A distribution system planning method, system, device and storage medium

Abstract

The present invention relates to the field of power distribution technology, and discloses a power distribution system planning method, system, equipment and storage medium. By adjusting the topological relationship between power supply nodes, load nodes and new energy nodes, different power distribution schemes are formed, and optimization is performed through an optimization algorithm to find the best solution and output the optimal power distribution scheme, which can reduce the peak capacity of the power supply node and achieve the optimization of the power distribution system; the peak capacity of the power supply node is obtained by superimposing the load curves of all nodes connected to the power supply node, and then the transformer configuration in the power supply node is optimized through the optimization algorithm, so as to obtain the best, most reasonable and most economical transformer configuration, and avoid the problem of over-large transformer selection. In addition, the present invention takes new energy nodes into consideration during planning, and the new energy nodes participate in the peak calculation of the power supply nodes, which can further reduce the expected transformer capacity of the power supply nodes and achieve optimization. The present invention also performs safety verification to ensure the safety of the planned power distribution system.

Description

Technical Field

[0001] The present invention relates to the field of power distribution technology, and in particular to a power distribution system planning method, system, device and storage medium. Background Art

[0002] For a complete power system, it is generally divided into three parts: power generation side, grid side and user side. In the field of power system design for the user side, especially the design of transformer capacity and low-voltage side (0.4kV) distribution system, the planning of user-side distribution system in the industry is currently mainly through unit index method or requirement coefficient method.

[0003] The capacity of the transformer is fixed and is divided into grades according to the size of the capacity. It is impossible to customize the capacity of the transformer according to actual needs. Only transformers of similar grades can be selected according to actual needs, and the capacity of the transformer must be greater than the maximum power consumption peak. The unit index method or the required coefficient method are both empirical methods. Since this empirical design method has high uncertainty in the index and coefficient values, the design economy of the power system on the user side is poor, especially the problem of the general selection of oversized transformers.

[0004] There are also some methods disclosed in the current technology that involve optimizing the design of power systems based on load characteristics, but these methods are mainly based on the high-voltage end of the grid side or the user side. In actual projects, the planning of the distribution system on the user side, especially the determination of the transformer capacity, is basically based on the unit area index method and the need coefficient method. These methods are also relatively conservative in various values, resulting in a higher planned transformer capacity. For the power consumption system on the user side, the power distribution is multi-level, and the installation capacity and power consumption rules of the terminal equipment are relatively easy to determine, especially for the terminal equipment, the power consumption curve is relatively easy to determine. In addition, the connection relationship between the electric box and the load, the upper electric box and the lower electric box, and the transformer and the first-level electric box, that is, the topological relationship, can also be changed, which can achieve the optimization of the distribution system. Therefore, in order to reduce the unreasonable design of the distribution system caused by traditional design methods, waste of investment and waste of energy, it is urgent to optimize the distribution system on the user side. Summary of the invention

[0005] The object of the present invention is to provide a distribution system planning method, system, device and storage medium with high rationality and economy.

[0006] In order to achieve the above object, the present invention provides a power distribution system planning method, comprising the following steps:

[0007] S1: Obtain the load curve of each load node and new energy node;

[0008] S2: Obtain classification information of load nodes, the classification information includes working condition classification;

[0009] S3: Obtain the location information of each power node, load node, and new energy node;

[0010] S4: According to the location information of each power node, load node, and new energy node, the nodes at each level are connected and adjusted to obtain multiple different power distribution schemes; when forming the power distribution scheme, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve;

[0011] S5: searching for the best solution among the multiple power distribution solutions obtained through an optimization algorithm, and outputting the optimal power distribution solution;

[0012] S6: In the optimal power distribution plan obtained in step S5, the required power distribution plan is selected, and according to the matching relationship among the power supply nodes, load nodes, and new energy nodes in the required power distribution plan and the peak power consumption of the power supply nodes, the optimal configuration of the transformer capacity and number in each power supply node and the matching relationship among the transformer, load nodes, and new energy nodes are obtained through an optimization algorithm, and the optimized power distribution plan is output;

[0013] S7: According to the operating condition classification of the load node, for the optimized distribution plan obtained in step S6, the capacity of the transformer and the distribution boxes at each level is verified through the different operating conditions of the load node. If the safety requirements are not met, the capacity of the transformer and the capacity of the distribution boxes at each level are increased to obtain the final transformer capacity and distribution plan.

[0014] As a preferred solution, in step S1, a load curve is outputted through a power load prediction model corresponding to the type of load node and new energy node.

[0015] As a preferred solution, in step S2, the classification information of the load node also includes flexibility classification, and the flexibility classification divides the load node into a flexible load node and a non-flexible load node, the non-flexible load node is connected to a transformer of the power node, and the flexible load node is connected to two or more transformers of the power node;

[0016] In step S4, when nodes are connected, only non-flexible load nodes are connected;

[0017] In step S6, after the optimized power distribution plan is output, a flexible load node is added, and the load curve of the power node connected to the flexible load node is superimposed on the load curve of the flexible load node to obtain a new power consumption peak of the power node. If the transformer configuration capacity of the power node is not less than the new power consumption peak of the power node, the configuration and matching relationship of the transformer capacity and number of units are not adjusted, and a new optimized power distribution plan is output; if the transformer configuration capacity of the power node is less than the new power consumption peak of the power node, the level of the transformer capacity is adjusted, and a new optimized power distribution plan is output;

[0018] In step S7, the new optimized power distribution scheme is safety checked according to the operating condition classification of the load nodes.

[0019] As a preferred solution, in step S2, the operating condition classification includes normal operating conditions and firefighting conditions; in step S7, the optimized power distribution plan output by step S6 is obtained, and the guaranteed loads according to the firefighting conditions or normal operating conditions of the load nodes are added to obtain the guaranteed load. If the transformer capacity of the power supply node is not less than the sum of the guaranteed loads of all the nodes connected to it, no adjustment is made; if the transformer capacity of the power supply node is less than the sum of the guaranteed loads of all the nodes connected to it, the transformer capacity is adjusted up by one level.

[0020] As a preferred solution, the optimization algorithms of step S5 and step S6 both adopt genetic algorithms.

[0021] As a preferred solution, in step S2, the load node classification further includes electricity fee type classification, and in step S4, the load node is connected to a power source node with the same electricity fee type.

[0022] As a preferred solution, in step S5, optimization is performed based on minimum investment, minimum operating energy consumption, minimum operating electricity cost or a combination of multiple objectives.

[0023] The present invention also provides a planning system for a power distribution system, comprising:

[0024] The load curve acquisition module is used to obtain the load curves of each load node and new energy node;

[0025] A classification information acquisition module is used to obtain classification information of load nodes, and the classification information includes working condition classification;

[0026] A location information acquisition module is used to obtain the location information of each power node, load node, and new energy node;

[0027] The power distribution plan generation module is used to connect and adjust nodes at each level according to the location information of each power node, load node, and new energy node to obtain multiple different power distribution plans. When forming a power distribution plan, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve;

[0028] The first optimization module is used to search for the best among the multiple power distribution schemes obtained by using an optimization algorithm and output the optimal power distribution scheme;

[0029] The second optimization module is used to select a required power distribution scheme from the optimal power distribution scheme obtained by the first optimization module, and obtain the optimal configuration of transformer capacity and number in each power node and the matching relationship between the transformer and the load node and the new energy node through an optimization algorithm according to the matching relationship among the power nodes, load nodes and new energy nodes in the required power distribution scheme and the peak power consumption of the power nodes, and output the optimized power distribution scheme;

[0030] The safety verification module classifies the operating conditions of the load nodes and verifies the capacity of the transformer and distribution boxes at all levels for the optimized distribution plan obtained by the second optimization module through different operating conditions of the load nodes. If the safety requirements are not met, the transformer capacity and the capacity of the distribution boxes at all levels are increased to obtain the final transformer capacity and distribution plan.

[0031] In addition, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned power distribution system planning method when executing the computer program.

[0032] In addition, the present invention also provides a computer storage medium on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned distribution system planning method is implemented.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention forms different power distribution schemes by adjusting the topological relationship among power supply nodes, load nodes and new energy nodes, and performs optimization through an optimization algorithm to output the optimal power distribution scheme, thereby reducing the peak capacity of the power supply node and optimizing the power distribution system; the peak capacity of the power supply node is obtained by superimposing the load curves of all nodes connected to the power supply node, and then the transformer configuration in the power supply node is optimized through an optimization algorithm, thereby obtaining the best, most reasonable and most economical transformer configuration, and avoiding the problem of over-large transformer selection. In addition, the present invention takes new energy nodes into consideration during planning, and the new energy nodes participate in the peak calculation of the power supply node, which can further reduce the expected transformer capacity of the power supply node and achieve optimization. The present invention also performs safety verification to ensure the safety of the planned power distribution system. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a flow chart of a power distribution system planning method according to a first embodiment of the present invention.

[0036] Figure 2 Schematic diagram of the hierarchy of the power distribution system according to the embodiment of the present invention.

[0037] Figure 3 It is a schematic diagram of constructing a power load prediction model in step S1 of an embodiment of the present invention.

[0038] Figure 4 It is an example diagram of the load curve superposition in step S4 of the embodiment of the present invention.

[0039] Figure 5 4 is a flowchart of step S4 and step S5 of an embodiment of the present invention.

[0040] Figure 6 is a flow chart of step S6 of an embodiment of the present invention.

[0041] Figure 7 is a flow chart of step S7 of an embodiment of the present invention.

[0042] Figure 8 It is a flow chart of a distribution system planning method according to the second embodiment of the present invention.

[0043] Fig. 9 It is a principle block diagram of a planning system for a power distribution system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0045] Embodiment 1

[0046] like Figures 1 to 7 As shown, a distribution system planning method according to a preferred embodiment of the present invention comprises the following steps:

[0047] S1: Obtain the load curve of each load node and new energy node;

[0048] S2: Obtain classification information of load nodes, the classification information includes working condition classification;

[0049] S3: Obtain the location information of each power node, load node, and new energy node;

[0050] S4: According to the location information of each power node, load node, and new energy node, the nodes at each level are connected and adjusted to obtain multiple different power distribution schemes; when forming the power distribution scheme, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve;

[0051] S5: searching for the best solution among the multiple power distribution solutions obtained through an optimization algorithm, and outputting the optimal power distribution solution;

[0052] S6: In the optimal power distribution plan obtained in step S5, the required power distribution plan is selected, and according to the matching relationship among the power supply nodes, load nodes, and new energy nodes in the required power distribution plan and the peak power consumption of the power supply nodes, the optimal configuration of the transformer capacity and number in each power supply node and the matching relationship among the transformer, load nodes, and new energy nodes are obtained through an optimization algorithm, and the optimized power distribution plan is output;

[0053] S7: According to the operating condition classification of the load node, for the optimized distribution plan obtained in step S6, the capacity of the transformer and the distribution boxes at each level is verified through the different operating conditions of the load node. If the safety requirements are not met, the capacity of the transformer and the capacity of the distribution boxes at each level are increased to obtain the final transformer capacity and distribution plan.

[0054] This embodiment forms different power distribution schemes by adjusting the topological relationship among power nodes, load nodes and new energy nodes, and performs optimization through an optimization algorithm to output the optimal power distribution scheme, thereby reducing the peak capacity of the power node and optimizing the power distribution system; the peak capacity of the power node is obtained by superimposing the load curves of all nodes connected to the power node, and then the transformer configuration in the power node is optimized through an optimization algorithm, thereby obtaining the best, most reasonable and most economical transformer configuration, thereby avoiding the problem of over-sized transformer selection. In addition, the present invention takes new energy nodes into consideration during planning, and the new energy nodes participate in the peak calculation of the power node, which can further reduce the expected transformer capacity of the power node and achieve optimization. The present invention also performs safety verification to ensure the safety of the planned power distribution system.

[0055] like Figure 2 As shown, the power distribution system on the user side is generally composed of a transformer station, a primary electric box, a secondary electric box... a terminal electric box and a terminal load. In this embodiment, the transformer station, the primary electric box, the secondary electric box... the terminal electric box are all referred to as power supply nodes, and the terminal load is a load node. The current distribution system is mostly involved in new energy equipment, so the location of the new energy equipment is called a new energy node. Since this embodiment is a power distribution system planning on the user side, the new energy equipment refers to small power generation devices and small energy storage devices. Currently, common small power generation devices include photovoltaic power generation, wind power generation, bioenergy power generation and other devices. Small energy storage devices include electrochemical energy storage, flywheel energy storage, new energy vehicle battery energy storage, etc. The highest-level power node is the transformer station. Each of the highest-level power nodes needs to be configured with multiple transformers, and the transformers are connected to the distribution box of the next-level power node. The distribution box is configured in the power node of the lower level, and the distribution box is connected to the distribution box of the next-level power node or directly to the load node. The lowest level in the distribution system is the load node, and each load node contains load equipment.

[0056] Specifically, in step S1 of this embodiment, a load curve is outputted through a power load prediction model corresponding to the type of load node and new energy node.

[0057] This embodiment is a plan for a power distribution system that is about to be put into use. Therefore, the load equipment at the load nodes and the new energy equipment at the new energy nodes are brand new equipment without historical usage data. Therefore, the usage data of the same type of equipment is used to train the electricity load prediction model, and the trained electricity load prediction model of the corresponding type is used to output the load curves of the load nodes and the new energy nodes.

[0058] In this embodiment, the power consumption method and the time series method are used to construct the power load prediction model, and the power consumption data of the same type of equipment for at least one year are obtained. The power consumption data is recorded using the time series method as follows: If the power consumption time series is one hour, then the real-time power Pt = the power consumption (kWh) in the hour period, and a time series curve of 365x24 sequences is obtained. If the power consumption time series interval is 15 minutes, then the real-time power Pt = the power consumption (kWh) in the 15-minute period x 4, and a time series curve of 365x96 sequences is obtained.

[0059] The power load prediction model of this embodiment adopts a deep learning model, such as LSTM, GRU and other models.

[0060] The acquired power consumption data is divided into a training set, a validation set and a test set to train the power load prediction model, and then the trained power load prediction model is used to predict the load curve of the corresponding load node or new energy node.

[0061] It should be pointed out that when the load equipment of the load node and the new energy equipment of the new energy node are general and typical equipment, the load curve can also be obtained by computer simulation and empirical analysis. For example, in the HVAC profession, the load curve of the air-conditioning equipment can be calculated based on the known conditions of ambient temperature and building enclosure, and the load curve can be obtained by computer simulation. Some relatively fixed and long-term working equipment can also be easily obtained.

[0062] Currently, new energy equipment is widely used and has become an essential power supply facility for distribution systems. However, the current distribution systems have not been included in the early planning of the distribution systems, resulting in too large a transformer selection. This embodiment includes new energy equipment in the planning because photovoltaic power generation can absorb a lot of daily electricity consumption around noon, and the energy storage device also plays a role in "peak shaving and valley filling". In this way, the installation capacity of the transformer can be further optimized.

[0063] In step S2, classification information of the load node is obtained, where the classification information includes operating condition classification, and the classification information in this embodiment also includes electricity fee type classification.

[0064] From the perspective of ensuring load, load nodes are divided into normal working conditions and firefighting working conditions, and are specifically divided into ordinary loads, normal ensuring loads, firefighting ensuring loads, and normal and firefighting ensuring loads. Ordinary loads are non-ensuring loads with no special requirements, such as air conditioning power. Normal ensuring loads are loads that only require dual power supply to ensure power supply during normal working conditions, such as ordinary elevators. Firefighting ensuring loads are loads that only require dual power supply to ensure power supply during firefighting conditions, such as fire pumps. Normal and firefighting ensuring loads are loads that require dual power supply to ensure power supply during both normal working conditions and firefighting conditions, such as firefighting elevators. Ensuring loads refer to loads that require guaranteed power supply. The size of the ensuring load is determined by the specific equipment, and the ensuring load is one of the parameters of the equipment.

[0065] The load nodes are classified according to their working conditions, so that it can be distinguished which load nodes need to be powered under normal working conditions, which load nodes need to be powered under fire working conditions, and which load nodes need to be powered under both normal working conditions and fire working conditions.

[0066] The purpose of classifying the loads at the load nodes is that in special circumstances, such as fire situations and transformer failure situations, certain loads need to be ensured, and the loads that need to be ensured within the capacity of the transformer and generator are used to verify whether the optimized transformer capacity meets the power supply requirements under the two working conditions, thereby ensuring safe and reliable power supply.

[0067] The electricity fee type classification is to define what type of electricity fee the load node has, so that the operating electricity fee can be calculated in the optimization of step S5, and in step S4, when the node is connected, the load node is powered by the power node transformer with the same electricity fee type. The electricity fee types include residential electricity, industrial and commercial electricity, large industrial electricity and educational electricity. Different load nodes have different electricity fee types. For example, residential electricity is used in residences, commercial electricity is used in shops and restaurants, large industrial electricity is used in charging piles, and educational electricity is used in school teaching buildings. Different types of electricity fees are priced differently, which will lead to different operating electricity costs. The load nodes of this embodiment are connected to power nodes of the same electricity fee type, so that the load nodes are powered by transformers of the same electricity fee type, which is conducive to cost saving and makes the power distribution system of this embodiment more economical and environmentally friendly.

[0068] In step S3, the location information of each power node, load node, and new energy node is obtained. Only by obtaining the location of each node can the nodes be connected to form a topology map, and the line investment of the distribution system can be calculated.

[0069] In step S4, nodes at each level are connected and adjusted according to the location information of each power node, load node, and new energy node to obtain multiple different power distribution schemes; when forming a power distribution scheme, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the peak power consumption of the node is obtained through the load curve.

[0070] After the power distribution plan is formed, the calculation of various economic indicators of the power distribution system cannot be separated from the load curve of each node, and the equipment configuration of the upper-level node also needs to meet the load requirements of the lower-level node, so the load calculation of nodes at all levels is particularly important. In this embodiment, the load curves of the load nodes and new energy nodes are obtained in step S1, and the distribution boxes and transformers of the power supply nodes are formed by superimposing the load curves of the nodes to which they are connected.

[0071] like Figure 4 As shown, the load curve of a node is formed by the superposition of the load curves of all the nodes connected to it. In this embodiment, the load curve of the terminal power supply node is formed by the superposition of the load curves of all the load nodes connected to it. Specifically, the load curve of each connected load node is obtained, and the load values ​​of each load node at the same time point are added together to obtain the load value of the connected terminal power supply node at that time point, thereby obtaining the load curve of the terminal power supply node.

[0072] The specific method of obtaining the peak power consumption of a node in this embodiment is as follows:

[0073] 1. Define vector

[0074] Assume that the time curves of the two loads are L1 and L2, which are at the time point The values ​​are:

[0075]

[0076] 2. Vector addition

[0077] Add these two vectors together to get a new vector :

[0078]

[0079] 3. Calculate the peak value

[0080] vector The maximum value can be calculated by the following formula:

[0081]

[0082] 4. Multi-level computing

[0083] The vector value of the power supply node at the end is obtained by adding the vector values ​​of the end power supply nodes, and the vector value of the secondary power supply node is obtained by adding the vector values ​​of the secondary power supply nodes, and the vector value of the primary power supply node is obtained by adding the vector values ​​of the primary power supply nodes, and the vector value of the power supply node where the transformer is located is obtained by adding the vector values ​​of the primary power supply nodes.

[0084] like Figure 5 As shown, in step S5, the optimization algorithm is used to search for the best among the multiple power distribution schemes obtained, and the best power distribution scheme is output. This embodiment searches for the best according to the minimum investment, the minimum operating energy consumption, the minimum operating electricity cost or a combination of multiple objectives.

[0085] When optimizing the power distribution plan, the following node connection schemes are preferably selected: (1) The load node should be connected to a transformer of the same electricity rate type, and the power supply node with a transformer of the same electricity rate type should be selected; (2) Since this embodiment uses small-scale new energy equipment, the new energy node is directly connected to the transformer of the power supply node.

[0086] The optimization algorithm adopted in step S5 of this embodiment is a genetic algorithm. It should be pointed out that the optimization algorithm can also adopt a simulated annealing algorithm, an ant colony algorithm, a particle swarm algorithm, etc. When searching for the best solution, an optimization target is set in the sample space to find the optimal design scheme for the power distribution system. Taking the output investment optimal power distribution scheme as an example, the optimization target includes the minimum investment, that is, the optimal combination of the number of power sources, power capacity and load distribution scheme. The total cost includes the comprehensive cost of the power supply facilities and the comprehensive cost of the line. The comprehensive cost of the power supply facilities is obtained through the power capacity; the comprehensive cost of the line is calculated by the estimated length of the line obtained through the relationship between the load position and the power position and its unit cost.

[0087] The total investment of the distribution system includes the cost of power supply facilities and lines. The power supply facilities are mainly transformers, and the line cost is determined by the line specifications and line length. The operating energy consumption of the distribution system includes transformer losses and line losses. The operating electricity cost of the distribution system is determined by the power consumption and electricity pricing.

[0088] like Figure 6 As shown, in step S6, the required power distribution scheme is selected from the optimal power distribution scheme obtained in step S5, and according to the matching relationship among the power supply nodes, load nodes, and new energy nodes in the required power distribution scheme and the peak power consumption of the power supply nodes, the optimal configuration of the capacity and number of transformers in each power supply node and the matching relationship between the transformer and the load nodes and new energy nodes are obtained through the optimization algorithm, and the optimized power distribution scheme is output.

[0089] The optimization algorithm adopted in step S6 of this embodiment is a genetic algorithm. It should be noted that the optimization algorithm may also adopt a simulated annealing algorithm, an ant colony algorithm, a particle swarm algorithm, etc.

[0090] In step S3, this embodiment obtains the positions of power nodes, load nodes, and new energy nodes, randomly matches load nodes with power nodes, and matches new energy nodes with nearby power nodes, to obtain multiple power distribution schemes. An optimization algorithm is used to search for the best solution, and constraints are added during the search: the electricity fee type of the load node is the same as the transformer of the power node to which it is connected; the effective distance between the power node and the load node is less than 200m. Adding constraints can improve the efficiency of the search.

[0091] After the optimization, the optimal power distribution plan is obtained, and thus the power consumption peak values ​​of the power supply nodes of each optimal power distribution plan can be obtained. The minimum power consumption peak value of the power supply node is obtained by comparison, and then the optimal matching relationship between the power supply node and the load node in the optimal power distribution plan to which the minimum power consumption peak value of the power supply node belongs is obtained.

[0092] like Figure 7 As shown, in step S7, according to the operating condition classification of the load node, the optimized distribution plan obtained in step S6 is used to check the capacity of the transformer and the distribution boxes at each level through different operating conditions of the load node. If the safety requirements are not met, the transformer capacity and the capacity of the distribution boxes at each level are increased to obtain the final transformer capacity and distribution plan.

[0093] In step S2 of the present embodiment, the operating condition classification includes normal operating conditions and firefighting operating conditions; in step S7, the optimized power distribution plan outputted in step S6 is obtained, and the guaranteed loads according to the firefighting operating conditions or normal operating conditions of the load nodes are added to obtain the guaranteed loads. If the transformer capacity of the power supply node is not less than the sum of the guaranteed loads of all the nodes connected to it, no adjustment is made; if the transformer capacity of the power supply node is less than the sum of the guaranteed loads of all the nodes connected to it, the transformer capacity is adjusted up by one level.

[0094] In step S2, the operating condition classification of the load node is obtained, which can be divided into normal operating conditions and firefighting conditions, and specifically divided into ordinary load, normal guaranteed load, firefighting guaranteed load, and normal and firefighting guaranteed load. Normal guaranteed load refers to the load that ensures power supply under normal operating conditions. Firefighting guaranteed load refers to the load that ensures power supply under firefighting conditions (power outage). Normal and firefighting guaranteed load refers to the load that needs to ensure power supply under both normal operating conditions and firefighting conditions.

[0095] The safety check uses the load capacity, without considering the load curve, and the required coefficient Kd is 1.0. When referring to the time characteristic curve of the load, some time characteristic curves multiply the load capacity by the required coefficient at each time. The required coefficient Kd of this embodiment is 1.0, which is completely based on the load capacity, so that the safety considerations are more secure.

[0096] After performing steps S1-S6, a desired optimized power distribution plan has been obtained, the transformers and distribution boxes have been selected, and the load capacity of each transformer and distribution box can be obtained, so the load capacity can be used during safety verification.

[0097] The inspection details are as follows:

[0098] (1) Fire condition verification method:

[0099] Get the actual load capacity of the upper node. The actual load capacity of the upper node is determined by the equipment selection of the upper node.

[0100] Get the first theoretical load capacity of the upper node. If the upper node is the upper power node of the load node, then the first theoretical load capacity of the upper node = the ensured load power of the load node with "fire-fighting ensured load" + the ensured load power of the load node with "normal and fire-fighting ensured load"; if the upper node is a power node other than the upper power node of the load node, then the first theoretical load capacity of the upper node = the load power of the lower node with "fire-fighting ensured load" + the ensured load power of the lower node with "normal and fire-fighting ensured load". The ensured load power is the power to ensure the operation of the load. When calculating, the theoretical load capacity is also the sum of the ensured load powers of all the lower nodes connected to the upper node, and is calculated from the load node upward step by step.

[0101] For example, the power node 1 of the terminal electrical box is connected to load nodes 1 (fire protection load), load node 2, load node 3 (fire protection load), load node 4 (normal and fire protection load), and load node 5. The power node 2 of the terminal electrical box is connected to load nodes 6, load node 7 (fire protection load), load node 8 (fire protection load), load node 9 (normal and fire protection load), and load node 10.

[0102] Then the first theoretical load capacity of the power supply node 1 of the terminal power box = the load power of load node 1 + the load power of load node 3 + the load power of load node 4;

[0103] The first theoretical load capacity of the power supply node 2 of the terminal power box = the load power of the load node 7 + the load power of the load node 8 + the load power of the load node 9;

[0104] The first theoretical load capacity of the secondary power node which only connects the power node 1 of the end power box and the power node 2 of the end power box is: the first theoretical load capacity of the secondary power node = the first theoretical load capacity of the power node 1 of the end power box + the first theoretical load capacity of the power node 2 = the load power of load node 1 + the load power of load node 3 + the load power of load node 4 + the load power of load node 7 + the load power of load node 8 + the load power of load node 9.

[0105] Verification requirements:

[0106] The actual load capacity of the upper node>the first theoretical load capacity of the upper node.

[0107] That is to say, the actual load capacity of the upper node must be greater than the first theoretical load capacity of the upper node. If the verification fails, the capacity of the transformer is adjusted up by one level until the verification requirements are met.

[0108] (2) Normal working condition calibration method:

[0109] Get the actual load capacity of the upper node. The actual load capacity of the upper node is determined by the equipment selection of the upper node.

[0110] Get the second theoretical load capacity of the upper node. If the upper node is the power node of the upper level of the load node, then the second theoretical load capacity of the upper node = the ensured load power of the load node with "usual times ensured load" + the ensured load power of the load node with "usual times and ensured load"; if the upper node is a power node other than the upper level power node of the load node, then the second theoretical load capacity of the upper node = the load power of the lower node with "usual times ensured load" + the ensured load power of the lower node with "usual times and ensured load" . Ensured load power is the power to ensure load operation. When calculating, the theoretical load capacity is also the sum of the ensured load powers of all lower nodes connected to the upper node, and is calculated from the load node upward step by step.

[0111] For example, the power node 1 of the terminal electrical box is connected to load nodes 1, 2 (load is ensured at ordinary times), 3, 4 (load is ensured at ordinary times and at other times), and 5 (load is ensured at ordinary times). The power node 2 of the terminal electrical box is connected to load nodes 6 (load is ensured at ordinary times), 7, 8, 9 (load is ensured at ordinary times and at other times), and 10 (load is ensured at ordinary times).

[0112] Then the second theoretical load capacity of the power supply node 1 of the terminal power box = the load power of the load node 2 + the load power of the load node 4 + the load power of the load node 5;

[0113] The second theoretical load capacity of the power supply node 2 of the terminal power box = the load power of the load node 6 + the load power of the load node 9 + the load power of the load node 10;

[0114] The second theoretical load capacity of the secondary power node which only connects the power node 1 of the terminal power box and the power node 2 of the terminal power box is: the second theoretical load capacity of the secondary power node = the second theoretical load capacity of the power node 1 of the terminal power box + the second theoretical load capacity of the power node 2 = the load power of load node 2 + the load power of load node 4 + the load power of load node 5 + the load power of load node 6 + the load power of load node 9 + the load power of load node 10.

[0115] Verification requirements:

[0116] The actual load capacity of the upper node>the second theoretical load capacity of the upper node.

[0117] That is to say, the actual load capacity of the upper node must be greater than the second theoretical load capacity of the upper node. If the verification fails, the capacity of the transformer is adjusted up by one level until the verification requirements are met.

[0118] Embodiment 2

[0119] like Figure 8 As shown, the difference between this embodiment and the first embodiment is that the planning method of this embodiment also considers flexible load.

[0120] In step S2 of this embodiment, the classification information of the load node also includes flexibility classification, and the flexibility classification divides the load node into a flexible load node and a non-flexible load node, the non-flexible load node is connected to a transformer of the power node, and the flexible load node is connected to two or more transformers of the power node;

[0121] In step S4, when nodes are connected, only non-flexible load nodes are connected;

[0122] In step S6, after the optimized power distribution plan is output, a flexible load node is added, and the load curve of the power node connected to the flexible load node is superimposed on the load curve of the flexible load node to obtain a new power consumption peak of the power node. If the transformer configuration capacity of the power node is not less than the new power consumption peak of the power node, the configuration and matching relationship of the transformer capacity and number of units are not adjusted, and a new optimized power distribution plan is output; if the transformer configuration capacity of the power node is less than the new power consumption peak of the power node, the level of the transformer capacity is adjusted, and a new optimized power distribution plan is output;

[0123] In step S7, the new optimized power distribution scheme is safety checked according to the operating condition classification of the load nodes.

[0124] Specifically, the power distribution system planning method of this embodiment includes the following steps:

[0125] S1: Obtain the load curve of each load node and new energy node;

[0126] S2: Obtain classification information of load nodes, including operating condition classification, electricity fee type classification, and flexibility classification; the flexibility classification divides load nodes into flexible load nodes and non-flexible load nodes, where non-flexible load nodes are connected to a transformer of a power source node, and flexible load nodes are connected to two or more transformers of a power source node;

[0127] S3: Obtain the location information of each power node, load node, and new energy node;

[0128] S4: Determine whether the load node is a flexible load node. If it is a flexible load node, exclude the flexible load node; connect and adjust the nodes at each level according to the location information of each power node, non-flexible load node, and new energy node to obtain multiple different power distribution schemes; wherein, when connecting nodes, only non-flexible load nodes are connected. When forming a power distribution scheme, the load curve of the upper-level node is formed by superimposing the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve;

[0129] S5: searching for the best solution among the multiple power distribution solutions obtained through an optimization algorithm, and outputting the optimal power distribution solution;

[0130] S6: In the optimal power distribution plan obtained in step S5, the required power distribution plan is selected, and according to the matching relationship among the power nodes, load nodes, and new energy nodes in the required power distribution plan and the peak power consumption of the power nodes, the optimal configuration of the transformer capacity and number of units in each power node and the matching relationship between the transformer and the load nodes and new energy nodes are obtained through the optimization algorithm, and the optimized power distribution plan is output; after the optimized power distribution plan is output, the flexible load node is added, and the load curve of the power node connected to the flexible load node is superimposed on the load curve of the flexible load node to obtain the new peak power consumption of the power node; if the transformer configuration capacity of the power node is not less than the new peak power consumption of the power node, the configuration and matching relationship of the transformer capacity and number are not adjusted, and a new optimized power distribution plan is output; if the transformer configuration capacity of the power node is less than the new peak power consumption of the power node, the level of the transformer capacity is adjusted, and a new optimized power distribution plan is output;

[0131] S7: According to the operating condition classification of the load node, a new optimized power distribution plan is obtained for step S6. The capacity of the transformer and the distribution boxes at each level is verified through the different operating conditions of the load node. If the safety requirements are not met, the capacity of the transformer and the capacity of the distribution boxes at each level are increased to obtain the final transformer capacity and power distribution plan.

[0132] Therefore, it should be noted that in this embodiment, when forming multiple power distribution schemes in step S4, non-flexible load nodes, new energy nodes and power supply nodes are connected. The first optimization in step S5 and the second optimization in step S6 are performed without flexible load nodes.

[0133] After the second optimization in step S6, a flexible load node is added. The two or more transformers connected to the flexible load node may be transformers of the same power node or different power nodes. After the flexible load node is added, the load curves of the connected power nodes are added with the load curve of the flexible load node to obtain a new peak power consumption.

[0134] In order to obtain the best power distribution solution, considering the line cost, the two or more transformers connected to the flexible load node in this embodiment belong to the same power node. In addition, according to the principle of proximity, the flexible load node is connected to the power node closest to it.

[0135] The transformer to which the flexible load node is specifically connected can be specified by the user, or the transformer with the lowest capacity in the power node and the transformer in the same group as the transformer with the lowest capacity can be connected by default.

[0136] After adding the flexible load node, the load curve of the transformer connected to the flexible load node is obtained, and the load curve of the flexible load node is added to the load curve of the connected transformer. Specifically, the load curve of the flexible load node is added to the real-time minimum load curve of the connected transformer to obtain the flexible load input time period, and then obtain the transformer switching time of the flexible load node, that is, during the peak period of a certain transformer, the flexible load node must be powered by a candidate transformer with a lower load rate.

[0137] The above-mentioned real-time minimum load curve refers to the curve of the real-time minimum values ​​of all transformers connected to the flexible load node changing over time, wherein the real-time minimum value is the load peak value of the transformer with the smallest load peak value among all transformers connected to the flexible load node at the same time. The load curve of the flexible load node is added to the real-time minimum load curve to verify whether the transformer capacity meets the safety requirements after adding the flexible load node. The transformer capacity needs to be greater than the sum of the peak value of the flexible load node and the peak value of the real-time minimum load curve, that is, the transformer capacity> the peak value of the flexible load node + the peak value of the real-time minimum load curve.

[0138] Other aspects of this embodiment are the same as those of the first embodiment and will not be described in detail here.

[0139] Embodiment 3

[0140] like Fig. 9As shown, an embodiment of the present invention provides a planning system for a power distribution system, including:

[0141] The load curve acquisition module is used to obtain the load curves of each load node and new energy node;

[0142] A classification information acquisition module is used to obtain classification information of load nodes, and the classification information includes working condition classification;

[0143] A location information acquisition module is used to obtain the location information of each power node, load node, and new energy node;

[0144] The power distribution plan generation module is used to connect and adjust nodes at each level according to the location information of each power node, load node, and new energy node to obtain multiple different power distribution plans. When forming a power distribution plan, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve;

[0145] The first optimization module is used to search for the best among the multiple power distribution schemes obtained by using an optimization algorithm and output the optimal power distribution scheme;

[0146] The second optimization module is used to select a required power distribution scheme from the optimal power distribution scheme obtained by the first optimization module, and obtain the optimal configuration of transformer capacity and number in each power node and the matching relationship between the transformer and the load node and the new energy node through an optimization algorithm according to the matching relationship among the power nodes, load nodes and new energy nodes in the required power distribution scheme and the peak power consumption of the power nodes, and output the optimized power distribution scheme;

[0147] The safety verification module classifies the operating conditions of the load nodes and verifies the capacity of the transformer and distribution boxes at all levels for the optimized distribution plan obtained by the second optimization module through different operating conditions of the load nodes. If the safety requirements are not met, the transformer capacity and the capacity of the distribution boxes at all levels are increased to obtain the final transformer capacity and distribution plan.

[0148] Embodiment 4

[0149] An embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the power distribution system planning method described in Embodiment 1 or Embodiment 2 when executing the computer program.

[0150] Embodiment 5

[0151] An embodiment of the present invention provides a computer storage medium on which a computer program is stored. When the computer program is executed by a processor, the power distribution system planning method described in Embodiment 1 or Embodiment 2 is implemented.

[0152] In summary, the embodiment of the present invention provides a distribution system planning method, which forms different distribution schemes by adjusting the topological relationship between power nodes, load nodes and new energy nodes, and performs optimization through an optimization algorithm to output the optimal distribution scheme, which can reduce the peak capacity of the power node and achieve the optimization of the distribution system; the peak capacity of the power node is obtained by superimposing the load curves of all nodes connected to the power node, and then the transformer configuration in the power node is optimized through the optimization algorithm, so as to obtain the best, most reasonable and most economical transformer configuration, avoiding the problem of transformer selection being too large. In addition, the present invention takes new energy nodes into consideration during planning, and the new energy nodes participate in the peak calculation of the power node, which can further reduce the expected transformer capacity of the power node and achieve optimization. The present invention also performs safety verification to ensure the safety of the planned distribution system.

[0153] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A power distribution system planning method, characterized in that: The steps include: S1: Obtain the load curve of each load node and new energy node; S2: Obtain classification information of load nodes, the classification information includes working condition classification; S3: Obtain the location information of each power node, load node, and new energy node; S4: According to the location information of each power node, load node, and new energy node, the nodes at each level are connected and adjusted to obtain multiple different power distribution schemes; when forming the power distribution scheme, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve; S5: searching for the best solution among the multiple power distribution solutions obtained through an optimization algorithm, and outputting the optimal power distribution solution; S6: In the optimal power distribution plan obtained in step S5, the required power distribution plan is selected, and according to the matching relationship among the power supply nodes, load nodes, and new energy nodes in the required power distribution plan and the peak power consumption of the power supply nodes, the optimal configuration of the transformer capacity and number in each power supply node and the matching relationship among the transformer, load nodes, and new energy nodes are obtained through an optimization algorithm, and the optimized power distribution plan is output; S7: According to the working condition classification of the load node, for the optimized power distribution plan obtained in step S6, the capacity of the transformer and the distribution boxes at all levels are verified by different working conditions of the load node. If the safety requirements are not met, the capacity of the transformer and the capacity of the distribution boxes at all levels are increased to obtain the final transformer capacity and power distribution plan; In step S2, the operating condition classification includes normal operating condition and fire-fighting operating condition; When checking the fire condition, in step S7, the optimized power distribution plan outputted in step S6 is obtained, and the guaranteed load according to the fire condition of the load node is added to obtain the guaranteed load. If the transformer capacity of the power supply node is not less than the sum of the guaranteed loads of all nodes connected to it, no adjustment is made; If the transformer capacity of the power node is less than the sum of the guaranteed loads of all nodes connected to it, the transformer capacity will be increased by one level; When performing normal operating condition verification, in step S7, the optimized power distribution plan output by step S6 is obtained, and the guaranteed load according to the normal operating condition of the load node is added to obtain the guaranteed load. If the transformer capacity of the power supply node is not less than the sum of the guaranteed loads of all the nodes connected to it, no adjustment is made; if the transformer capacity of the power supply node is less than the sum of the guaranteed loads of all the nodes connected to it, the transformer capacity is adjusted up by one level.

2. The power distribution system planning method according to claim 1, characterized in that: In step S1, a load curve is outputted through a power load prediction model corresponding to the load node and the new energy node.

3. The power distribution system planning method according to claim 1, characterized in that: In step S2, the classification information of the load node also includes flexibility classification, and the flexibility classification divides the load node into a flexible load node and a non-flexible load node, the non-flexible load node is connected to a transformer of the power node, and the flexible load node is connected to two or more transformers of the power node; In step S4, when nodes are connected, only non-flexible load nodes are connected; In step S6, after the optimized power distribution plan is output, a flexible load node is added, and the load curve of the power node connected to the flexible load node is superimposed on the load curve of the flexible load node to obtain a new power consumption peak of the power node. If the transformer configuration capacity of the power node is not less than the new power consumption peak of the power node, the configuration and matching relationship of the transformer capacity and number of units are not adjusted, and a new optimized power distribution plan is output; if the transformer configuration capacity of the power node is less than the new power consumption peak of the power node, the level of the transformer capacity is adjusted, and a new optimized power distribution plan is output; In step S7, the new optimized power distribution scheme is safety checked according to the operating condition classification of the load nodes.

4. The power distribution system planning method according to claim 1, characterized in that: The optimization algorithms of step S5 and step S6 both adopt genetic algorithm.

5. The power distribution system planning method according to claim 1, characterized in that: In step S2, the load node classification also includes electricity rate type classification. In step S4, the load node is connected to a power supply node of the same electricity rate type as the load node, so that the load node is powered by a transformer of the same electricity rate type.

6. The power distribution system planning method according to claim 1, characterized in that: In step S5, optimization is performed based on minimum investment, minimum operating energy consumption, minimum operating electricity cost or a combination of multiple objectives.

7. A planning system for a power distribution system, characterized in that: include: The load curve acquisition module is used to obtain the load curves of each load node and new energy node; A classification information acquisition module is used to obtain classification information of load nodes, and the classification information includes working condition classification; A location information acquisition module is used to obtain the location information of each power node, load node, and new energy node; The power distribution plan generation module is used to connect and adjust nodes at each level according to the location information of each power node, load node, and new energy node to obtain multiple different power distribution plans. When forming a power distribution plan, the load curve of the upper-level node is superimposed by the load curves of all the lower-level nodes connected to the node, and the power consumption peak of the node is obtained through the load curve; The first optimization module is used to search for the best among the multiple power distribution schemes obtained by using an optimization algorithm and output the optimal power distribution scheme; The second optimization module is used to select a required power distribution scheme from the optimal power distribution scheme obtained by the first optimization module, and obtain the optimal configuration of transformer capacity and number in each power node and the matching relationship between the transformer and the load node and the new energy node through an optimization algorithm according to the matching relationship among the power nodes, load nodes and new energy nodes in the required power distribution scheme and the peak power consumption of the power nodes, and output the optimized power distribution scheme; The safety verification module, according to the operating condition classification of the load node, verifies the capacity of the transformer and the distribution boxes at all levels for the optimized distribution plan obtained by the second optimization module through different operating conditions of the load node. If the safety requirements are not met, the capacity of the transformer and the capacity of the distribution boxes at all levels are increased to obtain the final transformer capacity and distribution plan; The working condition classification includes normal working condition and fire-fighting working condition; When checking the fire condition, the safety check module obtains the optimized power distribution plan output by the second optimization module, adds the guaranteed load according to the fire condition of the load node, and obtains the guaranteed load. If the transformer capacity of the power supply node is not less than the sum of the guaranteed loads of all nodes connected to it, no adjustment is made; If the transformer capacity of the power node is less than the sum of the guaranteed loads of all nodes connected to it, the transformer capacity will be increased by one level; When performing normal operating condition verification, the safety verification module obtains the optimized power distribution plan output by the second optimization module, adds the ensured load according to the normal operating condition of the load node, and obtains the guaranteed load. If the transformer capacity of the power supply node is not less than the sum of the guaranteed loads of all the nodes connected to it, no adjustment is made; if the transformer capacity of the power supply node is less than the sum of the guaranteed loads of all the nodes connected to it, the transformer capacity is adjusted up by one level.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the power distribution system planning method according to any one of claims 1 to 6 is implemented.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the power distribution system planning method described in any one of claims 1 to 6 is implemented.

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