A new energy base reactive power optimization method, device, equipment and medium

Abstract

The application discloses a new energy base reactive power optimization method, device, equipment and medium, comprising: obtaining the reactive power optimization parameter of the reactive power source cluster in the new energy base; based on the first preset condition and the reactive power optimization parameter of the reactive power source cluster, the first preset target function is optimized to determine the first predicted reactive power of the reactive power source cluster; based on the second preset condition and the first predicted reactive power of the reactive power source cluster, the second preset target function is optimized to determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station; based on the second predicted reactive power, the network loss and voltage deviation of the new energy power generation equipment are optimized to determine the target reactive power of the new energy power generation equipment. The hierarchical and hierarchical optimization from the cluster to the station and then to the equipment is adopted, the output result of the upper layer is taken as the input of the next layer, the coordinated optimization of different reactive power sources is realized, and the range of reactive power optimization is expanded.

Description

Technical Field

[0001] This invention relates to the field of power system operation and control technology, specifically to a method, device, equipment, and medium for reactive power optimization in a new energy base. Background Technology

[0002] Against the backdrop of building a new power system dominated by new energy sources, newly built new energy power plants are characterized by large installed capacity and clustered grid connection within regions. In the "Three Norths" region (Northeast, North, and Northwest China), a new development model has gradually formed, with new energy bases transmitting power through ultra-high-voltage power grids. As the proportion of new energy sources gradually increases, the scope of reactive power optimization also expands, and the types of reactive power sources become more diverse, including large-scale energy storage devices, newly built / renovated thermal power units within the region, and synchronous condensers. There are also many ways to combine various reactive power sources. The accuracy of reactive power source regulation capability assessment, the cost of reactive power regulation, and the differences in regulation capabilities and speeds of different power sources significantly increase the complexity of coordinated control.

[0003] Since new energy bases contain a variety of reactive power sources, the control performance, response time, and regulation capabilities of each reactive power source vary greatly. Existing reactive power optimization methods only obtain reactive power allocation at the station level and do not consider the coordinated optimization of multiple reactive power sources at a larger scale, which cannot meet the needs of new energy bases. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, equipment and medium for reactive power optimization in new energy bases, so as to achieve coordinated optimization of different reactive power sources in new energy bases.

[0005] According to a first aspect, embodiments of the present invention provide a reactive power optimization method for a new energy base, comprising:

[0006] Obtain reactive power optimization parameters for reactive power source clusters in new energy bases;

[0007] Based on the first preset conditions and the reactive power optimization parameters of the reactive power supply cluster, the first preset objective function is optimized to determine the first predicted reactive power of the reactive power supply cluster. The reactive power supply cluster includes at least a thermal power unit cluster and a new energy equipment cluster.

[0008] Based on the second preset conditions and the first predicted reactive power of the reactive power cluster, the second preset objective function is optimized to determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station.

[0009] Based on the second predicted reactive power, the grid loss and voltage deviation of the new energy power generation equipment are optimized to determine the target reactive power of the new energy power generation equipment.

[0010] The reactive power optimization method for new energy bases provided in this invention first optimizes a first preset objective function based on a first preset condition to obtain the first predicted reactive power of the reactive power source cluster. Then, based on a second preset condition, it optimizes the first predicted reactive power to obtain the target reactive power of the thermal power units in the reactive power source cluster and the second predicted reactive power of the new energy equipment station. Finally, based on the second predicted reactive power, it optimizes the network loss and voltage deviation of the new energy power generation equipment, outputting the target reactive power of the new energy power generation equipment. This method considers the inherent properties of various reactive power sources, adopts a hierarchical approach to optimize step-by-step from the cluster to the station and then to the equipment unit, and uses the output of the upper layer as the input of the lower layer, achieving coordinated optimization of different reactive power sources and expanding the scope of reactive power optimization.

[0011] In some implementations, optimizing the first preset objective function based on the first preset conditions and the reactive power optimization parameters of the reactive power source cluster to determine the first predicted reactive power of the reactive power source cluster includes:

[0012] The first preset objective function is determined based on the voltage offset of the reactive power supply cluster;

[0013] Using the sum of the predicted voltage values ​​of each reactive power source cluster as the first preset condition, the first preset objective function is optimized to determine the first predicted reactive power of each reactive power source cluster.

[0014] In some implementations, optimizing the second preset objective function based on the second preset conditions and the first predicted reactive power of the reactive power source cluster to determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station includes:

[0015] The second preset condition is determined based on the sum of the first predicted reactive power of the reactive power cluster and the voltage prediction value of the reactive power station in the first cycle.

[0016] The ratio of the grid loss and the maximum grid loss in the new energy base grid during the first cycle, and the ratio of the voltage deviation and the maximum voltage deviation of the reactive power station during the first cycle are calculated to determine the second preset objective function.

[0017] The second preset objective function is optimized based on the second preset condition to predict the second reactive power of the thermal power units and new energy equipment stations in the reactive power power cluster.

[0018] In some implementations, optimizing the grid loss and voltage deviation of the new energy power generation equipment based on the second predicted reactive power to determine the target reactive power of the new energy power generation equipment includes:

[0019] Calculate the ratio of the grid loss to the maximum grid loss of the new energy power generation equipment, and the ratio of the voltage deviation to the maximum voltage deviation of the new energy power generation equipment. Based on the sum of the ratio of the grid loss to the maximum grid loss and the ratio of the voltage deviation to the maximum voltage deviation, determine the third preset objective function.

[0020] Based on the second predicted reactive power, a state equation for the reactive power of each new energy power generation device is established. Based on the state equation, the third preset objective function is optimized to determine the target reactive power of the new energy power generation device.

[0021] In some implementations, the third preset objective function is determined according to the following formula:

[0022]

[0023] Among them, P loss_p P lossmax_p These represent the network loss and the maximum value of the network loss collected at the new energy power generation equipment p, respectively; ΔU p , ΔU max_p λ1 and λ2 are the voltage deviation and maximum voltage deviation of the new energy power generation equipment p, respectively; λ1 and λ2 are the weighting coefficients of network loss and voltage deviation, respectively.

[0024] In some implementations, the second preset objective function is determined according to the following formula:

[0025]

[0026] Wherein, ΔU p,t1 , ΔU max_p,t1 These represent the voltage deviation and maximum voltage deviation of reactive power source station P after t1 first cycles, respectively. Reactive power source stations include thermal power units and new energy equipment stations. loss,t1 P loss_max,t1 Let λ represent the grid loss and the maximum grid loss within the new energy base over the first t1 cycles, respectively. t1 N is the penalty coefficient for the voltage offset after t1 first cycles. g T represents the number of nodes in the power grid of the new energy base area, including all new energy power stations. l T represents the total duration. s This indicates the first cycle.

[0027] In some implementations, the first preset objective function is determined according to the following formula:

[0028]

[0029] Where, N s Indicates the number of reactive power source clusters, ΔUt This represents the voltage offset of reactive power supply cluster i.

[0030] According to a second aspect, embodiments of the present invention provide a reactive power optimization device for a new energy base, comprising:

[0031] The data acquisition module is used to acquire the reactive power optimization parameters of the reactive power generation cluster in the new energy base;

[0032] The first power determination module is used to optimize the first preset objective function based on the first preset conditions and the reactive power optimization parameters of the reactive power supply cluster, and determine the first predicted reactive power of the reactive power supply cluster. The reactive power supply cluster includes at least a thermal power unit cluster and a new energy equipment cluster.

[0033] The second power determination module is used to optimize the second preset objective function based on the second preset conditions and the first predicted reactive power of the reactive power power cluster, and determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station.

[0034] The third power determination module is used to optimize the grid loss and voltage deviation of the new energy power generation equipment based on the second predicted reactive power, so as to determine the target reactive power of the new energy power generation equipment.

[0035] According to a third aspect, embodiments of the present invention provide an electronic device, including: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the reactive power optimization method for new energy bases as described in the first aspect or any embodiment of the first aspect.

[0036] According to a fourth aspect, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing the computer to execute the reactive power optimization method for new energy bases as described in the first aspect or any embodiment of the first aspect. Attached Figure Description

[0037] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0038] Figure 1 This is a flowchart of a reactive power optimization method for a new energy base according to an embodiment of the present invention;

[0039] Figure 2 This is a structural block diagram of a reactive power optimization device for a new energy base according to an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] In existing new power systems dominated by new energy sources, the range of reactive power regulation gradually expands with the increasing proportion of new energy, extending from the power plant level to the cluster level, and then to the new energy base level. Furthermore, the types of reactive power sources are diverse, including thermal power, synchronous condensers, wind power, photovoltaic power, and energy storage. Therefore, considering the various scales of new energy power systems and the diverse reactive power sources, this invention provides a reactive power optimization method for new energy bases. This method employs a hierarchical approach to progressively optimize reactive power source clusters, power plants, and equipment units, achieving coordinated and optimized configuration of different reactive power sources. See the embodiments below for details.

[0043] According to an embodiment of the present invention, a method for optimizing reactive power in a new energy base is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0044] This embodiment provides a reactive power optimization method for a new energy base. Figure 1 This is a flowchart of a reactive power optimization method for a new energy base according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0045] S11: Obtain the reactive power optimization parameters of the reactive power supply cluster in the new energy base.

[0046] Reactive power sources in a new energy base can include thermal power, synchronous condensers, and new energy equipment, such as wind power equipment and photovoltaic equipment. A reactive power source cluster can include multiple reactive power source stations. A reactive power source cluster can include one or more types of reactive power sources. For example, a station composed of wind power equipment and photovoltaic equipment can be collectively referred to as a new energy equipment cluster. The specific combination of wind power equipment and photovoltaic equipment is not limited here.

[0047] Reactive power optimization parameters include the equipment's own operating parameters, voltage upper and lower limits, power upper and lower limits, etc. Different reactive power optimization parameters can be obtained in different ways. In this embodiment, the method of obtaining reactive power optimization parameters is not limited.

[0048] S12, based on the first preset conditions and the reactive power optimization parameters of the reactive power supply cluster, optimize the first preset objective function to determine the first predicted reactive power of the reactive power supply cluster, wherein the reactive power supply cluster includes at least a thermal power unit cluster and a new energy equipment cluster.

[0049] The first preset condition and the first preset objective function are constructed based on the reactive power optimization parameters of the reactive power supply cluster. The first preset objective function is optimized to obtain the first predicted reactive power of the reactive power supply cluster when the value of the first preset objective function is minimized. In this embodiment, the reactive power supply cluster includes at least a thermal power unit cluster and a new energy equipment cluster. The new energy equipment cluster includes a variety of new energy equipment or a combination of new energy equipment. The thermal power unit cluster includes a synchronous condenser.

[0050] S13, based on the second preset conditions and the first predicted reactive power of the reactive power supply cluster, optimize the second preset objective function to determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station.

[0051] After obtaining the first predicted reactive power output of the reactive power cluster, a second preset objective function and a second preset condition are established. The second preset objective function and the second preset condition are constructed at a mid-level time scale and are set to the minute level.

[0052] A reactive power supply cluster may consist of one or more reactive power supply stations. In this step, the reactive power supply cluster is further refined to obtain the reactive power output of each reactive power supply station in the cluster. In this embodiment, the reactive power supply stations include new energy equipment stations and thermal power units, wherein the thermal power units include synchronous condensers. The target reactive power of the thermal power units is obtained in this step, meaning that further subdivision and optimization of the thermal power units is not required in subsequent steps.

[0053] S14, Optimize the grid loss and voltage deviation of the new energy power generation equipment based on the second predicted reactive power, so as to determine the target reactive power of the new energy power generation equipment.

[0054] Based on the grid loss and voltage deviation of the new energy power generation equipment, an objective function is constructed. The second predicted reactive power of the new energy power station obtained in S13 is used as the input to the objective model in this step, and the objective function is calculated and solved to obtain the reactive power output of each new energy power generation device in the new energy power station. The new energy power generation devices can include wind power equipment and photovoltaic equipment. A shorter period is used in this layer, for example, it can be set to 5 minutes or less.

[0055] The reactive power optimization method for new energy bases provided in this invention first optimizes a first preset objective function based on a first preset condition to obtain the first predicted reactive power of the reactive power source cluster. Then, based on a second preset condition, it optimizes the first predicted reactive power to obtain the target reactive power of the thermal power units in the reactive power source cluster and the second predicted reactive power of the new energy equipment station. Finally, based on the second predicted reactive power, it optimizes the network loss and voltage deviation of the new energy power generation equipment, outputting the target reactive power of the new energy power generation equipment. This method considers the inherent properties of various reactive power sources, adopts a hierarchical approach to optimize step-by-step from the cluster to the station and then to the equipment unit, and uses the output of the upper layer as the input of the lower layer, achieving coordinated optimization of different reactive power sources and expanding the scope of reactive power optimization.

[0056] In some implementations... Figure 1 S12 in the text includes:

[0057] S21, determine the first preset objective function based on the voltage offset of the reactive power supply cluster.

[0058] S22, using the sum of the predicted voltage values ​​of each reactive power source cluster as the first preset condition, optimize the first preset objective function to determine the first predicted reactive power of each reactive power source cluster.

[0059] The voltage offset of each reactive power source cluster in the new energy base is obtained. The voltage offset can be obtained by calculating the difference between the predicted voltage value and the rated voltage value of the system. A first preset objective function is constructed based on the voltage offset.

[0060] In some implementations, the first preset objective function in S21 is determined according to the following formula:

[0061]

[0062] Where, N s Indicates the number of reactive power source clusters, ΔU t This represents the voltage offset of reactive power supply cluster i.

[0063] The first preset condition is determined according to the following formula:

[0064]

[0065] Among them, P i Q represents the active power injected into the grid by reactive power source cluster i. i U represents the reactive power injected into the grid by reactive power source cluster i. i U represents the predicted voltage value of reactive power source cluster i. j θ represents the predicted voltage value of reactive power source cluster j. ij G represents the voltage phase difference between reactive power source clusters i and j. ij B ij U represents the real and imaginary parts of the line admittance ij, respectively. max_i U min_i Q represents the upper and lower limits of the voltage of reactive power source cluster i, respectively. max_i Q min_i These are the upper and lower limits of the reactive power output of reactive power group i, respectively.

[0066] In some implementations... Figure 1 S13 in the text includes:

[0067] S31, determine the second preset condition based on the sum of the first predicted reactive power of the reactive power cluster and the predicted voltage of the reactive power station in the first cycle.

[0068] S32, calculate the ratio of the grid loss and the maximum grid loss of the power grid in the new energy base during the first cycle, and the ratio of the voltage deviation of the reactive power station to the maximum voltage deviation during the first cycle, in order to determine the second preset objective function.

[0069] S33, optimize the second preset objective function based on the second preset conditions to predict the second reactive power of the thermal power units and new energy equipment stations in the reactive power cluster.

[0070] The second preset objective function is determined according to the following formula:

[0071]

[0072] Wherein, ΔU p,t1 , ΔU max_p,t1 These represent the voltage deviation and maximum voltage deviation of reactive power source station P after t1 first cycles, respectively. Reactive power source stations include thermal power units and new energy equipment stations. losst1 P loss maxt1Let λ represent the grid loss and the maximum grid loss within the new energy base over the first t1 cycles, respectively. t1 N is the penalty coefficient for the voltage offset after t1 first cycles. g T represents the number of nodes in the power grid of the new energy base area, including all new energy power stations. l T represents the total duration. s This indicates the first cycle.

[0073] The second preset condition is determined according to the following formula:

[0074]

[0075] Among them, P p,t1 Q p,t1 These represent the active and reactive power outputs of the reactive power source station P after t1 first cycles. pnew,t1 Q pnew,t1 Q represents the active power and reactive power output of the new energy equipment power station p within the first cycle t1, respectively. pG,t1 Q represents the target reactive power of the thermal power unit after t1 cycles of the first cycle. pcomp,t1 Q represents the reactive power output of the reactive power compensation device after t1 first cycles. pstorage,t1 ΔQ represents the reactive power output of the energy storage after t1 first cycles. max_pnew ΔQ min_pnew ΔQ max_pcomp ΔQ min_pcomp ΔQ max_pstorage ΔQ min_pstorage k represents the upper and lower limits of the reactive power output changes of the reactive power source station p connected to the new energy equipment station, reactive power compensation equipment, and energy storage device based on the first cycle. new,t1 This represents the error coefficient for predicting the power of new energy equipment after t1 first cycles. Its value does not exceed 1, and the actual value needs to be determined in conjunction with the adjustable range of the power factor of the new energy equipment. storage,t1 This represents the reserve factor for the reactive power output of the energy storage device after t1 first cycles. Its value does not exceed 1, and the actual value needs to be determined in conjunction with the adjustable power factor range of the energy storage device. U p,t1 U represents the predicted voltage value of reactive power source station p after t1 first cycles. q,t1 θ represents the predicted voltage value of the reactive power source station q after t1 first cycles. pq,t1 G represents the voltage phase difference between p and q at a reactive power source station after t1 first cycles. pq B pq U represents the real and imaginary parts of the line pq admittance, respectively. max_p,t1 U min_p These represent the upper and lower limits of the p-voltage at the reactive power source station, respectively.q S represents the number of reactive power generation stations. new This indicates the capacity of the new energy equipment power station.

[0076] In some implementation methods, the grid loss within the new energy base during the first cycle is determined according to the following formula:

[0077]

[0078] Where, N g G represents the number of all new energy equipment stations and thermal power units within the new energy base. pq U represents the real and imaginary parts of the line pq admittance. p,t1 U represents the voltage deviation of a thermal power unit or new energy equipment station p after t1 first cycles. q,t1 This indicates the voltage deviation of the new energy equipment power station q within the first cycle t1.

[0079] The MATLAB-based matpower calculation toolkit optimizes a second preset objective function based on second preset conditions, outputting the reactive power of reactive power generation plants, including thermal power units and renewable energy equipment plants. The first cycle is set to a prediction interval in minutes, with a total duration of 15 minutes. Optimization is performed on the first minute-level cycle, with T optimization iterations on the time scale. l / T s .

[0080] In some implementations... Figure 1 S14 in the text includes:

[0081] S41, calculate the ratio of the grid loss of the new energy power generation equipment to the maximum grid loss, and the ratio of the voltage deviation of the new energy power generation equipment to the maximum voltage deviation. Based on the sum of the ratio of the grid loss to the maximum grid loss and the ratio of the voltage deviation to the maximum voltage deviation, determine the third preset objective function.

[0082] S42, establish the state equation of reactive power of each new energy power generation device based on the second predicted reactive power, and optimize the third preset objective function based on the state equation to determine the target reactive power of the new energy power generation device.

[0083] In this embodiment, the second predicted reactive power output of the new energy equipment station is optimized. There may be multiple new energy power generation equipment in the new energy equipment station, such as wind power equipment and photovoltaic equipment. Considering that there are many collection lines and step-up transformers in the station, a large network loss will be generated. Therefore, the optimization is carried out with minimizing this part of the network loss and voltage deviation as the objective function, and a third preset objective function is constructed.

[0084] In some implementations, the third preset objective function is determined according to the following formula:

[0085]

[0086] Among them, P loss_p P lossmax_p These represent the network loss and the maximum value of the network loss collected at the new energy power generation equipment p, respectively; ΔU p , ΔU max_p λ1 and λ2 represent the voltage deviation and maximum voltage deviation of the new energy power generation equipment p, respectively; λ1 and λ2 are the weighting coefficients for network loss and voltage deviation, respectively. Among them, network loss mainly refers to the network loss generated by transformers and collector lines.

[0087] Since there are numerous new energy power generation devices in a new energy power plant, to simplify the calculation, a state equation is established for calculation. The state equation is determined according to the following formula:

[0088]

[0089] Wherein, ΔU p U represents the voltage offset value of the new energy power generation equipment p. p ΔP represents the predicted voltage value of the new energy power generation equipment p. loss_p P represents the network loss of new energy equipment power stations. loss_p ΔQ represents the change in network losses at new energy power stations. punit ΔQ represents the reactive power vector output by the new energy power generation equipment. punit =[ΔQ punit1 ,ΔQ punit2 ,...ΔQ punitn ] T ΔP L ΔQ L P represents the change in active power and the change in reactive power of the load, respectively. L Q L These represent the active and reactive power of the load, respectively. The values ​​of the sensitivity matrix in the first term of the state equation are calculated. Larger values ​​in the first row indicate a greater impact of changes in reactive power output from the renewable energy generation equipment on voltage changes, while larger values ​​in the second row indicate a greater impact of changes in reactive power output from the renewable energy generation equipment on network losses. Multiplying [λ1, -λ2] by the column vectors of the sensitivity matrix yields the influence factors of each renewable energy generation device on network losses and voltage deviation. The reactive power output of each renewable energy generation device is then allocated according to the magnitude of these influence factors, using the following allocation formula:

[0090]

[0091] In the process of reactive power allocation, it is necessary to consider the adjustable range of the power factor of the actual new energy power generation equipment. The reactive power optimization method for new energy bases provided by this invention considers the characteristics of each reactive power source and constructs a three-layer optimization model. Each layer has a corresponding preset objective function. Considering the complexity of reactive power optimization in new energy bases, in order to reduce the amount of computation, it is divided by scale and time scale. The upper layer outputs the reactive power of the thermal power unit cluster and the new energy equipment cluster. The middle layer continues to optimize the thermal power unit cluster and the new energy equipment cluster to obtain the target reactive power of the thermal power unit and the reactive power of the new energy power station. The lower layer optimizes the new energy power station to obtain the reactive power of the new energy power generation equipment.

[0092] This embodiment also provides a reactive power optimization device for a new energy base. This device is used to implement the above embodiments and implementation methods, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0093] This embodiment provides a reactive power optimization device for a new energy base, such as... Figure 2 As shown, it includes:

[0094] The data acquisition module is used to acquire the reactive power optimization parameters of the reactive power generation cluster in the new energy base;

[0095] The first power determination module is used to optimize the first preset objective function based on the first preset conditions and the reactive power optimization parameters of the reactive power supply cluster, and determine the first predicted reactive power of the reactive power supply cluster. The reactive power supply cluster includes at least a thermal power unit cluster and a new energy equipment cluster.

[0096] The second power determination module is used to optimize the second preset objective function based on the second preset conditions and the first predicted reactive power of the reactive power power cluster, and determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station.

[0097] The third power determination module is used to optimize the grid loss and voltage deviation of the new energy power generation equipment based on the second predicted reactive power, so as to determine the target reactive power of the new energy power generation equipment.

[0098] In some implementations, the first power determination module includes:

[0099] The first function determination unit is used to determine the first preset target function based on the voltage offset of the reactive power supply cluster.

[0100] The first power determination unit is used to optimize the first preset objective function with the sum of the predicted voltage values ​​of each reactive power source cluster as the first preset condition, and determine the first predicted reactive power of each reactive power source cluster.

[0101] In some implementations, the second power determination module includes:

[0102] The second condition determination unit is used to determine the second preset condition based on the sum of the first predicted reactive power of the reactive power cluster and the voltage prediction value of the reactive power station in the first cycle.

[0103] The second function determination unit is used to calculate the ratio of the grid loss and the maximum grid loss of the power grid in the new energy base within the first cycle, and the ratio of the voltage deviation of the reactive power station to the maximum voltage deviation within the first cycle, so as to determine the second preset objective function.

[0104] The second power determination unit is used to optimize the second preset objective function based on the second preset conditions in order to determine the second predicted reactive power of the thermal power units and new energy equipment stations in the reactive power supply cluster.

[0105] In some implementations, the third power determination module includes:

[0106] The third function determination unit is used to calculate the ratio of the grid loss of the new energy power generation equipment to the maximum grid loss, and the ratio of the voltage deviation of the new energy power generation equipment to the maximum voltage deviation. Based on the sum of the ratio of the grid loss to the maximum grid loss and the ratio of the voltage deviation to the maximum voltage deviation, a third preset objective function is determined.

[0107] The third power determination unit is used to establish the state equation of the reactive power of each new energy power generation device based on the second predicted reactive power, and optimize the third preset objective function based on the state equation to determine the target reactive power of the new energy power generation device.

[0108] In some implementations, the third preset objective function is determined according to the following formula:

[0109]

[0110] Among them, P loss_p P lossmax_p These represent the network loss and the maximum value of the network loss collected at the new energy power generation equipment p, respectively; ΔU p , ΔU max_p λ1 and λ2 are the voltage deviation and maximum voltage deviation of the new energy power generation equipment p, respectively; λ1 and λ2 are the weighting coefficients of network loss and voltage deviation, respectively.

[0111] In some embodiments, the

[0112] The second preset objective function is determined according to the following formula:

[0113]

[0114] Wherein, ΔU p,t1 , ΔU max_p,t1 These represent the voltage deviation and maximum voltage deviation of reactive power source station P after t1 first cycles, respectively. Reactive power source stations include thermal power units and new energy equipment stations. loss,t1 P loss_max,t1 Let λ represent the grid loss and the maximum grid loss within the new energy base over the first t1 cycles, respectively. t1 N is the penalty coefficient for the voltage offset after t1 first cycles. g T represents the number of nodes in the power grid of the new energy base area, including all new energy power stations. l T represents the total duration. s This indicates the first cycle.

[0115] In some implementations, the first preset objective function is determined according to the following formula:

[0116]

[0117] Where, N s Indicates the number of reactive power source clusters, ΔU t This represents the voltage offset of reactive power supply cluster i.

[0118] In this embodiment, the reactive power optimization device for the new energy base is presented in the form of a functional unit. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0119] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0120] This invention also provides an electronic device having the above-described features. Figure 2 The reactive power optimization device shown is located in the new energy base.

[0121] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an optional embodiment of the present invention, such as... Figure 3As shown, the electronic device may include: at least one processor 601, such as a CPU (Central Processing Unit), at least one communication interface 603, memory 604, and at least one communication bus 602. The communication bus 602 is used to enable communication between these components. The communication interface 603 may include a display screen or a keyboard; optionally, the communication interface 603 may also include a standard wired interface or a wireless interface. The memory 604 may be high-speed RAM (Random Access Memory) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 604 may also be at least one storage device located remotely from the aforementioned processor 601. The processor 601 may be combined with... Figure 2 The described apparatus has an application program stored in memory 604, and a processor 601 calls the program code stored in memory 604 to perform any of the above method steps.

[0122] The communication bus 602 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus 602 can be divided into an address bus, a data bus, and a control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0123] The memory 604 may include volatile memory, such as random-access memory (RAM); the memory may also include non-volatile memory, such as flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory 604 may also include a combination of the above types of memory.

[0124] The processor 601 can be a central processing unit (CPU), a network processor (NP), or a combination of CPU and NP.

[0125] The processor 601 may further include a hardware chip. This hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0126] Optionally, the memory 604 is also used to store program instructions. The processor 601 can call the program instructions to implement the reactive power optimization method for new energy bases as shown in the embodiments of this application.

[0127] This invention also provides a non-transitory computer storage medium storing computer-executable instructions that can execute the reactive power optimization method for new energy bases in any of the above method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0128] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for reactive power optimization of a new energy base, characterized in that, The method comprises the following steps: acquiring reactive power optimization parameters of a reactive power source cluster in a new energy base; optimizing a first preset target function based on a first preset condition and the reactive power optimization parameters of the reactive power source cluster to determine first predicted reactive power of the reactive power source cluster, the reactive power source cluster at least including a thermal power unit cluster and a new energy equipment cluster; optimizing a second preset target function based on a second preset condition and the first predicted reactive power of the reactive power source cluster to determine target reactive power of the thermal power unit and second predicted reactive power of the new energy equipment station; optimizing network loss and voltage deviation of the new energy power generation equipment based on the second predicted reactive power to determine target reactive power of the new energy power generation equipment; the step of optimizing the first preset target function based on the first preset condition and the reactive power optimization parameters of the reactive power source cluster to determine the first predicted reactive power of the reactive power source cluster comprises the following steps: determining the first preset target function according to voltage deviation of the reactive power source cluster; and optimizing the first preset target function with the sum of voltage prediction values of each reactive power source cluster as the first preset condition to determine the first predicted reactive power of each reactive power source cluster; the step of optimizing the second preset target function based on the second preset condition and the first predicted reactive power of the reactive power source cluster to determine the target reactive power of the thermal power unit and the second predicted reactive power of the new energy equipment station comprises the following steps: determining the second preset condition according to the first predicted reactive power of the reactive power source cluster and the sum of voltage prediction values of the reactive power source station in a first period; calculating the ratio of network loss of the power grid in the new energy base to the maximum network loss in the first period and the ratio of voltage deviation of the reactive power source station to the maximum voltage deviation in the first period to determine the second preset target function; and optimizing the second preset target function based on the second preset condition to determine the second predicted reactive power of the thermal power unit and the new energy equipment station in the reactive power source cluster; the step of optimizing the network loss and the voltage deviation of the new energy power generation equipment based on the second predicted reactive power to determine the target reactive power of the new energy power generation equipment comprises the following steps: calculating the ratio of the network loss of the new energy power generation equipment to the maximum network loss and the ratio of the voltage deviation of the new energy power generation equipment to the maximum voltage deviation to determine a third preset target function based on the sum of the ratio of the network loss to the maximum network loss and the ratio of the voltage deviation to the maximum voltage deviation; and establishing a state equation of reactive power of each new energy power generation equipment based on the second predicted reactive power, and optimizing the third preset target function based on the state equation to determine the target reactive power of the new energy power generation equipment.

2. The method of claim 1, wherein, The third preset target function is determined according to the following formula: wherein, P loss_p , P lossmax_p are the network loss and the maximum network loss, respectively, aggregated to the new energy power generation device p; Δ U p , U max_p are the voltage deviation and the maximum voltage deviation, respectively, of the new energy power generation device p; The second preset target function is determined according to the following formula: 1, The first preset target function is determined according to the following formula: 2 are the weight coefficients of the network loss and the voltage deviation, respectively.

3. The method of claim 1, wherein, The method comprises the following steps: wherein, Δ U p,t1 , Δ U max_p,t1 respectively represent the voltage deviation and the maximum voltage deviation of the reactive power source station p in t1 first periods, the reactive power source station including thermal power units and new energy equipment stations, P loss,t1 , P loss_max,t1 respectively represent the grid loss and the maximum grid loss of the grid in the new energy base in t1 first periods, a data acquisition module configured to acquire reactive power optimization parameters of a reactive power source cluster in a new energy base; t1 is a penalty coefficient of the voltage deviation in t1 first periods, N g is the number of nodes of the new energy base regional grid containing all new energy stations, T l represents the total duration, T s represents the first period.

4. The method of claim 1, wherein, ​ wherein, N s represents the number of reactive power source clusters, Δ U t represents the voltage offset of the reactive power source cluster i.

5. A new energy base reactive power optimization device, characterized in that, ​ ​ The first power determination module is configured to optimize a first preset target function based on a first preset condition and a reactive power optimization parameter of the reactive power source cluster, and determine a first predicted reactive power of the reactive power source cluster, wherein the reactive power source cluster at least includes a thermal power unit cluster and a new energy equipment cluster. The second power determination module is configured to optimize a second preset target function based on a second preset condition and the first predicted reactive power of the reactive power source cluster, and determine a target reactive power of the thermal power unit and a second predicted reactive power of the new energy equipment station. The third power determination module is configured to optimize a network loss of the new energy power generation equipment and a voltage deviation based on the second predicted reactive power, and determine a target reactive power of the new energy power generation equipment. The first power determination module includes a first function determination unit configured to determine the first preset target function according to a voltage deviation of the reactive power source cluster, and a first power determination unit configured to optimize the first preset target function by taking a sum of voltage prediction values of the reactive power source clusters as the first preset condition, and determine the first predicted reactive power of each reactive power source cluster. The second power determination module includes a second condition determination unit configured to determine the second preset condition according to the first predicted reactive power of the reactive power source cluster and a sum of voltage prediction values of the reactive power source stations in the first period, a second function determination unit configured to calculate a ratio of a network loss of the power grid in the new energy base to a maximum value of the network loss, and a ratio of a voltage deviation of the reactive power source station to a maximum value of the voltage deviation in the first period, to determine the second preset target function, and a second power determination unit configured to optimize the second preset target function based on the second preset condition, to determine the second predicted reactive power of the thermal power unit and the new energy equipment station in the reactive power source cluster. The third power determination module includes a third function determination unit configured to calculate a ratio of the network loss of the new energy power generation equipment to a maximum value of the network loss, and a ratio of the voltage deviation of the new energy power generation equipment to a maximum value of the voltage deviation, and determine a third preset target function based on a sum of the ratio of the network loss to the maximum value of the network loss and the ratio of the voltage deviation to the maximum value of the voltage deviation, and a third power determination unit configured to establish a state equation of the reactive power of each new energy power generation equipment based on the second predicted reactive power, and optimize the third preset target function based on the state equation, to determine the target reactive power of the new energy power generation equipment.

6. An electronic device, comprising: The memory and the processor are connected in communication with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the new energy base reactive power optimization method in any one of claims 1-4. The computer readable storage medium stores computer instructions for causing a computer to perform the new energy base reactive power optimization method in any one of claims 1-4.

7. A computer readable storage medium characterized in that, ​

Images