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Dependent-chance two-layer programming model-based transmission network programming method

A planning model and transmission network technology, applied in the field of transmission network planning based on the relevant opportunity two-level planning model, can solve problems such as insufficient planning methods, uncertain transmission network modeling and solution, and achieve the effect of solving risk problems

Inactive Publication Date: 2013-06-12
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Problems solved by technology

[0004] The present invention is aimed at the problem of insufficient traditional planning methods, and proposes a transmission network planning method based on the correlation opportunity two-level planning model, applies the correlation opportunity two-level planning model to the transmission network planning modeling, and establishes a new model that can realize In the transmission network planning grid construction, solve the modeling and solution problems of transmission network planning in an uncertain environment

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  • Dependent-chance two-layer programming model-based transmission network programming method
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  • Dependent-chance two-layer programming model-based transmission network programming method

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Embodiment Construction

[0022] The transmission network planning method based on the two-level planning model of relevant opportunities: firstly, the two-level nonlinear programming model of relevant opportunities for transmission network planning is established. The maximum number of lines can be erected, and the lines that can be erected are sorted, and a set of chromosomes is formed by random erection, that is, the original population. The original population is selected, crossed, and mutated to continuously form new individuals. The fitness value of each individual is different. It is necessary to use the primal-dual interior point method to calculate the lower-level plan; according to the global search ability of the improved niche genetic algorithm, finally find the optimal solution.

[0023] Take the 18-node system as an example to conduct case analysis. 18-node system data reference (Wang Xifan. Power System Optimal Planning [M]. Beijing: Water Conservancy and Electric Power Press, 1990).

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Abstract

The invention relates to a dependent-chance two-layer programming model-based transmission network programming method. A dependent-chance two-layer nonlinear programming model for the programming of a transmission network is established. The upper-layer programming of the model aims to maximize a probability that return on investment of the transmission network is greater than a certain ideal value, and a constraint is about the erection number of candidate lines. The lower-layer programming of the model comprises two sub-problems, wherein one is the social benefit maximization of a system under a normal running condition, the other is maximization of a probability that the total load shedding amount of the system under a failure running condition is lower than a certain specified value, and a constraint is a failure running constraint. A hybrid algorithm combining a Monte-Carlo method, a genetic algorithm and an interior point algorithm is disclosed for solving the dependent-chance two-layer programming model. The problem of risks in the programming of the transmission network is rationally solved, a dependent-chance two-layer programming modeling-based concept is applied to the programming of the transmission network, and the aim of higher probability of realizing a rate of return on investment in an uncertain environment is fulfilled.

Description

technical field [0001] The invention relates to a transmission network expansion planning method, in particular to a transmission network planning method based on a correlation opportunity two-layer programming model. Background technique [0002] Due to the great changes in the load and power source in the transmission network expansion planning, it is difficult to describe in the traditional transmission network planning model. In order to make up for the deficiencies of traditional planning methods, consider the influence of uncertain factors, and enhance the adaptability and flexibility of the obtained planning schemes, the research on uncertain power grid planning methods has attracted widespread attention at home and abroad. Currently, the commonly used uncertainty planning methods are mostly research methods aimed at describing the uncertain factors in planning. [0003] The relative chance programming method is a new stochastic programming method. Its main idea is t...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06
Inventor 范宏程浩忠许仪勋阳育德丁会凯
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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