Paraguay is characterized by its clean and renewable energy generation, being one of the largest per capita hydropower producers in the world. Paradoxically, biomass and petroleum products are privileged as sources for final energy consumption. In the transport sector, the public fleet is old and mainly runs on imported gasoil, while the private fleet has increased rapidly in the last decade, putting under pressure the sustainability of the urban transport. In this study we make an overview of the transport sector in Paraguay, evaluating the main challenges of the country in the transition to the electric mobility. We propose an analysis of the evolution of the vehicle fleet, the energy consumption in the transport sector, the different norms and regulation for electric vehicles and the incentives to accelerate the transition to electric mobility. We propose to reinforce not only the economic and tax incentives for electric vehicles, but to work in the whole ecosystem of the electric mobility to accelerate the transition to a cleaner transport sector.
Nowadays, Fuel Cells are considered a viable alternative to the traditional sources of energy. Proton Exchange Membrane Fuel Cell (PEMFC) stack is the most common and famous kind between various kinds of fuel cell stacks. The PEMFC mathematical model is a very vital problem to understand the main performance and electrochemical features of the fuel cell. In this research paper, a new optimization algorithm called Tunicate Swarm Algorithm (TSA) is used to extract the unknown parameters of PEMFC mathematical model. Three different types of PEMFCs stacks, namely, 250W, BCS 500W and Temasek 1kW are used to validate the viability and accurateness of the TAS in solving this optimization problem. Furthermore, statistical measures based on various metrics has been performed and calculated to prove the reliability of TSA in dealing with this PEMFC's problem. The simulation results of TSA are compared with Tree growth Algorithm (TGA), Harris Hawks Optimizer (HHO) and other recent metaheuristic optimization algorithms. The optimized unknown parameters of PEMFC stacks are used to study the performance of the PEMFC in case of different temperature and pressures. The achieved results confirm the stability and precision of TSA in identifying the PEMFC's unknown parameters compared to TGA, HHO and other recent algorithms.
The present paper has looked for applying Machine Learning techniques to analyze and classify network traffic from a security perspective, traffic like email, web, malware hashes and flood attacks have been analyzed resembling ICAP protocol architecture, the machine learning models have been trained and tested by using public Datasets and traffic obtained from active security devices, also several models have been proven obtaining high accuracy with them, leading to the conclusion that personalized security engines based on ML can be used to process malware and threatening traffic in Data Networks, as well as to improve the process of hardening on network devices.
The Kalman filter has been extensively used in different applications due to its strengths in estimating the system states under noisy observations. In this paper, a modification of the classical Kalman filter for nonlinear state estimation is presented; firstly, a polytopic set of linear discrete-time models based on a Takagi-Sugeno inference system is used to describe the nonlinear operating region. The stabilizing gains of the linear filters are calculated using Linear Matrix Inequalities (LMI), the proposal is evaluated through simulations.
In general, isolated locations are a challenge to provide electrical power. One of these places is Puerto Edén, in Chile, which has a very restrictive electricity service based on Diesel Generation. However, the geographical location has a hydroelectric potential that is not well exploited. This paper presents a case study on the design of a micro hydroelectric plant for Puerto Edén. Calculations of basic parameters for design, estimation of electrical consumption through statistical curves and the process for choosing electromechanical equipment are show. Finally, the design is checked using a simulation in Digsilent. The idea is to provide a baseline approach to isolated locations with hydroelectric potential and to help the Puerto Edén community to understand the resources available to them.
