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Zhong H.,Tsinghua University | Xia Q.,Tsinghua University | Kang C.,Tsinghua University | Ding M.,Ningxia Electrical Power Company | And 2 more authors.
IEEE Transactions on Power Systems | Year: 2015

In response to the computational challenges produced by the integrated dispatch of generation and load (IDGL), this paper proposes a novel and efficient decomposition method. The IDGL is formulated using the mixed-integer quadratic constrained programming (MIQCP) method. To efficiently solve this complex optimization problem, the nodal equivalent load shifting bidding curve (NELSBC) is proposed to represent the aggregated response characteristics of customers at a node. The IDGL is subsequently decomposed into a two-level optimization problem. At the upper level, grid operators optimize load shifting schedules based on the NELSBC of each node. Transmission losses are explicitly incorporated into the model to coordinate them with generating costs and load shifting costs. At the bottom level, customer load adjustments are optimized at individual nodes given the nodal load shifting requirement imposed by the grid operators. The key advantage of the proposed method is that the load shifting among different nodes can be coordinated via NELSBCs without iterations. The proposed decomposition method significantly improves the efficiency of the IDGL. Parallel computing techniques are utilized to accelerate the computations. Using numerical studies of IEEE 30-bus, 118-bus, and practically sized 300-bus systems, this study demonstrates that accurate and efficient IDGL scheduling results, which consider the nonlinear impact of transmission losses, can be achieved. © 2014 IEEE.


Xia J.-K.,Ningxia Electrical Power Company
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2010

This paper indicates a number of factors which affect the normal action of current differential protection for transmission line in power system in actual operation. And it takes the principle and certain operating mode of differential protection for optical fiber as a view and the RCS-931 differential protection for optical fiber as an example to discuss and analyze intensively the influence over the differential protection for optical fiber from the line capacitance and current, high-impedance grounding fault under heavy load, CT saturation on the transmission line, disparity of CT on two sides of the transmission line, and the data sampling in step of the optical fiber line. Then it brings in some solutions in detail from the operational guidance, selection of design, and protection of software algorithm to remove the adverse effect brought by those problems above for the differential protection for optical fiber.


Chen H.,Ningxia Electrical Power Company
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2015

The optimal configuration of location and capacity of the distributed generation (DG) can ensure its better technical and economic utility. Based on the detailed analysis on peculiarity of DG, this paper establishes a model of DG which takes the minimal active network loss of DG and the least cost into consideration. A bacterial colony optimization (BCO) algorithm based on the basic growth law of bacterial colony is presented. An information sharing method is built for the colony. This BCO algorithm provides a new type of termination; it will terminate the iteration when the colony vanishes, regardless of the iteration number or the precision value. Finally, the effectiveness of the proposed algorithm is illustrated by experiments. © 2015, Power System Protection and Control Press. All right reserved.


Wei W.,Xian Jiaotong University | Hao M.,Ningxia Electrical Power Company
Applied Mechanics and Materials | Year: 2012

The theoretical properties of the ARMA model and the modeling process, then, the Shanghai power network and Shenzhen power network in China were established ARMA model and wavelet-based ARMA model fitting, prediction, and finally, to fit forecast The results were compared. It can be seen, combined with relatively good forecasting effect after wavelet.


Shi H.,Beifang University of Nationalities | Yang J.,Beifang University of Nationalities | Ding M.,Ningxia Electrical Power Company | Wang J.,Ningxia University
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2011

Establishing the wind power prediction system and improving the prediction accuracy is one of the key techniques for exploiting wind power. Based on numerical weather prediction, a wind power prediction model using the back propagation (BP) neural network is proposed. Factors that affect the prediction accuracy are analyzed using actual data of a certain wind farm. In the light of inconspicuous day characteristic of the original wind speed and the failure of the BP neural network to completely map its power sequence, a prediction model based on wavelet-BP neural network is proposed. With the wavelet-BP neural network model, the wind speed and power sequence are decomposed into different scales. Then the sub-sequences of different frequency components are predicted using multiple BP neural networks. Finally, the output data of BP neural networks are reconstructed to obtain the complete wind power predicting results. It is shown by the research results that the prediction accuracy of wavelet-BP neural network is effectively improved. © 2011 State Grid Electric Power Research Institute Press.

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