North China Electric Power University

Huaneng Group Technology Innovation Center Co., Ltd.

Huaneng Group R &d Center Co Ltd

The People's Bank of China National Clearing Center

Fang Fang

Wei Wang

Jian Zhang

Yang Hu

Jizhen Liu

Qinghua Wang

Xiaojiang Guo

Ziqiu Song

Feng Hong

Lu Liang

Haonan Wang

Shunping Jin

Weiran Wang

Siqi Chen

Heng Ge

Xinmeng Zhong

Maofeng Shao

Xinran Yao

Xinyi Jia

Junhong Hao

Yanjun Du

Yong Na

Yuwei Zeng

Xuejun Ma

A method and device for generating a wind turbine generator set simulation model, equipment and a medium, wherein the method includes: clustering a plurality of pieces of historical operation data of a wind turbine generator set, so as to obtain a predetermined number of target data sets, wherein wind speeds contained in each piece of the historical operation data in a target data set fall within a wind speed range corresponding to the target data set; different target data sets correspond to different wind speed ranges; training an initial simulation model by using each target data set, so as to obtain a segmented pneumatic simulation model corresponding to each target data set; constructing a transmission generation simulation model for a transmission system and a generator system, based on the historical operation data; concatenating the segmented pneumatic simulation model corresponding to each wind speed range and the transmission generation simulation model.

Method and device for generating wind turbine generator set simulation model, equipment, and medium

The present application provides an optimized regulating and controlling method and system for an integrated electricity and heat system with heat pumps, relating to the technical field of energy operation. According to the present application, regulating and controlling can be performed by regarding units as different agents and taking maximization of the self-interest of each agent as the objective, so that the load demands of heat and power consumers can be met, and each unit agent can be satisfied with its payoff to the greatest extent. The method includes: S. establishing a composition and structure framework of the integrated electricity and heat system with heat pumps, and establishing an output model of each unit; S. establishing a payoff function model of each unit in the integrated electricity and heat system with heat pumps; S. establishing a non-cooperative game model of the integrated electricity and heat system with heat pumps; and S. solving the game model by using a particle swarm optimization algorithm to obtain a heat and power scheduling optimization scheme of each unit. The technical solution provided by the present application is applicable to a process of regulating an integrated electricity and heat system with heat pumps.

Optimized regulating and controlling method and system for integrated electricity and heat system with heat pumps

A thermal power unit-flywheel energy storage cooperative frequency regulation control method and system is provided, which belongs to the technical field of a power grid. First, a real-time output increment of a thermal power unit is predicted, then a real-time frequency regulation power instruction of a flywheel energy storage system is determined based on the predicted real-time output increment of the thermal power unit, and finally the frequency regulation power instruction of the thermal power unit is determined by a difference adjustment coefficient of a governor and a grid frequency deviation. The thermal power unit and flywheel energy storage system is cooperatively controlled by frequency regulation based on the real-time output increment predicted value of the unit, which realizes self-adaptive adjustment of output of the flywheel energy storage system under dynamic working conditions, and improves the grid frequency stability and operation safety of the thermal power unit.

Thermal power unit-flywheel energy storage cooperative frequency regulation control method and system

The present disclosure provides a method and device for simulating a dynamic digital twin model of dominant operation of a wind turbine generator assembly, by which conventional operational parameters of the wind turbine generator assembly that are acquired in real time are preprocessed to obtain steady-state operational parameters of the wind turbine generator assembly. A pneumatic subsystem-related data black box model, a transmission subsystem model, a tower subsystem model, and an electrical subsystem model are simulated individually using the steady-state operational parameters, and then combined to form a dynamic dominant-operation simulation model for simulating an operation process of the wind turbine generator assembly. Meanwhile, a dynamic deviation compensation model is constructed on the basis of the dynamic dominant-operation simulation model.

Method and device for simulating dynamic digital twin model of dominant operation of wind turbine generator assembly

Provided are control method and device of an energy-storage coordinated floating wind turbine, relating to the technical field of wind turbines. The control method of an energy-storage coordinated floating wind turbine can construct a primary frequency regulation model of a floating wind farm based on a frequency response unit, construct a second frequency regulation model according to an energy storage system, further construct, according to the primary frequency regulation model and the second frequency regulation model, a frequency regulation model of a hybrid power system containing the floating wind farm, the energy storage system, and a pre-set thermal power unit, and design an overall frequency regulation control strategy of the hybrid power system based on the frequency regulation model of the hybrid power system.

Control method and device of energy-storage coordinated floating wind turbine

The present invention provides a frequency modulation dynamic modeling method and device for a wind farm, and an electronic device. The method includes: acquiring first frequency modulation data measured at a grid-connected point of the wind farm under a plurality of preset working conditions; establishing a state space model corresponding to each of the plurality of working conditions according to the first frequency modulation data; measuring the nonlinearity between the state space models corresponding to each two of the plurality of working conditions by using a gap measurement method; combining the first frequency modulation data according to the nonlinearity to obtain second frequency modulation data; and training a preset initial LSTM neural network according to the second frequency modulation data until a preset training requirement is met, and obtaining a trained frequency modulation dynamic model of the wind farm.

Frequency modulation dynamic modeling method and device for wind farm, and electronic device

The present invention discloses an intelligent soft measurement method for wind speed in front of a wind turbine. The method includes: first using laser radar data as a data sample, judging delay orders between input and output by using an AIC or BIC criterion, defining a dynamic difference regression vector according to the delay orders, dividing hyperplanes according to a clustering result by using a machine learning algorithm, and performing dynamic differential input/output nonlinear mapping modeling in a global scope and sub-scopes by using an artificial intelligence dynamic regression algorithm, respectively. Empirical mode decomposition and power spectral density analysis are performed on the wind speed in front of a laser radar measuring machine and the wind speed in front of a soft measurement machine, thereby further verifying the estimation performance of intelligent soft measurement for the wind speed in front of a wind turbine.

Intelligent soft measurement method for wind speed in front of wind turbine

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Beijing, China

Fang Fang