Planning method of reactive power compensation device of power distribution network and related equipment

Abstract

The embodiment of the invention discloses a planning method of a reactive power compensation device of a power distribution network and related equipment. According to the embodiment of the invention, load curves of different types of loads in a transformer area can represent characteristics of large-difference seasonal loads; the built bilevel planning model comprehensively considers energy storage, reactive power compensation device, inverter reactive power regulation capability and traditional reactive power compensation performance; according to the optimal installation position and the optimal capacity of the reactive power compensation device obtained based on the load curves of different types of loads in the transformer area and the bilevel programming model, the problem of voltage out-of-limit of the 10kV transformer area caused by large-scale distributed photovoltaic access and seasonal load distribution can be solved, and the photovoltaic light abandoning rate is reduced; coordinated operation of flexible adjustment equipment of a 10kV system is realized, and the difficulty of considering reliability and economical efficiency of a planning scheme is reduced.

Description

[Technical field]

[0001] The present invention relates to the technical field of power system planning, and in particular to a planning method for a reactive power compensation device of a distribution network and related equipment. [Background technology]

[0002] In recent years, with the support and guidance of national policies, renewable energy has made great progress. However, the contradiction between the explosive growth of new energy installed capacity and the lack of flexible regulation ability of the distribution network has become increasingly prominent. In particular, the load differences between the substations are large, and the loads caused by different industrial characteristics have special fluctuation cycles and characteristics, resulting in the imbalance of 10kV load in time and space, which is not only not conducive to the local consumption of new energy resources, but also leads to the decline of power quality and economy in the case of the lack of flexible regulation ability of the distribution network. Therefore, it is of practical engineering significance to study the coordinated planning strategy of distribution network flexibility resources in a targeted manner to realize the reasonable planning and application of highly volatile renewable energy.

[0003] Existing research on regulation methods focuses on the characteristics of different flexible devices or the impact of dealing with the uncertainty of wind and solar power, but does not consider the impact of large seasonal load differences between substations and between substations on distribution network planning and economic operation. For areas with large seasonal load differences, seasonal and temporary low voltage problems will occur in different 10kV outgoing lines and different substations. The location of low-voltage substation outgoing lines changes with the seasons and holidays, making it more difficult to plan a plan that takes into account both reliability and economy. [Summary of the invention]

[0004] In view of this, the present invention provides a planning method for a reactive power compensation device of a distribution network and related equipment.

[0005] The specific technical scheme of the first embodiment of the present invention is: a planning method for a reactive compensation device of a distribution network, the method comprising: obtaining load curves of different types of loads in a substation; obtaining the regulation cost of a voltage regulation device based on regulation of discrete and continuous voltage regulation devices; constructing a two-layer planning model taking into account the multi-quadrant operation capability of the converter; the two-layer planning model comprises an upper-layer planning model and a lower-layer planning model; the upper-layer planning model aims to minimize the investment and operation cost of the energy storage device, the reactive compensation cost of the reactive compensation device and the operation cost of the distribution network, and determines the installation location and capacity of the energy storage system and the reactive compensation device; the lower-layer planning model aims to minimize the operation cost of the distribution network while satisfying the operation constraints of the distribution network; the operation cost of the distribution network comprises: network loss, the cost of purchasing electricity from the distribution network, the operation cost of the photovoltaic system and the energy storage system, the regulation cost of the voltage regulation device and the carbon emission cost; the load curves of the different types of loads are input into the two-layer planning model to obtain the optimal installation location and optimal capacity of the reactive compensation device.

[0006] Preferably, the acquisition of load curves of different types of loads in the substation includes: classifying the load types of the substation according to the electricity consumption characteristics of the substation to obtain classification results of different load types; performing feature analysis on the classification results of the different load types to obtain a first load feature of each load type; obtaining the annual load fluctuation curves of the substation at different times; using a clustering algorithm to classify the annual load fluctuation curves at different times to obtain different types of annual load fluctuation curves; performing wavelet transform on the different types of annual load fluctuation curves to obtain second load features of different types of annual load fluctuation curves; determining the target load type of the substation based on the first load feature and the second load feature; the target load type is multiple load types; obtaining the target load fluctuation curve corresponding to each target load type in the annual load fluctuation curves at different times; obtaining the occurrence period of each target load fluctuation curve within the year, and analyzing the distribution pattern of the target load fluctuation curve in each month to determine the monthly load fluctuation curves and scenarios of the substation; the load fluctuation curves in different months and different scenarios constitute the load curves of different types of loads in the substation.

[0007] Preferably, the voltage regulation device regulation cost is obtained using the following formula:

[0008]

[0009] in, regulating costs for said voltage regulating device, The operating cost of discrete reactive power regulation equipment, For continuous reactive power regulation equipment operating costs, is the tap position of the on-load tap-changing transformer at time t, is the reactive power generated or absorbed by the energy storage at node i at time t, is the reactive power generated or absorbed by the photovoltaic inverter at node j at time t, is the reactive power generated or absorbed by the reactive power compensation device at node k at time t, Ⅱ(·) is the indicator function, and the output is 1 when it is not zero, ρ is the weight coefficient, and T is the specified operating time.

[0010] Preferably, the upper-level planning model is obtained using the following formula:

[0011] f 1 =min(F DES +F SVCc +F L )

[0012] Among them, f 1 is the upper-level planning model, F DES is the investment and operation cost of the energy storage device, F SVCcis the reactive power compensation cost of the reactive power compensation device, F L The operating cost of the distribution network.

[0013] Preferably, the lower-level planning model is obtained using the following formula:

[0014]

[0015] Among them, f 2 is the lower-level planning model, F loss is the network loss cost, F B is the electricity purchase cost of the distribution network, Punishment for abandoning the light, is the operating cost of the PV inverter, is the operating cost of the energy storage device, is the equipment adjustment cost, F carbon The cost of carbon emissions.

[0016] Preferably, the load curves of the different types of loads are input into the two-layer programming model to obtain the optimal installation position and the optimal capacity of the reactive compensation device, including: inputting the load curves of the different types of loads into the two-layer programming model to obtain different installation positions of the reactive compensation device and the capacity corresponding to each installation position; optimizing the different installation positions of the reactive compensation device and the capacity corresponding to each installation position with minimizing the equipment operating cost of the reactive compensation device as the objective function to obtain the optimal installation position and the optimal capacity of the reactive compensation device.

[0017] Preferably, the objective function is obtained using the following formula:

[0018]

[0019] Among them, F run is the equipment operating cost of the reactive power compensation device, F oper is the regulation energy consumption cost per unit capacity of the reactive power compensation device, is the access capacity of the i-th reactive power compensation device at time t, D i represents the moving distance of the i-th reactive power compensation device, F move is the moving cost per unit moving distance of the reactive power compensation device, N represents the total number of reactive power compensation devices, It is a binary variable, indicating whether the i-th reactive power compensation device is enabled. 0 indicates that the reactive power compensation device is not enabled, and 1 indicates that the reactive power compensation device is enabled.

[0020] The specific technical solution of the second embodiment of the present invention is: a planning system for reactive power compensation devices of a distribution network, the system comprising: a load curve acquisition module, a regulation cost acquisition module, a double-layer planning model construction module and an installation location and capacity output module; the load curve acquisition module is used to obtain load curves of different types of loads in the substation; the regulation cost acquisition module is used to obtain the regulation cost of voltage regulation equipment based on discrete and continuous voltage regulation equipment; the double-layer planning model construction module is used to construct a double-layer planning model taking into account the multi-quadrant operation capability of the converter; the double-layer planning model includes an upper-layer planning model and a lower-layer planning model; the upper-layer planning The model aims to minimize the investment and operation cost of the energy storage device, the reactive compensation cost of the reactive compensation device and the operation cost of the distribution network, and determines the installation location and capacity of the energy storage system and the reactive compensation device; the lower-level planning model aims to minimize the operation cost of the distribution network while satisfying the operation constraints of the distribution network; the operation cost of the distribution network includes: network loss, the cost of purchasing electricity from the distribution network, the operation cost of the photovoltaic system and the energy storage system, the regulation cost of the voltage regulation equipment and the carbon emission cost; the installation location and capacity output module is used to input the load curves of the different types of loads into the two-level planning model to obtain the optimal installation location and optimal capacity of the reactive compensation device.

[0021] The specific technical solution of the third embodiment of the present invention is: a planning device for a reactive compensation device of a distribution network, comprising a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method as described in any one of the first embodiments of the present application.

[0022] The specific technical solution of the fourth embodiment of the present invention is: a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to perform the steps of the method described in any one of the first embodiments of the present application.

[0023] Implementing the embodiments of the present invention will have the following beneficial effects:

[0024] The present invention obtains the load curves of different types of loads in the substation, and constructs a two-layer planning model taking into account the multi-quadrant operation capability of the converter based on the adjustment cost of the voltage regulation equipment. The optimal installation position and optimal capacity of the reactive compensation device are obtained by inputting the load curves of different types of loads into the two-layer planning model.

[0025] The load curves of different types of loads in the substation in this application can characterize the characteristics of large-scale seasonal load differences. The constructed two-layer planning model comprehensively considers the performance of energy storage, reactive compensation devices, inverter reactive regulation capabilities and traditional reactive compensation. The optimal installation position and optimal capacity of the reactive compensation device obtained based on the load curves of different types of loads in the substation and the two-layer planning model can not only solve the 10kV substation voltage over-limit problem caused by large-scale distributed photovoltaic access and seasonal load distribution problems, but also reduce the photovoltaic abandonment rate, realize the coordinated operation of the 10kV system flexible regulation equipment, and reduce the difficulty of planning schemes to take into account both reliability and economy.

Brief Description of the Drawings

[0026] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 A flowchart of the steps of a first embodiment of a method for planning a reactive power compensation device of a distribution network;

[0028] Figure 2 It is a schematic diagram of the node network topology of the distribution network system;

[0029] Figure 3 A flow chart of the steps for obtaining load curves for different types of loads in the substation;

[0030] Figure 4 A flowchart of steps for obtaining the optimal installation position and optimal capacity of the reactive power compensation device;

[0031] Figure 5 A flowchart of the steps of a second embodiment of a method for planning a reactive power compensation device;

[0032] Figure 6 It is a multi-quadrant operation diagram for distributed photovoltaic and energy storage;

[0033] Figure 7 The structural diagram of the planning system of reactive power compensation device for distribution network;

[0034] Among them, 601 is a load curve acquisition module; 602 is an adjustment cost acquisition module; 603 is a two-layer planning model construction module; 604 is an installation location and capacity output module. [Specific implementation method]

[0035] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0036] The terms "first", "second", etc. in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but optionally includes steps or modules that are not listed, or optionally includes other steps or modules that are inherent to these processes, methods, products or devices.

[0037] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0038] See also Figure 1 , is a flowchart of the steps of a planning method for a reactive power compensation device of a distribution network in the first embodiment of the present application, which reduces the difficulty of planning a scheme that takes both reliability and economy into consideration. The method includes:

[0039] Step 101, obtaining load curves of different types of loads in the substation;

[0040] Step 102, obtaining the voltage regulation device regulation cost based on the discrete and continuous voltage regulation devices;

[0041] Step 103, construct a two-level planning model that takes into account the multi-quadrant operation capability of the converter; the two-level planning model includes an upper-level planning model and a lower-level planning model; the upper-level planning model aims to minimize the investment and operation cost of the energy storage device, the reactive compensation cost of the reactive compensation device, and the operation cost of the distribution network, and determines the installation location and capacity of the energy storage system and the reactive compensation device; the lower-level planning model aims to minimize the operation cost of the distribution network under the constraints of the distribution network operation; the operation cost of the distribution network includes: network loss, the cost of purchasing electricity from the distribution network, the operation cost of the photovoltaic system and the energy storage system, the regulation cost of the voltage regulation equipment, and the carbon emission cost;

[0042] Step 104: Input the load curves of the different types of loads into the two-layer programming model to obtain the optimal installation position and optimal capacity of the reactive power compensation device.

[0043] Specifically, in the preferred embodiment of the present application, an improved IEEE 33 node distribution network system (hereinafter referred to as: system) is used for simulation. The improved IEEE 33 node network topology is as follows: Figure 2 The system reference value is U B =12.66kV, S B =1MVA. An on-load tap-changing transformer is installed at node 1, and the transformer tap adjustment range is 1.025±6×2.5%. Photovoltaic generators are connected at nodes 17 and 32, with a rated capacity of 1.5MW and a rated light intensity of 1000W / m 2 The simulation analysis was carried out on this system, and the selected simulation platform was matlab2021a. The capacity and location of two energy storage devices were planned, and the site selection planning was carried out for three reactive power compensation devices with a capacity of 1000kVar.

[0044] The load curves of different types of loads in the substation in this embodiment can characterize the characteristics of large-scale seasonal load differences. The constructed two-layer planning model comprehensively considers the performance of energy storage, reactive compensation devices, inverter reactive regulation capability and traditional reactive compensation. The optimal installation position and optimal capacity of the reactive compensation device obtained based on the load curves of different types of loads in the substation and the two-layer planning model can not only solve the 10kV substation voltage over-limit problem caused by large-scale distributed photovoltaic access and seasonal load distribution problems, but also reduce the photovoltaic abandonment rate, realize the coordinated operation of the 10kV system flexible regulation equipment, and reduce the difficulty of planning schemes to take into account both reliability and economy.

[0045] Specifically, Yunnan is taken as an example in the embodiments of the present application. Yunnan is mountainous, resulting in a long power supply radius and many branches in the Yunnan power grid. For areas where agriculture and tourism are the main economic pillars, their load fluctuations are affected by special load types such as the peak tourist season, spring farmland irrigation, tea picking and tobacco making. The industrial effect, seasonal effect and long and short holiday effects of the load are more prominent. Due to the impact of the wave of returning to work and school in February, the number of tourists decreased and the electricity load decreased. April is the peak season for tea making, and July-November is the peak season for flue-cured tobacco production, and the power load increases significantly. The daily maximum load difference in the province is as high as 11,000MW, and the daily load range is as high as more than 5,000MW, which are 44% and 20% of the annual maximum load respectively. Assume that the Yunnan Provincial Distribution Network selects the following three typical load curves of 10kV substations: the load during the peak tourist period of the Spring Festival, the tea making load in April in spring, and the load during the flue-cured tobacco period from July to November.

[0046] In the specific embodiments, see Figure 3 , the step of obtaining load curves of different types of loads in the substation includes:

[0047] Step 201: classify the load types of the substation according to the power consumption characteristics of the substation to obtain classification results of different load types;

[0048] Specifically, the load of the substation is preliminarily classified according to the electricity consumption characteristics of tea-making load, baking load, and tourism load; in the embodiment of the present application, the tourism load, tea-making load, and flue-cured tobacco load curves are very different. 12 noon is the morning peak of the tourism load, 5 pm to 9 pm is the evening peak, and the highest load of the day usually occurs during the evening peak. During the winter tourism peak, the increase in tourists leads to an increase in hotel occupancy rates and an increase in electricity consumption at night, while the electricity demand during the day is relatively low, and the load of the scenic area is similar to that of the working day. The tea-making load is connected to the tea season in April. Its daily load curve, although the overall load has little effect on the power grid, due to the concentrated electricity consumption in the tea area, tea picking during the day and tea making at night cause the load to rise rapidly during a specific period, which has a significant impact on the local power grid equipment and power quality. The daily load curve clearly shows that the load characteristics of the tea season are opposite to those of the non-tea season: the load is lower during the day and higher at night during the tea season, while the load is higher during the day and lower at night during the non-tea season. The electricity consumption characteristics of tourism load usually show a morning peak at noon and an evening peak from afternoon to evening. The load is especially high during the evening peak period. The tourism load shows obvious peak and low peak fluctuations. The load is higher during the winter tourism peak, but the daytime load is closer to that of ordinary working days.

[0049] Step 202: Perform feature analysis on the classification results of the different load types to obtain a first load feature of each load type;

[0050] In the embodiment of the present application, in the tobacco flue-curing cycle from July to November in Yunnan, the peak of the drying heat load is concentrated in the forced ventilation stage, the late withering stage and the large roll stage. The load fluctuation pattern in different baking periods is relatively similar, and the peak value does not exceed 40kW. The flue-cured tobacco load has a certain fluctuation pattern. During forced ventilation, the air flow is accelerated and the heat demand increases significantly; in the late withering stage, the evaporation of tobacco leaf moisture is accelerated, and the heat pump drying system needs to provide more heat, thereby increasing the load; and in the large roll stage, the curling of the tobacco leaves accelerates the drying process and further increases the heat load. According to the acquisition of the historical load curve of the substation, the peak period of the load curve, the seasonal fluctuation characteristics, etc. are analyzed, and the typical load characteristics of the loads in different substations can be extracted.

[0051] Step 203, obtaining the annual load fluctuation curve of the substation at different times;

[0052] Specifically, the annual load fluctuation curve of each substation is extracted. The load data should include detailed information on the change of power consumption over time, and should be collected at 15-minute intervals.

[0053] Step 204: using a clustering algorithm to classify the annual load fluctuation curves at different times to obtain different types of annual load fluctuation curves;

[0054] Specifically, the obtained fluctuation curves are divided into several categories according to the clustering algorithm to obtain several typical load curves. The k-means clustering analysis steps of the load curves include:

[0055] Step 1: Randomly select k data points as the initial cluster centers, and select the initial cluster centers by randomly selecting data points;

[0056] Step 2: Calculate the distance between each data point and all cluster centers and classify it into the cluster with the closest distance, using Euclidean distance as the distance metric;

[0057] Step 3: For each cluster, calculate the average value of all its data points and use it as the new cluster center;

[0058] Step 4: Repeat steps 2 and 3. You can set a convergence threshold and stop the iteration when the cluster center no longer changes or the change of the cluster center is less than the threshold.

[0059] Step 205: Perform wavelet transform on the different types of annual load fluctuation curves to obtain second load characteristics of the different types of annual load fluctuation curves;

[0060] Specifically, according to the various load fluctuation curves obtained, the characteristics of different types of loads in the load curves are identified by performing wavelet transform on the load curves. Wavelet transform is more suitable for analyzing load curves with localized characteristics, and can provide time and frequency information at the same time to decompose short-term load fluctuations.

[0061] Step 206: determine a target load type of the substation based on the first load characteristic and the second load characteristic; the target load type is a plurality of load types;

[0062] Specifically, after the cluster analysis, the short-term load fluctuations of the load curve of each substation are obtained, which are compared with the typical characteristics of the extracted tea-making load, baking load, and tourism load to determine the main load type of the substation, extract the load curve of the corresponding time period, and form a typical daily load curve for each type of substation.

[0063] Step 207: Obtain the target load fluctuation curve corresponding to each target load type from the annual load fluctuation curves at different times;

[0064] Step 208, obtain the occurrence period of each target load fluctuation curve within the year, and analyze the distribution pattern of the target load fluctuation curve in each month to determine the monthly load fluctuation curve and scenario of the substation; the load fluctuation curves in different months and different scenarios constitute the load curves of different types of loads in the substation.

[0065] Specifically, according to the extraction of the typical daily load curve of the substation, a group of typical load curves of each substation is obtained, the time period of occurrence of each typical load curve in the year is identified, the distribution pattern of these curves in each month is analyzed, and the typical load curve combination and the number of scenarios m of each substation per month are determined. By integrating the data of all substations, the typical load curve of the entire distribution network is formed.

[0066] In a specific embodiment, the voltage regulation device regulation cost is obtained using the following formula:

[0067]

[0068] in, regulating costs for said voltage regulating device, The operating cost of discrete reactive power regulation equipment, To reduce the operating cost of equipment for continuous reactive power regulation, is the tap position of the on-load tap-changing transformer at time t, is the reactive power generated or absorbed by the energy storage at node i at time t, is the reactive power generated or absorbed by the photovoltaic inverter at node j at time t, is the reactive power generated or absorbed by the reactive power compensation device at node k at time t, Ⅱ(·) is the indicator function, and the output is 1 when it is not zero, ρ is the weight coefficient, and T is the specified operating time.

[0069] Specifically, when the converters of distributed photovoltaic and energy storage participate in reactive voltage regulation, the coordination between traditional voltage regulation means and flexible voltage regulation means needs to be considered during operation. The converter can continuously adjust the reactive power it emits or absorbs, while the traditional voltage regulation equipment, the on-load tap-changing transformer tap, belongs to a voltage regulation device based on discrete rule control. The two need to work together, otherwise the low-order voltage regulation equipment may not be able to function, and the continuous regulation equipment reactive power compensation overload may cause harm. Therefore, the voltage regulation equipment regulation is obtained based on the operating cost of the discrete reactive regulation equipment and the operating cost of the continuous reactive regulation equipment, and the voltage regulation equipment regulation is analyzed as a constraint.

[0070] In a specific embodiment, the upper-level planning model is obtained using the following formula:

[0071] f 1 =min(F DES +F SVCc +F L )

[0072] Among them, f 1 is the upper-level planning model, F DES is the investment and operation cost of the energy storage device, F SVCc is the reactive power compensation cost of the reactive power compensation device, F L The operating cost of the distribution network.

[0073] The energy storage device investment F in the upper planning model DES The calculation formula is:

[0074]

[0075] F DT =β DES.P P DES +β DES.E E DES

[0076] Among them, F DT The investment cost of energy storage can be determined according to a certain ratio between the power and capacity of energy storage. is the energy storage operation cost returned by the lower-level planning model, β DES.P is the power cost coefficient, β DES.E is the capacity cost coefficient, P DES is the rated power of the energy storage device, E DES is the rated capacity of the energy storage device, Ω DES For energy storage collection;

[0077] The investment cost F of the reactive power compensation device SVC in the upper planning model SVCc It is approximately quadratic in relationship to the operating range, and its quantitative relationship is:

[0078]

[0079] Among them, Q i,SVC is the capacity of the reactive power compensation device SVC configured at node i, N b is the number of all nodes in the distribution network, σ c , θ, χ, δ are the coefficients obtained after optimization;

[0080] The system operation cost F in the upper planning model L The calculation formula is:

[0081]

[0082] Among them, f price is the average electricity price (yuan / kWh), is the network loss (kWh) of the optimal operation scheme under the g-th typical scenario, is the network loss value returned by the lower-level planning model, and hg is the duration of the g-th typical scene.

[0083] Specifically, the constraints of the upper-level planning model include: energy storage element installation constraints, reactive power compensation device SVC single unit capacity constraints, and reactive power compensation device SVC unit quantity constraints.

[0084] The calculation formula for the energy storage element installation constraint is:

[0085]

[0086] in, is the maximum number of energy storage components allowed to be installed, The number of energy storage elements installed;

[0087] The calculation formula for the capacity constraint of a single reactive power compensation device SVC is:

[0088]

[0089] in, is the capacity and location of the reactive power compensator in the decision variables, M SVC The upper limit of the access capacity of the reactive power compensator;

[0090] The calculation formula for the number of SVC units of reactive power compensation device is:

[0091]

[0092] in, The maximum number of SVC installations allowed in a single scenario.

[0093] Specifically, the upper-level planning model aims to minimize network losses, investment and operation costs of energy storage devices and reactive power compensation devices, as well as the cost of power purchase from the distribution network. The optimal location and capacity of the energy storage system and reactive power compensation device are determined, and the planning results of the energy storage and reactive power compensation device equipment are passed to the lower-level planning model.

[0094] In a specific embodiment, the lower-level planning model is obtained using the following formula:

[0095]

[0096] Among them, f 2 is the lower-level planning model, F loss is the network loss cost, F B is the electricity purchase cost of the distribution network, Punishment for abandoning the light, is the operating cost of the PV inverter, is the operating cost of the energy storage device, is the equipment adjustment cost, Fcarbon The cost of carbon emissions.

[0097] Specifically, the lower-level planning model takes into account the active-reactive regulation effects of photovoltaic and energy storage inverters, reactive compensation devices SVC, and on-load tap-changing transformers OLTC based on the site selection and sizing results of the energy storage and reactive compensation device SVC of the upper-level model, and takes the optimization of the economy, voltage quality, and low-carbon level of distribution network operation as the goal to obtain the active and reactive output of energy storage and photovoltaics.

[0098] The distribution network loss cost F in the lower-level planning model loss The calculation formula is:

[0099] F loss =f price P loss

[0100]

[0101] Among them, P loss is the network loss during operation, r ij is the branch resistance between nodes i and j, I ij is the effective value of the current in the corresponding branch at time t, Ω Line is a set of lines, T is the specified operating time, and a typical daily load curve is operated;

[0102] The power purchase cost F of the distribution network in the lower planning model B The calculation formula is:

[0103]

[0104] Among them, f price is the average electricity price, is the electricity purchase amount at time t;

[0105] In order to achieve stable voltage operation and balanced regulation of active and reactive power in the distribution network, the system includes a variety of regulation devices. According to their characteristics, these devices can be divided into active and reactive regulation devices, as well as discrete and continuous regulation devices, and they have different priorities and constraints in operation;

[0106] The on-load tap-changing transformer OLTC is a discrete regulating device that regulates reactive voltage. Its main function is to maintain voltage stability by adjusting the tap position. Since each tap adjustment will cause wear and tear on the equipment, the number of adjustments of the on-load tap-changing transformer is limited;

[0107] Energy storage converters can participate in the regulation of active and reactive power. They can balance the load by adjusting the active power output, and maintain voltage stability by adjusting the reactive power. Energy storage devices are usually continuous regulation devices, that is, their reactive output can be adjusted at any time within a certain range.

[0108] In addition to outputting active power, photovoltaic inverters can also assist in voltage control by adjusting reactive power. The reactive power regulation of photovoltaics is continuous, and the inverter can respond quickly to voltage fluctuations. Since the active power output of photovoltaics itself is affected by light conditions, when the active power is insufficient, the reactive power regulation ability of the inverter may be limited;

[0109] Static VAR compensator (SVC) is a typical continuous reactive power regulation device that can quickly adjust reactive power to maintain system voltage stability. It has a short response time and frequent actions, and is suitable for scenarios that require rapid response to voltage changes.

[0110] The cost of abandoned light in the lower-level planning model The calculation formula is:

[0111]

[0112] in, The penalty cost for abandoning the light unit, is the amount of abandoned light at time t;

[0113] When the PV inverter is performing reactive voltage regulation, its reactive power output causes significant thermal stress on the internal components. At the same time, greater power output will cause greater power loss in the inverter, further increasing operating costs and efficiency losses.

[0114] The photovoltaic power generation operation cost in the lower planning model The calculation formula is:

[0115]

[0116] Among them, f PV is the unit power operation cost of distributed photovoltaic power generation, is the active power of distributed photovoltaic power generation at time t, is the reactive power of distributed photovoltaic power generation at time t;

[0117] The energy storage operation cost in the lower planning model The calculation formula is:

[0118]

[0119] Among them, f DES is the unit power operating cost of energy storage, is the charging power of the energy storage system at time t, is the discharge power of the energy storage system at time t;

[0120] The inverters of distributed photovoltaic and energy storage can continuously adjust the reactive power they emit or absorb, while the traditional voltage regulation equipment, on-load voltage regulating transformer tap, belongs to the voltage regulation equipment based on discrete rule control. The two need to work together, otherwise the low-order voltage regulation equipment may not be able to play a role, and the reactive power compensation of the continuous regulation equipment may be overloaded.

[0121] The equipment adjustment cost in the lower-level planning model The calculation formula is:

[0122]

[0123] in, is the OLTC tap position at time t, is the reactive power generated or absorbed by the energy storage at node i at time t, is the reactive power generated or absorbed by the photovoltaic inverter at node j at time t, is the reactive power generated or absorbed by the reactive power compensation device SVC at node k at time t, Ⅱ(·) is the indicator function, and ρ is the weight coefficient;

[0124] The calculation formula of carbon emission cost in the lower-level planning model is:

[0125] F carbon =f carbon E carbon

[0126]

[0127] Among them, f carbon is the penalty cost per unit of carbon emission, E carbon is carbon emissions, γ PV is the carbon emission intensity per unit of PV power generation, which can be positive or negative. gride The carbon emission intensity of electricity purchased from the upper-level main grid unit can be positive or negative;

[0128] Preferably, the constraints of the lower-level planning model include: energy storage operation constraints, on-load tap-changing transformer OLTC operation constraints, energy storage active and reactive output constraints, power flow constraints and distribution network operation safety constraints;

[0129] The calculation formula for the energy storage element installation constraint is:

[0130]

[0131] in, is the maximum charge and discharge power of the DES installed at node i, are the SOC values ​​of the DES installed at node i in period t and period t-1, are the upper and lower limits of the SOC of the DES installed at node i, are the charging and discharging efficiencies of the DES installed at node i, respectively;

[0132] The calculation formula for the OLTC operation constraint of the on-load tap-changing transformer is:

[0133]

[0134] Among them, U h,t , U l,t are the high and low voltage side voltages of the on-load tap-changing transformer at time t, K B is the standard ratio of the on-load tap-changing transformer, is the tap position of the on-load tap-changing transformer at time t, ΔK is the transformation ratio step length of the on-load tap-changing transformer, The maximum gear ratio, The maximum number of times the on-load tap-changing transformer can be adjusted in a single day;

[0135] The reactive power compensation device SVC reactive power compensation capacity constraint;

[0136]

[0137] in, is the reactive power compensation capacity of the nth SVC at time t, and are the maximum and minimum values ​​of the SVC reactive compensation capacity respectively;

[0138] The energy storage active and reactive output constraints are:

[0139]

[0140] in, are the active power and reactive power generated by node i when it is connected to the energy storage at time t;

[0141] The maximum available capacity of energy storage connected to the i-node;

[0142] The active power balance constraint calculation formula in the power flow constraint is:

[0143]

[0144] in, is the active power generated by the upper grid generator and distributed photovoltaic at node i at time t, is the active power generated by the energy storage device at node i at time t. When the energy storage device absorbs active power, is negative, is the active power consumed by the load at node i at time t.

[0145] The reactive power balance constraint calculation formula in the power flow constraint is:

[0146]

[0147] in, is the reactive power generated by the upper grid generator and distributed photovoltaic at node i at time t, is the reactive power generated by the SVC at node i at time t, is the reactive power consumed by the load at node i at time t, The reactive power generated by the energy storage device at node i at time t is negative when the energy storage device absorbs reactive power;

[0148] The distribution network operation constraints include voltage safety constraints and current safety constraints.

[0149] U min ≤U i,t ≤U max

[0150] I min ≤I ij,t ≤I max

[0151] Among them, U max and U min are the maximum and minimum allowable values ​​of the node voltage, I max and I min The maximum and minimum values ​​allowed for the line current.

[0152] In the specific embodiments, see Figure 4 , the inputting of the load curves of the different types of loads into the two-layer programming model to obtain the optimal installation position and optimal capacity of the reactive power compensation device includes:

[0153] Step 301: Input the load curves of the different types of loads into the two-layer programming model to obtain different installation locations of the reactive power compensation device and the capacity corresponding to each installation location;

[0154] Step 302: Optimize different installation positions of the reactive compensation device and the capacity corresponding to each installation position with minimization of the equipment operation cost of the reactive compensation device as the objective function to obtain the optimal installation position and optimal capacity of the reactive compensation device.

[0155] Specifically, the installation location and capacity of the reactive power compensation device SVC in different scenarios are obtained through the two-layer planning model:

[0156]

[0157] in, represents the capacity and installation location of the kth SVC obtained by optimizing the mth scenario, represents the optimal capacity, represents the installation location, the subscript m represents the scenario, and the superscript k represents the kth reactive power compensation device installed in scenario m;

[0158] The optimal installation position of the reactive power compensation device SVC in each scenario is consistent with the optimization results in each scenario. The configuration principle is:

[0159]

[0160] The operating cost of the reactive power compensation device includes not only the energy consumption cost caused by the equipment adjustment, but also the cost of moving the equipment between various substations. The objective function of the optimal allocation of the reactive power compensation device SVC is:

[0161]

[0162] Among them, F run is the equipment operating cost of the reactive power compensation device SVC, F oper is the energy consumption cost per unit capacity of the equipment. is the access capacity of the i-th reactive power compensation device at time t, D i represents the moving distance of the i-th device, F move is the moving cost per unit moving distance, N represents the total number of reactive power compensation devices;

[0163] The calculation formula for the capacity constraint of a single reactive power compensation device SVC is:

[0164]

[0165] in, is the access capacity of the i-th reactive power compensation device at time t, Q RSVC The total capacity of reactive power compensation devices connected to the substation to compensate reactive power, and N represents the total number of reactive power compensation devices;

[0166] The calculation formula for limiting the number of SVC enabled reactive power compensation devices is:

[0167]

[0168] Among them, x i It is a binary variable, indicating whether the i-th device is enabled. 0 means the device is not enabled, and 1 means the device is enabled. The upper limit of the number of reactive power compensation devices that can be enabled in a single scenario.

[0169] In a specific embodiment, the objective function is obtained using the following formula:

[0170]

[0171] Among them, F run is the equipment operating cost of the reactive power compensation device, F oper is the regulation energy consumption cost per unit capacity of the reactive power compensation device, is the access capacity of the i-th reactive power compensation device at time t, D i represents the moving distance of the i-th reactive power compensation device, F move is the moving cost per unit moving distance of the reactive power compensation device, N represents the total number of reactive power compensation devices, It is a binary variable, indicating whether the i-th reactive power compensation device is enabled. 0 indicates that the reactive power compensation device is not enabled, and 1 indicates that the reactive power compensation device is enabled.

[0172] Among them, the parameters used in the simulation model are shown in Table 1.

[0173] parameter Numeric Average electricity purchase price / [yuan·(kWh)-1] 0.715 ESS unit capacity investment cost / [yuan·(kWh)-1] 1350 ESS unit power investment cost / [yuan·(kW)-1] 675 discount rate 0.08 Unit penalty cost for abandoned solar power / [yuan·(kWh)-1] 0.8 PV unit operating cost / [yuan·(kWh)-1] 0.35 ESS unit operating cost / [yuan·(kWh)-1] 0.08 SVC unit operating cost / [yuan·(kVar)-1] 0.1 OLTC unit adjustment cost / [yuan / time] 0.8 Carbon emission unit penalty cost / [yuan·(t)-1] 0.217 Carbon emission intensity per unit of PV power generation / [kg·(kWh)-1] 0.02 Carbon emission intensity of electricity generation of the upper-level power purchasing unit / [kg·(kWh)1] 0.4

[0174] Table 1 Simulation model parameters

[0175] In order to determine the advantages and disadvantages of the two-layer planning method of energy storage and mobile reactive compensation device for distribution network considering large range difference load, the traditional SVC fixed mode, and the photovoltaic only participating in active power regulation and participating in active and reactive comprehensive regulation to solve the voltage problem of the new distribution network, the following three examples of different flexible resources participating in active and reactive power planning are proposed. For each example, typical node load curves of three different time periods are input to obtain the planning results of energy storage and RSVC.

[0176] Plan 1: Photovoltaic only generates active power and does not participate in voltage regulation;

[0177] Plan 2: PV participates in the comprehensive regulation of active and reactive power, but the mobility of SVC is not considered;

[0178] Plan three: Photovoltaic power participates in the comprehensive regulation of active and reactive power, and is equipped with a mobile SVC.

[0179] In this embodiment, the two-layer planning method of distribution network energy storage-mobile reactive power compensation device considering large-range load difference is provided, which is aimed at the 10kV system problem when the temporal and spatial distribution of load in the distribution area is uneven. Figure 5The method includes: first, generating differential load curves of various types of loads; then, designing various voltage regulation equipment adjustment sequence constraints (voltage regulation equipment adjustment costs) taking into account the coordination of traditional voltage regulation means and flexible voltage regulation means; and then, constructing a two-level planning model taking into account the multi-quadrant operation capability of the converter, in which the multi-quadrant operation diagram of distributed photovoltaic and energy storage is as follows: Figure 6 As shown. The upper planning model aims to minimize the investment and operation cost of energy storage devices, the reactive power compensation cost of SVC, and the system operation cost, and determines the optimal location and capacity of the energy storage system and SVC. The lower optimization model is the distribution network operation under multiple typical load scenarios. The goal is to minimize the distribution network operation cost under typical scenarios while satisfying the distribution network operation constraints (including voltage deviation). The operation costs include: network loss, distribution network power purchase cost, photovoltaic and energy storage operation cost, voltage regulation equipment adjustment cost, and carbon emission cost. The lower model comprehensively considers the operation costs of various active and reactive regulation equipment in the distribution network, takes the minimum comprehensive cost under typical scenarios as the objective function, obtains the daily scheduling results of typical scenarios, and passes them to the upper layer; the upper model uses the particle swarm algorithm to obtain the fitness based on the planning results of energy storage and SVC equipment and the comprehensive cost under typical scenarios, and updates and iterates successively until the optimal planning result is solved; finally, according to the optimal planning result, the total capacity and optimal allocation of the mobile reactive power compensation device RSVC are determined.

[0180] This application proposes a two-layer planning model of distribution network energy storage-mobile reactive compensation device, which comprehensively considers energy storage, mobile reactive compensation device, inverter reactive regulation capability and traditional reactive compensation equipment. Through this model, not only can the voltage over-limit problem of 10kV substations caused by large-scale distributed photovoltaic access and seasonal load distribution problems be solved, but also the photovoltaic abandonment rate is reduced, and the coordinated operation of the 10kV system flexible regulation equipment is realized. In particular, the mobile reactive compensation equipment can effectively alleviate the voltage over-limit problem caused by seasonal loads. It provides a comprehensive and flexible new idea for the planning and operation of the distribution network, which helps to improve the renewable energy absorption capacity, optimize the performance of the distribution network, and promote the development of the distribution network in a sustainable direction.

[0181] In the specific embodiments, see Figure 7, is a structural diagram of a planning system for a reactive power compensation device of a distribution network in the second embodiment of the present application, characterized in that the system includes: a load curve acquisition module 601, an adjustment cost acquisition module 602, a double-layer planning model construction module 603 and an installation position and capacity output module 604; the load curve acquisition module 601 is used to obtain load curves of different types of loads in the substation; the adjustment cost acquisition module 602 is used to obtain the adjustment cost of the voltage regulation device based on discrete and continuous voltage regulation equipment; the double-layer planning model construction module 603 is used to construct a double-layer planning model taking into account the multi-quadrant operation capability of the converter; the double-layer planning model includes an upper-layer planning model and a lower-layer planning model. The upper-level planning model aims to minimize the investment and operation cost of the energy storage device, the reactive compensation cost of the reactive compensation device and the operation cost of the distribution network, and determines the installation location and capacity of the energy storage system and the reactive compensation device; the lower-level planning model aims to minimize the operation cost of the distribution network under the operation constraints of the distribution network; the operation cost of the distribution network includes: network loss, the cost of purchasing electricity from the distribution network, the operation cost of the photovoltaic system and the energy storage system, the regulation cost of the voltage regulation equipment and the carbon emission cost; the installation location and capacity output module 604 is used to input the load curves of the different types of loads into the double-layer planning model to obtain the optimal installation location and optimal capacity of the reactive compensation device.

[0182] In a specific embodiment, the third embodiment of the present application provides a planning device for a reactive compensation device of a distribution network, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method as described in any one of the first embodiments of the present application.

[0183] In a specific embodiment, the fourth embodiment of the present application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method as described in any one of the first embodiments of the present application.

[0184] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

[0185] The above description is only a preferred embodiment of the present invention and does not limit the present invention in other forms. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for planning a reactive power compensation device of a distribution network, characterized in that: The method comprises: Obtain load curves of different types of loads in the substation; Obtaining the voltage regulation equipment regulation cost based on discrete and continuous voltage regulation equipment regulation; Construct a two-level planning model that takes into account the multi-quadrant operation capability of the converter; the two-level planning model includes an upper-level planning model and a lower-level planning model; the upper-level planning model aims to minimize the investment and operation cost of the energy storage device, the reactive compensation cost of the reactive compensation device, and the operation cost of the distribution network, and determines the installation location and capacity of the energy storage system and the reactive compensation device; the lower-level planning model aims to minimize the operation cost of the distribution network while satisfying the operation constraints of the distribution network; the operation cost of the distribution network includes: network loss, the cost of purchasing electricity from the distribution network, the operation cost of the photovoltaic system and the energy storage system, the regulation cost of the voltage regulation equipment, and the carbon emission cost; The load curves of the different types of loads are input into the double-layer programming model to obtain the optimal installation position and optimal capacity of the reactive power compensation device.

2. The method for planning a reactive power compensation device for a distribution network according to claim 1, characterized in that: The step of obtaining load curves of different types of loads in the substation includes: Classify the load types of the substation according to the power consumption characteristics of the substation and obtain the classification results of different load types; Performing feature analysis on the classification results of the different load types to obtain a first load feature of each load type; Obtain the annual load fluctuation curve of the substation at different times; Using a clustering algorithm to classify the annual load fluctuation curves at different times, to obtain different types of annual load fluctuation curves; Performing wavelet transformation on the different types of annual load fluctuation curves to obtain second load characteristics of the different types of annual load fluctuation curves; Determine a target load type of the substation based on the first load characteristic and the second load characteristic; the target load type is a plurality of load types; Obtaining a target load fluctuation curve corresponding to each target load type from the annual load fluctuation curves at different times; Obtain the occurrence period of each target load fluctuation curve within the year, analyze the distribution pattern of the target load fluctuation curve in each month, and determine the monthly load fluctuation curve and scenario of the substation; the load fluctuation curves in different months and different scenarios constitute the load curves of different types of loads in the substation.

3. The planning method of the reactive power compensation device of the distribution network according to claim 1, characterized in that: The voltage regulation cost of the voltage regulation device is obtained by the following formula: in, regulating costs for said voltage regulating device, The operating cost of discrete reactive power regulation equipment, For continuous reactive power regulation equipment operating costs, is the tap position of the on-load tap-changing transformer at time t, is the reactive power generated or absorbed by the energy storage at node i at time t, is the reactive power generated or absorbed by the photovoltaic inverter at node j at time t, is the reactive power generated or absorbed by the reactive power compensation device at node k at time t, Ⅱ(·) is the indicator function, and the output is 1 when it is not zero, ρ is the weight coefficient, and T is the specified operating time.

4. The method for planning a reactive power compensation device for a distribution network according to claim 1, characterized in that: The upper-level planning model is obtained using the following formula: f1=min(F DES +F SVCc +F L ) Among them, f1 is the upper-level planning model, F DES is the investment and operation cost of the energy storage device, F SVCc is the reactive power compensation cost of the reactive power compensation device, F L The operating cost of the distribution network.

5. The planning method of the reactive power compensation device of the distribution network according to claim 1, characterized in that: The lower-level planning model is obtained using the following formula: Among them, f2 is the lower-level planning model, F loss is the network loss cost, F B is the electricity purchase cost of the distribution network, Punishment for abandoning the light, is the operating cost of the PV inverter, is the operating cost of the energy storage device, is the equipment adjustment cost, F carbon The cost of carbon emissions.

6. The planning method of the reactive power compensation device of the distribution network according to claim 1, characterized in that: Inputting the load curves of the different types of loads into the two-level programming model to obtain the optimal installation position and optimal capacity of the reactive power compensation device includes: Inputting the load curves of the different types of loads into the two-layer programming model to obtain different installation locations of the reactive power compensation device and the capacity corresponding to each installation location; Taking minimization of the equipment operation cost of the reactive compensation device as the objective function, different installation positions of the reactive compensation device and the capacity corresponding to each installation position are optimized to obtain the optimal installation position and optimal capacity of the reactive compensation device.

7. The method for planning a reactive power compensation device of a distribution network according to claim 6, characterized in that: The objective function is obtained using the following formula: Among them, F run is the equipment operating cost of the reactive power compensation device, F oper is the regulation energy consumption cost per unit capacity of the reactive power compensation device, is the access capacity of the i-th reactive power compensation device at time t, D i represents the moving distance of the i-th reactive power compensation device, F move is the moving cost per unit moving distance of the reactive power compensation device, N represents the total number of reactive power compensation devices, It is a binary variable, indicating whether the i-th reactive power compensation device is enabled. 0 indicates that the reactive power compensation device is not enabled, and 1 indicates that the reactive power compensation device is enabled.

8. A planning system for a reactive power compensation device of a distribution network, characterized in that: The system comprises: a load curve acquisition module, an adjustment cost acquisition module, a double-layer planning model construction module and an installation location and capacity output module; The load curve acquisition module is used to acquire load curves of different types of loads in the substation; The regulation cost acquisition module is used to acquire the regulation cost of the voltage regulation device based on the regulation of discrete and continuous voltage regulation devices; The two-layer planning model construction module is used to construct a two-layer planning model that takes into account the multi-quadrant operation capability of the converter; the two-layer planning model includes an upper-layer planning model and a lower-layer planning model; the upper-layer planning model aims to minimize the investment and operation cost of the energy storage device, the reactive compensation cost of the reactive compensation device and the operation cost of the distribution network, and determines the installation location and capacity of the energy storage system and the reactive compensation device; the lower-layer planning model aims to minimize the operation cost of the distribution network under the constraints of the distribution network operation; the operation cost of the distribution network includes: network loss, the cost of purchasing electricity from the distribution network, the operation cost of the photovoltaic system and the energy storage system, the regulation cost of the voltage regulation equipment and the carbon emission cost; The installation position and capacity output module is used to input the load curves of the different types of loads into the double-layer programming model to obtain the optimal installation position and optimal capacity of the reactive power compensation device.

9. A planning device for a reactive power compensation device of a distribution network, comprising a memory and a processor, characterized in that: The memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 7.

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