The reliability of a natural gas system involves the capacity of the supply, transportation, storage and distribution system to provide service without short-term interruptions in the event of contingencies. Typically, increasing the gas supply reliability implies diversification of gas sources, transportation redundancies or larger gas storage capabilities. In addition, the combined operative uncertainty of the transportation pipeline and gas supply are not considered when assessing the impact of new infrastructure seeking to increase the gas supply reliability. To overcome these deficiencies, we propose: (i) a stochastic cost-benefit analysis; (ii) a pipeline contingency model using topographical, societal (violence) and pipeline information; and (iii) a supply contingency model of scheduled and unscheduled maintenance. Moreover, we consider both the gas supply and transportation uncertainties using a Monte Carlo simulation and an optimization model; furthermore, the expected cost-benefit is estimated. Our methodology is applied and calibrated to the Colombian natural gas system to estimate the expected cost-benefit of a new pipeline: Jobo – Medellín. The results show that the expected benefit-cost ratio (BCR) of this pipeline is 2.02 and that the probability of having an economic benefit greater than the cost is equal to 99.0%.
Weather derivatives are financial instruments that can be used by organizations or individuals to hedge risks associated with adverse weather conditions. Weather conditions can directly decrease profits by affecting the volume of sales or costs. This paper develops a methodology for temperature option pricing in equatorial regions. In this approach, temperature is forecast by combining deterministic and stochastic models. We find that forecasting daily temperature with a model that combines a truncated third-order Fourier series with a mean reversion stochastic process proves the most accurate for pricing the options. The methodology is calibrated with data gathered in Bogotá, Colombia, using Monte Carlo simulations.
We propose a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature time series using copula functions. The use of copulas for the simulation gives flexibility to represent the serial stochastic variability of the solar irradiation and the air temperature affecting the photo-voltaic (PV) panel energy output. Moreover, it allows to have more control on the desired properties of the time series, not only in the temporal and cross-dependencies, but also in the marginal distributions. We use mixtures of zero mass adjusted density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time marginal distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, accurately models the stochastic phenomena.
There is limited evidence on the gender differences and location-specific built-environment factors associated with bicycling in Latin American cities. This study aimed to assess commuting in Bogotá by (1) analyzing the gender-specific trend of the standardized number of bicycle commuters during 2005–2017; and (2) assessing the socio-demographic, community, built-environment and natural factors associated with bicycle commuting stratified by gender. This secondary-data analysis included data from the Household Travel Surveys and Multipurpose Surveys to calculate the number of bicycle commuters per habitant from 2005 to 2017 by gender. We assessed the socio-demographic and built-environment factors fitting generalized additive models stratified by gender using the 2015 Household Travel Survey. Although both women and men increased the standardized number of bicycle commuters, male commuters show a steeper trend than women, evidencing the widening gender gap in bicycle commuting over time.
In the petroleum industry, there is an ever-increasing interest in oil recovery processes with high hydrocarbon extraction rates. One of the most common oil recovery processes is waterflooding, which involves the injection of water into a reservoir. This process is often challenging, as there is uncertainty in the reservoir’s properties. In this paper, we propose an optimal waterflooding management methodology for setting the producer and injector wells conditions to maximize the net present value (NPV). Our methodology integrates a predictive analytical model, which models the reservoir performance and forecasts the production rates based on the producer and injector well operating conditions.
Road safety research in low- and middle-income countries is limited, even though ninety percent of global road traffic fatalities are concentrated in these locations. In Colombia, road traffic injuries are the second leading source of mortality by external causes and constitute a significant public health concern in the city of Bogotá. Bogotá is among the top 10 most bike-friendly cities in the world. However, bicyclists are one of the most vulnerable road-users in the city.