A novel mppt technique based on mutual coordination between two pv modules/arrays

A novel maximum power point tracking (MPPT) technique based on mutual coordination of two photovoltaic (PV) modules/arrays has been proposed for distributed PV (DPV) systems. The proposed technique works in two stages. Under non-mismatch conditions between PV modules/arrays, superior performance stage 1 is active, which rectifies the issues inherited by the perturb and observe (P&O) MPPT. In this stage, the technique revolves around the perturb and observe (P&O) algorithm containing an intelligent mechanism of leader and follower between two arrays. In shading conditions, stage 2 is on, and it works like conventional P&O. Graphical analysis of the proposed technique has been presented under different weather conditions. Simulations of different algorithms have been performed in Matlab/Simulink. Simulation results of the proposed technique compliment the graphical analysis and show a superior performance and a fast response as compared to others, thus increasing the efficiency of distributed PV systems

Nature-inspired Methods for Stochastic, Robust and Dynamic Optimization

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of evolutionary algorithms, bio-inspired metaheuristics, or memetic methods, with empirical, innovative findings when used in different subfields of mathematical optimization, such as stochastic, dynamic, multimodal and robust optimization, as well as noisy optimization and dynamic and constraint satisfaction problems

A novel mine blast optimization algorithm (MBOA) based MPPT controlling for grid-PV systems

One of the most important areas in today's world is meeting the energy needs of various resources provided by nature. The advantages of renewable energy sources for many application sectors have attracted a lot of attention. The majority of grid-based enterprises use solar photovoltaic (PV) systems to collect sunlight as a reliable energy source. Due to solar PV's simple accessibility and efficient panel design, it is widely used in a variety of application scenarios. By employing the Maximum Power Point Tracking (MPPT) technique, the PV modules can typically operate at their best rate and draw the most power possible from the solar system. Some hybrid control mechanisms are utilized in solar PV systems in traditional works, which has limitations on the problems of increased time consumption, decreased efficiency, and increased THD. Thus, a new Mine Blast Optimization Algorithm (MBOA) based MPPT controlling model is developed to maximize the electrical energy produced by the PV panels under a different climatic situations. Also, an interleaved Luo DC-DC converter is used to significantly improve the output voltage of a PV system with a lower switching frequency. A sophisticated converter and regulating models are being created to effectively meet the energy demand of grid systems. The voltage source inverter is used to lower the level of harmonics and ensure the grid systems' power quality. Various performance indicators are applied to assess the simulation and comparative results of the proposed MBOA-MPPT controlling technique integrated with an interleaved Luo converter

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Bio-inspired optimization in integrated river basin management

Water resources worldwide are facing severe challenges in terms of quality and quantity. It is essential to conserve, manage, and optimize water resources and their quality through integrated water resources management (IWRM). IWRM is an interdisciplinary field that works on multiple levels to maximize the socio-economic and ecological benefits of water resources. Since this is directly influenced by the river’s ecological health, the point of interest should start at the basin-level. The main objective of this study is to evaluate the application of bio-inspired optimization techniques in integrated river basin management (IRBM). This study demonstrates the application of versatile, flexible and yet simple metaheuristic bio-inspired algorithms in IRBM. In a novel approach, bio-inspired optimization algorithms Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are used to spatially distribute mitigation measures within a basin to reduce long-term annual mean total nitrogen (TN) concentration at the outlet of the basin. The Upper Fuhse river basin developed in the hydrological model, Hydrological Predictions for the Environment (HYPE), is used as a case study. ACO and PSO are coupled with the HYPE model to distribute a set of measures and compute the resulting TN reduction. The algorithms spatially distribute nine crop and subbasin-level mitigation measures under four categories. Both algorithms can successfully yield a discrete combination of measures to reduce long-term annual mean TN concentration. They achieved an 18.65% reduction, and their performance was on par with each other. This study has established the applicability of these bio-inspired optimization algorithms in successfully distributing the TN mitigation measures within the river basin. Stakeholder involvement is a crucial aspect of IRBM. It ensures that researchers and policymakers are aware of the ground reality through large amounts of information collected from the stakeholder. Including stakeholders in policy planning and decision-making legitimizes the decisions and eases their implementation. Therefore, a socio-hydrological framework is developed and tested in the Larqui river basin, Chile, based on a field survey to explore the conditions under which the farmers would implement or extend the width of vegetative filter strips (VFS) to prevent soil erosion. The framework consists of a behavioral, social model (extended Theory of Planned Behavior, TPB) and an agent-based model (developed in NetLogo) coupled with the results from the vegetative filter model (Vegetative Filter Strip Modeling System, VFSMOD-W). The results showed that the ABM corroborates with the survey results and the farmers are willing to extend the width of VFS as long as their utility stays positive. This framework can be used to develop tailor-made policies for river basins based on the conditions of the river basins and the stakeholders' requirements to motivate them to adopt sustainable practices. It is vital to assess whether the proposed management plans achieve the expected results for the river basin and if the stakeholders will accept and implement them. The assessment via simulation tools ensures effective implementation and realization of the target stipulated by the decision-makers. In this regard, this dissertation introduces the application of bio-inspired optimization techniques in the field of IRBM. The successful discrete combinatorial optimization in terms of the spatial distribution of mitigation measures by ACO and PSO and the novel socio-hydrological framework using ABM prove the forte and diverse applicability of bio-inspired optimization algorithms

Journal of Telecommunications and Information Technology

kwartalni

Role of Peripheral Contacts in Structure and Function of c-Type Cytochromes

Structural perturbations influence many properties of proteins, but sequence variations are frequently observed in nature without perturbing the overall stability, fold, and function. In this thesis work, heme proteins cytochrome c and c2 have been used to provide insight into the relationship between peripheral contacts and its function. Recent studies with pathogenic cytochrome c mutations G41S and Y48H, and growth-inhibiting mutation K72A, have highlighted the importance of contacts between loops C and D in function of the protein. Characterization of these variants shows that loop D local stability and dynamics are altered upon loop C perturbation, influencing electron transfer, alkaline transition, and peroxidase activity. Effects of these structural perturbations are different for human and horse heart proteins. Computational models suggest these differences may depend on whether the native peripheral contacts involving loops C and D are preserved. These contacts are also important for the cooperative acid unfolding transition. Loop D packs closely to the 60’s helix, forming additional intermolecular contacts for the protein to fold into a compact state with a Met80-ligated 6-coordinate heme iron. Y67R mutation perturbs these inner peripheral contacts and triggers a conformational rearrangement to induce Lys-ligation. Conformational rearrangements are important in cytochrome c. Interaction between cardiolipin and cytochrome c breaks up native peripheral contacts, which triggers a conformational rearrangement that enhances peroxidase activity so the protein functions as a peroxidase instead of an electron carrier. The heme ligation state of the species responsible for the increased peroxidase activity has been under debate. Characterization of Y67H, a variant that readily forms bisHis-ligation upon structural perturbation, suggests that bisHis-ligated species is not the species responsible for the enhanced peroxidase activity. Peripheral contacts are key participants in the proton-coupled electron transfer mechanism of cytochrome c2, an electron carrier in the bacterial photosynthetic electron transfer pathway. A calorimetric characterization of Rhodospirillum rubrum cytochrome c2 suggests that His42, a residue hydrogen-bonded to heme propionate 7, participates in proton transfer and is responsible for the pH-dependent reduction potential. Preliminary studies designed to probe the relationship between peripheral contacts and the heterogeneity of unfolded states are also discussed

Genetic determination and layout rules of visual cortical architecture

The functional architecture of the primary visual cortex is set up by neurons that preferentially respond to visual stimuli with contours of a specific orientation in visual space. In primates and placental carnivores, orientation preference is arranged into continuous and roughly repetitive (iso-) orientation domains. Exceptions are pinwheels that are surrounded by all orientation preferences. The configuration of pinwheels adheres to quantitative species-invariant statistics, the common design. This common design most likely evolved independently at least twice in the course of the past 65 million years, which might indicate a functionally advantageous trait. The possible acquisition of environment-dependent functional traits by genes, the Baldwin effect, makes it conceivable that visual cortical architecture is partially or redundantly encoded by genetic information. In this conception, genetic mechanisms support the emergence of visual cortical architecture or even establish it under unfavorable environments. In this dissertation, I examine the capability of genetic mechanisms for encoding visual cortical architecture and mathematically dissect the pinwheel configuration under measurement noise as well as in different geometries. First, I theoretically explore possible roles of genetic mechanisms in visual cortical development that were previously excluded from theoretical research, mostly because the information capacity of the genome appeared too small to contain a blueprint for wiring up the cortex. For the first time, I provide a biologically plausible scheme for quantitatively encoding functional visual cortical architecture by genetic information that circumvents the alleged information bottleneck. Key ingredients for this mechanism are active transport and trans-neuronal signaling as well as joined dynamics of morphogens and connectome. This theory provides predictions for experimental tests and thus may help to clarify the relative importance of genes and environments on complex human traits. Second, I disentangle the link between orientation domain ensembles and the species-invariant pinwheel statistics of the common design. This examination highlights informative measures of pinwheel configurations for model benchmarking. Third, I mathematically investigate the susceptibility of the pinwheel configuration to measurement noise. The results give rise to an extrapolation method of pinwheel densities to the zero noise limit and provide an approximated analytical expression for confidence regions of pinwheel centers. Thus, the work facilitates high-precision measurements and enhances benchmarking for devising more accurate models of visual cortical development. Finally, I shed light on genuine three-dimensional properties of functional visual cortical architectures. I devise maximum entropy models of three-dimensional functional visual cortical architectures in different geometries. This theory enables the examination of possible evolutionary transitions between different functional architectures for which intermediate organizations might still exist