Independent microgrid flexible resource capacity allocation method based on scene decomposition-coordination

Abstract

The invention discloses an independent microgrid flexible resource capacity allocation method based on scene decomposition-coordination. The method comprises the following steps of establishing a source-load unbalanced power scene and dividing the unbalanced power scene into a power shortage scene set S- and a power excess scene set S+; calculating the feasible range of the controllable power supply capacity and the minimum capacity of a corresponding energy storage device according to the power shortage scene set S-; adopting a common mode search method to coordinate and modify the energy storage capacity to obtain the best configuration with the lowest electricity abandonment penalty according to the power excess scene set S+; comprehensively considering the lowest investment cost and the lowest operating cost to select a flexible resource FGR capacity allocation scheme. According to the method, not only no loss of load can be ensured, but also the best configuration with the lowestelectricity abandonment penalty can be obtained by coordination and correction of the energy storage capacity. The electricity abandonment quantity is reduced, and the planning comprehensive cost is reduced.

Description

technical field [0001] The invention relates to the field of electric power, in particular to a method for configuring flexible resource capacity of an independent microgrid based on scenario decomposition and coordination. Background technique [0002] With the rapid decline in the installed cost of renewable energy in recent years, the penetration rate of renewable energy in microgrids has gradually increased, and the uncertainty caused by the natural characteristics of renewable energy has become increasingly serious. The uncertainty problems faced by microgrid operation are mainly reflected in two aspects: one is the power fluctuation problem caused by the strong randomness and intermittency of renewable energy such as wind power and photovoltaics under the high penetration rate of the source side; The load fluctuation problem caused by the randomness of power consumption behavior of load-side power users. [0003] For the microgrid, it is necessary to ensure the safe a...

AI Technical Summary

Problems solved by technology

The scenario generation method can select a typical day based on seasonal division or annual average statistics, or an analysis scenario based on source-load forecast errors. This method usually uses scenario reduction to reduce the complexity of the problem and improve the solvability of the model. Impairs the ability to fully reflect source-load uncertainties

Describing the random behavior of wind speed, light intensity and load changes through the artificially specified probability distribution model does reflect the source-load uncertainty to a certain extent, but the probability distribution model often fails to fully consider the real situation of the actual microgrid. In many cases, the mixed integer linear programming problem will be solved on a large scale, which puts higher requirements on the computing equipment, and at the same time, the calculation speed of the problem is also greatly reduced, and even memory overflow or dimensionality disaster may easily occur, so that the solution of the problem cannot be obtained. understand that, in addition, the scenario generation method used does not fully reflect the source-load uncertainty of the stand-alone microgrid

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