Scheduling method and system for cooperation of Sagomean base and receiving end power grid

Abstract

The invention provides a scheduling method and a scheduling system for cooperation of a Sagolian district base and a receiving end power grid. The scheduling method comprises the following steps: establishing a Sagolian district new energy base cross-region delivery model based on an operation model of a Sagolian district new energy base and a direct current channel power delivery operation model; determining direct current virtual inertia and energy storage frequency modulation power according to the Sagomean new energy base cross-regional delivery model, and constructing a storage and direct current collaborative two-stage dynamic frequency response model based on the direct current virtual inertia, the energy storage frequency modulation power and inertia and frequency modulation power of traditional thermal power; establishing a new energy base and receiving-end power grid cooperative scheduling model based on a Sagomean new energy base cross-regional delivery model and a storage and direct current cooperative two-stage dynamic frequency response model; and based on frequency security constraints, solving the new energy base and receiving-end power grid collaborative scheduling model, and obtaining scheduling parameters of the Saggob base and receiving-end power grid collaboration. And the delivery flexibility, the new energy consumption capability and the system operation safety level are improved.

Description

Technical Field

[0001] This invention relates to the field of power system dispatching, specifically to a dispatching method and system for coordinated dispatching between the Shagohuang base and the receiving-end power grid. Background Technology

[0002] Accelerating the development of renewable energy power generation such as wind and solar power is an important way to achieve the low-carbon transformation of the power system. Large-scale renewable energy bases, exemplified by those in desert, Gobi, and arid regions, are a crucial method for renewable energy development. By 2030, China plans to construct 450 million kilowatts of large-scale wind and solar power bases in desert, Gobi, and arid regions to accelerate the construction of a clean, low-carbon, safe, and efficient energy system. However, the output of renewable energy bases is random and fluctuating, increasing the difficulty of system power balance. More importantly, the connection of desert and Gobi bases to the receiving-end grid via HVDC (High Voltage Direct Current) will reduce the number of synchronous generators in operation, leading to a decrease in the security support capacity of the receiving-end grid. Furthermore, the asynchronous interconnection of HVDC makes it difficult to couple regulation resources between regions, further weakening frequency support capacity. Adding frequency response design to HVDC control can strengthen the power support capacity for disturbances in asynchronous regions. Therefore, in order to achieve reliable power transmission and off-site consumption from the "Shagohuang" base, it is necessary to leverage the flexibility and support capabilities of the Shagohuang base and the DC transmission channel to achieve coordinated dispatch between the Shagohuang base and the receiving-end power grid.

[0003] To ensure stable cross-regional power transmission from the Shagohuang renewable energy base, extensive research has been conducted on the operation of this base. However, most studies on renewable energy bases suffer from the following shortcomings: the optimization scope of the models is limited to the renewable energy base itself; the coordinated scheduling of sending and receiving ends is not considered; and issues such as the scarcity of inertia and insufficient primary frequency regulation capacity brought about by large-scale renewable energy grid connection are not taken into account. Currently, some literature incorporates frequency security into the optimal scheduling of the power system, such as including the inertia support and frequency regulation characteristics of thermal power units in the frequency security constraints. However, most current studies treat conventional and renewable energy units as frequency regulation resources, neglecting the synergistic effect of multiple frequency regulation resources such as energy storage and DC channel regulation in renewable energy bases. Summary of the Invention

[0004] To effectively alleviate the power output volatility and frequency security issues caused by a high proportion of renewable energy grid integration, this invention provides a scheduling method for coordinated operation between the Shagohuang base and the receiving-end power grid, comprising:

[0005] Based on the operation model of the Shagohuang New Energy Base and the DC channel power transmission operation model, a cross-regional power transmission model of the Shagohuang New Energy Base is established.

[0006] Based on the cross-regional power transmission model of the Shagohuang New Energy Base, the DC virtual inertia and energy storage frequency regulation power are determined. Based on the DC virtual inertia and energy storage frequency regulation power, and the inertia and frequency regulation power of traditional thermal power, a two-stage dynamic frequency response model of DC-energy storage coordination is constructed.

[0007] Based on the cross-regional transmission model of the Shagohuang new energy base and the two-stage dynamic frequency response model of energy storage and direct current coordination, a collaborative scheduling model between the new energy base and the receiving-end power grid is established. Based on frequency security constraints, the collaborative scheduling model between the new energy base and the receiving-end power grid is solved to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid.

[0008] Furthermore, the operational model of the Shagohuang New Energy Base includes: new energy output constraints, conventional unit operation constraints, and energy storage unit operation constraints; among which,

[0009] The power output constraints for new energy sources are:

[0010]

[0011] in, This represents the actual output power received by renewable energy unit i during time period t. This represents the acceptable output of renewable energy unit i during time period t. This represents the amount of wind and solar power curtailed by renewable energy unit i during time period t.

[0012] The operating constraints for conventional generating units are:

[0013]

[0014] Where v represents the start-stop state of thermal power unit j during time period t, and is a binary 0-1 variable; P j,t s P represents the output of thermal power unit j during time period t; j max P j min These represent the upper and lower limits of the output power of thermal power unit j, respectively; S n Indicates the upper limit of primary frequency regulation power of thermal power units; P t PFR This represents the primary frequency regulation power provided by thermal power unit j during time period t;

[0015] The operating constraints of the energy storage unit are:

[0016]

[0017] in, E represents the charging and discharging state of energy storage unit k during time period t, and is a binary 0-1 variable; k,t This represents the capacity of energy storage unit k during time period t; e c ed Δt represents the charging and discharging efficiency of energy storage unit k; Δt represents the time for energy storage charging and discharging power. These represent the upper and lower limits of the energy storage capacity of energy storage unit k, respectively. These represent the upper and lower limits of the charging and discharging power of the energy storage unit k, respectively.

[0018] Furthermore, the DC power transmission operation model includes: DC channel operation constraints and power balance constraints for new energy bases, among which,

[0019] The operating constraints for the DC channel are:

[0020]

[0021] R max ≤4 (17)

[0022]

[0023] Among them, P DC,max Indicates the maximum transmission capacity of the DC channel; R represents the DC power transmitted during the r-th time interval; max Indicates the maximum number of adjustments to the DC channel's external power output within 24 hours; DR DC UR DC These represent the maximum uphill and downhill ramp rates of the DC channel, respectively.

[0024] The power balance constraint of the new energy base is:

[0025]

[0026] The left side represents the power output of the new energy base, and the right side represents the power transmitted via the DC channel; π RES π G π ES These respectively represent new energy power units, thermal power units, and energy storage units.

[0027] Furthermore, based on the cross-regional power transmission model of the Shagohuang New Energy Base, the DC virtual inertia and energy storage frequency regulation power are determined, including:

[0028] The primary frequency regulation of the synchronous machine in the cross-regional transmission model of the Shagohuang New Energy Base is essentially the same as the primary frequency regulation of the local synchronous machine at the receiving end, and its response power is:

[0029]

[0030] in, These represent the PFR capacity of the receiving and sending end synchronizers, respectively; T db1 T1 represents the primary frequency modulation delay of the transmitting and receiving end synchronizers; T1 represents the primary frequency modulation ramp-up time of the transmitting and receiving end synchronizers; ΔPPFR This indicates the first frequency modulation of the synchronous machine at the sending and receiving ends;

[0031] The response mode of primary frequency regulation for energy storage is as follows:

[0032]

[0033] in, Indicates the primary frequency regulation capacity of energy storage; Indicates the primary frequency regulation capacity of the energy storage unit; T db2 T1 represents the frequency regulation delay of energy storage; T2 represents the frequency regulation ramp-up time of energy storage. This indicates primary frequency regulation for energy storage.

[0034] Furthermore, based on the aforementioned DC virtual inertia and energy storage frequency regulation power, and the inertia and frequency regulation power of traditional thermal power, a two-stage dynamic frequency response model for DC-energy storage coordination is constructed, including:

[0035] The inertia of a synchronous machine is related to the number of times the unit starts and stops, exhibiting a discrete characteristic:

[0036]

[0037] Among them, v j Indicates the start-up status of the thermal power synchronous generator unit; H g,j P represents the inertial time constant of a thermal power unit. max Indicates the installed capacity of thermal power units;

[0038] The DC virtual inertia is provided by the DC capacitor. The voltage reference value of the fixed voltage station is linked to the frequency change of the AC power grid. When the DC voltage changes, the DC capacitor will provide inertial support power. The equation (24) can be obtained by combining the generator rotor motion equation with the DC capacitor charging and discharging power:

[0039]

[0040] After simplification, we obtain equation (25):

[0041]

[0042] Virtual inertia exhibits continuity:

[0043] H dc =H c S n (26)

[0044] Among them, H dc Represents the DC virtual inertia time constant; C represents the DC capacitance value; U dc0 Indicates the reference value of rated DC voltage; f0 indicates the rated frequency of the system; U dc,ref(t) represents the DC voltage reference value; N represents the number of thermal power units; H c S represents the virtual inertial time constant of the DC capacitor. n Indicates the capacity of the DC converter station;

[0045] Based on the virtual inertial delay of the DC channel, the rotor motion equations with two-stage frequency dynamic changes are shown in equations (27)-(28):

[0046]

[0047] Among them, H, H dc These represent the receiving-end synchronous machine inertia and DC virtual inertia, respectively, in MWs; Δf represents the receiving-end grid frequency difference; f0 represents the rated frequency; P e T represents the power of the receiving-end power grid disturbance. B Indicates the DC virtual inertial response delay;

[0048] H represents the inertial time constant of a constant-speed pumped-storage unit. g P is the inertial time constant of a conventional unit; s,n P g,n These are the rated power of the constant-speed pumped storage / conventional units, respectively.

[0049] Furthermore, the two-stage dynamic frequency response model for storage-DC collaboration includes system frequency security indicators such as frequency change rate constraints, frequency minimum point constraints, and quasi-steady-state constraints.

[0050] The frequency change rate constraint, in the presence of a response delay in DC virtual inertia, is determined solely by the disturbance power and the inertia of the thermal power synchronous unit in the initial stage of the disturbance:

[0051]

[0052] Frequency minimum point constraint: After the system is subjected to a disturbance, in order to prevent the frequency from continuing to drop, a frequency minimum point threshold needs to be set and limited.

[0053] |Δf(t nadir )|≤Δf max (30)

[0054] To obtain the minimum frequency constraint, the DC virtual inertial delay is first disregarded, and the dynamic frequency response equation is written as follows (31):

[0055]

[0056] Assume the lowest frequency point is t nadir Integrating the above equation, we obtain equation (32):

[0057]

[0058] The constraint on the lowest point of the received-end frequency, without considering virtual inertial delay, is obtained as shown in equation (33):

[0059]

[0060] Considering the virtual inertial delay, the above equation is corrected to the following equation (34):

[0061]

[0062] Quasi-steady-state constraints, to ensure that the frequency can recover normally to the rated frequency after falling to the lowest frequency point, must meet the following constraints:

[0063]

[0064] Furthermore, the collaborative dispatch model between the renewable energy base and the receiving-end power grid includes: an objective function aimed at minimizing total operating cost, constraints on inter-regional power transmission from the renewable energy base, and constraints on the collaborative operation of the renewable energy base and the receiving-end power grid.

[0065] The objective function that aims to minimize total operating cost is:

[0066]

[0067] Where, λ s Indicates the probability of different scenarios occurring; This represents the operating cost of thermal power unit j during time period t under scenario s, where a, b, and c represent the power generation cost coefficients of the thermal power unit, respectively; C SUit C SDit Let c represent the start-up and shutdown costs of thermal power unit j during time period t; curt These represent the penalty coefficients for wind and solar power curtailment;

[0068] The constraints on cross-regional power transmission from new energy bases specifically include: the expression corresponding to the operational constraints of conventional generating units is:

[0069]

[0070] The expression corresponding to the operating constraints of the energy storage unit is:

[0071]

[0072] The expression corresponding to the DC power transmission constraint is:

[0073]

[0074] Among them, S n Indicates the upper limit of primary frequency regulation power of thermal power units; Pt PFR P represents the primary frequency regulation power provided by thermal power unit j during time period t; Δt1 represents the discharge time of the primary frequency regulation power of the energy storage unit; t BES P represents the primary frequency regulation power provided by energy storage unit k during time period t; t EX This indicates the total PFR capacity provided by the new energy base;

[0075] Constraints on the coordinated operation of new energy bases and receiving ends specifically include: the expression corresponding to line power flow constraints is:

[0076] PL l,t =(θ i,t -θ j,t ) / x l ,θ ref,l =0 (42)

[0077]

[0078] The expression corresponding to the power balance constraint of the receiving-end grid node is:

[0079]

[0080] Where, θ i,t θ j,t The x-axis represents the phase angle of the node connected to line l. l Indicates the reactance of line l; Indicates the maximum transmission power capacity of line l; θ ref,l The phase angle of the equilibrium node; This represents the active power flow of line l merging into node nd during time period t in scenario s; π L Represents the set of receiving-end power grid lines; I nd This represents a binary variable, indicating whether the DC channel is connected to node nd; This represents the load of node nd during time period t in scenario s.

[0081] Furthermore, based on frequency security constraints, the collaborative scheduling model between the new energy base and the receiving-end power grid is solved to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid, including:

[0082] Based on the fact that the minimum frequency point constraint is a nonlinear constraint, the collaborative scheduling model between the new energy base and the receiving-end power grid is transformed into the following formula:

[0083]

[0084] Replacing the constraints with A, B, and C, we obtain equations (46)-(48):

[0085]

[0086] B = P PFR / T2 (47)

[0087]

[0088] The above formula can be transformed into:

[0089] AB≥C 2 (49)

[0090] (A+B) 2 -(AB) 2 ≥4C 2 (50)

[0091]

[0092] This invention also provides a dispatching system for coordinated operation between the Shagohuang base and the receiving-end power grid, comprising:

[0093] The inter-regional power transmission model establishment module is used to establish an inter-regional power transmission model for the Shagohuang New Energy Base based on the operation model of the Shagohuang New Energy Base and the DC channel power transmission operation model.

[0094] The frequency response model construction module is used to determine the DC virtual inertia and energy storage frequency regulation power based on the cross-regional transmission model of the Shagohuang New Energy Base, and to construct a two-stage dynamic frequency response model of DC-energy storage coordination based on the DC virtual inertia and energy storage frequency regulation power, the inertia and frequency regulation power of traditional thermal power.

[0095] The scheduling model solving module is used to establish a collaborative scheduling model between the new energy base and the receiving-end power grid based on the cross-regional transmission model of the Shagohuang new energy base and the two-stage dynamic frequency response model of energy storage and direct current coordination; based on frequency security constraints, it solves the collaborative scheduling model between the new energy base and the receiving-end power grid to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid.

[0096] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, it implements the scheduling method for coordinated operation between the Shagohuang base and the receiving-end power grid as described in any one of the preceding claims.

[0097] This invention provides a scheduling method and system for coordinating the power grid between the desert and barren land base and the receiving-end power grid. By constructing an integrated wind, solar, thermal and energy storage operation model for the new energy base and flexible operation constraints for DC tiered transmission, and introducing an energy storage-DC collaborative framework under frequency security constraints, it achieves unified optimization and computable solution for power balance and frequency security, thereby improving transmission flexibility, new energy absorption capacity and system operation safety level. Attached Figure Description

[0098] Figure 1 This is a schematic flowchart of a scheduling method for coordinated operation between the Shagohuang base and the receiving-end power grid, provided by an embodiment of the present invention.

[0099] Figure 2 This is a wind and solar power output prediction curve diagram related to an embodiment of the present invention;

[0100] Figure 3 These are the output diagrams of the new energy bases in Examples 1 and 2 of this invention;

[0101] Figure 4 These are the power transmission curves and total wind and solar curtailment diagrams for examples 1 and 2 involved in the embodiments of the present invention;

[0102] Figure 5 These are the area stacking diagram of calculation example 3 and the total wind and solar curtailment diagrams of calculation examples 2 and 3 involved in the embodiments of the present invention;

[0103] Figure 6 These are the variation graphs of RoCoF and Nadir in examples 2 and 3 of this invention.

[0104] Figure 7 This is a diagram illustrating the power output of the new energy base in Example 4 and the number of units started up in Examples 3 and 4, as described in this embodiment of the invention.

[0105] Figure 8 This is a schematic diagram of a scheduling system for coordinated operation between the Shagohuang base and the receiving-end power grid, provided by an embodiment of the present invention. Detailed Implementation

[0106] Numerous specific details are set forth in the following description to provide a full understanding of the invention. However, the invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0107] This invention provides a scheduling method for coordinated operation between the Shagohuang base and the receiving-end power grid, such as... Figure 1 As shown, it includes the following steps:

[0108] Step S101: Based on the operation model of the Shagohuang New Energy Base and the DC channel power transmission operation model, establish the Shagohuang New Energy Base inter-regional power transmission model.

[0109] First, we analyze the operation model of the new energy base, which includes constraints on new energy output, constraints on the operation of conventional units, and constraints on the operation of energy storage units.

[0110] (1) The power output constraint of new energy sources is:

[0111]

[0112] in, This represents the actual output power received by renewable energy unit i during time period t. This represents the acceptable output of renewable energy unit i during time period t. This represents the amount of wind and solar power curtailed by renewable energy unit i during time period t.

[0113] (2) The operating constraints for conventional generating units are:

[0114]

[0115] Where v represents the start-stop state of thermal power unit j during time period t, and is a binary 0-1 variable; P j,t s P represents the output of thermal power unit j during time period t; j max P j min These represent the upper and lower limits of the output power of thermal power unit j, respectively; S n Indicates the upper limit of primary frequency regulation power of thermal power units; P t PFR This represents the primary frequency regulation power provided by thermal power unit j during time period t;

[0116] (3) The operating constraints of the energy storage unit are:

[0117]

[0118] in, E represents the charging and discharging state of energy storage unit k during time period t, and is a binary 0-1 variable; k,t This represents the capacity of energy storage unit k during time period t; e c e d Δt represents the charging and discharging efficiency of energy storage unit k; Δt represents the time for energy storage charging and discharging power. These represent the upper and lower limits of the energy storage capacity of energy storage unit k, respectively. These represent the upper and lower limits of the charging and discharging power of the energy storage unit k, respectively.

[0119] The DC power transmission operation model includes DC channel operation constraints and power balance constraints for new energy bases.

[0120] (1) The operating constraints of the DC channel are:

[0121]

[0122] R max ≤4 (17)

[0123]

[0124] Among them, PDC,max Indicates the maximum transmission capacity of the DC channel; R represents the DC power transmitted during the r-th time interval; max Indicates the maximum number of adjustments to the DC channel's external power output within 24 hours; DR DC UR DC These represent the maximum uphill and downhill ramp rates of the DC channel, respectively.

[0125] (2) The power balance constraint of the new energy base is:

[0126]

[0127] The left side represents the power output of the new energy base, and the right side represents the power transmitted via the DC channel; π RES π G π ES These respectively represent new energy power units, thermal power units, and energy storage units.

[0128] Step S102: Based on the cross-regional power transmission model of the Shagohuang New Energy Base, determine the DC virtual inertia and energy storage frequency regulation power. Based on the DC virtual inertia and energy storage frequency regulation power, and the inertia and frequency regulation power of traditional thermal power, construct a two-stage dynamic frequency response model for DC-energy storage coordination.

[0129] First, the virtual inertia support capability of the DC channel and the frequency regulation response characteristics of energy storage are analyzed. A dynamic mapping is established between the voltage reference value of the constant voltage converter station and the frequency change of the AC grid, forming virtual inertia support provided by the DC capacitor. At the same time, the energy storage system adopts a virtual synchronous machine (VSG) control strategy, which enables it to have the external characteristics of synchronous machine grid-connected operation and fast primary frequency regulation capability.

[0130] Synchronous generators (PFRs) are a core supporting resource for power system frequency security. When the grid frequency deviates from its rated value, synchronous generators automatically adjust their active power output through speed governors to maintain system frequency stability. The synchronous generator primary frequency regulation in the Shagohuang New Energy Base inter-regional transmission model is essentially the same as the primary frequency regulation of the local synchronous generator at the receiving end, and its response power is:

[0131]

[0132] in, These represent the PFR capacity of the receiving and sending end synchronizers, respectively; T db1 T1 represents the primary frequency modulation delay of the transmitting and receiving end synchronizers; T1 represents the primary frequency modulation ramp-up time of the transmitting and receiving end synchronizers; ΔP PFR This indicates the first frequency modulation of the synchronous machine at the sending and receiving ends;

[0133] Grid-based energy storage technology is a key technology for promoting new power systems. Its application in energy storage not only improves the uncertainties brought about by the grid connection of new energy sources, but also alleviates frequency security and voltage issues under high-proportion grid connection of new energy sources. Compared with traditional grid-connected energy storage, which requires phase-locked loops and cannot provide instantaneous inertia and voltage support, grid-based energy storage has active voltage and current control capabilities, can simulate the characteristics of synchronous machines, and can still operate independently without strong power source support, thus providing good support for weak power grids.

[0134] The energy storage unit of this invention utilizes Virtual Synchronous Generator (VSG) technology for response, enabling the energy storage to exhibit the external characteristics of a synchronous generator operating in grid-connected mode. The response mode for primary frequency regulation of the energy storage is as follows:

[0135]

[0136] in, Indicates the primary frequency regulation capacity of energy storage; Indicates the primary frequency regulation capacity of the energy storage unit; T db2 T1 represents the frequency regulation delay of energy storage; T2 represents the frequency regulation ramp-up time of energy storage. This indicates primary frequency regulation for energy storage.

[0137] Step S103: Based on the cross-regional transmission model of the Shagohuang new energy base and the two-stage dynamic frequency response model of energy storage and direct current coordination, establish a collaborative scheduling model between the new energy base and the receiving-end power grid; based on frequency security constraints, solve the collaborative scheduling model between the new energy base and the receiving-end power grid to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid.

[0138] The inertia of a synchronous machine is essentially its ability to exchange the rotational kinetic energy stored in the generator rotor with disturbance power to maintain the rated frequency; its magnitude is related to the number of times the unit starts and stops, exhibiting a discrete characteristic.

[0139]

[0140] Among them, v j Indicates the start-up status of the thermal power synchronous generator unit; H g,j P represents the inertial time constant of a thermal power unit. max The virtual inertia can be provided by a DC capacitor. The voltage reference value of the fixed voltage station is linked to the frequency change of the AC power grid. The DC virtual inertia is provided by a DC capacitor. The voltage reference value of the fixed voltage station is linked to the frequency change of the AC power grid. When the DC voltage changes, the DC capacitor will provide inertial support power. The generator rotor motion equation and the DC capacitor charging and discharging power can be combined to obtain equation (24):

[0141]

[0142] After simplification, we obtain equation (25):

[0143]

[0144] Virtual inertia exhibits continuity:

[0145] H dc =H c S n (26)

[0146] Among them, H dc Represents the DC virtual inertia time constant; C represents the DC capacitance value; U dc0 Indicates the reference value of rated DC voltage; f0 indicates the rated frequency of the system; U dc,ref (t) represents the DC voltage reference value; N represents the number of thermal power units; H c S represents the virtual inertial time constant of the DC capacitor. n Indicates the capacity of the DC converter station;

[0147] Based on the virtual inertial delay of the DC channel, the rotor motion equations with two-stage frequency dynamic changes are shown in equations (27)-(28):

[0148]

[0149]

[0150] Among them, H, H dc These represent the receiving-end synchronous machine inertia and DC virtual inertia, respectively, in MWs; Δf represents the receiving-end grid frequency difference; f0 represents the rated frequency; P e T represents the power of the receiving-end power grid disturbance. B Indicates the DC virtual inertial response delay;

[0151] H represents the inertial time constant of a constant-speed pumped-storage unit. g P is the inertial time constant of a conventional unit; s,n P g,n These are the rated power of the constant-speed pumped storage / conventional units, respectively.

[0152] When new energy generating units fail, severe supply-demand imbalances occur, causing drastic changes in system frequency. To ensure sufficient frequency response capability under large disturbances, a two-stage dynamic frequency response model for energy storage-DC collaboration is used. Its system frequency safety indicators include constraints on the rate of frequency change, the minimum frequency point, and quasi-steady-state constraints. The derivation results of the frequency safety indicators based on the delayed virtual inertia response are as follows.

[0153] The frequency change rate constraint, in the presence of a response delay in DC virtual inertia, is determined solely by the disturbance power and the inertia of the thermal power synchronous unit in the initial stage of the disturbance:

[0154]

[0155] Frequency minimum point constraint: After the system is subjected to a disturbance, in order to prevent the frequency from continuing to drop, a frequency minimum point threshold needs to be set and limited.

[0156] |Δf(t nadir )|≤Δf max (30)

[0157] To obtain the minimum frequency constraint, the DC virtual inertial delay is first disregarded, and the dynamic frequency response equation is written as follows (31):

[0158]

[0159] Assume the lowest frequency point is t nadir Integrating the above equation, we obtain equation (32):

[0160]

[0161] The constraint on the lowest point of the received-end frequency, without considering virtual inertial delay, is obtained as shown in equation (33):

[0162]

[0163] Considering the virtual inertial delay, the above equation is corrected to the following equation (34):

[0164]

[0165] Quasi-steady-state constraints, to ensure that the frequency can recover normally to the rated frequency after falling to the lowest frequency point, must meet the following constraints:

[0166]

[0167] The proposed method for coordinated scheduling of the desert renewable energy base and the receiving-end power grid first constructs an uncertain wind and solar power output scenario, and then establishes a coordinated scheduling model between the renewable energy base and the receiving-end power grid. The coordinated scheduling model between the renewable energy base and the receiving-end power grid includes constraints and an objective function with the goal of minimizing the total operating cost. The constraints include: constraints on the inter-regional transmission of renewable energy from the renewable energy base and constraints on the coordinated operation of the renewable energy base and the receiving-end power grid.

[0168] Due to the limited time span and small sample size of wind and solar power output data, it is difficult to fully characterize the uncertainty and volatility of their output. Generative Adversarial Networks (GANs) are used to generate typical wind and solar power output scenarios. The model consists of a generator G and a discriminator D: the generator takes 32-dimensional random noise as input and outputs a 48-dimensional vector; the discriminator judges the samples and provides gradient constraints for the generator. Based on the scene reduction idea of ​​distribution similarity, representative curves are selected by sampling from the farthest point in the "shape space," and the amplitude is scaled at equal intervals in a "step-like" manner to compress five representative wind and solar power scenarios as input for random optimization.

[0169] The objective function that aims to minimize total operating cost is:

[0170]

[0171] Where, λ s Indicates the probability of different scenarios occurring; This represents the operating cost of thermal power unit j during time period t under scenario s, where a, b, and c represent the power generation cost coefficients of the thermal power unit, respectively; C SUit C SDit Let c represent the start-up and shutdown costs of thermal power unit j during time period t; curt These represent the penalty coefficients for wind and solar power curtailment;

[0172] The constraints on cross-regional power transmission from new energy bases specifically include: the expression corresponding to the operational constraints of conventional generating units is:

[0173]

[0174] The expression corresponding to the operating constraints of the energy storage unit is:

[0175]

[0176] The expression corresponding to the DC power transmission constraint is:

[0177]

[0178] Among them, S n Indicates the upper limit of primary frequency regulation power of thermal power units; P t PFR P represents the primary frequency regulation power provided by thermal power unit j during time period t; Δt1 represents the discharge time of the primary frequency regulation power of the energy storage unit; t BES P represents the primary frequency regulation power provided by energy storage unit k during time period t; t EX This indicates the total PFR capacity provided by the new energy base;

[0179] The constraints on the receiving-end power grid operation include conventional unit operation constraints, line power flow constraints, and power balance constraints at receiving-end power grid nodes. The constraints on renewable energy output and conventional unit operation are consistent with those described earlier and will not be repeated here. The expression for the line power flow constraint is:

[0180] PL l,t =(θ i,t -θ j,t ) / x l ,θ ref,l =0 (42)

[0181]

[0182] The expression corresponding to the power balance constraint of the receiving-end grid node is:

[0183]

[0184] Where, θ i,t θ j,t The x-axis represents the phase angle of the node connected to line l. l Indicates the reactance of line l; Indicates the maximum transmission power capacity of line l; θ ref,l The phase angle of the equilibrium node; This represents the active power flow of line l merging into node nd during time period t in scenario s; π L Represents the set of receiving-end power grid lines; I nd This represents a binary variable, indicating whether the DC channel is connected to node nd; This represents the load of node nd during time period t in scenario s.

[0185] Based on the collaborative scheduling model between new energy bases and receiving-end power grids, the frequency security constraint second-order cone is equivalent, forming a mixed integer convex optimization problem for solution.

[0186] Based on the fact that the minimum frequency point constraint is a nonlinear constraint, the collaborative scheduling model between the new energy base and the receiving-end power grid is transformed into the following formula:

[0187]

[0188] Replacing the constraints with A, B, and C, we obtain equations (46)-(48):

[0189]

[0190] B = P PFR / T2 (47)

[0191]

[0192] The above formula can be transformed into:

[0193] AB≥C 2 (49)(A+B) 2 -(AB) 2 ≥4C 2 (50)

[0194]

[0195] Taking the IEEE standard case as an example for simulation:

[0196] 1. Example Setup

[0197] The peak load is 2300MW, and the installed capacity of the receiving-end grid is 3600MW. The main parameters for the example are set as follows: DC transmission capacity is 800MW, wind and solar capacities are configured at 400MW and 800MW respectively, energy storage capacity is 100MW, and charge / discharge efficiencies are 0.98 and 0.93 respectively. The virtual inertia time constant of the DC capacitor is 2s. For frequency safety indicators: the preset disturbance is 10% of the load for each time period, and the maximum frequency change rate is... Maximum frequency deviation Δf max =0.8Hz.

[0198] To analyze the flexible adjustment capability of high-voltage direct current transmission channels and the impact of inertia and primary frequency regulation power brought about by the energy storage-DC collaborative model on the system, this paper sets up four different scheduling schemes for comparative experiments.

[0199] Example 1: Scheduling without considering frequency security constraints under fixed DC transmission power.

[0200] Example 2: Scheduling without considering frequency security constraints under flexible adjustment of DC transmission power.

[0201] Example 3: Flexible DC regulation, with frequency security constraints and scheduling provided solely by the receiving-end thermal power plant.

[0202] Example 4: Flexible DC regulation, frequency security constraint scheduling through grid-type energy storage, DC channels and receiving-end thermal power providing frequency support.

[0203] Table 1 Comparison of Case Settings

[0204]

[0205] Landscape output under different scenarios, such as Figure 2 As shown in the figure, wind power output exhibits strong overall fluctuations and a clear multi-peak characteristic, while photovoltaic output shows a typical single-peak distribution. The probabilities of the five scenarios are 0.23, 0.06, 0.29, 0.12, and 0.3, respectively.

[0206] 2. Comparative analysis of the running results.

[0207] To verify the effectiveness of the model and the impact of different control strategies on the scheduling results of this system, four calculation examples are set up for comparative analysis as shown in Table 1. Table 2 shows the renewable energy absorption rate of calculation examples 2-4. The operating costs of the four calculation examples are shown in Table 3. It can be seen that compared with calculation example 2, the cost of calculation example 2 is significantly reduced, only RMB 1.9072 million, which is significantly lower than the operating cost of thermal power and renewable energy penalties in calculation example 1, with a total cost reduction of 38.4%. In contrast, after introducing frequency security constraints in calculation example 3, the total cost rises to RMB 4.6605 million, and the wind and solar curtailment penalty is as high as RMB 2.5597 million. This indicates that without energy storage and DC frequency support, the system needs to curtail a large amount of wind and solar power to meet frequency security constraints, relying solely on the output of receiving-end thermal power units, thus leading to an increase in total operating costs. In Example 4, after introducing the frequency support mechanism of energy storage-DC collaboration, the total cost decreased significantly. The operating cost of thermal power and the penalty for wind and solar curtailment decreased by 20% and 64.1%, respectively. This shows that the frequency response and DC virtual inertia of grid-type energy storage can effectively provide frequency support, improve the new energy absorption capacity of the new power system, and reduce the operating cost of the new power system.

[0208] Table 2 Comparison of New Energy Consumption Rates in Examples 2-4

[0209]

[0210] Table 3 Cost Comparison of Examples 1-4

[0211]

[0212] 3. The impact of flexible DC adjustment.

[0213] Depend on Figure 3 and 4 It can be seen that the DC transmission strategy in Example 1 cannot meet the needs of a new power system with a high proportion of renewable energy, and it cannot transmit power as required, resulting in a power deficit. During peak renewable energy output periods (such as hours 10-16), the utilization rate of the DC channel in Example 2 is significantly higher than that in Example 1. Meanwhile, from... Figure 3 The comparison clearly shows that the total curtailed wind and solar power in Example 1 is not only large in value but also widely distributed over a wide period of time, further verifying that Example 1 suffers from significant power deficit due to the rigid constraints of DC operation, which limits the absorption of new energy sources. In summary, flexible adjustment of the DC channel enhances the economic efficiency of system operation, improves the absorption rate of new energy sources, and reduces the power deficit.

[0214] 4. The impact of frequency constraints.

[0215] Depend on Figure 5As can be seen, Example 2, while considering flexible DC regulation, did not take into account frequency security constraints. Therefore, the system could maximize the output of new energy sources, with both wind and solar power being utilized to a high degree, and the total renewable energy absorption rate reaching 99%. However, this example has potential risks because it did not consider the frequency security of the receiving-end grid. Example 3 introduced frequency security constraints and relied solely on the receiving-end traditional thermal power synchronous machine for inertia and primary frequency regulation. Limited by the frequency constraints and the combined constraints of synchronous machine inertia, frequency regulation capability, and response speed, renewable energy output was suppressed, especially during the morning and afternoon peak hours, when wind power output decreased significantly, and the DC transmission curve showed an overall decline. Compared to Example 2, the renewable energy base power output diagram in Example 3 showed a "cropping" phenomenon, with the renewable energy absorption rates of the renewable energy base and the receiving-end grid decreasing by 15% and 11%, respectively.

[0216] Depend on Figure 6 As can be seen, in Example 2, without considering frequency constraints, the RoCoF variation is significantly higher than in Example 3, exceeding the safety threshold of 0.5 Hz / s for most periods, especially showing a significant steepness in the 8-10 and 22-24 period. This indicates that Example 2, without considering frequency safety, has a significantly insufficient inertia level and an excessively rapid frequency change rate, posing a substantial safety hazard. Meanwhile, in Example 3, the lowest frequency points in each period are significantly higher than in Example 2, and the frequency drop amplitude is significantly narrower, indicating that the system can recover more quickly after being disturbed, reducing the risk of low-frequency load shedding. In summary, Example 3, by considering frequency constraints and frequency modulation resource allocation, effectively alleviates the problem of weak frequency dynamic response and significantly improves the frequency safety and dynamic stability of the system.

[0217] 5. The impact of energy storage-DC collaboration on frequency security constraints.

[0218] In Example 4, in addition to the traditional synchronous machine, energy storage and DC channels also participate in frequency support, thus enhancing the system's frequency regulation capability and response flexibility. Figure 7 It can be seen that the power output of new energy sources has been alleviated, the utilization of wind and solar power during the midday peak period has been significantly improved, the DC transmission curve has risen significantly, and the new energy absorption rate of new energy bases and receiving-end grids has increased by 10% and 9%, respectively. Example 3 shows high unit start-up and shutdown frequency, especially during the midday and evening peak periods. Because Example 3 only considers thermal power frequency regulation resources, the system lacks flexible auxiliary regulation resources, thus causing thermal power units to bear all frequency regulation tasks. Example 4 introduces grid-based energy storage and DC, resulting in a significant reduction in the number of units in operation, especially noticeable between 5 PM and 8 PM. In summary, the synergistic effect of grid-based energy storage and DC significantly improves the system's frequency regulation capability, reduces the system's dependence on thermal power unit frequency regulation resources, and thus achieves multi-source mutual support, flexible and stable frequency regulation.

[0219] 6. Analysis of the impact of energy storage configuration capacity on the coordinated operation of new energy base-receiving end power grid.

[0220] To analyze the economic impact of energy storage capacity on the system's renewable energy absorption rate and total operating cost, Table 4 provides comparative analysis of calculation examples considering different energy storage capacities.

[0221] Table 4 Results of coordinated operation of sending-receiving power grids under different energy storage configurations.

[0222]

[0223] Table 4 shows the renewable energy absorption rate and various costs of the system under different energy storage configurations. Scheme 1, without energy storage, accounts for approximately 55% of the total cost due to wind and solar curtailment penalties, resulting in severe curtailment and a low renewable energy absorption rate of 86%. Scheme 2, with 50MW of energy storage, significantly improves the renewable energy absorption rate, increasing the absorption rates at both the sending and receiving ends by 10% and 6%, respectively. Compared to without energy storage, the cost of wind and solar curtailment penalties is reduced by 48.9%, indicating a significant reduction in these penalties. Scheme 3, with 100MW of energy storage, improves the renewable energy absorption rate at the receiving end and reduces wind and solar curtailment penalties, resulting in a 9.6% reduction in total cost compared to Scheme 2. Scheme 4, with 200MW of energy storage, achieves near-complete absorption of wind power at the receiving end, with a renewable energy absorption rate of approximately 98%, and a slight reduction in various costs. Comparative analysis shows that as the installed capacity of energy storage increases, the utilization rate of renewable energy gradually rises, wind and solar curtailment gradually decreases, and ultimately, the total cost of the system also decreases.

[0224] 7. The impact of virtual inertia delay.

[0225] To analyze the impact of DC virtual inertia delay on the economic efficiency of the system's renewable energy absorption rate and total operating cost, Table 5 provides comparative analysis of calculation examples considering different energy storage capacities.

[0226] Table 5 Results of coordinated operation of sending-receiving power grids under different virtual inertia delays

[0227]

[0228] As shown in Table 5, an increase in virtual inertia delay will postpone the effective intervention of DC virtual inertia and primary frequency regulation of energy storage. To meet frequency security constraints, the system will rely more on thermal power and suppress new energy sources. Therefore, with the increase of DC virtual inertia delay, the total system cost increases, the penalty for wind and solar curtailment increases, and the renewable energy absorption rate decreases. A comprehensive comparison shows that when TB ≤ 200ms, economic efficiency and frequency security are well balanced; when TB ≥ 300ms, the deterioration trend becomes obvious. Therefore, controlling the TB delay within 200ms can ensure both frequency security and economic efficiency of system operation.

[0229] 8. The influence of the lowest frequency point.

[0230] To analyze the impact of the lowest frequency value on the economic efficiency of the system's renewable energy absorption rate and total operating cost, Table 6 provides comparative analysis of calculation examples considering different energy storage capacities.

[0231] Table 6 Results of coordinated operation of the sending-receiving power grid under different minimum frequency values.

[0232]

[0233] As shown in Table 6, the stricter the minimum frequency deviation constraint, the more the system needs to rely on energy storage, DC transmission lines, and rapid support from thermal power to meet frequency safety constraints. Dispatch will actively suppress wind and solar power output, resulting in increased penalties for wind and solar curtailment, higher total costs, and lower grid integration rates. Conversely, relaxing the minimum frequency deviation constraint releases adjustment space for DC and wind / solar power, gradually reducing total costs, significantly decreasing wind and solar curtailment, and simultaneously improving both the sending-end / receiving-end and overall grid integration rates. In summary, considering safety margin and economic efficiency, a minimum frequency limit of 0.6-0.8Hz is optimal: it effectively limits frequency drops while ensuring a high utilization rate of new energy sources.

[0234] With the large-scale grid connection of the Shagohuang power base, wind and solar power fluctuations have impacted the operational stability and frequency security of the receiving-end power grid, highlighting the issues of renewable energy consumption and security in the new power system. Through case studies, the following conclusions are drawn:

[0235] (1) The comparison between Example 1 and Example 2 shows that flexible DC regulation not only improves the utilization rate of DC channels but also effectively reduces the penalty for wind and solar curtailment. However, comparing Example 2 and Example 3 shows that without frequency safety constraints, the variation in RoCoF increases significantly, and Nadir fails to meet safety constraints in most periods. Therefore, flexible DC regulation improves the utilization rate of new energy sources, while setting frequency safety constraints enhances the operational safety and stability of the system.

[0236] (2) Through the coordinated frequency support mechanism of energy storage and DC, the frequency security problem caused by wind and solar fluctuations in the "Shagohuang" new energy base was effectively compensated. The rapid response of primary frequency regulation of energy storage and the virtual inertia of DC not only improved the frequency regulation capability of the system, but also reduced the dependence on thermal power units, increased the system's new energy consumption rate, thereby reducing the penalty for wind and solar curtailment and improving the safety and economy of system operation.

[0237] (3) With the increase in energy storage capacity, the reduction in virtual inertia response delay, and the appropriate relaxation of the allowable deviation at the lowest frequency point, the renewable energy consumption rate of the system has been improved, the curtailment of wind and solar power has gradually decreased, and the cost has also decreased. The application of energy storage in the power system, especially in its role in smoothing renewable energy fluctuations, DC transmission, and improving frequency regulation capabilities, proves that energy storage improves the system's regulation capability and is an important means to achieve efficient renewable energy consumption in the Gobi Desert and ensure the safe operation of the receiving-end power grid.

[0238] Based on the same inventive concept, this invention also provides a dispatching system 800 for coordination between the Shagohuang base and the receiving-end power grid, comprising:

[0239] The inter-regional power transmission model establishment module 810 is used to establish an inter-regional power transmission model for the Shagohuang New Energy Base based on the operation model of the Shagohuang New Energy Base and the DC channel power transmission operation model.

[0240] The frequency response model construction module 820 is used to determine the DC virtual inertia and energy storage frequency regulation power according to the cross-regional transmission model of the Shagohuang New Energy Base, and to construct a two-stage dynamic frequency response model of DC-energy storage coordination based on the DC virtual inertia and energy storage frequency regulation power, the inertia and frequency regulation power of traditional thermal power.

[0241] The scheduling model solving module 830 is used to establish a collaborative scheduling model between the new energy base and the receiving-end power grid based on the cross-regional transmission model of the Shagohuang new energy base and the two-stage dynamic frequency response model of energy storage and direct current coordination; based on frequency security constraints, it solves the collaborative scheduling model between the new energy base and the receiving-end power grid to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid.

[0242] This invention provides a scheduling method and system for coordinating the power grid between the desert and barren land base and the receiving-end power grid. By constructing an integrated wind, solar, thermal and energy storage operation model for the new energy base and flexible operation constraints for DC tiered transmission, and introducing an energy storage-DC collaborative framework under frequency security constraints, it achieves unified optimization and computable solution for power balance and frequency security, thereby improving transmission flexibility, new energy absorption capacity and system operation safety level.

[0243] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0244] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0245] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0246] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0247] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A scheduling method for coordinated operation between the Shagohuang base and the receiving-end power grid, characterized in that, include: Based on the operation model of the Shagohuang New Energy Base and the DC channel power transmission operation model, a cross-regional power transmission model of the Shagohuang New Energy Base is established. Based on the cross-regional power transmission model of the Shagohuang New Energy Base, the DC virtual inertia and energy storage frequency regulation power are determined. Based on the DC virtual inertia and energy storage frequency regulation power, and the inertia and frequency regulation power of traditional thermal power, a two-stage dynamic frequency response model of DC-energy storage coordination is constructed. Based on the cross-regional transmission model of the Shagohuang new energy base and the two-stage dynamic frequency response model of energy storage and direct current coordination, a collaborative scheduling model between the new energy base and the receiving-end power grid is established. Based on frequency security constraints, the collaborative scheduling model between the new energy base and the receiving-end power grid is solved to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid.

2. The method according to claim 1, characterized in that, The operational model of the Shagohuang New Energy Base includes: new energy output constraints, conventional unit operation constraints, and energy storage unit operation constraints; among them, The power output constraints for new energy sources are: in, This represents the actual output power received by renewable energy unit i during time period t. This represents the acceptable output of renewable energy unit i during time period t. This represents the amount of wind and solar power curtailed by renewable energy unit i during time period t. The operating constraints for conventional generating units are: Where v represents the start-stop state of thermal power unit j during time period t, and is a binary 0-1 variable; P j,t s This represents the output of thermal power unit j during time period t; S represents the upper and lower limits of the output of thermal power unit j, respectively; n Indicates the upper limit of primary frequency regulation power of thermal power units; P t PFR This represents the primary frequency regulation power provided by thermal power unit j during time period t; The operating constraints of the energy storage unit are: in, E represents the charging and discharging state of energy storage unit k during time period t, and is a binary 0-1 variable; k,t This represents the capacity of energy storage unit k during time period t; e c e d Δt represents the charging and discharging efficiency of energy storage unit k; Δt represents the time for energy storage charging and discharging power. These represent the upper and lower limits of the energy storage capacity of energy storage unit k, respectively. These represent the upper and lower limits of the charging and discharging power of the energy storage unit k, respectively.

3. The method according to claim 1, characterized in that, The DC power transmission operation model includes: DC channel operation constraints and power balance constraints for new energy bases, among which, The operating constraints for the DC channel are: R max ≤4(17) Among them, P DC,max Indicates the maximum transmission capacity of the DC channel; R represents the DC power transmitted during the r-th time interval; max Indicates the maximum number of adjustments to the DC channel's external power output within 24 hours; DR DC UR DC These represent the maximum uphill and downhill ramp rates of the DC channel, respectively. The power balance constraint of the new energy base is: The left side represents the power output of the new energy base, and the right side represents the power transmitted via the DC channel; π RES π G π ES These respectively represent new energy power units, thermal power units, and energy storage units.

4. The method according to claim 1, characterized in that, Based on the cross-regional power transmission model of the Shagohuang new energy base, the DC virtual inertia and energy storage frequency regulation power are determined, including: The primary frequency regulation of the synchronous machine in the cross-regional transmission model of the Shagohuang New Energy Base is essentially the same as the primary frequency regulation of the local synchronous machine at the receiving end, and its response power is: in, These represent the PFR capacity of the receiving and sending end synchronizers, respectively; T db1 T1 represents the primary frequency modulation delay of the transmitting and receiving end synchronizers; T1 represents the primary frequency modulation ramp-up time of the transmitting and receiving end synchronizers; ΔP PFR This indicates the first frequency modulation of the synchronous machine at the sending and receiving ends; The response mode of primary frequency regulation for energy storage is as follows: in, Indicates the primary frequency regulation capacity of energy storage; Indicates the primary frequency regulation capacity of the energy storage unit; T db2 T1 represents the frequency regulation delay of energy storage; T2 represents the frequency regulation ramp-up time of energy storage. This indicates primary frequency regulation for energy storage.

5. The method according to claim 1, characterized in that, Based on the aforementioned DC virtual inertia and energy storage frequency regulation power, and the inertia and frequency regulation power of traditional thermal power, a two-stage dynamic frequency response model for DC-energy storage coordination is constructed, including: The inertia of a synchronous machine is related to the number of times the unit starts and stops, exhibiting a discrete characteristic: Among them, v j Indicates the start-up status of the thermal power synchronous generator unit; H g,j P represents the inertial time constant of a thermal power unit. max Indicates the installed capacity of thermal power units; The DC virtual inertia is provided by the DC capacitor. The voltage reference value of the fixed voltage station is linked to the frequency change of the AC power grid. When the DC voltage changes, the DC capacitor will provide inertial support power. The equation (24) can be obtained by combining the generator rotor motion equation with the DC capacitor charging and discharging power: After simplification, we obtain equation (25): Virtual inertia exhibits continuity: H dc =H c S n (26) Among them, H dc Represents the DC virtual inertia time constant; C represents the DC capacitance value; U dc0 Indicates the reference value of rated DC voltage; f0 indicates the rated frequency of the system; U dc,ref (t) represents the DC voltage reference value; N represents the number of thermal power units; H c S represents the virtual inertial time constant of the DC capacitor. n Indicates the capacity of the DC converter station; Based on the virtual inertial delay of the DC channel, the rotor motion equations with two-stage frequency dynamic changes are shown in equations (27)-(28): Among them, H, H dc These represent the receiving-end synchronous machine inertia and DC virtual inertia, respectively, in MWs; Δf represents the receiving-end grid frequency difference; f0 represents the rated frequency; P e T represents the power of the receiving-end power grid disturbance. B Indicates the DC virtual inertial response delay; H represents the inertial time constant of a constant-speed pumped-storage unit. g P is the inertial time constant of a conventional unit; s,n P g,n These are the rated power of the constant-speed pumped storage / conventional units, respectively.

6. The method according to claim 1, characterized in that, The two-stage dynamic frequency response model for storage-DC co-operation includes system frequency security indicators such as frequency change rate constraints, frequency minimum point constraints, and quasi-steady-state constraints. The frequency change rate constraint, in the presence of a response delay in DC virtual inertia, is determined solely by the disturbance power and the inertia of the thermal power synchronous unit in the initial stage of the disturbance: Frequency minimum point constraint: After the system is subjected to a disturbance, in order to prevent the frequency from continuing to drop, a frequency minimum point threshold needs to be set and limited. |Δf(t nadir )|≤Δf max (30) To obtain the minimum frequency constraint, the DC virtual inertial delay is first disregarded, and the dynamic frequency response equation is written as follows (31): Assume the lowest frequency point is t nadir Integrating the above equation, we obtain equation (32): The constraint on the lowest point of the received-end frequency, without considering virtual inertial delay, is obtained as shown in equation (33): Considering the virtual inertial delay, the above equation is corrected to the following equation (34): Quasi-steady-state constraints, to ensure that the frequency can recover normally to the rated frequency after falling to the lowest frequency point, must meet the following constraints:

7. The method according to claim 1, characterized in that, The collaborative dispatch model between renewable energy bases and receiving-end power grids includes: an objective function aimed at minimizing total operating costs, constraints on inter-regional power transmission from renewable energy bases, and constraints on the collaborative operation of renewable energy bases and receiving-end power grids. The objective function that aims to minimize total operating cost is: Where, λ s Indicates the probability of different scenarios occurring; This represents the operating cost of thermal power unit j during time period t under scenario s, where a, b, and c represent the power generation cost coefficients of the thermal power unit, respectively; C SUit C SDit Let c represent the start-up and shutdown costs of thermal power unit j during time period t; curt These represent the penalty coefficients for wind and solar power curtailment; The constraints on cross-regional power transmission from new energy bases specifically include: the expression corresponding to the operational constraints of conventional generating units is: The expression corresponding to the operating constraints of the energy storage unit is: The expression corresponding to the DC power transmission constraint is: Among them, S n Indicates the upper limit of primary frequency regulation power of thermal power units; P t PFR P represents the primary frequency regulation power provided by thermal power unit j during time period t; Δt1 represents the discharge time of the primary frequency regulation power of the energy storage unit; t BES P represents the primary frequency regulation power provided by energy storage unit k during time period t; t EX This indicates the total PFR capacity provided by the new energy base; Constraints on the coordinated operation of new energy bases and receiving ends specifically include: the expression corresponding to line power flow constraints is: PL l,t =(θ i,t -θ j,t ) / x l ,i ref,l =0 (42) The expression corresponding to the power balance constraint of the receiving-end grid node is: Where, θ i,t θ j,t The x-axis represents the phase angle of the node connected to line l. l Indicates the reactance of line l; θ represents the maximum transmission power capacity of line l; ref,l The phase angle of the equilibrium node; This represents the active power flow of line l merging into node nd during time period t in scenario s; π L Represents the set of receiving-end power grid lines; I nd This represents a binary variable, indicating whether the DC channel is connected to node nd; This represents the load of node nd during time period t in scenario s.

8. The method according to claim 1, characterized in that, Based on frequency security constraints, the collaborative scheduling model between the new energy base and the receiving-end power grid is solved to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid, including: Based on the fact that the minimum frequency point constraint is a nonlinear constraint, the collaborative scheduling model between the new energy base and the receiving-end power grid is transformed into the following formula: Replacing the constraints with A, B, and C, we obtain equations (46)-(48): B=P PFR / T2 (47) The above formula can be transformed into: AB≥C 2 (49) (A+B) 2 -(A-B) 2 ≥4C 2 (50) 9. A dispatching system for coordinated operation between a desert base and a receiving-end power grid, characterized in that, include: The inter-regional power transmission model establishment module is used to establish an inter-regional power transmission model for the Shagohuang New Energy Base based on the operation model of the Shagohuang New Energy Base and the DC channel power transmission operation model. The frequency response model construction module is used to determine the DC virtual inertia and energy storage frequency regulation power based on the cross-regional transmission model of the Shagohuang New Energy Base, and to construct a two-stage dynamic frequency response model of DC-energy storage coordination based on the DC virtual inertia and energy storage frequency regulation power, the inertia and frequency regulation power of traditional thermal power. The scheduling model solving module is used to establish a collaborative scheduling model between the new energy base and the receiving-end power grid based on the cross-regional transmission model of the Shagohuang new energy base and the two-stage dynamic frequency response model of energy storage and direct current coordination; based on frequency security constraints, it solves the collaborative scheduling model between the new energy base and the receiving-end power grid to obtain the collaborative scheduling parameters between the Shagohuang base and the receiving-end power grid.

10. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the scheduling method for coordination between the Shagohuang base and the receiving-end power grid as described in any one of claims 1 to 8.

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