Application of artificial intelligent systems for real power transfer allocation

The application of various artificial intelligent(AI) techniques,namely artificial neural network(ANN),adaptive neuro fuzzy interface system(ANFIS),genetic algorithm optimized least square support vector machine(GA-LSSVM) and multivariable regression(MVR) models was presented to identify the real power transfer between generators and loads.These AI techniques adopt supervised learning,which first uses modified nodal equation(MNE) method to determine real power contribution from each generator to loads.Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques.The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of various AI methods compared to that of the MNE method.

Optimal Allocation of EG in Distribution System Using Genetic Algorithm Technique

The interconnection of Embedded Generation （EG） in a distribution network would change the radiality of the convention power flows in the system. Instead of helping to reduce the system losses, it also improves the quality of the overall system network. However, improper allocation and sizing of its interconnection to the system could oppositely change those advantages. The total system may experience higher losses and instability. In this paper, a new technique to determine the optimal allocation of EG in distribution system by using Genetic Algorithm （GA） technique is proposed. The effectiveness of the technique is demonstrated using IEEE-69 bus distribution test system and simulated in MATLAB.

Impact of electromagnetic radiation exposure during pregnancy on embryonic skeletal development in rats

Objective:To evaluate the teratogenic effect of mobile phone radiation exposure during pregnancy on embryonic skeletal development at the common used mobile phone frequency in our environment.Methods:Sixty female Sprague-Dawley rats were distributed into three experiment groups;control and two exposed groups (1 h/day, 2 h/day exposure groups) (n=20/ each group) and exposed to whole body radiation during gestation period from day 1- day 20. Electromagnetic radiofrequency signal generator was used to generate 1800 MHz GSM-like signals at specific absorption rate value 0.974 W/kg. Animals were exposed during experiment in an especial designed Plexiglas box (60 cm× 40 cm× 30 cm). At the end of exposure duration at day 20 of pregnancy animals were sacrificed and foetuses were removed, washed with normal saline and processed to Alizarin red and Alcian blue stain. Skeleton specimens were examined under a stereo microscope and skeleton's snaps were being carefully captured by built in camera fixed on the stereo microscope.Results:Intrauterine exposure to electromagneticradiation lead to variation in degree of ossification, mineralization, formation of certain parts of the skeleton majorly in head and lesser in other parts. Deformity and absence of formation of certain bones in the head, ribs, and coccygeal vertebrae were recorded in skeleton of foetuses from exposed dams compare to control group.Conclusions:The electromagnetic radiation exposure during pregnancy alter the processes of bone mineralization and the intensity of bone turnover processes, and thus impact embryonic skeleton formation and development directly.

A New Optimization Approach for Transmission Usage Allocation in Deregulated Power System

Deregulation of power system industry is a very large complex exercise based on respective national energy strategies and policies. A lot of matters and knowledge need to be studied before the idea of deregulation can be implemented. Theoretically, it is said that deregulation can make a large impact to increase efficiency and encourage the competitiveness among related parties. However, to implement the concept of deregulation to electric power supply is very tough challenge. In deregulation environment, regardless of market structure, to know the transmission usage allocation is vital and very a complex problem. Thus, a lot of algorithms have been proposed to overcome it. This paper intends to solve the transmission usage allocation problem using optimization approach. The optimization tool that will be utilized is Genetic Algorithm （GA）. GA is probabilistic search technique that has its roots in the principle of genetics and strives for survival. In addition, GA is very robust. Since the nonlinear nature of power flow, it is expected that GA can give optimize results that equitable and acceptable. In this paper, 4-bus and Klos-Kerner 11-bus systems are used for analysis studies. Comparison with other method is also given in this paper.