Optimal power flow by BAT search algorithm for generation reallocation with unified power flow controller

Optimal power flow with generation reallocation is a suitable method for better utilization of the existing system. In recent years, Flexible AC Transmission System (FACTS) devices, have led to the development of controllers that provide controllability and flexibility for power transmission. Out of the FACTS devices unified power flow controller (UPFC) is a versatile device, capable of controlling the power system parameters like voltage magnitude, phase angle and line impedance individually or simultaneously. The main aim of this paper is to minimize real power losses in a power system using BAT search algorithm without and with the presence of UPFC. Minimization of real power losses is done by considering the power generated by generator buses, voltage magnitudes at generator buses and reactive power injection from reactive power compensators. The proposed BAT algorithm based Optimal Power Flow (OPF) has been tested on a 5 bus test system and modified IEEE 30 bus system without and with UPFC. The results of the system with and without UPFC are compared in terms of active power losses in the transmission line using BAT algorithm. The obtained results are also compared with Genetic algorithm (GA).     

Advancements in the design and validation of an air pollution integrated assessment model for Spain

This paper describes the design and application of the Atmospheric Evaluation and Research Integrated model for Spain (AERIS). Currently, AERIS can provide concentration profiles of NO₂, O₃, SO₂, NH₃, PM, as a response to emission variations of relevant sectors in Spain. Results are calculated using transfer matrices based on an air quality modelling system (AQMS) composed by the WRF (meteorology), SMOKE (emissions) and CMAQ (atmospheric-chemical processes) models. The AERIS outputs were statistically tested against the conventional AQMS and observations, revealing a good agreement in both cases. At the moment, integrated assessment in AERIS focuses only on the link between emissions and concentrations. The quantification of deposition, impacts (health, ecosystems) and costs will be introduced in the future. In conclusion, the main asset of AERIS is its accuracy in predicting air quality outcomes for different scenarios through a simple yet robust modelling framework, avoiding complex programming and long computing times.     

Optimization of Improvable Flows by combining BAT Analysis and process simulation

This paper proposes a methodology to improve the sustainability of industrial processes combining two tools: BAT Analysis and process simulation. Both tools are jointly applied to identify the IF of the analyzed process, so that the most appropriate candidate techniques from an inventory can be selected. The selected alternatives are tested in different scenarios that are evaluated using simulation, which would determine the configuration that best improves the sustainability of the process. The combination of both tools in an integrated methodology will help decision makers to select the most sustainable configuration for a given process. The methodology is validated in a case study: a hydrogen production plant. After analysing several scenarios where different candidate techniques are implemented, results show that the IF identified can be highly improved when the appropriate combination of BAT is applied.     

Combining LCT tools for the optimization of an industrial process: material and energy flow analysis and best available techniques

Life cycle thinking (LCT) is one of the philosophies that has recently appeared in the context of the sustainable development. Some of the already existing tools and methods, as well as some of the recently emerged ones, which seek to understand, interpret and design the life of a product, can be included into the scope of the LCT philosophy. That is the case of the material and energy flow analysis (MEFA), a tool derived from the industrial metabolism definition.This paper proposes a methodology combining MEFA with another technique derived from sustainable development which also fits the LCT philosophy, the BAT (best available techniques) analysis. This methodology, applied to an industrial process, seeks to identify the so-called improvable flows by MEFA, so that the appropriate candidate BAT can be selected by BAT analysis. Material and energy inputs, outputs and internal flows are quantified, and sustainable solutions are provided on the basis of industrial metabolism.The methodology has been applied to an exemplary roof tile manufacture plant for validation. 14 Improvable flows have been identified and 7 candidate BAT have been proposed aiming to reduce these flows.The proposed methodology provides a way to detect improvable material or energy flows in a process and selects the most sustainable options to enhance them. Solutions are proposed for the detected improvable flows, taking into account their effectiveness on improving such flows.     

A Hybrid Model Using Bio-Inspired Metaheuristic Algorithms for Network Intrusion Detection System

Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one is to reduce the number of selected features for Network IDS. This objective was met through the hybridization of bio-inspired metaheuristic algorithms with each other in a hybrid model. The algorithms used in this paper are particle swarm optimization (PSO), multi-verse optimizer (MVO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale optimization algorithm (WOA), firefly algorithm (FFA), and bat algorithm (BAT). The second objective is to detect the generic attack using machine learning classifiers. This objective was met through employing the support vector machine (SVM), C4.5 (J48) decision tree, and random forest (RF) classifiers. UNSW-NB15 dataset used for assessing the effectiveness of the proposed hybrid model. UNSW-NB15 dataset has nine attacks type. The generic attack is the highest among them. Therefore, the proposed model aims to identify generic attacks. My data showed that J48 is the best classifier compared to SVM and RF for the time needed to build the model. In terms of features reduction for the classification, my data show that the MFO-WOA and FFA-GWO models reduce the features to 15 features with close accuracy, sensitivity and F-measure of all features, whereas MVO-BAT model reduces features to 24 features with the same accuracy, sensitivity and F-measure of all features for all classifiers.     

解读核设施放射性流出物释放的ALARA和BAT概念

基于对核设施放射性流出物释放最优化方面的ALARA和BAT这两个重要概念的理解,结合现存核设施放射性流出物的特征和污染消减技术,本文阐述了核设施放射性流出物排放的浓度控制原则,即以流出物消减的最佳可行技术为前提,引入良好的工程实践,适当考虑厂址条件等外部因素对流出物释放进行优化。     

Material Flow Analysis in a cooked mussel processing industry

Galicia (NW Spain) is an ideal environment for mussel culture owing to its excellent natural conditions. It is the first Spanish and European mussel producer and the second worldwide after China. More than 50% of the mussel collected in Galicia is used in the processing industry, which produces different products, as cooked mussel that is canned, frozen or used in the food industry.     

Power system stability enhancement in the presence of renewable energy resources and HVDC lines based on predictive control strategy

The renewable energy resources are increasingly employed as new electric power sources. However, their stochastic and uncertain behavior negatively influences the power system stability. In this paper, a hybrid system composed of PMSG-based wind farm, marine-current farm, and PV has been used to supply the network’s load. These resources have been connected to a nine-bus power system through a line-commutated HVDC link. A new control method has been proposed to enhance the damping characteristics of power system. This method is based on Generalized Predictive Control (GPC) for design of inverter current regulator (ICR) of HVDC link. In this regard, the BAT search algorithm has been employed for obtaining the best solution for the GPC’s objective function. In order to demonstrate the effectiveness of the proposed GPC-BAT method, the simulations using eigenvalue analysis and root-loci technique are presented. For further investigating the efficiency of conducted approach, a PID controller has been designed for controlling the ICR of HVDC link, and the results have been compared with those of GPC-BAT method. The comparisons have been made through a three-phase short circuit fault on the multi-machine power system in MATLAB software. The evaluations clearly show the effectiveness and superiority of the proposed approach.     

ACTS AERONAUTICAL EXPERIMENTS

This paper discusses a series of aeronautical experiments that utilize the advanced communication technology satellite (ACTS). As part of the ongoing effort to investigate commercial applications of ACTS technologies, NASA's Jet Propulsion Laboratory and various industry/government partners have developed a series of experiments that utilize the ACTS mobile terminal (AMT)¹ and the broadband aeronautical terminal¹ to investigate aeronautical uses of the ACTS. This paper discusses these experiments including the experiment configurations, technologies, results and future implications.     

电子节目指南在济南数字电视业务中的应用

本文结合实际工作经验,简要解析了电子节目指南(EPG)在济南广电数字电视业务中的应用