Coordinated optimization method and system of alternating current and direct current receiving end system considering direct current regulation

Abstract

The invention discloses a coordinated optimization method and system of an alternating current and direct current receiving end system considering direct current regulation. The method comprises the following steps: establishing an internal resource mathematical model representing the operation constraint of each resource based on the resource attribute of each resource in a receiving-end power grid; the method comprises the following steps: respectively establishing a mathematical model based on a direct-current feed-in channel and a data model based on an alternating-current feed-in channel for external access electric energy based on channel characteristics of the external electric energy accessed to a receiving-end power grid; based on the built internal resource mathematical model, the mathematical model of the direct current feed-in channel and the mathematical model of the alternating current feed-in channel, a dispatching model of the receiving end power grid is built; and solving the objective function to determine a scheduling scheme meeting the requirement of minimizing the operating cost of the receiving-end power grid in the scheduling period. According to the invention, the direct-current feed-in electric energy is regarded as a controllable resource with the power regulation capability, the regulation capability of direct-current feed-in can be effectively exerted, peak regulation of the system is assisted, wind curtailment is reduced, the resource utilization rate is improved, and resource waste is reduced.

Description

Technical Field

[0001] This invention relates to the field of power system operation optimization technology, specifically to a coordinated optimization method and system for AC / DC receiving-end systems that consider DC regulation. Background Technology

[0002] In order to achieve efficient utilization of electricity from energy bases, DC transmission technology is usually used to transmit the electricity generated by the energy bases to high-load areas, thereby breaking the spatial reversal between resource and consumption.

[0003] As DC transmission technology matures and its transmission capacity expands, the problems faced by the receiving-end power grid cannot be ignored. For example, when high-voltage DC is connected to the receiving-end power grid system, the lack of a comprehensive scheduling strategy for resources within the receiving-end system and the DC-feeded energy results in large amounts of wind curtailment and resource waste. Summary of the Invention

[0004] The purpose of this invention is to provide a coordinated optimization method and system for AC / DC receiving-end systems that consider DC regulation. By modeling the resources within the receiving-end power grid and the externally fed power, respectively, the method and system are used as constraints to solve the objective function of the receiving-end power grid scheduling model. This solves the problem of resource waste caused by the lack of integrated regulation of internal resources and DC-feeded energy after high-voltage DC is connected to the receiving-end power grid.

[0005] This invention is achieved through the following technical solution:

[0006] The first aspect of this application provides a coordinated optimization method for AC / DC receiving-end systems considering DC regulation, including:

[0007] Based on the resource attributes of each resource in the receiving-end power grid, an internal resource mathematical model is established to characterize the operational constraints of each resource.

[0008] Based on the channel characteristics of external power access to the receiving-end power grid, a mathematical model based on the DC feed-in channel and a data model based on the AC feed-in channel are established for the external power access. The mathematical model of the DC feed-in channel includes DC transmission capacity limitations and operational requirements for the power receiving capacity of the receiving-end power grid.

[0009] Based on the established mathematical models of internal resources, DC feed-in channels, and AC feed-in channels, a scheduling model for the receiving-end power grid is constructed. The scheduling model uses the minimization of the operating cost of the receiving-end power grid within the scheduling cycle as the objective function, and uses the output plans of multiple types of resources as constraints.

[0010] Solve the objective function to determine the scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0011] In one feasible implementation, the method further includes: solving the objective function to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle, specifically including:

[0012] The nonlinear expressions contained in the constraints are converted into linear expressions through piecewise linear approximation or Taylor series expansion.

[0013] Based on the constraints determined by the linear expression, the objective function is solved to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0014] In one feasible implementation, the internal resource mathematical model includes a cascade hydropower model, an energy storage system model, and a reactive power compensation model.

[0015] The cascade hydropower model includes constraints on the hydraulic coupling relationship between reservoirs, water balance constraints, and power generation characteristics.

[0016] The energy storage system model includes the dynamic process of the state of charge of the energy storage device and the physical constraints of the charging and discharging process.

[0017] The reactive power compensation model includes constraints on the reactive power regulation capability of the reactive power compensation device.

[0018] In one feasible implementation, the cascade hydropower model includes hydropower conversion constraints, power generation flow constraints, water balance constraints, and reservoir capacity constraints.

[0019] The expression for the hydropower conversion constraint is as follows: and ;

[0020] The expression for the power generation flow constraint is: ;

[0021] The expression for the water balance constraint is: and ;

[0022] The expression for the storage capacity constraint is: and ;

[0023] In the formula, u is the upstream hydropower station of hydropower station h; This represents the power generation capacity of the hydropower station during time period t (h). This represents the hydropower conversion efficiency of the cascade hydropower station h. , These represent the initial head and head coefficient of the hydropower station h, respectively. Let h be the reservoir capacity of the hydropower station during time period t; Let h be the power generation flow rate of the hydropower station during time period t; The generating head of the hydropower station during time period t is h. This represents the operating status of the hydropower station h during time period t. , The maximum and minimum allowable power generation flow rates for the hydropower station are given by h. Let h be the water discharge rate of the hydropower station during the time period t; Let h be the inflow rate of the hydropower station during the time period t. The time it takes for the water from hydropower station u to reach its immediate downstream flow; , Let U and U represent the power generation flow and water discharge flow of the direct upstream hydropower station U of hydropower station h in time period t, respectively, considering the water flow time delay. Let h be the amount of tap water supplied to the hydropower station during time period t. , Let h be the minimum and maximum reservoir capacity of the hydropower station during time period t; , These represent the initial and final reservoir capacities for the hydropower station h during its operation.

[0024] In one feasible implementation, the method further includes: converting the expression of the cascade hydropower model into a linear expression, and using the linear expression of the cascade hydropower model to solve the objective function;

[0025] Specifically, transforming the expression of the cascade hydropower model into a linear expression includes:

[0026] The power generation flow and reservoir capacity are segmented: the power generation flow is divided into m-1 continuous intervals, and the reservoir capacity is divided into n-1 continuous intervals; m and n are positive integers.

[0027] Based on the segmented power generation flow and reservoir capacity, the projection of the expression of the cascade hydropower model onto the plane composed of power generation flow and reservoir capacity is divided into a (m-1)·(n-1) dimensional grid.

[0028] Divide each grid into two triangles to determine the linear representation of the cascade hydropower model:

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[0037] In the formula, This indicates the generating capacity of a cascade hydropower station; This indicates the hydropower conversion efficiency of a cascade hydropower station; The power generation flow of the cascade hydropower station; , These are the initial head and head coefficient of the cascade hydropower station, respectively; The reservoir capacity for the cascade hydropower stations; Represents a grid Corresponding power generation capacity; For grid The corresponding power generation flow rate; For grid Corresponding storage capacity; As an auxiliary variable; and Representing grids respectively The two triangles that have been divided.

[0038] In one feasible implementation, the constraints include node balancing constraints, which in turn include line power flow constraints:

[0039] ;

[0040] ;

[0041] In the formula, , These are the real and imaginary parts of the corresponding line (i,j) in the admittance matrix, respectively. The phase angle difference between nodes i and j in time period t; , These are the voltage amplitudes at nodes i and j during time period t, respectively. , Let represent the active and reactive power flow on the transmission line (i,j) during time period t, respectively.

[0042] In one feasible implementation, the method further includes: converting the expression of the line power flow constraint into a linear expression, and using the linear expression of the line power flow constraint to solve the objective function;

[0043] Specifically, transforming the expression for the line power flow constraint into a linear expression includes:

[0044] Based on the value of the phase angle difference and the degree of closeness between the actual voltage value of each node in the power system and the rated voltage value, the trigonometric function in the expression of line power flow constraint is transformed, and the transformed expression of line power flow constraint includes active power loss term and reactive power loss term.

[0045] The active power loss term and reactive power loss term are expanded using Taylor series to obtain a linear expression for the line power flow constraint.

[0046] A second aspect of this application provides a coordinated optimization system for AC / DC receiving-end systems considering DC regulation, comprising:

[0047] The internal resource mathematical model construction unit establishes an internal resource mathematical model that characterizes the operational constraints of each resource based on the resource attributes of each resource in the receiving-end power grid.

[0048] The external power mathematical model construction unit establishes a mathematical model based on the DC feed channel and a data model based on the AC feed channel for external power access, based on the channel characteristics of external power access to the receiving end power grid. The mathematical model of the DC feed channel includes DC transmission capacity limitations and operational requirements for the power receiving capacity of the receiving end power grid.

[0049] The scheduling model construction unit constructs a scheduling model for the receiving-end power grid based on the established mathematical models of internal resources, DC feed-in channels, and AC feed-in channels. The scheduling model constructs an objective function based on minimizing the operating cost of the receiving-end power grid within the scheduling cycle, and uses the output plans of multiple types of resources as constraints.

[0050] The model solving unit is used to solve the objective function to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0051] A third aspect of this application provides an electronic device, including: a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the above-described method.

[0052] A fourth aspect of this application provides a storage medium, comprising: storing a program or instructions on the storage medium, wherein the program or instructions, when executed by a processor, implement the steps of the above-described method.

[0053] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0054] This application embodiment establishes mathematical models for each resource within the receiving-end power grid and the externally connected power, which are used as constraints to solve the objective function of the receiving-end power grid dispatch model. This ensures that the determined dispatch scheme considers the comprehensive dispatch of internal resources and externally connected power within the receiving-end power grid. Furthermore, the mathematical model of the externally connected power includes a mathematical model of the DC feed-in channel, and this mathematical model includes the operational requirements of the receiving-end power grid's power receiving capacity. By treating the DC-feed-in power as a controllable resource with power regulation capabilities, the regulation capabilities of the DC feed-in can be effectively utilized, assisting the system in peak shaving, reducing wind curtailment, improving resource utilization, and reducing resource waste. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0056] Figure 1 A flowchart illustrating a coordinated optimization method for an AC / DC receiving-end system considering DC regulation, provided in an embodiment of this application;

[0057] Figure 2 A schematic diagram of the topology of a 6-node example provided in an embodiment of this application;

[0058] Figure 3 A schematic diagram of the hydropower output, AC feed-in power, and thermal power unit output curves in an example of using implementation scheme 1 in this application embodiment;

[0059] Figure 4 A schematic diagram of the wind curtailment curves using embodiments 1-4 is provided as an example of an embodiment of this application.

[0060] Figure 5 A schematic diagram of the AC feed-in power and thermal power unit output curves of Scheme 1 and Scheme 2 provided in an example of the embodiments of this application;

[0061] Figure 6 A schematic diagram of the energy storage discharge curve of Scheme 3 in an example provided in this application embodiment;

[0062] Figure 7 A schematic diagram of DC power curves for Scheme 3 and Scheme 4 in an example provided for embodiments of this application;

[0063] Figure 8A schematic diagram of the structure of a coordinated optimization system for an AC / DC receiving-end system considering DC regulation, provided in an embodiment of this application;

[0064] Figure 9 This is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments and accompanying drawings. The illustrative embodiments and descriptions of this invention are for explanation only and are not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments in this application without creative effort are within the scope of protection of this application.

[0066] As will be known to those skilled in the art, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0067] The terms “comprising” and “having”, and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, product, or apparatus.

[0068] Example 1

[0069] Embodiment 1 of this application provides a coordinated optimization method for AC / DC receiving-end systems that considers DC regulation, in order to solve the problem of resource waste caused by the lack of integrated mobilization of system resources and DC-feeded energy after high-voltage DC is connected to the receiving-end power grid.

[0070] The subject executing this method can be any computing device capable of implementing the method, such as a server, mobile phone, personal computer, smart wearable device, smart robot, etc.

[0071] Furthermore, the embodiments of this application do not limit the execution order of different steps. When using the method provided in the embodiments of this application, the execution order of different steps can be adjusted according to actual needs.

[0072] For ease of description, the following uses a coordinated optimization device for an AC / DC receiving-end system considering DC regulation as the execution subject of this method to provide a detailed description of the method provided in the embodiments of this application.

[0073] like Figure 1The diagram shown is a flowchart illustrating a specific implementation of a coordinated optimization method for an AC / DC receiving-end system considering DC regulation, as provided in an embodiment of this application. The method includes the following steps 11-14:

[0074] Step 11: Based on the resource attributes of each resource in the receiving-end power grid, establish an internal resource mathematical model that characterizes the operational constraints of each resource.

[0075] The internal resource mathematical model includes a cascade hydropower model, an energy storage system model, and a reactive power compensation model. The cascade hydropower model includes constraints on the hydraulic coupling relationship between reservoirs, water balance constraints, and power generation characteristics constraints. The energy storage system model includes dynamic processes of the state of charge of energy storage devices and physical constraints on the charging and discharging processes. The reactive power compensation model includes constraints on the reactive power regulation capability of reactive power compensation devices.

[0076] Cascade hydropower is an important form of developing and utilizing river hydropower in stages and segments, and it is a significant hydropower development method in Sichuan Province, which is rich in water resources. The output constraints and gradient constraints of cascade hydropower are similar to those of thermal power units. In addition, cascade hydropower constraints include hydropower conversion constraints, as shown in the equation. - Power generation flow constraints are as follows: Water balance constraints are as follows: - Storage capacity constraints are as follows: - .

[0077] ;

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[0080] ;

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[0083] ;

[0084] In the formula, u is the upstream hydropower station of hydropower station h; This represents the power generation capacity of the hydropower station during time period t (h). This represents the hydropower conversion efficiency of the cascade hydropower station h. , These are the initial head and head coefficient of the hydropower station h, respectively, which are related to the physical characteristics of the hydropower station itself. Let h be the reservoir capacity of the hydropower station during time period t; Let h be the power generation flow rate of the hydropower station during time period t; The generating head of the hydropower station during time period t is h. This represents the operating status of the hydropower station h during time period t. , The maximum and minimum allowable power generation flow rates for the hydropower station are given by h. Let h be the water discharge rate of the hydropower station during the time period t; Let h be the inflow rate of the hydropower station during the time period t. The time it takes for the water from hydropower station u to reach its immediate downstream flow; , Let U and U represent the power generation flow and water discharge flow of the direct upstream hydropower station U of hydropower station h in time period t, respectively, considering the water flow time delay. Let h be the amount of tap water supplied to the hydropower station during time period t. , Let h be the minimum and maximum reservoir capacity of the hydropower station during time period t; , These represent the initial and final reservoir capacities for the hydropower station h during its operation.

[0085] Energy storage system constraints are given by formula - It means that, in which the formula To constrain the upper and lower limits of energy storage capacity, the formula is... To constrain the relationship between energy storage charging / discharging and capacity, the formula is... - To constrain the upper and lower limits of energy storage charging and discharging power, the formula is... This is a constraint on the charging and discharging state.

[0086] ;

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[0091] In the formula, , represents the upper and lower limits of the energy storage capacity s; Let be the capacity of energy storage s during time period t; , The charging and discharging efficiency of energy storage s; , The upper and lower limits of the charging power for energy storage s; , These are the upper and lower limits of the discharge power of the energy storage s; , The variable is 0-1, representing the charging and discharging state of the energy storage s during time period t.

[0092] An SVC (Static Var Compensator) consists of capacitors switched on and off by thyristors and is widely used to provide reactive power support and improve the stability of dynamic voltage in power systems. Its constraints are as follows: As shown, the upper and lower limits of reactive power regulation by SVC are limited.

[0093] ;

[0094] In the formula, Let be the reactive power of static var compensator b during time period t. The upper limit of reactive power adjustment for static var compensator b.

[0095] Step 12: Based on the channel characteristics of external power access to the receiving-end power grid, establish a mathematical model based on the DC feed-in channel and a data model based on the AC feed-in channel for the external power access; the mathematical model of the DC feed-in channel includes DC transmission capacity limitations and operational requirements for the power receiving capacity of the receiving-end power grid.

[0096] The mathematical model for the DC feed-in channel in this embodiment not only considers its transmission capacity limit but also comprehensively takes into account the power receiving capacity of the receiving-end grid and operational requirements such as the number of daily adjustments. The mathematical model for the AC feed-in channel mainly considers its transmission capacity constraints. These models will serve as important boundary conditions and controllable resources for the scheduling model.

[0097] The mathematical model of the DC feed-in channel specifically addresses the DC receiving-end operational constraints. In this embodiment, the DC receiving end receives energy transmitted from the DC transmission line through the converter station. Considering the active and reactive power constraints and voltage safety upper and lower limits of the converter station, as shown in the equation... - As shown:

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[0104] In the formula, , These represent the active and reactive power flowing into converter station c during time period t, respectively. , These represent the active and reactive power losses on the transmission line where converter station c is located during time period t, respectively. , These represent the active power and reactive power output by converter station C, respectively. This indicates the voltage value of converter station c during time period t.

[0105] Furthermore, this embodiment takes into account power adjustment constraints. - 1. Power unidirectional adjustment constraint Constraint that power cannot be adjusted in reverse between adjacent time periods DC input line adjustment frequency limit constraint Contract quantity constraints .

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[0112] In the formula, , These are the maximum upward and downward adjustment limits for the transmission power of the DC feeder lines connected to converter station c in adjacent time periods; , These represent the upward and downward adjustment states of the DC feeder line connected to converter station c during time period t, respectively. This indicates the maximum number of adjustments made to the DC feeder line connected to converter station c within the scheduling cycle. The contracted transmission volume of the DC feeder line connected to converter station c.

[0113] The mathematical model of the AC feed channel is specifically the AC feed receiving end constraint.

[0114] DC power input, as an actively controlled resource, requires power regulation within a contractually agreed-upon range and frequency to balance flexibility and equipment lifespan. AC power input, on the other hand, is determined by the natural distribution of system power flow, and its regulation is included in global optimization. The power transmission of AC lines is determined by the voltage, phase angle, and impedance distribution of all network nodes. Therefore, considering the active and reactive power constraints and voltage safety upper and lower limits for AC power input, as shown in equation... - As shown. It should be noted that, since AC feed-in essentially achieves power transmission through remote generator sets, its power fluctuation range is still constrained by the ramp-up rate of the corresponding units outside the system.

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[0120] In the formula, , These represent the active and reactive power generated by the external generator unit connected to the feed-in point h during time period t, respectively. , These represent the active and reactive power losses on the transmission line where the feed point h is located during time period t, respectively. , These represent the active power and reactive power fed into the feed point h during time period t, respectively. This indicates the voltage value at the feed point h during time period t.

[0121] Step 13: Based on the established mathematical models of internal resources, DC feed-in channels, and AC feed-in channels, construct a scheduling model for the receiving-end power grid; the scheduling model constructs an objective function based on minimizing the operating cost of the receiving-end power grid within the scheduling cycle, and uses the output plans of multiple types of resources as constraints.

[0122] The scheduling model constructed in this embodiment comprehensively optimizes the output plans of various resources such as thermal power, cascade hydropower, wind power, energy storage, and DC feed-in, thereby achieving economically optimal scheduling under multi-source collaboration.

[0123] This embodiment is based on improving the absorption of new energy sources, and the objective function is to minimize the system operating cost, as shown in the equation. As shown. The total system cost consists of operating cost and wind curtailment cost. The system operating cost includes the operating fuel consumption of the thermal power unit, the start-up and shutdown fuel consumption, and the AC feed-in cost.

[0124] ;

[0125] In the formula, g and w are the designations of thermal power units and wind power units, respectively; e is the segment designation of the coal consumption cost curve. This represents the incremental coal consumption of thermal power unit g in segment e; This represents the power generation of thermal power unit g in segment e at time t; , These represent the start-up and shutdown fuel consumption of thermal power unit g during time period t; This represents the input power of AC feeder a during time period t; , , These represent the unit costs of fuel, AC feed-in, and wind curtailment penalty, respectively. This represents the amount of wind curtailed by wind turbine w during time period t.

[0126] The constraints of the objective function also include output constraints of thermal power units and wind power units, nodal balance constraints, and line power flow constraints.

[0127] Among them, the operating constraints of thermal power units are as follows: - As shown. The operating constraints of the wind turbine are as follows. - As shown. Wherein, equation - To limit the climbing speed of thermal power units, - For fuel consumption during start / stop of thermal power units, formula - The minimum start / stop time limit for thermal power units, formula - To limit the output of thermal power units, the formula - To limit the active power output of wind turbines, the formula This is a limitation on the reactive power output of wind turbine units.

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[0140] In the formula, This represents the active power output of thermal power unit g during time period t; The variable is 0-1, representing the start-up and shutdown status of thermal power unit g during time period t; , These represent the upward and downward ramp limits of the thermal power unit, respectively. , Minimum and maximum values ​​of active power processing capacity of thermal power unit g; , These represent the unit start / stop cost of thermal power unit g, respectively. , These represent the start-up / shutdown costs of thermal power unit g during time period t; , These are the minimum start-up / shutdown times for thermal power unit g, respectively; , These represent the time that thermal power unit g operates continuously and the time that it remains in the off state before time period t, respectively. This represents the wind curtailment of wind turbine unit w during time period t; This represents the predicted output of wind turbine w during time period t; , This represents the actual power output and reactive power output of the wind turbine w during time period t.

[0141] Line power flow constraints: The line power flow formula for line (i,j) can be derived from equation [equation missing]. - Representation. Formula The formula for calculating voltage phase angle difference. The limits on active and reactive power transmission in a line are given by the formula... - Representation. Formula This is for upper and lower limits of voltage safety constraints.

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[0148] In the formula, , These are the real and imaginary parts of the corresponding line (i,j) in the admittance matrix, respectively. The phase angle difference between nodes i and j in time period t; , These are the voltage amplitudes at nodes i and j during time period t, respectively. , Let represent the active and reactive power flow on transmission line (i,j) during time period t, respectively. It represents the minimum or maximum value of a quantity.

[0149] Node balance constraints specifically refer to the balance constraints of active and reactive power at nodes:

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[0152] In the formula, k is the power system node number; b and h are the SVC and hydropower unit numbers; c is the converter station number; , These represent the active and reactive power transmitted from converter station c to the power grid during time period t; , This indicates the active and reactive power demand of node j during time period t; Let j be the set of devices. The output of the hydropower unit during time period t is h. For the thermal power unit, g represents the output during time period t. Let w be the output of the wind turbine during time period t; This represents the active load demand and reactive load demand of node j during time period t. , , These represent the reactive power outputs of the hydroelectric generator (h), the thermal power unit (g), and the wind turbine (w) during time period t, respectively. This provides reactive power support for the SVC during time period t. , , respectively, represent the charging and discharging power of energy storage s during time period t.

[0153] Step 14: Solve the objective function to determine the scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0154] In one feasible implementation, step 14 specifically includes: converting the nonlinear expression contained in the constraints into a linear expression through piecewise linear approximation or Taylor series expansion; and solving the objective function based on the constraints determined by the linear expression to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0155] Since the cascade hydropower constraints in step 11 and the line power flow constraints in step 13 are nonlinear constraints, this embodiment employs linearization techniques for efficient solution: piecewise linear approximation is used for the cascade hydropower constraints, while a linear approximation based on Taylor series expansion is used for the AC power flow constraints. Through this process, the original complex nonlinear optimization problem is transformed into a standard mixed-integer linear optimization problem, and its abstract mathematical form is given, enabling stable and efficient computational solutions using commercial solvers.

[0156] In this embodiment, the expression of the cascade hydropower model is transformed into a linear expression, and the linear expression of the cascade hydropower model is used to solve the objective function.

[0157] In this embodiment, the expression of the cascade hydropower model is transformed into a linear expression. The triangle approximation method is used to linearize the output constraint of the trapezoidal hydropower unit. Specifically, this includes:

[0158] The subscripts in the formula are simplified as shown in equation (52) to facilitate subsequent processing.

[0159] The power generation flow rate L and the reservoir capacity E are segmented: the power generation flow rate is divided into m-1 continuous intervals, and the reservoir capacity is divided into n-1 continuous intervals; m and n are positive integers.

[0160] Based on the segmented power generation flow and reservoir capacity, the projection of the expression of the cascade hydropower model onto the plane composed of power generation flow and reservoir capacity is divided into a (m-1)·(n-1) dimensional grid, and each point in the grid satisfies equation (53).

[0161] Divide each grid into two triangles, and use... and Indicate the upper left and lower right triangles, and introduce auxiliary variables. Determine the linear expression method for the cascade hydropower model:

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[0170] In the formula, This indicates the generating capacity of a cascade hydropower station; This indicates the hydropower conversion efficiency of a cascade hydropower station; The power generation flow of the cascade hydropower station; , These are the initial head and head coefficient of the cascade hydropower station, respectively; The reservoir capacity for the cascade hydropower stations; Represents a grid Corresponding power generation capacity; For grid The corresponding power generation flow rate; For grid Corresponding storage capacity; As an auxiliary variable; and Representing grids respectively The two triangles that have been divided.

[0171] The expression for the line power flow constraint is transformed into a linear expression, and the linear expression for the line power flow constraint is used to solve the objective function.

[0172] Specifically, transforming the expression for the line power flow constraint into a linear expression includes:

[0173] Based on the value of the phase angle difference and the degree of closeness between the actual voltage value and the rated voltage value of each node in the power system, the trigonometric functions in the expression of line power flow constraint are transformed, and the transformed expression of line power flow constraint includes active power loss term and reactive power loss term; the active power loss term and reactive power loss term are expanded using Taylor series to obtain the linear expression of line power flow constraint.

[0174] Specifically:

[0175] Considering the actual situation of the power transmission network, phase angle difference The value of is very small, and the voltages at each node in the system are very close to the rated voltage. Therefore, the equation can be considered... - If true, then the power flow model can be transformed into equation [formula missing]. - .

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[0180] This embodiment defines To express the pressure difference between nodes, the equation is... - Can be converted into formula - .Will and After treating them as independent variables, the equation becomes... - For linear constraints, the expressions for active and reactive power losses of the line are... - It remains nonlinear.

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[0185] In the formula, , This represents the active power and reactive power loss on line (i,j) during time period t.

[0186] This embodiment uses a first-order Taylor series expansion method, with the baseline operating state as the basis. Based on this, the formula and Taylor series expansion is performed to linearize the expressions for active and reactive power losses of the line. This embodiment decomposes the active power loss into two parts, as shown in equation [equation missing]. As shown.

[0187] ;

[0188] right Performing a Taylor series expansion on the baseline state yields a linearized expression. .

[0189] ;

[0190] because and Treating them as independent variables in this paper, we first need to... Approximately converted to a function related to the voltage square term, as shown in the equation. As shown. Then, for the formula Taylor series expansion, as shown in the equation As shown.

[0191] ;

[0192] ;

[0193] Similarly, the expression for reactive power loss in a power line can be linearized using Taylor series expansion. The linearized AC power flow formula is shown in equation [equation missing]. - As shown.

[0194] ;

[0195] ;

[0196] Furthermore, this embodiment also converts the scheduling model proposed in step 13 into a mixed-integer linear optimization model, the matrix expression of which is: Where x is a binary variable, representing unit start-up and shutdown, DC line power adjustment, etc.; y is a continuous variable including wind curtailment variables.

[0197] ;

[0198] In the formula, a, b, c, d, A, B, and D are abstract matrix forms and vectors, representing the coefficients of the objective function and constraints.

[0199] To verify the effectiveness of the optimization method proposed in this embodiment, specific examples are used for analysis below.

[0200] like Figure 2 As shown, a 6-node power system is given, including 1 thermal power unit G1, 2 cascade hydropower stations (H1, H2), 1 wind turbine unit W1, 1 energy storage power station E1, and 1 SVC. The installed capacities of thermal power, hydropower, wind power, and energy storage are 200MW, 410MW, 400MW, and 150MW, respectively.

[0201] The node-related parameters in this example are shown in Tables 1-4 below, where Table 1 represents the parameters of thermal power units, Table 2 represents the parameters of cascade hydropower units, Table 3 represents the parameters of energy storage equipment, and Table 4 represents the parameters of transmission lines.

[0202]

[0203] Table 1

[0204]

[0205] Table 2

[0206]

[0207] Table 3

[0208]

[0209] Table 4

[0210] Tables 5 and 6 provide the specific settings for the four schemes, as well as the corresponding operating costs of the power system.

[0211]

[0212] Table 5

[0213]

[0214] Table 6

[0215] The output of each generator unit at each time period in Scheme 1 is as follows: Figure 3 As shown in the diagram. Since hydropower has no generation cost, it is prioritized over thermal power units under certain constraints. In the cascade hydropower project, the downstream H2 hydropower station has a more stable output than the upstream H1 hydropower station, maintaining maximum output for most of the time. The upstream H1 hydropower station adjusts its output more frequently, allowing it to adjust its output to some extent in response to wind power fluctuations, thus alleviating the peak-shaving pressure on thermal power units. It is noted that during the peak wind power output period of 4:00-6:00, to minimize wind curtailment, both thermal and hydropower outputs are low, even zero. The wind curtailment curve for Scheme 1 is shown in the diagram. Figure 4 As shown.

[0216] Option 2 adds reactive power compensation to Option 1. Compared to Option 1, Option 2 reduces costs by 25,492.6 yuan, with decreases in system operating costs and wind curtailment penalties. Figure 5 As shown, by performing reactive power compensation at node 2, the feed power of the AC feed line was significantly improved, indicating that a reasonable configuration of reactive power compensation can improve the power receiving capacity of the system.

[0217] Scheme 3, building upon Scheme 2, considers the regulating role of energy storage. Compared to Scheme 2, Scheme 3 reduces system costs by 34,316.6 yuan, wind curtailment penalties by 15,378.7 yuan, and operating costs by 18,937.9 yuan. For example... Figure 4 As shown, although wind curtailment still exists in Scheme 3 from 4:00 to 6:00, the values ​​are lower than those in Scheme 2. The changes in energy storage charging and discharging power and energy storage capacity throughout the day in Scheme 3 are shown below. Figure 6 As shown, it can be observed that the energy storage maintains maximum charging power from 4:00 to 6:00, which alleviates the pressure on wind power consumption.

[0218] Based on Scheme 3, Scheme 4 considers the regulating effect of the DC feeder line, allowing a single line to be adjusted four times during the entire dispatch period. Compared with Scheme 3, Scheme 4 reduces the total system cost by 21,937.6 yuan, and the system operating cost and wind curtailment cost decrease by 7,537.6 yuan and 14,400 yuan, respectively. Compared with the non-adjustable DC feeder in Scheme 3, Scheme 4 allows for DC feeder power adjustment, and its DC feeder power is as follows: Figure 7 As shown in the diagram, Scheme 4 considers DC power regulation. Since the DC power input is transmitted daily according to the contracted amount, the cost is fixed. During normal system operation, DC power will be prioritized to meet the system's power demand, resulting in a significant reduction in system operating costs. When the wind power peak-shaving pressure is greatest from 4:00 to 6:00, the DC power can be reduced to alleviate the pressure on wind power absorption. Figure 4 As can be seen from the data, wind curtailment in Scheme 4 has also decreased, and the economic efficiency of the system has significantly improved.

[0219] In summary, this application embodiment establishes mathematical models for each resource within the receiving-end power grid and the externally connected power, which are used as constraints to solve the objective function of the receiving-end power grid dispatch model. This ensures that the determined dispatch scheme considers the comprehensive dispatch of resources within the receiving-end power grid and externally connected power. Furthermore, the mathematical model of the externally connected power includes a mathematical model of the DC feed-in channel, and this mathematical model includes the operational requirements of the receiving-end power grid's power receiving capacity. By treating the DC-feed-in power as a controllable resource with power regulation capabilities, the regulation capabilities of the DC feed-in can be effectively utilized, assisting the system in peak shaving, reducing wind curtailment, improving resource utilization, and reducing resource waste.

[0220] Example 2

[0221] To address the resource waste caused by the lack of integrated mobilization of system resources and DC-fed energy after high-voltage direct current (HVDC) is connected to the receiving-end power grid, this application also provides a coordinated optimization system for AC / DC receiving-end systems that considers DC regulation, based on the same inventive concept as Embodiment 1.

[0222] The specific structural diagram of the system is as follows: Figure 8 As shown, it includes the following functional units 81-84:

[0223] Internal resource mathematical model construction unit 81 establishes an internal resource mathematical model that characterizes the operational constraints of each resource based on the resource attributes of each resource in the receiving-end power grid.

[0224] The internal resource mathematical model includes a cascade hydropower model, an energy storage system model, and a reactive power compensation model. The cascade hydropower model includes constraints on the hydraulic coupling relationship between reservoirs, water balance constraints, and power generation characteristics. The energy storage system model includes dynamic processes of the state of charge of energy storage devices and physical constraints on the charging and discharging processes. The reactive power compensation model includes constraints on the reactive power regulation capability of reactive power compensation devices.

[0225] The cascade hydropower model includes constraints on hydropower conversion, power generation flow, water balance, and reservoir capacity.

[0226] The expression for the hydropower conversion constraint is as follows: and ;

[0227] The expression for the power generation flow constraint is: ;

[0228] The expression for the water balance constraint is: and ;

[0229] The expression for the storage capacity constraint is: and ;

[0230] In the formula, u is the upstream hydropower station of hydropower station h; This represents the power generation capacity of the hydropower station during time period t (h). This represents the hydropower conversion efficiency of the cascade hydropower station h. , These represent the initial head and head coefficient of the hydropower station h, respectively. Let h be the reservoir capacity of the hydropower station during time period t; Let h be the power generation flow rate of the hydropower station during time period t; The generating head of the hydropower station during time period t is h. This represents the operating status of the hydropower station h during time period t. , The maximum and minimum allowable power generation flow rates for the hydropower station are given by h. Let h be the water discharge rate of the hydropower station during the time period t; Let h be the inflow rate of the hydropower station during the time period t. The time it takes for the water from hydropower station u to reach its immediate downstream flow; , Let U and U represent the power generation flow and water discharge flow of the direct upstream hydropower station U of hydropower station h in time period t, respectively, considering the water flow time delay. Let h be the amount of tap water supplied to the hydropower station during time period t. , Let h be the minimum and maximum reservoir capacity of the hydropower station during time period t; , These represent the initial and final reservoir capacities for the hydropower station h during its operation.

[0231] The external power mathematical model construction unit 82 establishes a mathematical model based on the DC feed channel and a data model based on the AC feed channel for the external power access based on the channel characteristics of the external power access to the receiving end power grid. The mathematical model of the DC feed channel includes DC transmission capacity limitations and operational requirements including the power receiving capability of the receiving end power grid.

[0232] The scheduling model construction unit 83 constructs a scheduling model for the receiving-end power grid based on the established mathematical model of internal resources, the mathematical model of DC feed-in channel, and the mathematical model of AC feed-in channel. The scheduling model constructs an objective function based on minimizing the operating cost of the receiving-end power grid within the scheduling cycle, and uses the output plan of multiple types of resources as a constraint condition.

[0233] The constraints include node balance constraints, which in turn include line power flow constraints:

[0234] ;

[0235] ;

[0236] In the formula, , These are the real and imaginary parts of the corresponding line (i,j) in the admittance matrix, respectively. The phase angle difference between nodes i and j in time period t; , These are the voltage amplitudes at nodes i and j during time period t, respectively. , Let represent the active and reactive power flow on the transmission line (i,j) during time period t, respectively.

[0237] The model solving unit 84 is used to solve the objective function to determine the scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0238] The model solving unit is specifically used to: convert the nonlinear expression contained in the constraints into a linear expression through piecewise linear approximation or Taylor series expansion; and solve the objective function based on the constraints determined by the linear expression to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

[0239] The model solving unit is also used to: transform the expression of the cascade hydropower model into a linear expression, specifically including:

[0240] The power generation flow and reservoir capacity are segmented: the power generation flow is divided into m-1 continuous intervals, and the reservoir capacity is divided into n-1 continuous intervals; m and n are positive integers.

[0241] Based on the segmented power generation flow and reservoir capacity, the projection of the expression of the cascade hydropower model onto the plane composed of power generation flow and reservoir capacity is divided into a (m-1)·(n-1) dimensional grid.

[0242] Divide each grid into two triangles to determine the linear representation of the cascade hydropower model:

[0243] ;

[0244] ;

[0245] ;

[0246] ;

[0247] ;

[0248] ;

[0249] ;

[0250] ;

[0251] In the formula, This indicates the generating capacity of a cascade hydropower station; This indicates the hydropower conversion efficiency of a cascade hydropower station; The power generation flow of the cascade hydropower station; , These are the initial head and head coefficient of the cascade hydropower station, respectively; The reservoir capacity for the cascade hydropower stations; Represents a grid Corresponding power generation capacity; For grid The corresponding power generation flow rate; For grid Corresponding storage capacity; As an auxiliary variable; and Representing grids respectively The two triangles that have been divided.

[0252] The model solving unit is also used to: transform the expression of the line power flow constraint into a linear expression, specifically including:

[0253] Based on the value of the phase angle difference and the degree of closeness between the actual voltage value of each node in the power system and the rated voltage value, the trigonometric function in the expression of line power flow constraint is transformed, and the transformed expression of line power flow constraint includes active power loss term and reactive power loss term.

[0254] The active power loss term and reactive power loss term are expanded using Taylor series to obtain a linear expression for the line power flow constraint.

[0255] This application embodiment establishes mathematical models for each resource within the receiving-end power grid and the externally connected power, which are used as constraints to solve the objective function of the receiving-end power grid dispatch model. This ensures that the determined dispatch scheme considers the comprehensive dispatch of internal resources and externally connected power within the receiving-end power grid. Furthermore, the mathematical model of the externally connected power includes a mathematical model of the DC feed-in channel, and this mathematical model includes the operational requirements of the receiving-end power grid's power receiving capacity. By treating the DC-feed-in power as a controllable resource with power regulation capabilities, the regulation capabilities of the DC feed-in can be effectively utilized, assisting the system in peak shaving, reducing wind curtailment, improving resource utilization, and reducing resource waste.

[0256] Based on the same inventive concept as the foregoing embodiments of this application, this application also provides a computing device.

[0257] like Figure 9 As shown, the computing device includes a memory 91 and a processor 92. The memory 91 can be configured to store various other data to support operation on the electronic device. Examples of this data include instructions for any application or method used to operate on the electronic device. The memory 91 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0258] The processor 92, coupled to the memory 91, is used to execute the computer program stored in the memory 91 for performing a coordinated optimization method for an AC / DC receiving-end system considering DC regulation as described in the foregoing embodiments.

[0259] When the processor 92 executes the computer program to perform a coordinated optimization method for an AC / DC receiving-end system considering DC regulation, it establishes mathematical models for each resource within the receiving-end power grid and the external power access, which are used as constraints to solve the objective function of the receiving-end power grid scheduling model. This ensures that the determined scheduling scheme considers the comprehensive scheduling of internal resources of the receiving-end power grid and external power access. Furthermore, the mathematical model of the external power access includes a mathematical model of the DC feed-in channel, and this mathematical model includes the operational requirements of the receiving-end power grid's power receiving capacity. By treating the DC feed-in power as a controllable resource with power regulation capabilities, the regulation capacity of the DC feed-in can be effectively utilized, assisting the system in peak shaving, reducing wind curtailment, improving resource utilization, and reducing resource waste.

[0260] When the processor 92 executes the computer program in the memory 91, in addition to the functions described above, it can also perform other functions, as detailed in the descriptions of the preceding embodiments.

[0261] Furthermore, such as Figure 9 As shown, the computing device also includes other components such as a display 94, a communication component 93, a power supply component 95, and an audio component 96. Figure 9 The diagram only shows some components and does not mean that the computing device includes only these components. Figure 9 The components shown.

[0262] Accordingly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a computer, can implement the methods provided in the above embodiments.

[0263] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0264] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0265] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A coordinated optimization method for an AC / DC receiving-end system considering DC regulation, characterized in that, include: Based on the resource attributes of each resource in the receiving-end power grid, an internal resource mathematical model is established to characterize the operational constraints of each resource. Based on the channel characteristics of external power access to the receiving-end power grid, a mathematical model based on the DC feed-in channel and a data model based on the AC feed-in channel are established for the external power access. The mathematical model of the DC feed-in channel includes DC transmission capacity limitations and operational requirements for the power receiving capacity of the receiving-end power grid. Based on the established mathematical models of internal resources, DC feed-in channels, and AC feed-in channels, a scheduling model for the receiving-end power grid is constructed. The scheduling model uses the minimization of the operating cost of the receiving-end power grid within the scheduling cycle as the objective function, and uses the output plans of multiple types of resources as constraints. Solve the objective function to determine the scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

2. The method according to claim 1, characterized in that, The method further includes: solving the objective function to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle, specifically including: The nonlinear expressions contained in the constraints are converted into linear expressions through piecewise linear approximation or Taylor series expansion. Based on the constraints determined by the linear expression, the objective function is solved to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

3. The method according to claim 1, characterized in that, The internal resource mathematical model includes a cascade hydropower model, an energy storage system model, and a reactive power compensation model. The cascade hydropower model includes constraints on the hydraulic coupling relationship between reservoirs, water balance constraints, and power generation characteristics. The energy storage system model includes the dynamic process of the state of charge of the energy storage device and the physical constraints of the charging and discharging process. The reactive power compensation model includes constraints on the reactive power regulation capability of the reactive power compensation device.

4. The method according to claim 3, characterized in that, The cascade hydropower model includes constraints on hydropower conversion, power generation flow, water balance, and reservoir capacity. The expression for the hydropower conversion constraint is as follows: and ; The expression for the power generation flow constraint is: ; The expression for the water balance constraint is: and ; The expression for the storage capacity constraint is: and ; In the formula, u is the upstream hydropower station of hydropower station h; This represents the power generation capacity of the hydropower station during time period t (h). This represents the hydropower conversion efficiency of the cascade hydropower station h. , These represent the initial head and head coefficient of the hydropower station h, respectively. Let h be the reservoir capacity of the hydropower station during time period t; Let h be the power generation flow rate of the hydropower station during time period t; The generating head of the hydropower station during time period t is h. This represents the operating status of the hydropower station h during time period t. , The maximum and minimum allowable power generation flow rates for the hydropower station are given by h. Let h be the water discharge rate of the hydropower station during the time period t; Let h be the inflow rate of the hydropower station during the time period t. The time it takes for the water from hydropower station u to reach its immediate downstream flow; , Let U and U represent the power generation flow and water discharge flow of the direct upstream hydropower station U of hydropower station h in time period t, respectively, considering the water flow time delay. Let h be the amount of tap water supplied to the hydropower station during time period t. , Let h be the minimum and maximum reservoir capacity of the hydropower station during time period t; , These represent the initial and final reservoir capacities for the hydropower station h during its operation.

5. The method according to claim 4, characterized in that, The method further includes: converting the expression of the cascade hydropower model into a linear expression, and using the linear expression of the cascade hydropower model to solve the objective function; The process of transforming the expression of the cascade hydropower model into a linear expression specifically includes: The power generation flow and reservoir capacity are segmented: the power generation flow is divided into m-1 continuous intervals, and the reservoir capacity is divided into n-1 continuous intervals; m and n are positive integers. Based on the segmented power generation flow and reservoir capacity, the projection of the expression of the cascade hydropower model onto the plane composed of power generation flow and reservoir capacity is divided into a (m-1)·(n-1) dimensional grid. Divide each grid into two triangles to determine the linear representation of the cascade hydropower model: ； ； ； ； ； ； ； ； In the formula, This indicates the generating capacity of a cascade hydropower station; This indicates the hydropower conversion efficiency of a cascade hydropower station; The power generation flow of the cascade hydropower station; , These are the initial head and head coefficient of the cascade hydropower station, respectively; The reservoir capacity for the cascade hydropower stations; Represents a grid Corresponding power generation capacity; For grid The corresponding power generation flow rate; For grid Corresponding storage capacity; As an auxiliary variable; and Representing grids respectively The two triangles that have been divided.

6. The method according to claim 1, characterized in that, The constraints include node balance constraints, which in turn include line power flow constraints. ； ； In the formula, , These are the real and imaginary parts of the corresponding line (i,j) in the admittance matrix, respectively. The phase angle difference between nodes i and j in time period t; , These are the voltage amplitudes at nodes i and j during time period t, respectively. , Let represent the active and reactive power flow on the transmission line (i,j) during time period t, respectively.

7. The method according to claim 6, characterized in that, The method further includes: converting the expression of the line power flow constraint into a linear expression, and using the linear expression of the line power flow constraint to solve the objective function; Specifically, transforming the expression for the line power flow constraint into a linear expression includes: Based on the value of the phase angle difference and the degree of closeness between the actual voltage value of each node in the power system and the rated voltage value, the trigonometric function in the expression of line power flow constraint is transformed, and the transformed expression of line power flow constraint includes active power loss term and reactive power loss term. The active power loss term and reactive power loss term are expanded using Taylor series to obtain a linear expression for the line power flow constraint.

8. A coordinated optimization system for an AC / DC receiving-end system considering DC regulation, characterized in that, include: The internal resource mathematical model construction unit establishes an internal resource mathematical model that characterizes the operational constraints of each resource based on the resource attributes of each resource in the receiving-end power grid. The external power mathematical model construction unit establishes a mathematical model based on the DC feed channel and a data model based on the AC feed channel for external power access, based on the channel characteristics of external power access to the receiving end power grid. The mathematical model of the DC feed channel includes DC transmission capacity limitations and operational requirements for the power receiving capacity of the receiving end power grid. The scheduling model construction unit constructs a scheduling model for the receiving-end power grid based on the established mathematical models of internal resources, DC feed-in channels, and AC feed-in channels. The scheduling model constructs an objective function based on minimizing the operating cost of the receiving-end power grid within the scheduling cycle, and uses the output plans of multiple types of resources as constraints. The model solving unit is used to solve the objective function to determine a scheduling scheme that minimizes the operating cost of the receiving-end power grid within the scheduling cycle.

9. An electronic device, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method as claimed in any one of claims 1-7.

10. A storage medium, characterized in that, include: The storage medium stores a program or instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1-7.

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