Two-stage Optimization for Building Energy Management

AbstractContinuous increase of energy demand on one hand and integration of large number of renewable energy sources on the other require advanced control strategies to provide an uninterrupted service and guarantee high energy efficiency. Utilities and transmission system operators permanently supervise production facilities and grids to compensate any mismatch between production and consumption. With the gradual change from a centralized system with a few large power plants to a decentralized and distributed generation based on many renewable energy sources, local energy management systems can contribute to grid balancing. This paper presents a building energy management which determines the optimal scheduling of the different components of the local energy system. The two-stage optimization is based on the minimization of an economic function subject to the physical system constraints and uses a receding horizon approach. The proposed building energy management is implemented using mixed integer linear programming and applied in simulation to a hotel with photovoltaic installation and battery system

Soluciones alternativas al control predictivo basado en modelo de Volterra

[Resumen] El concepto básico de control predictivo basado en modelos (MPC) ofrece la posibilidad de usar modelos no lineales para predecir la evolución futura del sistema. La consideración de modelos no lineales en una función de coste cuadrática resulta en un problema de optimización posiblemente no convexo con varios mínimos. En este trabajo se presentan diferentes alternativas para la solución del problema del control predictivo no lineal basado en modelos de Volterra. Las opciones planteadas consisten en la utilización de un solver global no lineal incluido en Matlab, la utilización de la técnica de los momentos y, para el caso de modelos de Volterra de grado dos, la transformación del problema en uno de programación semidefinida. Se muestra mediante un ejemplo la bondad de las diferentes propuestas y la relación del coste computacional de cada opción en función de los horizontes de predicción y control.Este trabajo ha sido financiado por la Universitat Jaume I de Castelló a través del proyecto con referencia P11B2015-42, el Ministerio de Economía y Competitividad a través del proyecto con referencia TEC2015-69155-R y la Comunidad de Madrid a través del proyecto PRICAM con referencia S2013/ICE-2933Universitat Jaume I; P11B2015-42Comunidad de Madrid; S2013/ICE-2933https://doi.org/10.17979/spudc.978849749808

Multi-nodal short-term energy forecasting using smart meter data

This paper deals with the short-term forecasting of electrical energy demands at the local level, incorporating advanced metering infrastructure (AMI), or ‘smart meter’ data. It provides a study of the effects of aggregation on electrical energy demand modelling and multi-nodal demand forecasting. This paper then presents a detailed assessment of the variables which affect electrical energy demand, and how these effects vary at different levels of demand aggregation. Finally, this study outlines an approach for incorporating AMI data in short-term forecasting at the local level, in order to improve forecasting accuracy for applications in distributed energy systems, microgrids and transactive energy. The analysis presented in this study is carried out using large AMI data sets comprised of recorded demand and local weather data from test sites in two European countries.The authors kindly acknowledge the support of the European Commission provided through the Marie Curie researcher mobility action (FP7-PEOPLE-2013-COFUND), and the SmartHG research project (FP7-ICT-2011-8).peer-reviewe

Nonlinear predictive control based on Volterra models. Application to a pilot plant.

[EN] The present publication demonstrates the application of a nonlinear predictive control (NMPC) strategy based on Volterra models to a pilot plant in which the temperature of the reactor's content is controlled. The control is based on a second-order diagonal Volterra model in order to consider nonlinear effects. To calculate the control action, an iterative method with low computational cost, is used. The behavior of the process and the controller will be presented by means of experimental results. Finally, the experimental results of the NMPC will be compared to the results of a linear model based predictive controller (MPC).[ES] El presente artículo muestra la aplicación de una estrategia de control predictivo no lineal basado en modelos (Nonlinear Model Predictive Control, NMPC) a una planta piloto en la que se controla la temperatura de un reactor. El controlador está basado en un modelo diagonal de Volterra de segundo orden para considerar efectos no lineales. Para calcular la acción de control se utiliza un método iterativo que requiere pocos recursos computacionales. El comportamiento del proceso y del controlador se presenta mediante resultados experimentales. Finalmente se comparan los resultados experimentales del NMPC con los resultados de un controlador predictivo lineal (MPC).Este trabajo ha sido financiado parcialmente por el Ministerio de Educación y Ciencia a través del proyecto de investigación DPI-2004-07444-C04-01Gruber, JK.; Bordons, C. (2009). Control Predictivo no Lineal Basado en Modelos de Volterra. Aplicación a una Planta Piloto. Revista Iberoamericana de Automática e Informática industrial. 4(3):34-45. http://hdl.handle.net/10251/145957OJS34454

The incidence of pressure ulcers in patients after coronary artery bypass graft

Tato bakalářská práce se orientuje na téma Výskyt dekubitů u pacientů po aortokoronárním bypassu na kardiochirurgickém oddělení jednotky pooperační resuscitační péče v Nemocnici Na Homolce. V teoretické části práce definuji dekubity, klasifikaci dekubitů, prevenci a léčbu. Téma rozšiřuji o způsoby hojení ran a rizika vzniku dekubitů, která mohou ohrožovat pacienta po srdečním bypassu. Druhá polovina práce je zpracována formou kvalitativního výzkumu - kazuistiky. Je zde popsána ošetřovatelská problematika výskytu dekubitů u dvou pacientů. Výstup z práce bude zveřejněn v odborném časopise s lékařskou tématikou.ObhájenoThe focus of this bachelor's thesis is on the topic of the presssure ulcer incidence amongst the patients following a coronary artery bypass graft. The study was carried out at the department of the post operative intensive care cardiac surgery unit, Nemocnice Na Homolce. The theoretical part provides definitions of the pressure ulcers, the classification of decubitus, the prevention and the treatment. I further extend the topic by the possible ways of wounds healing and the risk of pressure sores fromation, which can threaten the patient after the heart bypass surgery. The second part is approached through a qualitative research of the case studies. It describes the issues related to the nursing of two patients, who suffered from the occurence of the pressure ulcers. The resulting output of this thesis will be published in a scientific journal with a medical theme

A glimpse of SmartHG project test-bed and communication infrastructure

The SmartHG project goal is to develop a suite of integrated software services (the SmartHG Platform) aiming at steering residential users energy demand in order to: keep operating conditions of the electrical grid within given healthy bounds, minimize energy costs, and minimize CO2 emissions. This is achieved by exploiting knowledge (demand awareness) of electrical energy prosumption of residential users as gained from SmartHG sensing and communication infrastructure. This paper describes such an infrastructure along with user demand patterns emerging from the data gathered from ~600 sensors installed in ~40 homes participating in SmartHG test-bed