Robust Operating Region Construction Method and Device for Flexibility Resources in New Energy Power Systems

Abstract

The present invention discloses a method and device for constructing a robust operation domain of flexible resources in a new energy power system, which relates to the field of power system operation control. The method includes: obtaining parameters of a generator set, an energy storage system and an HVDC transmission system, and constructing a flexible resource operation domain model; obtaining an uncertainty set of the power generation output of a new energy power station and the substation bus load; obtaining power grid topology information, and constructing multi-period power balance and line power flow safety constraints; constructing power values or energy values as uncertain quantities related to operation domain boundary variables, and calculating the robust operation domain of flexible resources by means of decision-related uncertainty and robust optimization methods; and performing operation control on the generator set, the energy storage system and the HVDC transmission system according to the robust operation domain. The present invention can meet the unexpected requirements of dynamic regulation of a new energy power system under the action of a stochastic process, and provides a simple and easy-to-implement strategy for flexible resource regulation and new energy consumption.

Description

Technical Field

[0001] The present invention relates to the field of power system operation control, and particularly to a method and device for constructing a robust operation domain of flexibility resources in a new energy power system. Background Art

[0002] New energy power generation represented by wind power and photovoltaic power is an effective technology for realizing carbon emission reduction in the power system. At the same time, the uncontrollability and randomness of new energy power generation output have brought great challenges to the power balance between power generation and consumption in the power system. New technologies such as flexible transformation of thermal power units, large-scale energy storage, flexible DC transmission, and demand response provide flexibility resources for the spatio-temporal complementarity and balance of power generation and consumption, and are the basic guarantee for new energy consumption. However, limited by the inherent technical constraints of flexibility resources (such as power ramp constraints of generator sets, capacity constraints of energy storage systems, power transmission constraints of high-voltage DC transmission systems, etc.), unreasonable operation control strategies will cause problems of spatial imbalance and short-sightedness in time of flexibility resources, restricting the efficient exertion of their flexibility and triggering the risk of power and energy imbalance in the system.

[0003] Since the output of new energy power generation is a random process, the dispatcher of the power system cannot determine in advance the power time series curve of flexibility resources matching the new energy power generation. The inventor has found through research that by constructing an operation domain model (i.e., a power or energy time series interval in the form of a band) for flexibility resources and obtaining a robust operation domain through optimization calculation, and realizing the coordinated control of the operation point and regulation reserve of flexibility resources with the robust operation domain, the spatio-temporal coordination problem of the time series operation control of the new energy power system under strong uncertain conditions can be effectively solved, the economic and reliable consumption of new energy can be realized, and the safe operation of the power system can be ensured. The robust operation domain of flexibility resources provides a global strategy of "responding to all changes with constancy" for the dispatcher, that is, coping with a large number of scenarios of new energy power generation output with the operation domain constructed in advance (weekly, daily, hourly).

[0004] The existing robust scheduling strategies can only give the unit start-stop plan, the power time series curve (i.e., a single operation point) of flexibility resources under a specific new energy power generation output scenario, and the reserve capacity corresponding to a specific operation point. Summary of the Invention

[0005] Aiming at the above deficiencies in the prior art, a method and device for constructing a robust operation domain of flexibility resources in a new energy power system provided by the present invention can meet the unexpected requirements of the dynamic regulation and control of the new energy power system under the action of a random process, and provide a simple and easy-to-execute strategy for the regulation and control of flexibility resources and new energy consumption.

[0006] To achieve the above invention purpose, the technical solution adopted by the present invention is: a method for constructing a robust operation domain of flexibility resources in a new energy power system, comprising the following steps:

[0007] S1: Obtain the parameters of the generator set, energy storage system, and HVDC transmission system, and construct a flexible resource operation domain model;

[0008] S2: Obtain the uncertainty sets of the new energy power generation output of the new energy power station and the substation bus load;

[0009] S3: Obtain the power grid topology information, and construct the multi-period power balance and line power flow security constraints;

[0010] S4: Based on the flexible resource operation domain model, uncertainty sets, and power balance and line power flow security constraints, construct the power value or energy value as an uncertain quantity related to the boundary variables of the operation domain, and calculate the robust operation domain of the flexible resource by means of decision-related uncertainty and robust optimization methods;

[0011] S5: Perform operation control on the generator set, energy storage system, and HVDC transmission system according to the robust operation domain.

[0012] Further, the flexible resource operation domain model in S1 includes:

[0013] For non-energy-limited generator sets, construct the upper and lower boundaries of the hourly power generation power interval ;

[0014] For energy-limited generator sets, construct the upper and lower boundaries of the hourly power generation quantity interval ;

[0015] For the energy storage system, construct the upper and lower boundaries of the hourly energy level interval ;

[0016] For the HVDC transmission system, construct the upper and lower boundaries of the hourly transmitted power quantity interval 。

[0017] Further, obtaining the uncertainty sets of the new energy power generation output of the new energy power station and the substation bus load in S2 includes any of the following methods:

[0018] Based on the new energy power generation output of the new energy power station and the substation bus load probability prediction system, obtain the hourly power interval under a given probability confidence level within the regulation time domain of each power station and bus, and use the power interval as the vector corresponding elements as the upper and lower limits to obtain the uncertainty set , where is the index of the elements of the vector , is any symbol;

[0019] Based on the historical data of the power generation output of new energy power stations and the substation bus loads, statistical analysis is carried out to construct a polyhedron or ellipsoidal uncertainty set, and an uncertainty set in the form of is obtained, where the matrix and the vector , the positive definite matrix and the scalar are parameters obtained from statistical analysis.

[0020] Furthermore, the construction of multi-period power balance and line power flow security constraints in S3 is as follows:

[0021]

[0022] where and are matrices, is a vector, is the decision variable related to the active power of flexible resources.

[0023] Furthermore, S4 includes the following sub-steps:

[0024] S41: For non-energy-constrained generating units, the technical constraints related to the active power in time period are as follows:

[0025]

[0026] where is the unified index of flexible resources, is the unified symbol of the active power and power boundary decision variables, is the active power of flexible resource in time period , is the active power of flexible resource in time period , and are the obtained up and down power ramp rate data, is a binary variable representing the available situation of flexible resources, and are the obtained power upper and lower limit data, and are the lower and upper boundaries of the active power of flexible resource in time period ;

[0027] Taking the active power in time period as an uncertain quantity, an uncertainty set of is constructed with the operation domain boundary variables as parameters:

[0028]

[0029] wherein, is the uncertainty set of and are flexible resources at time period the lower and upper bounds of the active power;

[0030] S42: For energy - limited generating units, energy storage systems, and HVDC transmission systems, the technical constraints related to the active power at time period are:

[0031]

[0032] wherein, is a linear function describing the relationship between energy and power, is the energy at time period is the energy at time period is the energy at time period is the energy at time period and are the lower and upper bounds of the energy of the energy - limited flexible resource at time period and are the obtained upper and lower limit data of energy;

[0033] Taking the energy at time period as an uncertain quantity, and using the operation domain boundary variables as parameters to construct the uncertainty set of

[0034]

[0035] wherein, is the uncertainty set of, and are the lower and upper bounds of the energy of the energy - limited flexible resource at time period

[0036] S43: Establish a three - layer two - stage robust optimization model as:

[0037]

[0038] wherein, is the robust operation domain decision variable, , and are decision - related uncertainty parameters characterizing the external uncertainties of new energy and load, and the uncertainties of flexibility resources respectively. is the decision variable for the actual regulation of flexibility resources. is the system operation cost. is the uncertainty set of power. is the uncertainty set of energy. , and are vectors of power, energy, and operating condition indication variables. is the vector of energy and operating condition indication variables. is the binary indication variable of the power generation and consumption operating condition of flexibility resources. , , , , , , , , and are the coefficient matrices or right - hand - side vectors of relevant constraints.

[0039] S44: Iteratively solve the three - layer two - stage robust optimization model through the column - row generation algorithm to obtain the robust operation domain of flexibility resources , where and are the optimal values of the lower and upper bounds of the power of the flexibility resource vector. and are the optimal values of the lower and upper bounds of the energy of the flexibility resource vector.

[0040] Furthermore, in step S5, the operation control of the generator set, energy storage system, and HVDC transmission system is carried out according to the robust operation domain, including any of the following control strategies:

[0041] Time - series decoupled control strategy: Based on the measured values of new energy and load in the current period, regulate the flexibility resources under the condition of satisfying the robust operation domain.

[0042] Model predictive control strategy: Based on the predicted data of new energy and load in the current and future multiple periods, regulate the flexibility resources under the condition of satisfying the robust operation domain.

[0043] The technical solution adopted by the present invention is also: A device for constructing the robust operation domain of flexibility resources in a new - energy power system, the device includes:

[0044] Memory: Used to save computer programs.

[0045] Processor: configured to execute the computer program to implement the method for constructing the robust operation domain of the flexibility resources in the new energy power system as described above.

[0046] The beneficial effects of the present invention are as follows: 1) High model accuracy, capable of simultaneously considering the spatio-temporal correlation characteristics of the random process of new energy power generation output and the unexpectedness of the sequential operation of the new energy power system; 2) High richness of decision-making information, capable of giving the set of operation points of various flexibility resources at all times, and realizing the spatio-temporal coordinated optimization of operation points and regulation reserve; 3) Strong strategy intuitiveness, capable of explicitly representing the mapping between the uncertainty set of new energy power generation output and the operation domain of flexibility resources; 4) Facilitating engineering deployment, directly providing guiding strategies for the real-time regulation of flexibility resources and new energy consumption; 5) Strong robustness and adaptability. The proposed method can construct a robust operation domain for various flexibility resources in the new energy power system, ensure the dynamic full consumption of new energy power generation within the expected fluctuation range, and avoid the risk of power and electricity imbalance. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of a method for constructing the robust operation domain of the flexibility resources in a new energy power system according to the present invention.

[0048] Figure 2 It is a schematic diagram of a model predictive control strategy based on the robust operation domain of flexibility resources provided by an embodiment of the present invention.

[0049] Figure 3 It is a schematic diagram of the robust operation domain of a generator set provided by an embodiment of the present invention.

[0050] Figure 4 It is a schematic diagram of the robust operation domain of an energy storage system provided by an embodiment of the present invention.

[0051] Figure 5 It is a schematic diagram of the robust operation domain of an HVDC transmission system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0053] Embodiment 1, as Figure 1 shown, a method for constructing the robust operation domain of the flexibility resources in a new energy power system includes the following steps:

[0054] S1: Obtain the parameters of the generator set, energy storage system, and HVDC transmission system, and construct a model of the operation domain of the flexibility resources;

[0055] S2: Obtain the uncertainty sets of the new energy power station power generation output and the substation bus load;

[0056] S3: Obtain the power grid topology information and construct the power balance and line power flow security constraints for multiple time periods;

[0057] S4: Based on the flexible resource operation domain model, the uncertainty set, and the power balance and line power flow security constraints, construct the power value or energy value as an uncertain quantity related to the operation domain boundary variables, and calculate the robust operation domain of the flexible resources by means of decision-related uncertainty and robust optimization methods;

[0058] S5: Conduct the operation control of the generator sets, energy storage systems, and HVDC transmission systems according to the robust operation domain.

[0059] Obtain the parameters of the generator sets, energy storage systems, and HVDC transmission systems, including: for the generator sets (or power plants), obtain the upper and lower limits of the hourly generated power, the upper and lower power ramp rates, and the upper and lower limits of the cumulative generated energy in the last time period. For the energy storage systems (including pumped-storage units), obtain the upper and lower limits of the hourly power generation and consumption, the upper and lower power ramp rates, and the upper and lower limits of the hourly energy level (or the water volume of the pumped-storage power station). For the HVDC transmission system, obtain the upper and lower limits of the hourly power generation and consumption of the transmission line, the upper and lower power ramp rates, and the upper and lower limits of the cumulative transmitted power in the last time period. The above parameters can be obtained through the energy management system, market clearing system, etc. of the power dispatching agency.

[0060] Construct the flexible resource operation domain model, and its specific form is the decision variables of the upper and lower boundaries of the power or energy time series interval. The operation domain models of various flexibilities are as follows.

[0061] The flexible resource operation domain model in S1 includes:

[0062] For non-energy-limited generator sets (such as thermal power with unrestricted primary energy in the short term or no daily power generation constraint), construct the upper and lower boundaries of the hourly generated power interval ;

[0063] For energy-limited generator sets, construct the upper and lower boundaries of the hourly generated energy interval , where 、 are the indices of the generator set and the regulation time period respectively;

[0064] For the energy storage system, construct the upper and lower boundaries of the hourly energy level interval , where 、 are the indices of the energy storage system and the regulation time period respectively;

[0065] For the HVDC transmission system, construct the upper and lower boundaries of the hourly transmitted power interval , where 、 They are the indexes of the HVDC transmission line and the regulation period respectively.

[0066] In step S2, an uncertainty set of the power generation output of the new energy power station and the substation bus load is obtained, and the uncertain quantities of the power generation output of the new energy power station and the substation bus load are constructed into a high-dimensional spatio-temporal vector. The set of all possible values of this vector is defined as the uncertainty set, denoted as . The uncertainty set is constructed through two alternative schemes:

[0067] Scheme 1: Based on the probability prediction system of the power generation output of the new energy power station and the substation bus load, the per-period power interval under a given probability confidence level within the regulation time domain of each power station and bus is obtained, and the power interval is used as the upper and lower limits of the corresponding elements of the vector to obtain the uncertainty set , where is the index of the elements of the vector , and is an arbitrary symbol;

[0068] Scheme 2: Based on the historical data of the power generation output of the new energy power station and the substation bus load, statistical analysis is carried out to construct a polyhedral or ellipsoidal uncertainty set, and an uncertainty set in the form of is obtained, where the matrix and the vector , the positive definite matrix and the scalar are parameters obtained from statistical analysis.

[0069] Grid topology information is obtained, and multi-period power balance and line power flow security constraints are constructed, specifically including: obtaining the corresponding voltage level transmission grid topology information from the energy management system, market clearing system, etc. of the power dispatching agency, including the connection relationship between transmission lines and buses, voltage levels, transmission line capacities, and transmission line impedances.

[0070] Using the transmission grid topology information to construct a linearized multi-period power flow model to characterize the power generation and consumption balance condition and the line power flow security constraint. The model is a linear system in the form of .

[0071] The multi-period power balance and line power flow security constraints constructed in step S3 are:

[0072]

[0073] where and are matrices, is a vector, Decision variables related to the active power of flexibility resources.

[0074] The S4 includes the following sub-steps:

[0075] S41: For non-energy-constrained generating units, the operation domain boundary variable is the active power boundary of the generating unit . To represent the power upper and lower limit constraints and the power ramp constraint, and to avoid using the actual active power values across time periods, it is necessary to construct the active power of the generating unit in the previous time period as an uncertain quantity related to the power boundary decision variable , which serves as the input information for the decision-making module in the time period . The technical constraints related to the active power in the time period are as follows:

[0076]

[0077] where is the unified index of flexibility resources, is the unified symbol of the active power and power boundary decision variables, is the active power of flexibility resource in the time period , is the active power of flexibility resource in the time period , and are the obtained up and down power ramp capacity data, is a binary variable representing the availability of flexibility resources, related to the start-stop state of the generating unit, and are the obtained power upper and lower limit data, and are the lower and upper boundaries of the active power of flexibility resource in the time period ;

[0078] Taking the active power in the time period as an uncertain quantity, construct the uncertainty set with the operation domain boundary variable as a parameter:

[0079]

[0080] where is the uncertainty set of , and are the active power of flexibility resource in the time period ​​​The lower and upper boundaries of the active power;

[0081] S42: For energy-constrained generating units, energy storage systems, and HVDC transmission systems, during a time period The technical constraints related to the active power are as follows:

[0082] For energy-constrained flexibility resources (including energy-constrained generating units, energy storage systems, HVDC transmission systems, etc.), the operation domain boundary variables are the energy boundary decision variables for each time period, including the upper and lower boundaries of the cumulative power generation interval of the generating unit The upper and lower boundaries of the energy level interval stored in the energy storage system The upper and lower boundaries of the cumulative transmitted power interval of the HVDC transmission line . The energy values of the previous several time periods (denoted as ) are constructed into uncertainties related to the energy boundary decision variables , which are used as the input information of the decision-making module for the time period to characterize the active power and related technical constraints of the flexibility resource during the time period . Specifically, the active power of the th flexibility resource during the time period can be characterized by its energy during the time period and the energy value during the time period , that is . The function is a linear function describing the relationship between energy and power; for the energy storage system, affected by the power generation and consumption efficiency, this function is a piecewise linear function, and a binary variable indicating the power generation and consumption conditions needs to be introduced to describe the function . Using the above conversion and characterization techniques, the energy state quantities of flexibility resources in a large number or infinite number of scenarios are treated as uncertainties, ensuring that the active power regulation of flexibility resources is unanticipated, and thus meeting the basic logic of time-sequence operation control under dynamic non-deterministic conditions. Furthermore, the power upper and lower limit constraints, power ramp constraints, and energy constraints of flexibility resources can be uniformly characterized by the following three inequalities:

[0083]

[0084] Among them, is a linear function describing the relationship between energy and power, is the energy during the time period , is the energy during the time period , is the energy during the time period , and is an energy - limited flexible resource At time period the lower and upper energy bounds, and are the acquired upper and lower energy limit data;

[0085] Take the energy at time period as an uncertain quantity, and construct using the operation domain boundary variables as parameters uncertainty set:

[0086]

[0087] where, is uncertainty set, and is an energy - limited flexible resource At time period the lower and upper energy bounds;

[0088] S43: Establish a three - layer two - stage robust optimization model as:

[0089]

[0090] where, is the robust operation domain decision variable, , and are respectively the decision - related uncertainty parameters characterizing the external uncertainties of new energy and load and the flexibility resource, is the decision variable for the actual regulation of the flexibility resource, is the system operation cost, is the uncertainty set of power, is the uncertainty set of energy, , and are the vectors of power, energy, and operating condition indicator variables, is the vector of energy and operating condition indicator variables, is the binary indicator variable of the power generation and consumption operating condition of the flexibility resource, , , , , , , , , and is the coefficient matrix or right - hand - side vector of relevant constraints, specifically: the active - power - related technical constraints of non - energy - limited power generation units, the upper and lower power limits, power ramp constraints, and energy constraints of flexible resources of energy - limited flexible resources, and the scalar - expression data such as the constraints of the uncertainty set form the coefficient matrix and the right - hand - side vector;

[0091] In the formula, the first - row constraint represents the constraint conditions of the decision variables in the robust operation domain and their coupling relationship with the regulation decision of flexible resources. The second - row constraint is the system power balance and line - flow constraint jointly described by the active power of flexible resources, new - energy power generation, bus load, and grid topology. The third - row is the coupling relationship between the energy and power of flexible resources. The fourth - row constraint describes the coupling relationship between the power regulation decision of flexible resources at time period and the power unknown quantity at time period . The fifth - row constraint describes the coupling relationship among the decision variable of the robust operation domain of flexible resources at time period , the energy regulation decision at time period , and the energy unknown quantity at time period and time period .

[0092] S44: Iteratively solve the three - layer two - stage robust optimization model through the column - and - row generation algorithm to obtain the robust operation domain of flexible resources , where and are the optimal values of the lower and upper boundaries of the power of the flexible - resource vector, and are the optimal values of the lower and upper boundaries of the energy of the flexible - resource vector.

[0093] As Figure 2 shows, the robust operation domain provides the robust upper and lower boundary vectors of the power interval of non - energy - limited power generation units and the robust upper and lower boundary vectors of the energy interval of energy - limited flexible resources.

[0094] The basic strategy of operation control is to maintain the power or energy of flexible resources within the corresponding robust operation domain at each time period. Furthermore, according to the new - energy power generation and bus load observed in real - time operation, optimize and adjust the active power of flexible resources to achieve new - energy consumption, power generation - consumption balance, and line - flow safety. Two alternative solutions can be specifically adopted.

[0095] The operation control of the generator set, energy - storage system, and HVDC transmission system according to the robust operation domain in S5 described above includes any of the following control strategies:

[0096] Scenario 1: Sequential decoupling control strategy. Based on the measured values of new energy and load in the current period, flexibility resources are regulated under the condition of meeting the robust operation region.

[0097] The sequential decoupling control strategy means that only the current period is considered in real-time operation control, without considering subsequent periods. Denote the current period as , obtain the measured values of new energy and load , obtain the current period The known values of the power and energy of flexibility resources in the previous several periods . Furthermore, according to the robust operation region of period , regulate flexibility resources. With the goal of minimizing the system operation cost of period , under the premise of satisfying the power upper and lower limit constraints, power ramp constraint, and energy constraint of flexibility resources themselves, regulate the power and energy values of flexibility resources in period within the robust operation region, and meet system requirements such as power generation and consumption balance, line power flow safety, and new energy accommodation;

[0098] Scenario 2: Model predictive control strategy. Based on the predicted data of new energy and load in the current and future multiple periods, flexibility resources are regulated under the condition of meeting the robust operation region.

[0099] The model predictive control strategy means that not only the current period but also subsequent periods are considered in real-time operation control. Denote the current period as , and the number of forward-looking periods as . Obtain the measured values of new energy and load , obtain the current period The known values of the power and energy of flexibility resources in the previous several periods , obtain the predicted data of new energy and load in the subsequent periods. Furthermore, according to the robust operation region of period , regulate flexibility resources. With the goal of minimizing the sum of the system operation cost of period and the expected value of the system operation cost of future periods , under the premise of satisfying the power upper and lower limit constraints, power ramp constraint, and energy constraint of flexibility resources themselves, regulate the expected power and energy values of flexibility resources in period within the robust operation region, and only deploy the flexibility resource regulation strategy of period , meeting system requirements such as power generation and consumption balance, line power flow safety, and new energy accommodation.

[0100] Both Solution 1 and Solution 2 can ensure the robustness in subsequent periods, while Solution 2 can release a greater adjustment ability of flexible resources. Solution 2 is the preferred solution recommended by the present invention.

[0101] In an embodiment of the present invention, as Figures 3 - 5 shown, the robust operation regions of non-energy-constrained power generation units and energy-constrained flexible resources are determined by the present invention, specifically the upper and lower power boundaries of non-energy-constrained power generation units in each period, the upper and lower energy boundaries of energy storage systems in each period, and the upper and lower energy boundaries of HVDC transmission systems in each period.

[0102] Embodiment 2, a device for constructing a robust operation region of flexible resources in a new energy power system, the device includes:

[0103] A memory: used to store computer programs;

[0104] A processor: used to execute the computer program to implement the method for constructing the robust operation region of flexible resources in the new energy power system as described above.

[0105] The robust operation region method proposed by the present invention can simultaneously consider the spatio-temporal coupling characteristics of the random process of new energy power generation output and the unexpectedness of the sequential operation of the new energy power system, can give the operation regions of various flexible resources in all periods (i.e., the set of operation points in the spatio-temporal dimension), and can explicitly represent the mapping between the uncertainty set of new energy power generation output and the operation regions of flexible resources, providing direct guidance for power and energy balance, real-time operation control, and new energy consumption under dynamic uncertain conditions.

[0106] Those of ordinary skill in the art will realize that the embodiments described herein are for helping the reader understand the principles of the present invention, and it should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the protection scope of the invention.

Claims

1. A method for constructing a robust operation region of flexibility resources in a new energy power system, characterized in that It includes the following steps: S1: Obtain the parameters of the generator set, energy storage system, and HVDC transmission system, and construct a flexible resource operation domain model; The flexible resource operation domain model in S1 includes: For non-energy-constrained generating units, construct the upper and lower boundaries of the hourly generating power intervals For an energy-limited power generation unit, construct the upper and lower boundaries of the power generation interval for each time period For the energy storage system, construct the upper and lower boundaries of the energy level intervals for each time period For the HVDC transmission system, construct the upper and lower boundaries of the hourly transmitted power intervals S2: Obtain the uncertainty sets of the new energy power station's power generation output and the substation bus load; S3: Obtain the power grid topology information and construct the multi-period power balance and line power flow security constraints; S4: Based on the flexible resource operation domain model, uncertainty sets, and power balance and line power flow security constraints, construct the power value or energy value as an uncertain quantity related to the operation domain boundary variables, and calculate the robust operation domain of the flexible resources by means of decision-related uncertainty and robust optimization methods; The following sub-steps are included in S4: S41: For non-energy-constrained generator sets, the technical constraints related to the active power in time period t are: Among them, i is the unified index of flexibility resources, p is the unified symbol of active power and power boundary decision variables, p i,t is the active power of flexibility resource i at time t, p i,t-1 is the active power of flexibility resource i at time t-1, P i RampDn and P i RampUp are the obtained up and down power ramp rate data, z i,t is a binary variable representing the availability of flexibility resources, and are the obtained power upper and lower limit data, and are the lower and upper boundaries of the active power of flexibility resource i at time t; Take the active power at time period t-1 as an uncertain quantity, and construct the uncertainty set with the operating region boundary variables as parameters: where P i,t-1 is the uncertainty set of and are the lower and upper bounds of the active power of flexible resource i at time period t - 1; S42: For energy-constrained generator sets, energy storage systems, and HVDC transmission systems, the technical constraints related to the active power in time period t are: Among them, η(·) is a linear function describing the relationship between energy and power, and e i,t is the energy at time period t, is the energy at time period t - 1, is the energy at time period t - 2, and are the lower and upper boundaries of the energy of the energy - limited flexibility resource i at time period t, and are the upper and lower limit data of the obtained energy; Take the energy at time period t-1 as an uncertain quantity and construct an uncertainty set with the operating region boundary variables as parameters: Among them, E i,t-1 is the uncertainty set of, and are the lower and upper energy bounds of the energy-limited flexibility resource i at time period t - 1; S43: Establish a three-layer two-stage robust optimization model as: Among them, x is the decision variable of the robust operation region, ξ, and are the decision-related uncertainty parameters representing the external uncertainties of new energy and load and the flexibility resources respectively, y is the decision variable of the actual regulation of flexibility resources, f cost is the system operation cost, P(·) is the uncertainty set of power, E(·) is the uncertainty set of energy, y p 、y e and y u are the vectors of power, energy and operating condition indicator variables, y e,u is the vector of energy and operating condition indicator variables, u i,t is the binary indicator variable of the power generation and consumption operating condition of flexibility resources, C, D, V p 、W p 、U e 、V e and W e are the coefficient matrices of relevant constraints, d, w p and w e are the right-hand vectors, is an arbitrary sign, ξ is a vector, F and G are matrices, and g is a vector; S44: Iteratively solve the three - layer two - stage robust optimization model through the column - row generation algorithm to obtain the robust operation domain of the flexibility resources [p inf* , p sup* , e inf* , e sup* , where p inf* and p sup* are the optimal values of the lower and upper bounds of the power of the flexibility resource vector, and e inf* and e sup* are the optimal values of the lower and upper bounds of the energy of the flexibility resource vector; S5: Perform the operation control of the generator set, energy storage system, and HVDC transmission system according to the robust operation domain.

2. The method for constructing the robust operation region of the flexibility resources of the new energy power system according to claim 1, wherein The obtaining of the uncertainty sets of the new energy power station's power generation output and the substation bus load in S2 includes any of the following methods: Based on the power probability prediction system of new energy power stations and substation bus loads, the power intervals for each time period within the regulation time domain of the power station and the bus are obtained under a given probability confidence level, and the power intervals are used as the upper and lower limits of the corresponding elements ξ of the vector ξ j to obtain the uncertainty set where j is the index of the elements of the vector ξ, is an arbitrary symbol; Based on the historical data of the power generation output of new energy power stations and the substation bus loads, statistical analysis is carried out to construct a polyhedron or ellipsoidal uncertainty set, and an uncertainty set in the form of Ξ={ξ|Aξ≤b, ξB -1 ξ≤c} is obtained, where the matrix A, the vector b, the positive definite matrix B, and the scalar c are parameters obtained from statistical analysis.

3. The method for constructing the robust operation region of the flexibility resources of the new energy power system according to claim 2, wherein The construction of the multi-period power balance and line power flow security constraints in S3 is: Fy p +Gξ = g。 4. The method for constructing the robust operation region of flexible resources in a new energy power system according to claim 3, wherein, The operation control of the generator set, energy storage system, and HVDC transmission system according to the robust operation domain in S5 includes any of the following control strategies: Time-series decoupled control strategy: Based on the measured values of new energy and load in the current time period, regulate the flexible resources under the condition of satisfying the robust operation domain; Model predictive control strategy: Based on the predicted data of new energy and load in the current and future multiple time periods, regulate the flexible resources under the condition of satisfying the robust operation domain.

5. A robust operating region construction device for flexibility resources of a new energy power system, characterized in that The device includes: Memory: Used to store computer programs; Processor: Used to execute the computer program to implement the method for constructing the robust operation domain of the flexible resources of the new energy power system as described in any one of claims 1-4.

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