Method and system for obtaining new energy output extreme value of regional power grid based on constraint optimization

Abstract

The application discloses a kind of based on constraint optimization regional power grid new energy output extreme value seeking method and system.Therein, the method includes: collecting the basic information of power system, based on the information obtained analysis power system flow rationality;With the output of each new energy unit in the near area as decision variable, and list the corresponding objective function;Determine the target constraint condition that near area new energy output adjustment should satisfy;According to objective function and target constraint condition, by adjusting the output level of each new energy unit in the near area, the maximum value of the sum of the output of new energy unit in the near area and the corresponding new energy output distribution are solved.The application can be applied to the situation that there are a large number of new energy access in the near area of the sending end of DC power transmission project, and the new energy output level and the DC project operating power are constrained by the near area new energy transient overvoltage, the new energy output in the near area of the DC sending end can be adjusted, and the maximum benefit goal can be achieved under the premise of ensuring the safe and stable operation of power grid.

Description

Technical Field

[0001] This invention relates to the field of large-scale power grid planning and operation technology, and more specifically, to a method and system for obtaining the extreme values ​​of renewable energy output in a regional power grid based on constraint optimization, as well as a storage medium and electronic device. Background Technology

[0002] The multiple renewable energy station short circuit ratio (MRSCR) is a short circuit ratio indicator that takes into account the mutual influence between multiple renewable energy stations. This indicator considers the amplitude and phase difference of various electrical quantities between different nodes, and can also take into account the reactive power impact of renewable energy power generation equipment. It is applicable to voltage intensity assessment calculations for multiple renewable energy station access systems under various scenarios.

[0003] The short-circuit ratio of multiple renewable energy power plants reflects the voltage intensity of the system connected to multiple renewable energy power plants and the grid's reactive voltage support capacity for the grid-side connection point / power plant connection point of the renewable energy power generation equipment. In engineering, the receiving impedance ratio... And|U i |=|U j The assumption is that | = 1, and the calculation is performed based on this premise. Observe equation (1.1) MRSCR i In terms of its expression, qualitatively speaking, the output P of unit i is... i The smaller the value, the lower the MRSCR. i The larger the output P of other new energy units in the region, the greater the output P. j According to the conversion factor λ ij Size affects MRSCR to varying degrees. i The size of the MRSCR will increase as the output of regional new energy units decreases. This corresponds to a greater voltage strength at which multiple new energy power stations are connected to the system, and a greater reactive voltage support capacity of the power grid for the grid-side connection point bus of new energy power generation equipment.

[0004] In engineering, the MRSCR (Mean Short-Circuit Ratio) index has a certain indicative capability for the transient overvoltage level of new energy sources at the sending end of DC transmission projects. Existing technologies have proposed the concept of critical short-circuit ratio for new energy power plants and the criterion of a critical short-circuit ratio index of 1.5. The Australian power grid requires that any generating equipment must be able to operate stably under system conditions where the short-circuit ratio at the connection point is 1.5, and Huawei has conducted tests to verify this. The 2020 mandatory national standard "Guidelines for the Safety and Stability of Power Systems" proposed a definition of the short-circuit ratio for multiple new energy power plants. Combining existing relevant standards at home and abroad and the actual performance that new energy sources can achieve under various operating conditions and disturbances, the short-circuit ratio of multiple power plants on the low-voltage side of the step-up transformer of the new energy power generation unit should not be less than 1.5, which is the minimum requirement for stable operation of the equipment. The short-circuit ratio of multiple power plants at the grid connection point of new energy is a guiding indicator that comprehensively reflects the stable operation level of new energy and system strength, and is an important indicator for evaluating the safety and stability of the system. In this method, 1.5 is used as the critical value index of MRSCR on the low-voltage side of the step-up transformer of the new energy power generation unit, i.e., the new energy generator terminal.

[0005] Constrained optimization is a mathematical method that seeks a set of parameter values ​​under a series of constraints to optimize the objective value of a function or a set of functions. It is an important branch of optimization problems that was studied early, developed rapidly, widely applied, and has mature methods. It is widely used in military operations, economic analysis, business management, and engineering technology. Constrained optimization methods can be used to achieve coordinated control of power output in flexible DC power projects and power plants in the vicinity.

[0006] However, due to the presence of a large number of renewable energy sources in the vicinity of the AC sending end of the DC transmission project, and the fact that the output level of renewable energy sources and the operating power of the DC project are constrained by the transient overvoltage of renewable energy sources in the vicinity, it is impossible to accurately give the maximum value of the total output of renewable energy sources in the regional power grid constrained by the transient overvoltage of renewable energy sources.

[0007] There is currently no effective solution to the technical problem that the existing technology cannot accurately give the maximum value of the total output of new energy sources in a regional power grid constrained by the transient overvoltage of new energy sources. Summary of the Invention

[0008] To address the technical problem in existing technologies that cannot accurately determine the maximum value of the total renewable energy output in a regional power grid constrained by renewable energy transient overvoltages, this invention provides a method and system for obtaining the extreme value of renewable energy output in a regional power grid based on constraint optimization, as well as a storage medium and electronic device.

[0009] According to one aspect of the present invention, a method for determining the extreme values ​​of renewable energy output in a regional power grid based on constraint optimization is provided, comprising:

[0010] Collect basic information about the power system and perform power flow rationality analysis based on the collected basic information;

[0011] Set the output of each new energy unit in the near area as the decision variable, and list the objective function corresponding to the output of each new energy unit in the near area;

[0012] Determine the target constraints that should be met for adjusting the output of nearby renewable energy sources;

[0013] Based on the objective function and objective constraints, solve for the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution.

[0014] Optionally, the basic information includes: the active power value P of each renewable energy node in the vicinity. i Power output limit P based on regional weather factors ilim_up Lower limit P ilim_low Short-circuit capacity S aci And power system topology, power conversion ratio and impedance matrix

[0015] Optionally, power flow rationality analysis is performed on the power system based on the collected basic information, including:

[0016] Based on the collected basic information, check the node voltage, line power, and transformer grid connection power to ensure power flow convergence and rationality.

[0017] If the power flow does not converge or is unreasonable, the power system parameters should be readjusted.

[0018] Optionally, the output of each new energy unit in the nearby area is P i Then the objective function corresponding to the power output of each new energy unit in the nearby area is:

[0019] Optionally, the target constraints that the adjustment of near-area renewable energy output should meet are determined, including:

[0020] The first constraint condition is that the short-circuit ratio of all new energy power stations near the new energy generator terminal is greater than or equal to 1.5.

[0021] Determine the power output P of each new energy unit in the vicinity based on regional weather factors. i upper limit of output P ilim_up Lower limit of output P ilim_low This is the second constraint condition;

[0022] Based on the first and second constraints, determine the target constraints that the adjustment of near-area renewable energy output should meet.

[0023] Optionally, based on the objective function and objective constraints, the extreme values ​​of the total output of nearby renewable energy units and the corresponding renewable energy output distribution are solved, including:

[0024] Based on the objective function and objective constraints, the constrained optimization expression for the output of nearby renewable energy sources is determined as follows:

[0025]

[0026] In the formula, P i MRSCR provides power to various new energy units in the nearby area. i Let P be the short-circuit ratio of the i-th near-field new energy generator terminal for multiple new energy power stations. ilim_up Powering various new energy units in the nearby area i The upper limit of P ilim_low Powering various new energy units in the nearby area i The lower limit;

[0027] Based on the constrained optimization expression of the near-area renewable energy output, the short-circuit ratio of renewable energy multi-stations for each renewable energy unit is calculated.

[0028] Based on the calculated short-circuit ratio of new energy power plants, determine whether the short-circuit ratio of each new energy unit is greater than or equal to 1.5.

[0029] Based on the assessment results, the output of each new energy unit will be adjusted according to the corresponding adjustment rules.

[0030] Based on the adjusted results, the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution are determined.

[0031] Optionally, based on the judgment result, the output of each new energy unit is adjusted according to the corresponding adjustment rules, including: when the judgment result is that the short-circuit ratio of new energy multi-site at the generator end of the new energy unit is greater than or equal to 1.5, the new energy units are sorted according to the short-circuit ratio of new energy multi-site.

[0032] Starting from the N new energy units with the largest short-circuit ratios at multiple new energy power stations, in P... ilim_low ≤P i ≤P ilim_up The output is gradually increased within the range, and the ΔP is adjusted and increased for each unit each time.

[0033] If a certain new energy unit's j reaches its upper limit P jlim_up Or, the output level after increasing ΔP is greater than P. jlim_up Then P j =P jlim_up When adjusting the output ranking later, new energy unit j is excluded;

[0034] The output was adjusted multiple times, and the short-circuit ratio of new energy units at each new energy power station was recalculated after each adjustment until the short-circuit ratio of new energy units at each power station was reduced to the first critical range of 1.52 ≥ MRSCR. m ≥1.5;

[0035] If, under initial operating conditions, the new energy generating unit m with the smallest short-circuit ratio at multiple power stations satisfies 1.52 ≥ MRSCR m If the value is ≥1.5, it is directly considered as a set of maxima.

[0036] Optionally, based on the judgment result, the output of each new energy unit is adjusted according to the corresponding adjustment rules, including:

[0037] When the result of the judgment is that the short-circuit ratio of multiple new energy power stations with new energy units in the vicinity is less than 1.5, the new energy units are sorted according to the short-circuit ratio of multiple new energy power stations.

[0038] Starting with the N new energy units with the smallest short-circuit ratios at multiple new energy power stations, in P... ilim_low ≤P i ≤P ilim_up The output is gradually reduced within the range, and each time the output is reduced by ΔP for each unit.

[0039] If a certain new energy unit j reaches the lower limit P jlim_low Or, after reducing ΔP, the output level is less than P. jlim_low Then P j =P jlim_low When adjusting the output ranking later, new energy unit j is excluded;

[0040] The power output was adjusted multiple times, and the short-circuit ratio of each renewable energy unit was recalculated after each adjustment until the short-circuit ratio of the renewable energy unit m with the smallest short-circuit ratio of its renewable energy units first increased to the first critical range of 1.52 ≥ MRSCR. m ≥1.5.

[0041] Optionally, based on the adjusted results, the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution are calculated, including:

[0042] Based on the adjusted results, a set of solutions to the objective function corresponding to the output of each new energy unit in the near area is obtained, thereby obtaining the maximum value of the total output of the new energy units in the near area and the corresponding distribution of new energy output.

[0043] According to another aspect of the present invention, a system for determining the extreme values ​​of renewable energy output in a regional power grid based on constraint optimization is provided, comprising:

[0044] The information acquisition module is used to collect basic information about the power system and perform power flow rationality analysis based on the collected basic information.

[0045] The objective function determination module is used to set the output of each new energy unit in the near area as a decision variable and list the objective functions corresponding to the output of each new energy unit in the near area.

[0046] The constraint determination module is used to determine the target constraints that the adjustment of the output of nearby renewable energy sources should meet;

[0047] The extreme value solution module is used to determine the maximum value of the total output of the near-field renewable energy units and the corresponding renewable energy output distribution by adjusting the output of each renewable energy unit in the near-field area according to the objective function and objective constraints.

[0048] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0049] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0050] Therefore, the method and system for determining the extreme values ​​of renewable energy output in regional power grids based on constraint optimization proposed in this invention first collects basic information about the power system and performs a power flow rationality analysis based on the collected information. Then, it sets the output of each renewable energy unit in the near-area as a decision variable and lists the objective function corresponding to the output of each renewable energy unit in the near-area. Next, it determines the target constraints that the adjustment of renewable energy output in the near-area should satisfy. Finally, based on the objective function and the target constraints, it solves for the maximum value of the total output of renewable energy units in the near-area and the corresponding renewable energy output distribution. Thus, this invention can be applied to situations where a large number of renewable energy sources are connected to the AC sending end of a DC transmission project, and the renewable energy output level and the DC project's operating power are constrained by transient overvoltages of the renewable energy sources in the near-area. Using constraints such as the near-area renewable energy generator terminal MRSCR being greater than 1.5 and the upper and lower limits of output considering regional weather factors, the invention adjusts the output of renewable energy in the near-area, thereby obtaining the maximum value of renewable energy output and the corresponding renewable energy output distribution within the regional power grid. This achieves the goal of maximizing benefits while ensuring the safe and stable operation of the power grid. Attached Figure Description

[0051] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0052] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present invention for a method of obtaining the extreme value of new energy output in a regional power grid based on constraint optimization.

[0053] Figure 2 This is a schematic diagram of the overall process for obtaining the extreme value of new energy output in a regional power grid based on constraint optimization, provided by an exemplary embodiment of the present invention.

[0054] Figure 3 This is a schematic diagram of a constrained optimization-based regional power grid renewable energy output extremum determination system provided by an exemplary embodiment of the present invention; and

[0055] Figure 4 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. Detailed Implementation

[0056] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0057] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0058] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0059] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0060] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless explicitly defined or given contrary instructions in the context.

[0061] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0062] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0063] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0064] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0065] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0066] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0067] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0068] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0069] Exemplary methods

[0070] Figure 1 This is a flowchart illustrating a method for determining the extreme values ​​of renewable energy output in a regional power grid based on constraint optimization, provided in an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as… Figure 1 As shown, the method 100 for obtaining the extreme values ​​of new energy output in a regional power grid based on constraint optimization includes the following steps:

[0071] Step 101: Collect basic information about the power system and perform a power flow rationality analysis based on the collected basic information.

[0072] Optionally, the basic information includes: the active power value P of each renewable energy node in the vicinity. i Power output limit P based on regional weather factors ilim_up Lower limit of output P ilim_low Short-circuit capacity S aci And power system topology, power conversion ratio and impedance matrix

[0073] Optionally, power flow rationality analysis is performed on the power system based on the collected basic information, including: checking node voltage, line power, and transformer grid connection power based on the collected basic information to ensure power flow convergence and rationality; if the power flow does not converge or is unreasonable, the power system parameters are readjusted.

[0074] In this embodiment of the invention, step 101 includes the following steps:

[0075] Step 101-1: Collect power system information, including collecting the active power value P of each renewable energy node in the vicinity. i Power output limit P based on regional weather factors ilim_up Lower limit of output P ilim_low Short-circuit capacity S aci And power system topology, power conversion ratio Impedance matrix Information such as...

[0076] Step 101-2: Calculate the power flow based on the information in Step 101-1, check node voltages, line power, and transformer grid connection / disconnection power to ensure power flow convergence and rationality. Furthermore, the output of each power station must be lower than the upper limit P that takes into account local weather factors. ilim_up , higher than the lower limit of output P ilim_low P ilim_low ≤P i ≤P ilim_up If the power flow is reasonable, proceed to the next step; if the power flow does not converge or is unreasonable, return to step 101-1 to readjust the power system parameters.

[0077] Step 102: Set the output of each new energy unit in the near area as a decision variable, and list the objective function corresponding to the output of each new energy unit in the near area.

[0078] Optionally, the output of each new energy unit in the nearby area is P i Then the objective function corresponding to the power output of each new energy unit in the nearby area is:

[0079] Step 103: Determine the target constraints that the adjustment of the output of new energy sources in the near-area should meet.

[0080] Optionally, the target constraints that the adjustment of the output of nearby renewable energy should meet are determined, including: determining that the short-circuit ratio of all renewable energy power plants at the generator end in the nearby area is greater than or equal to 1.5 as the first constraint; and determining the output P of each renewable energy unit in the nearby area based on regional weather factors. i upper limit of output P ilim_up Lower limit of output P ilim_low The second constraint condition is defined; based on the first and second constraints condition, the target constraints that the adjustment of the output of new energy sources in the near-area should meet are determined.

[0081] In this embodiment of the invention, step 103 includes the following steps:

[0082] Step 103-1: The constraint condition is that the short-circuit ratio (MRSCR) of all new energy power stations near the new energy generator terminal is greater than or equal to 1.5. i ≥1.5;

[0083] Step 103-2: Determine the upper limit P of the output of each new energy unit in the near area, taking into account the weather factors of the region. ilim_up Lower limit of output P ilim_low P ilim_low ≤P i ≤P ilim_up ;

[0084] Step 103-3: Based on steps 103-1 to 103-2, determine that the power output adjustment of nearby renewable energy sources should always meet the listed operating power constraints.

[0085] Step 104: Based on the objective function and objective constraints, solve for the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution.

[0086] Optionally, based on the objective function and objective constraints, the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution are solved, including: determining the constrained optimization expression for the near-area renewable energy output based on the objective function and objective constraints as follows:

[0087]

[0088] In the formula, P i MRSCR provides power to various new energy units in the nearby area. i Let P be the short-circuit ratio of the i-th near-field new energy generator terminal for multiple new energy power stations. ilim_up Powering various new energy units in the nearby area i The upper limit of Pilim_low Powering various new energy units in the nearby area i The lower limit;

[0089] Based on the constrained optimization expression of the near-field renewable energy output, the short-circuit ratio of renewable energy multi-site for each renewable energy unit is calculated; based on the calculated short-circuit ratio of renewable energy multi-site for each renewable energy unit, it is determined whether the short-circuit ratio of renewable energy multi-site for each renewable energy unit is greater than or equal to 1.5; based on the determination result, the output of each renewable energy unit is adjusted according to the corresponding adjustment rules; based on the adjusted result, the extreme value of the near-field renewable energy output is solved.

[0090] Optionally, based on the judgment result, the output of each new energy unit is adjusted according to the corresponding adjustment rules, including: when the judgment result is that the short-circuit ratio of the new energy multi-site at the generator terminal is greater than or equal to 1.5, the new energy units are sorted according to the short-circuit ratio of the new energy multi-site; starting from the N new energy units with the largest short-circuit ratio of the new energy multi-site, the output of each new energy unit is adjusted according to the corresponding adjustment rules. ilim_low ≤P i ≤P ilim_up The output is increased sequentially within the range, with each unit adjusting and increasing ΔP at a time; if a certain new energy unit j reaches the upper limit P jlim_up Or, the output level after increasing ΔP is greater than P. jlim_up Then P j =P jlim_up When adjusting the output ranking, new energy unit j is excluded; the output adjustment is performed multiple times, and the short-circuit ratio of new energy units at the generator terminal is recalculated after each adjustment, until the short-circuit ratio of new energy units m at the generator terminal with the smallest short-circuit ratio of new energy units at the generator terminal first decreases to the first critical range of 1.52≥MRSCR. m ≥1.5; If, under initial operating conditions, the new energy generating unit m with the smallest short-circuit ratio at multiple power stations satisfies 1.52≥MRSCR m If the value is ≥1.5, it is directly considered as a set of maxima.

[0091] Optionally, based on the judgment result, the output of each new energy unit is adjusted according to the corresponding adjustment rules, including: when the judgment result is that the short-circuit ratio of multiple new energy power stations with new energy units in the near area is less than 1.5, the new energy units are sorted according to the short-circuit ratio of the multiple new energy power stations; starting from the N new energy units with the smallest short-circuit ratio of the multiple new energy power stations, the output of each new energy unit is adjusted according to the corresponding adjustment rules. ilim_low ≤P i ≤P ilim_up The output is gradually reduced within the range, with each unit adjusting the reduction by ΔP each time; if a certain new energy unit j reaches the lower limit P jlim_low Or, after reducing ΔP, the output level is less than P. jlim_low Then P j =P jlim_lowWhen adjusting the output ranking, new energy unit j is excluded; the output adjustment is performed multiple times, and the short-circuit ratio of new energy units at multiple power stations is recalculated after each adjustment until the short-circuit ratio of new energy unit m with the smallest short-circuit ratio at multiple power stations first rises to the first critical range of 1.52≥MRSCR. m ≥1.5.

[0092] Optionally, based on the adjusted results, the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution are solved, including: based on the adjusted results, obtaining a set of solutions to the objective function corresponding to the output of each renewable energy unit in the nearby area, thereby obtaining the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution.

[0093] In an embodiment of the present invention, see Figure 2 As shown, step 104 includes the following steps:

[0094] Step 104-1: Based on the objective function and constraints listed in Steps 102 and 103, the constraint optimization expression can be listed as follows:

[0095]

[0096] In the formula, P i MRSCR provides power to various new energy units in the nearby area. i Let P be the short-circuit ratio of the i-th near-field new energy generator terminal for multiple new energy power stations. ilim_up Powering various new energy units in the nearby area i The upper limit of P ilim_low Powering various new energy units in the nearby area i The lower limit.

[0097] Step 104-2: Calculate the new energy multi-site short-circuit ratio (MRSCR) at the generator terminals of each new energy unit.

[0098] Step 104-3: If the initial power flow conditions fully satisfy MRSCR i ≥1.5, sorted by MRSCR. Starting from the N new energy units with the largest short-circuit ratios at multiple new energy power stations, at P ilim_low ≤P i ≤P ilim_up The output is gradually increased within the range, with each unit adjusting and increasing ΔP each time. If a certain new energy unit j reaches the upper limit P... jlim_up Or, the output level after increasing ΔP is greater than P. jlim_up Then P j =P jlim_upWhen adjusting the output ranking, new energy unit j is excluded; the output adjustment is performed multiple times, and the short-circuit ratio of new energy units at the generator terminal and the new energy multi-site is recalculated after each adjustment, until the short-circuit ratio of new energy unit m with the smallest new energy multi-site short-circuit ratio at the generator terminal first decreases to the first critical range of 1.52≥MRSCR. m ≥1.5; If, under initial operating conditions, the new energy generating unit m with the smallest short-circuit ratio at multiple power stations satisfies 1.52≥MRSCR m If the value is ≥1.5, it is directly considered as a set of maxima.

[0099] Step 104-4: If the initial power flow conditions cannot fully satisfy MRSCR i ≥1.5, sorted according to MRSCR; starting from the N new energy units with the smallest short-circuit ratios at multiple new energy power stations, at P ilim_low ≤P i ≤P ilim_up The output is gradually reduced within the range, with each unit adjusting and reducing ΔP each time. If a certain new energy unit j reaches the lower limit P... jlim_low Or, after reducing ΔP, the output level is less than P. jlim_low Then P j =P jlim_low When adjusting the output ranking, new energy unit j is excluded; the output adjustment is performed multiple times, and the short-circuit ratio of new energy units at multiple power stations is recalculated after each adjustment until the short-circuit ratio of new energy unit m with the smallest short-circuit ratio at multiple power stations first rises to the first critical range of 1.52≥MRSCR. m ≥1.5.

[0100] Step 104-5: Based on steps 104-3 and 104-4, a set of solutions to the constrained optimization problem can be obtained, from which the power output of new energy sources within the regional power grid can be calculated. The maximum value of .

[0101] The values ​​of the number of power stations N adjusted each time and the output ΔP adjusted each time will affect the algorithm performance: the smaller N and ΔP are, the more precise the adjustment, and the longer the algorithm execution time; the smaller N and ΔP are, the more coarse the adjustment, and the shorter the algorithm execution time.

[0102] A preferred embodiment of the present invention:

[0103] The Shaanxi-Wuhan UHVDC transmission line project (referred to as Shaanxi-Wuhan DC) starts at the Shaanxi-North Converter Station in Yulin City, Shaanxi Province, passes through Shaanxi, Shanxi, Henan and Hubei provinces, and terminates at the Wuhan Converter Station. The line is about 1000kV long, with a rated voltage of ±800kV and a rated power of 8000MW.

[0104] The construction of the Shaanbei-Wuhan ±800kV ultra-high-voltage direct current (UHVDC) transmission project will establish a "highway" for "north-to-south power transmission," significantly improving the power transmission capacity of coal-fired power bases and enabling direct power supply from Northwest coal-fired power bases to load centers in central China. This will create favorable conditions for optimized resource allocation on a larger scale. Simultaneously, the completion and operation of the Shaanbei-Wuhan ±800kV UHVDC project will also expand the scope of renewable energy consumption, promote resource development and poverty alleviation in the old revolutionary base areas of northern Shaanxi, and ensure the healthy and sustainable economic development of the region. Renewable energy in northern Shaanxi is mainly connected to four power supply areas: Shuofang, Yuheng, Xiazhou, and Luochuan. Among these, Xiazhou and the Dabaodang area of ​​Yuheng have concentrated renewable energy connections but lack thermal power unit support, making them two areas with more prominent stability issues.

[0105] The power grid data was selected from a typical renewable energy generation scenario on a summer day in 2020. The power grid data was built in the PSASP simulation program to perform preliminary power flow calculations and check the convergence and rationality of the power flow.

[0106] Collect power system information, including the active power value P of each renewable energy node in the vicinity. i Power output limit P based on regional weather factors ilim_up Lower limit of output P ilim_low Short-circuit capacity S aci And power system topology, power conversion ratio Impedance matrix etc.; the objective function can be listed. Based on operational experience in Shaanxi Province, the upper limit of wind turbine output is 50% of the rated output, and the upper limit of photovoltaic output is 80% of the rated output. Therefore, the output constraint P can be determined. ilim_low ≤P i ≤P ilim_up middle:

[0107] When the new energy unit i is photovoltaic:

[0108] P ilim_up =80%·P imax

[0109] P ilim_low =0

[0110] When the new energy unit i is a wind turbine:

[0111] P ilim_up =50%·P imax

[0112] P ilimulow =0

[0113] The calculation and range of the other constraint, the machine-side MRSCR, are as follows:

[0114]

[0115] During the output adjustment, the number of units adjusted each time is N=5, and the output variable ΔP for each adjustment is 1MW.

[0116] The power output of the four renewable energy sources connected to the power supply area near the sending end of the Shaanxi-Wuhan DC transmission project is shown in Table 1:

[0117] Table 1 Initial and Optimized Distribution of Near-City Renewable Energy Output at the Shaanxi-Wuhan DC Transmission Terminal (Unit: 10,000 kW)

[0118]

[0119] When solving the constrained optimization problem based on the above objective function and constraints, and obtaining the force distribution as shown in the table above, Z max =6860MW.

[0120] Since the number of generating units N adjusted each time and the output variable ΔP adjusted each time have a significant impact on the performance of this algorithm, the following table compares the algorithm execution time and the final new energy output Z value corresponding to different values ​​in this scenario, as shown in Table 2:

[0121] Table 2 shows the algorithm execution time and the final Z-value of new energy output for different values ​​in this scenario.

[0122]

[0123] For this scenario, choosing N=5 power stations for each adjustment and ΔP=1MW for each output variable is more efficient and accurate. Since the total number of new energy generating units in this region is 232, it is known that selecting N at approximately 2% of the total number of new energy generating units in the region yields a more efficient and accurate algorithm.

[0124] The algorithm execution time was calculated based on a laptop equipped with an Intel(R) Core(TM) i7-8565U CPU@1.8GHz processor and 16GB of memory during the parameter selection process above.

[0125] Therefore, the method for determining the extreme value of renewable energy output in a regional power grid based on constraint optimization provided by this invention first collects basic information about the power system and performs a power flow rationality analysis based on the collected information. Then, it sets the output of each renewable energy unit in the near-area as a decision variable and lists the objective function corresponding to the output of each renewable energy unit in the near-area. Next, it determines the target constraint conditions that the adjustment of renewable energy output in the near-area should satisfy. Finally, based on the objective function and the target constraint conditions, it solves for the maximum value of the total output of each renewable energy unit in the near-area and the corresponding renewable energy output distribution. Thus, this invention can be applied to situations where a large number of renewable energy sources are connected to the AC sending end of a DC transmission project, and the renewable energy output level and the DC project's operating power are constrained by transient overvoltages of the renewable energy sources in the near-area. Using constraints such as the near-area renewable energy generator terminal MRSCR being greater than 1.5 and the upper and lower limits of output considering regional weather factors, the method adjusts the output of renewable energy in the near-area to obtain the maximum value of renewable energy output in the regional power grid, achieving the goal of maximizing benefits while ensuring the safe and stable operation of the power grid.

[0126] Exemplary System

[0127] Figure 3 This is a schematic diagram of a system for determining the extreme values ​​of renewable energy output in a regional power grid based on constraint optimization, provided in an exemplary embodiment of the present invention. Figure 3 As shown, system 300 includes:

[0128] The information acquisition module 310 is used to collect basic information of the power system and perform power flow rationality analysis on the collected basic information.

[0129] The objective function determination module 320 is used to set the output of each new energy unit in the near area as a decision variable and list the objective functions corresponding to the output of each new energy unit in the near area.

[0130] The constraint determination module 330 is used to determine the target constraint conditions that the adjustment of the output of near-field renewable energy should meet.

[0131] The extreme value solving module 340 is used to solve for the maximum value of the total output of the near-field renewable energy units and the corresponding renewable energy output distribution based on the objective function and objective constraints.

[0132] Optionally, the basic information includes: the active power value P of each renewable energy node in the vicinity. i Power output limit P based on regional weather factors ilim_up Lower limit of output P ilim_low Short-circuit capacity S aci And power system topology, power conversion ratio and impedance matrix

[0133] Optionally, the information collection module 310 is specifically used for:

[0134] Based on the collected basic information, check the node voltage, line power, and transformer grid connection power to ensure power flow convergence and rationality.

[0135] If the power flow does not converge or is unreasonable, the power system parameters should be readjusted.

[0136] Optionally, the output of each new energy unit in the nearby area is P i Then the objective function corresponding to the power output of each new energy unit in the nearby area is:

[0137] Optionally, the constraint determination module 330 is specifically used for:

[0138] The first constraint condition is that the short-circuit ratio of all new energy power stations near the new energy generator terminal is greater than or equal to 1.5.

[0139] Determine the power output P of each new energy unit in the vicinity based on regional weather factors. i upper limit of output P ilim_up Lower limit of output P ilim_low This is the second constraint condition;

[0140] Based on the first and second constraints, determine the target constraints that the adjustment of near-area renewable energy output should meet.

[0141] Optionally, the extremum solving module 340 is specifically used for:

[0142] Based on the objective function and objective constraints, the constrained optimization expression for the output of nearby renewable energy sources is determined as follows:

[0143]

[0144] In the formula, P i MRSCR provides power to various new energy units in the nearby area. i Let P be the short-circuit ratio of the i-th near-field new energy generator terminal for multiple new energy power stations. ilim_up Powering various new energy units in the nearby area i The upper limit of P ilim_low Powering various new energy units in the nearby area i The lower limit;

[0145] Based on the constrained optimization expression of the near-area renewable energy output, the short-circuit ratio of renewable energy multi-stations at the generator terminals of each renewable energy unit is calculated;

[0146] Based on the calculated short-circuit ratio of new energy power plants, determine whether the short-circuit ratio of new energy power plants at the generator terminal of each new energy unit is greater than or equal to 1.5.

[0147] Based on the assessment results, the output of each new energy unit will be adjusted according to the corresponding adjustment rules.

[0148] Based on the adjusted results, the maximum output of each new energy unit in the near-field area is calculated.

[0149] Optionally, the extremum solving module 340 is also specifically used for:

[0150] When the result of the judgment is that the short-circuit ratio of new energy power units at multiple power stations is greater than or equal to 1.5, the new energy power units are sorted according to the short-circuit ratio of new energy power units at multiple power stations.

[0151] Starting from the N new energy units with the largest short-circuit ratios at multiple new energy power stations, in P... ilim_low ≤P i ≤P ilim_up The output is gradually increased within the range, and the ΔP is adjusted and increased for each unit each time.

[0152] If a certain new energy unit's j reaches its upper limit P jlim_up Or, the output level after increasing ΔP is greater than P. jlim_up Then P j =P jlim_up When adjusting the output ranking later, new energy unit j is excluded;

[0153] The power output was adjusted multiple times, and the short-circuit ratio of the renewable energy units at the generator terminal and the renewable energy multi-site short-circuit ratio was recalculated after each adjustment until the short-circuit ratio of the renewable energy unit m with the smallest renewable energy multi-site short-circuit ratio at the generator terminal first decreased to the first critical range of 1.52≥MRSCR. m ≥1.5;

[0154] If, under initial operating conditions, the new energy generating unit m with the smallest short-circuit ratio at multiple power stations satisfies 1.52 ≥ MRSCR m If the value is ≥1.5, it is directly considered as a set of maxima.

[0155] Optionally, the extremum solving module 340 is also specifically used for:

[0156] When the result of the judgment is that the short-circuit ratio of new energy units at multiple new energy power stations is less than 1.5, the new energy units are sorted according to the short-circuit ratio of new energy units at multiple new energy power stations.

[0157] Starting with the N new energy units with the smallest short-circuit ratios at multiple new energy power stations, in P... ilim_low ≤P i ≤P ilim_up The output is gradually reduced within the range, and each time the output is reduced by ΔP for each unit.

[0158] If a certain new energy unit j reaches the lower limit P jlim_low Or, after reducing ΔP, the output level is less than P.jlim_low Then P j =P jlim_low When adjusting the output ranking later, new energy unit j is excluded;

[0159] The power output was adjusted multiple times, and the short-circuit ratio of each renewable energy unit was recalculated after each adjustment until the short-circuit ratio of the renewable energy unit m with the smallest short-circuit ratio of its renewable energy units first increased to the first critical range of 1.52 ≥ MRSCR. m ≥1.5.

[0160] Optionally, the extremum solving module 340 is also specifically used for:

[0161] Based on the adjusted results, a set of solutions to the objective function corresponding to the output of each new energy unit in the near area is obtained, thereby obtaining the maximum output of each new energy unit in the near area and the corresponding distribution of new energy output.

[0162] The constrained optimization-based regional power grid renewable energy output extremum determination system 300 of the present invention corresponds to the constrained optimization-based regional power grid renewable energy output extremum determination method 100 of the present invention, and will not be described again here.

[0163] Exemplary electronic devices

[0164] Figure 4 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. The electronic device may be either or both of a first device and a second device, or a standalone device independent of them, which may communicate with the first device and the second device to receive acquired input signals from them. Figure 4 A block diagram of an electronic device according to an embodiment of the present invention is illustrated. Figure 4 As shown, the electronic device 40 includes one or more processors 41 and a memory 42.

[0165] The processor 41 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0166] The memory 42 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 41 may execute the program instructions to implement the methods for information mining of historical change records and / or other desired functions of the software programs of the various embodiments of the present invention described above. In one example, the electronic device may also include an input system 43 and an output system 44, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0167] In addition, the input system 43 may also include, for example, a keyboard, a mouse, etc.

[0168] The output system 44 can output various types of information to the outside. The output device 44 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0169] Of course, for the sake of simplicity, Figure 4 Only some of the components of the electronic device relevant to the present invention are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0170] Exemplary computer program products and computer-readable storage media

[0171] In addition to the methods and devices described above, embodiments of the present invention may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps of the methods for information mining of historical change records according to various embodiments of the present invention as described in the "Exemplary Methods" section of this specification.

[0172] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of the present invention. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0173] Furthermore, embodiments of the present invention may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the methods for information mining of historical change records according to various embodiments of the present invention as described in the "Exemplary Methods" section above.

[0174] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0175] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0176] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0177] The block diagrams of devices, systems, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0178] The methods and systems of the present invention may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of the present invention are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, the present invention may also be implemented as a program recorded on a recording medium, the program comprising machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers recording media storing programs for performing the methods according to the present invention.

[0179] It should also be noted that in the systems, apparatus, and methods of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0180] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method for determining the extreme values ​​of renewable energy output in a regional power grid based on constrained optimization, characterized in that, include: Collect basic information about the power system and perform power flow rationality analysis based on the collected basic information; Set the output of each new energy unit in the near area as the decision variable, and list the objective function corresponding to the output of each new energy unit in the near area; Determine the target constraints that should be met for adjusting the output of nearby renewable energy sources; Based on the objective function and objective constraints, solve for the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution; The target constraints that should be met for adjusting the output of nearby renewable energy sources include: The first constraint condition is that the short-circuit ratio of all new energy power stations near the new energy generator terminal is greater than or equal to 1.

5. Determine the power output P of each new energy unit in the vicinity based on regional weather factors. i upper limit of output P i lim_up Lower limit of output P i lim_low This is the second constraint condition; Based on the first and second constraints, determine the target constraints that the adjustment of near-area renewable energy output should meet; Based on the objective function and objective constraints, the maximum value of the total output of nearby renewable energy units and the corresponding renewable energy output distribution are determined, including: Based on the objective function and objective constraints, the constrained optimization expression for the output of nearby renewable energy sources is determined as follows: In the formula, P i MRSCR provides power to various new energy units in the nearby area. i Let P be the short-circuit ratio of the i-th near-field new energy generator terminal for multiple new energy power stations. i lim_up Powering various new energy units in the nearby area i The upper limit of P i lim_low Powering various new energy units in the nearby area i The lower limit; Based on the constrained optimization expression of the near-area renewable energy output, the short-circuit ratio of renewable energy multi-stations for each renewable energy unit is calculated. Based on the calculated short-circuit ratio of new energy power plants, determine whether the short-circuit ratio of each new energy unit is greater than or equal to 1.

5. Based on the assessment results, the output of each new energy unit will be adjusted according to the corresponding adjustment rules. Based on the assessment results, the output of each new energy unit will be adjusted according to the corresponding adjustment rules, including: When the result of the judgment is that the short-circuit ratio of new energy power generation units at multiple new energy power stations is greater than or equal to 1.5, the new energy power generation units are sorted according to the short-circuit ratio of new energy power stations. Starting from the N new energy units with the largest short-circuit ratios at multiple new energy power stations, in P... i lim_low ≤P i ≤P i lim_up The output is gradually increased within the range, and the ΔP is adjusted and increased for each unit each time. If a certain new energy unit's j reaches its upper limit P j lim_up Or, the output level after increasing ΔP is greater than P. j lim_up Then P j =P j lim_up When adjusting the output ranking later, new energy unit j is excluded; The output was adjusted multiple times, and the short-circuit ratio of new energy units at each new energy power station was recalculated after each adjustment until the short-circuit ratio of new energy units at each power station was reduced to the first critical range of 1.52 ≥ MRSCR. m ≥1.5; If, under initial operating conditions, the new energy generating unit m with the smallest short-circuit ratio at multiple power stations satisfies 1.52 ≥ MRSCR m If the value is ≥1.5, it is directly considered as a set of maxima; Based on the assessment results, the output of each new energy unit will be adjusted according to the corresponding adjustment rules, including: When the result of the judgment is that the short-circuit ratio of multiple new energy power stations with new energy units in the vicinity is less than 1.5, the new energy units are sorted according to the short-circuit ratio of multiple new energy power stations. Starting with the N new energy units with the smallest short-circuit ratios at multiple new energy power stations, in P... i lim_low ≤P i ≤P i lim_up The output is gradually reduced within the range, and each time the output is reduced by ΔP for each unit. If a certain new energy unit j reaches the lower limit P j lim_low Or, after reducing ΔP, the output level is less than P. j lim_low Then P j =P j lim_low When adjusting the output ranking later, new energy unit j is excluded; The power output was adjusted multiple times, and the short-circuit ratio of each renewable energy unit was recalculated after each adjustment until the short-circuit ratio of the renewable energy unit m with the smallest short-circuit ratio of its renewable energy units first increased to the first critical range of 1.52 ≥ MRSCR. m ≥1.5; Based on the adjusted results, the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution are determined, including: Based on the adjusted results, a set of solutions to the objective function corresponding to the output of each new energy unit in the near area is obtained, thereby obtaining the maximum value of the total output of the new energy units in the near area and the corresponding distribution of new energy output.

2. The method according to claim 1, characterized in that, Basic information includes: active power values ​​P of each renewable energy node in the vicinity. i Power output limit P based on regional weather factors i lim_up Lower limit of output P i lim_low Short-circuit capacity S aci And power system topology, power conversion ratio and impedance matrix 3. The method according to claim 1, characterized in that, Based on the collected basic information, a power flow rationality analysis is performed on the power system, including: Based on the collected basic information, check the node voltage, line power, and transformer grid connection power to ensure power flow convergence and rationality. If the power flow does not converge or is unreasonable, the power system parameters should be readjusted.

4. The method according to claim 1, characterized in that, The output of each new energy unit in the nearby area is P i Then the objective function corresponding to the power output of the nearby renewable energy units is:

5. A system for determining the extreme values ​​of renewable energy output in a regional power grid based on constraint optimization using the method described in claim 1, characterized in that, include: The information acquisition module is used to collect basic information about the power system and perform power flow rationality analysis based on the collected basic information. The objective function determination module is used to set the output of each new energy unit in the near area as a decision variable and list the objective functions corresponding to the output of each new energy unit in the near area. The constraint determination module is used to determine the target constraints that the adjustment of the output of nearby renewable energy sources should meet; The extreme value solution module is used to solve for the maximum value of the total output of the nearby renewable energy units and the corresponding renewable energy output distribution based on the objective function and objective constraints.

6. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-4.

7. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-4.

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