CN-122000866-A - Intensive intelligent management and control method and system for new energy power station group

CN122000866ACN 122000866 ACN122000866 ACN 122000866ACN-122000866-A

Abstract

The invention discloses an intensive intelligent management and control method and system for a new energy power station group, and relates to the technical field of operation monitoring of new energy power stations, wherein the method is implemented by an intensive intelligent management and control system deployed in a cloud-edge cooperative framework and comprises the steps of acquiring and fusing operation data from a plurality of heterogeneous new energy power stations to form a unified data view of a power station group level; and generating a collaborative optimization control strategy for the power station group based on the prediction information and the evaluation information, and distributing a control instruction to each power station for execution. The invention can realize the collaborative control of the cross-power stations, ensure the overall operation to be optimal, effectively reduce the operation and maintenance cost and meet the large-scale intensive operation requirement of the new energy power station group.

Inventors

ZHANG YUANYIN
WANG XIAOYAN
HE LI
ZHAO JUNAN
JIA JIAN
TIAN YU
TANG XIAOYAN
LIU KE
ZHOU DAI
Lei Bangxue
Lu Yanjia
LIU BIAO

Assignees

贵州送变电有限责任公司

Dates

Publication Date: 20260508
Application Date: 20251228

Claims (9)

1. The intensive intelligent management and control method for the new energy power station group is characterized by being executed by an intensive intelligent management and control system deployed in a cloud-edge cooperative framework and comprises the following steps of: acquiring and fusing operation data from a plurality of heterogeneous new energy power stations to form a unified data view of a power station group level; based on the unified data view, generating prediction information of future power generation power of the power station group and evaluation information of the health state of key equipment; And generating a collaborative optimization control strategy for the power station group based on the prediction information and the evaluation information, and distributing a control instruction to each power station for execution.
2. The method for the intensive intelligent management and control of a new energy power station group according to claim 1, wherein the steps of obtaining and fusing operation data from a plurality of heterogeneous new energy power stations to form a unified data view of a power station group level include: The collected original data based on different communication protocols are subjected to protocol analysis and format conversion through edge computing gateways deployed at all power stations; Uploading the data with unified analysis and format to a cloud platform, and performing data mapping and association based on a predefined unified information model to form the unified data view.
3. The method for the intensive intelligent management and control of a new energy power station group according to claim 2, further comprising, after forming the unified data view: Based on the unified data view, a digital twin model corresponding to the power station group is established and updated; in the digital twin model, virtual sensing and state deduction are carried out on missing or lagged actual acquired data through a mechanism model or a data driving model, blind areas or delays of the actual acquired data are supplemented, and the unified data view after complementation is obtained.
4. The method for the intensive intelligent management and control of a new energy power station group according to claim 1, wherein generating the prediction information of the future generation power of the power station group based on the unified data view comprises: Inputting meteorological data, historical power data and space correlation characteristics in the unified data view into a multi-time scale power prediction model, wherein the multi-time scale power prediction model synchronously outputs at least three types of prediction results with different time resolutions and prediction durations; The first type of prediction result corresponds to a first prediction duration with high time resolution and is used for real-time power control; The second type of prediction result corresponds to a second prediction duration with medium time resolution, wherein the second prediction duration is longer than the first prediction duration and is used for a day-ahead scheduling plan; and the third type of prediction result corresponds to a third prediction duration with low time resolution, wherein the third prediction duration is larger than the second prediction duration and is used for medium-long running planning.
5. The method for the intensive intelligent management and control of a new energy power station group according to claim 1 or 4, wherein generating the evaluation information of the health status of the key equipment based on the unified data view comprises: Calculating an index value representing the health state of the equipment according to the real-time operation parameters of the equipment in the unified data view; Comparing the index value with a preset health reference threshold value; and when the comparison result meets the preset early warning condition, generating evaluation information comprising fault probability, component positioning and residual life estimation.
6. The method of claim 5, wherein generating a collaborative optimal control strategy for the power plant cluster based on the prediction information and the evaluation information, and distributing control instructions to each power plant, comprises: Constructing an optimization decision model comprising electricity market price, equipment health, power grid operation safety and equipment health constraint by taking the overall operation cost of a power station group as a target; inputting the power predicted value and the power market price prediction in the predicted information and the equipment health index in the evaluation information as key parameters into the optimization decision model and solving to obtain the optimized power set value of each power station; And converting the optimized power set value into a device control instruction which is adaptive to a local control system of each power station, and issuing and executing the device control instruction.
7. The method for the intensive intelligent management and control of a new energy power station group according to claim 6, wherein the objective function of the optimization decision model is expressed as Wherein, the In order to optimize the total number of periods of the cycle, For the total number of power stations, For power stations In the time period Is used for the planning of the active output, As a function of the cost of the power generation, For and output and equipment health index A function of the associated maintenance cost of the device, For a period of time And the electricity market of (3) predicts electricity prices.
8. The method for the intensive intelligent management and control of a new energy power station group according to claim 6, further comprising: when the power grid frequency is detected to deviate from a preset rated value, at least one first type of unit is selected to adjust the output of the first type of unit in a first time window based on the adjustment rate characteristics of each unit in the power station group; wherein the first type of unit comprises an energy storage system and/or a unit; And after the power grid frequency is restored to the preset rated value, recalculating the output set value of each unit in a subsequent time window based on the optimization decision model so as to smoothly transition the power station group to a cost optimal running state.
9. An intensive intelligent management and control system, characterized in that an intensive intelligent management and control method for a new energy power station group according to any one of claims 1-8 is applied, comprising: the edge perception layer is formed by edge computing gateways deployed in all power stations and is used for acquiring operation data from a plurality of heterogeneous new energy power stations; The cloud intelligent layer is used for receiving and fusing operation data from a plurality of heterogeneous new energy power stations to form a unified data view of a power station group level, generating prediction information of future power generation power of the power station group and evaluation information of the health state of key equipment based on the unified data view, generating a cooperative optimization control strategy of the power station group based on the prediction information and the evaluation information, and distributing control instructions to each power station for execution; And the data transmission layer is used for connecting the edge perception layer and the cloud intelligent layer in a communication way.

Description

Intensive intelligent management and control method and system for new energy power station group Technical Field The invention relates to the technical field of operation monitoring of new energy power stations, in particular to an intensive intelligent management and control method and system for a new energy power station group. Background New energy sources represented by wind power and photovoltaic enter a new stage of large-scale clustered development. Wind power and photovoltaic power generation installation planned in each region is continuously increased. This growth, while driving energy structure transformation, also presents unprecedented challenges to the operational management of power stations. The transmission of a one-control distributed management mode of a single station causes the defect of high operation and maintenance cost and poor cluster coordination capability, and becomes a key bottleneck for restricting the quality improvement and the efficiency improvement and the high-quality development of the industry. Currently, operation management of new energy power station groups mainly faces operation mode decentralization and decision islanding. The method is characterized in that each new energy station operates independently, and a monitoring system of the new energy station has a single function and forms a plurality of information islands. This makes it impossible for operators to obtain a unified, real-time, accurate view of the overall operation of the plant group level, all analyses and decisions being able to be made based on local data and limited experience of a single plant. The mode can not predict the cooperative power of the cross-power station, and can not formulate a cooperative control strategy considering global optimum, so that the overall efficiency of the power system is low, and the requirement of the intensive operation of the new energy power station can not be met. Disclosure of Invention Aiming at the problems that in the prior art, the independent operation mode of a new energy power station group cannot be used for carrying out collaborative power prediction of a cross power station, and a global optimal collaborative control strategy cannot be formulated to be considered, so that the overall efficiency of a power system is low, the invention provides an intensive intelligent management and control method and system of the new energy power station group, which can realize collaborative management and control of the cross power station, ensure global operation optimal, effectively reduce operation and maintenance cost and meet the intensive operation requirement of the new energy power station group in a large scale. The specific technical scheme is as follows: The invention provides an intensive intelligent management and control method of a new energy power station group, which is executed by an intensive intelligent management and control system deployed in a cloud-edge cooperative framework and comprises the following steps of: acquiring and fusing operation data from a plurality of heterogeneous new energy power stations to form a unified data view of a power station group level; based on the unified data view, generating prediction information of future power generation power of the power station group and evaluation information of the health state of key equipment; And generating a collaborative optimization control strategy for the power station group based on the prediction information and the evaluation information, and distributing a control instruction to each power station for execution. Preferably, the obtaining and fusing the operation data from the plurality of heterogeneous new energy power stations, and forming the unified data view of the power station group level includes: The collected original data based on different communication protocols are subjected to protocol analysis and format conversion through edge computing gateways deployed at all power stations; Uploading the data with unified analysis and format to a cloud platform, and performing data mapping and association based on a predefined unified information model to form the unified data view. Preferably, after forming the unified data view, the method further includes: Based on the unified data view, a digital twin model corresponding to the power station group is established and updated; in the digital twin model, virtual sensing and state deduction are carried out on missing or lagged actual acquired data through a mechanism model or a data driving model, blind areas or delays of the actual acquired data are supplemented, and the unified data view after complementation is obtained. Preferably, generating the prediction information of the future generation power of the power station group based on the unified data view includes: Inputting meteorological data, historical power data and space correlation characteristics in the unified data view into a multi-time scale power predi