Optimization of micro-grid system using MOPSO

The world population depends highly on fossil fuels, particularly for transportation and power generation. This dependency leads to oil price increases because of the depletion of fossil fuels. Burning of fossil fuels also increases greenhouse gas emissions that are greatly responsible for global warming. Thus, electric vehicles (EVs) are considered one of the premium solutions in the land transportation system because they can significantly reduce the dependency on crude oil and minimize transportation-related carbon dioxide emissions along with other pollutants. This study presents an extensive review of the three key areas of EV research, namely, EV charging technologies, the various impacts of EVs, and optimal EV charging station (CS) placement and sizing. Several technical publications related to EV charging technologies are highlighted, and the performance comparison of different EV technologies is discussed. A review of literature on these key areas reveals an increasing interest in these topics in the last decade, with the impacts of EV on the electric power system and the optimal placement and sizing of CS issues widely investigated. By providing an overview of these areas, this study demonstrates the current issues and challenges of widespread deployment of EVs in the market as well as the future research direction in this field. A total of 185 publications are arranged and appended for quick referencing.

A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles

An adaptive Cuckoo search algorithm for optimisation

Molecular docking is a process through which small molecules are docked into the macromolecular structures for scoring its complementary values at the binding sites. It is a vibrant research area with dynamic utility in structure-based drug-designing, lead optimization, biochemical pathway and for drug designing being the most attractive tools. Two pillars for a successful docking experiment are correct pose and affinity prediction. Each program has its own advantages and drawbacks with respect to their docking accuracy, ranking accuracy and time consumption so a general conclusion cannot be drawn. Moreover, users don't always consider sufficient diversity in their test sets which results in certain programs to outperform others. In this review, the prime focus has been laid on the challenges of docking and troubleshooters in existing programs, underlying algorithmic background of docking, preferences regarding the use of docking programs for best results illustrated with examples, comparison of performance for existing tools and algorithms, state of art in docking, recent trends of diseases and current drug industries, evidence from clinical trials and post-marketing surveillance are discussed. These aspects of the molecular drug designing paradigm are quite controversial and challenging and this review would be an asset to the bioinformatics and drug designing communities.

Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective

Coordinated design of PSSs and SVC via bacteria foraging optimization algorithm in a multimachine power system

Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method developed in 1995 by Eberhart and Kennedy based on the social behaviors of birds flocking or fish schooling. A number of basic variations have been developed due to improve speed of convergence and quality of solution found by the PSO. On the other hand, basic PSO is more appropriate to process static, simple optimization problem. Modification PSO is developed for solving the basic PSO problem. The observation and review 46 related studies in the period between 2002 and 2010 focusing on function of PSO, advantages and disadvantages of PSO, the basic variant of PSO, Modification of PSO and applications that have implemented using PSO. The application can show which one the modified or variant PSO that haven’t been made and which one the modified or variant PSO that will be developed.

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Siti Sophiyati Yuhaniz

Papers

Particle Swarm Optimization: Technique, System and Challenges