Probabilistic approach to multi-objective Volt/Var control of distribution system considering hybrid fuel cell and wind energy sources using Improved Shuffled Frog Leaping Algorithm

Deregulation and restructuring in power systems, the ever-increasing demand for electricity, and concerns about the environment are the major driving forces for using Renewable Energy Sources (RES). Recently, Wind Farms (WFs) and Fuel Cell Power Plants (FCPPs) have gained great interest by Distribution Companies (DisCos) as the most common RES. In fact, the connection of enormous RES to existing distribution networks has changed the operation of distribution systems. It also affects the Volt/Var control problem, which is one of the most important schemes in distribution networks. Due to the intermittent characteristics of WFs, distribution systems should be analyzed using probabilistic approaches rather than deterministic ones. Therefore, this paper presents a new algorithm for the multi-objective probabilistic Volt/Var control problem in distribution systems including RES. In this regard, a probabilistic load flow based on Point Estimate Method (PEM) is used to consider the effect of uncertainty in electrical power production of WFs as well as load demands. The objective functions, which are investigated here, are the total cost of power generated by WFs, FCPPs and the grid; the total electrical energy losses and the total emission produced by WFs, FCPPs and DisCos. Moreover, a new optimization algorithm based on Improved Shuffled Frog Leaping Algorithm (ISFLA) is proposed to determine the best operating point for the active and reactive power generated by WFs and FCPPs, reactive power values of capacitors, and transformers’ tap positions for the next day. Using the fuzzy optimization method and max-min operator, DisCos can find solutions for different objective functions, which are optimal from economical, operational and environmental perspectives. Finally, a practical 85-bus distribution test system is used to investigate the feasibility and effectiveness of the proposed method.     

Synthesis of nano-structured La0.8Ba0.2MnO3 perovskite via a mechano-thermal route

In this study, barium-doped lanthanum manganite, La_0.8Ba_0.2MnO₃, was synthesized via a mechano-thermal route employing high energy ball milling and subsequent heat treatment. The structural evolution, morphology and thermal behaviour of the powders were evaluated using XRD, FESEM, and DTA/TGA, respectively. DTA/TGA results showed that the calcination temperature of the carbonates significantly decreased by increasing the milling time. The results revealed that single phase perovskite was formed at 900 °C in a milled sample for 2 h and this temperature decreased to 600 °C by increasing the milling time to 30 h. The mean crystallite size also decreased from 32 to 20 nm by increasing the milling time from 2 to 30 h. The reaction sequence of La_0.8Ba_0.2MnO₃ formation via the mechano-thermal route is proposed using XRD and DTA/TGA results. FESEM micrographs showed that the mean particle size of the perovskite phase is increased slightly from 30 to 40 nm by increasing the heat treatment temperature from 600 to 900 °C.     

The Effects of One and Double Heat Treatment Cycles on the Microstructure and Mechanical Properties of a Ferritic–Bainitic Dual Phase Steel

Metallurgical and Materials Transactions A - In this study, samples with ferritic–bainitic dual phase structures consisting of 62 pct bainite were obtained from the AISI 4140 steel...     

Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production

In this study, various Artificial Neural Networks (ANNs) were developed to estimate the production yield of greenhouse basil in Iran. For this purpose, the data collected by random method from 26 greenhouses in the region during four periods of plant cultivation in 2009–2010. The total input energy and energy ratio for basil production were 14,308,998 MJ ha^?1 and 0.02, respectively. The developed ANN was a multilayer perceptron (MLP) with seven neurons in the input layer, one, two and three hidden layer(s) of various numbers of neurons and one neuron (basil yield) in the output layer. The input energies were human labor, diesel fuel, chemical fertilizers, farm yard manure, chemicals, electricity and transportation. Results showed, the ANN model having 7-20-20-1 topology can predict the yield value with higher accuracy. So, this two hidden layer topology was selected as the best model for estimating basil production of regional greenhouses with similar conditions. For the optimal model, the values of the models outputs correlated well with actual outputs, with coefficient of determination (R²) of 0.976. For this configuration, RMSE and MAE values were 0.046 and 0.035, respectively. Sensitivity analysis revealed that chemical fertilizers are the most significant parameter in the basil production.     

Physical and mechanical properties of a poly-3-hydroxybutyrate-coated nanocrystalline hydroxyapatite scaffold for bone tissue engineering

A major challenge for tissue engineers is the design of scaffolds with appropriate physical and mechanical properties. The present research discusses the formation of ceramic scaffolding in tissue engineering. Hydroxyapatite (HAp) powder was made from bovine bone by thermal treatment at 900?°C; 40, 50 and 60%wt porous HAp was then produced using the polyurethane sponge replication method. Scaffolds were coated with poly-3-hydroxybutyrate (P3HB) for 30?s and 1?min in order to increase the scaffold??s mechanical properties. XRD, SEM and FT-IR were used to study phase structure, morphology and agent groups, respectively. In XRD and FT-IR data, established hydrogen bands between polymer and ceramic matrix confirm that the scaffold is formed as a composite. The scaffold obtained with 50%wt HAp and a 30?s coating was 90% porous, with an average diameter of 100?C400???m, and demonstrated a compressive strength and modulus of 1.46 and 21.27?MPa, respectively. Based on these results, this scaffold is optimised for the aforementioned properties and can be utilised in bone tissue engineering.     

Thermogravimetric analysis and kinetic study of heavy oil pyrolysis

Pyrolysis, so-called devolatilization, is one of the first steps of all thermochemical processes occurring in an inert atmosphere. The authors discuss the main kinetic features of heavy oil pyrolysis, on the basis of the data derived m from a TGA analysis and by using a kinetic model. The samples were heated over a range of temperature from 400 K to 430°C at various heating rates between 10 and 80°C/min. Experimental results showed that the effect of time is considerable in the case of tar conversion, compared to char and gases.     

A fast algorithm for feature extraction of hyperspectral images using the first order statistics

Multimedia Tools and Applications - A new supervised feature extraction method appropriate for small sample size situations is proposed in this work. The proposed method is based on the first-order...     

Thermal performance and energy saving investigation in a modified baseboard radiator and compare it with conventional heating systems—Experimental and CFD approach

In the present work, thermal performance of a new modified baseboard radiator is investigated experimentally based on the European Standard EN-442. Temperature distribution and thermal comfort conditions of the floor heating system and panel radiator is compared with the present system numerically. To validation of the simulation results, a comparison has been made between the simulation and the experimental obtained results. Comparison shows that there is a good agreement between them. The heat output rate of the new system increased about 46.06% compared with conventional baseboard radiant model and also the baseboard heating system is capable of providing better thermal comfort conditions than two other systems. Energy consumption in three systems is investigated experimentally by smart temperature control mechanism. Results show that energy consumption in the baseboard radiant is 83.03% and 55.96% lower than floor heating system and panel radiator, respectively.     

Collaboration barriers in BIM-based construction networks: A conceptual model

Building information modelling (BIM) teams, hereafter referred to as BIM-based construction networks, are teams whose possibly geographically dispersed members from various organisations and disciplines, perform project tasks on BIM-enabled projects. In recent years, BIM-based construction networks have progressively become the norm in executing BIM activities on projects. However, even though achieving BIM's full capabilities relies on effective collaboration among the team members in BIM-based construction networks, it is still a struggle for these members to collaborate. Nonetheless, only a few studies have been conducted to identify the barriers to strengthening team collaboration in BIM-based construction networks. To address this gap, the current study, by examining 73 journal articles on collaboration in BIM-based construction networks, builds upon a theoretical review of the literature. A conceptual model is presented to capture the main barriers to collaboration in BIM-based construction networks. The study benefits researchers as well as project managers. For researchers, the conceptual model provides an intermediate theory, namely, a theoretical basis to direct further knowledge creation attempts on the topic. In addition, the conceptual model supports project managers on BIM-enabled projects. That is, it simplifies the knowledge now available for practical applications enabling it to be translated into guidelines and practical instructions on real-life projects.     

Experimental characterization of the small strain shear modulus of soft clay stabilized with cement and nano-SiO2 using bender element tests

Bulletin of Engineering Geology and the Environment - The accurate and efficient modification of the static and dynamic properties of problematic soils is a primary concern in geotechnical...