In this paper, an improved version of the particle swarm optimization algorithm is proposed for the online tuning of power system stabilizers in a standard four-machine two-area power system to mitigate local and inter-area mode oscillations. Moreover, an innovative objective function is proposed for performing the optimization, which is a weight function of two functions. The first part of fitness is the function of the angular velocity deviation of the generators, and the other part is a function based on the percentage of undershoot and maximum overshoot, and also the damping time of the power system oscillations. The performance of the proposed stabilization method is compared with the genetic algorithm and bacteria foraging algorithm results. Simulations are made in three different power system operation conditions by changing the system load. The simulation results indicate the superiority of the proposed method over the genetic algorithm and bacteria foraging algorithm. In all the scenarios, power system oscillations are damped faster and with lower amplitude when the power system stabilizers coordinate with the proposed optimization method.
Reactive power compensation is one of the practical tools that can be used to improve power systems and reduce costs. These benefits are achieved when the compensators are installed in a suitable place with optimal capacity. This study solves the issues of optimal supply and the purchase of reactive power in the IEEE 30-bus power system, especially when considering voltage stability and reducing total generation and operational costs, including generation costs, reserves, and the installation of reactive power control devices. The modified version of the artificial bee colony (MABC) algorithm is proposed to solve optimization problems and its results are compared with the artificial bee colony (ABC) algorithm, the particle swarm optimization (PSO) algorithm and the genetic algorithm (GA). The simulation results showed that the minimum losses in the power system requires further costs for reactive power compensation. Also, optimization results proved that the proposed MABC algorithm has a lower active power loss, reactive power costs, a better voltage profile and greater stability than the other three algorithms.
More than 110 million people in this world are facing some kind of disability, for which they experience difficulty while eating food. Eating Assistive Robots could meet the needs of the elderly and people with upper limb disabilities or dysfunctions in gaining independence in eating. We are researching making a robot, which can assist the disabled in eating their meals. Our Eating Assistive Robot will detect the face of the disabled and process it for whether his/her mouth is opened or closed. Our robot will put a pre-prepared replaceable spoon of food in his/her mouth iteratively until the food lasts in the food container. The methodology we used for it i.e. firstly there is a live camera feed through which we are detecting human faces, after this, a library of Affectiva calculates how much mouth is open. We have set a certain threshold after which the program starts the stepper motor which brings the pre-filled spoon of food into the mouth of the disabled.
A structured questionnaire was distributed to 65 participants. The questionnaire was divided into 2 sections. In the first section, demographic information of the participants was included. In the second section, 6 questions regarding radiation protection were included. Results: Out of total 65 participants, males were predominantly higher 51 (78%) as compared to females 14 (22%) ]. Majority of the participants 43 (66%) were residents while 22 (34%) were technologists. Awareness for evaluation of personal dosimeter data and radiation protection tool was found to be higher 55 (85%) followed by disease caused by radiation damaged 48 (74%), tissue most susceptible to injury from ionizing radiation 40 (62%), knowledge about dose optimization 34 (52%), standard about radiations 29 (45%) while only 14 (22%) were susceptible to radiation damage. Conclusions: The findings of our study have showed considerably low knowledge in our studied participants. In particular, technologist working in VIR department should be trained through regular educational seminar.
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