Method and System for Coordinated Optimization Configuration of Reactive Power Compensation Device and Energy Storage

Abstract

The present invention provides a method and system for coordinated optimal configuration of reactive power compensation devices and energy storage. The method includes: establishing a short-circuit ratio index constraint model for ensuring the grid strength of a new energy cluster system and improving the grid voltage support ability; establishing a two-layer optimal configuration model with the objectives of minimizing the total system cost index, minimizing the curtailment rate index, and maximizing the system strength index. The upper layer is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model. The upper layer transmits the reactive power compensation device and energy storage configuration information to the lower layer model. The lower layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result and feedback it to the upper layer model, so that the upper layer model can calculate the objective function value of the upper layer model according to the optimization result. Based on the influence mechanism of synchronous condensers, SVC, SVG, and the reactive power of new energy itself on the system short-circuit ratio, the present invention establishes a short-circuit ratio index constraint model for comprehensive configuration of reactive power compensation devices.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy access, and particularly to a method and system for coordinated optimization configuration of a reactive power compensation device and energy storage. Background Art

[0002] At present, large-scale new energy power stations such as wind power and photovoltaic power are connected to the power system, forming a weak power grid pattern mainly composed of new energy and supplemented by fossil energy. Power quality problems such as voltage instability and harmonic oscillation occur frequently. The transmission capacity of new energy power generation through high-voltage direct current transmission is limited. In severe cases, new energy units will operate off-grid. How to improve the strength of the power grid after new energy access is the key to solving the problem.

[0003] With the continuous in-depth study of the operating characteristics and stability mechanism of weak power grids, the insufficient dynamic reactive power support ability is considered to be the fundamental reason for the low strength of the power grid. According to GB / 38755-2019 "Power System Safety and Stability Guide", dynamic reactive power regulation equipment should be reasonably configured in new energy collection areas to make the short-circuit ratio of grid connection meet the requirements. At the same time, since energy storage plays an important role in improving new energy consumption, the problem of serious curtailment of wind and light can be solved. Therefore, studying the coordinated optimization configuration method of hybrid reactive power compensation devices and energy storage can give full play to the capacity advantages and economic advantages of various dynamic reactive power regulation devices, and achieve the safe and stable operation of the power grid and the maximum consumption of new energy.

[0004] At present, a large number of studies have been carried out on the compensation technology of dynamic reactive power regulation equipment for new energy grid connection in the existing technology. Some have carried out research on the planning and configuration scheme of synchronous condensers participating in reactive power compensation of the power system; some have carried out research on the planning and configuration scheme of static var generators (SVG) participating in reactive power compensation of the power system; and some have carried out research on the capacity configuration of energy storage participating in new energy consumption. These studies only consider the role of a single regulation device and do not consider the comprehensive configuration of multiple devices such as synchronous condensers, SVG, static var compensators (SVC), and energy storage. Summary of the Invention

[0005] In view of this, the present invention provides a method and system for coordinated optimization configuration of a reactive power compensation device and energy storage to solve at least one of the above-mentioned problems.

[0006] To achieve the above object, the present invention adopts the following solutions:

[0007] According to the first aspect of the present invention, an embodiment of the present invention provides a method for coordinated optimal configuration of a reactive power compensation device and energy storage, the method comprising: establishing a short-circuit ratio index constraint model for ensuring the grid strength of a new energy cluster system and improving the grid voltage support ability; establishing a two-layer optimal configuration model with the minimum total system cost index, the minimum curtailment rate index, and the maximum system strength index as the objectives, wherein the upper layer of the two-layer optimal configuration model is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model; the upper layer model transmits the reactive power compensation device and energy storage configuration information to the lower layer model, and the lower layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result, and feeds back the optimization result to the upper layer model, so that the upper layer model can calculate the objective function value of the upper layer model according to the optimization result.

[0008] Preferably, in the two-layer optimal configuration model in the method of the embodiment of the present invention, it includes: a first objective function F1 representing the minimization of the total system cost, and the first objective function F1 includes a reactive power compensation device investment cost parameter, an energy storage investment cost parameter, and a system operation cost parameter.

[0009] Preferably, the reactive power compensation device in the method of the embodiment of the present invention includes: a synchronous condenser, a static var generator SVG, and a static var compensator SVC, and the reactive power compensation device investment cost parameter is obtained according to the number, unit capacity investment cost, and investment capacity of the synchronous condenser, SVG, and SVC; the energy storage investment cost parameter is obtained according to the number, unit capacity investment cost, and investment capacity of the energy storage device; the system operation cost parameter is obtained according to the number and unit operation cost of thermal power units, synchronous condensers, SVG, and energy storage devices, and the power generation power of thermal power units, the charging power of energy storage devices, the discharging power of energy storage devices, the reactive power of SVG, and the reactive power of synchronous condensers.

[0010] Preferably, in the two-layer optimal configuration model in the method of the embodiment of the present invention, it includes: a second objective function F2 for ensuring the grid strength of the new energy cluster system, and the second objective function F2 includes a reactive power compensation device investment cost parameter, the number parameters of photovoltaic power stations and wind farms, and the curtailment penalty item parameters of photovoltaic power stations and wind farms based on the short-circuit ratio index constraint model.

[0011] Preferably, the curtailment penalty item parameter of the photovoltaic power station in the method of the embodiment of the present invention is obtained according to the maximum theoretical output of the photovoltaic power station and the limit value of the photovoltaic power that can be absorbed under the short-circuit ratio constraint; the curtailment penalty item parameter of the wind farm is obtained according to the maximum theoretical output of the wind farm and the limit value of the wind power that can be absorbed under the short-circuit ratio index constraint model.

[0012] Preferably, the double-layer optimization configuration model in the above method of the embodiment of the present invention includes: a third objective function F3 based on the curtailment rate index constraint for improving the new energy consumption capacity, and the third objective function F3 includes energy storage investment cost parameters, the number of parameters of photovoltaic power stations and wind farms, and the consumption penalty term parameters of photovoltaic power stations and wind farms based on the new energy curtailment rate index constraint model.

[0013] Preferably, the consumption penalty term parameter of the photovoltaic power station in the above method of the embodiment of the present invention is obtained according to the maximum theoretical output of the photovoltaic power station and the consumable photovoltaic power; the consumption penalty term parameter of the wind farm is obtained according to the maximum theoretical output of the wind farm and the consumable wind power.

[0014] Preferably, in the above method of the embodiment of the present invention, the maximum investment capacities of energy storage devices, SVG, SVC, and synchronous condensers are constrained by an investment capacity constraint model.

[0015] Preferably, the short-circuit ratio index constraint model in the above method of the embodiment of the present invention includes a photovoltaic power station short-circuit ratio constraint model and a wind farm short-circuit ratio constraint model. The expression of the photovoltaic power station short-circuit ratio constraint model is as follows:

[0016]

[0017] The expression of the wind farm short-circuit ratio constraint model is as follows:

[0018]

[0019] Wherein, is the short-circuit capacity of the power supply node ex at time t; and are the apparent powers of the photovoltaic power station and the wind farm respectively; is the apparent power of the power supply node new at time t; r new / ex,t is the voltage interaction influence factor between the power supply nodes new and ex at time t; and represent 0-1 variables indicating whether the positions pv and wd use reactive power compensation of new energy units. 1 means that reactive power compensation is carried out using the reactive power of the new energy unit itself at the corresponding position, and 0 means that reactive power compensation is not carried out using the reactive power of the new energy unit itself at the corresponding position; and represent 0-1 variables indicating whether SVG and synchronous condensers are configured at the positions svg and sc; and are the reactive powers generated by the photovoltaic power station pv and the wind farm wd at time t respectively; and represent the SVG reactive power and the synchronous condenser reactive power at time t respectively; and The installed capacities of photovoltaic and wind power respectively; and represent the maximum theoretical output of the photovoltaic power station pv and the wind power station wd at time t; ΔV new,t and ΔV ex,t represent the voltage change amounts of the power supply nodes new and ex at time t; and are the mutual impedance and self-impedance of the power supply nodes new and ex at time t respectively.

[0020] Preferably, in the double-layer optimal configuration model of the above method of the embodiment of the present invention, the operation constraints of the thermal power units are satisfied, including the maximum output and minimum output constraints of the thermal power units, and the up and down ramp constraints of the thermal power units.

[0021] Preferably, in the double-layer optimal configuration model of the above method of the embodiment of the present invention, the operation constraints of new energy are satisfied, including the maximum output constraints of the wind power station and the photovoltaic power station, the processing limit constraints calculated by the short-circuit ratio constraints, and the reactive power output constraints of the wind power station and the photovoltaic power station.

[0022] Preferably, when a synchronous condenser is used for reactive power compensation in the above method of the embodiment of the present invention, the operation constraint expression of the synchronous condenser is as follows:

[0023]

[0024] Wherein, h SC represents the reactive power reserve coefficient of the synchronous condenser; represents the reactive power output of the synchronous condenser installed at the position sc; represents a 0-1 variable indicating whether a synchronous condenser is configured at the position sc, 1 means a synchronous condenser is installed at the corresponding position, and 0 means not installed; represents the investment capacity of the synchronous condenser at the position sc.

[0025] Preferably, when an SVG is used for reactive power compensation in the above method of the embodiment of the present invention, the reactive power output of the SVG is 10% of the active power output of the power supply, and the operation constraint expression of the SVG is as follows:

[0026]

[0027] Wherein, represents the SVG reactive power at time t; represents a 0-1 variable indicating whether an SVG is configured at the position svg, 1 means an SVG is installed at the corresponding position, and 0 means not installed; is the set of the outputs of the photovoltaic power station and the wind power station at time t; and respectively represent the photovoltaic and wind power that can be absorbed by the photovoltaic power station pv and the wind power station wd at time t.

[0028] Preferably, the energy storage configuration model in the above method of the embodiment of the present invention includes power range constraint, energy range constraint, power-energy relationship constraint, cycle period constraint, and initial and end state constraint.

[0029] Preferably, the double-layer optimal configuration model in the above method of the embodiment of the present invention satisfies the power flow operation constraint, including line capacity constraint of power flow, DC power flow constraint, and node phase angle range constraint.

[0030] Preferably, the double-layer optimal configuration model in the above method of the embodiment of the present invention satisfies the power balance constraint, and the expression of the power balance constraint is as follows:

[0031]

[0032] Wherein, respectively represent the thermal power unit, wind farm, photovoltaic power station, and energy storage device used at node n; represents the set of lines with node n as the starting node, represents the set of lines with node n as the end node; represents the output of the unit at time t; represents the wind power that can be absorbed by the wind power station wd at time t; represents the photovoltaic power that can be absorbed by the photovoltaic power station pv at time t; and respectively represent the discharge power and charge power of the energy storage device at time t; represents the tie line power at time t; represents the system load value at time t.

[0033] Preferably, the double-layer optimal configuration model in the above method of the embodiment of the present invention satisfies the reserve constraint, and the expression of the reserve constraint is as follows:

[0034]

[0035] Wherein, P R is the system spinning reserve capacity, N G , N PV , N WD are the numbers of thermal power units, photovoltaic power stations, and wind power stations respectively; represents the binary variable of the operation state of the thermal power unit, 1 represents operation, and 0 represents stop; and respectively represent the photovoltaic power and wind power that can be absorbed by the photovoltaic power station pv and the wind power station wd at time t; represents the maximum output of the thermal power unit; Represents the system load value at time t.

[0036] According to the second aspect of the present invention, an embodiment of the present invention provides a reactive power compensation device and energy storage coordinated optimization configuration system. The system includes: a short-circuit ratio index constraint model establishment unit for establishing a short-circuit ratio index constraint model to ensure the power grid strength of the new energy cluster system and improve the power grid voltage support ability; a two-layer optimization configuration model establishment unit for establishing a two-layer optimization configuration model with the objectives of minimizing the total system cost index, minimizing the curtailment rate index, and maximizing the system strength index. The upper layer of the two-layer optimization configuration model is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model. The upper layer model in the two-layer optimization configuration model transmits the reactive power compensation device and energy storage configuration information to the lower layer model. The lower layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result, and feeds back the optimization result to the upper layer model, so that the upper layer model can calculate the objective function value of the upper layer model based on the optimization result.

[0037] According to the third aspect of the present invention, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0038] According to the fourth aspect of the present invention, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0039] According to the fifth aspect of the present invention, an embodiment of the present invention further provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the steps of the above method are implemented.

[0040] The reactive power compensation device and energy storage coordinated optimization configuration method and system proposed by the present invention establish a short-circuit ratio index constraint model considering various reactive power compensation measures based on the influence mechanism of synchronous condensers, SVCs, SVG, and the reactive power of new energy itself on the system short-circuit ratio, to quantify the power grid strength of the new energy cluster system. With the goal of improving the power grid strength of the system, a comprehensive configuration of reactive power compensation devices is carried out. In addition, a multi-objective two-layer hybrid reactive power compensation device and energy storage coordinated optimization configuration method with the objectives of minimizing the total system cost, maximizing the power grid strength of the system, and minimizing the curtailment rate of new energy can balance economy and the safety of the new energy cluster system. Description of the Drawings

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings. In the accompanying drawings:

[0042] Figure 1 is a schematic flowchart of a method for coordinated optimization configuration of a reactive power compensation device and energy storage provided by an embodiment of the present application;

[0043] Figure 2 is a schematic structural diagram of a system for coordinated optimization configuration of a reactive power compensation device and energy storage provided by an embodiment of the present application;

[0044] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Specific embodiments

[0045] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer and more understandable, the following will further elaborate on the embodiments of the present invention in conjunction with the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but not to limit the present invention.

[0046] As Figure 1 shown is a schematic flowchart of a method for coordinated optimization configuration of a reactive power compensation device and energy storage provided by an embodiment of the present application. The method includes the following steps:

[0047] Step S101: Establish a short-circuit ratio index constraint model to ensure the grid strength of the new energy cluster system and improve the grid voltage support ability.

[0048] Step S102: Establish a two-layer optimization configuration model with the objectives of minimizing the total system cost index, minimizing the curtailment rate index, and maximizing the system strength index. The upper layer of the two-layer optimization configuration model is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model.

[0049] Step S103: The upper layer model transmits the reactive power compensation device and energy storage configuration information to the lower layer model. The lower layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result, and feeds back the optimization result to the upper layer model, so that the upper layer model can calculate the objective function value of the upper layer model based on the optimization result.

[0050] Preferably, the double-layer optimization configuration model in the above step S102 includes: a first objective function F1 representing the minimization of the total system cost, and the first objective function F1 includes reactive power compensation device investment cost parameters, energy storage investment cost parameters, and system operation cost parameters.

[0051] Further preferably, the reactive power compensation device includes: a synchronous condenser, a static var generator SVG, and a static var compensator SVC. The reactive power compensation device investment cost parameters are obtained based on the quantity, unit capacity investment cost, and investment capacity of the synchronous condenser, SVG, and SVC; the energy storage investment cost parameters are obtained based on the quantity, unit capacity investment cost, and investment capacity of the energy storage device; the system operation cost parameters are obtained based on the quantity and unit operation cost of thermal power units, synchronous condensers, SVG, and energy storage devices, as well as the power generation power of thermal power units, the charging power of energy storage devices, the discharging power of energy storage devices, the reactive power of SVG, and the reactive power of synchronous condensers.

[0052] Specifically, the above first objective function F1, reactive power compensation device investment cost parameters, energy storage investment cost parameters, and system operation cost parameters can be determined by the following formulas (1)-(4):

[0053]

[0054] Among them, C OPR respectively represent the reactive power compensation device investment cost, energy storage investment cost, and system operation cost; a SC 、a SVC 、a SVG are respectively the unit capacity investment costs of the synchronous condenser, SVC, and SVG, in units of 10,000 yuan / MVar, are respectively the investment capacities of the corresponding reactive power compensation devices at positions sc, svc, and svg, in units of MVar; a ES,P is the unit power investment cost of the energy storage, in 10,000 yuan / MW, and the energy storage investment power at the corresponding position es is in units of MW; a ES,E is the unit capacity investment cost of the energy storage, in 10,000 yuan / MWh, and the energy storage investment capacity at the corresponding position es is in units of MWh; respectively represent the 0-1 variables of whether reactive power compensation devices and energy storage are configured at positions sc, svc, svg, and es. 1 indicates that a reactive power compensation device or energy storage is installed at the corresponding position, and 0 indicates that no reactive power compensation device or energy storage is installed; N G 、N SC 、N SVG 、N ES are respectively the quantities of thermal power units, SVG, synchronous condensers, and energy storage devices, N TIt represents the total time of the sequential production simulation operation, and in this paper, it is taken as 8760 h; c SC and c SVG and c ES are respectively the unit power generation cost of the thermal power unit, the unit operation cost of the synchronous condenser, SVG, and energy storage; are respectively the power generation power of the thermal power unit, the charging power of the energy storage device, and the discharging power of the energy storage device at time t, with the unit of MW; are respectively the reactive power of SVG and the reactive power of the synchronous condenser at time t, with the unit of MVar.

[0055] Preferably, the double-layer optimization configuration model in the above step S102 includes: the second objective function F2 for ensuring the grid strength of the new energy cluster system. In this embodiment, in order to ensure the safe and stable operation of the new energy cluster system, a grid strength model quantified based on the short-circuit ratio index is proposed, considering the hybrid reactive power compensation configuration, and the second objective function F2 is established. The second objective function F2 includes the investment cost parameter of the reactive power compensation device, the number parameters of the photovoltaic power station and the wind farm, and the consumption penalty item parameter of the photovoltaic power station and the wind farm based on the system short-circuit ratio index constraint model.

[0056] Further preferably, the consumption penalty item parameter of the above photovoltaic power station is obtained according to the maximum theoretical output of the photovoltaic power station and the limit value of the photovoltaic power that can be consumed under the short-circuit ratio constraint; the consumption penalty item parameter of the wind farm is obtained according to the maximum theoretical output of the wind farm and the limit value of the wind power that can be consumed under the short-circuit ratio index constraint model.

[0057] Specifically, the above second objective function F2, the consumption penalty item parameter of the photovoltaic power station, and the consumption penalty item parameter of the wind farm can be determined by the following formulas (5)-(7):

[0058]

[0059]

[0060] Among them, N PV and N WD respectively represent the numbers of the photovoltaic power station and the wind farm; and are respectively the consumption penalty items of each new energy power station of the photovoltaic power station pv and the wind farm wd based on the system short-circuit ratio index constraint; N T represents the total time of the sequential production simulation operation; and respectively represent the maximum theoretical outputs of the photovoltaic power station pv and the wind farm wd at time t, and They respectively represent the limits of the photovoltaic and wind power that can be absorbed by the photovoltaic power station pv and the wind power station wd at time t under the short-circuit ratio constraint.

[0061] Preferably, the double-layer optimal configuration model in the above step S102 includes: a third objective function F3 based on the curtailment rate index constraint to improve the new energy absorption capacity. The third objective function F3 includes the energy storage investment cost parameter, the number parameters of the photovoltaic power station and the wind power station, and the absorption penalty term parameter of the photovoltaic power station and the wind power station based on the new energy curtailment rate index constraint model.

[0062] Further preferably, the absorption penalty term parameter of the photovoltaic power station is obtained based on the maximum theoretical output value and the absorbable photovoltaic power of the photovoltaic power station; the absorption penalty term parameter of the wind power station is obtained based on the maximum theoretical output value and the absorbable wind power of the wind power station.

[0063] Specifically, the above third objective function F3, the absorption penalty term parameter of the photovoltaic power station, and the absorption penalty term parameter of the wind power station can be determined by the following formulas (8)-(10):

[0064]

[0065]

[0066] Among them, and are respectively the absorption penalty terms of each new energy power station of the photovoltaic power station pv and the wind power station wd based on the new energy curtailment rate index constraint. When the curtailment rate of the new energy power station is greater than 5%, take 10 10 , otherwise it is 0; and respectively represent the photovoltaic and wind power that can be absorbed by the photovoltaic power station pv and the wind power station wd at time t.

[0067] Preferably, in this embodiment, considering the limitations of various reactive power compensation, energy storage technology conditions and site factors, it is necessary to constrain its maximum investment capacity, that is, to constrain the maximum investment capacity of energy storage devices, SVG, SVC and synchronous condensers through the investment capacity constraint model. Specifically, the investment capacity constraint model is shown in the following formulas (11)-(15):

[0068]

[0069] Among them, B ES represents the capacity-storage ratio of the energy storage; are respectively the maximum investment capacities of the energy storage, SVC, SVG and synchronous condenser; is the energy storage investment power at position es; is the energy storage investment capacity at position es; They are the investment capacities of the corresponding reactive power compensation devices at positions sc, SVC, and SVG, respectively.

[0070] Preferably, to ensure the grid connection strength of the new energy cluster system and improve the grid voltage support capacity, in this embodiment, a short-circuit ratio index constraint model is established. The following formula (16) shows the coupling mechanism of the influence of different reactive power compensation methods on the system short-circuit capacity:

[0071]

[0072] The above short-circuit ratio index constraint model includes a short-circuit ratio constraint model for photovoltaic power stations and a short-circuit ratio constraint model for wind power stations. The expression of the short-circuit ratio constraint model for photovoltaic power stations is as follows in formula (17):

[0073]

[0074] The expression of the short-circuit ratio constraint model for wind power stations is as follows in formula (18):

[0075]

[0076] Among them, the function f1 indicates that the system impedance matrix is related to the on-off state of conventional units, the capacity of synchronous condensers, and the capacity of SVCs. That is, the system impedance matrix will change with the on-off state of the units, the configured capacity of synchronous condensers, and the capacity of SVCs; is the system impedance matrix at time t, is to extract the self-impedance and mutual-impedance of each power supply node from the system impedance matrix, is the equivalent impedance of thermal power unit g, and are the mutual-impedance and self-impedance of power supply nodes new and ex at time t, respectively; is the short-circuit capacity of power supply node ex at time t; and are the apparent powers of the photovoltaic power station and the wind power station, respectively; is the apparent power of power supply node new at time t; r new / ex,t is the voltage interaction influence factor between power supply nodes new and ex at time t; and represent 0-1 variables indicating whether the reactive power compensation of new energy units is used at positions pv and wd. 1 means that the reactive power of the new energy units themselves is used for reactive power compensation at the corresponding positions, and 0 means that the reactive power of the new energy units themselves is not used for reactive power compensation at the corresponding positions; and represent 0-1 variables indicating whether SVG and synchronous condensers are configured at positions SVG and sc; and are the reactive powers generated by the photovoltaic power station pv and the wind power station wd at time t, respectively; and respectively represent the SVG reactive power and the synchronous condenser reactive power at time t; and are respectively the installed capacities of photovoltaic and wind power; and represent the maximum theoretical output of the photovoltaic power station pv and the wind power station wd at time t; ΔV new,t and ΔV ex,t represent the voltage change amounts of the power supply nodes new and ex at time t; and are respectively the mutual impedance and self-impedance of the power supply nodes new and ex at time t.

[0077] Preferably, the power grid system in the double-layer optimal configuration model needs to satisfy the operating constraints of thermal power units, including the maximum output and minimum output constraints of thermal power units, and the up and down ramp constraints of thermal power units. The specific thermal power unit constraints are as shown in the following formulas (19) and (20):

[0078]

[0079] wherein, represents the unit output at time t, and respectively represent the maximum output and minimum output of the thermal power unit, and are respectively the up and down ramp constraints of the unit; represents the binary variable of the operating state of the thermal power unit, 1 represents operating, and 0 represents not operating.

[0080] Preferably, the power grid system in the double-layer optimal configuration model also needs to satisfy the operating constraints of new energy, including the maximum output constraints of wind power stations and photovoltaic power stations, the processing limit constraints calculated by the short-circuit ratio constraints, and the reactive power output constraints of wind power stations and photovoltaic power stations.

[0081] Specifically, the outputs of wind power stations and photovoltaic power stations should be less than their maximum theoretical outputs, as shown in the following formulas (21) and (22):

[0082]

[0083] wherein, and respectively represent the photovoltaic and wind power that can be absorbed by the photovoltaic power station pv and the wind power station wd at time t.

[0084] The outputs of wind power stations and photovoltaic power stations should be less than the new energy output limits calculated by the short-circuit ratio constraints, as shown in the following formulas (23) and (24):

[0085]

[0086] Among them, and are the output limits calculated by the short-circuit ratio constraint.

[0087] The reactive power output constraints of the wind farm and the photovoltaic power station are shown in the following formulas (25) and (26):

[0088]

[0089] Among them, and are the reactive powers generated by the photovoltaic power station pv and the wind farm wd at time t, respectively; and represent the 0-1 variables indicating whether the new energy units are used for reactive power compensation at positions pv and wd. 1 means that the reactive power of the new energy unit itself is used for reactive power compensation at the corresponding position, and 0 means no reactive power compensation.

[0090] Preferably, when a synchronous condenser is used for reactive power compensation in the above steps, the operation constraint expression of the synchronous condenser is shown in the following formula (27):

[0091]

[0092] Among them, h SC represents the reactive power reserve coefficient of the synchronous condenser; represents the reactive power output of the synchronous condenser installed at position sc; represents the 0-1 variable indicating whether a synchronous condenser is configured at position sc. 1 means that a synchronous condenser is installed at the corresponding position, and 0 means not installed; represents the investment capacity of the synchronous condenser at position sc.

[0093] Preferably, when an SVG is used for reactive power compensation in the above steps, the reactive power output of the SVG is 10% of the active power output of the power supply, and the operation constraint expression of the SVG is shown in the following formula (28):

[0094]

[0095] Among them, represents the SVG reactive power at time t; represents the 0-1 variable indicating whether an SVG is configured at position svg. 1 means that an SVG is installed at the corresponding position, and 0 means not installed; is the set of the outputs of the photovoltaic power station and the wind farm at time t; and represent the photovoltaic and wind power that can be absorbed by the photovoltaic power station pv and the wind farm wd at time t, respectively.

[0096] Preferably, the energy storage configuration model in the above step S102 includes power range constraint, energy range constraint, power-energy relationship constraint, cycle period constraint, and initial and final state constraints, and its specific operation constraints are shown in the following formulas (29)-(33):

[0097]

[0098]

[0099] wherein, are the charging power and discharging power of the energy storage at time t, respectively; is the energy level of the energy storage; h ch 、h dis 、h self are the charging efficiency, discharging efficiency, and self-loss efficiency of the energy storage, respectively; N ST is the cycle period of the energy storage; δ is the initial energy level of the energy storage.

[0100] Preferably, the power grid system in the above double-layer optimal configuration model also satisfies the power flow operation constraints, including line capacity constraint of power flow, DC power flow constraint, and node phase angle range constraint, which are specifically shown in the following formulas (34)-(36):

[0101]

[0102] wherein, and represent the power flow and line capacity on line l, W LE represents the set of existing lines, q l(+),t and q l(-),t represent the phase angles of the start node and end node of line l, respectively. Formula (28) indicates that the line power flow is not greater than its line capacity, formula (29) indicates that the power flow satisfies the DC power flow constraint, and formula (30) constrains the node phase angle range.

[0103] Preferably, the power grid system in the above double-layer optimal configuration model also needs to satisfy the power balance constraint, and the expression of the power balance constraint is as follows formula (37):

[0104]

[0105] wherein, represent the thermal power units, wind farms, photovoltaic power plants, and energy storage devices used at node n, respectively; represents the set of lines with node n as the start node, represents the set of lines with node n as the end node; represents the unit output at time t; represents the wind power that can be absorbed by the wind farm wd at time t; It represents the PV power that can be absorbed by the PV power station at time t. and respectively represent the discharge power and charge power of the energy storage device at time t. It represents the tie-line power at time t. It represents the system load value at time t.

[0106] Preferably, the power grid system in the above double-layer optimal configuration model also needs to satisfy the reserve constraint, and the reserve constraint expression is as follows in formula (38):

[0107]

[0108] Where, P R is the system spinning reserve capacity, N G , N PV , N WD are the numbers of thermal power units, PV power stations and wind power stations respectively; is a binary variable representing the operating state of the thermal power unit, 1 represents operating, and 0 represents stopped; and respectively represent the PV power and wind power that can be absorbed by the PV power station pv and the wind power station wd at time t; represents the maximum output of the thermal power unit; represents the system load value at time t.

[0109] For the reactive power compensation device and energy storage coordinated optimal configuration method proposed by the present invention, based on the influence mechanism of synchronous condensers, SVC, SVG and the reactive power of new energy itself on the system short-circuit ratio, a short-circuit ratio index constraint model considering various reactive power compensation measures is established to quantify the grid strength of the new energy cluster system. With the goal of improving the grid strength of the system, the comprehensive configuration of the reactive power compensation device is carried out; in addition, the multi-objective double-layer hybrid reactive power compensation device and energy storage coordinated optimal configuration method with the goals of minimizing the total cost of the system, maximizing the grid strength of the system and minimizing the new energy curtailment rate can take into account both economy and the safety of the new energy cluster system.

[0110] As Figure 2 shown is a schematic structural diagram of a reactive power compensation device and energy storage coordinated optimal configuration system provided by an embodiment of the present invention. The system includes: a short-circuit ratio index constraint model establishment unit 210 and a double-layer optimal configuration model establishment unit 220.

[0111] The short-circuit ratio index constraint model establishment unit 210 is used to establish a short-circuit ratio index constraint model for ensuring the grid strength of the new energy cluster system and improving the grid voltage support ability.

[0112] The double - layer optimal configuration model establishment unit 220 is used to establish a double - layer optimal configuration model with the objectives of minimizing the total system cost index, minimizing the curtailment rate index, and maximizing the system strength index. The upper layer of the double - layer optimal configuration model is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model.

[0113] In the upper - layer model of the double - layer optimal configuration model, the reactive power compensation device and energy storage configuration information are sent to the lower - layer model. The lower - layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result, and feeds back the optimization result to the upper - layer model, so that the upper - layer model can calculate the objective function value of the upper - layer model based on the optimization result.

[0114] For the specific descriptions related to the double - layer optimal configuration model, reference can be made to the descriptions in the foregoing method embodiments, and details will not be elaborated here.

[0115] The reactive power compensation device and energy storage coordinated optimal configuration system proposed by the present invention establishes a short - circuit ratio index constraint model considering various reactive power compensation measures based on the influence mechanism of synchronous condensers, SVC, SVG, and the reactive power of new energy itself on the system short - circuit ratio, quantifies the grid strength of the new - energy cluster system, and conducts comprehensive configuration of reactive power compensation devices with the goal of improving the grid strength of the system. In addition, the multi - objective double - layer hybrid reactive power compensation device and energy storage coordinated optimal configuration method with the objectives of minimizing the total system cost, maximizing the grid strength of the system, and minimizing the curtailment rate of new energy can balance economy and the safety of the new - energy cluster system.

[0116] Figure 3 It is a schematic diagram of an electronic device provided in an embodiment of the present invention. Figure 3 The shown electronic device is a general - purpose data - processing device, which includes a general computer hardware structure and at least includes a processor 801 and a memory 802. The processor 801 and the memory 802 are connected through a bus 803. The memory 802 is suitable for storing one or more instructions or programs executable by the processor 801. The one or more instructions or programs are executed by the processor 801 to implement the steps in the above - mentioned method for suppressing low - frequency oscillations.

[0117] The above-mentioned processor 801 can be an independent microprocessor or a set of one or more microprocessors. Thus, the processor 801 processes data and controls other devices by executing the commands stored in the memory 802, thereby implementing the method flow of the embodiments of the present invention as described above. The bus 803 connects the above-mentioned multiple components together and also connects the above-mentioned components to the display controller 804, the display device, and the input / output (I / O) device 805. The input / output (I / O) device 805 can be a mouse, a keyboard, a modem, a network interface, a touch input device, a somatosensory input device, a printer, and other devices well-known in the art. Typically, the input / output (I / O) device 805 is connected to the system through the input / output (I / O) controller 806.

[0118] Among them, the memory 802 can store software components, such as an operating system, a communication module, an interaction module, and application programs. Each of the above-mentioned modules and application programs corresponds to a set of executable program instructions for completing one or more functions and the methods described in the embodiments of the invention.

[0119] The embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for coordinated optimal configuration of a reactive power compensation device and energy storage are implemented.

[0120] The embodiments of the present invention also provide a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the steps of the above-mentioned method for coordinated optimal configuration of a reactive power compensation device and energy storage are implemented.

[0121] In summary, for the method and system for coordinated optimal configuration of a reactive power compensation device and energy storage proposed by the present invention, based on the influence mechanism of the synchronous condenser, SVC, SVG, and the reactive power of new energy itself on the system short-circuit ratio, a short-circuit ratio index constraint model considering various reactive power compensation measures is established to quantify the grid strength of the new energy cluster system. With the goal of improving the grid strength of the system, the comprehensive configuration of the reactive power compensation device is carried out; in addition, the multi-objective two-layer hybrid method for coordinated optimal configuration of a reactive power compensation device and energy storage with the goals of minimizing the total cost of the system, maximizing the grid strength of the system, and minimizing the new energy curtailment rate can take into account both economy and the safety of the new energy cluster system.

[0122] The preferred embodiments of the present invention have been described above with reference to the accompanying drawings. Many features and advantages of these embodiments are apparent from this detailed description, and thus the claims are intended to cover all such features and advantages of these embodiments that fall within their true spirit and scope. In addition, since many modifications and variations are readily envisioned by those skilled in the art, the embodiments of the present invention are not to be limited to the exact construction and operation illustrated and described, but may cover all suitable modifications and equivalents that fall within their scope.

[0123] Those skilled in the art will appreciate that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

[0124] The present invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processors of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processors of the computer or other programmable data processing device create means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0125] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0127] In the specific embodiments described above, the object, technical solution and beneficial effects of the present invention have been further described in detail. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for coordinated optimization configuration of a reactive power compensation device and energy storage, characterized in that, The method includes: Establishing a short-circuit ratio index constraint model for ensuring the grid strength of the new energy cluster system and improving the grid voltage support ability; Establishing a two-layer optimal configuration model with the objectives of minimizing the total system cost index, minimizing the curtailment rate index, and maximizing the system strength index. The upper layer of the two-layer optimal configuration model is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model; The upper-layer model transmits the reactive power compensation device and energy storage configuration information to the lower-layer model. The lower-layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result, and feeds back the optimization result to the upper-layer model, so that the upper-layer model calculates the objective function value of the upper-layer model based on the optimization result; The two-layer optimal configuration model includes: a first objective function F1 representing minimizing the total system cost, and the first objective function F1 includes reactive power compensation device investment cost parameters, energy storage investment cost parameters, and system operation cost parameters; a second objective function F2 for ensuring the grid strength of the new energy cluster system, and the second objective function F2 includes reactive power compensation device investment cost parameters, the number of photovoltaic power stations and wind farms, and the curtailment penalty term parameters of photovoltaic power stations and wind farms based on the system short-circuit ratio index constraint model; a third objective function F3 based on the curtailment rate index constraint for improving the new energy consumption capacity, and the third objective function F3 includes energy storage investment cost parameters, the number of photovoltaic power stations and wind farms, and the curtailment penalty term parameters of photovoltaic power stations and wind farms based on the new energy curtailment rate index constraint model.

2. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1, characterized in that, The reactive power compensation device includes: a synchronous condenser, a static var generator SVG, and a static var compensator SVC. The reactive power compensation device investment cost parameters are obtained based on the number, unit capacity investment cost, and investment capacity of the synchronous condenser, SVG, and SVC; the energy storage investment cost parameters are obtained based on the number, unit capacity investment cost, and investment capacity of the energy storage device; the system operation cost parameters are obtained based on the number and unit operation cost of thermal power units, synchronous condensers, SVG, and energy storage devices, as well as the power generation power of thermal power units, the charging power of energy storage devices, the discharging power of energy storage devices, the reactive power of SVG, and the reactive power of synchronous condensers.

3. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1, characterized in that, The curtailment penalty term parameters of the photovoltaic power station are obtained based on the maximum theoretical output value of the photovoltaic power station and the limit value of the photovoltaic power that can be consumed under the short-circuit ratio constraint; the curtailment penalty term parameters of the wind farm are obtained based on the maximum theoretical output value of the wind farm and the limit value of the wind power that can be consumed under the short-circuit ratio index constraint model.

4. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1, characterized in that, The curtailment penalty term parameters of the photovoltaic power station are obtained based on the maximum theoretical output value of the photovoltaic power station and the photovoltaic power that can be consumed; the curtailment penalty term parameters of the wind farm are obtained based on the maximum theoretical output value of the wind farm and the wind power that can be consumed.

5. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 2, characterized in that, Constraining the maximum investment capacity of energy storage devices, SVG, SVC, and synchronous condensers through an investment capacity constraint model.

6. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1 or 3, characterized in that, The short-circuit ratio index constraint model includes a photovoltaic power station short-circuit ratio constraint model and a wind farm short-circuit ratio constraint model. The expression of the photovoltaic power station short-circuit ratio constraint model is as follows: The short-circuit ratio constraint model expression of the wind farm station is as follows: Among them, is the short-circuit capacity of the power supply node ex at time t; and are the apparent powers of the photovoltaic power station and the wind farm respectively; is the apparent power of the power supply node new at time t; r new / ex,t is the voltage interaction influence factor between the power supply nodes new and ex at time t; and are 0-1 variables indicating whether the new energy unit reactive power compensation is utilized at positions pv and wd. 1 means that the reactive power of the new energy unit itself is used for reactive power compensation at the corresponding position, and 0 means that the reactive power of the new energy unit itself is not used for reactive power compensation at the corresponding position; and are 0-1 variables indicating whether SVG and synchronous condensers are configured at positions svg and sc; and are the reactive powers generated by the photovoltaic power station pv and the wind farm wd at time t respectively; and represent the SVG reactive power and the synchronous condenser reactive power at time t respectively; and are the installed capacities of photovoltaic and wind power respectively; and represent the maximum theoretical output values of the photovoltaic power station pv and the wind farm wd at time t; ΔV new,t and ΔV ex,t represent the voltage change amounts at the power supply nodes new and ex at time t; and are the mutual impedance and self-impedance of the power supply nodes new and ex at time t respectively.

7. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1, characterized in that, The double-layer optimal configuration model satisfies the operating constraints of thermal power units, including the maximum and minimum output constraints of thermal power units, as well as the up and down ramp constraints of thermal power units.

8. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1, characterized in that, The double-layer optimal configuration model satisfies the operating constraints of new energy, including the maximum output constraints of wind farm stations and photovoltaic power stations, the processing limit constraints calculated by short-circuit ratio constraints, and the reactive power output constraints of wind farm stations and photovoltaic power stations.

9. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 2, characterized in that, When a synchronous condenser is used for reactive power compensation, the operating constraint expression of the synchronous condenser is as follows: Among them, h SC represents the reactive power reserve coefficient of the synchronous condenser; represents the reactive power output of the synchronous condenser installed at location sc; represents a 0-1 variable indicating whether a synchronous condenser is configured at location sc, where 1 means a synchronous condenser is installed at the corresponding location and 0 means not installed; represents the investment capacity of the synchronous condenser at location sc.

10. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 2, characterized in that, When an SVG is used for reactive power compensation, the reactive power output of the SVG is 10% of the active power output of the power source, and the operating constraint expression of the SVG is as follows: Among them, represents the SVG reactive power at time t; represents the 0-1 variable indicating whether SVG is configured at the position of svg. 1 means SVG is installed at the corresponding position, and 0 means it is not installed; is the set of the outputs of the PV power station and the wind power station at time t; and respectively represent the PV and wind power that can be absorbed by the PV power station pv and the wind power station wd at time t.

11. The method for coordinated optimization configuration of a reactive power compensation device and energy storage according to claim 1, characterized in that, The energy storage configuration model includes power range constraints, energy range constraints, power-energy relationship constraints, cycle period constraints, and initial and final state constraints.

12. The reactive power compensation device and energy storage coordinated optimization configuration method according to claim 1, wherein, The double-layer optimal configuration model satisfies the power flow operating constraints, including the line capacity constraints of the power flow, the DC power flow constraints, and the node phase angle range constraints.

13. The reactive power compensation device and energy storage coordinated optimization configuration method according to claim 1, wherein, The double-layer optimal configuration model satisfies the power balance constraint, and the power balance constraint expression is as follows: Among them, respectively represent the thermal power unit, wind farm, photovoltaic power station, and energy storage device used at node n; represents the set of lines with node n as the starting node, represents the set of lines with node n as the ending node; represents the output of the unit at time t; represents the wind power that can be absorbed by the wind farm wd at time t; represents the photovoltaic power that can be absorbed by the photovoltaic power station pv at time t; and respectively represent the discharge power and charge power of the energy storage device at time t; represents the tie-line power at time t; represents the system load value at time t.

14. The reactive power compensation device and energy storage coordinated optimization configuration method according to claim 1, wherein, The double-layer optimal configuration model satisfies the reserve constraint, and the reserve constraint expression is as follows: Among them, P R is the system's spinning reserve capacity, N G , N PV , N WD are the numbers of thermal power units, PV power stations, and wind power stations respectively; is a binary variable representing the operating state of the thermal power unit, where 1 represents operating and 0 represents stopped; and represent the PV power and wind power that can be absorbed by the PV power station pv and the wind power station wd at time t respectively; represents the maximum output of the thermal power unit; represents the system load value at time t.

15. A reactive power compensation device and energy storage coordinated optimization configuration system, wherein, The system includes: A short-circuit ratio index constraint model establishment unit for establishing a short-circuit ratio index constraint model to ensure the grid strength of the new energy cluster system and improve the grid voltage support ability; A double-layer optimal configuration model establishment unit for establishing a double-layer optimal configuration model with the minimum system total cost index, the minimum curtailment rate index, and the maximum system strength index as the objectives. The upper layer of the double-layer optimal configuration model is a reactive power compensation device and energy storage configuration model, and the lower layer is an operation optimization model; In the upper layer model of the double-layer optimal configuration model, the reactive power compensation device and energy storage configuration information are sent to the lower layer model. The lower layer model performs optimization calculations based on the reactive power compensation device and energy storage configuration information to obtain an optimization result, and feeds back the optimization result to the upper layer model, so that the upper layer model calculates the objective function value of the upper layer model based on the optimization result; The double-layer optimal configuration model includes: a first objective function F1 representing the minimization of the system total cost, and the first objective function F1 includes reactive power compensation device investment cost parameters, energy storage investment cost parameters, and system operation cost parameters; a second objective function F2 for ensuring the grid strength of the new energy cluster system, and the second objective function F2 includes reactive power compensation device investment cost parameters, the number of photovoltaic power stations and wind farm stations, and the curtailment penalty term parameters of photovoltaic power stations and wind farm stations based on the system short-circuit ratio index constraint model; a third objective function F3 based on the curtailment rate index constraint for improving the new energy consumption capacity, and the third objective function F3 includes energy storage investment cost parameters, the number of photovoltaic power stations and wind farm stations, and the curtailment penalty term parameters of photovoltaic power stations and wind farm stations based on the new energy curtailment rate index constraint model.

16. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 14.

17. A computer-readable storage medium, on which a computer program is stored, wherein, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 14 are implemented.

18. A computer program product, comprising a computer program / instructions, wherein, When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 14 are implemented.

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