Gas-Electricity Coordination in Competitive Markets under Renewable Energy Uncertainty

As climate concerns, low natural gas prices, and renewable technologies increase the electric power sector’s dependence on natural gas-fired power plants, operational and investment models for gas and electric power systems will need to incorporate the interdependencies between these two systems to accurately capture the impacts of one on the other. Currently, few hybrid gas-electricity models exist. This paper reviews the state of the art for hybrid gas-electricity models and presents a new model and case study to illustrate a few potential coupling effects between gas and electric power systems. Specifically, the proposed model analyzes the optimal operation of gas-fired power plants in a competitive electricity market taking into consideration gas purchases, gas capacity contracting, and residual demand uncertainty for the generation company due to renewable energy sources

Subjetividad farmacéutica en tiempos de crisis en Madrid: Entre la supervivencia, la cronificación y el “Debo ser yo”

In recent years, mental health has gained significant relevance, accompanied by a gradual reduction in stigma. As a result, more people are understanding and analyzing their suffering in psychological terms. However, for many individuals accessing public mental health services in a city like Madrid, medication remains the primary treatment option. This study aims to analyze the type of subjectivity produced through this form of intervention, based on the findings of an ethnographic research conducted between 2012 and 2014. The research included observation in mental health center consultations, 19 in-depth interviews with psychotropic drug users, and a reflection group with periodic meetings. Key findings highlight ambivalence towards medication and the need for continuous adjustments to minimize side effects. The resulting subjectivity revolves around central aspects such as the fear of relapse and side effects; autonomy, which conflicts with the notion of not trying on one’s own; accountability, feelings of vulnerability and self-governance, core aspects of neoliberal subjectivity.En los últimos años, la salud mental ha cobrado una enorme relevancia con una progresiva desestigmatización. Esto hace que cada vez más personas entiendan y analicen su sufrimiento en términos psicológicos. Pero para muchas personas que acceden a los dispositivos públicos de salud mental en una ciudad como Madrid, la principal opción de tratamiento es la medicación. Con el objetivo de analizar qué tipo de subjetividad se produce a partir de esa forma de intervención, se analizan los resultados obtenidos en una etnografía realizada entre 2012 y 2014 que incluyó la observación en las consultas de un centro de salud mental, 19 entrevistas en profundidad con consumidores de psicofármacos y un grupo de reflexión con encuentros periódicos. Entre los principales hallazgos encontramos la ambivalencia respecto a los fármacos y la necesidad de ajustes continuos para minimizar los efectos secundarios. En la subjetividad resultante se vuelven centrales aspectos como el miedo a la recaída y a los efectos secundarios; la autonomía, que choca con la idea de no intentarlo por uno mismo; la responsabilización, el sentimiento de vulnerabilidad y el autogobierno, aspectos claves de la subjetividad neoliberal

Dynamic risk control by human nucleus accumbens

Real-world decisions about reward often involve a complex counterbalance of risk and value. Although the nucleus accumbens has been implicated in the underlying neural substrate, its criticality to human behaviour remains an open question, best addressed with interventional methodology that probes the behavioural consequences of focal neural modulation. Combining a psychometric index of risky decision-making with transient electrical modulation of the nucleus accumbens, here we reveal profound, highly dynamic alteration of the relation between probability of reward and choice during therapeutic deep brain stimulation in four patients with treatment-resistant psychiatric disease. Short-lived phasic electrical stimulation of the region of the nucleus accumbens dynamically altered risk behaviour, transiently shifting the psychometric function towards more risky decisions only for the duration of stimulation. A critical, on-line role of human nucleus accumbens in dynamic risk control is thereby established

Pharmaceutical subjectivity in times of crisis in Madrid: Between survival, chronicity, and “It Must Be Me”

In recent years, mental health has gained significant relevance, accompanied by a gradual reduction in stigma. As a result, more people are understanding and analyzing their suffering in psychological terms. However, for many individuals accessing public mental health services in a city like Madrid, medication remains the primary treatment option. This study aims to analyze the type of subjectivity produced through this form of intervention, based on the findings of an ethnographic research conducted between 2012 and 2014. The research included observation in mental health center consultations, 19 in-depth interviews with psychotropic drug users, and a reflection group with periodic meetings. Key findings highlight ambivalence towards medication and the need for continuous adjustments to minimize side effects. The resulting subjectivity revolves around central aspects such as the fear of relapse and side effects; autonomy, which conflicts with the notion of not trying on one’s own; accountability, feelings of vulnerability and self-governance, core aspects of neoliberal subjectivity

Análisis de la operación de los mercados de generación de energía eléctrica a medio plazo

Programa de doctorado en Ingeniería eléctricaLa generación en sistemas de energía eléctrica de gran tamaño entraña unos costes muy elevados que deben ser minimizados mediante la explotación eficiente de los recursos disponibles. Durante las últimas décadas se viene produciendo un proceso de liberalización del negocio de suministro de energía eléctrica, que ha dado lugar en muchos países a la aparición de mercados de generación de electricidad. La tesis se centra en el análisis de los mercados de generación de energía eléctrica en el horizonte de medio plazo, que abarca desde unos pocos meses hasta tres años. Este análisis está, en la actualidad, en relación con tres disciplinas del conocimiento: la ingeniería eléctrica, la investigación operativa y el análisis microeconómico. El trabajo realizado en esta tesis profundiza simultáneamente en las tres, combinando enfoques que hasta ahora sólo se habían utilizado por separado. La diferencia fundamental respecto a otros trabajos radica en que se propone un método de resolución novedoso al que se pueden aplicar técnicas de programación lineal. El método propuesto calcula el punto de equilibrio del mercado con un enfoque enmarcado dentro de los modelos basados en variaciones conjeturales. La utilización de programación lineal permite abordar la resolución de problemas de un tamaño muy superior a lo que el resto de técnicas propuestas son capaces, además de proporcionar información dual que aporta un valor añadido. El análisis realizado se enfoca con un doble objetivo: la planificación de la generación, que supone disponer de unas previsiones fiables del comportamiento del mercado; y la operación de la generación, que se corresponde con la toma decisiones por parte de las empresas participantes. En la tesis se analiza la localización de recursos de medio plazo, distinguiendo dos tipos: recursos limitados en energía y recursos de utilización obligada

Vicinity Occlusion Maps: Enhanced Depth Perception of Volumetric Models

Volume models often show high depth complexity. This poses di±culties to the observer in judging the spatial relationships accurately. Illustrators usually use certain techniques such as halos or edge darkening in order to enhance depth perception of certain structures. Halos may be dark or light, and even colored. Halo construction on a volumetric basis impacts rendering performance due to the complexity of the construction process. In this paper we present Vicinity Occlusion Maps: a simple and fast method to compute the light occlusion due to neighboring voxels. Vicinity Occlusion Maps may be used to generate flexible halos around objects or selected structures in order to enhance depth perception or accentuate the presence of some structures in volumetric models at a low cost. The user may freely select the structure that requires the halos to be generated, its color and size, and our proposed application generates those in real time. They may also be used to perform vicinity shading in realtime, or even to combine both effects.Peer ReviewedPostprint (author’s final draft

Epidemiology of traumatic spinal cord injury in Galicia, Spain: trends over a 20-year period

[Abstract] Study design: Observational study with prospective and retrospective monitoring. Objective: To describe the epidemiological and demographic characteristics of traumatic spinal cord injury (TSCI), and to analyze its epidemiological changes. Setting: Unidad de Lesionados Medulares, Complejo Hospitalario Universitario A Coruña, in Galicia (Spain). Methods: The study included patients with TSCI who had been hospitalized between January 1995 and December 2014. Relevant data were extracted from the admissions registry and electronic health record. Results: A total of 1195 patients with TSCI were admitted over the specified period of time; 76.4% male and 23.6% female. Mean patient age at injury was 50.20 years. Causes of injury were falls (54.2%), traffic accidents (37%), sports/leisure-related accidents (3.5%) and other traumatic causes (5.3%). Mean patient age increased significantly over time (from 46.40 to 56.54 years), and the number of cases of TSCI related to traffic accidents decreased (from 44.5% to 23.7%), whereas those linked to falls increased (from 46.9% to 65.6%). The most commonly affected neurological level was the cervical level (54.9%), increasing in the case of levels C1–C4 over time, and the most frequent ASIA (American Spinal Injury Association) grade was A (44.3%). The crude annual incidence rate was 2.17/100 000 inhabitants, decreasing significantly over time at an annual percentage rate change of −1.4%. Conclusions: The incidence rate of TSCI tends to decline progressively. Mean patient age has increased over time and cervical levels C1–C4 are currently the most commonly affected ones. These epidemiological changes will eventually result in adjustments in the standard model of care for TSCI

Short-term electricity price forecasting with recurrent regimes and structural breaks

This paper develops a new approach to short-term electricity forecasting by focusing upon the dynamic specification of an appropriate calibration dataset prior to model specification. It challenges the conventional forecasting principles which argue that adaptive methods should place most emphasis upon recent data and that regime-switching should likewise model transitions from the latest regime. The approach in this paper recognises that the most relevant dataset in the episodic, recurrent nature of electricity dynamics may not be the most recent. This methodology provides a dynamic calibration dataset approach that is based on cluster analysis applied to fundamental market regime indicators, as well as structural time series breakpoint analyses. Forecasting is based upon applying a hybrid fundamental optimisation model with a neural network to the appropriate calibration data. The results outperform other benchmark models in backtesting on data from the Iberian electricity market of 2017, which presents a considerable number of market structural breaks and evolving market price drivers

Air temperature forecasting using machine learning techniques: a review

Efforts to understand the influence of historical climate change, at global and regional levels, have been increasing over the past decade. In particular, the estimates of air temperatures have been considered as a key factor in climate impact studies on agricultural, ecological, environmental, and industrial sectors. Accurate temperature prediction helps to safeguard life and property, playing an important role in planning activities for the government, industry, and the public. The primary aim of this study is to review the different machine learning strategies for temperature forecasting, available in the literature, presenting their advantages and disadvantages and identifying research gaps. This survey shows that Machine Learning techniques can help to accurately predict temperatures based on a set of input features, which can include the previous values of temperature, relative humidity, solar radiation, rain and wind speed measurements, among others. The review reveals that Deep Learning strategies report smaller errors (Mean Square Error = 0.0017 °K) compared with traditional Artificial Neural Networks architectures, for 1 step-ahead at regional scale. At the global scale, Support Vector Machines are preferred based on their good compromise between simplicity and accuracy. In addition, the accuracy of the methods described in this work is found to be dependent on inputs combination, architecture, and learning algorithms. Finally, further research areas in temperature forecasting are outlined

Wind power long-term scenario generation considering spatial-temporal dependencies in coupled electricity markets

This article belongs to the Section A3: Wind, Wave and Tidal EnergyWind power has been increasing its participation in electricity markets in many countries around the world. Due to its economical and environmental benefits, wind power generation is one of the most powerful technologies to deal with global warming and climate change. However, as wind power grows, uncertainty in power supply increases due to wind intermittence. In this context, accurate wind power scenarios are needed to guide decision-making in power systems. In this paper, a novel methodology to generate realistic wind power scenarios for the long term is proposed. Unlike most of the literature that tackles this problem, this paper is focused on the generation of realistic wind power production scenarios in the long term. Moreover, spatial-temporal dependencies in multi-area markets have been considered. The results show that capturing the dependencies at the monthly level could improve the quality of scenarios at different time scales. In addition, an evaluation at different time scales is needed to select the best approach in terms of the distribution functions of the generated scenarios. To evaluate the proposed methodology, several tests have been made using real data of wind power generation for Spain, Portugal and France