Recording of krill swarms and the observations of the state of the sea and the force of wind were conducted on the M/T "Gemini" from 6 to 26 February, 1978, eastwards of the South Orkneys Archipelago. It has been found that a heavy sea and strong winds disperse krill swarms. At night krill swarms occur much more frequently than during the day.
Results of hydroacoustic investigations of krill swarms occurring southwest of Elephant Island carried out between 30 October and 5 November 1986, are presented. Krill swarms of the geometric length of 32 m, mean vertical cross section area of 206 m2 , and mean density of 133 g m-3 were recorded and measured. Biomass distribution is presented in maps. The highest density values amounting to 5001 nM-2 were recorded in the eastern part of the survey area, above the slope of Elephant Island's shelf. On the basis of upper and lower limits of the occurrence of given krill swarms, a scheme of their vertical, diurnal distribution was constructed.
A transformer is an important part of power transmission and transformation equipment. Once a fault occurs, it may cause a large-scale power outage. The safety of the transformer is related to the safe and stable operation of the power system. Aiming at the problem that the diagnosis result of transformer fault diagnosis method is not ideal and the model is unstable, a transformer fault diagnosis model based on improved particle swarm optimization online sequence extreme learning machine (IPSO-OS-ELM) algorithm is proposed. The improved particle swarmoptimization algorithm is applied to the transformer fault diagnosis model based on the OS-ELM, and the problems of randomly selecting parameters in the hidden layer of the OS-ELM and its network output not stable enough, are solved by optimization. Finally, the effectiveness of the improved fault diagnosis model in improving the accuracy is verified by simulation experiments.
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.