Bio inspired techniques for simultaneous design of multiple optimal power system stabilizers

Bio-inspired techniques are fields of study that are inspired from topics of connectionism, social behavior and emergence. Researchers have ventured into the intricacies involved with the techniques and devised algorithms based on their study. Such techniques are the focus of this thesis. The two bio-inspired techniques used for simultaneous design of power system stabilizers (PSSs) in this study are - Particle Swam Optimization (PSO) and Bacteria Foraging Algorithm (BFA). The work in this thesis is presented in three papers as follows: Paper 1 -This paper introduces an improved PSO called Small Population based PSO (SPPSO) with less number of particles and unique regeneration concept. The efficacy of the algorithm is evaluated for the simultaneous design of power system stabilizers (PSSs) on the two-area and 16 machine power systems. Paper 2 - The second paper presents a new algorithm - Bacterial Foraging Algorithm (BFA) for simultaneous tuning of multiple PSSs on a 16 machine power system. The variants of the BFA like the run length and the swarming are explored for better performance for two different design techniques and the results are compared. Paper 3 - The third paper compares SPPSO and BFA towards simultaneous tuning of multiple PSSs on two-area and Nigerian power system. This paper presents both algorithms as a first step towards online optimization and proposes to implement these algorithms in real power systems in near future --Abstract, page iv

Optimal Design of Power System Stabilizers using a Small Population Based PSO

Power system stabilizers (PSSs) are used to generate supplementary control signals to excitation systems in order to damp out local and inter-area oscillations. In this paper, a modified particle swarm optimization (PSO) algorithm with a small population is presented for the design of optimal PSSs. The small population based PSO (SPPSO) is used to determine the optimal parameters of several PSSs simultaneously in a multi-machine power system. In order to maintain a dynamic search process, the idea of particle regeneration in the population is also proposed. Optimal PSS parameters are determined for the power system subjected to small and large disturbances. The effectiveness of the PSSs parameters determined by the SPPSO algorithm is observed in damping out the power system oscillations fast after a disturbance. The advantage of the proposed approach is its convergence in fewer evaluations and lesser computations are required per evaluation. Results obtained with the SPPSO optimized PSSs parameters are compared against published PSS parameters for the Kundur\u27\u27s two area power system

Bio-inspired Algorithms for the Design of Multiple Optimal Power System Stabilizers: SPPSO and BFA

Power System Stabilizers (PSSs) provide stabilizing control signals to excitation systems to damp out inter-area and intra-area oscillations. The PSS must be optimally tuned to accommodate the variations in the system dynamics. Designing multiple optimal PSSs is a challenging task for researchers. This paper presents the comparison between two bio-inspired algorithms: a Small Population based Particle Swarm Optimization (SPPSO) and the Bacterial Foraging Algorithm (BFA) for the simultaneous tuning of a number of PSSs in a multi-machine power system. The cost function to be optimized by both algorithms takes into consideration the time domain transient responses. The effectiveness of the algorithms is evaluated and compared for damping the system oscillations during small and large disturbances. The robustness of the optimized PSSs in terms of damping is shown using the Matrix Pencil analysis

Optimal Design of SVC Damping Controllers with Wide Area Measurements Using Small Population Based PSO

Static Var Compensator (SVC) are employed for providing better voltage regulation and transient stability especially for increased power transfer through the transmission lines. In this paper, two SVC damping controllers with single and dual inputs respectively are designed based on wide area measurements of generator speed deviations. A Small Population based Particle Swarm Optimization algorithm (SPPSO) is applied to determine the optimal parameters of the damping controllers for small and large disturbances. Simulation results are provided to show that the effectiveness of the optimal damping controllers on the Kundur\u27\u27s two-area benchmark power system. Results show the dual input controller further improves the damping provided by the single input controller

Bio-Inspired Algorithms for the Design of Multiple Optimal Power System Stabilizers: SPPSO and BFA

Damping intra-area and interarea oscillations are critical to optimal power flow and stability in a power system. Power system stabilizers (PSSs) are effective damping devices, as they provide auxiliary control signals to the excitation systems of generators. The proper selection of PSS parameters to accommodate variations in the power system dynamics is important and is a challenging task particularly when several PSSs are involved. Two classical bio-inspired algorithms, which are smallpopulation- based particle swarm optimization (SPPSO) and bacterial foraging algorithm (BFA), are presented in this paper for the simultaneous design of multiple optimal PSSs in two power systems. A classical PSO with a small population of particles is called SPPSO in this paper. The SPPSO uses the regeneration concept, introduced in this paper, to attain the same performance as a PSO algorithm with a large population. Both algorithms use time domain information to obtain the objective function for the determination of the optimal parameters of the PSSs. The effectiveness of the two algorithms is evaluated and compared for damping the system oscillations during small and large disturbances, and their robustness is illustrated using the transient energy analysis. In addition, the computational complexities of the two algorithms are also presented

SILYMARIN PROTECTS AGAINST COPPER-ASCORBATE INDUCED INJURY TO GOAT CARDIAC MITOCHONDRIA IN VITRO: INVOLVEMENT OF ANTIOXIDANT MECHANISM(S)

Silymarin, 'one of the component of the Milk thistle seeds Silybum marianum (L.) is used in traditional food and medicine in India. In the present study, we investigated the antioxidant activities of Silymarin against copper-ascorbate induced toxic injury to mitochondria obtained from goat heart, in vitro. Incubation of isolated cardiac mitochondria with copper-ascorbate resulted in elevated levels of lipid peroxidation and protein carbonylation of the mitochondrial membrane, a reduced level of mitochondrial GSH and altered status of antioxidant enzymes as well as decreased activities of pyruvate dehydrogenase and the Kreb's cycle enzymes, altered mitochondrial morphology, mitochondrial swelling and di-tyrosine level. All these changes were found to be ameliorated when the cardiac mitochondria were co-incubated with copper-ascorbate and Silymarin, in vitro. Silymarin, in our in vitro experiments, was found to scavenge hydrogen peroxide, superoxide anion free radicals, hydroxyl radicals and DPPH radical, in a chemically defined system, indicating that this compound may provide protection to cardiac mitochondria against copper-ascorbate induced toxic injury through its antioxidant activities. The results of this study suggest that Silymarin may be considered as a future therapeutic antioxidant and may be used singly or as a co-therapeutic in the treatment of diseases associated with mitochondrial oxidative stress

Beyond Reality: The Pivotal Role of Generative AI in the Metaverse

Imagine stepping into a virtual world that's as rich, dynamic, and interactive as our physical one. This is the promise of the Metaverse, and it's being brought to life by the transformative power of Generative Artificial Intelligence (AI). This paper offers a comprehensive exploration of how generative AI technologies are shaping the Metaverse, transforming it into a dynamic, immersive, and interactive virtual world. We delve into the applications of text generation models like ChatGPT and GPT-3, which are enhancing conversational interfaces with AI-generated characters. We explore the role of image generation models such as DALL-E and MidJourney in creating visually stunning and diverse content. We also examine the potential of 3D model generation technologies like Point-E and Lumirithmic in creating realistic virtual objects that enrich the Metaverse experience. But the journey doesn't stop there. We also address the challenges and ethical considerations of implementing these technologies in the Metaverse, offering insights into the balance between user control and AI automation. This paper is not just a study, but a guide to the future of the Metaverse, offering readers a roadmap to harnessing the power of generative AI in creating immersive virtual worlds.Comment: 8 pages, 4 figure

Association of respiratory symptoms and lung function with occupation in the multinational Burden of Obstructive Lung Disease (BOLD) study

Background Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. Methods We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Results Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. Conclusion At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.publishedVersio

Simultaneous Design of Power System Stabilizers for the Nigeria Power System Using Bacteria Foraging

The basic intent of adding Power System Stabilizers (PSSs) is to enhance system damping and power transfer limits. The PSS with the excitation system of a synchronous machine modifies the torque angle of the shaft to increase damping. In this paper, Bacterial Foraging Algorithm (BFA) is presented for the design of optimal PSSs. The BFA is used to determine the optimal parameters of multiple PSSs simultaneously for the Nigerian power system. Optimal PSS parameters are determined for the power system subjected to small and large disturbances. The effectiveness of the PSS parameters determined by the BFA is observed in damping out the power system oscillations after a disturbance. The advantage of the proposed approach is presented in this paper

Ultrafast FRET in ionic liquid-P123 mixed micelles: region and counterion dependence

Ultrafast fluorescence resonance energy transfer (FRET) in a mixed micelle containing a room-temperature ionic liquid (RTIL) is studied by picosecond and femtosecond emission spectroscopy. The mixed micelle consists of a triblock copolymer, (PEO)20-(PPO)70-(PEO)20 (Pluronic P123), and a RTIL, 1-pentyl-3-methyl-imidazolium tetra-flouroborate, ([pmim][BF4]) or 1-pentyl-3-methyl-imidazolium bromide ([pmim][Br]). Coumarin 480 (C480) is used as the donor, and the acceptor is rhodamine 6G (R6G). Multiple time scales of FRET were detected-an ultrashort component of 1-3 ps and two relatively long components (300-400 ps and 2500-3500 ps). The different time scales are attributed to different donor-acceptor distances. It is proposed that the ionic acceptor (R6G) is localized in the polar corona region of the mixed micelle, while the neutral donor (C480) is distributed over both corona and hydrophobic core regions. The ultrafast (1-3 ps) components are assigned to FRET at a close contact of donor and acceptor. This occurs for the donor in the polar corona region in close proximity of the acceptor. The longer components (300-400 ps and 2500-3500 ps) arise from long-distance FRET from the donor at the core and the acceptor at the corona region. The relative contribution of the ultrafast component of FRET (~3 ps) increases from 5% at λex= 375 nm to 30% at λex= 435 nm in the 0.3 M [pmim][BF4] mixed micelle and from 25 to 100% in the 0.9 M [pmim][BF4] mixed micelle. It is suggested that, at λex= 435 nm, mainly the donor molecules present at the corona are excited, causing ultrafast FRET due to a short donor-acceptor distance. At shorter λex, the donor (C480) molecule at the core regions is excited, giving rise to a very long 3400 ps component (RDA~50 Å ). Thus, λex variation leads to excellent spatial resolution. The counterion dependence (Br- vs BF4-) is attributed to the difference in the local polarity and size of the two mixed micelles