CN117277428A - Wind power output fluctuation optimization scheduling method considering frequency constraint - Google Patents

Wind power output fluctuation optimization scheduling method considering frequency constraint Download PDF

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CN117277428A
CN117277428A CN202311046324.4A CN202311046324A CN117277428A CN 117277428 A CN117277428 A CN 117277428A CN 202311046324 A CN202311046324 A CN 202311046324A CN 117277428 A CN117277428 A CN 117277428A
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王秋杰
陈嘉迅
刘国安
刘观辉
冷子豪
王昊
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China Three Gorges University CTGU
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    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
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Abstract

The wind power output fluctuation optimization scheduling method considering frequency constraint comprises the following steps: step 1: acquiring element parameters, load data and energy storage system parameters of a power grid, and predicting the power of a wind turbine generator in a full time period; step 2: constructing an objective function of wind power output fluctuation optimization scheduling taking frequency constraint into consideration in extreme weather; step 3: establishing constraint conditions of the objective function in the step 2 to obtain an optimized scheduling model under wind power output fluctuation; step 4: and (3) converting the optimized scheduling model in the step (3) into a compact mathematical model, and solving by a solver by adopting a column and constraint generation (C & CG) algorithm. The method can obtain the optimal unit combination and scheduling scheme in extreme weather.

Description

Wind power output fluctuation optimization scheduling method considering frequency constraint
Technical Field
The invention relates to the technical field of power system optimization scheduling, in particular to a wind power output fluctuation optimization scheduling method considering frequency constraint in extreme weather.
Background
As new energy permeability is continuously increased, the inertia response and primary frequency response capabilities of conventional units are continuously reduced. The frequency is used as one of important indexes for measuring the electric quantity, and when the power grid is subjected to high-power disturbance, the frequency safety problem needs to be considered seriously. On the one hand, many scholars study the influence of frequency variation on the scheduling result of the whole system mainly from load disturbance. When power disturbance occurs at the source side, the influence research of frequency change on a dispatching result is less, for example, under extreme weather (such as strong wind, typhoon, hurricane and the like), the actual output of the wind turbine generator is larger in deviation compared with the predicted output, the power disturbance is easy to be caused, and further the hidden trouble of frequency deviation out of limit occurs. On the other hand, how to refine the frequency change rate (Rate of Change of Frequency, rocofs) and the frequency nadir as important indexes of the measured frequency and consider the two important indexes into a scheduling model becomes a problem to be solved urgently. In addition, the energy storage device is used as a virtual synchronous generator (Virtual synchronous generator, VSG), and the participation of the energy storage device can effectively improve the inertia supporting and primary frequency modulation capacity of the system.
Disclosure of Invention
In order to solve the technical problems, the invention provides the wind power output fluctuation optimization scheduling method considering frequency constraint in extreme weather, and the optimal unit combination and scheduling scheme in extreme weather can be obtained.
The technical scheme adopted by the invention is as follows:
the wind power output fluctuation optimization scheduling method considering frequency constraint comprises the following steps:
step 1: acquiring element parameters, load data, energy storage system parameters of a power grid and power output data of fluctuation of a wind turbine generator set in a full time period;
step 2: constructing an objective function of wind power output fluctuation optimization scheduling in consideration of frequency constraint;
step 3: establishing constraint conditions of the objective function in the step 2 to obtain a wind power output fluctuation optimization scheduling model;
step 4: the optimized scheduling model of the step 3 is converted into a compact mathematical model, and a column and constraint generation (Column and Constraint generation, C & CG) algorithm is adopted for solving through a solver.
In the step 1, the element parameters of the power grid comprise impedance, line transmission capacity and node numbers;
the load data comprises predicted values in the scheduling period of each load node;
the energy storage system parameters include charge and discharge efficiency, maximum charge and discharge power, maximum and minimum state of charge, and energy storage device capacity.
In the step 2, the objective function is that the comprehensive cost is minimum in the worst case of wind power output in the worst weather scene,
the method comprises the steps of operating cost, start-stop cost and frequency modulation cost of a conventional unit in a scheduling period;
in the method, in the process of the invention,the start-stop cost of the first-stage unit is minimum; u and v are binary variables of the energy storage device and the conventional unit combination respectively; />In the worst case of the output of the wind turbine generator in the worst weather, the output cost of the conventional wind turbine generator and the frequency modulation spare capacity cost R are minimum; t is the total scheduling period; n (N) g The total number of the conventional units; a, b and c are cost coefficients of the output of the conventional unit; p (P) i,t The output of the conventional unit i is the period t; v i,t The operation state of the conventional unit i in the period t; s is(s) i,t The starting state of the conventional unit i in the period t; r is (r) i,t The shutdown state of the conventional unit i in the period t; />Starting up cost of a conventional unit i for a period t; />The shutdown cost of the conventional unit i is set for a period t; i is the ith conventional unit; t is the t-th period; p (P) g The output of the conventional unit is provided; x is a state variable of the output taking-down boundary of the wind turbine generator; z is the output power of the wind turbine generator set and takes the upper bound state variable;
r is the total spare capacity cost required during system frequency modulation, and the expression is as follows:
wherein e and f are standby capacity cost coefficients of the conventional unit and the energy storage device respectively; r is R i,t The standby capacity of the conventional unit i in a period t; r is R s,t Standby capacity for the energy storage device s period t; n (N) s The total number of the energy storage devices; t is the total scheduling period; s is the s-th energy storage device.
In the step 3, each constraint condition is as follows:
1) Conventional unit output constraint:
in the method, in the process of the invention,maximum technical output of the conventional unit g, < ->The minimum technical output of the conventional unit g; p (P) g,t The output of the conventional unit in the period of g is output; r is R g,t The standby capacity of the conventional unit in the period g is the standby capacity of the conventional unit in the period t; v g,t Is the operating state variable of the conventional unit g period t.
2) Unit combination constraint:
in the formula, v g,t The running state variable is the running state variable of the conventional unit in the period g; v g,t-1 The operation state variable is the operation state variable of the conventional unit in the period t-1; r is (r) g,t The starting state variable is the starting state variable of the conventional unit g period t; s is(s) g,t For the shutdown state variable of the conventional unit g period tFor the period g of the conventional unit->Is a running state variable of (1);
representing arbitrary +.>Belonging to [ t+1, min (t+T) off -1,T)]；T on The minimum starting time of the conventional unit is set; t (T) off Minimum downtime for a conventional unit; min (t+T) on -1, T) represents t+T on -a minimum value is taken between 1 and T; min (t+T) off -1, T) represents t+T off -a minimum value is taken between 1 and T.
3) Energy storage device restraint:
in the method, in the process of the invention,discharging power of the energy storage device s for a period t; />Maximum discharge power of the energy storage device s for a period t; u (u) s,t The charge and discharge states of the energy storage device s are the period t; />Charging power for the energy storage device s for a period t; />Maximum charging power for the energy storage device s; />The state of charge of the energy storage device s for a period t; η (eta) ch Charging efficiency of the energy storage device; η (eta) dis Is the discharge efficiency of the energy storage device; />Is the rated capacity of the energy storage device s; />A minimum state of charge for the energy storage device s; />The maximum state of charge of the energy storage device s; />State of charge for time period t+1 energy storage device s; />Charging power for the energy storage device s for a period t+1; />For a period t+1, the discharge power of the energy storage device s.
4) Power balance constraint:
wherein:is a set of all nodes connected to node n; />Predicted output of the wind turbine generator set in the j period t;the required power for the load d period t; n (N) w The total number of the wind turbine generators is the total number of the wind turbine generators; n (N) load Is the total number of loads.
5) Node voltage phase angle constraint:
in the method, in the process of the invention,the minimum node voltage phase angle for node i; />The maximum node voltage phase angle of the node i; θ i,t A voltage phase angle of a node i period t; θ ref,t Is the voltage phase angle of the reference node ref period t.
6) Line capacity constraint:
in the method, in the process of the invention,for maximum transmission capacity of line ij, B ij Susceptance for line ij; θ i,t A node voltage phase angle of the node i period t; θ j,t The node voltage phase angle for node j period t.
7) Output constraint of the wind turbine generator system:
wherein DeltaP w,t The deviation power of the period t of the wind turbine generator w caused by bad weather; p (P) w,t The actual output of the wind turbine generator set in the w period t is obtained;predicted output of the wind turbine set in w time period t; x is x w,t The output of the wind turbine generator set w time period t is taken as an upper bound; z w,t And (5) representing the output taking-off boundary of the wind turbine generator set w time period t.
8) Frequency constraint:
at the moment of frequency change of active disturbance, the system has a frequency dead zone, and in the period, the system cannot perform primary frequency modulation, the moment of change is supported by the inertia support power of the system, the inertia support power of the system comprises the inertia support power of a conventional unit and an energy storage device, and the inertia support power of the system is represented by the following formula:
conventional unit inertia support power:
in the method, in the process of the invention,the inertia support power provided for the period t conventional unit g; h g For the conventional units gAn inertial time constant; Δf (t) is the frequency deviation of period t; />Frequency change rate for period t; f (f) 0 Is the operating frequency of the system. />The maximum technical output provided for the conventional unit g.
Energy storage device inertia support power:
wherein H is s,t An equivalent inertial time constant for the period t of the energy storage device s; p (P) s,t The residual electric quantity of the energy storage device s in a period t;is the rated capacity of the energy storage device s; s is S B Is the reference power of the system; />Is the maximum charge-discharge multiplying power of the energy storage device s; />The power is supported for the inertia of the energy storage device s for a period t.
When the frequency dead time is reached, the conventional unit and the energy storage device perform primary frequency modulation:
conventional unit frequency support power:
in the method, in the process of the invention,support power for providing primary frequency modulation for g period t of conventional unitA rate; delta g The difference adjustment coefficient is the difference adjustment coefficient of the conventional unit g; Δf t Frequency deviation resulting from power disturbance for period t.
Energy storage device frequency support power:
in the method, in the process of the invention,providing primary frequency modulation support power for the energy storage device s in a period t; delta s Is the difference adjustment coefficient of the conventional unit s.
When the system is disturbed, the frequency is nonlinear, so that the inertia and frequency modulation process is discretized, and the specific process is as follows:
in the method, in the process of the invention,active disturbance power for the nth step of the period t; />Active disturbance power is initialized for a period t; n (N) d The total number of the load nodes; d is a load difference adjustment coefficient; Δf t,n Frequency deviation for the nth step of time period t; deltaP g,t,n Power adjustment provided for the nth time step of the g period t of the synchronous machine set; deltaP s,t,n Power adjustment provided for the n-th time step of the energy storage device s-period t; />Is the load d-period t active load.
Wherein E is sys,t,n Reserve rotational kinetic energy for the system of the nth step of time period t; h s,t,n The inertia time constant of the n-th step energy storage device s for the period t.The maximum power of the synchronous unit g; p (P) s max Is the maximum power of the energy storage device s.
Frequency rate of change constraint:
in the formula, roCoF t,n The frequency change rate of the nth step length of the period t; rocofs max Is the maximum value of the frequency change rate;active disturbance power for the nth step of the period t; e (E) sys,t,n Reserve rotational kinetic energy for the system of the nth step of time period t;
frequency deviation constraint:
wherein Deltaf t,n Frequency deviation for the nth step of time period t; delta n is the frequency change rate, and the span time step length is selected; Δf max Is the maximum value of frequency deviation; Δf t,n-1 Frequency deviation for the n-1 th step of period t.
In the step 4, the objective function of the step 2 is constructed as a compact mathematical model as follows:
in the method, in the process of the invention,the starting and stopping cost of the conventional unit in the first stage is minimum; />The worst case unit running cost and the worst frequency modulation cost of the wind turbine generator in the worst scene in the second stage are shown to be minimum; a, b, c are the corresponding vector forms of the cost coefficients of the objective function; y, P g R is the corresponding vector form of the objective function variable; a, a T ，b T ，c T Transpose of a, b, c coefficient vectors, respectively; p (P) g Is the active output vector of the conventional unit.
The constraint of step 3 is constructed as a compact mathematical model as follows:
wherein e is a coefficient matrix corresponding to the start-stop constraint of the unit; f is a coefficient matrix corresponding to the output force of the conventional unit; h is a coefficient matrix corresponding to the spare capacity of the system; g is a constant vector corresponding to the unit start-stop constraint, the conventional unit output constraint and the system reserve capacity constraint; f (F) x Representing a coefficient matrix associated with the x-variable; f (F) z Representing a matrix of coefficients associated with the z-variable. F represents a constant coefficient vector corresponding to x and z.
In the step 4, a column and constraint generation (C & CG) algorithm is adopted to solve through MATLAB software and a CPLEX solver. Thereby obtaining the optimal unit combination and scheduling scheme, comprising the following steps:
stpe1, setting upper and lower bounds: the lower bound is set to LB = - ≡, the upper boundary is set as ub= + infinity; setting an allowable error epsilon and solving times k;
stpe2 solving the main problem: converting the compact mathematical model of the objective function and the constraint condition obtained above into a model capable of solving, as follows;
wherein:representing that the total cost of the objective function is minimum; p (P) l Representing the output vector of the routine unit of the first iteration; r is R l Representing a spare capacity vector of the first iteration system; l represents the number of iterations of the first time; k represents the total number of iterations.
Solving to obtainAnd update the lower bound->Wherein: LB (LB) k-1 Lower bound representing the k-1 th update +.>Representing a y value obtained by solving for the kth time; />The η value obtained by the kth solution is represented.
The state of starting and stopping the machine set and the working state of the energy storage deviceTransmitting to the child problem;
stpe3 solve the sub-problem: solving the main problem to obtain state variablesCarrying out the following model solving:
wherein: [ e f h] T Representation [ e f h ]]Is a transpose of (2); λ represents an auxiliary variable introduced using the dual principle; f (F) x Representing a coefficient matrix associated with the x-variable; f (F) z Representing a coefficient matrix associated with the z-variable; f represents a constant coefficient vector corresponding to x and z.
Solving to obtainAnd update the upper bound->Wherein: UB (UB) k+1 An upper bound representing the number of k+1 iterations; UB (UB) k An upper bound representing the number of k iterations; />Representing a y value obtained by solving the k+1st time; />Representing lambda value obtained by solving for the (k+1) th time; g T Represents the transpose of G.
Solving the sub-problem to obtain the output of the wind turbineTransmitting to the host problem;
stpe4 if UB is present k -LB k And if epsilon is less than or equal to epsilon, jumping out of the loop, outputting a result, wherein epsilon is a given minimum upper and lower bound difference value, otherwise, turning to Stpe2 to continue solving, and if K=k+1.
The invention relates to a wind power output fluctuation optimization scheduling method considering frequency constraint in extreme weather, which has the following technical effects:
1) The frequency safety problem caused by the output fluctuation of the wind turbine generator cannot be considered in the existing scheduling method considering the active disturbance caused by the load side and source side switching machines, so that the scheduling method for the active disturbance generated by the wind turbine generator is provided, the disturbance power caused by the output fluctuation of the wind turbine generator in extreme weather is considered, the frequency-related constraint is not out of limit, and the optimal scheduling result, the conventional unit combination and the conventional unit standby capacity required by primary frequency modulation and the energy storage device standby capacity can be obtained.
2) The method for optimizing and scheduling the wind power output fluctuation by taking frequency constraint into consideration in extreme weather is more accurate.
Drawings
FIG. 1 is a frame diagram of a wind power output fluctuation optimization scheduling model.
Fig. 2 is a solution flowchart of step 4.
FIG. 3 is a wind turbine generator system predictive map.
Fig. 4 is a graph of total load.
Fig. 5 is a schematic diagram of the optimal unit combination of the conventional unit.
FIG. 6 is a wind turbine generator set diagram.
Fig. 7 is a schematic diagram of optimal scheduling of a conventional unit.
Fig. 8 is a diagram of the spare capacity required for the system for each period.
Fig. 9 is a diagram of the spare capacity required for the frequency response provided by the conventional unit and the energy storage machine.
Detailed Description
The invention will be further described with reference to the accompanying drawings and examples.
A wind power output fluctuation optimization scheduling method considering frequency constraint in extreme weather comprises the following steps:
step 1: acquiring element parameters, load data, energy storage system parameters of a power grid and power output data of fluctuation of a wind turbine generator set in a full time period;
step 2: constructing an objective function of wind power output fluctuation optimization scheduling taking frequency constraint into consideration in extreme weather;
step 3: establishing constraint conditions of the objective function in the step 2 to obtain a wind power output fluctuation optimization scheduling model;
step 4: the optimized scheduling model of the step 3 is converted into a compact mathematical model, and a column and constraint generation (Column and Constraint generation, C & CG) algorithm is adopted for solving through a solver.
In the step 1, the element parameters of the power grid include impedance, line transmission capacity and node number, as shown in table 1;
the load data comprises predicted values in the scheduling period of each load node, as shown in table 2;
the energy storage system parameters include charge and discharge efficiency, maximum charge and discharge power, and energy storage device capacity, as shown in table 3;
the wind turbine generator system in the full period predicts the force output data as shown in table 4.
Examples:
an improved IEEE 9 node system is taken as an example, and 5 conventional units are added, a 250MW wind turbine is added to a node 1, and a 100MW energy storage device is added to a node 7. The invention adopts the data of a 24-period test system of 5 conventional units purchased by a certain power grid company, the data of each unit is obtained by arrangement, the parameters of the conventional units are shown in a table 5, and in the embodiment, the extreme weather types mainly refer to: strong winds, typhoons, and hurricanes.
Table 1 grid element parameters
Node numbering Inflow node Outflow node Resistor (p.u.) Reactance (p.u.)
1 1 4 0 0.0576
2 4 5 0.017 0.092
3 5 6 0.039 0.17
4 3 6 0 0.0586
5 6 7 0.0119 0.1008
6 7 8 0.0085 0.072
7 8 2 0 0.0625
8 8 9 0.032 0.161
9 9 4 0.01 0.085
TABLE 2 prediction parameters of total load (Unit: MW)
Time period of 1 2 3 4 5 6 7 8 9 10 11 12
Load of 587.2 538.4 507.0 487.1 448.4 448.5 457.7 474.2 477.9 508.9 527.2 540.1
Time period of 13 14 15 16 17 18 19 20 21 22 23 24
Load of 551.1 558.4 569.4 585.9 596.9 607.9 606.2 609.9 630.0 619.1 604.1 590.5
TABLE 3 energy storage system parameters
Table 4 wind turbine generator system predicted output parameters (unit: MW)
Table 5 conventional unit parameters
The predicted force of the wind turbine generator is shown in fig. 3, and the load of each period is shown in fig. 4.
From the simulation results, the load is smaller at time period 3-7. And therefore unit No. 5 is in a shutdown state as shown in fig. 5. In fig. 6, the "worst output" curve of the wind turbine represents the output condition of the wind turbine in the extreme condition, and it can be seen from fig. 6 that the output is mainly concentrated at 13-15 and 20-24 hours in the extreme condition of the wind turbine, in order to meet the system frequency safety, the conventional wind turbine and the energy storage machine of the system provide the spare capacity required by the frequency response in the period that the output of the wind turbine deviates from the predicted result, as shown in fig. 9. As can be seen from fig. 9, at 13-15, the conventional unit output is less required due to the relatively smaller load, and the conventional unit can provide more spare capacity at this time; and at 20-24 hours, the load is in the peak period and more conventional unit output is needed, so the period is mainly reserved by the energy storage device.
Fig. 7 is a conventional crew optimal scheduling scheme. It can be seen from fig. 7 that the conventional unit 1 is basically in full load operation except for 12 hours, the conventional unit 2, the conventional unit 4 and the conventional unit 5 have larger output at the load peak 15-24 hours, and the conventional unit 2, the conventional unit 4 and the conventional unit 5 have smaller output due to the load at the valley period 4-10 hours. The conventional unit 3 has smaller output at the time of load peak, and is mainly in a standby state for dealing with disturbance power.

Claims (7)

1. The wind power output fluctuation optimization scheduling method considering frequency constraint is characterized by comprising the following steps of:
step 1: acquiring element parameters, load data, energy storage system parameters of a power grid and power output data of fluctuation of a wind turbine generator set in a full time period;
step 2: constructing an objective function of wind power output fluctuation optimization scheduling in consideration of frequency constraint;
step 3: establishing constraint conditions of the objective function in the step 2 to obtain a wind power output fluctuation optimization scheduling model;
step 4: the optimized scheduling model of the step 3 is converted into a compact mathematical model, and a column and constraint generation (Column and Constraint generation, C & CG) algorithm is adopted for solving through a solver.
2. The optimal scheduling method for wind power output fluctuation taking frequency constraint into consideration according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the step 1, the element parameters of the power grid comprise impedance, line transmission capacity and node numbers;
the load data includes predicted values within each load node scheduling period.
The energy storage system parameters include charge and discharge efficiency, maximum charge and discharge power, maximum and minimum state of charge, and energy storage device capacity.
3. The optimal scheduling method for wind power output fluctuation taking frequency constraint into consideration according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the step 2, the objective function is that the comprehensive cost is minimum in the worst case of wind power output in the worst weather scene, and the comprehensive cost comprises the running cost, the start-stop cost and the frequency modulation cost of a conventional unit in a scheduling period;
in the method, in the process of the invention,the start-stop cost of the first-stage unit is minimum; u and v are binary variables of the energy storage device and the conventional unit combination respectively; />In the worst case of the output of the wind turbine generator in the worst weather, the output cost of the conventional wind turbine generator and the frequency modulation spare capacity cost R are minimum; t is the total scheduling period; n (N) g The total number of the conventional units; a, b and c are cost coefficients of the output of the conventional unit; p (P) i,t The output of the conventional unit i is the period t; v i,t The operation state of the conventional unit i in the period t; s is(s) i,t The starting state of the conventional unit i in the period t; r is (r) i,t The shutdown state of the conventional unit i in the period t; />Starting up cost of a conventional unit i for a period t; />The shutdown cost of the conventional unit i is set for a period t; i is the ith conventional unit; t is the t-th period; p (P) g The output of the conventional unit is provided; x is a state variable of the output taking-down boundary of the wind turbine generator; z is the output power of the wind turbine generator set and takes the upper bound state variable;
r is the total spare capacity cost required during system frequency modulation, and the expression is as follows:
wherein e and f are standby capacity cost coefficients of the conventional unit and the energy storage device respectively; r is R i,t The standby capacity of the conventional unit i in a period t; r is R s,t Standby capacity for the energy storage device s period t; n (N) s The total number of the energy storage devices; t is the total scheduling period; s is the s-th energy storage device.
4. The optimal scheduling method for wind power output fluctuation considering frequency constraint according to claim 3, wherein the method comprises the following steps of: in the step 3, each constraint condition is as follows:
1) Conventional unit output constraint:
in the method, in the process of the invention,maximum technical output of the conventional unit g, < ->The minimum technical output of the conventional unit g; p (P) g,t The output of the conventional unit in the period of g is output; r is R g,t The standby capacity of the conventional unit in the period g is the standby capacity of the conventional unit in the period t; v g,t The running state variable is the running state variable of the conventional unit in the period g;
2) Unit combination constraint:
in the formula, v g,t The running state variable is the running state variable of the conventional unit in the period g; v g,t-1 The operation state variable is the operation state variable of the conventional unit in the period t-1; r is (r) g,t The starting state variable is the starting state variable of the conventional unit g period t; s is(s) g,t For the shutdown state variable of the conventional unit g period tFor the period g of the conventional unit->Is a running state variable of (1);
representing arbitrary +.>Belonging to [ t+1, min (t+T) off -1,T)]；T on The minimum starting time of the conventional unit is set; t (T) off Minimum downtime for a conventional unit; min (t+T) on -1, T) represents t+T on -a minimum value is taken between 1 and T; min (t+T) off -1, T) represents t+T off -a minimum value is taken between 1 and T;
3) Energy storage device restraint:
in the method, in the process of the invention,discharging power of the energy storage device s for a period t; />For a period t the maximum of the energy storage means sDischarge power; u (u) s,t The charge and discharge states of the energy storage device s are the period t; />Charging power for the energy storage device s for a period t; />Maximum charging power for the energy storage device s; />The state of charge of the energy storage device s for a period t; η (eta) ch Charging efficiency of the energy storage device; η (eta) dis Is the discharge efficiency of the energy storage device; />Is the rated capacity of the energy storage device s; />A minimum state of charge for the energy storage device s; />The maximum state of charge of the energy storage device s; />State of charge for time period t+1 energy storage device s; />Charging power for the energy storage device s for a period t+1; />Discharging power of the energy storage device s for a period t+1;
4) Power balance constraint:
wherein:is a set of all nodes connected to node n; />Predicted output of the wind turbine generator set in the j period t; />The required power for the load d period t; n (N) w The total number of the wind turbine generators is the total number of the wind turbine generators; n (N) load Is the total number of loads;
5) Node voltage phase angle constraint:
in the method, in the process of the invention,the minimum node voltage phase angle for node i; />The maximum node voltage phase angle of the node i; θ i,t A voltage phase angle of a node i period t; θ ref,t A voltage phase angle of a reference node ref period t;
6) Line capacity constraint:
in the method, in the process of the invention,for maximum transmission capacity of line ij, B ij Susceptance for line ij; θ i,t A node voltage phase angle of the node i period t; θ j,t A node voltage phase angle of a node j period t;
7) Output constraint of the wind turbine generator system:
wherein DeltaP w,t The deviation power of the period t of the wind turbine generator w caused by bad weather; p (P) w,t The actual output of the wind turbine generator set in the w period t is obtained;predicted output of the wind turbine set in w time period t; x is x w,t The output of the wind turbine generator set w time period t is taken as an upper bound; z w,t Representing the output taking-off boundary of the wind turbine generator set in the w period t;
8) Frequency constraint:
at the moment of frequency change of active disturbance, the system has a frequency dead zone, and in the period, the system cannot perform primary frequency modulation, the moment of change is supported by the inertia support power of the system, the inertia support power of the system comprises the inertia support power of a conventional unit and an energy storage device, and the inertia support power of the system is represented by the following formula:
conventional unit inertia support power:
in the method, in the process of the invention,the inertia support power provided for the period t conventional unit g; h g The inertia time constant of the conventional unit g; Δf (t) is the frequency deviation of period t; />Frequency change rate for period t; f (f) 0 Is the working frequency of the system; />The maximum technical output provided for the conventional unit g;
energy storage device inertia support power:
wherein H is s,t An equivalent inertial time constant for the period t of the energy storage device s; p (P) s,t The residual electric quantity of the energy storage device s in a period t;is the rated capacity of the energy storage device s; s is S B Is the reference power of the system; />Is the maximum charge-discharge multiplying power of the energy storage device s;supporting power for inertia of the energy storage device for a period t;
when the frequency dead time is reached, the conventional unit and the energy storage device perform primary frequency modulation:
conventional unit frequency support power:
in the method, in the process of the invention,providing primary frequency modulation support power for a conventional unit g period t; delta g The difference adjustment coefficient is the difference adjustment coefficient of the conventional unit g; Δf t Frequency deviation resulting from power disturbance for period t;
energy storage device frequency support power:
in the method, in the process of the invention,for storing energyThe s-setting period t provides primary frequency modulation supporting power; delta s The difference adjustment coefficient of the conventional unit s;
when the system is disturbed, the frequency is nonlinear, so that the inertia and frequency modulation process is discretized, and the specific process is as follows:
in the method, in the process of the invention,active disturbance power for the nth step of the period t; />Active disturbance power is initialized for a period t; n (N) d The total number of the load nodes; d is a load difference adjustment coefficient; Δf t,n Frequency deviation for the nth step of time period t; deltaP g,t,n Power adjustment provided for the nth time step of the g period t of the synchronous machine set; deltaP s,t,n Power adjustment provided for the n-th time step of the energy storage device s-period t; />Active load for load d period t;
wherein E is sys,t,n Reserve rotational kinetic energy for the system of the nth step of time period t; h s,t,n The inertia time constant of the energy storage device s in the nth step of the period t;the maximum power of the synchronous unit g; />Maximum power for the energy storage device s;
frequency rate of change constraint:
in the formula, roCoF t,n The frequency change rate of the nth step length of the period t; rocofs max Is the maximum value of the frequency change rate;active disturbance power for the nth step of the period t; e (E) sys,t,n Reserve rotational kinetic energy for the system of the nth step of time period t;
frequency deviation constraint:
wherein Deltaf t,n Frequency deviation for the nth step of time period t; delta n is the frequency change rate, and the span time step length is selected; Δf max Is the maximum value of frequency deviation; Δf t,n-1 Frequency deviation for the n-1 th step of period t.
5. The optimal scheduling method for wind power output fluctuation taking frequency constraint into consideration according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the step 4, the objective function of the step 2 is constructed as a compact mathematical model as follows:
in the method, in the process of the invention,the starting and stopping cost of the conventional unit in the first stage is minimum; />Representing worst case unit running cost and adjustment of wind turbine generator in worst scene in second stageThe frequency cost is minimum; a, b, c are the corresponding vector forms of the cost coefficients of the objective function; y, P g R is the corresponding vector form of the objective function variable; a, a T ，b T ，c T Transpose of a, b, c coefficient vectors, respectively; p (P) g Is the active output vector of the conventional unit.
6. The optimal scheduling method for wind power output fluctuation considering frequency constraint according to claim 4, wherein the optimal scheduling method is characterized by comprising the following steps of: the constraint of step 3 is constructed as a compact mathematical model as follows:
wherein e is a coefficient matrix corresponding to the start-stop constraint of the unit; f is a coefficient matrix corresponding to the output force of the conventional unit; h is a coefficient matrix corresponding to the spare capacity of the system; g is a constant vector corresponding to the unit start-stop constraint, the conventional unit output constraint and the system reserve capacity constraint; f (F) x Representing a coefficient matrix associated with the x-variable; f (F) z Representing a coefficient matrix associated with the z-variable; f represents a constant coefficient vector corresponding to x and z.
7. The optimal scheduling method for wind power output fluctuation taking frequency constraint into consideration according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the step 4, a column and constraint generation (C & CG) algorithm is adopted to solve through MATLAB software and a CPLEX solver, so as to obtain an optimal unit combination and scheduling scheme, which comprises the following steps:
stpe1, setting upper and lower bounds: the lower bound is set to LB = - ≡, the upper boundary is set as ub= + infinity; setting an allowable error epsilon and solving times k;
stpe2 solving the main problem: converting the compact mathematical model of the objective function and the constraint condition obtained above into a model capable of solving, as follows;
wherein:representing that the total cost of the objective function is minimum; p (P) l Representing the output vector of the routine unit of the first iteration; r is R l Representing a spare capacity vector of the first iteration system; l represents the number of iterations of the first time; k represents the total number of iterations;
solving to obtainAnd update the lower bound->Wherein: LB (LB) k-1 Lower bound representing the k-1 th update +.>Representing a y value obtained by solving for the kth time; />Representing the eta value obtained by the kth solving;
the state of starting and stopping the machine set and the working state of the energy storage deviceTransmitting to the child problem;
stpe3 solve the sub-problem: solving the main problem to obtain state variablesCarrying out the following model solving:
wherein: [ e f h] T Representation [ e f h ]]Is a transpose of (2); λ represents an auxiliary variable introduced using the dual principle; f (F) x Representing a coefficient matrix associated with the x-variable; f (F) z Representing a coefficient matrix associated with the z-variable; f represents a constant coefficient vector corresponding to x and z;
solving to obtainAnd update the upper bound->Wherein: UB (UB) k+1 An upper bound representing the number of k+1 iterations; UB (UB) k An upper bound representing the number of k iterations; />Representing a y value obtained by solving the k+1st time; />Representing lambda value obtained by solving for the (k+1) th time; g T Represents the transpose of G;
solving the sub-problem to obtain the output of the wind turbineTransmitting to the host problem;
stpe4 if UB is present k -LB k And if epsilon is less than or equal to epsilon, jumping out of the loop, outputting a result, wherein epsilon is a given minimum upper and lower bound difference value, otherwise, turning to Stpe2 to continue solving, and if K=k+1.
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