Monitoring systems for managing natural resources: economics, indicators and environmental externalities in a Costa Rican watershed

The worsening degradation of natural resources urgently requires the adoption of more sustainable management practices. This need has led to growing interest and investment in monitoring systems for tracking the condition of natural resources. This study is concerned with the design of monitoring systems that have direct relevance for the management of natural resources. We call these Policy Relevant Monitoring Systems (PRMS). Such systems have several key characteristics. They provide: a) a decision framework for selecting resource problems to monitor that offer potentially large social payoffs relative to the costs of monitoring, b) timely, including early warning information on emerging problems, c) a means of identifying the causes of an emerging problem, d) an analytical framework for identifying options for corrective action, e) an institutional framework for achieving ownership among key stakeholders (the resource users and those affected by the resource use) and agreement about emerging problems, the corrective actions to take, and effective implementation, and f) a built-in mechanism for learning from past experience to improve the performance of the monitoring system over time. The approach is developed and illustrated through detailed examination of the Arenal-Tempisque watershed in Costa Rica. This watershed exhibits classic multiple user and externality problems: deforestation by dairy and cattle farmers in the upper watershed leads to soil erosion and siltation of the various reservoirs that feed an important hydro-electric power generation system, and agro-chemical use by irrigated farmers has adverse impacts on a highly valued wetlands park and on wildlife and fishing in the lower reaches of the watershed.Natural resources., Environmental degradation., Costa Rica, Watershed management.,

Reasoning about the Reliability of Diverse Two-Channel Systems in which One Channel is "Possibly Perfect"

This paper considers the problem of reasoning about the reliability of fault-tolerant systems with two "channels" (i.e., components) of which one, A, supports only a claim of reliability, while the other, B, by virtue of extreme simplicity and extensive analysis, supports a plausible claim of "perfection." We begin with the case where either channel can bring the system to a safe state. We show that, conditional upon knowing pA (the probability that A fails on a randomly selected demand) and pB (the probability that channel B is imperfect), a conservative bound on the probability that the system fails on a randomly selected demand is simply pA.pB. That is, there is conditional independence between the events "A fails" and "B is imperfect." The second step of the reasoning involves epistemic uncertainty about (pA, pB) and we show that under quite plausible assumptions, a conservative bound on system pfd can be constructed from point estimates for just three parameters. We discuss the feasibility of establishing credible estimates for these parameters. We extend our analysis from faults of omission to those of commission, and then combine these to yield an analysis for monitored architectures of a kind proposed for aircraft

Contributions to smart grids based on renewable energy sources with hydrogen as backup system. Energy management system: design, modeling and physical implementation based on model predictive control theory

Atendiendo al concepto de Smart Grid (Red Inteligente), estos sistemas están íntimamente relacionados con el uso de los sistemas de generación renovable. A pesar de los beneficios de esta tecnología, su dependencia de los recursos ambientales hace imposible garantizar el balance de energía entre generación y demanda en todo momento. Para ello, la hibridación de sistemas, así como el uso de sistemas basados en hidrógeno, se muestra como una solución técnica viable para resolver o mitigar los problemas asociados a este tipo de tecnologías. El empleo de este tipo de sistemas híbridos plantea una mayor complejidad en materia de gestión debido a la elevada cantidad de parámetros y factores a tener en cuenta de cara a garantizar un óptimo reparto energético en función de la aplicación y el estado energético del sistema. En este sentido, han de considerarse ciertos aspectos asociados a la operación real de los sistemas, tales como la topología del sistema, costes de operación y mantenimiento, la necesidad de un control de tensión de carga para baterías, la degradación de los equipos, la dinámica de cada sistema, las pérdidas asociadas al punto de trabajo, o parámetros relacionados con la calidad del suministro eléctrico. A tenor de lo anterior, es necesario el empleo de estrategias de gestión de la energía que permitan determinar el reparto energético entre dispositivos, con el objetivo de optimizar la respuesta del sistema desde el punto de vista técnico y económico, planteándose por lo tanto un problema de optimización multiobjetivo. Para dar respuesta al problema de optimización multiobjetivo propuesto, en la presente Tesis, se hace uso de una arquitectura de control distribuida, compuesta en un primer nivel por controladores locales, y en el nivel superior, se propone el uso de un controlador supervisor basado en técnicas de control predictivo (MPC). La función principal del controlador propuesto es determinar la consigna de operación de cada uno de los equipos que componen la Smart Grid, dando respuesta a la función objetivo propuesta de acuerdo a los criterios de diseño del sistema. Las ventajas de la utilización de técnicas de control predictivo respecto a otro tipo de técnicas son claras; permite el empleo de técnicas de control multivariable, permitiendo plantear problemas de optimización multiobjetivo con restricciones; así como implementar una estrategia de control basado en un horizonte de predicción, lo que permite al sistema adaptar la respuesta del controlador en base a acontecimientos futuros, mejorando la respuesta del sistema frente a técnicas de control meramente pasivas. Como base de conocimientos del controlador propuesto, en esta tesis se presenta un modelo lineal discreto generalista de la planta, calculado en cada periodo de muestreo, en base a una linealización recursiva, lo que permite aument ar la calidad del modelo respecto a soluciones basadas en torno a un único punto de linealización. El modelo incluye todos los parámetros necesarios para el control de una planta real, incluyendo los términos asociados al estado energético del sistema, tensión de operación de baterías, así como los parámetros técnicos y económicos. tales como degradación. oérdidas o coste de operación con el obietivo de definir una función de coste del sistema que permita su generalidad para cualquier tipo de aplicación u objetivo de diseño. Atendiendo al diseño del controlador propuesto, y con el objetivo de garantizar la generalidad requerida en todo el proceso, en la presente tesis se propone una metodología de diseño basado en el modelo propuesto y una función de coste que incluye todos los parámetros técnicos y económicos necesarios para resolver el problema de optimización multiobjetivo propuesto, independientemente de la aplicación y topología del sistema. Esta función objetivo permite establecer un problema de tracking de acuerdo al balance de potencia instantáneo del sistema, a la vez que son considerados los parámetros técnicos y económicos asociados a la respuesta del sistema, véase degradación y rendimiento de equipos, límites y dinámica de operación, costes de operación y mantenimiento, criterios de carga de baterías, etc. Para garantizar la generalidad del controlador propuesto, fomentando así su uso, independientemente de la aplicación y topología del sistema, en la presente tesis se propone una metodología de diseño y tuning de los parámetros del controlador, de acuerdo a la función objetivo propuesta y los criterios de diseño en materia de prioridad de uso y distribución de energía entre equipos. La propuesta metodológica está basada en las relaciones causa-efecto entre los distintos parámetros, las cuales permiten definir el comportamiento del sistema de acuerdo a la estrategia de gestión de la energía y objetivos de diseño propuestos. De forma similar, con el objetivo de considerar la optimización a corto y largo plazo del sistema, limitada por el concepto de horizonte deslizante propio de las técnicas de control predictivo, se hace uso de técnicas de control adicionales, las cuales actúan directamente sobre el proceso de ajuste de los parámetros del controlador. En este sentido, en base a la historia del sistema, se recalculan los parámetros del controlador, en caso de que sea necesario, actuándose directamente sobre los parámetros de ponderación, de tal forma que permita adaptar la respuesta dinámica o reparto energético de acuerdo a los criterios de diseño del controlador. Finalmente, la metodología de diseño y el controlador propuesto fueron validados sobre la micro red experimental del grupo de investigación TEP-192. Para ello, fue necesario el diseño, desarrollo e implementación de toda la electrónica de control, adquisición y electrónica de potencia para la correcta operación e integración de los equipos.Attending to the concept of Smart Grid, these systems are closely related to the use of renewable generation systems. Despite the benefits of this technology, its dependence on environmental resources makes it impo ssible to guarantee the balance of energy between generation and demand at all times. Far this, the hybridization of systems, as well as the use of hydrogen-basedsystems, is shown as a viable technical solution to salve or mitigate the probel ms associated with this type of technologies. The use of this type of hybrid systems poses a greater compel xity in terms of managementdue to the high number of parameters and factors to be taken into account in arder to guarantee an optimal energy distribution dependingon the application and the energy status of the system. In this sense, certain aspects associated with the actual operation of the systems, such as the topology, the operating and maintenance costs, the need far a charge voltage control far batterie s, the degradation of equipment, dynamics of each system, the lossesassociated with the working point, or parameters related to the quality of the electricity supply.In the light of the above, it is necessary to use energy management strategies to determine the energy distribution between devices, in arder to optimize the response of the system from a technicaland economic point of view, thereforeposing a multi-objective optimization problem. In arder to respond to the proposed multiobjective optimization problem, in this Thesis, a distributed control architecture is used, composed of local controllers at th e first level, and at the top level, the use of a supervisory controlel r based on predictive control techniques (MPC). The main function of the proposed controlel r is to det ermine the operating setpoint of each of the equipment that makes up the Smart Grid, responding to the proposed objective function accordingto the system design criteria. The advantages of using predictive control techniques over other types of techniques are clear; allows the use of multivariable control techniques, allowing multiobjective optimization in constrained problems; as well as implementing a control strategy based on a prediction horizon, which allows the system to adapt the response of the controller based on future events, improvingthe response of the system against merely passive control techniques. As a knowledge base of the proposed controller, this Thesis presents a general discrete linear model of the plant, calculated in each sampling period, based on a recursive linearization, which allows to increase the quality of the model with respectto solutions based on lathe to a singlepoint of linearization. The model includes all the necessary parameters far the control of a real plant, including the terms associated with the energy status of the system, battery operating voltage, as well as technical and economic parameters, such as degradation, losses or operating cost, with the objective of defining a system cost function that allows its generality far any type of application or design objective. Based on the design of the proposed controller, and with the objective of guaranteeing the generality required throuqhout the orocess. in this Thesis a desian methodoloav basedon the orooosed model and a cost function that includes ali the necessary technical and economic parameters are proposed to solve the proposed multiobjective optimization problem, regardless of the application and system topology. This objective function allows to establish a tracking problem according to the instantaneous power balance of the system, while the technical and economic parameters associated with the system response are considered, see equipment degradation and performance, limits and operating dynamics, operation and maintenance costs, battery charging criteria, etc. To guarantee the generality of the proposed controller, thus promoting its use, regardless of the application and topology of the system, this Thesis proposes a design and tuning methodology of the controller parameters, according to the proposed objective function and the design criteria in terms of priority of use and energy distribution. The methodological proposal is based on the cause-effect relationships between the different parameters, which allow defining the behavior of the system according to the energy management strategy and proposed design objectives. Similarly, in order to consider the short and long-term optimization of the system, limited by the concept of the sliding horizon typical of predictive control techniques, additional control techniques are used, which act directly on the process of adjustment of the parameters of the controller. In this sense, based on the history of the system, the parameters of the controller are recalculated, if necessary, acting directly on the weighting parameters, in such a way that it allows adapting the dynamic response or energy distribution according to the controller design criteria. Finally, the design methodology and the proposed controller were validated on the experimental micro grid of the TEP-192 research group. For this, it was necessary to design, develop and implement ali the control, acquisition and power electronics for the correct operation and integration of the equipment

Assessment of the level of awareness of intelligent buildings in Lagos State, Nigeria

The feasibility of achieving sustainable building development, an eco-friendly environment, and building investment conservation by integrating technological intelligence in buildings is highly viable. Intelligence features are, therefore, increasingly being incorporated in new designs and existing buildings to enhance the useful life, productivity and satisfaction of occupants, and a greener environment. This article evaluates the use of intelligent building systems in Nigeria. Primary data were obtained with the use of structured questionnaires that were self-administered to construction professionals in the private and public sectors in Lagos State. Data collected were analysed using descriptive and inferential statistics. Findings established that 90.24% of the respondents were aware of intelligent building systems, while practitioners who have worked or were working on buildings with intelligent features were limited to 51.2%. Approximately 64.60% of the respondents have used intelligent buildings previously, but only thirteen (13) notable buildings were identified to have employed intelligent building systems to a reasonable extent in the study area. The features of intelligent buildings with top level of awareness were CCTV system; access control and locks (mean = 3.96); alarms and alerts (mean = 3.92); HVAC system (mean = 3.90), and fire alarm system (mean = 3.89). Features with high level of utilisation include lighting system, which was the most utilised feature (mean = 3.57); fire alarm system (mean = 3.48); access control and lock; CCTV system (mean = 3.45), and HVAC system (mean = 3.43). The results showed that most of the features with a high level of awareness were also those with a high level of utilisation. The study established that the level of awareness and utilisation of intelligent building systems in the study area is high, but full adoption of the system is still low. &nbsp

Una nueva capa de protección a través de súper alarmas con capacidad de diagnóstico

An alarm management methodology can be proposed as a discrete event sequence recognition problem where time patterns are used to identify the process safe condition, especially in the start-up and shutdown stages. Industrial plants, particularly in the petrochemical, energy, and chemical sectors, require a combined approach of all the events that can result in a catastrophic accident. This document introduces a new layer of protection (super-alarm) for industrial processes based on a diagnostic stage. Alarms and actions of the standard operating procedure are considered discrete events involved in sequences, where the diagnostic stage corresponds to the recognition of a special situation when these sequences occur. This is meant to provide operators with pertinent information regarding the normal or abnormal situations induced by the flow of alarms. Chronicles Based Alarm Management (CBAM) is the methodology used to build the chronicles that will permit to generate the super-alarms furthermore, a case study of the petrochemical sector using CBAM is presented to build the chronicles of the normal startup, abnormal start-up, and normal shutdown scenarios. Finally, the scenario validation is performed for an abnormal start-up, showing how a super-alarm is generated.Se puede formular una metodología de gestión de alarmas como un problema de reconocimiento de secuencia de eventos discretos en el que se utilizan patrones de tiempo para identificar la condición segura del proceso, especialmente en las etapas de arranque y parada de planta. Las plantas industriales, particularmente en las industrias petroquímica, energética y química, requieren una administración combinada de todos los eventos que pueden producir un accidente catastrófico. En este documento, se introduce una nueva capa de protección (súper alarma) a los procesos industriales basados en una etapa de diagnóstico. Las alarmas y las acciones estándar del procedimiento operativo son asumidas como eventos discretos involucrados en las secuencias, luego la etapa de diagnóstico corresponde al reconocimiento de la situación cuando ocurren estas secuencias. Esto proporciona a los operadores información pertinente sobre las situaciones normales o anormales inducidas por el flujo de alarmas. La gestión de alarmas basadas en crónicas (CBAM) es la metodología utilizada en este artículo para construir las crónicas que permitirán generar las super alarmas, además, se presenta un caso de estudio del sector petroquímico que usa CBAM para construir las crónicas de los escenarios de un arranque normal, un arranque anormal y un apagado normal. Finalmente, la validación del escenario se realiza para un arranque anormal, mostrando cómo se genera una súper alarma