Partition autonomous control method for local autonomous power grid based on power supply and storage capacity of power distribution network

Abstract

The invention belongs to the technical field of local area autonomous power grid control, and particularly relates to a local area autonomous power grid partition autonomous control method based on the power supply and storage capacity of a power distribution network. Comprising the following steps: S1, setting a global and autonomous region two-stage control center in an active power distribution network range on the basis of a layered and partitioned coordination control mode; s2, dividing the active power distribution network into a plurality of autonomous areas according to the network topology structure of the active power distribution network and the active and reactive power regulation characteristics of each controllable device; s3, establishing a controllable unit model; s4, calculating a power supply and storage capacity index; s5, performing global optimization and regional control; according to the method, the advantages of the regional autonomous power grid and the partition control strategy are combined, the power supply reliability, economical efficiency and flexibility of the power grid are improved, the operation efficiency and safety of the power grid are improved, and a solid foundation is laid for future energy transformation and sustainable development.

Description

Technical Field

[0001] The present invention belongs to the technical field of local autonomous power grid control, and in particular relates to a local autonomous power grid partition autonomous control method based on the power supply and storage capacity of a distribution network. Background Art

[0002] With the continuous adjustment of the global energy structure and the rapid development of power technology, the local autonomous power grid partition autonomous control mode, as a new power management mode, is gradually showing its importance and advantages. This section will elaborate on the background technology of the local autonomous power grid partition autonomous control mode from the aspects of energy Internet evolution, the third industrial revolution, technology and model innovation, distribution network autonomy concept, hierarchical control method, coordinated control strategy and reactive voltage autonomous control.

[0003] 1. Evolution of Energy Internet

[0004] The introduction of the Energy Internet has broken the supply and demand boundaries between traditional energy industries and promoted the interconnection, interoperability and complementarity of primary and secondary energy types such as coal, oil, natural gas, heat and electricity. On the user side, the Energy Internet supports large-scale access to various new energy sources and distributed energy sources, and realizes plug-and-play of electrical equipment. Through local autonomous consumption and wide-area peer-to-peer interconnection, the Energy Internet realizes the optimal regulation and efficient utilization of energy flows, and builds an open and flexible industry and business model.

[0005] The core features of the energy internet include taking the power system as the center, the smart grid as the backbone, the Internet, big data, cloud computing and other cutting-edge information and communication technologies as the link, and comprehensively using advanced power electronics technology and intelligent management technology to form a next-generation energy system with a high degree of integration of energy and information. This system is flat, platform-based, commercial and user-serviceable, providing broad space for the development of local autonomous power grids.

[0006] 2. The Third Industrial Revolution

[0007] The third industrial revolution, represented by informatization, the Internet, and new energy, has pushed human society into a new stage of development. In this context, local autonomous power grids have become an important means to achieve energy transformation and energy democratization. Through distributed energy production and storage, each building can be turned into a micro power plant to achieve energy localization and self-sufficiency. This model not only improves energy utilization efficiency, but also promotes energy democratization, fundamentally reshaping interpersonal relationships and social structures.

[0008] 3.Technology and model innovation

[0009] The local autonomous power grid has achieved many innovations in technology and model. First, in terms of technology, the local autonomous power grid adopts advanced power electronics technology and intelligent management technology to achieve zoning control and scientific integration of various sources and loads. Secondly, in terms of model, the local autonomous power grid achieves flexible control and efficient processing of power grid operation through zoning autonomy. This innovation not only improves the power supply reliability of the power grid, but also reduces operation and maintenance costs, and improves economic and social benefits.

[0010] 4. Distribution network autonomy concept

[0011] The concept of distribution network autonomy is one of the core ideas of the local autonomous power grid partition autonomous control mode. By introducing the concept of active distribution network, using hierarchical target guidance and autonomous units to achieve autonomous control, it can replace manual work in power system operation control. This concept enables the distribution network to respond quickly to various disturbances and load changes, and achieve self-adjustment and optimization. Summary of the invention

[0012] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a method for controlling the partition of a local autonomous power grid based on the power supply and storage capacity of a distribution network, combining the advantages of the regional autonomous power grid and the partition control strategy to improve the power supply reliability, economy and flexibility of the power grid.

[0013] The object of the present invention is achieved in this way: a local autonomous power grid partition autonomous control method based on the power supply and storage capacity of the distribution network comprises the following steps:

[0014] S1. Based on the hierarchical and zoned coordinated control mode, two levels of control centers, global and autonomous regional, are set up within the scope of the active distribution network;

[0015] S2. Divide the active distribution network into several autonomous areas according to the network topology of the active distribution network and the active and reactive regulation characteristics of each controllable device;

[0016] S3, establish a controllable unit model;

[0017] S4. Calculate the power supply and storage capacity index;

[0018] S5. Perform global optimization and regional control.

[0019] Furthermore, the step S1 is based on the hierarchical and partitioned coordinated control mode, and two levels of control centers, namely, global and autonomous regional control centers, are set within the active distribution network, including:

[0020] (1) Regional Control Center

[0021] The regional control center is located inside each autonomous region to monitor the power and voltage conditions of each line and node in the region and the operating status of each controllable unit. At the beginning of the global optimization cycle, the regional control center calculates the range of power supplied to or absorbed from the external power grid by the region as a whole within the tolerable voltage range based on the current voltage operation status and the output level of each controllable unit in the region, taking into account the changes and impacts in the future. This is used as the power supply and storage capacity indicator that the region can achieve during this optimization cycle, and the indicator is uploaded to the global control center. Subsequently, after receiving the control requirements issued by the global control center, the regional control center performs optimization calculations to obtain the regional optimal solution that meets the regional export voltage and power constraints, and sends the control requirements of each controllable unit in the region to each device. The regional control center is the "brain" of the entire autonomous region, and is also the "messenger" between the region and the global, responsible for coordinating the operating actions of each controllable unit in the region, and completing the tasks of uploading capacity indicators and issuing control instructions.

[0022] (2) Global Control Center

[0023] The global control center is located above the autonomous regional control center. It is responsible for coordinating the autonomous regions within the active distribution network area and the lines, nodes and operating equipment independent of the autonomous regions. Through the feedback of measurement information, it completes the global optimization calculation with the goal of the highest global power supply reliability or economic optimization, and sends the goal to each subordinate region or controllable unit. The global optimization cycle is carried out, and a global optimization calculation is performed once in each optimization cycle. Since the power storage capacity index reported by the region takes into account the voltage fluctuation range after power adjustment, the results of the global optimization calculation performed within this constraint are effective and feasible.

[0024] Furthermore, the step S2 divides the active distribution network into several autonomous areas according to the network topology of the active distribution network and the active and reactive regulation characteristics of each controllable device, including:

[0025] According to the network topology of the active distribution network and the active and reactive power regulation characteristics of each controllable device, the active distribution network is divided into several autonomous areas. The autonomous areas can be divided into active autonomous areas and reactive autonomous areas. The division rules are as follows:

[0026] (1) In terms of topology, the autonomous area is located between two section switches on the feeder or between the section switch and the end of the line;

[0027] (2) In terms of power characteristics, each active autonomous area should include all controllable active power sources or active loads in the area described in (1) (at least one, otherwise it cannot be regarded as an autonomous area), and does not include adjustable reactive equipment or the equipment has weak reactive power, and the impact of its reactive power change on the two processes of participating in the calculation of the supply and storage capacity of the area and the optimization control within the area can be ignored; each reactive autonomous area should include all adjustable reactive power sources in the area described in (1) (at least one, otherwise it cannot be regarded as an autonomous area), generally such as the end of the line and other reactive concentrated compensation areas; in addition, power sources or controllable units with high active and reactive coupling and rapid power changes, such as distributed power grid connection points with large-capacity reactive compensation, will no longer be included in the autonomous area, but will be directly managed and controlled by the active distribution network control center.

[0028] Furthermore, the step S3 of establishing the controllable unit model includes:

[0029] (1) Distributed power generation constraints

[0030] Common distributed power sources connected to the active distribution network are divided into two categories. One is intermittent energy such as photovoltaic power generation and wind turbines, whose power is determined by rated power and meteorological conditions such as light, temperature, wind force and wind direction. Although some intermittent distributed power sources can adjust the output power by changing the operating point, it is generally believed that they operate at the maximum power point determined by the rated power and meteorological conditions; the other type of distributed power source, such as micro gas turbines and internal combustion engines, has an output power between the rated power and the minimum normal operating power, and can be continuously adjusted and controlled within this range; for the above two types of distributed power sources, their power constraints are described as:

[0031]

[0032] Where: E unc is the set of power uncontrollable DGs, P i is the actual power of the i-th power uncontrollable DG, is the maximum power operating point of the i-th power uncontrollable DG determined by the rated power and meteorological conditions; E con is the set of power controllable DGs, P j is the actual power of the jth power-controllable DG, and are the minimum normal operating power and rated power of the jth power-controllable DG respectively;

[0033] (2) Energy storage system power constraints

[0034] The energy storage system is in the charging and discharging states respectively, and power can flow in both directions; its charging and discharging power is constrained by the rated power of the energy storage system, and is also related to the current battery power level (SOC), and its SOC level is determined by the charging and discharging power and charging and discharging time;

[0035] The SOC change of the energy storage system is:

[0036]

[0037] Where: △Soc represents the SOC change of the energy storage system from T to T+△T; μ represents the efficiency of the energy storage system during the charging process, η represents the efficiency of the energy storage system during the discharging process; Pc represents the power of the energy storage system during the charging process, Pd represents the power of the energy storage system during the discharging process; ER represents the rated capacity of the energy storage system;

[0038] Considering that overcharging and over-discharging will cause irreversible damage to the life of the energy storage system, its SOC level should also meet the following constraints:

[0039]

[0040] In the formula, Soc represents the current SOC level of the energy storage system. and They are the lower and upper limits of the SOC level for the normal operation of the energy storage system to avoid over-discharge and over-charge, respectively;

[0041] The charging and discharging power of the energy storage system is shown in formula (4):

[0042]

[0043] Where: and are the rated charging and discharging power of the energy storage system respectively; and are the maximum charging and discharging powers of the energy storage system calculated after considering the rated power constraint and the SOC level constraint;

[0044] (3) Reactive power constraints

[0045] Reactive power sources in active distribution networks can be divided into two categories according to their regulation characteristics: continuous reactive power sources and discrete reactive power sources;

[0046] The reactive power of the continuous reactive power source must meet the rated power constraint, as shown in formula (5):

[0047]

[0048] Where: F ctn represents the collection of continuous reactive power sources, Q irepresents the reactive power of the i-th continuous reactive power source, represents the rated capacity of the i-th continuous reactive power source;

[0049] The number of capacitor groups switched each time is one group, and the time interval between two operations is one global optimization cycle. That is, if the capacitor group was switched in the last global optimization cycle, the capacitor group cannot be adjusted in the current optimization cycle; if the capacitor group was not switched in the last global optimization cycle, one group of capacitors can be switched in or out in the current optimization cycle. The power constraint of the discrete reactive power source is expressed by formula (6):

[0050]

[0051] Where: F dct represents the collection of discrete reactive power sources, Q j represents the reactive power of the jth discrete reactive power source, It represents the reactive power change of a group of capacitors. w is the switching operation permission signal of the current cycle. If the switching operation can be performed in the current cycle, w is 1, otherwise it is 0.

[0052] Furthermore, the step S4 of calculating the power storage capacity index includes:

[0053] (1) Determine the adjustable voltage range based on the regional threshold voltage

[0054] Since the voltage amplitude of each area outlet may change after the global optimization is performed, the calculation of the supply and storage capacity should take into account the change range of the voltage amplitude. The voltage range is taken as the current voltage ±0.03 (unit value) and does not exceed the safety range, as follows:

[0055]

[0056]

[0057] In the formula, is the upper limit of the regional gateway voltage, is the lower limit of the regional threshold voltage, is the current threshold voltage of the region;

[0058] (2) Calculate the storage capacity based on the upper and lower limits of the regional voltage threshold

[0059] Determine the sensitivity of the controllable active (reactive) power supply in the region to the active (reactive) power at the regional export, and calculate the maximum output power or storage power corresponding to the upper or lower limit of the voltage according to the dynamic sensitivity algorithm, that is, the regional supply and storage capacity.

[0060] a. Calculate the sensitivity of each controllable power source to the output power

[0061] The relationship between node injection current and node voltage is:

[0062] I N =Y N U N (9)

[0063] In the formula, I N is the node injection current column vector, Y N is the node admittance matrix, U N is the node voltage column vector;

[0064] The relationship between branch current and node voltage is:

[0065] I L =Y L A T U N (10)

[0066] In the formula, I L is the branch current column vector, Y L is the branch admittance matrix, A is the node association matrix;

[0067] According to equations (9) and (10), we can get

[0068]

[0069] make

[0070]

[0071] but

[0072] I L =CI N (13)

[0073] For a distribution network area with n nodes and l branches, C is an l×n-order real matrix; the C matrix is ​​only related to the topological structure and network parameters. For a radial distribution network, the increase or decrease of the current injected into a single node causes the branches on the path from the first node to the node to decrease or increase the same amount of current accordingly, while the current of other branches not on the path will not change, so the elements of the C matrix are 0 or -1; the branch k current I k,L It is a linear combination of the current injected into each node;

[0074]

[0075]

[0076] In the formula, is the current in branch k, C k,i is the coefficient of node i in branch k in the C matrix, is the voltage vector at the head end of branch k, is the voltage vector of node i; simplifying formula (15), we can get

[0077]

[0078] Where P k,L and Q k,L is the active power and reactive power at the head end of branch k, C k,i is the kth row and ith column element of the coefficient matrix C, P i,N and Q i,N is the active injection power and reactive injection power of node i, U k,L and are the voltage amplitude and phase angle at the head end of branch k, U i,N and are the voltage amplitude and phase angle of node i respectively;

[0079] Expanding equation (16), we get equation (17) and equation (18) for the real part and imaginary part respectively.

[0080]

[0081]

[0082] According to the above principle, when only the active power of a node is adjusted, its reactive power will not be changed. Therefore, the branch active power and node injected active power in equation (17) are changed to variables, and the reactive power is set to 0, and we get

[0083]

[0084] Similarly, when only the reactive power of a node is adjusted, its active power is not changed. Therefore, the branch reactive power and node injected reactive power in equation (18) are changed into variables, and the reactive power is set to 0, and we get

[0085]

[0086] Therefore, the active sensitivity matrix B(β) between the branch active change and the node injected active change and the reactive sensitivity matrix D(γ) between the branch reactive change and the node injected reactive change can be defined respectively, where the power sensitivity β between the branch k active change and the node i active injection change is k,i Expressed as

[0087]

[0088] Power sensitivity γ of the reactive power change of branch m to the reactive power injection change of node j m,j Expressed as

[0089]

[0090] b. Dynamic sensitivity algorithm to solve regional supply and storage capacity

[0091] For each region, the maximum output power corresponding to the lower limit of the region's outlet voltage is solved through the dynamic sensitivity algorithm. (or ) and maximum absorbed power (or ), and the maximum output power corresponding to the upper limit of the regional outlet voltage (or ) and maximum absorbed power (or ); For each region, the upper and lower limits of its outlet voltage correspond to a power band range, which represents the power storage capacity of the region when the voltage is at the upper or lower limit, and the intersection of the two power bands represents the conservative power storage capacity of the region when the regional voltage is between the upper and lower limits;

[0092] After each power flow calculation, update the sensitivity of each controllable power source to the regional gateway power and arrange them from high to low according to the sensitivity. Increase (or decrease) the power of the controllable power source with the largest sensitivity according to the specified step size, check the constraints, and perform the next iterative calculation if the constraints are met. If the constraints are not met, determine the exact power through dichotomy. The specific steps are as follows:

[0093] ① Check whether the number of adjustable power supplies is 0. If not, execute ②; if it is 0, end;

[0094] ② Calculate the sensitivity of each controllable power supply and arrange the sensitivity from high to low;

[0095] ③Adjust the controllable power supply with the highest sensitivity by one step unit;

[0096] ④ Check whether the power of the power supply exceeds its adjustable capacity, if not, execute ⑤; if yes, adjust its power to the upper limit (or lower limit) of the adjustable capacity, and remove the power supply from the sensitivity sorting table, and execute ⑤;

[0097] ⑤ Flow calculation, verify the constraints of each network. If the constraints are met, execute ①; if the constraints are not met, execute ⑥;

[0098] ⑥ Determine the precise value of the power adjustment amount that satisfies the network constraints by the binary method, and output the current power value.

[0099] Furthermore, the step S5 of performing global optimization and regional control includes:

[0100] (1) Global Optimization Process

[0101] Through the power storage capacity corresponding to the upper and lower limits of the regional outlet voltage reported by each region, each region is equivalent to a power controllable power source to participate in the global coordinated optimization of the active distribution network. The steps are as follows:

[0102] ①Propose the objective function of global optimization;

[0103] ② Propose equality constraints for global optimization;

[0104] ③ The inequality constraints of global optimization and the regional power supply and storage capacity constraints are taken as the union;

[0105] ④ For optimization calculation, the interior point optimization method can be adopted;

[0106] ⑤ Check whether the power and voltage ranges of the regional calculation results conflict. If they do not match, limit the power supply and storage capacity constraints of the conflicting area to the corresponding voltage upper limit power range or voltage lower limit power range, keep other constraints unchanged, and perform new optimization calculations;

[0107] ⑥Distribute the optimization results to each region;

[0108] (2) Regional control process

[0109] Each region uses the optimization calculation results issued by the region as equality constraints, takes the corresponding target as the optimization target, performs optimization calculations, and implements control over the controllable power supply. The steps are as follows:

[0110] Determine the objective function of regional optimization control,

[0111]

[0112] Among them, F is the power generation cost, N G is the number of generating units, P Gi is the power generation cost of the i-th generator set, a i 、b i 、c i is the cost coefficient of the i-th generator set;

[0113] Determine the equality constraints of regional optimization control. The regional power and voltage should be the values ​​issued after global optimization.

[0114]

[0115] Determine the inequality constraints for regional optimization control,

[0116]

[0117] For optimization calculation, the interior point optimization algorithm can be used.

[0118] Beneficial effects of the present invention: The local autonomous power grid partition autonomous control method based on the power storage capacity of the distribution network of the present invention realizes independent control and optimization of the local area by dividing the power grid into multiple autonomous areas, thereby improving the operation efficiency of the entire power grid. The autonomous area has independent control capabilities, which can isolate faults to a certain extent, prevent fault propagation, and improve the safety of the power grid. In the event of a fault, the autonomous area can quickly adjust its internal distributed power sources and loads to form an island operation, provide continuous power supply for critical loads, and thus improve the reliability of the power grid. By optimizing the use of distributed resources within the autonomous area, the operating cost of the power grid is reduced and the economic benefits are improved. The purpose of the local autonomous power grid partition autonomous control mode is to improve the operating efficiency, safety and reliability of the power grid, and optimize resource allocation. In order to achieve these goals, the mode needs to complete tasks such as real-time monitoring and control, fault detection and isolation, load management and optimization, distributed energy access and management, coordination with other autonomous areas, and data collection and analysis. The present invention combines the advantages of regional autonomous power grids and partition control strategies, aiming to improve the power supply reliability, economy and flexibility of the power grid. The local autonomous power grid partition autonomous control mode has shown significant beneficial effects in improving power supply reliability, enhancing power grid flexibility, improving economy, enhancing system stability, and promoting technological innovation and industrial upgrading. These effects not only help improve the operating efficiency and safety of the power grid, but also lay a solid foundation for future energy transformation and sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] In order to more clearly illustrate the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0120] Figure 1 This is a schematic diagram of the coordination relationship between the global and regional areas;

[0121] Figure 2 This is a schematic diagram of the optimized zoning of the active distribution network based on the regional supply and storage capacity indicators.

[0122] Figure 3 It is the block diagram of dynamic sensitivity algorithm;

[0123] Figure 4 This is a binary logic block diagram.

[0124] Figure 5 It is a schematic diagram of the supply and storage capacity corresponding to the upper and lower limits of the regional outlet voltage;

[0125] Figure 6Flowchart of the regional control process for global optimization. DETAILED DESCRIPTION

[0126] The present invention will be further described below in conjunction with the accompanying drawings.

[0127] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0128] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0129] The method for controlling the local autonomous power grid partition based on the power supply and storage capacity of the distribution network of the present invention comprises the following steps:

[0130] S1. Based on the hierarchical and zoned coordinated control mode, two levels of control centers, global and autonomous regional, are set up within the scope of the active distribution network;

[0131] S2. Divide the active distribution network into several autonomous areas according to the network topology of the active distribution network and the active and reactive regulation characteristics of each controllable device;

[0132] S3, establish a controllable unit model;

[0133] S4. Calculate the power supply and storage capacity index;

[0134] S5. Perform global optimization and regional control.

[0135] Furthermore, the step S1 is based on the hierarchical and partitioned coordinated control mode, and two levels of control centers, namely, global and autonomous regional control centers, are set within the active distribution network, including:

[0136] (1) Regional Control Center

[0137] The regional control center is located inside each autonomous region to monitor the power and voltage conditions of each line and node in the region and the operating status of each controllable unit. At the beginning of the global optimization cycle, the regional control center calculates the range of power supplied to or absorbed from the external power grid by the region as a whole within the tolerable voltage range based on the current voltage operation status and the output level of each controllable unit in the region, taking into account the changes and impacts in the future. This is used as the power supply and storage capacity indicator that the region can achieve during this optimization cycle, and the indicator is uploaded to the global control center. Subsequently, after receiving the control requirements issued by the global control center, the regional control center performs optimization calculations to obtain the regional optimal solution that meets the regional export voltage and power constraints, and sends the control requirements of each controllable unit in the region to each device. The regional control center is the "brain" of the entire autonomous region, and is also the "messenger" between the region and the global, responsible for coordinating the operating actions of each controllable unit in the region, and completing the tasks of uploading capacity indicators and issuing control instructions.

[0138] (2) Global Control Center

[0139] The global control center is located above the autonomous regional control center. It is responsible for coordinating the autonomous regions within the active distribution network area and the lines, nodes and operating equipment independent of the autonomous regions. Through the feedback of measurement information, it completes the global optimization calculation with the goal of the highest global power supply reliability or economic optimization, and sends the goal to each subordinate region or controllable unit. The global optimization cycle is carried out, and a global optimization calculation is performed once in each optimization cycle. Since the power storage capacity index reported by the region takes into account the voltage fluctuation range after power adjustment, the results of the global optimization calculation performed within this constraint are effective and feasible.

[0140] This method divides the active distribution network into autonomous areas based on the topological characteristics and the active and reactive characteristics of the power load in the area, regards each area as a whole, and proposes a power storage capacity model that quantitatively describes the power regulation capability of the area; in each optimization cycle, each area control center reports the adjustable voltage range of the area's outlet and the overall power storage capacity of the area to the global control center. The global control center performs global optimization based on the data reported by each area, and sends the optimization calculation results to each regional control center. Each area performs its own independent control process on the basis of meeting the global requirements for its voltage and power, thereby achieving optimization within each area. The coordination relationship between the global and regional is as follows: Figure 1 shown.

[0141] Furthermore, the step S2 divides the active distribution network into several autonomous areas according to the network topology of the active distribution network and the active and reactive regulation characteristics of each controllable device, including:

[0142] With the access of a large number of controllable devices to the active distribution network and energy-efficient power plants such as electric vehicles extending the coverage of the distribution network in time and space, the controllable area of ​​the active distribution network, which originally assumed all the functions of power supply, distribution and consumption, has become complex and huge. Reasonable zoning should fully consider the internal geo-topological relationship of the distribution network, utilize the complementary coordination capabilities of different types of controllable units, reduce the pressure of upgrading and transforming communication lines, and make the calculation of supply and storage capacity indicators faster and more accurate.

[0143] According to the network topology of active distribution network and the active and reactive regulation characteristics of each controllable device, the active distribution network is divided into several autonomous areas, such as Figure 2 As shown in Figure 1, the autonomous region can be divided into active autonomous region and reactive autonomous region. The division rules are as follows:

[0144] (1) In terms of topology, the autonomous area is located between two section switches on the feeder or between the section switch and the end of the line;

[0145] (2) In terms of power characteristics, each active autonomous area should include all controllable active power sources or active loads in the area described in (1) (at least one, otherwise it cannot be regarded as an autonomous area), and does not include adjustable reactive equipment or the equipment has weak reactive power, and the impact of its reactive power change on the two processes of participating in the calculation of the supply and storage capacity of the area and the optimization control within the area can be ignored; each reactive autonomous area should include all adjustable reactive power sources in the area described in (1) (at least one, otherwise it cannot be regarded as an autonomous area), generally such as the end of the line and other reactive concentrated compensation areas; in addition, power sources or controllable units with high active and reactive coupling and rapid power changes, such as distributed power grid connection points with large-capacity reactive compensation, will no longer be included in the autonomous area, but will be directly managed and controlled by the active distribution network control center.

[0146] The above-mentioned active distribution network zoning method, which comprehensively considers the topological structure and power characteristics, realizes the decoupling of active and reactive power in each autonomous area. In the process of coordinated interaction between each autonomous area and the global system, its active (or reactive) regulation capability is considered as a whole, so that the active autonomous area (or reactive autonomous area) is equivalent to a controllable active (or reactive) power source, participating in the global coordinated optimization control.

[0147] Furthermore, the step S3 of establishing the controllable unit model includes:

[0148] (1) Distributed power generation constraints

[0149] Common distributed power sources connected to the active distribution network are divided into two categories. One is intermittent energy such as photovoltaic power generation and wind turbines, whose power is determined by rated power and meteorological conditions such as light, temperature, wind force and wind direction. Although some intermittent distributed power sources can adjust the output power by changing the operating point, it is generally believed that they operate at the maximum power point determined by the rated power and meteorological conditions; the other type of distributed power source, such as micro gas turbines and internal combustion engines, has an output power between the rated power and the minimum normal operating power, and can be continuously adjusted and controlled within this range; for the above two types of distributed power sources, their power constraints are described as:

[0150]

[0151] Where: E unc is the set of power uncontrollable DGs, P i is the actual power of the i-th power uncontrollable DG, is the maximum power operating point of the i-th power uncontrollable DG determined by the rated power and meteorological conditions; E con is the set of power controllable DGs, P j is the actual power of the jth power-controllable DG, and are the minimum normal operating power and rated power of the jth power-controllable DG respectively;

[0152] (2) Energy storage system power constraints

[0153] The energy storage system is in the charging and discharging states respectively, and power can flow in both directions; its charging and discharging power is constrained by the rated power of the energy storage system, and is also related to the current battery power level (SOC), and its SOC level is determined by the charging and discharging power and charging and discharging time;

[0154] The SOC change of the energy storage system is:

[0155]

[0156] Where: △Soc represents the SOC change of the energy storage system from T to T+△T; μ represents the efficiency of the energy storage system during the charging process, η represents the efficiency of the energy storage system during the discharging process; Pc represents the power of the energy storage system during the charging process, Pd represents the power of the energy storage system during the discharging process; ER represents the rated capacity of the energy storage system;

[0157] Considering that overcharging and over-discharging will cause irreversible damage to the life of the energy storage system, its SOC level should also meet the following constraints:

[0158]

[0159] In the formula, Soc represents the current SOC level of the energy storage system. and They are the lower and upper limits of the SOC level for the normal operation of the energy storage system to avoid over-discharge and over-charge, respectively;

[0160] At the beginning of the global optimization of the active distribution network, the regional control center calculates the output and absorption power of the energy storage system according to the current operating status of the energy storage system. It not only needs to meet the constraints of the rated charging and discharging power of the energy storage system, but also ensures that the SOC level of the energy storage system at the end of the control cycle meets the requirements of formula (3). Therefore, the charging and discharging power of the energy storage system can be derived as shown in formula (4):

[0161]

[0162] Where: and are the rated charging and discharging power of the energy storage system respectively; and are the maximum charging and discharging powers of the energy storage system calculated after considering the rated power constraint and the SOC level constraint;

[0163] (3) Reactive power constraints

[0164] Reactive power sources in active distribution networks can be divided into two categories according to their regulation characteristics: continuous reactive power sources and discrete reactive power sources;

[0165] For continuous reactive power sources, mainly including static synchronous compensators (STATCOM), static VAR generators (SVG) and converter stations based on voltage source converters, the reactive capacity is large, dynamic continuous regulation can be achieved, the response speed and regulation speed are fast, and the regulation accuracy is high. The reactive power of the continuous reactive power source must meet the rated power constraint, as shown in formula (5)

[0166]

[0167] Where: F ctn represents the collection of continuous reactive power sources, Q i represents the reactive power of the i-th continuous reactive power source, represents the rated capacity of the i-th continuous reactive power source;

[0168] For discrete reactive power sources, the common discrete reactive compensation devices in distribution networks are mainly grouped capacitors. The reactive power is increased or decreased by switching on and off capacitor groups. The reactive capacity is small, the response speed and adjustment speed are slow, and the control accuracy is low. Frequent switching will damage the normal life of the capacitor group. Switching on multiple groups of capacitors at a time will have a greater impact on the voltage quality of the power grid. Therefore, it is stipulated that the number of groups of capacitors switched each time is one group, and the time interval between two operations is one global optimization cycle. That is, if the switching operation of the capacitor group was performed in the last global optimization cycle, the capacitor group cannot be adjusted in the current optimization cycle; if the switching operation of the capacitor group was not performed in the last global optimization cycle, a group of capacitors can be switched on or off in the current optimization cycle; the power constraint of the discrete reactive power source is expressed by formula (6):

[0169]

[0170] Where: F dct represents the collection of discrete reactive power sources, Q j represents the reactive power of the jth discrete reactive power source, It represents the reactive power change of a group of capacitors. w is the switching operation permission signal of the current cycle. If the switching operation can be performed in the current cycle, w is 1, otherwise it is 0.

[0171] Furthermore, the step S4 of calculating the power storage capacity index includes:

[0172] (1) Determine the adjustable voltage range based on the regional threshold voltage

[0173] Since the voltage amplitude of each area outlet may change after the global optimization is performed, the calculation of the supply and storage capacity should take into account the change range of the voltage amplitude. The voltage range is taken as the current voltage ±0.03 (unit value) and does not exceed the safety range, as follows:

[0174]

[0175]

[0176] In the formula, is the upper limit of the regional gateway voltage, is the lower limit of the regional threshold voltage, is the current threshold voltage of the region;

[0177] (2) Calculate the storage capacity based on the upper and lower limits of the regional voltage threshold

[0178] Determine the sensitivity of the controllable active (reactive) power supply in the region to the active (reactive) power at the regional export, and calculate the maximum output power or storage power corresponding to the upper or lower limit of the voltage according to the dynamic sensitivity algorithm, that is, the regional supply and storage capacity.

[0179] a. Calculate the sensitivity of each controllable power source to the output power

[0180] The relationship between node injection current and node voltage is:

[0181] I N =Y N U N (9)

[0182] In the formula, I N is the node injection current column vector, Y N is the node admittance matrix, U N is the node voltage column vector;

[0183] The relationship between branch current and node voltage is:

[0184] I L =Y L A T U N (10)

[0185] In the formula, I L is the branch current column vector, Y L is the branch admittance matrix, A is the node association matrix;

[0186] According to equations (9) and (10), we can get

[0187]

[0188] make

[0189]

[0190] but

[0191] I L =CI N (13)

[0192] For a distribution network area with n nodes and l branches, C is an l×n-order real matrix; the C matrix is ​​only related to the topological structure and network parameters. For a radial distribution network, the increase or decrease of the current injected into a single node causes the branches on the path from the first node to the node to decrease or increase the same amount of current accordingly, while the current of other branches not on the path will not change, so the elements of the C matrix are 0 or -1; the branch k current I k,L It is a linear combination of the current injected into each node;

[0193]

[0194]

[0195] In the formula, is the current in branch k, C k,i is the coefficient of node i in branch k in the C matrix, is the voltage vector at the head end of branch k, is the voltage vector of node i; simplifying formula (15), we can get

[0196]

[0197] Where P k,L and Q k,L is the active power and reactive power at the head end of branch k, C k,i is the kth row and ith column element of the coefficient matrix C, P i,N and Q i,N is the active injection power and reactive injection power of node i, U k,L and are the voltage amplitude and phase angle at the head end of branch k, U i,N and are the voltage amplitude and phase angle of node i respectively;

[0198] Expanding equation (16), we get equation (17) and equation (18) for the real part and imaginary part respectively.

[0199]

[0200]

[0201] According to the above principle, when only the active power of a node is adjusted, its reactive power will not be changed. Therefore, the branch active power and node injected active power in equation (17) are changed to variables, and the reactive power is set to 0, and we get

[0202]

[0203] Similarly, when only the reactive power of a node is adjusted, its active power is not changed. Therefore, the branch reactive power and node injected reactive power in equation (18) are changed into variables, and the reactive power is set to 0, and we get

[0204]

[0205] Therefore, the active sensitivity matrix B(β) between the branch active change and the node injected active change and the reactive sensitivity matrix D(γ) between the branch reactive change and the node injected reactive change can be defined respectively, where the power sensitivity β between the branch k active change and the node i active injection change is k,i Expressed as

[0206]

[0207] Power sensitivity γ of the reactive power change of branch m to the reactive power injection change of node j m,j Expressed as

[0208]

[0209] b. Dynamic sensitivity algorithm to solve regional supply and storage capacity

[0210] For each region, the maximum output power corresponding to the lower limit of the region's outlet voltage is solved through the dynamic sensitivity algorithm. (or ) and maximum absorbed power (or ), and the maximum output power corresponding to the upper limit of the regional outlet voltage (or ) and maximum absorbed power (or ); For each region, the upper and lower limits of its outlet voltage correspond to a power band range, which represents the power storage capacity of the region when the voltage is at the upper or lower limit, and the intersection of the two power bands represents the conservative power storage capacity of the region when the regional voltage is between the upper and lower limits;

[0211] After each power flow calculation, update the sensitivity of each controllable power source to the regional gateway power and arrange them from high to low according to the sensitivity. Increase (or decrease) the power of the controllable power source with the largest sensitivity according to the specified step size, check the constraints, and perform the next iterative calculation if the constraints are met. If the constraints are not met, determine the exact power through dichotomy. The specific steps are as follows:

[0212] ① Check whether the number of adjustable power supplies is 0. If not, execute ②; if it is 0, end;

[0213] ② Calculate the sensitivity of each controllable power supply and arrange the sensitivity from high to low;

[0214] ③Adjust the controllable power supply with the highest sensitivity by one step unit;

[0215] ④ Check whether the power of the power supply exceeds its adjustable capacity, if not, execute ⑤; if yes, adjust its power to the upper limit (or lower limit) of the adjustable capacity, and remove the power supply from the sensitivity sorting table, and execute ⑤;

[0216] ⑤ Flow calculation, verify the constraints of each network. If the constraints are met, execute ①; if the constraints are not met, execute ⑥;

[0217] ⑥ Determine the precise value of the power adjustment amount that satisfies the network constraints by the binary method, and output the current power value.

[0218] Dynamic sensitivity algorithm and binary logic block diagram (taking the maximum output power of a certain active autonomous area as an example, the storage power and reactive autonomous area supply and storage capacity can be obtained by analogy) as shown in Figure 3 , 4 The storage capacity limit corresponding to the upper and lower limits of the regional outlet voltage is as follows: Figure 5 shown.

[0219] Furthermore, the step S5 of performing global optimization and regional control includes:

[0220] (1) Global Optimization Process

[0221] Through the power storage capacity corresponding to the upper and lower limits of the regional outlet voltage reported by each region, each region is equivalent to a power controllable power source to participate in the global coordinated optimization of the active distribution network. The steps are as follows:

[0222] ①Propose the objective function of global optimization;

[0223] ② Propose equality constraints for global optimization;

[0224] ③ The inequality constraints of global optimization and the regional power supply and storage capacity constraints are taken as the union;

[0225] ④ For optimization calculation, the interior point optimization method can be adopted;

[0226] ⑤ Check whether the power and voltage ranges of the regional calculation results conflict. If they do not match, limit the power supply and storage capacity constraints of the conflicting area to the corresponding voltage upper limit power range or voltage lower limit power range, keep other constraints unchanged, and perform new optimization calculations;

[0227] ⑥Distribute the optimization results to each region;

[0228] (2) Regional control process

[0229] Each region uses the optimization calculation results issued by the region as equality constraints, takes the corresponding target as the optimization target, performs optimization calculations, and implements control over the controllable power supply. The steps are as follows:

[0230] Determine the objective function of regional optimization control,

[0231]

[0232] Among them, F is the power generation cost, N G is the number of generating units, P Gi is the power generation cost of the i-th generator set, a i 、b i 、c i is the cost coefficient of the i-th generator set;

[0233] Determine the equality constraints of regional optimization control. The regional power and voltage should be the values ​​issued after global optimization.

[0234]

[0235] Determine the inequality constraints for regional optimization control,

[0236]

[0237] For optimization calculation, the interior point optimization algorithm can be used. The global optimization and regional control process flow chart is as follows: Figure 6 shown.

[0238] In summary, the local autonomous power grid partition autonomous control method based on the power supply and storage capacity of the distribution network of the present invention is as follows: By dividing the power grid into multiple autonomous regions, independent control and optimization of local regions can be achieved, thereby improving the operating efficiency of the entire power grid. The autonomous region has independent control capabilities, which can isolate faults to a certain extent, prevent fault propagation, and improve the safety of the power grid. In the event of a fault, the autonomous region can quickly adjust its internal distributed power sources and loads to form an island operation, provide continuous power supply for key loads, and thus improve the reliability of the power grid. By optimizing the use of distributed resources within the autonomous region, the operating cost of the power grid is reduced and the economic benefits are improved. The purpose of the local autonomous power grid partition autonomous control mode is to improve the operating efficiency, safety and reliability of the power grid, and optimize resource allocation. In order to achieve these goals, the mode needs to complete tasks such as real-time monitoring and control, fault detection and isolation, load management and optimization, distributed energy access and management, coordination with other autonomous regions, and data collection and analysis. The present invention combines the advantages of regional autonomous power grids and partition control strategies, aiming to improve the power supply reliability, economy and flexibility of the power grid. The local autonomous power grid partition autonomous control mode has shown significant beneficial effects in improving power supply reliability, enhancing power grid flexibility, improving economy, enhancing system stability, and promoting technological innovation and industrial upgrading. These effects not only help improve the operational efficiency and safety of the power grid, but also lay a solid foundation for future energy transformation and sustainable development.

[0239] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0240] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A local autonomous power grid partition autonomous control method based on the power supply and storage capacity of the distribution network, characterized in that: The following steps are involved: S1. Based on the hierarchical and zoned coordinated control mode, two levels of control centers, global and autonomous regional, are set up within the scope of the active distribution network; S2. Divide the active distribution network into several autonomous areas according to the network topology of the active distribution network and the active and reactive regulation characteristics of each controllable device; S3, establish a controllable unit model; S4. Calculate the power supply and storage capacity index; S5. Perform global optimization and regional control.

2. The method for controlling the local autonomous power grid based on the power supply and storage capacity of the distribution network according to claim 1, characterized in that: The step S1 is based on the hierarchical and partitioned coordinated control mode, and sets up two levels of control centers, namely, global and autonomous regional, within the active distribution network, including: (1) Regional Control Center The regional control center is located inside each autonomous region to monitor the power and voltage conditions of each line and node in the region and the operating status of each controllable unit. At the beginning of the global optimization cycle, the regional control center calculates the range of power supplied to or absorbed from the external power grid by the region as a whole within the tolerable voltage range based on the current voltage operation status in the region and the output level of each controllable unit, taking into account the changes and impacts in the future. This is used as the power supply and storage capacity indicator that the region can achieve during this optimization cycle, and the indicator is uploaded to the global control center. Subsequently, after receiving the control requirements issued by the global control center, the regional control center performs optimization calculations to obtain the regional optimal solution that meets the regional export voltage and power constraints, and sends the control requirements of each controllable unit in the region to each device. (2) Global Control Center The global control center is located above the autonomous regional control center. It is responsible for coordinating the autonomous regions within the active distribution network area as well as the lines, nodes and operating equipment independent of the autonomous regions. Through measurement information feedback, with the goal of maximum global power supply reliability or economic optimization, it completes the global optimization calculation and sends the goal to each subordinate region or controllable unit.

3. The method for controlling the local autonomous power grid based on the power supply and storage capacity of the distribution network according to claim 1, characterized in that: The step S2 divides the active distribution network into several autonomous areas according to the network topology of the active distribution network and the active and reactive regulation characteristics of each controllable device, including: According to the network topology of the active distribution network and the active and reactive power regulation characteristics of each controllable device, the active distribution network is divided into several autonomous areas. The autonomous areas can be divided into active autonomous areas and reactive autonomous areas. The division rules are as follows: (1) In terms of topology, the autonomous area is located between two section switches on the feeder or between the section switch and the end of the line; (2) In terms of power characteristics, each active autonomous area should include all controllable active power sources or active loads in the area described in (1), and do not include adjustable reactive equipment or equipment with weak reactive power, and the impact of its reactive power changes on the two processes of participating in the calculation of the supply and storage capacity of the area and the optimization control within the area can be ignored; each reactive autonomous area should include all adjustable reactive power sources in the area described in (1); in addition, power sources or controllable units with a high degree of active and reactive coupling and rapid power changes will no longer be included in the autonomous area, but will be directly managed and controlled by the active distribution network control center.

4. The method for controlling the local autonomous power grid based on the power supply and storage capacity of the distribution network according to claim 1, characterized in that: The step S3 of establishing the controllable unit model includes: (1) Distributed power generation constraints There are two common types of distributed power sources connected to the active distribution network. One type is intermittent energy such as photovoltaic power generation and wind turbines. The other type of distributed power source has an output power between the rated power and the minimum normal operating power, and can be continuously adjusted and controlled within this range. For the above two types of distributed power sources, their power constraints are described as follows: Where: E unc is the set of power uncontrollable DGs, P i is the actual power of the i-th power uncontrollable DG, P i max is the maximum power operating point of the i-th power uncontrollable DG determined by the rated power and meteorological conditions; E con is the set of power controllable DGs, P j is the actual power of the jth power-controllable DG, and are the minimum normal operating power and rated power of the jth power-controllable DG respectively; (2) Energy storage system power constraints The energy storage system is in the charging and discharging states respectively, and power can flow in both directions; its charging and discharging power is constrained by the rated power of the energy storage system, and is also related to the current battery power level (SOC), and its SOC level is determined by the charging and discharging power and charging and discharging time; The SOC change of the energy storage system is: Where: △Soc represents the SOC change of the energy storage system from T to T+△T; μ represents the efficiency of the energy storage system during the charging process, η represents the efficiency of the energy storage system during the discharging process; Pc represents the power of the energy storage system during the charging process, Pd represents the power of the energy storage system during the discharging process; ER represents the rated capacity of the energy storage system; Considering that overcharging and over-discharging will cause irreversible damage to the life of the energy storage system, its SOC level should also meet the following constraints: In the formula, Soc represents the current SOC level of the energy storage system. and They are the lower and upper limits of the SOC level for the normal operation of the energy storage system to avoid over-discharge and over-charge, respectively; The charging and discharging power of the energy storage system is shown in formula (4): Where: P c R and are the rated charging and discharging power of the energy storage system respectively; P c max and are the maximum charging and discharging powers of the energy storage system calculated after considering the rated power constraint and the SOC level constraint; (3) Reactive power constraints Reactive power sources in active distribution networks can be divided into two categories according to their regulation characteristics: continuous reactive power sources and discrete reactive power sources; The reactive power of the continuous reactive power source must meet the rated power constraint, as shown in formula (5): Where: F ctn represents the collection of continuous reactive power sources, Q i represents the reactive power of the i-th continuous reactive power source, represents the rated capacity of the i-th continuous reactive power source; The number of capacitor groups switched each time is one group, and the time interval between two operations is one global optimization cycle. That is, if the capacitor group was switched in the last global optimization cycle, the capacitor group cannot be adjusted in the current optimization cycle; if the capacitor group was not switched in the last global optimization cycle, one group of capacitors can be switched in or out in the current optimization cycle. The power constraint of the discrete reactive power source is expressed by formula (6): Where: F dct represents the collection of discrete reactive power sources, Q j represents the reactive power of the jth discrete reactive power source, It represents the reactive power change of a group of capacitors. w is the switching operation permission signal of the current cycle. If the switching operation can be performed in the current cycle, w is 1, otherwise it is 0.

5. The method for controlling the local autonomous power grid based on the power supply and storage capacity of the distribution network according to claim 1, characterized in that: The step S4 of calculating the power storage capacity index comprises: (1) Determine the adjustable voltage range based on the regional threshold voltage The voltage range is ±0.03 of the current voltage and does not exceed the safety range, as follows: In the formula, is the upper limit of the regional gateway voltage, is the lower limit of the regional threshold voltage, is the current threshold voltage of the region; (2) Calculate the storage capacity based on the upper and lower limits of the regional voltage threshold a. Calculate the sensitivity of each controllable power source to the output power The relationship between node injection current and node voltage is: I N =Y N U N (9) In the formula, I N is the node injection current column vector, Y N is the node admittance matrix, U N is the node voltage column vector; The relationship between branch current and node voltage is: I L =Y L A T U N (10) In the formula, I L is the branch current column vector, Y L is the branch admittance matrix, A is the node association matrix; According to equations (9) and (10), we can get make but AND L =CI N (13) For a distribution network area with n nodes and l branches, C is an l×n-order real matrix; the C matrix is ​​only related to the topological structure and network parameters. For a radial distribution network, the increase or decrease of the current injected by a single node causes each branch on the path from the first node to the node to decrease or increase the same amount of current accordingly, while the current of other branches not on the path will not change, so the elements of the C matrix are 0 or -1; the branch k current I k,L It is a linear combination of the current injected into each node; In the formula, is the current in branch k, C k,i is the coefficient of node i in branch k in the C matrix, is the voltage vector at the head end of branch k, is the voltage vector of node i; simplifying formula (15), we can get Where P k,L and Q k,L is the active power and reactive power at the head end of branch k, C k,i is the kth row and ith column element of the coefficient matrix C, P i,N and Q i,N is the active injection power and reactive injection power of node i, U k,L and are the voltage amplitude and phase angle at the head end of branch k, U i,N and are the voltage amplitude and phase angle of node i respectively; Expanding equation (16), we get equation (17) and equation (18) for the real part and imaginary part respectively. According to the above principle, when only the active power of a node is adjusted, its reactive power will not be changed. Therefore, the branch active power and node injected active power in equation (17) are changed to variables, and the reactive power is set to 0, and we get Similarly, when only the reactive power of a node is adjusted, its active power is not changed. Therefore, the branch reactive power and node injected reactive power in equation (18) are changed into variables, and the reactive power is set to 0, and we get Therefore, the active sensitivity matrix B(β) between the branch active change and the node injected active change and the reactive sensitivity matrix D(γ) between the branch reactive change and the node injected reactive change can be defined respectively, where the power sensitivity β between the branch k active change and the node i active injection change is k,i Expressed as Power sensitivity γ of the reactive power change of branch m to the reactive power injection change of node j m,j Expressed as b. Dynamic sensitivity algorithm to solve regional supply and storage capacity For each region, the maximum output power corresponding to the lower limit of the region's outlet voltage is solved through the dynamic sensitivity algorithm. (or ) and maximum absorbed power (or ), and the maximum output power corresponding to the upper limit of the regional outlet voltage (or ) and maximum absorbed power (or ); For each region, the upper and lower limits of its outlet voltage correspond to a power band range, which represents the power storage capacity of the region when the voltage is at the upper or lower limit, and the intersection of the two power bands represents the conservative power storage capacity of the region when the regional voltage is between the upper and lower limits; After each power flow calculation, update the sensitivity of each controllable power source to the regional gateway power and arrange them from high to low according to the sensitivity. Increase (or decrease) the power of the controllable power source with the largest sensitivity according to the specified step size, check the constraints, and perform the next iterative calculation if the constraints are met. If the constraints are not met, determine the exact power through dichotomy. The specific steps are as follows: ① Check whether the number of adjustable power supplies is 0. If not, execute ②; if it is 0, end; ② Calculate the sensitivity of each controllable power supply and arrange the sensitivity from high to low; ③Adjust the controllable power supply with the highest sensitivity by one step unit; ④ Check whether the power of the power supply exceeds its adjustable capacity, if not, execute ⑤; if yes, adjust its power to the upper limit (or lower limit) of the adjustable capacity, and remove the power supply from the sensitivity sorting table, and execute ⑤; ⑤ Flow calculation, verify the constraints of each network. If the constraints are met, execute ①; if the constraints are not met, execute ⑥; ⑥ Determine the precise value of the power adjustment amount that satisfies the network constraints by the binary method, and output the current power value.

6. The method for controlling the local autonomous power grid based on the power supply and storage capacity of the distribution network according to claim 1, characterized in that: The step S5 of performing global optimization and regional control includes: (1) Global Optimization Process Through the power storage capacity corresponding to the upper and lower limits of the regional outlet voltage reported by each region, each region is equivalent to a power controllable power source to participate in the global coordinated optimization of the active distribution network. The steps are as follows: ①Propose the objective function of global optimization; ② Propose equality constraints for global optimization; ③ The inequality constraints of global optimization and the regional power supply and storage capacity constraints are taken as the union; ④ For optimization calculation, the interior point optimization method can be adopted; ⑤ Check whether the power and voltage ranges of the regional calculation results conflict. If they do not match, limit the power supply and storage capacity constraints of the conflicting area to the corresponding voltage upper limit power range or voltage lower limit power range, keep other constraints unchanged, and perform new optimization calculations; ⑥Distribute the optimization results to each region; (2) Regional control process Each region uses the optimization calculation results issued by the region as equality constraints, takes the corresponding target as the optimization target, performs optimization calculations, and implements control over the controllable power supply. The steps are as follows: Determine the objective function of regional optimization control, Among them, F is the power generation cost, N G is the number of generating units, P Gi is the power generation cost of the i-th generator set, a i , b i 、c i is the cost coefficient of the i-th generator set; Determine the equality constraints of regional optimization control. The regional power and voltage should be the values ​​issued after global optimization. Determine the inequality constraints for regional optimization control, For optimization calculation, the interior point optimization algorithm can be used.

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