones de las VPPs relacionadas con la arquitectura infraestructural y tecnología de los sistemas, el mercado eléctrico, modelos de optimización para la toma de decisiones, y las tecnologías de la información y de la comunicación; y dar así respuesta a la pregunta clave: ¿Cómo el rol de las VPPs puede utilizarse para minimizar los costes de operación y maximizar los beneficios comerciales de las redes de generación y distribución eléctrica, optimizando el uso de la electricidad de manera sostenible?. Finalmente, se indican esquemas de sistemas centralizados, descentralizados e híbridos, en los cuales las VPPs desempeñan su gestión mediante la aplicación de su rol y funciones para cumplir con los requerimientos de sus Stakeholders, mencionando las ventajas y dificultades según los escenarios en los que se desempeñe

    Social Shaping for Multi-Agent Systems

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    Multi-agent systems have gained attention due to advances in automation, technology, and AI. In these systems, intelligent agents collaborate through networks to achieve goals. Despite successes, multi-agent systems pose social challenges. Problems include agents finding resource prices unacceptable due to efficient allocation, interactions being cooperative/competitive, leading to varying outcomes, and sensitive data being at risk due to sharing. Problems are: 1. Price Acceptance; 2. Agent Cooperation and Competition; 3. Privacy Risks. For Price Acceptance, we address decentralized resource allocation systems as markets. We solve price acceptance in static systems with quadratic utility functions by defining allowed quadratic ranges. For dynamic systems, we present dynamic competitive equilibrium computation and propose a horizon strategy for smoothing dynamic pricing. Concerning Agent Cooperation and Competition, we study the well-known Regional Integrated Climate-Economy model (RICE). It's a dynamic game. We analyze cooperative and competitive solutions, showing impact on negotiations and consensus for regional climate action. Regarding Privacy Risks, we infer network structures from linear-quadratic game best-response dynamics to reveal agent vulnerabilities. We prove network identifiability tied to controllability conditions. A stable, sparse system identification algorithm learns network structures despite noise. Lastly, we contribute privacy-aware algorithms. We address network games where agents aggregate under differential privacy. Extending to network games, we propose a Laplace linear-quadratic functional perturbation algorithm. A tutorial example demonstrates meeting privacy needs through tuning. In summary, this thesis solves social challenges in multi-agent systems: Price Acceptance, Agent Cooperation and Competition, and Privacy Risks

    Wind Farms and Flexible Loads Contribution in Automatic Generation Control: An Extensive Review and Simulation

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    With the increasing integration of wind energy sources into conventional power systems, the demand for reserve power has risen due to associated forecasting errors. Consequently, developing innovative operating strategies for automatic generation control (AGC) has become crucial. These strategies ensure a real-time balance between load and generation while minimizing the reliance on operating reserves from conventional power plant units. Wind farms exhibit a strong interest in participating in AGC operations, especially when AGC is organized into different regulation areas encompassing various generation units. Further, the integration of flexible loads, such as electric vehicles and thermostatically controlled loads, is considered indispensable in modern power systems, which can have the capability to offer ancillary services to the grid through the AGC systems. This study initially presents the fundamental concepts of wind power plants and flexible load units, highlighting their significant contribution to load frequency control (LFC) as an important aspect of AGC. Subsequently, a real-time dynamic dispatch strategy for the AGC model is proposed, integrating reserve power from wind farms and flexible load units. For simulations, a future Pakistan power system model is developed using Dig SILENT Power Factory software (2020 SP3), and the obtained results are presented. The results demonstrate that wind farms and flexible loads can effectively contribute to power-balancing operations. However, given its cost-effectiveness, wind power should be operated at maximum capacity and only be utilized when there is a need to reduce power generation. Additionally, integrating reserves from these sources ensures power system security, reduces dependence on conventional sources, and enhances economic efficiency

    A Distributed Coordination Strategy for Heterogeneous Building Flexible Thermal Loads in Responding to Smart Grids

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    Air conditioning systems are promising energy flexibility resources for smart grids. However, buildings with various thermodynamics must be coordinated to utilize limited energy flexibility effectively. This study proposes a distributed coordination strategy to coordinate building flexible thermal loads of different characteristics for optimized utilization of energy flexibility in a scalable and distributed manner. It consists of two components:1) an average consensus-based distributed sensing scheme to estimate the average thermal state of charge (SoC) of multiple zones, and 2) a weighted consensus-based distributed allocation module to allocate the demand response (DR) tasks or limited energy resources to multiple zones, proportional to their thermal storage capacities and deviations to the average thermal SoCs. Both algorithms achieve their goals respectively by fully distributed means through a sparse network with neighbor-to-neighbor communication. The sufficient condition for converging the weighted consensus algorithm is also derived for the first time. The proposed strategy is adopted for 1) weighted DR participation of residential inverter air conditioners and 2) weighted water flow redistribution of the commercial building water heating systems under urgent DR events. Simulation results show that adopting the distributed coordination strategy avoids the early depletion of demand flexibility resources and nonuniform thermal comfort sacrifices under uncoordinated control

    A Multi-Stakeholder Information Model to Drive Process Connectivity In Smart Buildings

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    Smart buildings utilise IoT technology to provide stakeholders with efficient, comfortable, and secure experiences. However, previous studies have primarily focused on the technical aspects of it and how it can address specific stakeholder requirements. This study adopts socio-technical theory principles to propose a model that addresses stakeholders' needs by considering the interrelationship between social and technical subsystems. A systematic literature review and thematic analysis of 43 IoT conceptual frameworks for smart building studies informed the design of a comprehensive conceptual model and IoT framework for smart buildings. The study's findings suggest that addressing stakeholder requirements is essential for developing an information model in smart buildings. A multi-stakeholder information model integrating multiple stakeholders' perspectives enhances information sharing and improves process connectivity between various systems and subsystems. The socio-technical systems framework emphasises the importance of considering technical and social aspects while integrating smart building systems for seamless operation and effectiveness. The study's findings have significant implications for enhancing stakeholders' experience and improving operational efficiency in commercial buildings. The insights from the study can inform smart building systems design to consider all stakeholder requirements holistically, promoting process connectivity in smart buildings. The literature analysis contributed to developing a comprehensive IoT framework, addressing the need for holistic thinking when proposing IoT frameworks for smart buildings by considering different stakeholders in the building

    Resilience-oriented control and communication framework for cyber-physical microgrids

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    Climate change drives the energy supply transition from traditional fossil fuel-based power generation to renewable energy resources. This transition has been widely recognised as one of the most significant developing pathways promoting the decarbonisation process toward a zero-carbon and sustainable society. Rapidly developing renewables gradually dominate energy systems and promote the current energy supply system towards decentralisation and digitisation. The manifestation of decentralisation is at massive dispatchable energy resources, while the digitisation features strong cohesion and coherence between electrical power technologies and information and communication technologies (ICT). Massive dispatchable physical devices and cyber components are interdependent and coupled tightly as a cyber-physical energy supply system, while this cyber-physical energy supply system currently faces an increase of extreme weather (e.g., earthquake, flooding) and cyber-contingencies (e.g., cyberattacks) in the frequency, intensity, and duration. Hence, one major challenge is to find an appropriate cyber-physical solution to accommodate increasing renewables while enhancing power supply resilience. The main focus of this thesis is to blend centralised and decentralised frameworks to propose a collaboratively centralised-and-decentralised resilient control framework for energy systems i.e., networked microgrids (MGs) that can operate optimally in the normal condition while can mitigate simultaneous cyber-physical contingencies in the extreme condition. To achieve this, we investigate the concept of "cyber-physical resilience" including four phases, namely prevention/upgrade, resistance, adaption/mitigation, and recovery. Throughout these stages, we tackle different cyber-physical challenges under the concept of microgrid ranging from a centralised-to-decentralised transitional control framework coping with cyber-physical out of service, a cyber-resilient distributed control methodology for networked MGs, a UAV assisted post-contingency cyber-physical service restoration, to a fast-convergent distributed dynamic state estimation algorithm for a class of interconnected systems.Open Acces

    CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

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    This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship
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