Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy

The energy output of photovoltaic (PV) power plants depends on the environment and thus fluctuates over time. As a result, PV power can cause instability in the power grid, in particular when increasingly used. Limiting the rate of change of the power output is a common way to mitigate these fluctuations, often with the help of large batteries. A reactive controller that uses these batteries to compensate ramps works in practice, but causes stress on the battery due to a high energy throughput. In this paper, we present a deep learning approach that uses images of the sky to compensate power fluctuations predictively and reduces battery stress. In particular, we show that the optimal control policy can be computed using information that is only available in hindsight. Based on this, we use imitation learning to train a neural network that approximates this hindsight-optimal policy, but uses only currently available sky images and sensor data. We evaluate our method on a large dataset of measurements and images from a real power plant and show that the trained policy reduces stress on the battery.Comment: 7 pages, 7 figure

Development of a control strategy to compensate transient behaviour due to atmospheric disturbances in solar thermal energy generation systems using short-time prediction data

La energía solar térmica concentrada (CSP) es una forma prometedora de energía renovable que puede aprovechar la energía del sol y ayudar a sustituir el uso de combustibles fósiles para la generación de electricidad. Sin embargo, enfrenta retos para aumentar su despliegue a nivel mundial. Las torres solares, un tipo de tecnología CSP, se componen principalmente de un campo solar y una torre en la que un receptor funciona como intercambiador de calor para alimentar un bloque de potencia. El campo solar está formado por miles de heliostatos, que son espejos capaces de seguir el sol y proyectar la luz solar concentrada sobre el receptor. Las torres solares con almacenamiento térmico funcionan continuamente, pero están sujetas a perturbaciones causadas por la interacción de la luz solar con la atmósfera. Este comportamiento puede afectar la integridad del receptor. Para determinar la posición de cada helióstato se utilizan complejos métodos de optimización. Sin embargo, estos métodos están sujetos a incertidumbre en los parámetros y no pueden compensar perturbaciones en tiempo real, como las nubes, debido a su costo computacional. Esta tesis aborda esta cuestión como un problema de control, reduciendo el número de variables. En lugar de encontrar el ángulo de elevación y azimutal para miles de helióstatos, se utilizan dos variables dentro de grupos de helióstatos. A continuación, se implementa una estrategia de control por retroalimentación, aprovechando esta reducción dimensional. Además, la metodología desarrollada en esta tesis utiliza información de un sistema de predicción de radiación solar a corto plazo de última generación, dentro de una novedosa estrategia de control adaptativo para el campo solar.DoctoradoDoctor en Ingeniería Mecánic

High Efficient Buildings in Mediterranean Area

The Building sector requires a conspicuous considerable amount of energy for services related to annual air-conditioning and the thermal comfort of indoor spaces. The design of highly efficient low-energy buildings is often a challenging task, especially in the mediterranean area, where the balanced requirement for heating and cooling energy does not usually permit a high level of envelope insulation in order to avoid summer overheating. This topical Special Issue of Energies is dedicated to “High Efficient Buildings in Mediterranean Area: Challenges and Perspectives” and collects studies related to the assessment and evaluation of systems and technologies for building energy management and control in the Mediterranean climate, with the aim of optimizing the building–plant system and reducing energy use. This collection of papers presents the latest research results related to the topic; these articles offer valuable insights into the energy simulation of highly efficient buildings, propose innovative envelope solutions, such as green roofs, Trombe walls, and PCM, and investigate the use of renewable sources such as photovoltaic systems. The topics also include the innovative use and control of Venetian blinds and fixed solar shades in order to reduce energy consumption and preserve visual comfort, as well as an interesting economic analysis based on the cost-optimal approach

Using learning from demonstration to enable automated flight control comparable with experienced human pilots

Modern autopilots fall under the domain of Control Theory which utilizes Proportional Integral Derivative (PID) controllers that can provide relatively simple autonomous control of an aircraft such as maintaining a certain trajectory. However, PID controllers cannot cope with uncertainties due to their non-adaptive nature. In addition, modern autopilots of airliners contributed to several air catastrophes due to their robustness issues. Therefore, the aviation industry is seeking solutions that would enhance safety. A potential solution to achieve this is to develop intelligent autopilots that can learn how to pilot aircraft in a manner comparable with experienced human pilots. This work proposes the Intelligent Autopilot System (IAS) which provides a comprehensive level of autonomy and intelligent control to the aviation industry. The IAS learns piloting skills by observing experienced teachers while they provide demonstrations in simulation. A robust Learning from Demonstration approach is proposed which uses human pilots to demonstrate the task to be learned in a flight simulator while training datasets are captured. The datasets are then used by Artificial Neural Networks (ANNs) to generate control models automatically. The control models imitate the skills of the experienced pilots when performing the different piloting tasks while handling flight uncertainties such as severe weather conditions and emergency situations. Experiments show that the IAS performs learned skills and tasks with high accuracy even after being presented with limited examples which are suitable for the proposed approach that relies on many single-hidden-layer ANNs instead of one or few large deep ANNs which produce a black-box that cannot be explained to the aviation regulators. The results demonstrate that the IAS is capable of imitating low-level sub-cognitive skills such as rapid and continuous stabilization attempts in stormy weather conditions, and high-level strategic skills such as the sequence of sub-tasks necessary to takeoff, land, and handle emergencies

Full Proceedings, 2018

Full conference proceedings for the 2018 International Building Physics Association Conference hosted at Syracuse University

Renewable Energies for Sustainable Development

In the current scenario in which climate change dominates our lives and in which we all need to combat and drastically reduce the emission of greenhouse gases, renewable energies play key roles as present and future energy sources. Renewable energies vary across a wide range, and therefore, there are related studies for each type of energy. This Special Issue is composed of studies integrating the latest research innovations and knowledge focused on all types of renewable energy: onshore and offshore wind, photovoltaic, solar, biomass, geothermal, waves, tides, hydro, etc. Authors were invited submit review and research papers focused on energy resource estimation, all types of TRL converters, civil infrastructure, electrical connection, environmental studies, licensing and development of facilities, construction, operation and maintenance, mechanical and structural analysis, new materials for these facilities, etc. Analyses of a combination of several renewable energies as well as storage systems to progress the development of these sustainable energies were welcomed

Forecasting: theory and practice

Forecasting has always been in the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The lack of a free-lunch theorem implies the need for a diverse set of forecasting methods to tackle an array of applications. This unique article provides a non-systematic review of the theory and the practice of forecasting. We offer a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts, including operations, economics, finance, energy, environment, and social good. We do not claim that this review is an exhaustive list of methods and applications. The list was compiled based on the expertise and interests of the authors. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of the forecasting theory and practice

Human reproduction in space. Late results

Objectius de Desenvolupament Sostenible::3 - Salut i BenestarPostprint (published version

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases.info:eu-repo/semantics/publishedVersio