CN118054439A - Distributed frequency stable inertia transaction method and system - Google Patents
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Abstract
The invention relates to the technical field of power systems, and discloses a distributed frequency stable inertia transaction method and a distributed frequency stable inertia transaction system, wherein inertia quotation data and generator node information data are obtained; calculating the frequency after each generator node is disturbed based on the generator node information data, and combining the frequencies after each generator node is disturbed to form a generator node disturbed frequency matrix; according to the frequency matrix after the disturbance of the generator nodes, calculating to obtain the frequency matrix after the disturbance of the nodes of the power system by utilizing a power system node frequency transfer equation; constructing frequency response constraints of all nodes based on the frequency matrix after the disturbance of the nodes of the power system; constructing an objective function with the lowest running cost as a target based on inertia quotation data; based on the objective function and the frequency response constraint of each node, constructing an inertia optimization clear model; and solving the inertia optimization clear model to obtain an optimal inertia transaction result, and solving the problem that the prior art cannot consider the frequency stability requirements of all nodes in the system.
Description
Technical Field
The invention relates to the technical field of power systems, in particular to a distributed frequency stable inertia transaction method and system.
Background
In order to improve the inertia level of a system containing a high proportion of renewable energy sources and enhance the stability of the system, many researches have been proposed to utilize the non-synchronous power sources (such as fans, photovoltaics and energy storage, etc.) to simulate the mechanical and electrical transient characteristics of the synchronous power sources, so that the input and output characteristics of the ac-dc converter approach to the synchronous power sources, and further provide equivalent virtual inertia for the system and enhance the stability of the system, however, the virtual synchronous machine technology (Virtual Synchronous Generation) is not well popularized and used in actual production life, because for the non-synchronous power sources, the VSG technology is used to provide virtual inertia for the system, which needs to occupy the self power generation capacity, and the part of the power generation capacity has a certain economic value in the electric energy market, so if the non-synchronous power sources use the VSG technology to provide inertia for the system, which does not consume capacity to provide inertia for the system, a reasonable inertia compensation transaction strategy is formulated, and the non-synchronous power sources (new energy sources) are encouraged to provide inertia for the system to become research.
In the prior art, whether the frequency response condition of a system meets the requirement or not is represented by aiming at a unified system index (system frequency or minimum system inertia), and then a corresponding transaction strategy is formulated, but when a large-scale power system is disturbed, even if the distributed inertia or the total system inertia in the system is the same, the frequency change conditions of different nodes are different, and when the unified system index is used for analyzing the frequency stability of the system, the frequency stability requirement of all nodes in the system cannot be considered.
Therefore, it is of great importance to study a distributed frequency-stable inertia transaction method and system which can consider the frequency response conditions of all nodes in a power system.
Disclosure of Invention
The invention aims to provide a distributed frequency stable inertia transaction method and system, which solve the problem that the frequency stability requirement of all nodes in a system cannot be considered because the frequency response condition is represented by adopting a unified system index when the required inertia is calculated in the prior art by analyzing the frequency response condition of all nodes in a power system.
In order to solve the technical problems, the first technical scheme of the invention provides a distributed frequency stable inertia transaction method, which comprises the following steps:
Acquiring inertia quotation data and generator node information data;
calculating the frequency after each generator node is disturbed based on the generator node information data, and combining the frequencies after each generator node is disturbed to form a generator node disturbed frequency matrix;
According to the frequency matrix after the disturbance of the generator nodes, calculating to obtain the frequency matrix after the disturbance of the nodes of the power system by utilizing a power system node frequency transfer equation;
constructing frequency response constraints of all nodes based on the frequency matrix after the power system nodes are disturbed;
Constructing an objective function with the lowest running cost as a target based on the inertia quotation data;
based on the objective function and the frequency response constraint of each node, constructing an inertia optimization clearing model;
and solving the inertia optimization clear model by utilizing a genetic algorithm to obtain an optimal inertia transaction result.
In some embodiments of the first technical solution, in calculating the frequency after each of the generator nodes is disturbed based on the generator node information data, the method specifically includes the following steps:
and calculating the disturbance distributed by each generator node by using a frequency equation of the disturbed generator node obtained by deriving a generator rotor motion equation and a power system disturbance distribution equation according to the generator node information data, and obtaining the frequency of each generator node after disturbance.
In some embodiments of the first technical solution, the expression of the frequency equation of the post-disturbance generator node is as follows:
In the above-mentioned method, the step of, Expressed as power system node/>Generator node/>, when disturbance occurs onFrequency of/(I)Expressed as generator node/>Initial phase angle of/>Expressed as generator node/>Voltage amplitude of/(v)Expressed as power system node/>Voltage amplitude of/(v)Expressed as/>, in the node admittance matrixReactive component of/>Expressed as power system node/>Amplitude of disturbance occurring above,/>Expressed as generator node/>, after the disturbance occursPhase angle of/>Expressed as generator/>The inertia provided.
In some embodiments of the first aspect, the expression of the power system node frequency transfer equation is as follows:
In the above-mentioned method, the step of, Expressed as a frequency matrix after power system node disturbance,/>Expressed as a coefficient matrix,/>Expressed as a post-disturbance frequency matrix of generator nodes,/>Expressed as/>, in the node admittance matrixReactive component of/>Expressed as/>, in the node admittance matrixReactive component of/>Expressed as/>, in the node admittance matrixReactive component of/>Representing generator node/>, at t moment after disturbance of power system node rFrequency of/(I)Representing power system node/>, at t moment after disturbance of power system node rIs a frequency of (a) is a frequency of (b).
In some embodiments of the first technical solution, after the power system node perturbs the frequency matrix, constructing a frequency response constraint of each node, where the step specifically includes the following steps:
Calculating the frequency change rate of the power system nodes after disturbance by using the frequency matrix after disturbance of the power system nodes, and constructing a frequency change rate constraint according to the frequency change rate and the maximum allowable frequency change rate preset by the power system nodes;
Calculating the frequency variation of the power system node after disturbance by using the frequency matrix after disturbance of the power system node, and constructing an overshoot constraint according to the frequency variation and the maximum allowable overshoot preset by the power system node;
And combining the frequency change rate constraint and the overshoot constraint into a node frequency response constraint.
In some embodiments of the first technical solution, the expression of the node frequency response constraint is as follows:
In the above-mentioned method, the step of, Expressed as node frequency response constraint,/>Expressed as disturbance event/>Rear/>Moment power system node/>Frequency change rate of/(v)Expressed as the maximum allowable rate of change of frequency at the power system node,Expressed as disturbance event/>Rear/>Moment power system node/>Frequency variation of/>Expressed as disturbance event/>Rear/>Moment power system node/>Maximum allowable overshoot of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Frequency values of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Is a minimum frequency value of/(Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Maximum frequency value of/()Represented as steady state frequency.
In some embodiments of the first aspect, in constructing an inertia optimized clearance model based on the objective function and the node frequency response constraints, in this step, the inertia optimized clearance model is constructed using inertia supply upper and lower limit constraints;
The expression of the inertia supply upper and lower limit constraint is as follows:
In the above-mentioned method, the step of, Expressed as upper and lower limit constraints of inertia supply,/>Expressed as generator/>Lower bound of output,/>Expressed as the upper limit of generator a output,/>Expressed as generator/>Actual output of/(I)Expressed as generator/>Capacity for providing inertia,/>Contract Power Generation Capacity expressed as other electric markets,/>Expressed as occurrence of disturbance event/>Rear electric generator/>Providing the power generation capacity occupied by inertia,/>Expressed as generator/>Inertia provided,/>Expressed as disturbance event/>Rear/>Time 1/>Frequency rate of change of individual power system nodes.
In some embodiments of the first technical solution, in constructing an inertia optimization model based on the objective function and the node frequency response constraints, the step further includes constructing the inertia optimization model using line transmission constraints;
The expression of the line transmission constraint is as follows:
In the above-mentioned method, the step of, Expressed as line transmission constraints,/>Expressed as upper limit of line transmission capacity,/>Expressed as the actual transmission capacity of the line,/>Expressed as a system transfer factor matrix,/>Expressed as/>Stripe line and/>Transfer factor between individual power system nodes,/>Expressed as a generator-power system node correlation matrix,/>Expressed as a load-power system node association matrix,/>Expressed as generator output matrix,/>Expressed as/>Output of each generator,/>Expressed as the number of gensets,/>Expressed as the sum of the load powers,/>Expressed as load/>Power of/>Expressed as the number of loads.
In some embodiments of the first technical solution, the expression of the objective function is as follows:
In the above-mentioned method, the step of, Expressed as the total cost of purchasing inertia,/>Expressed as/>Quotation of individual inertial suppliers,/>Expressed as from the/>Number of inertias purchased at an inertial supplier,/>Expressed as the total number of inertia suppliers.
The application provides a distributed frequency-stable inertia transaction system, which is characterized by comprising:
the acquisition module is used for acquiring inertia quotation data and generator node information data;
the first calculation module is used for calculating the frequency of each generator node after disturbance based on the power system node power data, and combining the frequencies of each generator node after disturbance to form a generator node frequency matrix after disturbance;
The second calculation module is used for calculating the post-disturbance frequency matrix of the power system nodes by utilizing a power system node frequency transfer equation according to the post-disturbance frequency matrix of the power generator nodes;
the construction constraint module is used for constructing frequency response constraints of all nodes based on the frequency matrix after the power system nodes are disturbed;
the building target module is used for building a target function with the lowest running cost as a target based on the inertia quotation data;
the model building module is used for building an inertia optimization clearing model based on the objective function and the frequency response constraint of each node;
and the solving module is used for solving the inertia optimization clear model by utilizing a genetic algorithm to obtain an optimal inertia transaction result.
The beneficial effects of the invention are as follows:
1. According to the scheme, the inertia optimization clearing model is built by using the objective function taking the lowest running cost of the power grid as a target and the frequency response constraint of each node, when the inertia optimization clearing model is solved to obtain the optimal inertia cost, the frequency response condition of each node can be calculated according to disturbance generated by random nodes in the power system and the inertia distribution of the power system, the frequency stability requirements of all nodes in the system are considered, and the stability of the power system after transaction is effectively ensured.
2. The scheme innovatively provides upper and lower limit constraint of inertia supply, and can set an upper limit for a supplier in an inertia transaction strategy, which has important significance in evaluating the supply capacity of the inertia supplier.
3. Because this scheme has rationally described the contribution of each inertia provider to electric power system stability to the excitation inertia provider provides inertia for the system, improves the frequency stability of system, and then promotes novel electric power system's further development.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow diagram of an overall scheme provided by a preferred embodiment of the present invention;
FIG. 2 is a schematic flow chart of a genetic algorithm solution inertia optimization model provided by the preferred embodiment of the invention;
FIG. 3 is a graph of inertia trade results using a genetic algorithm in accordance with a preferred embodiment of the present invention;
FIG. 4 is a diagram comparing a conventional method with the technology of the present invention;
FIG. 5 is a graph comparing the frequency change of node 7 of FIG. 4 in the case of a transaction according to the conventional method and the proposed technique;
fig. 6 is a schematic diagram of a system structure according to a conventional method and the technology of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
In the existing inertia trading method, an inertia pricing mechanism inspired by a power supply auxiliary service market is proposed based on a VCG mechanism, in the mechanism, virtual inertia suppliers are invited to participate in bidding, and the actual inertia supply quantity of each participant is determined according to social benefit maximization, however, the document does not study the actual frequency response of a power system, only considers the dynamic response cost in the worst case, and does not analyze the actual supporting effect of a specific inertia supplier; the literature designs a random electric market based on an opportunity constraint random unit commitment model with inertia requirements, and pricing energy, reserves and inertia supplies of an electric power system containing high-proportion renewable energy sources; there are also documents for providing a power generation capacity market pricing method considering the system inertia demand, and the inertia pricing method is designed by taking the lowest frequency, the frequency change rate and the quasi-steady state frequency as frequency safety indexes, but in the prior art, the response situation of the system frequency under the system inertia is roughly considered, the frequency response situation of each node is not analyzed specifically under different inertia supplies, when disturbance occurs in a large power system, even if distributed inertia or total system inertia in the system is the same, the frequency change situations of different nodes are different, and when the system frequency stability is analyzed by using a unified system index, the frequency stability requirements of all nodes in the system cannot be considered.
In order to solve the problem that the prior art adopts unified system indexes to represent the frequency response situation when the required inertia is calculated, so that the frequency stability requirements of all nodes in the system cannot be considered.
Referring to fig. 1, the present embodiment provides a distributed frequency-stabilized inertia transaction method, and the preferred embodiment specifically includes the following steps:
S1, acquiring required data, wherein the required data at least comprises inertia quotation data, generator node information data, disturbance data, load nodes, power transmission lines and other original data of a power system, and the inertia quotation data at least comprises inertia quantity purchased from a supplier and quotation of an inertia supplier; the generator node information data includes at least inertial data of each generator, angular velocity data of each generator.
S2, constructing corresponding constraint of each node frequency.
Specifically, step S2 includes the following steps:
s20, calculating the frequency of each generator node after disturbance based on the generator node information data, and combining the frequencies of each generator node after disturbance to form a generator node after disturbance frequency matrix.
Preferably, step S20 specifically includes the following steps:
And S200, calculating the disturbance shared by each generator node by using a frequency equation of the generator node after disturbance according to the generator node information data, and obtaining the frequency of each generator node after disturbance.
The frequency equation of the post-disturbance generator node is derived from the calculation of the generator rotor motion equation and the disturbance sharing equation of the electric power system, and the expression of the derivation process can be shown in the following generator rotor motion equation and the disturbance sharing equation of the electric power system.
The expression of the generator rotor equation of motion is as follows:
In the above-mentioned method, the step of, Expressed as generator/>Inertia provided,/>Expressed as generator/>Angular velocity of/>Expressed as generator/>The apportioned disturbance amplitude,/>Expressed as power system node/>Generator node/>, when disturbance occurs onIs used for the frequency of (a),Expressed as/>Generator set connectivity matrix,/>Expressed as slave/>The amount of inertia purchased at the supplier.
The expression of the power system disturbance sharing equation is as follows:
In the above-mentioned method, the step of, Expressed as generator/>Inertia provided,/>Expressed as power system node/>Generator node/>, when disturbance occurs onFrequency of/(I)Expressed as power system node/>Generator node/>, when disturbance occurs onUnbalanced power split coefficient of/>Expressed as power system node/>Amplitude of disturbance occurring above,/>Expressed as generator node/>Initial phase angle of/>Expressed as generator node/>, after the disturbance occursPhase angle of/>Expressed as generator node/>Voltage amplitude of/(v)Expressed as power system node/>Voltage amplitude of/(v)Expressed as/>, in the node admittance matrixIs used for the reactive component of the (c).
The expression of the frequency equation of the post-disturbance generator node is as follows:
In the above-mentioned method, the step of, Expressed as power system node/>Generator node/>, when disturbance occurs onFrequency of/(I)Expressed as generator node/>Initial phase angle of/>Expressed as generator node/>Voltage amplitude of/(v)Expressed as power system node/>Voltage amplitude of/(v)Expressed as/>, in the node admittance matrixReactive component of/>Expressed as power system node/>Amplitude of disturbance occurring above,/>Expressed as generator node/>, after the disturbance occursPhase angle of/>Expressed as generator/>The inertia provided.
It should be noted that, through the disturbance sharing equation of the power system, other generator nodes can be generalized and calculated, so that frequencies of all generator nodes in the power system are obtained, and a generator node frequency matrix is formed.
S201, combining the frequencies after the disturbance of all the generator nodes to form a frequency matrix after the disturbance of the generator nodes.
S21, according to the frequency matrix after the disturbance of the generator nodes, calculating to obtain the frequency matrix after the disturbance of the nodes of the power system by using a power system node frequency transfer equation.
Regarding the above power system node frequency transfer equation, the expression is as follows:
In the above-mentioned method, the step of, Expressed as a frequency matrix after power system node disturbance,/>Expressed as a coefficient matrix,/>Expressed as a post-disturbance frequency matrix of generator nodes,/>Expressed as/>, in the node admittance matrixReactive component of/>Expressed as/>, in the node admittance matrixReactive component of/>Expressed as/>, in the node admittance matrixReactive component of/>Representing generator node/>, at t moment after disturbance of power system node rFrequency of/(I)Representing power system node/>, at t moment after disturbance of power system node rIs a frequency of (a) is a frequency of (b).
S22, constructing frequency response constraints of all nodes based on the frequency matrix after disturbance of the power system nodes.
Specifically, step S22 includes the following steps:
s220, deducing and calculating the frequency change rate of the power system nodes after disturbance by utilizing the frequency matrix after disturbance of the power system nodes according to the definition of the frequency change rate, wherein the calculation process of the frequency change rate after disturbance is as follows:
In the above-mentioned method, the step of, Expressed as disturbance event/>Rear/>Moment power system node/>Frequency change rate of,/>Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Frequency values of (2).
And constructing a frequency change rate constraint according to the frequency change rate and a maximum allowable frequency change rate preset by the power system node, wherein the frequency change rate constraint is as follows:
In the above-mentioned method, the step of, Expressed as disturbance event/>Rear/>Moment power system node/>Is used for the frequency change rate of (a),Expressed as the maximum allowable rate of change of frequency at the power system node.
S221, deducing and calculating the frequency variation of the power system nodes after disturbance by using the frequency matrix after disturbance of the power system nodes, wherein the calculation process of the frequency variation after disturbance is as follows:
In the above-mentioned method, the step of, Expressed as disturbance event/>Rear/>Moment power system node/>Frequency variation of/>Expressed as disturbance event/>Rear/>Moment power system node/>Maximum allowable overshoot of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Frequency values of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Is a minimum frequency value of/(Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Maximum frequency value of/()Expressed as steady state frequency,/>Expressed as a disturbance event function,/>Represented as a disturbance event,Is the power system node where the disturbance occurs.
And constructing an overshoot constraint according to the frequency variation and a maximum allowable overshoot preset by the power system node, wherein the overshoot constraint is as follows:
In the above-mentioned method, the step of, Expressed as disturbance event/>Rear/>Moment power system node/>Frequency variation of/>Expressed as disturbance event/>Rear/>Moment power system node/>Is used for the maximum allowable overshoot.
S222, forming a node frequency response constraint by using the frequency change rate constraint and the overshoot constraint, wherein the expression of the node frequency response constraint is as follows:
In the above-mentioned method, the step of, Expressed as node frequency response constraint,/>Expressed as disturbance event/>Rear/>Moment power system node/>Frequency change rate of/(v)Expressed as the maximum allowable rate of change of frequency at the power system node,Expressed as disturbance event/>Rear/>Moment power system node/>Frequency variation of/>Expressed as disturbance event/>Rear/>Moment power system node/>Maximum allowable overshoot of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Frequency values of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Is a minimum frequency value of/(Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Maximum frequency value of/()Expressed as steady state frequency,/>Expressed as a disturbance event function,/>Expressed as disturbance event,/>Is the power system node where the disturbance occurs.
Wherein,Indicated as a preset value for the maximum allowable rate of change of frequency at the power system node,Expressed as interference event/>Post power system node/>The maximum allowable overshoot of (2) is a preset value, and can be set by a person skilled in the art according to national standards or actual conditions.
Summarizing step S2, in the prior art, whether the frequency response condition of the system meets the requirement or not is represented by a unified system index (system frequency or minimum inertia of the system), and then a corresponding transaction strategy is formulated, however, when a disturbance occurs in the power system, even if the distributed inertia or total inertia of the system is the same, the frequency change condition of different nodes can be different, when the system frequency stability is analyzed by using the unified system index, the frequency stability requirement of all nodes in the system cannot be considered, and compared with the prior art, the frequency response constraint of each node in the scheme is constructed according to the disturbance occurring at random nodes in the power system and the inertia distribution of the power system, the frequency response condition of each node is calculated by calculating the generator node frequency under each power system node, and the frequency stability requirement of all nodes in the system is considered.
S3, constructing upper and lower limit constraints of inertia supply.
The expression of the inertia supply upper and lower limit constraint is as follows:
In the above-mentioned method, the step of, Expressed as upper and lower limit constraints of inertia supply,/>Expressed as generator/>Lower bound of output,/>Expressed as generator/>Upper limit of output,/>Expressed as generator/>Actual output of/(I)Expressed as generator/>Capacity for providing inertia,/>Contract Power Generation Capacity expressed as other electric markets,/>Expressed as occurrence of disturbance event/>Rear electric generator/>Providing the power generation capacity occupied by inertia,/>Expressed as generator/>Inertia provided,/>Expressed as generator/>Is a function of the angular velocity of the rotor; /(I)Expressed as disturbance event/>Rear/>Time 1/>Frequency rate of change of individual power system nodes.
Summarizing step S3, in the prior art, since the supply party of inertia transaction needs to occupy the power generation capacity of the generator set when providing inertia to the system, the power generation capacity of the generator set has a certain upper limit, and the inertia supply party also has the problem of upper and lower limit constraint in the process of participating in inertia transaction, compared with the prior art, the solution, when constructing the inertia optimization model, integrates the upper and lower limit constraint of inertia supply, and the upper and lower limit constraint of inertia supply is described by using the upper and lower limit of power generation capacity, so that the upper limit can be set for the supply party in the inertia transaction strategy, which has important significance for evaluating the supply capacity of the inertia supply party.
S4, constructing line transmission constraints.
The expression of the line transmission constraint is as follows:
In the above-mentioned method, the step of, Expressed as line transmission constraints,/>Expressed as upper limit of line transmission capacity,/>Expressed as the actual transmission capacity of the line,/>Expressed as a system transfer factor matrix,/>Expressed as/>Stripe line and/>Transfer factor between individual power system nodes,/>Expressed as a generator-power system node correlation matrix,/>Expressed as a load-power system node association matrix,/>Expressed as generator output matrix,/>Expressed as/>Output of each generator,/>Expressed as the number of gensets,/>Expressed as the sum of the load powers,/>Expressed as load/>Power of/>Expressed as the number of loads.
Summarizing step S4, because the transmission capacity of the transmission line is limited to a certain extent when the new energy unit in the power system transmits electric quantity to the outside, the transmission capacity constraint of the line is integrated when the inertia optimization clear model is built.
S5, the power grid operator constructs an objective function with the lowest power grid operation cost as a target based on inertia quotation data of all inertia suppliers, wherein the expression of the objective function is as follows:
In the above-mentioned method, the step of, Expressed as the total cost of purchasing inertia,/>Expressed as/>Quotation of individual inertial suppliers,/>Expressed as from the/>Number of inertias purchased at an inertial supplier,/>Expressed as the total number of inertia suppliers.
S6, constructing an inertia optimization clear model based on the objective function, the frequency response constraint of each node, the upper and lower limit constraint of inertia supply and the line transmission constraint.
It should be noted that, in some embodiments, the inertia optimization model may be obtained by constructing an objective function and frequency response constraints of each node; in other embodiments, the inertia optimization model may be constructed from objective functions, node frequency response constraints, and inertia supply upper and lower constraints; or the inertia optimization clear model can be obtained by constructing an objective function, frequency response constraints of all nodes and line transmission constraints, the problem that the frequency stability requirements of all nodes in the system cannot be considered in the prior art can be solved by the embodiment, the optimal selection of the preferred embodiment provided by the scheme is the best effect, and the preferred embodiment can be selected by a person skilled in the art according to the actual requirements of the person.
Summarizing step S6, optimizing inertia to obtain an optimal solution obtained by the clear model, and achieving the aim of obtaining the lowest inertia compensation cost under the condition of meeting the frequency change of all nodes, wherein on one hand, the requirement of the frequency stability of all nodes in the system is considered; on the other hand, the constructed model can reasonably describe the contribution of each inertia provider to the stability of the power system, and can more accurately represent the contribution of the inertia provider under different nodes to the frequency stability of the power system, so that the inertia provider is stimulated to provide inertia for the system, the frequency stability of the system is improved, and further the further development of a novel power system is promoted.
And S7, solving the inertia optimization clear model by utilizing a genetic algorithm to obtain an optimal inertia transaction result.
Specifically, referring to fig. 2, the process of solving the inertia optimization model by using the genetic algorithm is as follows:
s70, firstly, setting optimization constraint, inputting original data of power systems such as distributed generator nodes, node loads and transmission lines, and constructing a grid diagram of the power system.
S71, an objective function (inertia compensation cost), that is, a cost spent purchasing inertia, is mapped to an fitness function.
S72, integrating the frequency response constraint, the inertia supply upper limit constraint, the inertia supply lower limit constraint and the line transmission constraint of each node into an algorithm, wherein the integration methods aiming at different constraints are different.
For each node frequency response constraint, the frequency response constraint of each node is integrated into the algorithm in a punishment function mode, and the specific method is as follows: adding node frequency response constraints to the objective function in the form of penalty terms (or penalty functions) whose construction concept is that when the argument is satisfied to satisfy the constraints, the penalty term is small, almost 0; when the argument does not meet the constraint, the penalty becomes larger, and a specific penalty can be represented by a step function or a linear function with a k value approaching infinity.
For the line transmission constraint, the line transmission constraint is integrated into the algorithm in an initializing mode, and because the algorithm firstly needs to input network architecture parameters (namely system load information, system generator set information, transmission line information and the like) of the system into the algorithm in the initializing process, the system generator and power system node association matrix can be obtained through the parametersGenerator output matrix/>Number of gensets/>And (3) waiting data, and calculating the upper limit/>, of the transmission capacity of the line according to the waiting data。
For the upper and lower limit constraint of inertia supply, the constraint is integrated into an algorithm in an initialized mode; the power generation capacity occupied by the unit inertia in the generator set can be calculated, when all the capacity in the generator set is used for providing inertia, the inertia which can be generated is the upper limit of the inertia which can be provided by the generator set, the lower limit is generally set to be zero, and in the process of initializing the independent variable (the inertia provided by the inertia supplier), the upper limit and the lower limit of the inertia are required to be calculated, so that the independent variable is restrained.
S73, generating an initial population through chromosome coding;
S74, calculating an fitness function of each individual in the population;
And S75, judging whether the calculation result of the fitness function meets a stopping criterion, decoding and outputting the result if the calculation result meets the stopping criterion, obtaining the result with the lowest inertia compensation cost, and if the calculation result does not meet the stopping criterion, continuing a series of means such as selection, intersection, variation and the like, generating a new generation population, and circulating until the optimal result is obtained.
The genetic algorithm is used for solving the technical model, and has the advantages of strong global searching capability, high solving precision, convenience in parallel operation and the like, thus being very suitable for the technical model.
Next, the present solution performs effect contrast with the prior art based on the present solution.
As shown in fig. 3, after basic power grid data of a certain city is input, a model is solved by using a genetic algorithm, and the obtained transaction result is shown in fig. 3.
As shown in fig. 4, we can find that under the conventional method, even if the minimum inertia of the system meets the requirement, the frequency change condition of some nodes still does not meet the requirement, for example: in disturbance case 1, the rocfs of nodes 1,2,3, 8, 9 do not meet the constraint; in disturbance scenario 2, rocfs of nodes 1,2,3, 8 and 9 do not satisfy the constraint. Node 7 also does not meet the constraint in the conventional approach due to its special requirement for the lowest frequency (49.81 hz); in disturbance scenario 3, rocfs for nodes 5, 6, 7 and 8 do not meet the constraint; under the technical scheme, the frequency change conditions of all nodes meet the requirements.
Further, the analysis is performed on the node 7 in fig. 4, and as shown in fig. 5, the frequency overshoot in the conventional technology does not meet the requirement, and the overshoot in the present technical solution meets the requirement.
As can be seen from the foregoing, the basic method and flow of the present embodiment will hereinafter be described with reference to fig. 6, which shows a distributed frequency-stabilized inertia transaction system to which the method is applied, including:
An acquisition module 800, configured to acquire inertia quotation data and generator node information data;
The first calculation module 801 is configured to calculate frequencies after each generator node is disturbed based on the power system node power data, and combine the frequencies after each generator node is disturbed to form a frequency matrix after the generator node is disturbed.
Specifically, according to the generator node information data, calculating the frequency of the generator node by using a generator rotor motion equation; and calculating the disturbance allocated by each generator node by using a disturbance allocation equation of the power system according to the frequency of the generator node, and obtaining the frequency of each generator node after disturbance.
The second calculation module 802 is configured to calculate, according to the post-disturbance frequency matrix of the generator node, a post-disturbance frequency matrix of the power system node by using a power system node frequency transfer equation.
And a construction constraint module 803 is used for constructing frequency response constraints of all nodes based on the frequency matrix after the power system nodes are disturbed.
Specifically, a frequency matrix after disturbance of the power system nodes is utilized, the frequency change rate of the power system nodes after disturbance is calculated, and a frequency change rate constraint is constructed according to the frequency change rate and the maximum allowable frequency change rate preset by the power system nodes; calculating the frequency variation of the power system nodes after disturbance by using the frequency matrix of the power system nodes after disturbance, and constructing overshoot constraint according to the frequency variation and the maximum allowable overshoot preset by the power system nodes; and combining the frequency change rate constraint and the overshoot constraint into a node frequency response constraint.
A build objective module 804 is configured to build an objective function that targets a minimum running cost based on the inertia bid data.
A build model module 805 for building an inertia optimization model based on the objective function and the node frequency response constraints.
And a solving module 806, configured to solve the inertia optimization model by using a genetic algorithm, so as to obtain an optimal inertia transaction result.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that changes and modifications may be made without departing from the principles of the invention, such changes and modifications are also intended to be within the scope of the invention.
Claims (10)
1. A distributed frequency stabilized inertia trading method, comprising the steps of:
Acquiring inertia quotation data and generator node information data;
calculating the frequency after each generator node is disturbed based on the generator node information data, and combining the frequencies after each generator node is disturbed to form a generator node disturbed frequency matrix;
According to the frequency matrix after the disturbance of the generator nodes, calculating to obtain the frequency matrix after the disturbance of the nodes of the power system by utilizing a power system node frequency transfer equation;
constructing frequency response constraints of all nodes based on the frequency matrix after the power system nodes are disturbed;
Constructing an objective function with the lowest running cost as a target based on the inertia quotation data;
based on the objective function and the frequency response constraint of each node, constructing an inertia optimization clearing model;
and solving the inertia optimization clear model by utilizing a genetic algorithm to obtain an optimal inertia transaction result.
2. A distributed frequency stabilized inertia trading method in accordance with claim 1, wherein the step of calculating the frequency of each generator node disturbance based on the generator node information data comprises the steps of:
And calculating the disturbance allocated by each generator node by using a frequency equation of the generator node after disturbance according to the generator node information data, and obtaining the frequency of each generator node after disturbance.
3. A distributed frequency stabilized inertia trade method as claimed in claim 2, wherein the expression of the frequency equation of the post-disturbance generator node is as follows:
In the above-mentioned method, the step of, Expressed as power system node/>Generator node/>, when disturbance occurs onFrequency of/(I)Expressed as generator node/>Initial phase angle of/>Expressed as generator node/>Voltage amplitude of/(v)Expressed as power system node/>Voltage amplitude of/(v)Expressed as/>, in the node admittance matrixReactive component of/>Expressed as power system node/>Amplitude of disturbance occurring above,/>Expressed as generator node/>, after the disturbance occursPhase angle of/>Expressed as generator/>The inertia provided.
4. A distributed frequency stabilized inertia trading method in accordance with claim 1, wherein the expression of the power system node frequency transfer equation is as follows:
In the above-mentioned method, the step of, Expressed as a frequency matrix after power system node disturbance,/>Expressed as a coefficient matrix,/>Expressed as a post-disturbance frequency matrix of generator nodes,/>Expressed as/>, in the node admittance matrixReactive component of/>Expressed as/>, in the node admittance matrixReactive component of/>Expressed as/>, in the node admittance matrixReactive component of/>Representing generator node/>, at t moment after disturbance of power system node rFrequency of/(I)Indicating power system node r to generate disturbance and then to generate power system node at t momentIs a frequency of (a) is a frequency of (b).
5. A distributed frequency stabilized inertia trading method as claimed in claim 1, wherein the step of constructing each node frequency response constraint based on the power system node post-disturbance frequency matrix comprises the steps of:
Calculating the frequency change rate of the power system nodes after disturbance by using the frequency matrix after disturbance of the power system nodes, and constructing a frequency change rate constraint according to the frequency change rate and the maximum allowable frequency change rate preset by the power system nodes;
Calculating the frequency variation of the power system node after disturbance by using the frequency matrix after disturbance of the power system node, and constructing an overshoot constraint according to the frequency variation and the maximum allowable overshoot preset by the power system node;
And combining the frequency change rate constraint and the overshoot constraint into a node frequency response constraint.
6. A distributed frequency stabilized inertia trading method in accordance with claim 5, wherein the expression of the node frequency response constraint is as follows:
In the above-mentioned method, the step of, Expressed as node frequency response constraint,/>Expressed as disturbance event/>Rear/>Moment power system node/>Frequency change rate of/(v)Expressed as the maximum allowable rate of change of frequency at the power system node,/>Expressed as disturbance event/>Rear/>Moment power system node/>Frequency variation of/>Expressed as disturbance event/>Rear/>Moment power system node/>Maximum allowable overshoot of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Frequency values of (2); /(I)Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Is a minimum frequency value of/(Expressed as power system node/>After disturbance of the upper part/>Moment power system node/>Maximum frequency value of/()Represented as steady state frequency.
7. A distributed frequency stabilized inertia trading method as claimed in claim 1, wherein in constructing an inertia optimized clearance model based on said objective function and said node frequency response constraints, the step further comprises constructing said inertia optimized clearance model using inertia supply upper and lower limit constraints;
The expression of the inertia supply upper and lower limit constraint is as follows:
In the above-mentioned method, the step of, Expressed as upper and lower limit constraints of inertia supply,/>Expressed as generator/>Lower bound of output,/>Expressed as generator/>Upper limit of output,/>Expressed as generator/>Actual output of/(I)Expressed as generator/>Capacity for providing inertia,/>Contract Power Generation Capacity expressed as other electric markets,/>Expressed as occurrence of disturbance event/>Rear generatorProviding the power generation capacity occupied by inertia,/>Expressed as generator/>Inertia provided,/>Expressed as disturbance event/>Rear/>Time 1/>Frequency rate of change of individual power system nodes.
8. A distributed frequency stabilized inertia trading method as claimed in claim 1, wherein in constructing an inertia optimized purge model based on the objective function and the node frequency response constraints, the step further comprises constructing the inertia optimized purge model using line transfer constraints;
The expression of the line transmission constraint is as follows:
In the above-mentioned method, the step of, Expressed as line transmission constraints,/>Expressed as upper limit of line transmission capacity,/>Expressed as the actual transmission capacity of the line,/>Expressed as a system transfer factor matrix,/>Expressed as/>Stripe line and/>Transfer factor between individual power system nodes,/>Expressed as a generator-power system node correlation matrix,/>Expressed as a load-power system node association matrix,/>Expressed as generator output matrix,/>Expressed as/>Output of each generator,/>Expressed as the number of gensets,/>Expressed as the sum of the load powers,/>Expressed as load/>Power of/>Expressed as the number of loads.
9. A distributed frequency stabilized inertia trading method in accordance with claim 1, wherein the expression of the objective function is as follows:
In the above-mentioned method, the step of, Expressed as the total cost of purchasing inertia,/>Expressed as/>Quotation of individual inertial suppliers,/>Expressed as from the/>Number of inertias purchased at an inertial supplier,/>Expressed as the total number of inertia suppliers.
10. A distributed frequency stabilized inertia trading system, comprising:
the acquisition module is used for acquiring inertia quotation data and generator node information data;
the first calculation module is used for calculating the frequency of each generator node after disturbance based on the power system node power data, and combining the frequencies of each generator node after disturbance to form a generator node frequency matrix after disturbance;
The second calculation module is used for calculating the post-disturbance frequency matrix of the power system nodes by utilizing a power system node frequency transfer equation according to the post-disturbance frequency matrix of the power generator nodes;
the construction constraint module is used for constructing frequency response constraints of all nodes based on the frequency matrix after the power system nodes are disturbed;
the building target module is used for building a target function with the lowest running cost as a target based on the inertia quotation data;
the model building module is used for building an inertia optimization clearing model based on the objective function and the frequency response constraint of each node;
and the solving module is used for solving the inertia optimization clear model by utilizing a genetic algorithm to obtain an optimal inertia transaction result.
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