Lianyungang Power Supply Company

Xinpu, China

Lianyungang Power Supply Company

Xinpu, China

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Zhang D.-L.,China University of Mining and Technology | Yanjian,China University of Mining and Technology | Wang W.-H.,Lianyungang Power Supply Company | Yang X.-L.,Beijing Electrical Power Research Institute
China International Conference on Electricity Distribution, CICED | Year: 2016

In the process of mid-long term load forecasting, it is important to choose right models according to the trend of the historical data. This paper chose the continuous 11 years electricity data of a certain district in Lianyungang to make up the historical data. Five forecasting models were always used in load forecasting field to forecast the electric quantity of the twelfth year. The data, which had been chosen in this paper, had the feature-the medium-term data showed fluctuation and the overall rising tendency was unstable. In order to check the forecasting results whether meet accuracy requirement, the concept of the grey relational degree was introduced. In terms of problems that even the forecast models meet the requirements of the grey relational degree, the forecast results still have great differences. According to the feature that the growth rate of load data is non-after effect property of Markov chains, by analyzing the growth rate of load data, using Markov chain to divide the growth rate to three state intervals, and getting the Markov state-transition matrix. According to the growth rate between the tenth and the eleventh data, combining with the Markov state-transition matrix, judging the rising tendency of the growth rate between the eleventh and the twelfth data. According to the rising tendency, screening two kinds from the models which had met the accuracy requirement, the method of variance-covariance was used to assign weights. Calculating results show that more targeted models could be chosen and combined. By this method of screening, not only can be appropriate for the rising tendency unstable data, but have a high precision. © 2016 IEEE.


Guo H.-K.,Nanjing University of Science and Technology | Wu J.-J.,Nanjing University of Science and Technology | Heng S.-K.,Lianyungang Power Supply Company | Ying Z.-F.,Nanjing University of Science and Technology | And 2 more authors.
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2012

Noise interference is one of the main factors that affect the reliability of the electric communication. The circuit for measuring noise in the power communication channel is built and the actual noise is measured. The AR model of background noise and the improved Markov model of impulse noise are established respectively. The power channel noise is synthesized, calculated and simulated by using the model. The results show that the power spectral density of back noise measured in the model is almost the same as the actual noise and the statistical regularity error of impulse noise is small. The simulation of synthesized noise has similarity with measured ones. The model is of great significance for the future study of the noise in the power line communication channel.


Fu X.,Lianyungang Power Supply Company | Zhao M.,Lianyungang Power Supply Company | Yao G.,Lianyungang Power Supply Company
Dianli Zidonghua Shebei/Electric Power Automation Equipment | Year: 2010

A neural line current compensator is proposed to solve the problem of neural line overload caused by the nonlinear and unbalanced loads in distribution system, which connects a single-phase inverter between the neural point of zig-zag transformer and the neural line. The output current of the inverter is injected into system through the path provided by the zig-zag transformer for neural line current compensation, which is of low impedance to the zero-sequence current. The output of the zig-zag transformer at secondary side is commutated by a controllable rectifier to supply DC voltage for the inverter. If the uncontrollable rectifier is applied, the DC voltage arises when the compensator absorbs the active power. With the controllable rectifier, energy flows in both directions to avoid the DC voltage elevation and switching device damage. Modeling and simulation show that, the proposed compensator eliminates the neural line current effectively and the DC voltage of inverter keeps steady.


Sun H.,Lianyungang Power Supply Company | Tian Y.,China Electric Power Research Institute
Dianwang Jishu/Power System Technology | Year: 2011

The problem of cross-security zone data transmission of secondary system existing in Lianyungang power network is introduced. To solve this problem, a crosssecurity zone data transmission and sharing system is proposed. The architecture of current security protection system for secondary system and the features of data transmission via physical isolation devices are analyzed and how to design and encapsulate various communication protocols to carry out data exchange and transmission are researched. An actual example of applying cross-security zone data transmission and sharing in the construction of load forecasting system for Lianyungang power network is given.


Hang F.-H.,Lianyungang Power Supply Company | Yang W.,Nanjing University of Science and Technology | Zhu W.-Y.,Nanjing University of Science and Technology
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2014

In the photovoltaic power generation process, the maximum power point of photovoltaic cell requires tracking control, which aims to improve the battery utilization and power generation efficiency. The principle of the fundamental disturbance observer method is analyzed, as well as its advantages and disadvantages. And then, an improved algorithm is proposed by adding a re-judgment of the climbing slope, which is considered to be the criterion for junction point of variable step size. Combining with the incremental conductance algorithm, the maximum power point of photovoltaic cell is tracked and controlled by using the variable step and weak oscillation method. Finally, the simulation results show the correctness of this algorithm. The results show that the improved tracking algorithm is more stable, and eliminates the oscillation and improves the accuracy. The dynamic response is better.

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