Coordination of flexible generation and transmission investments under uncertainty

The liberalization of power markets has led to a paradigm shift in the scope of the generation and transmission expansion planning. The assessment of this issue is complex because of the uncertainties that usually determine the long term evolution of the market. Moreover, and from the point of view of regulators and policy makers, an optimal assessment is of great interest because the lack of coordination between two types of investments can jeopardize competition and efficiency in the whole sector. In this regard, the literature suggests the use of holistic approaches, which are a suitable to address risks associated to the coordination of investments in the power market. This allows regulators to identify an efficient investment alternative, even in scenarios in which the uncertain variables evolve unfavorably. In that context, this paper proposes an improved method to assess the joint Transmission and Generation Expansion Planning segments, considering the inherent flexibility of generation investments, using the Real Options Valuation approach, calculated with the Least Squares Monte Carlo.CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI

Power Generation and Transmission Expansion Planning under Uncertainty considering Flexibility in Generation Investments

The process of liberalization of power markets has led to a paradigm shift in the joint expansion planning of the generation and transmission segments. The assessment of this problem is even more complex when considering the uncertainties that usually determine the long-term evolution of the system. Moreover, and from the point of view of regulators and policy makers, an optimal assessment is of great interest because the lack of coordination between the two types of investment can jeopardize competition and efficiency in the whole electricity sector. In this regard, the literature suggests the use of holistic approaches, which necessarily evaluate the risks associated with the coordination of investments in the power system, in order to allow regulators to identify an efficient investment alternative, considering scenarios in which the uncertain variables evolve unfavorably. In this context, this paper test a method to assess the joint expansion planning of the generation and transmission segments, considering the inherent flexibility of generation investments, using the Real Options Valuation approach, calculated with the Least Squares Monte Carlo. In order to validate this method, a case study has been simulated. It is shown that the consideration of investments’ flexibility allows increasing the system-wide social benefit through the coordinated planning of the generation and transmission segments.CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Dinámica de Sistemas aplicado a variables económicas

Presentación realizada en el marco del Proyecto PINV18-1827: Evaluación del impacto de políticas públicas en variables socioeconómicas y energéticas fundamentales del Paraguay: un enfoque basado en Sistemas Dinámicos.CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI

Agent-Based learning model for assessing strategic generation investments in electricity markets

The liberalization of electricity markets has significantly changed the perspective of the power generation business. Nowadays, generation companies pursue economic goals due their investment decisions are based on expectations of profitability and the risk of their alternatives. These expectations are difficult to predict because they depend upon various factors that are highly uncertain, including both exogenous uncertainties -such as variations of demand and endogenous uncertainties - such as the behavior of competing generation agents. This paper proposes a numerical tool that financially evaluates investment alternatives of generation companies based on a novel adaptive learning technique that links the generation agents' experiences under the current situation considering their expectations of profitability and risk. In this model, the Agent-based Computational Economics approach has been applied. This method represents generation agents through autonomous and heterogeneous entities pursuing economic goals and interacting through computer models.CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI

Option games applied for investment in power generation capacity

This kind of problem is usually described by a Game Theory (GT) approach. Furthermore, the investor must evaluate the investment alternatives taking into account the flexibility of the investment options, in order to face unfavorable market scenarios, including the strategic movements of its competitors. This kind of of problem is usually described by a Real Option (RO) approach. Therefore, it has been highlighted the necessity of developing a hybrid tool that combines the methods of GT and RO in order those inconveniences in the order to fully face in the power generation problem mentioned. This evaluation tool, called Options Games has been developed recently. Despite its enormous potential, this new methodology has not yet received significant attention in the field of power generation. This paper presents an application of the Options Games approach in order to describe the challenge of investment in power generation capacity in a duopoly market.CONACYT - Consejo Nacional de Ciencias y TecnologíaPROCIENCI

Analysis of Shared Heritability in Common Disorders of the Brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology