CN117081170A - Power system scheduling method, device and medium for offshore wind farm under typhoon - Google Patents

Power system scheduling method, device and medium for offshore wind farm under typhoon Download PDF

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Publication number
CN117081170A
CN117081170A CN202311044399.9A CN202311044399A CN117081170A CN 117081170 A CN117081170 A CN 117081170A CN 202311044399 A CN202311044399 A CN 202311044399A CN 117081170 A CN117081170 A CN 117081170A
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typhoon
offshore wind
power
constraint
operation information
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朱誉
刘洋
李力
杨银国
伍双喜
林英明
华威
苏瑞文
谭嫣
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Guangdong Power Grid Co Ltd
Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd
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Guangdong Power Grid Co Ltd
Electric Power Dispatch Control Center of Guangdong Power Grid Co Ltd
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Priority to CN202311044399.9A priority Critical patent/CN117081170A/en
Publication of CN117081170A publication Critical patent/CN117081170A/en
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    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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    • H02J3/144—Demand-response operation of the power transmission or distribution network
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
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    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving

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Abstract

The invention discloses a power system scheduling method, a device and a medium of a typhoon offshore wind farm, wherein the scheduling method comprises the following steps: generating a typical scene set by analyzing typhoon operation information; predicting to obtain a predicted value sequence of wind speed and wind power by combining longitude and latitude coordinates of typhoon path points; establishing a risk index, operation constraint and expected yield objective function of the operation of the offshore wind turbine, so as to establish an offshore wind power optimal output model; establishing an objective function and an operation constraint group of the total operation cost of the power system, so as to establish an optimization model; solving the two models to obtain an optimal solution, and scheduling the power system of the offshore wind farm by taking the optimal solution as a power system scheduling method. The invention provides a power system dispatching method, a device and a medium of a typhoon offshore wind farm, which are used for improving the feasibility of the dispatching method of a power grid during typhoon by considering wind power uncertainty caused by typhoon forecasting errors and optimizing the output process of offshore wind power.

Description

Power system scheduling method, device and medium for offshore wind farm under typhoon
Technical Field
The invention relates to the technical field of disaster prevention and reduction of power systems, in particular to a power system scheduling method, device and medium of an offshore wind farm under typhoons.
Background
In recent years, the development of offshore wind power in China is rapid, the installed capacity is increased year by year, the wind power has stronger randomness and fluctuation, the influence caused by the connection of the offshore wind power into a power system is not negligible, the offshore weather conditions are complex and changeable, and the extreme weather conditions can have adverse effects on the offshore wind farm and the power system, so that the problem that how to schedule the power system containing large-scale offshore wind power under typhoon conditions is the current problem to be considered. The output level of the offshore wind farm is strongly related to the wind speed, and wind power uncertainty caused by typhoon forecast errors is not considered in the dispatching method of the power grid during typhoons disclosed in the prior art; in addition, the prior art is to directly formulate a scheduling method according to the predicted output of the offshore wind farm, and the output process of the offshore wind power is not optimized, so that the feasibility of the scheduling method of the power grid during typhoons is low.
Disclosure of Invention
The invention provides a power system dispatching method, a device and a medium of an offshore wind farm under typhoons, which are used for solving the problems that wind power uncertainty caused by typhoons forecast errors and the output process of offshore wind power are not optimized in the existing dispatching method of a power grid during typhoons.
The invention provides a power system scheduling method of a typhoon offshore wind farm, which comprises the following steps:
acquiring historical typhoon operation information and offshore wind farm operation information, and generating a typical scene set according to a clustering method by analyzing the typhoon operation information; predicting the wind speed and wind power at the offshore wind farm of the typical scene set by combining the longitude and latitude coordinates of the typhoon path point in the typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence;
establishing a risk index and a first operation constraint of the operation of the offshore wind turbine and a first objective function of expected benefits of the offshore wind turbine according to the operation information, the wind speed predicted value sequence and the wind power predicted value sequence of the offshore wind turbine, and constructing an offshore wind power optimal output model according to the risk index, the first operation constraint and the first objective function; establishing a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint set of the offshore wind farm according to the operation information of the offshore wind farm, and constructing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint set;
And solving the offshore wind power optimal output model and the power system multi-day-ahead optimization model to obtain a first optimal solution of a thermal power unit start-stop plan and a start-stop plan of the pumping and storage unit during typhoon and a second optimal solution of a thermal power unit reference operation plan, and using the first optimal solution and the second optimal solution as a power system scheduling method to schedule a power system of the offshore wind power plant.
According to the method, the wind speed and the wind power are predicted to obtain a wind speed predicted value sequence and a wind power predicted value sequence, the problem of uncertainty of the wind speed and the wind power caused by typhoon prediction errors is fully considered by the two predicted value sequences, and the accuracy is enhanced for the formulation of the power system scheduling method; the risk index of the operation of the offshore wind turbine, the expected income of the offshore wind farm and the operation state of the offshore wind turbine can be comprehensively considered through the optimal output model of the offshore wind turbine, so that the overall output is optimal; through the multi-day-ahead optimization model of the power system, the running cost and the running constraint condition can be considered from various aspects, so that the power system is optimal; the optimal solution obtained by solving the optimal output model of the offshore wind power and the multi-day-ahead optimization model of the power system is used as the power system to schedule the power system of the offshore wind power plant, so that the aim of optimizing the output process of the offshore wind power can be achieved. Compared with the prior art, the wind power uncertainty caused by typhoon forecast errors can be considered, and the output process of offshore wind power is optimized.
As a preferred scheme, by analyzing the typhoon operation information, a typical scene set is generated according to a clustering method, specifically:
calculating to obtain the relative error of the forecast value and the actual value according to the forecast value and the actual value of the typhoon path in the typhoon operation information, selecting the step length of the typhoon path or the direction forecast error, respectively drawing a forecast error histogram of the typhoon path and the direction forecast error by using the typhoon path and the angle error of all the historical sampling points in the typhoon operation information, and establishing an initial fitting distribution index corresponding to the typhoon path or the direction forecast error according to the forecast error histogram;
determining parameters in the initial fitting distribution index through a maximum likelihood estimation method to obtain a final fitting distribution index, and constructing an error distribution model according to the final fitting distribution index;
and generating a typical scene set by a clustering method according to the error distribution model and typhoon operation information.
According to the optimal scheme, the error distribution model is built through the forecast value and the actual value of the typhoon path, the problem of data uncertainty caused by typhoon forecast errors can be fully considered by the model, and typical data support is provided for subsequent building of a typical scene set.
As a preferred scheme, according to the error distribution model and typhoon operation information, a typical scene set is generated by a clustering method, specifically:
generating a first group of typhoon paths and direction prediction error sequences through a Monte Carlo method according to the error distribution model and typhoon prediction information in typhoon operation information, clustering the first group of typhoon paths and the direction prediction error sequences through a clustering method, generating a second group of typhoon paths and direction prediction error sequences, and taking each sequence in the second group of typhoon paths and the direction prediction error sequences as a typical scene of typhoon prediction errors to obtain the typical scene set.
According to the optimal scheme, a typical scene set is generated through a clustering method according to the error distribution model and typhoon forecast information, is a typical summary of historical typhoon data, is used as a typical example set, and can provide powerful data support for subsequent data prediction and calculation.
As a preferred scheme, wind speed and wind power at the offshore wind farm of the typical scene set are predicted by combining longitude and latitude coordinates of typhoon path points in typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence, wherein the wind speed predicted value sequence and the wind power predicted value sequence are specifically as follows:
The wind speed at each wind turbine generator set in the offshore wind farm in the typical scene set is predicted by using a preset wind speed prediction method under typhoon conditions according to longitude and latitude coordinates of typhoon path points in typhoon operation information, so that a wind speed predicted value sequence is obtained;
combining longitude and latitude coordinates of a typhoon path point in the typhoon operation information, and fitting a wind speed and an output curve of each wind turbine set by adopting a least square method according to the historical wind speed and a corresponding output value of each wind turbine set in the offshore wind farm operation information; and calculating the output value of each wind turbine according to the wind speed and output curve to obtain the wind power predicted value sequence.
According to the optimal scheme, the wind speed and the wind power are predicted, a wind speed predicted value sequence and a wind power predicted value sequence are obtained, uncertainty of the wind speed and the wind power caused by typhoon prediction errors is fully considered by the two predicted value sequences, and reliability is enhanced for the establishment of the power system scheduling method.
As a preferred scheme, according to the operation information, the wind speed predicted value sequence and the wind power predicted value sequence of the offshore wind turbine, a risk index and a first operation constraint of the operation of the offshore wind turbine and a first objective function of expected benefits of the offshore wind turbine are established, specifically:
Obtaining a first wind speed of a first wind turbine generator set at a first moment according to the wind speed predicted value sequence, and constructing a fault rate of the first wind turbine generator set according to the first wind speed; constructing a risk state continuous operation time of the first wind turbine according to the offshore wind farm operation information, and building a risk index of operation of the offshore wind turbine according to the fault rate and the risk state continuous operation time;
according to the wind power predicted value sequence, combining the operation information of the offshore wind farm to establish a first operation constraint of the offshore wind turbine;
and according to the risk index of the operation of the offshore wind turbine, combining the operation information of the offshore wind farm, and establishing a first objective function of expected benefits of the offshore wind farm.
The risk index of the operation of the offshore wind turbine constructed by the preferred scheme can comprehensively consider the failure rate and the risk state continuous operation time of the offshore wind turbine, the first operation constraint can consider the operation state of the offshore wind turbine, the first objective function can systematically consider the income of the offshore wind farm, the optimal output model of the offshore wind power generated on the basis can be guaranteed to be considered from the three angles, and the aim of optimal output of the offshore wind power is achieved.
As a preferred scheme, a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint group of the offshore wind farm are established according to the operation information of the offshore wind farm, specifically:
calculating to obtain the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding loss cost of a first scene in the typical scene set according to the operation information of the offshore wind farm, and establishing the second objective function according to the probability that the first scene possibly occurs by combining the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding loss cost;
and establishing thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint according to the offshore wind power plant operation information, wherein the thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint form a second operation constraint group of the offshore wind power plant.
The second objective function constructed by the preferred scheme can consider the operation cost from a plurality of angles of the operation of the power system, the second operation constraint group can consider constraint conditions of thermal power units, pumping and storage units, storage capacity and the like, and the power system multi-day-front optimization model generated on the basis can be guaranteed to be considered from the two angles, so that the purpose of optimizing the power system is achieved.
As a preferred scheme, the offshore wind power operation constraint is established according to the offshore wind power plant operation information, and specifically comprises the following steps:
and calculating the total output of the first offshore wind farm according to the active output of the first wind turbine in the first offshore wind farm at the second moment in the first scene and the number of the wind turbines in the first offshore wind farm, and constructing the offshore wind power operation constraint by enabling the total output of the first offshore wind farm to be smaller than or equal to the maximum value of the predicted value sequence of the wind power.
Preferably, the generating a typical scene set according to a clustering method by analyzing the typhoon operation information further includes:
correcting the longitude and latitude predicted coordinates of the typhoon path point in the typhoon operation information to obtain corrected longitude and latitude coordinates of the typhoon path point.
According to the optimization scheme, the longitude and latitude predicted coordinates of the typhoon path points are corrected, so that data errors caused by the longitude and latitude predicted coordinates of the typhoon path points can be reduced.
The invention provides a power system dispatching device of a typhoon offshore wind farm, which comprises:
the scene and predicted value acquisition module is used for acquiring historical typhoon operation information and offshore wind farm operation information, and generating a typical scene set according to a clustering method by analyzing the typhoon operation information; predicting the wind speed and wind power at the offshore wind farm of the typical scene set by combining the longitude and latitude coordinates of the typhoon path point in the typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence;
the optimization model construction module is used for building a risk index and a first operation constraint of the operation of the offshore wind turbine generator set and a first objective function of expected benefits of the offshore wind turbine generator set according to the operation information, the wind speed predicted value sequence and the wind power predicted value sequence of the offshore wind turbine generator set, and constructing an offshore wind power optimal output model according to the risk index, the first operation constraint and the first objective function; establishing a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint set of the offshore wind farm according to the operation information of the offshore wind farm, and constructing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint set;
And the application module is used for solving the optimal output model of the offshore wind power and the multi-day-ahead optimization model of the power system to obtain a first optimal solution of a start-stop plan of the thermal power unit and a start-stop plan of the pumping and storage unit during typhoons and a second optimal solution of a reference operation plan of the thermal power unit, and the first optimal solution and the second optimal solution are used as a power system scheduling method for scheduling the power system of the offshore wind power plant.
Preferably, the scene and predicted value obtaining module includes:
a typical scene set first construction unit calculates a relative error between a predicted value and an actual value of a typhoon path according to the predicted value and the actual value of the typhoon path in typhoon operation information, selects a step length of the typhoon path or direction prediction error, respectively draws a prediction error histogram of the typhoon path and the direction prediction error by using typhoon paths and angle errors of all historical sampling points in the typhoon operation information, and establishes an initial fitting distribution index corresponding to the typhoon path or the direction prediction error according to the prediction error histogram;
determining parameters in the initial fitting distribution index through a maximum likelihood estimation method to obtain a final fitting distribution index, and constructing an error distribution model according to the final fitting distribution index;
Generating a typical scene set by a clustering method according to the error distribution model and typhoon operation information;
the second construction unit of the typical scene set is used for generating a first group of typhoon paths and direction prediction error sequences through a Monte Carlo method according to the error distribution model and typhoon forecast information in typhoon operation information, clustering the first group of typhoon paths and the direction prediction error sequences through a clustering method to generate a second group of typhoon paths and direction prediction error sequences, and taking each sequence in the second group of typhoon paths and the direction prediction error sequences as a typical scene of typhoon forecast errors to obtain the typical scene set;
the correction unit is used for correcting the longitude and latitude predicted coordinates of the typhoon path point in the typhoon operation information to obtain corrected longitude and latitude coordinates of the typhoon path point;
the sequence value obtaining unit is used for predicting the wind speed at each wind turbine generator set in the offshore wind power plant in each classical scene in the typical scene set by using a preset wind speed prediction method under typhoon conditions in combination with the longitude and latitude coordinates of the typhoon path points in the typhoon operation information to obtain the wind speed prediction value sequence;
Combining longitude and latitude coordinates of a typhoon path point in the typhoon operation information, and fitting a wind speed and an output curve of each wind turbine set by adopting a least square method according to the historical wind speed and a corresponding output value of each wind turbine set in the offshore wind farm operation information; and calculating the output value of each wind turbine according to the wind speed and output curve to obtain the wind power predicted value sequence.
Preferably, the optimization model construction module includes:
the first model parameter acquisition unit is used for obtaining a first wind speed of a first wind turbine generator set at a first moment according to the wind speed predicted value sequence, and constructing a fault rate of the first wind turbine generator set according to the first wind speed; constructing a risk state continuous operation time of the first wind turbine according to the offshore wind farm operation information, and building a risk index of operation of the offshore wind turbine according to the fault rate and the risk state continuous operation time;
according to the wind power predicted value sequence, combining the operation information of the offshore wind farm to establish a first operation constraint of the offshore wind turbine;
according to the risk index of the operation of the offshore wind turbine, a first objective function of expected benefits of the offshore wind farm is established in combination with the operation information of the offshore wind farm;
The second model parameter obtaining unit is used for obtaining the pumping and accumulating unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding cost of the first scene in the typical scene set in a calculation mode according to the operation information of the offshore wind farm, and establishing the second objective function according to the probability that the first scene possibly happens by combining the pumping and accumulating unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding cost;
establishing thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint according to the offshore wind power plant operation information, and forming a second operation constraint group of the offshore wind power plant by the thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint;
the third model parameter obtaining unit is configured to calculate, according to the active power output of the first wind turbine in the first offshore wind farm at the second moment in the first scene and the number of wind turbine in the first offshore wind farm, the total output of the first offshore wind farm, and construct the offshore wind power operation constraint by making the total output of the first offshore wind farm be less than or equal to the maximum value of the predicted value sequence of the wind power.
The application provides a storage medium, wherein a computer program is stored on the storage medium, and the computer program is called and executed by a computer to realize the power system scheduling method of the offshore wind farm under typhoons.
Drawings
FIG. 1 is a schematic flow chart of a power system scheduling method for a typhoon offshore wind farm provided by an embodiment of the application;
FIG. 2 is a comparison chart of output conditions before and after offshore wind power optimization, which is provided by the embodiment of the application;
fig. 3 is a schematic structural diagram of a power system dispatching device for a typhoon offshore wind farm according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present application, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
The foregoing is a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention and are intended to be comprehended within the scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a power system scheduling method for a wind farm at sea under typhoons, including S1 to S3:
s1, acquiring historical typhoon operation information and offshore wind farm operation information, and generating a typical scene set according to a clustering method by analyzing the typhoon operation information; and predicting the wind speed and wind power at the offshore wind farm of the typical scene set by combining the longitude and latitude coordinates of the typhoon path point in typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence.
In the embodiment of the invention, S1 comprises S1.1-S1.3:
s1.1, calculating to obtain the relative error of the predicted value and the actual value according to the predicted value and the actual value of the typhoon path in typhoon operation information, and selecting typhoonsStep delta of path or direction forecast error l Respectively drawing a prediction error histogram of typhoon paths and direction prediction errors by using typhoon paths and angle errors of all historical sampling points in typhoon operation information, and establishing initial fitting distribution indexes corresponding to the typhoon paths or the direction prediction errors according to the prediction error histogram;
The initial fitting distribution index is:
wherein N is the error step delta of the selected path or direction forecast l Time-corresponding prediction error histogram interval number H i To predict the height of the error histogram, φ (A i ) Is an error distribution model.
Parameters in the initial fitting distribution index are determined through a maximum likelihood estimation method, a final fitting distribution index is obtained, and an error distribution model phi (A) is constructed according to the final fitting distribution index i )；
From error distribution model phi (A i ) And typhoon operation information, and generating a typical scene set through a clustering method.
S1.2, according to the error distribution model phi (A i ) And typhoon forecast information in typhoon operation information, generating a first group of typhoon paths and direction forecast error sequences through a Monte Carlo method, clustering the first group of typhoon paths and the direction forecast error sequences through a clustering method, generating a second group of typhoon paths and direction forecast error sequences, and taking each sequence in the second group of typhoon paths and the direction forecast error sequences as a typical scene of typhoon forecast errors to obtain a typical scene set omega.
S1.3, firstly, correcting the longitude and latitude predicted coordinates of a typhoon path point in typhoon operation information to obtain corrected longitude coordinates and latitude coordinates of the typhoon path point;
The corrected longitude coordinates and latitude coordinates of the typhoon route point are respectively as follows:
wherein R is e Is the earth radius (preferably 6371.39 km),and->Typhoon path forecast errors and angle forecast errors at all moments in any one of a plurality of typical scenes s are respectively, and ψ is the typical scene set omega i And phi i The longitude prediction coordinates and the latitude prediction coordinates of the ith sampling point of typhoon forecast information in typhoon operation information are respectively.
Then, combining longitude and latitude coordinates of typhoon path points in the corrected typhoon running information, and predicting the wind speed at each wind turbine generator set in the offshore wind farm in each classical scene in the classical scene set omega by using a preset wind speed prediction method under typhoon conditions to obtain a wind speed prediction value sequence;
combining longitude and latitude coordinates of typhoon path points in the corrected typhoon operation information, and fitting a wind speed and an output curve of each wind turbine set by adopting a least square method according to the historical wind speed and the corresponding output value of each wind turbine set in the offshore wind farm operation information; and calculating the output value of each wind turbine generator set in each classical scene in the classical scene set omega according to the wind speed and the output curve to obtain a wind power predicted value sequence.
According to the method, an error distribution model is built through the forecast value and the actual value of the typhoon path, the problem of data uncertainty caused by typhoon forecast errors can be fully considered by the model, and typical data support is provided for subsequent building of a typical scene set; generating a typical scene set by a clustering method according to the error distribution model and typhoon forecast information, wherein the typical scene set is a typical summary of historical typhoon data, and the typical scene set is used as a typical example set and can provide powerful data support for subsequent data prediction and calculation; by correcting the longitude and latitude predicted coordinates of the typhoon path points, the data errors caused by the longitude and latitude predicted coordinates of the typhoon path points can be reduced, so that the wind speed predicted value sequence and the wind power predicted value sequence generated on the basis are more accurate; the wind speed predicted value sequence and the wind power predicted value sequence fully consider the uncertainty of wind speed and wind power caused by typhoon prediction errors, and the reliability is enhanced for the formulation of the power system scheduling method.
S2, establishing risk indexes and first operation constraints of operation of the offshore wind turbine and a first objective function of expected benefits of the offshore wind turbine according to operation information, a wind speed predicted value sequence and a wind power predicted value sequence of the offshore wind turbine, and establishing an offshore wind power optimal output model according to the risk indexes, the first operation constraints and the first objective function; and establishing a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint set of the offshore wind farm according to the operation information of the offshore wind farm, and establishing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint set.
In the embodiment of the invention, S2 comprises S2.1-S2.4:
s2.1, firstly, obtaining a first wind speed of a first wind turbine generator set at a first moment according to a wind speed predicted value sequence, and constructing a fault rate of the first wind turbine generator set according to the first wind speed; constructing a risk state continuous operation time of the first wind turbine according to the operation information of the offshore wind farm, and establishing a risk index of operation of the offshore wind turbine according to the failure rate and the risk state continuous operation time;
the fault rate, the risk state continuous operation time and the risk index are respectively as follows:
J 2,i (t)＝max{0,J 2,i (t－1)+s i,t }；
Wherein w is a weight coefficient (taking a real number greater than 0 and less than 1), T d For typhoon duration (which may take different values depending on typhoon influence duration), v r Wind speed at turning point (15 m/s), v i (t) is the wind speed (obtained by a wind speed predicted value sequence) at the wind turbine generator group i at the moment t; b is the degree parameter (0.15) of the fault probability affected by the wind speed, p normal Is the failure probability s of the wind turbine under the normal condition i,t For the state variable of the running of the wind turbine generator set i at the moment t (the value of the running is 1 in the risk state, and the value of the running is-5), J 2,i (t-1) is the risk status duration operation time at the previous time, exp represents an exponential function based on a natural constant e.
Then, according to the wind power predicted value sequence, combining operation information of the offshore wind farm, and establishing a first operation constraint of the offshore wind turbine;
the first operational constraint is:
wherein,for the predicted output state of the wind turbine according to the wind speed, < > for the wind turbine>And->The output minimum value, the predicted value and the optimized report value of the ith offshore wind farm wind turbine m at the t moment (/ -)>Obtained from a sequence of predicted values of wind power),>and->The wind speed is the cut-in wind speed and the cut-out wind speed of the wind turbine generator m of the ith offshore wind farm, and the wind turbine generator m is +.>The running state variable v of the wind turbine m of the ith offshore wind farm at the moment t i,m,t And (3) the wind speed at the m position of the wind turbine generator m of the ith offshore wind farm at the t moment.
Secondly, according to risk indexes of operation of the offshore wind turbine, a first objective function of expected benefits of the offshore wind farm is established by combining operation information of the offshore wind farm;
the first objective function is:
for parameters ofThe method comprises the following steps:
wherein,and->Generating income, cutting cost and risk cost of the wind turbine generator m of the ith offshore wind farm at the moment T are respectively, and T is the length of a scheduling time window; n (N) pl And->C is the number of wind turbines in the offshore wind farm and one offshore wind farm respectively price 、c wf 、C off And C repair The power price, the risk cost conversion coefficient, the cutting cost and the expected maintenance cost are respectively sent out for the offshore wind power, and the wind power generation system is in charge of>For the active power of the ith offshore wind farm wind turbine m at time t, +.>And->The running state variables of the ith offshore wind farm wind turbine m are respectively the time t and the time (t-1), J i (T) is a risk index of the operation of the offshore wind turbine, T wf To assume the time from failure to failure repair of wind turbine m at this moment, Δt is the scheduling interval, +.>For the output predicted value of the ith offshore wind farm wind turbine m at k time, +.>And the running state variable of the wind turbine m of the ith offshore wind farm at the moment t.
And finally, constructing an offshore wind power optimal output model by the risk index, the first operation constraint and the first objective function.
S2.2, calculating to obtain the pumping and storage unit cost (comprising start-stop cost and operation cost), the thermal power unit cost (comprising start-stop cost and operation cost), the abandoned wind punishment cost, the energy storage operation cost and the load shedding cost of the first scene in the typical scene set according to the operation information of the offshore wind farm, and establishing a second objective function according to the probability that the first scene possibly happens by combining the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding cost;
the second objective function is:
wherein Ω is a typical scene set, s is any typical scene in the typical scene set Ω, ω s Is the probability that a typical scene s may occur,and->The method comprises the steps of respectively starting and stopping the pumping and accumulating unit and the thermal power unit which participate in multi-day-ahead scheduling, and adding ∈>And->Respectively representing the running cost of the pumping and storage unit, the running cost of the thermal power unit, the wind abandoning punishment cost, the energy storage running cost and the load shedding loss cost which participate in the multi-day scheduling under the typical scene s; />The number of wind turbines in the ith offshore wind farm;
For parameters ofAnd->The method comprises the following steps:
wherein NP, NG, NB and ND are respectively the number of pumped storage units, thermal power units, battery energy storage units and load node numbers which participate in scheduling operation, N pl Andthe number of the wind power generation sets in the offshore wind power plant and one offshore wind power plant are respectively C pu 、C pd 、C gu And C gd The cost of single start operation and stop operation of the water pump of the pumping and storage unit and the thermal power unit is respectively;and->The method comprises the steps of respectively starting and stopping a variable of a water pump of an ith pumping and accumulating unit, a state variable of the operation of a thermal power unit k, and a starting variable and a stopping variable of the thermal power unit k at t moment; />And->The cost conversion coefficient of pumping cost and the cost conversion coefficient of generating cost of the pumped storage unit i are respectively; /> And->Respectively obtaining pumping power and generating power of a pumping and accumulating unit, generating power of a thermal power unit, reported output and actual output of a wind power unit, charging power and generating power of battery energy storage and preventive load shedding of a load node d in a typical scene s at a moment t; a, a k 、b k And c k Are all cost coefficients of the thermal power unit k; c (C) w 、π c And pi d The method comprises the steps of respectively punishing cost coefficient of abandoned wind, breaking unit operation cost of battery energy storage and charging equivalent life and breaking unit operation cost of discharging equivalent life; c load Penalty for preventive load sheddingThe cost factor, T, is the scheduling time window length, and Δt is the scheduling time interval.
S2.3, establishing thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, reservoir capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint according to the operation information of the offshore wind power plant, and forming a second operation constraint group of the offshore wind power plant by the thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, reservoir capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint;
the first, thermal power generating unit operation constraint is:
wherein,and->The lower limit and the upper limit of the active output of the kth thermal power generating unit are respectively>Generating power of kth thermal power unit at t moment in typical scene s, < + >>For the time of continuous operation of the kth thermal power generating unit at the time T, T g Minimum time for allowing continuous operation for thermal power generating unit, < >>And->Respectively, a state variable of the operation of the thermal power generating unit k at the moment t, a start variable and a stop variable of the thermal power generating unit k, and +.>Is a state variable of the operation of the thermal power generating unit k at the time (t-1).
Second, climbing constraint is:
wherein R is D,k 、R U,k Respectively the maximum downhill climbing rate and the maximum uphill climbing rate of the kth thermal power generating unit, delta t is a scheduling time interval,and->Respectively starting variable and stopping variable of the thermal power generating unit k at the moment t, and +.>And->For the minimum shutdown power and startup power of the kth thermal power generating unit, +.>And->And the power generation power of the kth thermal power unit and the (k-1) thermal power unit at the t moment in the typical scene s respectively.
Thirdly, the operation constraint of the pumping and storage unit is as follows:
/>
wherein,is the operation variable of the pumping state and the power generation state of the ith pumping and storage unit at t time +.>Andthe variable of the start of the water pump of the ith pumping and storage unit and the variable of the stop of the thermal power unit k at the moment T are respectively, T e 、T b N is the time point of scheduling start and end in one day respectively p The maximum number of times of starting and stopping is allowed for the water pump unit for pumping and accumulating in one day; />Respectively the time of continuous operation of the ith pumping and accumulating unit in pumping or generating state at the moment T, T p 、T pg Respectively, the minimum time for allowing continuous operation of the pumping and storing unit in pumping and generating states is +.>And->Respectively the rated pumping power, the lower limit value and the upper limit value of the generating power of the ith pumping and accumulating unit, < + >>And pumping power for the pumping and accumulating unit at the moment t under a typical scene s.
Fourth, the storage capacity constraint is:
wherein,respectively pumping the storage capacities of an upper reservoir and a lower reservoir of the storage power station P at the moment t under a typical scene s,respectively pumping the storage capacity of the upper reservoir of the power storage station P at the moment t under a typical scene s at the beginning and the end of dispatching, c g,P 、c p,P Conversion coefficients of pumping water, generating power and flow rate of pumping and storing power station P respectively, +.>Respectively the pumping power and the generating power of the pumping and accumulating unit i at the moment t under the typical scene s, eta g,P 、η p,P Respectively the power generation efficiency and the water pumping efficiency of the P unit of the water pumping and accumulating power station, ρ 0 G and h P The density, the gravity acceleration and the average water head difference between the upper reservoir and the lower reservoir of the pumping and accumulating power station P are respectively;and->The upper limit and the lower limit of the upper reservoir storage capacity and the lower limit of the lower reservoir storage capacity of the pumping and storing power station P are respectively, delta Pmin 、δ Pmax The lower limit value and the upper limit value of the reservoir capacity variation of the upper (lower) reservoir of the pumping and accumulating power station P in a scheduling day are respectively set, and deltat is a scheduling time interval.
Fifth, offshore wind power operation constraint is:
for parameters ofThe method comprises the following steps:
wherein,for the active output of the wind turbine generator m in the ith offshore wind farm at t moment in the typical scene s,for the maximum value of the predicted value sequence of wind power, +.>For the total output of the ith offshore wind farm at time t in typical scenario s, +.>Is the number of wind turbines in the ith offshore wind farm.
Sixth, battery energy storage operation constraint is:
E n,0 SOC n min≤E n,t,s ≤E n,0 SOC n max；
wherein E is n,t,s For the power value of the battery energy storage n at time t in a typical scene s,the power value of the battery energy storage n at the beginning and end of the schedule in a typical scenario s, respectively,/-, is->Charging power and generating power of battery energy storage at t moment under typical scene s, and xi n Is the self-discharge rate, eta of the battery energy storage system c,n ,η d,n Charging and discharging efficiency of battery energy storage respectively, < >>Respectively the upper limit value of charge and discharge power of the battery energy storage n and the SOC n min、SOC n max is the upper limit and the lower limit of the allowable running of the battery energy storage charge state respectively, E n,0 For the rated capacity of the battery energy storage device, +.> The energy storage and charge operation state variable and the discharge operation state variable of the battery at the moment t in a typical scene s are respectively, and delta t is a scheduling time interval.
Seventh, system power balancing and standby constraints are:
for parameters ofAnd->The method comprises the following steps: />
Wherein,and->Upper rotation reserve which can be provided by a thermal power unit, a pumping and accumulating unit and battery energy storage unit respectively>Lower rotation reserve which can be provided for thermal power generating unit and battery energy storage respectively, beta L 、β W Rotational reserve coefficients NW, NG, NB, ND and N required for system load, offshore wind power, respectively ph The total number of the wind power generation units, the number of thermal power generation units operated in a scheduling manner, the number of battery energy storage units, the number of load nodes and the number of pumping power storage stations are respectively N pl And->The number of wind turbines in the offshore wind farm and the offshore wind farm are respectively; /> And->Respectively pumping power and generating power of a pumping and accumulating unit, generating power of a thermal power unit, reported output and actual output of a wind power unit, charging power and generating power of battery energy storage and preventive load shedding amount in a typical scene s at t moment; r is R D,k 、R U,k Respectively the maximum downhill climbing rate and the maximum uphill climbing rate of the kth thermal power generating unit,respectively the maximum value and the minimum value of the power generation power of the thermal power generating unit, the maximum value of the power generation power of the pumping and accumulating unit and the maximum value and the minimum value of the power generation power in the battery energy storage at the t moment under the typical scene s,respectively representing a state variable of the operation of the thermal power generating unit k at the moment t under a typical scene s, an operation variable of the power generation state of the pumping and accumulating unit i, a battery energy storage charging operation state variable and a discharging operation state variable, < >>A load at load node d is predicted.
Eighth, network constraints are:
wherein θ i,t,s 、θ i min And theta i max Respectively, node i is at time t under a typical scene sPhase angle, phase angle minimum and maximum; delta is the balancing node number; θ δ,t,s And theta j,t,s The phase angles of the nodes delta and j at the time t under a typical scene s are respectively; x is X ij Reactance for line ij; The transmission power of the line l at the time t under a typical scene s; />Respectively the minimum transmission power and the maximum transmission power of the circuit in the normal operation state; delta is the balancing node number; k (K) L 、K G 、K P 、K W 、K B And K D Respectively node-branch, node-generator, node-pumping and accumulating station, node-wind power station, node-battery energy storage and node-load association matrix (node branch matrix is defined as branch pointing node 1, departure node is-1, and other association matrix is defined as taking value 1 if the element is directly connected with node and taking value 0 if not directly connected with node), and the node-wind power station, node-battery energy storage and node-load association matrix>For the line transmission power vector (dimension nl×1) at time t in a typical scenario s,>and->The system comprises a generator power generation vector, a pumping power vector of a pumping power storage station, a power generation vector of an offshore wind farm, a battery energy storage and discharge power vector, a battery energy storage and charge power vector, a load vector and a load loss vector (the components of the power system represented by the vectors are orderly arranged downwards from small to large to form a column vector).
S2.4, constructing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint group.
The risk index of the operation of the offshore wind turbine constructed by the embodiment can comprehensively consider the failure rate and the risk state continuous operation time of the wind turbine, the first operation constraint can consider the operation state of the offshore wind turbine, the first objective function can systematically consider the income of the offshore wind farm, and the subsequent generation of the offshore wind power optimal output model on the basis can be ensured to be considered from the three angles, so that the aim of optimal output of the offshore wind power is achieved; the second objective function can consider the operation cost from a plurality of angles of the operation of the power system, the second operation constraint group can consider constraint conditions of thermal power units, pumping and storage units, storage capacity and the like, and the power system multi-day-ahead optimization model generated on the basis can be guaranteed to be considered from the two angles, so that the purpose of optimizing the power system is achieved.
And S3, solving an offshore wind power optimal output model and a power system multi-day-ahead optimization model to obtain a first optimal solution of a thermal power unit start-stop plan and a start-stop plan of a pumping and accumulating unit during typhoon and a second optimal solution of a thermal power unit reference operation plan, and using the first optimal solution and the second optimal solution as a power system scheduling method to schedule a power system of an offshore wind power plant.
In the embodiment of the invention, firstly, an offshore wind power optimal output model and a power system multi-day-ahead optimization model are solved to obtain a thermal power unit start-stop plan and a pumping and accumulating unit start-stop plan during typhoonsPumping and generating power of pumping and storing unit>Generating power of thermal power generating unit>Actual output of offshore wind turbine generator system +.>Energy storage charge and discharge power->Is a solution to the optimization of (3).
Then, obtaining a reference operation plan of the thermal power unit according to the power generation power of the thermal power unit;
the thermal power generating unit reference operation plan is as follows:
wherein,is the generating power of the thermal power generating unit, omega is a typical scene set, s is any typical scene in the typical scene set omega, omega s Is the probability that a typical scene s may occur.
Finally, the thermal power generating unit start-stop plan and the pumping and accumulating unit start-stop plan during typhoon And thermal power unit reference operation plan +. >As a power system scheduling method, scheduling the power system of the offshore wind farm. />
In order to apply the embodiments of the present invention, referring to fig. 2, an embodiment of the present invention provides a comparison chart of the output conditions before and after the optimization of the offshore wind farm, and it can be seen that after 250 time points (the interval between every two time points is 15 min), the active output of the optimized offshore wind farm is always maintained at a stable high level, and the phenomenon of unstable output or lower output does not occur.
In general, the embodiments of the present invention have the following beneficial effects:
according to the embodiment of the invention, the wind speed and the wind power are predicted to obtain the wind speed predicted value sequence and the wind power predicted value sequence, and the problems of uncertainty of the wind speed and the wind power caused by typhoon prediction errors are fully considered by the two predicted value sequences, so that the accuracy of the scheduling method of the power system is enhanced; the risk index of the operation of the offshore wind turbine, the expected income of the offshore wind farm and the operation state of the offshore wind turbine can be comprehensively considered through the optimal output model of the offshore wind turbine, so that the overall output is optimal; through the multi-day-ahead optimization model of the power system, the running cost and the running constraint condition can be considered from various aspects, so that the power system is optimal; the optimal solution obtained by solving the optimal output model of the offshore wind power and the multi-day-ahead optimization model of the power system is used as the power system to schedule the power system of the offshore wind power plant, so that the aim of optimizing the output process of the offshore wind power can be achieved. Compared with the prior art, the wind power uncertainty caused by typhoon forecast errors can be considered, and the output process of offshore wind power is optimized.
Referring to fig. 3, an embodiment of the present invention provides a power system dispatching apparatus for a typhoon offshore wind farm, including:
the scene and predicted value acquisition module 10 is used for acquiring historical typhoon operation information and offshore wind farm operation information, and generating a typical scene set according to a clustering method by analyzing the typhoon operation information; predicting the wind speed and wind power at the offshore wind farm of the typical scene set by combining the longitude and latitude coordinates of the typhoon path points in typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence;
the optimization model construction module 20 is configured to establish a risk index and a first operation constraint of operation of the offshore wind turbine according to the operation information, the wind speed predicted value sequence and the wind power predicted value sequence of the offshore wind turbine, and a first objective function of expected benefits of the offshore wind turbine, and construct an offshore wind power optimal output model according to the risk index, the first operation constraint and the first objective function; establishing a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint set of the offshore wind farm according to the operation information of the offshore wind farm, and establishing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint set;
The application module 30 is used for solving the offshore wind power optimal output model and the power system multi-day-ahead optimization model to obtain a first optimal solution of a thermal power unit start-stop plan and a start-stop plan of the pumping and storage unit during typhoons and a second optimal solution of a thermal power unit reference operation plan, and the first optimal solution and the second optimal solution are used as a power system scheduling method to schedule a power system of an offshore wind farm.
In one embodiment, the scene and predictor extraction module 10 further comprises:
the method comprises the steps that a first construction unit of a typical scene set calculates and obtains the relative error of a forecast value and an actual value according to the forecast value and the actual value of a typhoon path in typhoon operation information, selects the step length of the typhoon path or direction forecast error, draws a forecast error histogram of the typhoon path and the direction forecast error respectively by using typhoon paths and angle errors of all historical sampling points in the typhoon operation information, and establishes an initial fitting distribution index corresponding to the typhoon path or the direction forecast error according to the forecast error histogram;
determining parameters in the initial fitting distribution index by a maximum likelihood estimation method to obtain a final fitting distribution index, and constructing an error distribution model according to the final fitting distribution index;
Generating a typical scene set by a clustering method according to the error distribution model and typhoon operation information;
the second construction unit of the typical scene set is used for generating a first group of typhoon paths and direction prediction error sequences through a Monte Carlo method according to the error distribution model and typhoon forecast information in typhoon operation information, clustering the first group of typhoon paths and the direction prediction error sequences through a clustering method, generating a second group of typhoon paths and direction prediction error sequences, and taking each sequence in the second group of typhoon paths and the direction prediction error sequences as a typical scene of typhoon forecast errors to obtain the typical scene set;
the correction unit is used for correcting the longitude and latitude predicted coordinates of the typhoon path point in the typhoon operation information to obtain corrected longitude and latitude coordinates of the typhoon path point;
the sequence value obtaining unit is used for predicting the wind speed at each wind turbine generator set in the offshore wind power plant in the typical scene set by using a preset wind speed prediction method under the typhoon condition in combination with the longitude and latitude coordinates of the typhoon path point in the typhoon operation information to obtain a wind speed prediction value sequence;
combining longitude and latitude coordinates of typhoon path points in typhoon operation information, and fitting a wind speed and an output curve of each wind turbine unit by adopting a least square method according to the historical wind speed and the corresponding output value of each wind turbine unit in offshore wind farm operation information; and calculating the output value of each wind turbine according to the wind speed and the output curve to obtain a wind power predicted value sequence.
In one embodiment, the optimization model building module 20 further includes:
the first model parameter acquisition unit is used for obtaining a first wind speed of the first wind turbine generator set at a first moment according to the wind speed predicted value sequence, and constructing a fault rate of the first wind turbine generator set according to the first wind speed; constructing a risk state continuous operation time of the first wind turbine according to the operation information of the offshore wind farm, and establishing a risk index of operation of the offshore wind turbine according to the failure rate and the risk state continuous operation time;
according to the wind power predicted value sequence, in combination with the operation information of the offshore wind farm, establishing a first operation constraint of the offshore wind turbine;
according to risk indexes of operation of the offshore wind turbine, a first objective function of expected benefits of the offshore wind farm is established by combining operation information of the offshore wind farm;
the second model parameter acquisition unit is used for calculating and obtaining the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding loss cost of the first scene in the typical scene set according to the operation information of the offshore wind farm, and establishing a second objective function according to the probability that the first scene possibly happens by combining the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding loss cost;
Establishing thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, reservoir capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint according to the offshore wind power plant operation information, and forming a second operation constraint group of the offshore wind power plant by the thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, reservoir capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint;
the third model parameter obtaining unit is used for calculating the total output of the first offshore wind farm according to the active output of the first wind turbine in the first offshore wind farm at the second moment in the first scene and the number of the wind turbines in the first offshore wind farm, and constructing the offshore wind power operation constraint by enabling the total output of the first offshore wind farm to be smaller than or equal to the maximum value of the predicted value sequence of the wind power.
The wind speed and wind power are predicted to obtain a wind speed predicted value sequence and a wind power predicted value sequence, and the two predicted value sequences fully consider the problem of uncertainty of wind speed and wind power caused by typhoon prediction errors, so that the accuracy is enhanced for the formulation of the power system scheduling method; the risk index of the operation of the offshore wind turbine, the expected income of the offshore wind farm and the operation state of the offshore wind turbine can be comprehensively considered through the optimal output model of the offshore wind turbine, so that the overall output is optimal; through the multi-day-ahead optimization model of the power system, the running cost and the running constraint condition can be considered from various aspects, so that the power system is optimal; the optimal solution obtained by solving the optimal output model of the offshore wind power and the multi-day-ahead optimization model of the power system is used as the power system to schedule the power system of the offshore wind power plant, so that the aim of optimizing the output process of the offshore wind power can be achieved. Compared with the prior art, the wind power uncertainty caused by typhoon forecast errors can be considered, and the output process of offshore wind power is optimized.
Correspondingly, the embodiment of the invention also provides a computer readable storage medium, which comprises a stored computer program, wherein the equipment where the computer readable storage medium is located is controlled to execute the power system scheduling method of the offshore wind farm under typhoons when the computer program runs;
wherein a power system scheduling method of a typhoon offshore wind farm can be stored in a computer readable storage medium if implemented in the form of a software functional unit and used as a stand alone product. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the steps of each method embodiment described above may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
The foregoing is a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention and are intended to be comprehended within the scope of the present invention.

Claims (12)

1. A power system scheduling method for a typhoon offshore wind farm, comprising:
acquiring historical typhoon operation information and offshore wind farm operation information, and generating a typical scene set according to a clustering method by analyzing the typhoon operation information; predicting the wind speed and wind power at the offshore wind farm of the typical scene set by combining the longitude and latitude coordinates of the typhoon path point in the typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence;
establishing a risk index and a first operation constraint of the operation of the offshore wind turbine and a first objective function of expected benefits of the offshore wind turbine according to the operation information, the wind speed predicted value sequence and the wind power predicted value sequence of the offshore wind turbine, and constructing an offshore wind power optimal output model according to the risk index, the first operation constraint and the first objective function; establishing a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint set of the offshore wind farm according to the operation information of the offshore wind farm, and constructing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint set;
And solving the offshore wind power optimal output model and the power system multi-day-ahead optimization model to obtain a first optimal solution of a thermal power unit start-stop plan and a start-stop plan of the pumping and storage unit during typhoon and a second optimal solution of a thermal power unit reference operation plan, and using the first optimal solution and the second optimal solution as a power system scheduling method to schedule a power system of the offshore wind power plant.
2. The power system scheduling method of a typhoon offshore wind farm according to claim 1, wherein a typical scene set is generated according to a clustering method by analyzing typhoon operation information, specifically:
calculating to obtain the relative error of the forecast value and the actual value according to the forecast value and the actual value of the typhoon path in the typhoon operation information, selecting the step length of the typhoon path or the direction forecast error, respectively drawing a forecast error histogram of the typhoon path and the direction forecast error by using the typhoon path and the angle error of all the historical sampling points in the typhoon operation information, and establishing an initial fitting distribution index corresponding to the typhoon path or the direction forecast error according to the forecast error histogram;
determining parameters in the initial fitting distribution index through a maximum likelihood estimation method to obtain a final fitting distribution index, and constructing an error distribution model according to the final fitting distribution index;
And generating a typical scene set by a clustering method according to the error distribution model and typhoon operation information.
3. The power system scheduling method of a typhoon offshore wind farm according to claim 2, wherein a typical scene set is generated by a clustering method according to the error distribution model and typhoon operation information, specifically:
generating a first group of typhoon paths and direction prediction error sequences through a Monte Carlo method according to the error distribution model and typhoon prediction information in typhoon operation information, clustering the first group of typhoon paths and the direction prediction error sequences through a clustering method, generating a second group of typhoon paths and direction prediction error sequences, and taking each sequence in the second group of typhoon paths and the direction prediction error sequences as a typical scene of typhoon prediction errors to obtain the typical scene set.
4. The power system scheduling method of a typhoon offshore wind farm according to claim 1, wherein the wind speed and wind power at the offshore wind farm of the typical scene set are predicted by combining longitude and latitude coordinates of typhoon path points in the typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence, and specifically:
The wind speed at each wind turbine generator set in the offshore wind farm in the typical scene set is predicted by using a preset wind speed prediction method under typhoon conditions according to longitude and latitude coordinates of typhoon path points in typhoon operation information, so that a wind speed predicted value sequence is obtained;
combining longitude and latitude coordinates of a typhoon path point in the typhoon operation information, and fitting a wind speed and an output curve of each wind turbine set by adopting a least square method according to the historical wind speed and a corresponding output value of each wind turbine set in the offshore wind farm operation information; and calculating the output value of each wind turbine according to the wind speed and output curve to obtain the wind power predicted value sequence.
5. The power system scheduling method of a typhoon offshore wind farm according to claim 1, wherein a risk index and a first operation constraint of the operation of the offshore wind turbine and a first objective function of expected benefits of the offshore wind farm are established according to the operation information of the offshore wind farm, the wind speed predicted value sequence and the wind power predicted value sequence, specifically:
obtaining a first wind speed of a first wind turbine generator set at a first moment according to the wind speed predicted value sequence, and constructing a fault rate of the first wind turbine generator set according to the first wind speed; constructing a risk state continuous operation time of the first wind turbine according to the offshore wind farm operation information, and building a risk index of operation of the offshore wind turbine according to the fault rate and the risk state continuous operation time;
According to the wind power predicted value sequence, combining the operation information of the offshore wind farm to establish a first operation constraint of the offshore wind turbine;
and according to the risk index of the operation of the offshore wind turbine, combining the operation information of the offshore wind farm, and establishing a first objective function of expected benefits of the offshore wind farm.
6. The power system scheduling method of a typhoon offshore wind farm according to claim 1, wherein the second objective function of the total operation cost of the power system in the offshore wind farm and the second operation constraint group of the offshore wind farm are established according to the operation information of the offshore wind farm, specifically:
calculating to obtain the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding loss cost of a first scene in the typical scene set according to the operation information of the offshore wind farm, and establishing the second objective function according to the probability that the first scene possibly occurs by combining the pumping and storage unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding loss cost;
and establishing thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint according to the offshore wind power plant operation information, wherein the thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint form a second operation constraint group of the offshore wind power plant.
7. The power system scheduling method of a typhoon offshore wind farm according to claim 6, wherein the offshore wind farm operation constraint is established according to the offshore wind farm operation information, specifically:
and calculating the total output of the first offshore wind farm according to the active output of the first wind turbine in the first offshore wind farm at the second moment in the first scene and the number of the wind turbines in the first offshore wind farm, and constructing the offshore wind power operation constraint by enabling the total output of the first offshore wind farm to be smaller than or equal to the maximum value of the predicted value sequence of the wind power.
8. A power system scheduling method of a typhoon offshore wind farm according to claim 1, wherein a typical scene set is generated according to a clustering method by analyzing the typhoon operation information, further comprising:
correcting the longitude and latitude predicted coordinates of the typhoon path point in the typhoon operation information to obtain corrected longitude and latitude coordinates of the typhoon path point.
9. A power system dispatch device for a typhoon offshore wind farm, comprising:
the scene and predicted value acquisition module is used for acquiring historical typhoon operation information and offshore wind farm operation information, and generating a typical scene set according to a clustering method by analyzing the typhoon operation information; predicting the wind speed and wind power at the offshore wind farm of the typical scene set by combining the longitude and latitude coordinates of the typhoon path point in the typhoon operation information to obtain a wind speed predicted value sequence and a wind power predicted value sequence;
The optimization model construction module is used for building a risk index and a first operation constraint of the operation of the offshore wind turbine generator set and a first objective function of expected benefits of the offshore wind turbine generator set according to the operation information, the wind speed predicted value sequence and the wind power predicted value sequence of the offshore wind turbine generator set, and constructing an offshore wind power optimal output model according to the risk index, the first operation constraint and the first objective function; establishing a second objective function of the total operation cost of the power system in the offshore wind farm and a second operation constraint set of the offshore wind farm according to the operation information of the offshore wind farm, and constructing a multi-day-ahead optimization model of the power system according to the second objective function and the second operation constraint set;
and the application module is used for solving the optimal output model of the offshore wind power and the multi-day-ahead optimization model of the power system to obtain a first optimal solution of a start-stop plan of the thermal power unit and a start-stop plan of the pumping and storage unit during typhoons and a second optimal solution of a reference operation plan of the thermal power unit, and the first optimal solution and the second optimal solution are used as a power system scheduling method for scheduling the power system of the offshore wind power plant.
10. The power system scheduling apparatus of a typhoon offshore wind farm according to claim 9, wherein the scenario and predictor acquisition module comprises:
A typical scene set first construction unit calculates a relative error between a predicted value and an actual value of a typhoon path according to the predicted value and the actual value of the typhoon path in typhoon operation information, selects a step length of the typhoon path or direction prediction error, respectively draws a prediction error histogram of the typhoon path and the direction prediction error by using typhoon paths and angle errors of all historical sampling points in the typhoon operation information, and establishes an initial fitting distribution index corresponding to the typhoon path or the direction prediction error according to the prediction error histogram;
determining parameters in the initial fitting distribution index through a maximum likelihood estimation method to obtain a final fitting distribution index, and constructing an error distribution model according to the final fitting distribution index;
generating a typical scene set by a clustering method according to the error distribution model and typhoon operation information;
the second construction unit of the typical scene set is used for generating a first group of typhoon paths and direction prediction error sequences through a Monte Carlo method according to the error distribution model and typhoon forecast information in typhoon operation information, clustering the first group of typhoon paths and the direction prediction error sequences through a clustering method to generate a second group of typhoon paths and direction prediction error sequences, and taking each sequence in the second group of typhoon paths and the direction prediction error sequences as a typical scene of typhoon forecast errors to obtain the typical scene set;
The correction unit is used for correcting the longitude and latitude predicted coordinates of the typhoon path point in the typhoon operation information to obtain corrected longitude and latitude coordinates of the typhoon path point;
the sequence value obtaining unit is used for predicting the wind speed at each wind turbine generator set in the offshore wind power plant in each classical scene in the typical scene set by using a preset wind speed prediction method under typhoon conditions in combination with the longitude and latitude coordinates of the typhoon path points in the typhoon operation information to obtain the wind speed prediction value sequence;
combining longitude and latitude coordinates of a typhoon path point in the typhoon operation information, and fitting a wind speed and an output curve of each wind turbine set by adopting a least square method according to the historical wind speed and a corresponding output value of each wind turbine set in the offshore wind farm operation information; and calculating the output value of each wind turbine according to the wind speed and output curve to obtain the wind power predicted value sequence.
11. The power system scheduling apparatus of a typhoon offshore wind farm according to claim 9, wherein the optimization model building module comprises:
the first model parameter acquisition unit is used for obtaining a first wind speed of a first wind turbine generator set at a first moment according to the wind speed predicted value sequence, and constructing a fault rate of the first wind turbine generator set according to the first wind speed; constructing a risk state continuous operation time of the first wind turbine according to the offshore wind farm operation information, and building a risk index of operation of the offshore wind turbine according to the fault rate and the risk state continuous operation time;
According to the wind power predicted value sequence, combining the operation information of the offshore wind farm to establish a first operation constraint of the offshore wind turbine;
according to the risk index of the operation of the offshore wind turbine, a first objective function of expected benefits of the offshore wind farm is established in combination with the operation information of the offshore wind farm;
the second model parameter obtaining unit is used for obtaining the pumping and accumulating unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding cost of the first scene in the typical scene set in a calculation mode according to the operation information of the offshore wind farm, and establishing the second objective function according to the probability that the first scene possibly happens by combining the pumping and accumulating unit cost, the thermal power unit cost, the abandoned wind punishment cost, the energy storage operation cost and the load shedding cost;
establishing thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint according to the offshore wind power plant operation information, and forming a second operation constraint group of the offshore wind power plant by the thermal power unit operation constraint, climbing constraint, pumping and accumulating unit operation constraint, storage capacity constraint, offshore wind power operation constraint, battery energy storage operation constraint, system power balance and standby constraint and network constraint;
The third model parameter obtaining unit is configured to calculate, according to the active power output of the first wind turbine in the first offshore wind farm at the second moment in the first scene and the number of wind turbine in the first offshore wind farm, the total output of the first offshore wind farm, and construct the offshore wind power operation constraint by making the total output of the first offshore wind farm be less than or equal to the maximum value of the predicted value sequence of the wind power.
12. A storage medium, characterized in that the storage medium has stored thereon a computer program, which is invoked and executed by a computer, for implementing a power system scheduling method of an offshore wind farm under typhoons according to any of the preceding claims 1 to 8.
CN202311044399.9A 2023-08-17 2023-08-17 Power system scheduling method, device and medium for offshore wind farm under typhoon Pending CN117081170A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117977715A (en) * 2024-03-29 2024-05-03 国网江苏省电力有限公司无锡供电分公司 Wind farm scheduling method, system, device and medium
CN118232318A (en) * 2024-03-12 2024-06-21 山东大学 Short-term wind power prediction method, system, medium and equipment in typhoon scene

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118232318A (en) * 2024-03-12 2024-06-21 山东大学 Short-term wind power prediction method, system, medium and equipment in typhoon scene
CN117977715A (en) * 2024-03-29 2024-05-03 国网江苏省电力有限公司无锡供电分公司 Wind farm scheduling method, system, device and medium
CN117977715B (en) * 2024-03-29 2024-06-07 国网江苏省电力有限公司无锡供电分公司 Wind farm scheduling method, system, device and medium

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