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Small Universal Numerical P Systems with Thresholds for Computing Functions

Liu Liucheng, Yi Wenmei, Yang Qian, Peng Hong, Wang Jun

Fundamenta Informaticae

2020

Vol. 176, nr 1

43--59

Abstracted from the nested structure of biological cells with application on the modeling of economical processes, numerical P systems (in short, NP systems) as a kind of distributed parallel computation systems have been proposed. It has been proven that NP systems and variants are Turing universal for number accepting/generating devices and language generating device. However, universality of NP systems as function computing devices has not been established. Aiming at numerical P systems with thresholds (in short, TNP systems), small universality for computing functions is discussed in this paper. Six small universal function computing devices of TNP systems for two threshold cases and working on three different modes are constructed, respectively.

Research on islanding detection of solar distributed generation based on best wavelet packet and neural network

Xi Zhongmei, Zhao Faqi, Zhao Xiangyang, Peng Hong, Xi Chuanxin

Archives of Electrical Engineering

2019

Vol. 68, nr 4

703--717

The active distribution network (ADN) represents the future development of distribution networks, whether the islanding phenomenon occurs or not determines the control strategy adopted by the ADN. The best wavelet packet has a better time-frequency characteristic than traditional wavelet analysis in the different signal processing, because it can extract better and more information from the signal effectively. Based on wavelet packet energy and the neural network, the islanding phenomenon of the ADN can be detected. Firstly, the wavelet packet is used to decompose current and voltage signals of the public coupling point between the distributed photovoltaic (PV) system and power grid, and calculate the energy value of each decomposed frequency band. Secondly, the network is trained using the constructed energy characteristic matrix as a neural network learning sample. At last, in order to achieve the function of identification for islanding detection, lots of samples are trained in the neural network. Based on the actual circumstance of PV operation in the ADN, the MATLAB/SIMULINK simulation model of the ADN is established. After the simulation, there are good output results, which show that the method has the characteristics of high identification accuracy and strong generalization ability.