Method for computing maximum access capacity of distributed power sources on basis of expansion second-order cone programming

Abstract

The invention discloses a method for computing the maximum access capacity of distributed power sources on the basis of expansion second-order cone programming. The method includes inputting related information of power distribution networks and setting the computational accuracy and the maximum number of iteration of the maximum deviation of cone relaxation; judging whether the numbers of iteration exceed the maximum number of iteration or not; taking the maximum access capacity of the distributed power sources in systems into account according to the related information of the power distribution networks and building models for computing the maximum access capacity of the distributed power sources; converting the models for computing the maximum access capacity of the distributed power sources into second-order cone programming models according to standard forms of second-order cone programming; carrying out computation and solution by the aid of mathematical solvers for solving second-order cone programming, outputting solution results and judging whether the maximum deviation of cone relaxation meets given accuracy requirements or not; adding cutting plane constraints on the basis of the second-order cone programming models and integrally forming expansion second-order cone programming models. The method has the advantages that complicated nonlinear programming problems can be solved, tedious iteration and large quantities of tests can be omitted, and the optimal access schemes for the distributed power sources can be quickly obtained.

Description

technical field [0001] The invention relates to a method for calculating the maximum access capability of a distributed power source. In particular, it relates to a method for calculating the maximum access capacity of distributed power sources based on extended second-order cone programming. Background technique [0002] New energy and renewable energy are widely and densely connected to the distribution network in a distributed way. While meeting the energy demand of the power grid, its operation characteristics are greatly affected by the environment and have obvious randomness and volatility. It brings many problems to the operation and control of the distribution network, among which the two-way power flow and the voltage exceeding the limit are particularly serious. Moreover, the output and load of distributed power supply often show a negative correlation, resulting in large fluctuations in the voltage and power of the distribution network within a certain range. Th...

AI Technical Summary

Problems solved by technology

Although traditional mathematical optimization methods can theoretically perform global optimization, there will be a "curse of dimensionality" problem when dealing with large-scale nonlinear problems in practice, and the calculation time often shows an explosive surge; A polynomial time bound, the calculation speed is fast, but only a local optimal solution can be obtained, and the global optimality of the solution cannot be guaranteed

Therefore, traditional mathematical optimization methods and heuristic algorithms cannot meet the requirements of speed or accuracy at the same time for solving such problems.

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