A method and device for smoothing wind power fluctuations in a wind farm

Abstract

The present invention relates to a method and apparatus for smoothing wind power fluctuations in a wind farm. The method comprises: determining a power adjustment target for a data center within a control period based on the wind farm's original predicted wind power output within the control period; and adjusting the data center's planned power consumption within the control period based on the power adjustment target. The technical solution provided by the present invention addresses the shortcomings of conventional energy sources in smoothing wind power fluctuations, providing a theoretical basis for effectively utilizing demand-side resources to smooth wind power fluctuations and achieving safe and stable wind power grid integration.

Description

Technical Field

[0001] The present invention relates to the technical field of power dispatching and control, and in particular to a method and device for smoothing wind power fluctuations in a wind farm. Background Art

[0002] my country's wind power industry has developed rapidly in recent years. However, the intermittent, volatile, and random nature of wind power has significantly increased the demand for and difficulty of peak-shaving in the system. Large fluctuations in wind power over short periods of time pose a potential threat to grid security and stability. Well-designed demand response can effectively balance wind power fluctuations, providing more peak-shaving and backup services for renewable energy integration. Advanced control strategies using battery energy storage to mitigate short-term wind power fluctuations, as well as technologies that combine load distribution of air conditioning chillers with fluctuating wind turbine output, have been developed to mitigate wind power fluctuations.

[0003] Data centers, with their ability to respond, transfer, and adjust power in real time, represent a vast new type of demand response entity. Data center demand response is essentially the migration of network load over time or the shifting of load over space. The resulting changes in equipment operating status are the direct cause of data center power consumption fluctuations. Technologies already exist for load balancing across geographically dispersed data centers to reduce electricity costs.

[0004] Current research on data centers has the following deficiencies: on the one hand, while effective ways to smooth wind power fluctuations are currently being explored through various demand-side resources such as energy storage, air conditioning, and electric vehicles, there is insufficient understanding of data center load as a resource; on the other hand, applications of the adjustable power properties of data centers focus on their transferability in the spatial dimension, failing to fully utilize the regulation potential within the data center. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a method and device for smoothing wind power fluctuations in a wind farm, which adjusts the power consumption of the data center within the control period according to the power adjustment target of the data center within the control period, thereby making up for the shortcomings of conventional energy in smoothing wind power fluctuations, and providing a theoretical basis for effectively utilizing demand-side resources to smooth wind power fluctuations and achieve safe and stable wind power grid connection.

[0006] The purpose of the present invention is achieved by adopting the following technical solutions:

[0007] A method for smoothing wind power fluctuations in a wind farm, wherein the improvement is that the method comprises:

[0008] Determine the power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period;

[0009] The planned power consumption of the data center within the control period is adjusted according to the power consumption target of the data center within the control period.

[0010] Preferably, determining the power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period includes:

[0011] The power adjustment target of the data center in the i-th period during the control cycle is determined by the following formula:

[0012]

[0013] In the above formula, i∈[1,N], N is the total number of time periods in the control cycle; is the power consumption of the data center in the i-th period within the control cycle, is the target value of the average power of the wind farm in the i-th period within the control cycle, is the original wind power forecast output of the wind farm in the i-th period within the control period.

[0014] Furthermore, the target value of the average power of the wind farm in the i-th period within the control cycle is determined as follows:

[0015]

[0016] In the above formula, is the target value of the average power of the wind farm in the i-1 period within the control period, is the original wind power forecast output of the wind farm in the i-1 period within the control period, P N is the installed capacity of wind turbines in the wind farm, where, when i=1, is the average power of the wind farm in the period before the first period in the control period.

[0017] Preferably, adjusting the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period includes:

[0018] Substituting the power adjustment target of the data center within the control period into a pre-established wind speed suppression optimization model;

[0019] Solving the pre-established wind power level suppression optimization model to obtain an optimal solution for the power migration matrix of the data center within the control period;

[0020] Determining an adjustment amount of electric power consumption of the data center within the control period by using an optimal solution of a power migration matrix of the data center within the control period;

[0021] The planned power consumption of the data center within the control period is adjusted by utilizing the power consumption adjustment amount of the data center within the control period.

[0022] Furthermore, the objective function of the pre-established wind level suppression optimization model is determined as follows:

[0023]

[0024] In the above formula, f is the target value of the wind speed suppression optimization model, i∈[1,N], j∈[1,N], i≤j, and N is the total number of time periods in the control cycle; s ij The ratio of the power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total power generated by the delayed network load that needs to be processed in the i-th period. The electric power generated by the delay load during the i-th period of the control cycle is processed. In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. is the central power of the data in the jth period within the control cycle, is the power adjustment target of the data center in the jth period within the control cycle, E is the power utilization rate, T is the optimization deadline within the control cycle, T start T is the starting time of the time window that needs to smooth fluctuations within the control period. end T is the end time of the time window that needs to smooth fluctuations within the control period. ahead T is the advance notice duration within the control period. ahead =T start -T0, T0 is the moment when the grid side sends the wind power output leveling signal within the control period.

[0025] Specifically, the constraint conditions of the wind speed suppression optimization model are determined as follows:

[0026]

[0027] In the above formula, The equivalent output of the wind farm in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle is: The equivalent output of the wind farm in the j-1 period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, P N is the installed capacity of wind turbines in the wind farm, In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period for processing the non-delayable load is obtained. The power generated by the data center processing the network load in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, The power value generated by processing network load when the data center is running at full load, i+d m -1≤T, n is the total number of categories of delayed loads classified according to processing time limits, d m is the processing time limit corresponding to the mth type of deferrable load classified by processing time limit, The ratio of the electric power generated by the data center in the i-th period during the control period when processing the m-th type of deferrable load classified by processing time limit to the total electric power generated by all types of deferrable load classified by processing time limit in the i-th period;

[0028] Among them, the adjusted equivalent output of the wind farm is determined by the following formula:

[0029]

[0030] In the above formula, is the original wind power forecast output of the wind farm in the jth period within the control period, After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the central power of the data in the jth period in the control period is obtained. is the center power of the data in the jth period within the control period.

[0031] Furthermore, solving the pre-established wind speed suppression optimization model to obtain an optimal solution of the power migration matrix of the data center within the control period includes:

[0032] Solving the pre-established wind speed suppression model using the active set method to obtain an optimal solution for the power migration matrix of the data center within the control period;

[0033] The optimal solution S of the power migration matrix of the data center during the control period is determined by the following formula:

[0034]

[0035] In the above formula, i∈[1,N], j∈[1,N], i≤j, N is the total number of time periods in the control cycle; s ijThe ratio of the electric power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total electric power generated by the delayable network load that needs to be processed in the i-th period.

[0036] Furthermore, the determining of the power adjustment amount of the data center within the control period by using the optimal solution of the power migration matrix of the data center within the control period includes:

[0037] The power adjustment amount ΔP(j) of the data center during the j-th period of the control cycle is determined by the following formula:

[0038]

[0039] In the above formula, The electric power generated by the delay load during the i-th period of the control cycle is processed. is the electric power generated by the delayable load during the j-th period of the control cycle, and E is the electric energy utilization rate.

[0040] Specifically, the adjusting the planned power consumption of the data center within the control period by using the power consumption adjustment amount of the data center within the control period includes:

[0041] The planned power consumption of the data center in the jth period of the control cycle is adjusted according to the following formula:

[0042] P′(j)=P(j)+ΔP(j)

[0043] In the above formula, P′(j) is the planned power consumption of the data center in the j-th period within the control cycle after adjustment, and P(j) is the original planned power consumption of the data center in the j-th period within the control cycle.

[0044] A device for smoothing wind power fluctuations in a wind farm, wherein the device comprises:

[0045] a determination unit, configured to determine an electric power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period;

[0046] The regulating unit is used to regulate the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period.

[0047] Compared with the closest prior art, the present invention has the following beneficial effects:

[0048] The technical solution provided by the present invention determines the power consumption adjustment target of the data center within the control period based on the original wind power forecast output of the wind farm within the control period, and adjusts the power consumption of the data center within the control period according to the power consumption adjustment target of the data center within the control period, thereby making up for the shortcomings of conventional energy in smoothing wind power fluctuations, and providing a theoretical basis for effectively utilizing demand-side resources to smooth wind power fluctuations and achieve safe and stable wind power grid connection. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of a method for smoothing wind power fluctuations in a wind farm according to an embodiment of the present invention;

[0050] Figure 2 is a comparison diagram of the initial state wind turbine output power curve, the target value curve of the wind farm average power, and the adjusted wind power equivalent output curve in an embodiment of the present invention;

[0051] Figure 3 It is a structural schematic diagram of a wind power fluctuation smoothing device in a wind farm according to an embodiment of the present invention. DETAILED DESCRIPTION

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

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0054] The present invention provides a method for smoothing wind power fluctuations in a wind farm, such as Figure 1 As shown, the method includes:

[0055] 101. Determine the power adjustment target of the data center within the control period based on the original wind power forecast output of the wind farm within the control period;

[0056] 102. Adjust the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period.

[0057] Furthermore, the step 101 includes:

[0058] The power adjustment target of the data center in the i-th period during the control cycle is determined by the following formula:

[0059]

[0060] In the above formula, i∈[1,N], N is the total number of time periods in the control cycle; is the power consumption of the data center in the i-th period within the control cycle, is the target value of the average power of the wind farm in the i-th period within the control cycle, is the original wind power forecast output of the wind farm in the i-th period within the control period.

[0061] Specifically, the target value of the average power of the wind farm in the i-th period within the control cycle is determined as follows:

[0062]

[0063] In the above formula, is the target value of the average power of the wind farm in the i-1 period within the control period, is the original wind power forecast output of the wind farm in the i-1 period within the control period, P N is the installed capacity of wind turbines in the wind farm, where, when i=1, is the average power of the wind farm in the period before the first period in the control period.

[0064] Furthermore, the step 102 includes:

[0065] Substituting the power adjustment target of the data center within the control period into a pre-established wind speed suppression optimization model;

[0066] Solving the pre-established wind power level suppression optimization model to obtain an optimal solution for the power migration matrix of the data center within the control period;

[0067] Determining an adjustment amount of electric power consumption of the data center within the control period by using an optimal solution of a power migration matrix of the data center within the control period;

[0068] The planned power consumption of the data center within the control period is adjusted by utilizing the power consumption adjustment amount of the data center within the control period.

[0069] Specifically, the objective function of the pre-established wind level suppression optimization model is determined as follows:

[0070]

[0071] In the above formula, f is the target value of the wind speed suppression optimization model, i∈[1,N], j∈[1,N], i≤j, and N is the total number of time periods in the control cycle; s ij The ratio of the power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total power generated by the delayed network load that needs to be processed in the i-th period. The electric power generated by the delay load during the i-th period of the control cycle is processed. In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. is the central power of the data in the jth period within the control cycle, is the power adjustment target of the data center in the jth period within the control cycle, E is the power utilization rate, T is the optimization deadline within the control cycle, T start T is the starting time of the time window that needs to smooth fluctuations within the control period. end T is the end time of the time window that needs to smooth fluctuations within the control period. ahead T is the advance notice duration within the control period. ahead =T start -T0, T0 is the moment when the grid side sends the wind power output leveling signal within the control period.

[0072] For example, taking the 5-minute period from 8:55 to 9:00 on a certain day as an example, 8:55 to 8:56 is recorded as the first period, 8:56 to 8:57 is recorded as the second period, and so on. Assume that the power generated by the data center processing the delayed network load in the first period is 100kW. If part of the network load processing tasks are migrated to the third period, the power generated by the data center processing the delayed network load in the first period will drop to 80kW. Correspondingly, the power generated by the data center processing the delayed network load in the third period will increase by 20kW. It can be considered that the power generated by the data center processing the network load delayed from the first period to the third period is 20kW. At this time

[0073] The constraint conditions of the wind speed suppression optimization model are determined as follows:

[0074]

[0075] In the above formula, The equivalent output of the wind farm in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle is: The equivalent output of the wind farm in the j-1 period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, P N is the installed capacity of wind turbines in the wind farm, In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period for processing the non-delayable load is obtained. The power generated by the data center processing the network load in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, The power value generated by processing network load when the data center is running at full load, i+d m -1≤T, n is the total number of categories of delayed loads classified according to processing time limits, d m is the processing time limit corresponding to the mth type of deferrable load classified by processing time limit, The ratio of the electric power generated by the data center in the i-th period during the control period when processing the m-th type of deferrable load classified by processing time limit to the total electric power generated by all types of deferrable load classified by processing time limit in the i-th period;

[0076] Among them, the adjusted equivalent output of the wind farm is determined by the following formula:

[0077]

[0078] In the above formula, is the original wind power forecast output of the wind farm in the jth period within the control period, After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the central power of the data in the jth period in the control period is obtained. is the center power of the data in the jth period within the control period.

[0079] Specifically, solving the pre-established wind speed suppression optimization model to obtain the optimal solution of the power migration matrix of the data center within the control period includes:

[0080] Solving the pre-established wind speed suppression model using the active set method to obtain an optimal solution for the power migration matrix of the data center within the control period;

[0081] The optimal solution S of the power migration matrix of the data center during the control period is determined by the following formula:

[0082]

[0083] In the above formula, i∈[1,N], j∈[1,N], i≤j, N is the total number of time periods in the control cycle; s ij The ratio of the electric power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total electric power generated by the delayable network load that needs to be processed in the i-th period.

[0084] Specifically, determining the power adjustment amount of the data center within the control period by using the optimal solution of the power migration matrix of the data center within the control period includes:

[0085] The power adjustment amount ΔP(j) of the data center during the j-th period of the control cycle is determined by the following formula:

[0086]

[0087] In the above formula, The electric power generated by the delay load during the i-th period of the control cycle is processed. is the electric power generated by the delayable load during the j-th period of the control cycle, and E is the electric energy utilization rate.

[0088] Specifically, the adjusting the planned power consumption of the data center within the control period by using the power consumption adjustment amount of the data center within the control period includes:

[0089] The planned power consumption of the data center in the jth period of the control cycle is adjusted according to the following formula:

[0090] P′(j)=P(j)+ΔP(j)

[0091] In the above formula, P′(j) is the planned power consumption of the data center in the j-th period within the control cycle after adjustment, and P(j) is the original planned power consumption of the data center in the j-th period within the control cycle.

[0092] For example, Figure 2 The figure shows a comparison of the initial state wind turbine output power curve, the target value curve of the wind farm average power and the adjusted wind power equivalent output curve after the technical solution provided by the present invention is used to smooth the wind power fluctuation of the wind farm.

[0093] The present invention also provides a wind power fluctuation smoothing device for a wind farm, such as Figure 3 As shown, the device includes:

[0094] a determination unit, configured to determine an electric power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period;

[0095] The regulating unit is used to regulate the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period.

[0096] Furthermore, the determining unit includes:

[0097] The first determination module is used to determine the power adjustment target of the data center in the i-th period within the control cycle according to the following formula

[0098]

[0099] In the above formula, i∈[1,N], N is the total number of time periods in the control cycle; is the power consumption of the data center in the i-th period within the control cycle, is the target value of the average power of the wind farm in the i-th period within the control cycle, is the original wind power forecast output of the wind farm in the i-th period within the control period.

[0100] The second determination module is used to determine the target value of the average power of the wind farm in the i-th period within the control cycle according to the following formula

[0101]

[0102] In the above formula, is the target value of the average power of the wind farm in the i-1 period within the control period, is the original wind power forecast output of the wind farm in the i-1 period within the control period, P N is the installed capacity of wind turbines in the wind farm, where, when i=1, is the average power of the wind farm in the period before the first period in the control period.

[0103] Furthermore, the adjustment unit includes:

[0104] A substitution module, configured to substitute the power adjustment target of the data center within the control period into a pre-established wind power level suppression optimization model;

[0105] An acquisition module, configured to solve the pre-established wind speed suppression optimization model and obtain an optimal solution of the power migration matrix of the data center within a control period;

[0106] A third determining module is configured to determine an adjustment amount of electric power consumption of the data center within the control period by using an optimal solution of the power migration matrix of the data center within the control period;

[0107] The regulating module is configured to regulate the planned power consumption of the data center within the control period by using the power consumption adjustment amount of the data center within the control period.

[0108] Furthermore, the substitution module includes:

[0109] The first determination submodule is used to determine the objective function of the pre-established wind speed suppression optimization model according to the following formula:

[0110]

[0111] In the above formula, f is the target value of the wind speed suppression optimization model, i∈[1,N], j∈[1,N], i≤j, and N is the total number of time periods in the control cycle; s ij The ratio of the power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total power generated by the delayed network load that needs to be processed in the i-th period. The electric power generated by the delay load during the i-th period of the control cycle is processed. In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. is the central power of the data in the jth period within the control cycle, is the power adjustment target of the data center in the jth period within the control cycle, E is the power utilization rate, T is the optimization deadline within the control cycle, T start T is the starting time of the time window that needs to smooth fluctuations within the control period. end T is the end time of the time window that needs to smooth fluctuations within the control period. ahead T is the advance notice duration within the control period. ahead =T start -T0, T0 is the moment when the grid side sends the wind power output leveling signal within the control period.

[0112] The second determination submodule is used to determine the constraint conditions of the wind speed suppression optimization model according to the following formula:

[0113]

[0114] In the above formula, The equivalent output of the wind farm in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle is: The equivalent output of the wind farm in the j-1 period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, P N is the installed capacity of wind turbines in the wind farm, In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period for processing the non-delayable load is obtained. The power generated by the data center processing the network load in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, The power value generated by processing network load when the data center is running at full load, i+d m -1≤T, n is the total number of categories of delayed loads classified according to processing time limits, d m is the processing time limit corresponding to the mth type of deferrable load classified by processing time limit, The ratio of the electric power generated by the data center in the i-th period during the control period when processing the m-th type of deferrable load classified by processing time limit to the total electric power generated by all types of deferrable load classified by processing time limit in the i-th period;

[0115] The third determination submodule is used to determine the adjusted equivalent output of the wind farm according to the following formula:

[0116]

[0117] In the above formula, is the original wind power forecast output of the wind farm in the jth period within the control period, After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the central power of the data in the jth period in the control period is obtained. is the center power of the data in the jth period within the control cycle. Specifically, the acquisition module is used to:

[0118] Solving the pre-established wind speed suppression model using the active set method to obtain an optimal solution for the power migration matrix of the data center within the control period;

[0119] The optimal solution S of the power migration matrix of the data center during the control period is determined by the following formula:

[0120]

[0121] In the above formula, i∈[1,N], j∈[1,N], i≤j, N is the total number of time periods in the control cycle; s ij The ratio of the electric power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total electric power generated by the delayable network load that needs to be processed in the i-th period.

[0122] Specifically, the third determining module is used to:

[0123] The power adjustment amount ΔP(j) of the data center during the j-th period of the control cycle is determined by the following formula:

[0124]

[0125] In the above formula, The electric power generated by the delay load during the i-th period of the control cycle is processed. is the electric power generated by the delayable load during the j-th period of the control cycle, and E is the electric energy utilization rate.

[0126] Specifically, the adjustment module is used to:

[0127] The planned power consumption of the data center in the jth period of the control cycle is adjusted according to the following formula:

[0128] P′(j)=P(j)+ΔP(j)

[0129] In the above formula, P′(j) is the planned power consumption of the data center in the j-th period within the control cycle after adjustment, and P(j) is the original planned power consumption of the data center in the j-th period within the control cycle.

[0130] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0131] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] 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 work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for smoothing wind power fluctuations in a wind farm, characterized in that: The method comprises: Determine the power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period; Adjusting the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period; The step of adjusting the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period includes: Substituting the power adjustment target of the data center within the control period into a pre-established wind speed suppression optimization model; Solving the pre-established wind power level suppression optimization model to obtain an optimal solution for the power migration matrix of the data center within the control period; Determining an adjustment amount of electric power consumption of the data center within the control period by using an optimal solution of a power migration matrix of the data center within the control period; The planned power consumption of the data center within the control period is adjusted by utilizing the power consumption adjustment amount of the data center within the control period.

2. The method according to claim 1, wherein The step of determining the power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period includes: The power adjustment target of the data center in the i-th period during the control cycle is determined by the following formula: In the above formula, i∈[1,N], N is the total number of time periods in the control cycle; is the power consumption of the data center in the i-th period within the control cycle, is the target value of the average power of the wind farm in the i-th period within the control cycle, is the original wind power forecast output of the wind farm in the i-th period within the control period.

3. The method according to claim 2, wherein The target value of the average power of the wind farm in the i-th period within the control cycle is determined by the following formula: In the above formula, is the target value of the average power of the wind farm in the i-1 period within the control period, P N is the installed capacity of wind turbines in the wind farm, where, when i=1, is the average power of the wind farm in the period before the first period in the control period.

4. The method according to claim 1, wherein The objective function of the pre-established wind level suppression optimization model is determined as follows: In the above formula, f is the target value of the wind speed suppression optimization model, i∈[1,N], j∈[1,N], i≤j, and N is the total number of time periods in the control cycle; s ij The ratio of the power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total power generated by the delayed network load that needs to be processed in the i-th period. The electric power generated by the delay load during the i-th period of the control cycle is processed. In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. is the data center power in the jth period of the control cycle, is the power adjustment target of the data center in the jth period within the control cycle, E is the power utilization rate, T is the optimization deadline within the control cycle, T start T is the starting time of the time window that needs to smooth fluctuations within the control period. end T is the end time of the time window that needs to smooth fluctuations within the control period. ahead T is the advance notice duration within the control period. ahead =T start -T0, T0 is the moment when the grid side sends the wind power output leveling signal within the control period.

5. The method according to claim 4, wherein The constraints of the wind speed suppression optimization model are determined as follows: In the above formula, The equivalent output of the wind farm in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle is: The equivalent output of the wind farm in the j-1 period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, P N is the installed capacity of wind turbines in the wind farm, In order to adjust the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period to process the non-delayable load is obtained. After adjusting the planned power consumption of the data center in the control period by using the power consumption adjustment amount of the data center in the control period, the power generated by the data center in the jth period of the control period for processing the non-delayable load is obtained. The power generated by the data center processing the network load in the jth period of the control cycle after adjusting the planned power consumption of the data center in the control cycle by using the power consumption adjustment amount of the data center in the control cycle, The power value generated by processing network load when the data center is running at full load, i+d n -1≤T, n is the total number of categories of delayed loads classified according to processing time limits, d n is the processing time limit corresponding to the nth type of deferrable load classified by processing time limit, The ratio of the electric power generated by the data center in the i-th period during the control period when processing the m-th type of deferrable load classified by processing time limit to the total electric power generated by all types of deferrable load classified by processing time limit in the i-th period; Among them, the adjusted equivalent output of the wind farm is determined by the following formula: In the above formula, is the original wind power forecast output of the wind farm in the jth period within the control period, After the planned power consumption of the data center in the control period is adjusted by using the power consumption adjustment amount of the data center in the control period, the power consumption of the data center in the jth period in the control period is obtained. is the data center power in the jth period within the control period.

6. The method according to claim 1, wherein Solving the pre-established wind speed suppression optimization model to obtain an optimal solution of the power migration matrix of the data center within the control period includes: Solving the pre-established wind speed suppression model using the active set method to obtain an optimal solution for the power migration matrix of the data center within the control period; The optimal solution S of the power migration matrix of the data center during the control period is determined by the following formula: In the above formula, i∈[1,N], j∈[1,N], i≤j, N is the total number of time periods in the control cycle; s ij The ratio of the electric power generated by the data center to process the network load that needs to be processed from the i-th period to the j-th period to the total electric power generated by the delayable network load that needs to be processed in the i-th period.

7. The method according to claim 6, wherein The determining the power adjustment amount of the data center within the control period by using the optimal solution of the power migration matrix of the data center within the control period includes: The power adjustment amount ΔP(j) of the data center during the j-th period of the control cycle is determined by the following formula: In the above formula, The electric power generated by the delay load during the i-th period of the control cycle is processed. is the electric power generated by the delayable load during the j-th period of the control cycle, and E is the electric energy utilization rate.

8. The method according to claim 7, wherein The adjusting the planned power consumption of the data center within the control period by using the power consumption adjustment amount of the data center within the control period includes: The planned power consumption of the data center in the jth period of the control cycle is adjusted according to the following formula: P′(j)=P(j)+ΔP(j) In the above formula, P′(j) is the planned power consumption of the data center in the j-th period within the control cycle after adjustment, and P(j) is the original planned power consumption of the data center in the j-th period within the control cycle.

9. A wind power fluctuation smoothing device for a wind farm, characterized in that: The device comprises: a determination unit, configured to determine an electric power adjustment target of the data center within the control period according to the original wind power forecast output of the wind farm within the control period; An adjustment unit, configured to adjust the planned power consumption of the data center within the control period according to the power consumption target of the data center within the control period; The adjustment unit specifically includes: Substituting the power adjustment target of the data center within the control period into a pre-established wind speed suppression optimization model; Solving the pre-established wind power level suppression optimization model to obtain an optimal solution for the power migration matrix of the data center within the control period; Determining an adjustment amount of electric power consumption of the data center within the control period by using an optimal solution of a power migration matrix of the data center within the control period; The planned power consumption of the data center within the control period is adjusted by utilizing the power consumption adjustment amount of the data center within the control period.

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