Coordinated planning method and system for power transmission network expansion and thermal power generating unit transformation

Abstract

The invention discloses a coordinated planning method and system for power transmission network expansion and thermal power generating unit transformation, and the method comprises the steps: building a power transmission network expansion and thermal power generating unit transformation coordinated planning model with the minimum total cost as an optimization target; creating a constraint condition corresponding to an input variable of the transmission network expansion and thermal power generating unit transformation collaborative planning model and a mixed fuzzy set used for representing the power output and load prediction uncertainty, introducing the mixed fuzzy set into the transmission network expansion and thermal power generating unit transformation collaborative planning model to obtain a final model, obtaining the input variable, and calculating the output power and load prediction uncertainty. According to the power transmission network expansion and thermal power generating unit transformation collaborative planning method, the power transmission network expansion and thermal power generating unit transformation collaborative planning model is established, various condition constraints and uncertainty are introduced, the model is more accurate, and the resistance of the system to large disturbance faults is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore wind power clustering, and in particular to a coordinated planning method and system for transmission network expansion and thermal power unit transformation. Background Art

[0002] The cluster development of offshore wind power faces several challenges: first, it is necessary to improve the transmission capacity of the external transmission grid under the condition of limited land resources in coastal areas; second, the continuous increase in the penetration rate of new energy will lead to increasingly severe peak-shaving situations in the power grid; third, the retirement of coal-fired power units will further highlight the problems of the power grid's dynamic reactive power support capacity and insufficient rotational inertia.

[0003] In this regard, most existing studies are based on the flexibility transformation of a single thermal power unit or the expansion of the transmission network, studying how to control costs and improve the ability to absorb new energy. In terms of the flexibility transformation planning of thermal power plants, the existing scheme studies a mixed integer nonlinear model that takes into account the investment decision of the flexibility transformation of thermal power units and the long-term dispatch decision of the power system to improve wind power absorption, but the model only considers the base state operation constraints and the margin constraints, and lacks constraints on the fault state of the power system. In terms of the coordinated planning of transmission network expansion and flexibility, the existing scheme is a multi-stage joint decision-making method for the transformation of thermal power units and transmission network planning that coordinates system flexibility and transmission capacity, and considers the safe operation constraints under the N-1 fault state, but does not consider the system voltage and frequency stability problems caused by DC locking faults.

[0004] However, studying the new energy absorption capacity from only a single perspective cannot completely and comprehensively control costs and improve the system's wind power absorption capacity; and due to the interference of many fault factors, the wind power cluster system's ability to resist large disturbance faults cannot be guaranteed. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a coordinated planning method and system for transmission network expansion and thermal power unit transformation, which can completely and comprehensively control costs and improve the system's wind power absorption capacity, while ensuring the system's ability to resist large disturbance faults.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] The coordinated planning method for transmission network expansion and thermal power unit transformation includes the following steps:

[0008] S1. Taking the minimum total cost as the optimization goal, a coordinated planning model for transmission network expansion and thermal power unit transformation is established, and its expression is as follows:

[0009] Min:C IN +C MA +C OP +CPB ;

[0010] Among them, C IN represents the total investment cost of transmission network expansion and thermal power unit transformation, C MA represents the equipment maintenance cost, C OP represents the operating cost, C PB represents the penalty cost for wind curtailment;

[0011] S2. Create constraints corresponding to the input variables of the transmission network expansion and thermal power unit transformation collaborative planning model, wherein the constraints include investment and construction logic relationship and phased investment cost constraints, base state operation constraints, peak load regulation constraints, blocking fault safety constraints, and transient voltage stabilization constraints;

[0012] S3, creating a mixed fuzzy set for characterizing the uncertainty of power output and load forecasting, and introducing the mixed fuzzy set into the transmission network expansion and thermal power unit transformation collaborative planning model to obtain a final model;

[0013] S4. Obtain input variables, and solve the final model in combination with the constraint conditions to obtain the results of the coordinated planning of transmission network expansion and thermal power unit transformation.

[0014] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0015] A coordinated planning system for transmission network expansion and thermal power unit transformation includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the coordinated planning method for transmission network expansion and thermal power unit transformation is implemented.

[0016] The beneficial effects of the present invention are: providing a coordinated planning method and system for transmission network expansion and thermal power unit transformation, taking the minimum total cost as the optimization goal, establishing a coordinated planning model for transmission network expansion and thermal power unit transformation, and considering the flexibility transformation of transmission network expansion and in-service thermal power units at the same time, achieving more comprehensive and complete cost control and improving the system's wind power absorption capacity, introducing investment and construction logic relationships and phased investment cost constraints, base state operation constraints, peak-shaving constraints, locked fault safety constraints and transient voltage stabilization constraints, strengthening the system's ability to resist large disturbance faults, considering the uncertainty of power output and load forecasting, making the model more accurate, and coordinating the transmission capacity, peak-shaving capacity and anti-disturbance capability of the wind power cluster system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of the steps of the coordinated planning method for transmission network expansion and thermal power unit transformation of the present invention;

[0018] Figure 2A layout diagram of an IEEE-39 node test system for application of the coordinated planning method for transmission network expansion and thermal power unit transformation of the present invention;

[0019] Figure 3 A line graph showing the application of the coordinated planning method for transmission network expansion and thermal power unit transformation of the present invention to wind power consumption in a small load scenario;

[0020] Figure 4 It is a comparison diagram of transient overvoltage results after a DC line locking fault between Model 5 to which the transmission network expansion and thermal power unit transformation method of the present invention is applied and Model 2 to which the method is not applied.

[0021] Figure 5 The system block diagram of the coordinated planning system for transmission network expansion and thermal power unit transformation of the present invention.

[0022] Description of labels:

[0023] 1. Coordinated planning system for transmission network expansion and thermal power unit transformation; 2. Memory; 3. Processor. DETAILED DESCRIPTION

[0024] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0025] Please refer to Figures 1 to 4 , a coordinated planning method for transmission network expansion and thermal power unit transformation includes the following steps:

[0026] S1. Taking the minimum total cost as the optimization goal, a coordinated planning model for transmission network expansion and thermal power unit transformation is established, and its expression is as follows:

[0027] Min:C IN +C MA +C OP +C PB ;

[0028] Among them, C IN represents the total investment cost of transmission network expansion and thermal power unit transformation, C MA represents the equipment maintenance cost, C OP represents the operating cost, C PB represents the penalty cost for wind curtailment;

[0029] S2. Create constraints corresponding to the input variables of the transmission network expansion and thermal power unit transformation collaborative planning model, wherein the constraints include investment and construction logic relationship and phased investment cost constraints, base state operation constraints, peak load regulation constraints, blocking fault safety constraints, and transient voltage stabilization constraints;

[0030] S3, creating a mixed fuzzy set for characterizing the uncertainty of power output and load forecasting, and introducing the mixed fuzzy set into the transmission network expansion and thermal power unit transformation collaborative planning model to obtain a final model;

[0031] S4. Obtain input variables, and solve the final model in combination with the constraint conditions to obtain the results of the coordinated planning of transmission network expansion and thermal power unit transformation.

[0032] From the above description, it can be seen that the beneficial effects of the present invention are: taking the minimum total cost as the optimization goal, establishing a coordinated planning model for transmission network expansion and thermal power unit transformation, while considering the flexibility transformation of transmission network expansion and in-service thermal power units, achieving more comprehensive and complete cost control and improving the system's wind power absorption capacity, introducing investment and construction logic relationships and phased investment cost constraints, base state operation constraints, peak-shaving constraints, locked fault safety constraints and transient voltage stabilization constraints, strengthening the system's ability to resist large disturbance faults, considering the uncertainty of power output and load forecasting, making the model more accurate, and coordinating the transmission capacity, peak-shaving capacity and anti-disturbance capability of the wind power cluster system.

[0033] Furthermore, the total investment cost of the transmission network expansion and thermal power unit transformation is expressed as:

[0034]

[0035] Among them, Ω y , Ω g , They are the planning stage set, the set of retired thermal power units in stage y, the set of in-service thermal power units, and the set of lines to be built in stage y (i, j). are the investment cost of the lines to be built, the investment cost of the unit capacity transformation of thermal power units, and the investment cost of the unit capacity transformation of the phase-shifting function of retired units, respectively. l , are the capital recovery coefficients for line, flexibility and phase shifter function transformation, respectively, Y is the equipment life; z y,ij,k , are 0-1 variables, indicating whether the line k is put into construction in the yth stage, whether the thermal power unit i is transformed into flexibility, and whether the retired unit i is transformed into a phase-shifting function. 0 means no, 1 means yes, They are the maximum output of the thermal power unit and the minimum output before flexibility transformation. The minimum output after flexibility modification, represents the set of lines to be put into operation in stage y (i, j);

[0036] and:

[0037]

[0038] Where r represents the discount rate;

[0039] The expression of equipment maintenance cost is:

[0040]

[0041] Among them, Ω l represents the set of transmission lines, Indicates the corresponding equipment maintenance cost;

[0042] The expression of equipment maintenance cost is:

[0043]

[0044] Among them, Ω s Indicates the running scene collection. are the fuel cost coefficient and standby cost coefficient of thermal power units, respectively. T represents the operating period. They are respectively the active output, up-ramp reserve and down-ramp reserve of thermal power unit i in the yth stage s scenario t period;

[0045] The expression of the wind curtailment penalty cost is:

[0046]

[0047] Among them, Ω w represents the set of wind turbines, represents the unit penalty cost of wind curtailment, It represents the wind curtailment in the yth stage under the sth scenario and the tth period.

[0048] Furthermore, the expression of the investment and construction logic relationship and the phased investment cost constraint is:

[0049] z y,ij,k ≥z y-1,ij,k ;

[0050]

[0051] Among them, z y-1,ij,k Indicates whether the line k in the previous stage of stage y is put into construction, K y,ij Indicates the set of lines that have been put into operation. They represent the minimum and maximum values ​​of the lines allowed to be constructed in the line corridor (i, j) in the yth stage, Represents the maximum investment limit allowed in stage y.

[0052] From the above description, it can be seen that the investment and construction logic relationship and the phased investment cost constraints include two parts: investment and construction logic relationship constraints and phased investment cost constraints, which strictly control costs through investment restrictions.

[0053] Furthermore, the base state operation constraints include unit output constraints, UHV DC line operation modeling constraints, AC power flow safety constraints, and output characteristic modeling constraints of thermal power units after transformation.

[0054] From the above description, it can be seen that the operating constraints of the system in the base state include four items: unit output constraints, UHV DC line operation modeling constraints, AC power flow safety constraints, and output characteristic modeling constraints after thermal power unit transformation, so as to ensure its operation safety in the UHV transmission scenario.

[0055] Furthermore, it is characterized in that the AC power flow safety constraints include system active and reactive power balance constraints, node voltage amplitude constraints and line apparent power transfer limit constraints.

[0056] Furthermore, the output characteristic modeling constraints after the transformation of the thermal power units include active output constraints, climbing constraints and reactive output limitations after the flexibility transformation of the in-service thermal power units.

[0057] From the above description, it can be seen that the output characteristics of the modified thermal power units are constrained from three aspects: active output constraint, climbing constraint and reactive output, to ensure that their operation is sufficiently safe and stable.

[0058] Furthermore, the peak load constraint is expressed as follows:

[0059]

[0060] in, are the maximum and minimum transmission active power of the UHV DC line; PCP y,s,t 、TCP y,s,t They represent the peak capacity pressure and valley capacity pressure of the system in the yth stage, sth scenario, and tth period, respectively. represents the active load of the node, represents the active power of the UHV DC line, are the corresponding minimum thresholds respectively.

[0061] From the above description, it can be seen that as the scale of offshore wind power clusters increases, the peak-shaving pressure of the sending-end power grid is increasing, which directly affects the problem of power supply. Therefore, peak capacity pressure and valley capacity pressure are introduced into the peak-shaving constraints to dynamically characterize the peak-shaving effect of the system.

[0062] Furthermore, the creation of a mixed fuzzy set for characterizing the uncertainty of power output and load forecasting includes:

[0063] The empirical distribution is obtained based on the historical data of wind power output and load.

[0064]

[0065] Among them, N represents the amount of historical sample data, ζ n is the historical data of wind power output and load, δ (·) represents the Dirac measure;

[0066] According to the wind power output and load forecast error, the Wassertein distance is defined to characterize the distance between the empirical distribution and the true distribution.

[0067]

[0068] Among them, Ψ(·) represents the joint probability distribution between the empirical distribution and the true distribution;

[0069] The fuzzy set Θ based on Wassertein distance W The definition is as follows:

[0070]

[0071] Constructing fuzzy set Θ based on first-order moment information M :

[0072] Θ M = {P∈P ζ (Ω ζ )|μ - ≤E P (ζ-μ)≤μ +};

[0073] Among them, E p (·) represents the expected operator, μ represents the mean of historical wind power output and historical load, and μ - , μ + represents the expected variance;

[0074] Create a fuzzy set Θ that satisfies W and θ M The probability distribution of the mixed fuzzy set:

[0075]

[0076] From the above description, it can be seen that when creating a hybrid fuzzy set, the first-order moment information is introduced to construct the fuzzy set, which can accurately characterize the correlation between the true distribution and the empirical distribution of wind power output and load forecast errors, and then combine it with the fuzzy set based on Wassertein distance to characterize the uncertainty of wind power output and load forecasting and improve the accuracy of the model.

[0077] Furthermore, the step S4 comprises:

[0078] According to Slater's rule, the final model is reformulated as a two-stage mixed integer linear model with an equivalent minimization problem:

[0079]

[0080] st

[0081]

[0082] ||γ|| * ≤λ;

[0083] Ex+l T ζ-q+v T ζ≤Ny;

[0084] Among them, θ s , π + , π - , λ represents the dual variable, represents the wind power output and load in the nth scenario, γ is the introduced auxiliary variable, ||·|| * represents the second-order norm;

[0085] The two-stage mixed integer linear model is decomposed into a main problem MP and a sub-problem SP to facilitate solution:

[0086] MP:

[0087]

[0088] stAx+b≤0;

[0089] ||γ|| * ≤λ;

[0090]

[0091] Ex+l T ζ m -q+v T ζ≤Ny m ;

[0092] SP:

[0093]

[0094] s T T α=d.

[0095] From the above description, it can be seen that the final model is reconstructed into a two-stage mixed integer linear model of an equivalent minimization problem according to Slater's rule, which is easier to handle and reduces the calculation pressure.

[0096] Please refer to Figure 5A coordinated planning system 1 for transmission network expansion and thermal power unit transformation includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, the coordinated planning method for transmission network expansion and thermal power unit transformation is implemented.

[0097] Please refer to Figures 1 to 4 , Embodiment 1 of the present invention is:

[0098] The coordinated planning method for transmission network expansion and thermal power unit transformation includes the following steps:

[0099] S1. Taking the minimum total cost as the optimization goal, a coordinated planning model for transmission network expansion and thermal power unit transformation is established, and its expression is as follows:

[0100] Min:C IN +C MA +C OP +C PB (1)

[0101] Among them, C IN represents the total investment cost of transmission network expansion and thermal power unit transformation, C MA represents the equipment maintenance cost, C OP represents the operating cost, C PB represents the penalty cost for wind curtailment;

[0102] In this embodiment, the total investment cost of the transmission network expansion and thermal power unit transformation is expressed as:

[0103]

[0104] Among them, Ω y , Ω g , They are the planning stage set, the set of retired thermal power units in stage y, the set of in-service thermal power units, and the set of lines to be built in stage y (i, j). are the investment cost of the lines to be built, the investment cost of the unit capacity transformation of thermal power units, and the investment cost of the unit capacity transformation of the phase-shifting function of retired units, respectively. l , are the capital recovery coefficients for line, flexibility and phase shifter function transformation, respectively, Y is the equipment life; z y,ij,k , are 0-1 variables, indicating whether the line k is put into construction in the yth stage, whether the thermal power unit i is transformed into flexibility, and whether the retired unit i is transformed into a phase-shifting function. 0 means no, 1 means yes, They are the maximum output of the thermal power unit and the minimum output before flexibility transformation. The minimum output after flexibility modification, represents the set of lines to be put into operation in stage y (i, j);

[0105] and:

[0106]

[0107] Where r represents the discount rate;

[0108] The expression of equipment maintenance cost is:

[0109]

[0110] Among them, Ω l represents the set of transmission lines, Indicates the corresponding equipment maintenance cost;

[0111] The expression of equipment maintenance cost is:

[0112]

[0113] Among them, Ω s Indicates the running scene collection. are the fuel cost coefficient and standby cost coefficient of thermal power units, respectively. T represents the operating period. They are respectively the active output, up-ramp reserve and down-ramp reserve of thermal power unit i in the yth stage s scenario t period;

[0114] The expression of wind curtailment penalty cost is:

[0115]

[0116] Abandoned wind volume in stage s scenario and time period t.

[0117] S2. Create constraints for the input variables of the coordinated planning model for transmission network expansion and thermal power unit transformation. The constraints include investment and construction logic relationship and phased investment cost constraints, base state operation constraints, peak load regulation constraints, blocking fault safety constraints, and transient voltage stabilization constraints;

[0118] In this embodiment, the constraint conditions are used as the limiting conditions of the input variables used for solving the model. Each constraint condition is described as follows:

[0119] 1. Investment and construction logic relationship and phased investment cost constraints

[0120] The investment decision of transmission network expansion and thermal power unit transformation is subject to the constraints of investment and construction logic and staged investment cost constraints, which can be expressed as shown in equations (7)-(11):

[0121] z y,ij,k ≥zy-1,ij,k (7)

[0122]

[0123]

[0124] Among them, z y-1,ij,k Indicates whether the line k in the previous stage of stage y is put into construction, K y,ij Indicates the set of lines that have been put into operation. They represent the minimum and maximum values ​​of the lines allowed to be constructed in the line corridor (i, j) in the yth stage, It represents the maximum investment limit allowed in the yth stage. Formulas (7)-(9) are the logical relationship constraints of line investment and construction; Formula (10) is the logical relationship constraint of the flexibility transformation of in-service thermal power units and the phase-shifting function transformation of retired thermal power units; Formula (11) is the stage investment constraint.

[0125] 2. Base State Operation Constraints

[0126] The operating constraints of the system in the base state include the following four items: (1) unit output constraints; (2) UHV DC line operation modeling; (3) AC power flow safety constraints; and (4) output characteristic modeling of thermal power units after transformation.

[0127] Among them, the first two constraints are common in existing research literature, so they are not repeated here. The last two constraints are shown in (12)-(19):

[0128]

[0129] In the formula, Represents the reactive power output of thermal power units; V y,s,t,i Indicates the node voltage amplitude; They are respectively the active output and reactive output of the controllable wind farm; They represent the active power and reactive power of the UHV DC line respectively; Respectively represent the active load and reactive load of the node; Respectively represent the active and reactive power, reactive power and maximum apparent power of the line; G ij ,B ij represents the conductance and susceptance of branch (i, j); They are the maximum landslide power and climbing power per unit time before the flexibility transformation of the in-service thermal power unit i; They represent the maximum landslide power and climbing power per unit time of the in-service thermal power unit i without oil-operated peak-shaving transformation and after oil-operated peak-shaving transformation respectively; They represent the minimum and maximum reactive power output limits of phase-converter units after functional transformation of retired thermal power units; V max 、V minare the upper and lower limits of the node amplitude, respectively. It represents the minimum output of in-service thermal power units before flexibility transformation, non-oil peak-shaving transformation and after oil peak-shaving transformation.

[0130] Among them, equations (12) and (13) are the linear expressions of the active and reactive power balance of the system, as the independent variable

[12] ; Formula (14) is the node voltage amplitude constraint; Formula (15) is the apparent power transmission limit constraint of the line; Formulas (16)-(18) respectively represent the active output constraint and ramp constraint of the in-service thermal power units after the flexibility transformation. Formula (19) is the reactive output limit of the retired thermal power units after the phase-shifting function transformation.

[0131] 3. Peak Loading Constraints

[0132] This embodiment introduces two indicators, Peak Capacity Pressure (PCP) and Trough Capacity Pressure (PCP), to dynamically characterize the peak-shaving effect of the system. The existing UHV DC control technology and equipment technology level meet the requirements of fast action. Therefore, this paper considers UHV DC participating in system peak-shaving, and the peak-shaving constraints are as follows:

[0133]

[0134] in, are the maximum and minimum transmission active power of the UHV DC line; PCP y,s,t 、TCP y,s,t They represent the peak capacity pressure and valley capacity pressure of the system in the yth stage, sth scenario, and tth period, respectively. represents the active load of the node, represents the active power of the UHV DC line, are the corresponding minimum thresholds respectively.

[0135] 4. Lockout Fail-Safe Constraints

[0136] When a bipolar locking fault occurs in an ultra-high voltage DC line, the DC active power drops to zero instantly, and the absorbed reactive power also drops rapidly. On the one hand, the remaining reactive power of the converter station is fed back to the AC system, which may cause transient overvoltage problems in the DC near area, thereby affecting equipment safety and even causing cascading failures of the system; on the other hand, the huge active power imbalance may cause high-frequency collapse of the sending-end power grid, triggering the system's third line of defense - high-frequency cutting. Therefore, the present invention considers relevant constraints in the model to ensure that the system can cope with such serious emergencies and ensure the safe and stable operation of the system.

[0137] Assuming that a bipolar blocking fault occurs in the kth DC line, the unbalanced power of the sending-end system at the moment of the fault is for:

[0138]

[0139] After a bipolar blocking fault occurs, the protection and control system usually takes action after a delay of 200ms to disconnect all AC filters in the converter station. This is also the root cause of transient overvoltages in the DC near-AC busbars after a bipolar blocking fault. As the system strength weakens, the transient voltage increases, and there is a negative correlation between the blocking capacity and the equivalent potential under transient overvoltage. For this reason, the reactive power sent back to the AC system after the fault It can be expressed as:

[0140]

[0141] Where U e is the equivalent voltage amplitude of the power grid at the sending end; it represents the upper limit of the voltage allowed by the commutation bus; N d MISCR is the ratio of DC operating power to rated power; y,i and MIIF k,i represent the multi-infeed short-circuit ratio and DC interaction factor respectively.

[0142] On the one hand, in order to ensure that the transient overvoltage of the system after DC blocking remains within a reasonable level, the synchronous generators and synchronous phase condensers in the AC system should be able to fully absorb the reactive power sent back to the AC system due to the fault:

[0143]

[0144] Where M TF It represents the transfer factor of reactive resources between the DC landing point and the generator node (including the completion of the functional transformation of the phase-converter of retired units), reflecting the voltage support capability of reactive sources for UHV DC lines.

[0145] On the other hand, in order to ensure the frequency safety and stability of the system after the fault, it is considered to reduce the unbalanced power of the system by cutting off the power support of wind power and non-fault DC to prevent triggering the third line of defense of the system. Its constraints are as follows (25)-(31):

[0146]

[0147] In the formula, Ω hk represents the set of non-fault DC lines; ΔP W,max is the maximum wind power curtailment amount; ρ is the short-time overload factor of the DC line, which is 1.2; They represent the power modulation amount of the non-fault DC and the maximum transmission power of the DC line respectively; Indicates the unbalanced power of the system after non-fault DC emergency power support and wind turbine shutdown; are the frequency change rate and quasi-steady-state frequency deviation of the system after the fault; RoCoF max , Δf ss,max They represent the frequency change rate and the maximum threshold of quasi-steady-state frequency deviation allowed by the system respectively; H y,s,t , D represent the system inertia level and load droop coefficient respectively; v i is the ramp rate of the thermal power unit; f 0 、f OFGS 、f db They are the reference frequency, the high-frequency cutting action frequency of the sending-end power grid and the frequency dead zone.

[0148] Among them, equation (25) represents the wind turbine cutting constraint; equations (26)-(27) represent the non-fault DC emergency power support constraint; equations (29)-(31) represent the frequency change rate constraint, the frequency minimum point constraint and the quasi-steady-state frequency constraint respectively.

[0149] 5. Transient Voltage Stability Constraints

[0150] As the penetration rate of wind power in the power system continues to increase, the problem of transient voltage stability becomes more and more serious and cannot be ignored. According to the WEEC planning standard, the voltage drop should not exceed 20% and exceed 20 cycles. To this end, the present invention introduces the transient voltage stability margin indicator (TVI) in the model to construct the transient voltage stability constraint, which can be expressed as:

[0151]

[0152] In the formula, It indicates the sensitivity of the phase-converter transformation of retired thermal power units to the transient voltage stability trajectory of the system; TVI req It represents the transient voltage stability margin, with a value of 0.2, TVI y,s,t,i It represents the transient voltage stability margin in the yth stage under the sth scenario and the tth period.

[0153] S3, creating a mixed fuzzy set for characterizing the uncertainty of power output and load forecasting, introducing the mixed fuzzy set into the coordinated planning model of transmission network expansion and thermal power unit transformation, and obtaining the final model;

[0154] In this embodiment, the above-mentioned transmission network expansion and thermal power unit transformation coordinated planning model can be decomposed into a long-term planning model and a short-term operation verification model. For the convenience of description, its general expression is given:

[0155]

[0156] f1(x)=c T x (35)

[0157] st Ax+b≤0 (36)

[0158]

[0159] st Ex+l T ζ-q+v T ζ≤Ny (38)

[0160] Where x represents the discrete variable matrix related to planning decision-making; y represents the continuous variable matrix in the short-term operation verification model; A, b, E, N, l, q, v are the coefficient matrices in the constraints; c and d represent the coefficient matrices in the objective function; and the superscript T represents transposition.

[0161] In this embodiment, creating a mixed fuzzy set for characterizing the uncertainty of power output and load forecasting includes the process of introducing uncertain scenarios, namely: obtaining its empirical distribution based on historical data of wind power output and load

[0162]

[0163] Among them, N represents the amount of historical sample data, ζ n is the historical data of wind power output and load, δ (·) represents the Dirac measure;

[0164] According to the wind power output and load forecast error, the Wassertein distance is defined to characterize the distance between the empirical distribution and the true distribution.

[0165]

[0166] Among them, Ψ(·) represents the joint probability distribution between the empirical distribution and the true distribution;

[0167] The fuzzy set Θ based on Wassertein distance W The definition is as follows:

[0168]

[0169] Constructing fuzzy set Θ based on first-order moment information M :

[0170] Θ M = {P∈P ζ (Ω ζ )|μ - ≤E P (ζ-μ)≤μ +} (42)

[0171] Among them, E p (·) represents the expected operator, μ represents the mean of historical wind power output and historical load, and μ - , μ + represents the expected variance;

[0172] Create a fuzzy set Θ that satisfies W and θ M Mixed fuzzy sets of probability distribution:

[0173]

[0174] S4. Obtain input variables, solve the final model in combination with constraint conditions, and obtain the coordinated planning results of transmission network expansion and thermal power unit transformation.

[0175] In this embodiment, the process of solving the model includes:

[0176] Since the short-run validation model is non-convex, according to Slater’s rule, the final model is reconstructed as a two-stage mixed integer linear model of the equivalent minimization problem:

[0177]

[0178] ||γ|| * ≤λ (46)

[0179] Ex+l T ζ-q+v T ζ≤Ny (47)

[0180] Among them, θ s , π + , π - , λ represents the dual variable; represents the wind power output and load in the nth scenario; γ is the introduced auxiliary variable; ||·|| * represents the second-order norm. Then, the above two-stage mixed integer linear model can be decomposed into the master problem (MP) and the slave problem (SP) for solution, as shown below:

[0181] MP:

[0182]

[0183] st Ax+b≤0 (49)

[0184] ||γ|| * ≤λ (50)

[0185]

[0186] Ex+l T ζ m -q+v T ζ≤Ny m (52)

[0187] SP:

[0188]

[0189] s T T α=d (54)

[0190] Among them, the sub-problem objective function (53) contains the bilinear term ζ T α, this embodiment proposes to use an alternating direction algorithm to iteratively solve.

[0191] At the same time, in order to illustrate the effect of the final model of this embodiment, it is applied to the improved IEEE-39 node system, such as Figure 2 As shown, in order to achieve safe, economical and efficient transmission of large-scale offshore wind power clusters via UHV DC, the results are shown in Table 1:

[0192]

[0193]

[0194] Table 1 Comparison of planning results under different models

[0195] At the same time, data collection is used to depict the wind power consumption under small load scenarios. The transient overvoltage results after the DC line h1 is locked out are as follows: Figure 3 shown. Figure 4 It represents the transient overvoltage result after the DC line h1 is locked fault. The results show that for model 2, the transient overvoltage of the adjacent AC bus after the fault is close to 1.5pu, which will have a great impact on the insulation of the power equipment and system stability in the local area; while for model 5, under the same fault, the transient voltage of the AC bus is within a reasonable range.

[0196] Please refer to Figure 5 , Embodiment 2 of the present invention is:

[0197] A coordinated planning system 1 for transmission network expansion and thermal power unit transformation includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, a coordinated planning method for transmission network expansion and thermal power unit transformation as described in Example 1 is implemented.

[0198] In summary, the coordinated planning method and system for transmission network expansion and thermal power unit transformation provided by the present invention takes the minimum total cost as the optimization goal, establishes a coordinated planning model for transmission network expansion and thermal power unit transformation, and considers the flexibility transformation of transmission network expansion and in-service thermal power units at the same time, so as to achieve more comprehensive and complete cost control and improve the wind power absorption capacity of the system, introduce the investment and construction logic relationship and the phased investment cost constraints, base state operation constraints, peak load constraints, locked fault safety constraints and transient voltage stabilization constraints, strengthen the system's ability to resist large disturbance faults, consider the uncertainty of power output and load forecasting, make the model more accurate, and coordinate the transmission capacity, peak load capacity and anti-disturbance capability of the wind power cluster system.

[0199] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A coordinated planning method for transmission network expansion and thermal power unit transformation, characterized in that: The steps include: S1. Taking the minimum total cost as the optimization goal, a coordinated planning model for transmission network expansion and thermal power unit transformation is established, and its expression is as follows: My:C IN +C MA +C OP +C PB ; Among them, C IN represents the total investment cost of transmission network expansion and thermal power unit transformation, C MA represents the equipment maintenance cost, C OP represents the operating cost, C PB represents the penalty cost for wind curtailment; S2. Create constraints corresponding to the input variables of the transmission network expansion and thermal power unit transformation collaborative planning model, wherein the constraints include investment and construction logic relationship and phased investment cost constraints, base state operation constraints, peak load regulation constraints, blocking fault safety constraints, and transient voltage stabilization constraints; S3, creating a mixed fuzzy set for characterizing the uncertainty of power output and load forecasting, and introducing the mixed fuzzy set into the transmission network expansion and thermal power unit transformation collaborative planning model to obtain a final model; S4. Obtain input variables, and solve the final model in combination with the constraint conditions to obtain the results of the coordinated planning of transmission network expansion and thermal power unit transformation.

2. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 1 is characterized in that: The expression of the total investment cost of the transmission network expansion and thermal power unit transformation is: Among them, Ω y , Ω g , They are the planning stage set, the set of retired thermal power units in stage y, the set of in-service thermal power units, and the set of lines to be built in stage y (i, j). are the investment cost of the lines to be built, the investment cost of the unit capacity transformation of thermal power units, and the investment cost of the unit capacity transformation of the phase-shifting function of retired units, respectively. l , i FR , i SR are the capital recovery coefficients for line, flexibility and phase shifter function transformation, respectively, Y is the equipment life; z y,ij,k , is a 0-1 variable, indicating whether the line k is put into construction in the yth stage, whether the thermal power unit i is transformed for flexibility, and whether the retired unit i is transformed for phase-shifting function. 0 means no, 1 means yes, P i G,max , P i G，min are the maximum output of the thermal power unit and the minimum output before flexibility transformation, P i G，min* The minimum output after flexibility modification, represents the set of lines to be put into operation in stage y (i, j); and: Where r represents the discount rate; The expression of equipment maintenance cost is: Among them, Ω l represents the set of transmission lines, Indicates the corresponding equipment maintenance cost; The expression of equipment maintenance cost is: Among them, Ω s Indicates the running scene collection. are the fuel cost coefficient and standby cost coefficient of thermal power units, respectively. T represents the operating period. They are respectively the active output, up-ramp reserve and down-ramp reserve of thermal power unit i in the yth stage s scenario t period; The expression of the wind curtailment penalty cost is: Among them, Ω w represents the set of wind turbines, represents the unit penalty cost of wind curtailment, It represents the wind curtailment in the yth stage under the sth scenario and the tth period.

3. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 2 is characterized in that: The expression of the investment and construction logic relationship and the phased investment cost constraint is: With y,ij,k ≥from y-1,ij,k ; Among them, z y-1,ij,k Indicates whether the line k in the previous stage of stage y is put into construction, K y,ij Indicates the set of lines that have been put into operation. They represent the minimum and maximum values ​​of the lines allowed to be constructed in the line corridor (i, j) in the yth stage, Represents the maximum investment limit allowed in stage y.

4. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 2 is characterized in that: The base state operation constraints include unit output constraints, UHV DC line operation modeling constraints, AC power flow safety constraints, and output characteristic modeling constraints of thermal power units after transformation.

5. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 4 is characterized in that: The AC power flow safety constraints include system active and reactive power balance constraints, node voltage amplitude constraints, and line apparent power transfer limit constraints.

6. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 4 is characterized in that: The output characteristic modeling constraints after the transformation of the thermal power unit include active output constraints, ramp constraints and reactive output limitations after the flexibility transformation of the in-service thermal power unit.

7. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 2 is characterized in that: The expression of the peak load constraint is as follows: Among them, P i H,max , P i H,min are the maximum and minimum transmission active power of the UHV DC line, PCP y,s,t 、TCP y,s,t They represent the peak capacity pressure and valley capacity pressure of the system in the yth stage, sth scenario, and tth period, respectively. represents the active load of the node, represents the active power of the UHV DC line, are the corresponding minimum thresholds respectively.

8. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 2 is characterized in that: The hybrid fuzzy set created to characterize the uncertainty of power output and load forecasting includes: The empirical distribution is obtained based on the historical data of wind power output and load. Among them, N represents the amount of historical sample data, ζ n is the historical data of wind power output and load, δ (·) represents the Dirac measure; According to the wind power output and load forecast error, the Wassertein distance is defined to characterize the distance between the empirical distribution and the true distribution. Among them, Ψ(·) represents the joint probability distribution between the empirical distribution and the true distribution; The fuzzy set Θ based on Wassertein distance W The definition is as follows: Constructing fuzzy set Θ based on first-order moment information M : I M ={P∈P ζ (Oh ζ )|m - ≤E P (z-μ)≤μ + }; Among them, E p (·) represents the expected operator, μ represents the mean of historical wind power output and historical load, and μ - , μ + represents the expected variance; Create a fuzzy set Θ that satisfies W and θ M The probability distribution of the mixed fuzzy set:

9. The coordinated planning method for transmission network expansion and thermal power unit transformation according to claim 1 is characterized in that: The step S4 comprises: According to Slater's rule, the final model is reformulated as a two-stage mixed integer linear model with an equivalent minimization problem: ||c|| * ≤λ; From +1 T ζ-q+v T ζ≤Ny; Among them, θ s , π + , π - , λ represents the dual variable, represents the wind power output and load in the nth scenario, γ is the introduced auxiliary variable, ||·|| * represents the second-order norm; The two-stage mixed integer linear model is decomposed into a main problem MP and a sub-problem SP to facilitate solution: MP: stAx+b≤0; ||c|| * ≤λ; SP: s.t.M T α＝d 。 10. A coordinated planning system for transmission network expansion and thermal power unit transformation, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the coordinated planning method for transmission network expansion and thermal power unit transformation as described in any one of claims 1 to 9 is implemented.

Images