Distributed robust coordinated optimization scheduling model for electrothermal integrated system with consideration to wind power uncertainty

Abstract

The invention discloses a distributed robust coordinated optimization scheduling model for an electrothermal integrated system with the consideration to wind power uncertainty. The electrothermal integrated system which takes a combined heat and power generation unit and an electric boiler as coupling units is constructed, and wind power output uncertainty is considered. The two-stage distributedrobust coordinated optimization scheduling model is constructed on the basis of the available wind power historical data of the scheduling system. In the model, the start / stop state of a conventionalunit and the related variables of a heat storage device and an electricity storage device are designed to be first-stage robustness variables, and other variables are designed to be second-stage variables. The model is decomposed into a main question and a subquention through a decomposition method for repeated iteration solving, thereby speeding up the solving. The equivalent conversion of an absolute value constrained condition is performed so as to convert a solving problem into a mixed integer programming problem, and a conventional solving toolkit CPLEX is used for effective solving.

Description

technical field [0001] The invention relates to the technical field of a distributed robust coordination optimization dispatching model of an electrothermal integrated system, in particular to a distributed robust coordination optimization dispatching model of an electrothermal integrated system considering the uncertainty of wind power. Background technique [0002] At present, with the continuous access of thermoelectric coupling elements, the connection between electric heating systems is becoming increasingly close, and it is of great practical significance to coordinate and optimize the electric heating integrated system including cogeneration units, electric boilers and other devices; at the same time, large-scale cleaning After the energy is connected to the power system, the uncertainty of its output brings new challenges to the integrated electrothermal system; the current uncertainty methods for the integrated electrothermal system including wind power are mostly tr...

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Problems solved by technology

[0002] At present, with the continuous access of thermoelectric coupling elements, the connection between electric heating systems is becoming increasingly close, and it is of great practical significance to coordinate and optimize the electric heating integrated system including cogeneration units, electric boilers and other devices; at the same time, large-scale cleaning After the energy is connected to the power system, the uncertainty of its output brings new challenges to the integrated electrothermal system; the current uncertainty methods for the integrated electrothermal system including wind power are mostly traditional stochastic programming methods and robust optimization methods, but , both of these two uncertainty processing methods have limitations to a certain extent; stochastic programming methods are mainly characterized by probability descriptions, and then generate a large number of discrete samples, often with a large amount of calculation, and it is difficult to obtain accurate probability in practice distribution, and the robust optimization method is expressed by the boundary parameters of the uncertainty parameters, and there is a problem that the optimization decision result is too conservative; therefore, the present invention proposes a data-driven distribution-based robust optimization that combines stochastic programming and robust optimization method, by extracting a large amount of available wind power historical data in the actual dispatching system, and establishing 1-norm and ∞-norm sets for constraints, which are used to constrain the uncertainty probability distribution set, and obtain all probability distribution functions that satisfy the parameter information, In order to find the robust decision-making scheme of the worst expected goal in all distributions satisfying the above conditions

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