Don't blame the economists. It is an inverse problem!

The seriousness of the current crisis urgently demands new economic thinking that breaks the austerity vs. deficit spending circle in economic policy. The core tenet of the paper is that the most important problems that natural and social science are facing today are inverse problems, and that a new approach that goes beyond optimization is necessary. The approach presented here is radical in the sense that it identifies the roots in key assumptions in economic theory such as optimal behavior and stability to provide an inverse thinking perspective to economic modeling, of use in economic and financial stability policy. The inverse problem provides a truly multidisciplinary platform where related problems from different disciplines can be studied under a common approach with comparable results.

Exploring users inter-temporal preferences for measuring transport social equity effects

There exist different ways for defining a welfare function. Traditionally, welfare economic theory foundation is based on the Net Present Value (NPV) calculation where the time dependent preferences of considered agents are taken into account. However, the time preferences, remains a controversial subject. Currently, the traditional approach employs a unique discount rate for various agents. Nevertheless, this way of discounting appears inconsistent with sustainable development. New research work suggests that the discount rate may not be a homogeneous value. The discount rates may change following the individual’s preferences. A significant body of evidence suggests that people do not behave following a constant discount rate. In fact, UK Government has quickly recognized the power of the arguments for time-varying rates, as it has done in its official guidance to Ministries on the appraisal of investments and policies. Other authors deal with not just time preference but with uncertainty about future income (precautionary saving). In a situation in which economic growth rates are similar across time periods, the rationale for declining social optimal discount rates is driven by the preferences of the individuals in the economy, rather than expectations of growth. However, these approaches have been mainly focused on long-term policies where intergenerational risks may appear. The traditional cost-benefit analysis (CBA) uses a unique discount rate derived from market interest rates or investment rates of return for discounting the costs and benefits of all social agents included in the CBA. However, recent literature showed that a more adequate measure of social benefit is possible by using different discount rates including inter-temporal preferences rate of users, private investment discount rate and intertemporal preferences rate of government. Actually, the costs of opportunity may differ amongst individuals, firms, governments, or society in general, as do the returns on savings. In general, the firms or operators require an investment rate linked to the current return on savings, while the discount rate of consumers-users depends on their time preferences with respect of the current and the future consumption, as well as society can take into account the intergenerational well-being, adopting a lower discount rate for today’s generation. Time discount rate of social actors (users, operators, government and society) places a lower value in a future gain, but the uncertainty about future income strongly determines the individual preferences. These time and uncertainty depends on preferences and should be integrated into a transport policy formulation that may have significant social impacts. The discount rate of a user cannot be the same than the operator’s discount rate. The preferences of both are different. In addition, another school of thought suggests that people, such as a social group, may have different attitudes towards future costs and benefits. Particularly, the users have different discount rates related to their income. Some research work tried to modify user discount rates using a compensating weight which represents the inverse of household income level. The inter-temporal preferences are a proxy of the willingness to pay during the time. Its consideration is important in order to make acceptable or not a policy or investment

Using Clouds to Scale Grid Resources: An Economic Model

Infrastructure as a Service clouds are a flexible and fast way to obtain (virtual) resources as demand varies. Grids, on the other hand, are middleware platforms able to combine resources from different administrative domains for task execution. Clouds can be used by grids as providers of devices such as virtual machines, so they only use the resources they need. But this requires grids to be able to decide when to allocate and release those resources. Here we introduce and analyze by simulations an economic mechanism (a) to set resource prices and (b) resolve when to scale resources depending on the users’ demand. This system has a strong emphasis on fairness, so no user hinders the execution of other users’ tasks by getting too many resources. Our simulator is based on the well-known GridSim software for grid simulation, which we expand to simulate infrastructure clouds. The results show how the proposed system can successfully adapt the amount of allocated resources to the demand, while at the same time ensuring that resources are fairly shared among users.

Application of the agency theory for the analysis of performance-based mechanisms in road management

El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte, y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper develops a model based on agency theory to analyze road management systems (under the different contract forms available today) that employ a mechanism of performance indicators to establish the payment of the agent. The base assumption is that of asymmetric information between the principal (Public Authorities) and the agent (contractor) and the risk aversion of this latter. It is assumed that the principal may only measure the agent?s performance indirectly and by means of certain performance indicators that may be verified by the authorities. In this model there is presumed to be a relation between the efforts made by the agent and the performance level measured by the corresponding indicators, though it is also considered that there may be dispersion between both variables that gives rise to a certain degree of randomness in the contract. An analysis of the optimal contract has been made on the basis of this model and in accordance with a series of parameters that characterize the economic environment and the particular conditions of road infrastructure. As a result of the analysis made, it is considered that an optimal contract should generally combine a fixed component and a payment in accordance with the performance level obtained. The higher the risk aversion of the agent and the greater the marginal cost of public funds, the lower the impact of this performance-based payment. By way of conclusion, the system of performance indicators should be as broad as possible but should not overweight those indicators that encompass greater randomness in their results.

Hybrid wind-diesel power plant valuation and optimization using real option theory and dynamic programming

El sistema de energía eólica-diesel híbrido tiene un gran potencial en la prestación de suministro de energía a comunidades remotas. En comparación con los sistemas tradicionales de diesel, las plantas de energía híbridas ofrecen grandes ventajas tales como el suministro de capacidad de energía extra para "microgrids", reducción de los contaminantes y emisiones de gases de efecto invernadero, y la cobertura del riesgo de aumento inesperado del precio del combustible. El principal objetivo de la presente tesis es proporcionar nuevos conocimientos para la evaluación y optimización de los sistemas de energía híbrido eólico-diesel considerando las incertidumbres. Dado que la energía eólica es una variable estocástica, ésta no puede ser controlada ni predecirse con exactitud. La naturaleza incierta del viento como fuente de energía produce serios problemas tanto para la operación como para la evaluación del valor del sistema de energía eólica-diesel híbrido. Por un lado, la regulación de la potencia inyectada desde las turbinas de viento es una difícil tarea cuando opera el sistema híbrido. Por otro lado, el bene.cio económico de un sistema eólico-diesel híbrido se logra directamente a través de la energía entregada a la red de alimentación de la energía eólica. Consecuentemente, la incertidumbre de los recursos eólicos incrementa la dificultad de estimar los beneficios globales en la etapa de planificación. La principal preocupación del modelo tradicional determinista es no tener en cuenta la incertidumbre futura a la hora de tomar la decisión de operación. Con lo cual, no se prevé las acciones operativas flexibles en respuesta a los escenarios futuros. El análisis del rendimiento y simulación por ordenador en el Proyecto Eólico San Cristóbal demuestra que la incertidumbre sobre la energía eólica, las estrategias de control, almacenamiento de energía, y la curva de potencia de aerogeneradores tienen un impacto significativo sobre el rendimiento del sistema. En la presente tesis, se analiza la relación entre la teoría de valoración de opciones y el proceso de toma de decisiones. La opción real se desarrolla con un modelo y se presenta a través de ejemplos prácticos para evaluar el valor de los sistemas de energía eólica-diesel híbridos. Los resultados muestran que las opciones operacionales pueden aportar un valor adicional para el sistema de energía híbrida, cuando esta flexibilidad operativa se utiliza correctamente. Este marco se puede aplicar en la optimización de la operación a corto plazo teniendo en cuenta la naturaleza dependiente de la trayectoria de la política óptima de despacho, dadas las plausibles futuras realizaciones de la producción de energía eólica. En comparación con los métodos de valoración y optimización existentes, el resultado del caso de estudio numérico muestra que la política de operación resultante del modelo de optimización propuesto presenta una notable actuación en la reducción del con- sumo total de combustible del sistema eólico-diesel. Con el .n de tomar decisiones óptimas, los operadores de plantas de energía y los gestores de éstas no deben centrarse sólo en el resultado directo de cada acción operativa, tampoco deberían tomar decisiones deterministas. La forma correcta es gestionar dinámicamente el sistema de energía teniendo en cuenta el valor futuro condicionado en cada opción frente a la incertidumbre. ABSTRACT Hybrid wind-diesel power systems have a great potential in providing energy supply to remote communities. Compared with the traditional diesel systems, hybrid power plants are providing many advantages such as providing extra energy capacity to the micro-grid, reducing pollution and greenhouse-gas emissions, and hedging the risk of unexpected fuel price increases. This dissertation aims at providing novel insights for assessing and optimizing hybrid wind-diesel power systems considering the related uncertainties. Since wind power can neither be controlled nor accurately predicted, the energy harvested from a wind turbine may be considered a stochastic variable. This uncertain nature of wind energy source results in serious problems for both the operation and value assessment of the hybrid wind-diesel power system. On the one hand, regulating the uncertain power injected from wind turbines is a difficult task when operating the hybrid system. On the other hand, the economic profit of a hybrid wind-diesel system is achieved directly through the energy delivered to the power grid from the wind energy. Therefore, the uncertainty of wind resources has increased the difficulty in estimating the total benefits in the planning stage. The main concern of the traditional deterministic model is that it does not consider the future uncertainty when making the dispatch decision. Thus, it does not provide flexible operational actions in response to the uncertain future scenarios. Performance analysis and computer simulation on the San Cristobal Wind Project demonstrate that the wind power uncertainty, control strategies, energy storage, and the wind turbine power curve have a significant impact on the performance of the system. In this dissertation, the relationship between option pricing theory and decision making process is discussed. A real option model is developed and presented through practical examples for assessing the value of hybrid wind-diesel power systems. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. This framework can be applied in optimizing short term dispatch decisions considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. Comparing with the existing valuation and optimization methods, result from numerical example shows that the dispatch policy resulting from the proposed optimization model exhibits a remarkable performance in minimizing the total fuel consumption of the wind-diesel system. In order to make optimal decisions, power plant operators and managers should not just focus on the direct outcome of each operational action; neither should they make deterministic decisions. The correct way is to dynamically manage the power system by taking into consideration the conditional future value in each option in response to the uncertainty.