Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

Demand side management studies on distributed energy resources: A survey

The number of distributed environmentally friendly energy sources and generators necessitates new operating methods and a power network board to preserve or even increase the efficiency and quality of the power supply. Similarly, the growth of matriculates promotes the formation of new institutional systems, in which power and power exchanges become increasingly essential. Because of how an inactive entity traditionally organizes distribution systems, the DG’s connection inevitably changes the system’s qualifications to which it is connected. As a consequence of the Distributed Generation, this presumption is currently legal and non-existent. This article glides on demand side management and analysis on distributed energy resources. Investigation of DSM along with zonal wise classification has been carried out in this survey. Its merits and applications are also presented.Universidad Tecnológica de Bolíva

Demand Side Management Studies on Distributed Energy Resources: A Survey

The number of distributed environmentally friendly energy sources and generators necessitates new operating methods and a power network board to preserve or even increase the efficiency and quality of the power supply. Similarly, the growth of matriculates promotes the formation of new institutional systems, in which power and power exchanges become increasingly essential. Because of how an inactive entity traditionally organizes distribution systems, the DG’s connection inevitably changes the system’s qualifications to which it is connected. As a consequence of the Distributed Generation, this presumption is currently legal and non-existent. This article glides on demand side management and analysis on distributed energy resources. Investigation of DSM along with zonal wise classification has been carried out in this survey. Its merits and applications are also presented

Demand Response Driven Load Scheduling in Formal Smart Grid Framework

In this technical report, we present the current state of the research conducted during the first part of the PhD project named “Demand Response Driven Load Scheduling in Formal Smart Grid Framework”. The PhD project focuses on smart grids which employ information and communication technologies to assist the electricity production, distribution, and consumption. Designing smart grid applications is a novel challenging task that requires modeling, integrating, and validating different grid aspects in an efficient way. The project tackles such challenges by proposing an effective framework to formally describe smart grid elements along with their interactions. To validate this framework, the report concentrates on deploying efficiency in managing the electricity consumption in households which requires focusing on different impacts of demand response programs running in the smart grid to engage consumers to participate. A demand response system is considered which is connected to all households and utilizes their information to determine an effective load management strategy taking into account the grid constraints imposed by distribution system operators. The main responsibility of the demand response system is scheduling the operation of appliances of a large number of consumers in order to achieve a network-wide optimized performance. Finally, the PhD report demonstrates the simulation results, publications, courses, and dissemination activities done during this period. They are followed by envisaging future plans that will lead to completion of the PhD study

Evolutionary Computation 2020

Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms

Putting food in context: Embedding-based food recommendations

Food is an integral part of everyday life, and food choices directly affect one’s health. Both academics and practitioners have attempted to help consumers make good decisions about their food choices and recommended better or healthier alternatives. However, in thinking about food it is important to put it in context, as each food item is often combined with other food items to create the gestalt of a recipe or meal. Understanding the complex interaction between food items that are used or consumed together is crucial to provide effective recommendations. In this research, I leverage tools from machine learning and textual analysis like the embedding approach for representation learning to understand food in its context and to build recommender systems that account for the complementarity or fit of co-consumed food items. I show that this consideration of fit among food items can lead to better and healthier food recommendations

Micro/Nano Manufacturing

Micro manufacturing involves dealing with the fabrication of structures in the size range of 0.1 to 1000 µm. The scope of nano manufacturing extends the size range of manufactured features to even smaller length scales—below 100 nm. A strict borderline between micro and nano manufacturing can hardly be drawn, such that both domains are treated as complementary and mutually beneficial within a closely interconnected scientific community. Both micro and nano manufacturing can be considered as important enablers for high-end products. This Special Issue of Applied Sciences is dedicated to recent advances in research and development within the field of micro and nano manufacturing. The included papers report recent findings and advances in manufacturing technologies for producing products with micro and nano scale features and structures as well as applications underpinned by the advances in these technologies