Convergence analysis and parity conservation of a new form of a quadratic explicit spline with applications to integral equations

In this study, a new form of a quadratic spline is obtained, where the coefficients are determined explicitly by variational methods. Convergence is studied and parity conservation is demonstrated. Finally, the method is applied to solve integral equations.Fil: Ferrari, Alberto José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas Ingeniería y Agrimensura. Escuela de Ciencias Exactas y Naturales. Departamento de Matemática; ArgentinaFil: Lara, Luis Pedro. Universidad del Centro Educativo Latinoamericano; ArgentinaFil: Santillan Marcus, Eduardo Adrian. Universidad Nacional de Rosario. Facultad de Ciencias Exactas Ingeniería y Agrimensura. Escuela de Ciencias Exactas y Naturales. Departamento de Matemática; Argentin

Comparative study of some numerical schemes for a fractional order model of HIV infection treatment

A fractional order mathematical model that already exists in the literature, was considered. This model was established to study the effects of medicinal treatment in people infected with the human immunodeficiency virus (HIV). The importance of this study is that the model evaluates, among other parameters, the density of healthy and HIV-infected CD$4^+$ T cells. These data are very necessary for the subject infected by the virus given the effects that an antiretroviral treatment causes in it. The objective of this work is to consider several numerical schemes that involve fractional derivatives in order to compare their behaviors and to obtain a good approximation of the mentioned model solution. Convergence of these schemes will be studied as well as sensitivity with respect to the variation of the parameters eta (drug efficacy) and alpha (fractional derivative order). Furthermore, through the collection of medical records of people living with HIV, it is intended to determine the optimal fractional derivative order for the model and to compare it with the classical model.Fil: Ferrari, Alberto José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Escuela de Formación Básica; ArgentinaFil: Lara, Luis Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; ArgentinaFil: Olguin, Mariela Carina. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Escuela de Formación Básica; ArgentinaFil: Santillan Marcus, Eduardo Adrian. Universidad Nacional de Rosario. Facultad de Ciencias Exactas, Ingeniería y Agrimensura. Escuela de Formación Básica; Argentin

Visibility Assessment of New Photovoltaic Power Plants in Areas with Special Landscape Value

Power plants based on renewable sources offer environmental, technical and economic advantages. Of particular importance is the reduction in greenhouse gas emissions compared to conventional power plants. Despite the advantages, people are often opposed to the construction of these facilities due to their high visual impact, particularly if they are close to places with a great cultural and/or landscape value. This paper proposes a new methodology for identifying the most suitable geographical areas for the construction of new photovoltaic (PV) power plants in zones of special scenic or cultural interest, helping to keep the environment free from the visual intrusions caused by these facilities. From several repeated analyses, the degree of visibility of the new PV plant, the potential observation time of passing visitors, considering the route they follow and their speed, and the increase in visibility of the plants when seen totally or partially with the sky as background, are determined. The result obtained is a map showing the ranking of the geographical areas based on a variable calculated in such analyses: the Global Accumulated Perception Time (GAPT). The application of this methodology can help the different agents involved in the decision-making process for the installation of new PV plant by providing them with an objective visibility criterion

Net demand short-term forecasting in a distribution substation with PV power generation

The integration of renewable energies, specifically solar energy, in electric distribution systems is increasingly common. For an optimal operation, it is very important to forecast the final net demand of the power distribution network, considering the variability of solar energy combined with the variability of the electric energy consumption habits of population. This paper presents the methodology followed to forecast the net demand in a power distribution substation. Two approaches are considered, the net demand direct prediction, and the indirect prediction with the forecasts of PV power generation and load demand. Artificial Neural Network (ANN) based models and autoregressive models with exogenous variables (ARX) are used to predict the net demand, directly and indirectly, for the 24 hours of the day-ahead. The methodology is applied to a medium voltage distribution substation and the direct and indirect forecasts are compared

Probabilistic reference model for hourly PV power generation forecasting

This paper presents a new probabilistic forecasting model of the hourly mean power production in a Photovoltaic (PV) plant. It uses the minimal information and it can provide probabilistic forecasts in the form of quantiles for the desired horizon, which ranges from the next hours to any day in the future. The proposed model only needs a time series of hourly mean power production in the PV plant, and it is intended to fill a gap in international literature where hardly any model has been proposed as a reference for comparison or benchmarking purposes with other probabilistic forecasting models. The performance of the proposed forecasting model is tested, in a case study, with the time series of hourly mean power production in a PV plant with 1.9 MW capacity. The results show an improvement with respect to the reference probabilistic PV power forecasting models reported in the literature

Electric power distribution planning tool based on geographic information systems and evolutionary algorithms

The expansion of electric distribution networks in new geographic areas is a tedious task. Once the position of the low voltage power substations has been decided, the planning engineers need to select the routes for the new power lines ensuring more efficient connections among the substations. This paper presents the methodology followed to plan the set of overhead power lines which achieves the optimal distribution network with the minimum installation and maintenance costs. The methodology is based on the use of Geographic Information Systems, which provide the needed functions to find feasible and economic routes for the new overhead power lines linking the substations, and an evolutionary algorithm which selects the optimal links. The application of the proposed methodology allows finding the optimal solution under an economic perspective in an automatic manner

Day-ahead probabilistic photovoltaic power forecasting models based on quantile regression neural networks

This paper presents the results obtained in the development of probabilistic short-term forecasting models of the power production in a photovoltaic power plant for the day-ahead. The probabilistic models are based on quantile regression neural networks. The structure of such neural networks is optimized with a genetic algorithm which selects the values for the main parameters of the neural network and the variables used as inputs. These input variables are selected among a set of variables which includes chronological, astronomical and forecasted weather variables related to the location of the power plant. The forecasts correspond to quantiles of the hourly power generation in the photovoltaic power plant for the daytime hours of the day-ahead. The forecasts are obtained in the first hours of the day, allowing their use for preparing bid offers for the day-ahead in electricity markets

Short-term net load forecast in distribution networks with PV penetration behind the meter

In recent years there has been a strong expansion of photovoltaic (PV) distributed generation systems. A high PV penetration level can cause uncertainty in the operation and management processes carried out by electric utilities, since most meters register the net load, i.e., the actual load minus the power generated by the PV systems behind the meter. The goal of this paper was to analyze the difference in the net load forecasting error achieved by models using or not using behind-the-meter PV generation data. The PV plant is connected to the lower voltage side of the power substation, representing a penetration level of more than 35% of the total load. The study shows that the best forecasting results are obtained with an indirect approach using two forecasting models, one for the total load and the other for the PV generation. However, the difference with respect to the results obtained with a unique net load forecasting model is almost negligible, which may be of special interest for power system distributors or other agents who do not have access to behind-the-meter generation data

Site selection for new PV power plants based on their observability

Despite the advantages that power plants based on renewable energies offer, there are some restrictions to the social acceptance of these facilities. One of these restrictions is the visual impact that large power plants may generate on people. This paper presents a new methodology for ranking the feasible places in a zone for the construction of new photovoltaic (PV) power plants according to their visibility. The methodology is based on the fuzzy viewshed and the distance decay methods, which enable to calculate the maximum number of hours in a mean day in which the new PV plant may be viewed by each possible observer. This number is related to the inhabitants in the zone, the size of the plant, the possible observers from paths and roads, and their distance to the PV plant. The proposed methodology is implemented in a Geographical Information System which allows the presentation of visual results that help to identify the best areas in the zone under study. This methodology can be useful to local authorities who have to authorize the installation of the new power plant, or investors who are trying to find the best locations from the point of view of visual impact