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This paper explores the relationship between adherence to corporate social responsibility goals and firm financial risk. Data on an international sample of 209 firms were collected for the period 2002 to 2022. Firm risk was proxied using stock return volatility and probability of default. The results show that the environmental performance of hospitality and tourism firms unequivocally influences firm risk, whether this risk is quantified as probability of default or volatility of stock market returns. This finding confirms that the adoption of environmentally sustainable and responsible practices is crucial not only for the environment but also for the stability of hospitality and tourism firms. [ABSTRACT FROM AUTHOR]

In the current study, a fixed‐bed downdraft gasifier was used, in addition to gas cleaning and treatment units, to evaluate hydrogen production from the waste from a date molasses factory. Date pits and pomace were gasified at a temperature of 800°C with oxygen‐rich air and standard air as the gasifying agents. Simulations were performed using the Cycle‐Tempo simulation tool. The impact of many process parameters (air–fuel ratio, gasification temperature, moisture content, oxygen concentration and temperature of the water–gas shift) on gas composition was investigated. The economic evaluation of hydrogen production is also discussed in this paper. Depending on the operating conditions, the results indicate that gasification of biomass in oxygen‐rich air improves hydrogen yield compared with air gasification of biomass. Over the range of operating conditions examined, the maximum hydrogen production reached 45.86% for pits and 35.81% for pomace from gasification with oxygen‐rich air while the H2 content reached 36.71 and 28.72% respectively for air gasification of pits and pomace. The cost analysis for the date waste gasification unit showed that the hydrogen production cost is $3/kg for date pits and $4/kg for pomace. The production of hydrogen from date molasses manufacturing waste helps to lessen reliance on fossil fuels and is an environmentally beneficial alternative source of renewable energy. [ABSTRACT FROM AUTHOR]

This paper introduces a Modified Reptile Search Algorithm (MRSA) designed to optimize the operation of distribution networks (DNs) considering the growing integration of renewable energy sources (RESs). The integration of RESs‐based Distributed Generation (DG) systems, such as wind turbines (WTs) and photovoltaics (PVs), presents a complex challenge due to its significant impact on DN operations and planning, particularly considering uncertainties related to solar irradiance, temperature, wind speed, consumption, and energy prices. The primary objective is cost reduction, encompassing electricity acquisition, PV and WTs unit costs, and annual energy losses. The proposed MRSA incorporates two strategies: the fitness‐distance balance method and Levy flight motion, enhancing its searching capabilities beyond standard Reptile Search Algorithm and mitigating local optima issues. The uncertainties in load demand, energy prices, and renewable energy generation are represented through probability density functions and simulated using Monte Carlo methods. Evaluation involves typical bentchmark functions and a real 112‐bus Algerian DN, comparing MRSA's efficacy with other optimization techniques. Results indicate that the proposed DN optimization program with WTs and PVs integration reduces annual costs by 21.43%, from 6.2715E + 06 to 4.9270E + 06 USD, reduce voltage deviations by 21.67%, from 77.1022 to 60.4007 USD, and enhance system stability by 2.59%, from 2.3699E + 03 to 2.4314E + 03 USD, compared with the base case. [ABSTRACT FROM AUTHOR]

This study addresses the challenging task of solving optimal reactive power dispatch (ORPD) while incorporating renewable energy resources (RERs), considering their stochastic and time‐varying nature. Specifically, the focus is on solving the stochastic optimal reactive power dispatch (SORPD) problem, taking into account uncertainties in load demand and generated power, as well as the reactive power generation capability of photovoltaic (PV) systems. To tackle this problem, an enhanced Artificial Gorilla Troops Optimizer (EGTO) is proposed, which utilizes multiple strategies. The objective is to minimize power loss and improve voltage profile and system stability under uncertain conditions. The algorithm is applied and tested on the IEEE 30‐bus system, both with and without the STATCOM functionality of the PV system. A comparison is conducted against other well‐known optimization algorithms. The results demonstrate the significant improvement achieved by incorporating the PV unit. The inclusion of the PV system leads to reduced expected power losses, voltage deviations, and improved voltage stability. Specifically, without and with the STATCOM functionality, the expected power loss decreases from 5.9218 MW at the base case to 1.1419 MW and 1.1197 MW, respectively. Similarly, the expected voltage deviation decreases from 1.9320 p.u. to 0.0909 p.u. and 0.0893 p.u., respectively, and the expected voltage stability decreases from 0.1336 p.u. to 0.07199 p.u. and 0.07142 p.u., respectively. [ABSTRACT FROM AUTHOR]

With the emergence of the Smart Grid concept, utility companies require more active participation of home users in the power sector. This changing paradigm is enabled by the wide deployment of multiple home assets such as small renewable‐based generators or storage facilities. In this context, consumers are no longer conceived as pure loads but also active agents that can exchange energy with the grid. To promote this active participation, utility companies promote different price‐based demand response programs to change the consumer patterns on pursuing a more efficient and economic system operation. In this regard, home energy management programs are becoming an essential tool for efficiently managing the different home users while addressing multiple demand response goals at minimum cost. In essence, a home energy management system is a computational optimization tool, which has to handle multiple uncertainties brought by weather forecast or energy pricing. This paper tackles this issue by developing a novel robust home energy management program based on interval optimization. In contrast to other related approaches, the proposal avoids the explicit use of interval arithmetic. Instead, the different uncertain parameters are sequentially incorporated into the scheduling task through different stages and interval‐based formulation. The developed methodology incorporates weather, load, energy pricing and plug‐in electric vehicle related uncertainties. A benchmark case study in a smart prosumer layout serves to prove the effectiveness of the new approach. [ABSTRACT FROM AUTHOR]

The constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices. [ABSTRACT FROM AUTHOR]

Here, an improved version of an African vultures optimization algorithm (AVOA), known as MAVOA is applied to solve the coordination issue between distance relays and directional overcurrent relays (DOCRs). The suggested method enhances the balance between exploration and exploitation features for the AVOA algorithm in order to find the optimal DOCR settings and operating time for zone‐2 distance relays. In 8‐bus, IEEE 30‐bus, and IEEE 39‐bus networks, the ability of the MAVOA technique to find the optimal solution for the coordination between DOCRs and distance relays is evaluated. Both MAVOA and AVOA algorithms are assessed in the case of standard and non‐standard DOCR characteristic curves. The results indicate the significant superiority of the suggested MAVOA algorithm in solving the coordination issue of the combined DOCR and distance relays. The reduction in operating time for DOCRs and zone‐2 of distance relays decreased by about 30% compared to the conventional AVOA technique. The results also prove the MAVOA's superiority over the recently developed algorithm and other algorithms in solving the coordination problem of the combined DOCRs and distance relays. Additionally, the total operating time for the non‐standard characteristic curve for DOCRs results in a reduction of the overall operating time of primary relays of more than 15%. [ABSTRACT FROM AUTHOR]

This article describes a technique for improving the performance of an offshore wind farm (OWF), which includes a permanent magnet synchronous generator (PMSG) driven by a variable‐speed wind turbine (VSWT) and connected to the grid through a high‐voltage direct current transmission system (HVDC). Under various network disturbances, the gorilla tropical optimization (GTO) metaheuristic method is used to fine‐tune the proportional‐integral (PI) controller gains for VSC‐based PMSG‐VSWT and VSC‐based HVDC transmission systems. This study compares several strategies for extracting the maximum power from a system while maintaining stability under symmetrical and unsymmetrical fault circumstances. Compared to different algorithms, GTO provides better results and improves system recovery and stability after disturbances. As a consequence, dynamic and transient stability may be enhanced. MATLAB/Simulink is used to implement the control mechanism. [ABSTRACT FROM AUTHOR]

The main objective of this work is the modeling of a combined heat and power (CHP) system that transforms waste from manufacturing date molasses in the Babylon province in central Iraq into electrical and thermal energy. A compact CHP facility that uses date waste (pomace and pits) as a feedstock is the subject of theoretical modeling and simulation research. The planned power plant consists of a downdraft gasifier, a microturbine (MT), and an organic Rankine cycle engine (ORC) as a bottom unit to maximize electric generation by recovering the MT exhaust gas heat and achieving a maximum electric output. The net electric production is 361.68 kW (280 kW from the MT unit and 81.68 kW from the ORC unit). To determine the best‐working fluid for the ORC system as a whole, three working fluids, including isopentane, benzene, and R113, were investigated. The temperature difference between the heat source and the fluid's boiling point is a key factor in choosing a more appropriate ORC working fluid. Isopentane is the most suitable working fluid for CHP applications, according to the findings of the simulation. The electric efficiency achieved is 30%, and the overall efficiency of the CHP plant was 56.87% from the gasification of date pits. The simulation results showed a satisfactory producer gas lower calorific value of 3.92 MJ k‐g‐1 for date pomace and 4.65 MJ k‐g‐1 for date pits, and cold gasification efficiencies of 73% and 76% for pomace and pits, respectively. © 2023 Society of Industrial Chemistry and John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Power‐Flow (PF) solution in isolated microgrids has attracted notable attention recently, because these systems present various particularities compared with the traditional PF solution in large meshed transmission networks. In this sense, this paper develops a novel Newton‐like PF solver for isolated microgrids. The new proposal is based on the Modified Midpoint method and shows high convergence order with relatively low computational burden. These characteristics bring superior theoretical performance compared with the standard Newton–Raphson (NR) method and other high order techniques, which has been conventionally used. Extensive simulations are performed on various small‐, and large‐scale benchmark Microgrids under different loading conditions and R/X ratios. Results provided serve to confirm the theoretical features of the developed solver, outperforming the NR technique as well as other recently developed solvers in all the studied systems with acceptable reliability even under high stressed conditions. [ABSTRACT FROM AUTHOR]

The present work develops a novel gorilla troops optimization algorithm (GTO) for optimal control of an autonomous microgrid. The proposed proportional‐integral controller parameters are properly designed by the GTO algorithm. It is based on the integral squared error to minimize the system objective function. The suggested islanded microgrid system operates with several decentralized, electronically interfaced energy resources and their local loads. The new optimal controller is applied to regulate its voltage at the different points of common coupling and its frequency despite the load variation. The performance of the new proposal is compared with the PI controller that was designed by a particle swarm optimization algorithm. It is observed that the microgrid functioning operation is improved even more by applying a GTO‐based than the other. The control strategy is thoroughly tested using a Matlab/Simulink simpower‐system environment under various microgrid operating situations. It is also implemented with OPAL 4510 real‐time hardware in the loop and a rapid control prototyping module. The different benchmark experiments serve to show the superiority of the new optimizer. [ABSTRACT FROM AUTHOR]

Aims: Hyperkalaemia (HK) is common in heart failure (HF) patients, related to renal dysfunction and medical treatment. It limits medical therapy optimization, which impacts prognosis. New potassium (K) binders help control HK, allowing better medical management of HF. Methods and results: A retrospective multicentre register included all outpatients with HF and HK (K ≥ 5.1 mEq/L) treated with patiromer according to current recommendations. We evaluated analytic and clinical parameters before starting the treatment and at 7, 30 and 90 days, as well as adverse events related to patiromer and treatment optimization. We included 74 patients (71.6% male) with a mean age of 70.8 years (SD 9.2). Sixty‐seven patients (90.5%) presented HK in the previous year. Forty patients (54.1%) underwent down‐titration of a renin–angiotensin–aldosterone inhibitor (RAASi) or a mineralocorticoid receptor antagonist (MRA), and 27 (36.5%) stopped any of them due to HK. Initial K was 5.5 mEq/L (SD 0.6), with a significantly reduction at 7 days (4.9 mEq/L (SD 0.8); P < 0.001), maintained at 90 days (4.9 mEq/L (SD 0.8); P < 0.001). There were no other electrolyte disturbances, with a slight improvement in renal function [glomerular filtration rate 39.6 mL/min (SD 20.4) to 42.7 mL/min (SD 23.2); P = 0.005]. Adverse events were reported in 33.9% of patients, the most common being hypomagnesaemia (16.3%), gastrointestinal disturbances (14.9%) and HK (2.8%). Withdrawal of patiromer was uncommon (12.2%) due to gastrointestinal disturbances in 66.7% of cases. Nine patients (12.2%) started on a RAASi, and 15 patients (20.3%) on an MRA during the follow‐up. Forty‐five patients (60.8%) increased the dose of RAASi or MRA, increasing to target doses in 5.4 and 10.8% of patients, respectively. At 90 days, NTproBNP values were reduced from 2509.5 pg/mL [IQR 1311–4,249] to 1396.0 pg/mL [IQR 804–4263]; P = 0.003, but the reduction was only observed in those who optimized HF medical treatment [NTproBNP from 1950.5 pg/mL (IQR 1208–3403) to 1349.0 pg/mL (IQR 804–2609); P < 0.01]. NYHA functional class only improved in 7.5% of patients, corresponding with those who optimized HF medical treatment. Compared with the previous 3 months before patiromer treatment, the rate of hospitalization was reduced from 28.4 to 10.9% (P < 0.01), and the emergency room visits from 18.9 to 5.4% (P < 0.01). Conclusions: In a real‐life cohort of patients with HF, patiromer reduced and maintained K levels during 3 months of follow‐up. The most common adverse events were hypomagnesaemia and gastrointestinal disturbances. Patiromer helps optimize medical treatment, increasing the percentage of patients treated with RAASi and MRA at target doses. At the end of follow‐up, natriuretic peptides values and hospital visits were reduced, suggesting the benefit of optimizing HF medical treatment. [ABSTRACT FROM AUTHOR]

This paper proposes an improved version of Barnacles mating optimizer (BMO) for solving the optimal allocation problem of distribution generator (DGs) in radial distribution systems (RDSs). BMO is a recent bioinspired optimization algorithm that mimics the intelligence behavior of Barnacles' mating. However, like with any metaheuristic optimization approach, it may face issues such as local optima trapping and low convergence rate. Hence, an improved BMO is adopted based on the quasi oppositional (QOBMO) and the chaos maps theories (CQOBMO). The two improvement methods are applied to increase the convergence performance of the conventional BMO. To prove the efficiency of the improved QOBMO and CQOBMO algorithms, 23 benchmark functions are used, and the accomplished results are compared with the conventional BMO. Then, the improved algorithm is applied to minimize the total power and energy losses in the distribution systems considering the uncertainty of DG power generation and time‐varying load demand. The uncertainty of DG is represented using photovoltaic‐based DG (PVDG). The improved method is employed to find the optimal power scheduling of PVDG and battery energy storage (BES) during 24 h. Two standard IEEE RDS (IEEE 33‐bus and IEEE 69‐bus) are used to simulate the case studies. Finally, the obtained results show that significant loss reductions (LRs) are achieved using the improved BMO where LRs reach 65.26%, and 68.86% in IEEE 33‐bus and 69‐bus, respectively, in the case of PVDG integration. However, using PVDG and BES the energy loss reductions reach 64% and 67.80% in IEEE 33‐bus and 69‐bus, respectively, which prove the efficiency of the improved BMO algorithm in finding the optimal solutions obtained so far. [ABSTRACT FROM AUTHOR]

The configuration, modelling and control of several possible hybrid systems for the propulsion of the existing tramway in Cuenca‐Ecuador are analysed. The system consists of novel renewable sources: Photovoltaic energy, hydrokinetic turbines and a biomass gasifier, which increases the reliability of the system and reduces CO2 emissions. In addition, a proton exchange fuel cell and a super capacitor thatsupply the necessary power for the tramway, as well as, a hydrogen tank that stores the excess energy. Energy management is done through renewable sources that recharge the super capacitor and the fuel cell at the charging stations along the tramway route. Different renewable hybrid systems have been analysed, which indicates that the most favourable case from a technical, environmental and economic point of view using data analysis and machine learning techniques is S4. Sensitivity analyses allow the study of variables such as CO2, net present cost and COE for different demand variations, as well as, for the minimum state of charge in the super capacitor. The results indicate the optimal net present cost is M$ 1.46 and 0.12 $ kWh−1 in cost of energy, validity of the proposed system in the round trip of the tramway. [ABSTRACT FROM AUTHOR]

Minimising the total power losses and enhancing the voltage profile is achieved using a proposed multi‐objective chaotic salp swarm algorithm with fuzzy logic decision‐making. The proposed multi‐objective chaotic salp swarm algorithm is utilised to determine the optimal size and location of photovoltaic in radial distribution system to minimise the total power losses, total voltage deviation, and maximise the voltage stability index. In addition, the proposed multi‐objective chaotic salp swarm algorithm is used to find suitable scheduling for battery energy storage charge/discharge during 24 h considering the intermittent nature of photovoltaic power generation. The proposed algorithm is tested on standard and practical radial distribution systems (IEEE 33‐bus and 94‐bus Portuguese systems). The performance of the proposed algorithm is validated by comparing its results with those obtained by other competitive optimisation techniques. The obtained results prove the ability of the proposed algorithm to achieve an efficient setting for photovoltaics and battery energy storages and determine their optimal allocations in order to minimise the power losses and enhance the voltage profile with satisfying all operating constraints. [ABSTRACT FROM AUTHOR]

Solving power-flow (PF) problem of ill-conditioned systems is still a challenge in realistic power systems due to most of available techniques are quite inefficient. This study aims to address this issue by introducing a novel PF solution paradigm. It basically reformulates the traditional continuous Newton's method in a multistep scheme, so that, the variables are progressively refined each step using different numerical arrangements. The developed solution paradigm envisages a novel family of PF techniques. For the sake of exemplify, two novel methods based on the introduced solution paradigm are developed. They are tested in several large-scale realistic ill-conditioned systems under different stressing and demanding conditions. Up to eight well known PF solution techniques are considered for comparison. Results shown that the introduced solution paradigm constitutes a promising framework for developing robust and efficient PF methods, which may be widespread used in industry applications. [ABSTRACT FROM AUTHOR]

This paper focuses on the optimal performance of a small tri‐generation power, heat, and cooling plant, which uses corn stover as the feedstock. First, 100 kg h−1 of the corn stover is converted into syngas by the gasification process, using a downdraft fixed‐bed reactor at gasification temperatures reaching 995 °C and with an oxidant–fuel ratio of 1.65. About 243.18 kg h−1 of product gas mass flow with 4.766 MJ kg−1 of calorific value is supplied to an externally fired gas turbine (EFGT) to convert this fuel to electrical power. It is estimated that the EFGT is capable of producing 70.57 kW of electrical power with a high‐temperature heat exchanger efficiency of 75% and a pressure ratio of 4.84 at a turbine inlet temperature of 875 °C. The absorption refrigeration system is used for the cooling process. The cooling power (ℚeva) of the absorption cooling system is 130.92 kW with a cooling tower temperature of 15 °C and a system performance coefficient (PC) of 0.6. The recovered heat flow to the generator (ℚgen) and the refrigerating heat flow are 82.62 kWth and 48.83 kWref, respectively, with a circulation ratio of 4.07. For the whole system (gasifier, EFGT, and absorption cooling), the gross electrical efficiency (ηnetEL) is 21.78% and the net thermal efficiency (ηth) is 47.43% with a system cooling‐to‐power ratio (CPR) of 1.88. The simulation of this system was conducted using Cycle‐Tempo software. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

This study presents a new energy management system (EMS) for the optimised operation of power sources of a hybrid charging station for electric vehicles and fuel cell vehicles. It is composed of a photovoltaic (PV) system, a battery and a hydrogen system as energy storage systems (ESSs), a grid connection, six fast charging units and a hydrogen supplier. The proposed EMS is designed to reduce the utilisation costs of the ESS and make them work, as much as possible, around their maximum efficiency points. The optimisation function depends on a cost prediction system that calculates the net present cost of the components from their previous performance and a fuzzy logic system designed for improving their efficiency. Finally, a particle swarm optimisation algorithm is used to solve the optimisation function and obtain the required power for each ESS. The proposed EMS is checked under Simulink environment for long‐term simulations (25 years). By comparing the EMS with a simpler one that optimises only the costs, it is proved that the proposed EMS achieves better efficiency of the charging station (+7.35%) and a notable reduction in the loss of power supply probability (−57.32%) without compromising excessively its average utilisation cost (+1.81%). [ABSTRACT FROM AUTHOR]

BACKGROUND Pea powdery mildew incited by Erysiphe pisi represents a major constraint for pea crops worldwide. Crop protection is largely based on chemical control, although recently a renewed interest in the discovery of natural products as alternatives to synthetic fungicides application has emerged. Thus, 12 bioactive plant and fungal metabolites belonging to different class of natural compounds were evaluated, together with a commercial fungicide, at different concentrations on detached pea leaves for their potential to inhibit spore germination and subsequent stages of fungal growth. The most effective metabolites were tested at different concentrations in planta under controlled conditions to evaluate the level of control achieved by treatments before, concurrently and after pathogen inoculation. Pathogen development was macroscopically scored on whole plants as percentage of disease severity and area under the disease progress curve. RESULTS: Cavoxin, inuloxin C and sphaeropsidin A strongly inhibited E. pisi germination and haustoria formation and reduced colony size. This effect was dose dependent. These results were further confirmed in whole plants by spraying the metabolites on plant leaves for preventive or curative control, which reduced fungal developmental of E. pisi at levels comparable with those obtained by application of the fungicide. CONCLUSIONS: Cavoxin, inuloxin C and sphaeropsidin A have potential as alternatives to synthetic fungicides for the control of crop pathogens of economic importance such as powdery mildew. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

In this study, the authors focus on solving the power‐flow (PF) problems of badly initialised/ill‐conditioned power systems, where the solution of these systems is a challenge for most of state‐of‐the‐art PF techniques. This challenge is increased in case of large and very large‐scale power systems which have a huge number of variables. Consequently, the PF techniques used should have a high degree of efficiency in order to handle the large vectors and matrix computations. In this study, a novel PF approach based on the Richardson extrapolation is proposed to solve these systems. The proposed approach is validated using various badly initialised/ill‐conditioned systems, comparing its performance with several well known PF techniques. The obtained results prove that the proposed approach is robust and efficient enough to properly manage the badly initialised/ill‐conditioned systems even if they consist of a huge number of buses, whereas the other PF techniques face different convergence difficulties. [ABSTRACT FROM AUTHOR]

In this paper, we present a teaching methodology based on a low‐cost embedded system platform that is easy to use and replicate, oriented to real‐time simulation project development. Designed for real‐time implementation of coding generated with MPLAB Device Blocks for Simulink. The purpose of this methodology is that students, teachers, and professionals will be able to carry out a theoretical project of a simulation in a computer, which includes complex mathematical modeling, to interact with its environment in real‐time. This system has been utilized already by students of Engineering of the first semesters as well as professors and researchers in updated and initialization courses in embedded systems within the University of Guadalajara. Finally, in the results section, we show a comparison of the proposed platform and a dSPACE platform applied in a control problem with an intricate mathematical model to process through a Hardware‐in‐the‐loop (HIL). [ABSTRACT FROM AUTHOR]

This study presents a new bidirectional DC-DC converter with high gains, based on impedance source. The design of the impedance network has been studied in step-up and step-down modes. The most significant innovations of the proposed converter are the linearity of the high gains in step-up and step-down modes with respect to the cycle variations and a full use of the duty cycle, very few passive and semiconductor elements are needed to implement the converter. The switching techniques are very simple, since only the switching of a single transistor in each mode is required. To improve efficiency, the cores of the inductors have been constructed with nanocrystalline material and the resistance of Z-red has been reduced as much as possible. Finally, a laboratory prototype has been implemented. [ABSTRACT FROM AUTHOR]

Load flow (LF) is an extensively used tool in planning and operation of power systems. Formulation of LF problem can be assimilated as a set of autonomous ordinary differential equations, therefore, many numeric methods can be used to solve this problem. However, LF methods often need to compute one or more Jacobian matrix inversions in each iteration. Owing to this fact, these methods might not be computationally efficient. In this study, the authors propose combined Runge-Kutta Broyden's LF (RK4B) method in order to reduce the required Jacobian matrix inversion to only one in the first iteration. In this proposed method, Broyden's approach is employed in fourth-order Runge-Kutta method. In addition, two modifications of the proposed method are presented to reduce the number of iterations and improve the computational performance. The proposed method and the two modifications are validated using several well- and ill-conditioned cases. Results show that the combined approach has better computational performance than the classical multistage numeric methods, besides it preserves the robustness features of fourth-order Runge-Kutta method. [ABSTRACT FROM AUTHOR]

The static synchronous series compensator ( SSSC) is an important component of flexible AC transmission systems ( FACTS) devices. SSSC can be used to control the active and reactive power flow in transmission lines. This paper presents a simplified model for SSSC in Newton-Raphson ( NR) load flow algorithm. It also presents strategies for handling the operating constraints of SSSC including the series-injected voltage and current passing through this device. The presented strategies are based on modifying the specified active and reactive powers with the maximum limits of the operating constraints. However, the SSSC is simply implemented in NR load flow algorithm based on the power injection approach. In this model, the SSSC is represented as injected loads as a function of the desired power flow through the transmission line. The main advantages of this model are avoiding the modification of Jacobin matrix and reducing the complexities of incorporating SSSC in the load flow algorithm. Moreover, the resistance of SSSC is considered in this model. Standard IEEE 14-bus and 30-bus test systems are used to verify the performance of the developed model and strategies handling the constraints of the SSSC model. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

This study proposes the generalised unified power flow controller (GUPFC) model in the hybrid current power mismatch Newton–Raphson formulation (HPCIM). In this model, active power, real and imaginary current components are injected at the terminals of series impedances of GUPFC. These injected values are calculated during the iterative process based on the desired controlled values and buses voltage at the terminals of GUPFC. The parameters of GUPFC can be calculated during the iterative process and the final values are updated after load flow convergence. Using the developed GUPFC model, the original structure and symmetry of the admittance and Jacobian matrices can still be kept, the changing of Jacobian matrix is eliminated. Consequently, the complexities of the computer load flow program codes with GUPFC are reduced. The HPCIM load flow code with the proposed model is written in C++ programming language. Where, the SuperLU library is utilised to handle the sparse Jacobian matrix. The proposed model has been validated using the standard IEEE test systems. [ABSTRACT FROM AUTHOR]

Probabilistic harmonic load flow (HLF) is currently enjoying renewed popularity. This is not surprising since in the near future, thousands of photovoltaic (PV) systems will be integrated into distribution systems. However, as yet, there is no model capable of explaining PV harmonic current behaviour in probabilistic HLF studies. To fill this gap, the harmonic modelling of PV systems proposed in this paper has three key points. First, it provides an effective model of the relationship between PV harmonic current emission and background harmonic voltages. Second, it statistically characterises PV harmonic currents (relative magnitude and phase angle) at different fundamental-frequency current output intervals using historical time-series data. In this statistical characterisation, the first fifth moments of each PV harmonic current are used to accurately approximate the raw probability density function (PDF) by means of the Legendre series. Finally, the third key point of this harmonic modelling is a method capable of determining the distribution functions of PV harmonic currents (absolute magnitude and phase angle), based on the statistical characterisation and a fundamental-frequency probabilistic PV model. The numerical results obtained confirm the effectiveness of this PV model. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, real-time results for a novel continuous-time adaptive tracking controller algorithm for nonlinear multiple input multiple output systems are presented. The control algorithm includes the combination of a recurrent high order neural network with block control transformation using a high order sliding modes technique as control law. A neural network is used to identify the dynamic plant behavior where a filtered error algorithm is used to train the neural identifier. A decentralized high order sliding mode, named the twisting algorithm, is used to design chattering-reduced independent controllers to solve the trajectory tracking problem for a robot arm with three degrees of freedom. Stability analyses are given via a Lyapunov approach. [ABSTRACT FROM AUTHOR]

Hybrid systems comprising battery energy storage systems (BESSs) and wind power generation entail considerable advances on the grid integration of renewable energy. Doubly fed induction generators (DFIGs) stand out among different wind turbine (WT) technologies. On the other hand, electrochemical batteries have proved to be valid for these purposes. In this paper, a comparative analysis is carried out between two alternative configurations for hybrid WT-BESS systems, where the BESS is connected either outside or inside the DFIG. The modeling of these two configurations and the control systems applied for achieving the coordinate operation of the energy sources (DFIG and batteries) are illustrated. The hybrid systems under study are evaluated by simulation under normal operation (wind speed fluctuations and grid demand changes) and grid faults. Simulation results show that both configurations improve the grid integration capability of the WT, although the configuration with external BESS presents better results since it can provide additional active/reactive power injection. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this study, a method for solving a probabilistic three‐phase power flow in radial distribution networks and taking into account the technical constraints of the system is presented. Regulation of voltage is one of the main problems to be taken into account in networks with distributed generation. The present study introduces a probabilistic model to determine the performance of the distribution system. This study considers the random nature of lower heating value of biomass and loads. This study presents a new hybrid technique combining the shuffled frog leaping algorithm with probabilistic three‐phase power flow that is solved by Monte Carlo method. Feasible results are achieved in a few iterations. The results show that the proposed technique can be applied to keep the voltages within the limits specified at each node of a distribution network with biomass power plants. The outcomes are attained using the unbalanced distribution system IEEE‐13 node and connecting biomass power plants at some nodes. This study shows that the power losses and voltage unbalance are reduced as a result of the inclusion of distributed generation. [ABSTRACT FROM AUTHOR]

ABSTRACT For the representation of wind farms in transient stability studies of electrical power systems, reduced models based on aggregating identical wind turbines are commonly used. In the case of a wind farm with different wind turbines coupled to the same grid connection point, it is usual to aggregate identical wind turbines operating in similar conditions into an equivalent one. However, in the existing literature, there are not any references to the aggregation of different wind turbines (same wind turbine technology but different rated power or components) into a single one. This paper presents a comparative study of four reduced models for aggregating different DFIG wind turbines, experiencing different incoming winds, into an equivalent model. The first of them is the classical clustering model, in which each equivalent model experiences an equivalent wind. The other reduced models have the same equivalent generation system but different equivalent mechanical systems. Thus, the second and third ones are compound models with a clustering aggregated mechanical system and individual simplified models, respectively, to approximate the individual mechanical power according to the incoming wind speeds. The fourth is a mixed model that uses an equivalent wind speed, which is applied to an equivalent mechanical system (equivalent rotor and drive train) in order to approximate the mechanical power of the aggregated wind turbines. The equivalent models are validated by means of comparison with the complete model of the wind farm when simulated under wind fluctuations and grid disturbances. Finally, recommendations with regard to the applicability of models are established. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

ABSTRACT Computer Programming competence is a good research field in which students of Computer Science can be assisted by an Intelligent Tutoring System (ITS). An ITS can guide the students in their learning process proposing the corresponding learning activities for each particular student. In this article, we will outline a proposal about how to use eLearning standard and automatic assessment techniques to build an ITS for learning to program. In addition, we will show the implemented system to test our proposal and how we have evaluated it with students in our university.© 2012 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:774-787, 2014; View this article online at ; DOI [ABSTRACT FROM AUTHOR]

This paper presents a facile incorporation of a static synchronous series compensator (SSSC) into the fast decoupled (FD) load flow method. The model is based on power injection formulation. The SSSC is represented by a series impedance and two power injection loads at the terminal nodes. These power injection loads are based on the specified power flow and updated during the iterative process. This developed model of SSSC can be implemented easily in the FD load flow method without changing in the basic computational algorithm. The developed model overcomes the problem of power flow SSSC model which exists when only the SSSC links two subnetworks. The FD load flow with the power injection model of SSSC has been validated using standard IEEE data. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this paper, a vision-based system is proposed, using the KINECT sensor ( KS), for three-dimensional ( 3D) trajectory tracking. A target object to track in the 3D space is defined in order to describe its trajectory on a virtual reality environment by an emulated quadrotor unmanned aerial vehicle ( UAV). The 3D position vector for the centroid of the target to track is recovered from image processing and information from the depth camera. A color-based object tracking approach is used. A stable fuzzy controller, as well as a LQR controller, for the emulated quadrotor UAV are implemented and compared, where the estimated 3D position of the target is given as reference signal. Important benefits of the proposed object tracking method are its efficiency in the use of the information provided by the KS with a low computational cost for image processing to estimate the target object position and the possibility of improving robustness of the image segmentation by online adjustment of the color filtering parameters. The main contribution of the paper is the use of the estimated position as the reference for the simultaneous control of attitude and translation of a quadrotor from a single controller. Experimental simulation results validate the proposed approach. [ABSTRACT FROM AUTHOR]

This study presents a new isolated DC/DC converter of full-bridge to connect a fuel cell to DC bus in a hybrid distribution generation system. This converter consists of a high-frequency transformer and a voltage booster circuit. The circuit has been designed and each isolated-gate bipolar transistor (IGBT) presents soft-switching during the whole power range of the converter. The switching losses of the IGBTs, the reverse-recovery losses of all of the diodes, and the core losses have almost been eliminated. To improve the efficiency, transformer cores and inductors have been built with material nanocrystalline. The efficiency is improved if this is compared with that of a conventional zero-voltage switching converter. Also, this converter can obtain a high-voltage gain and medium and high DC power can be converted. The analysis and switching techniques have been reported. Finally, to verify the principle of operation, a laboratory prototype of i kW has been performed. [ABSTRACT FROM AUTHOR]

The analysis of activities in CSCL ( Computer-Supported Collaborative Learning) environments can provide us with some interesting conclusions about collaborative learning processes themselves. Specifically, such an analysis can show the effectiveness of such processes and allow for the definition of intervention mechanisms which can motivate and engage the students in the learning activities. Until now, this analysis has focused on the collaboration process and the resulting product separately. We hypothesize that the use of Artificial Intelligence techniques can be useful for the production of a rule-based system that considers both the process and the product. Of the existing techniques, we propose the use of Genetic Classifier Systems (GCS) for their ability to evolve and adapt. The use of these rules allows for the identification and characterization of learning situations, in addition to the generation of feedback that can guide the students and the group towards a more effective learning experience. At the same time, the rule system can adapt to the new learning activities. The analysis method proposed in this article focuses on CSCL environments in which the collaboration takes the form of a conversation. We also present a tool that implements this approach and the results of its application to some learning activities, using an environment for collaborative learning of design. © Wiley Periodicals, Inc. Comput Appl Eng Educ 21: 704-716, 2013 [ABSTRACT FROM AUTHOR]

Matrix converters are becoming an actual alternative for many AC-AC power conversion applications. This paper shows that it is possible to use the six-phase matrix converter to increase the maximum voltage gain. A complete diagram of simulation is presented. At last, evaluation of the study over students is showed. © 2010 Wiley Periodicals, Inc. Comput Appl Eng Educ 21: 503-515, 2013 [ABSTRACT FROM AUTHOR]