Qinghai Electrical Power Dispatching Center

Xining, China

Qinghai Electrical Power Dispatching Center

Xining, China
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Zhang J.,Qinghai Electrical Power Dispatching Center | Wang M.,Qinghai Electrical Power Dispatching Center | Xu Y.,Qinghai Electrical Power Dispatching Center | Zhang H.,Qinghai Electrical Power Dispatching Center | Tian H.,Qinghai Electrical Power Dispatching Center
Dianwang Jishu/Power System Technology | Year: 2011

Based on the principle of equal-risk and taking minimum variance of risk in all maintenance time intervals as objective function, a generation unit maintenance scheduling model for power system containing wind farms is built and a heuristic solution based on minimum cumulative risk algorithm for the built model is proposed. The random variables such as load, output of generation unit and so on are described by semi-invariants; the convolution and deconvolution operations of equivalent sustained load curve are turned into the addition and subtraction of semi-variants. The discretization method is used to make the wind power generation units equivalent to multi-state units, and then the semi-variants of wind power generation units' outage capacity are solved. Considering the uncertainty of wind farm output, the risk of power system containing wind farms is solved by semi-variant method combining with Gram-Charlier series expansion. By means of searching the interval with minimum cumulative risk within the maintenance interval, the maintenance interval of the generation unit to be maintained can be determined. The effectiveness of the proposed method is verified by the result of unit maintenance scheduling for IEEE-RTS system.


Zhang J.,Qinghai Electrical Power Dispatching Center | Pang S.,Thermal Power Research Institute | Tian H.,Qinghai Electrical Power Dispatching Center | Wang M.,Qinghai Electrical Power Dispatching Center
2010 International Conference on Power System Technology: Technological Innovations Making Power Grid Smarter, POWERCON2010 | Year: 2010

In the smart grid, the active management (AM) mode will be applied for the connection and operation of distributed generation (DG), which means real time control and management of DG units and distribution network devices based on real time measurements of primary system parameters. The application of AM is a challenge to the validity of traditional distribution network planning, operation, and commercial practices. Network planning and operation should be synchronous when AM is applied in the distribution network: The determination of the connection capacity of DG should consider different operation situations that will appear in the future as well as the positive effect of AM to improve the technical level of the network. In this paper, a novel bi-level programming model for distributed wind generation (DWG) planning under AM mode is put forward. The model takes the maximum expectation of net benefit of DWG as the upper level program objective, and takes the minimum expectation of generation curtailment as the lower level program objective. The impact of active management algorithm on improvement of branch power flow and node voltage is taken into account. A hybrid algorithm combining the plant growth simulation algorithm (PGSA) with probabilistic optimal power flow (POPF) algorithm is presented to solve the optimal planning of DWG under AM mode. The case studies have been carried out on a 33-node distribution network, and the results verify the rationality of the planning model and the effectiveness of the proposed method. ©2010 IEEE.

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