Method and system for defining responsibility boundary of novel grid-connected main body of distribution network

Abstract

The invention relates to a method and system for defining a responsibility boundary based on a novel grid-connected main body of a distribution network, and the method comprises the steps: carrying out the feature analysis of the novel grid-connected main body of the distribution network, and determining the features used for defining a dispatching management responsibility boundary; the method comprises the following steps: collecting operation parameters of a novel grid-connected main body of a distribution network, and preprocessing the operation parameters to obtain standard format data; according to the characteristics and the standard format data, constructing a scheduling management responsibility boundary model of the novel grid-connected main body of the distribution network; obtaining a dispatching management responsibility boundary of the novel grid-connected main body of the distribution network according to the dispatching management responsibility boundary model; and based on a dynamic feedback mechanism, according to the running state of the power grid and the real-time change data of the novel grid-connected main body of the distribution network, adjusting the scheduling management responsibility boundary of the novel grid-connected main body of the distribution network to obtain an optimal scheduling management responsibility boundary. And the scheduling efficiency and the operation stability of the power distribution network are improved.

Description

Technical Field

[0001] The present invention belongs to the field of distribution network dispatching management, and particularly relates to a method and system for defining the responsibility boundary of a new type of grid-connected entity in a distribution network. Background Art

[0002] With the wide application of new types of grid-connected entities in the distribution network such as distributed power sources, new energy storage, virtual power plants, and microgrids, the dispatching management of the distribution network faces increasingly complex challenges.

[0003] The traditional dispatching management mode cannot adapt to the dynamics and uncertainties of these new entities, and lacks a clear definition of the dispatching responsibility boundaries of each entity. Therefore, how to reasonably divide the dispatching management responsibilities of grid-connected entities and improve the dispatching efficiency and operation stability of the distribution network has become an urgent problem to be solved.

[0004] Currently, distributed resources are not included in the grid regulation and management responsibilities, and the research on the flexible dispatching management mode of new types of grid-connected entities in the distribution network has not been carried out; the processes and mechanisms for new types of grid-connected entities in the distribution network to participate in demand response are not yet perfect. Currently, the regulation boundaries and aggregation scopes for adjustable loads have not been determined, and the aggregation boundaries and dispatching management modes of large virtual power plants are not yet clear. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a method and system for defining the responsibility boundary of a new type of grid-connected entity in a distribution network.

[0006] The technical solution adopted by the present invention is as follows:

[0007] In the first aspect, a method for defining the responsibility boundary of a new type of grid-connected entity in a distribution network is provided, including:

[0008] Performing feature analysis on the new type of grid-connected entity in the distribution network to determine the features for defining the dispatching management responsibility boundary;

[0009] Collecting the operation parameters of the new type of grid-connected entity in the distribution network, and preprocessing the operation parameters to obtain data in a standard format;

[0010] According to the features and the data in the standard format, constructing a dispatching management responsibility boundary model for the new type of grid-connected entity in the distribution network;

[0011] Obtaining the dispatching management responsibility boundary of the new type of grid-connected entity in the distribution network according to the dispatching management responsibility boundary model;

[0012] Based on a dynamic feedback mechanism, adjusting the dispatching management responsibility boundary of the new type of grid-connected entity in the distribution network according to the grid operation state and the real-time change data of the new type of grid-connected entity in the distribution network to obtain an optimal dispatching management responsibility boundary.

[0013] Further, conduct a feature analysis on the new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities, including:

[0014] Obtain the boundary of dispatching management responsibilities of known grid-connected entities; the known grid-connected entities include power grid operators and power plants;

[0015] Analyze different types of new grid-connected entities in the distribution network from four dimensions of technology, economy, management, and responsibility, rights, and interests to obtain the dispatching management responsibilities of different types of new grid-connected entities in the distribution network;

[0016] Compare and analyze the boundary of dispatching management responsibilities of known grid-connected entities and the dispatching management responsibilities of each new grid-connected entity in the distribution network to determine the features for defining the boundary of dispatching management responsibilities of each new grid-connected entity in the distribution network.

[0017] Further, collect the operation parameters of new grid-connected entities in the distribution network, and preprocess the operation parameters to obtain data in a standard format, including:

[0018] Obtain the operation parameters of new grid-connected entities in the distribution network;

[0019] Perform noise removal processing and missing value filling processing on the operation parameters;

[0020] Normalize the operation parameters after noise removal processing and missing value filling processing, and convert them into standard format data in a unified standard format.

[0021] Further, according to the features and standard format data, construct a boundary model for the dispatching management responsibilities of new grid-connected entities in the distribution network, including:

[0022] Determine the location of each new grid-connected entity in the distribution network according to the features;

[0023] Divide the dispatching management responsibilities of each new grid-connected entity in different operating states according to the location;

[0024] According to the standard format data and dispatching management responsibilities, construct a boundary model for the dispatching management responsibilities based on the K-means clustering algorithm of machine learning.

[0025] Further, according to the standard format data and dispatching management responsibilities, construct a boundary model for the dispatching management responsibilities based on the K-means clustering algorithm of machine learning, including:

[0026] According to the standard format data and dispatching management responsibilities;

[0027] Divide the dispatching management responsibilities of each time period and different new grid-connected entities in the distribution network into multiple dispatching responsibility groups;

[0028] Establish a dispatching responsibility matrix Y for each dispatching responsibility group, and Y is:

[0029]

[0030] where y ij represents the value of the dispatching management responsibility of the new grid-connected entity j in the power distribution network during the time period t i ; m is the number of time periods; n represents the number of new grid-connected entities in the power distribution network;

[0031] The K-means clustering algorithm is used to construct the dispatching management responsibility boundary model, and the data points composed of time periods and dispatching management responsibilities are assigned to k clusters, so that the data points within each cluster have the maximum similarity and the data points between clusters have the minimum similarity. Each cluster corresponds to a dispatching responsibility matrix Y;

[0032]

[0033] where J is the clustering loss function; k is the number of clusters; C i is the i-th cluster; x j is the data point belonging to the cluster C i and represents the time period t i and the dispatching management responsibility of the new grid-connected entity j in the power distribution network, μ i is the center point of the cluster C i and represents the average value of all data points in the cluster; S i is the set of data points of the i-th clustering, and |S i | represents the number of data points.

[0034] Furthermore, based on the dynamic feedback mechanism, according to the grid operation status, different scenario requirements, and the real-time change data of the new grid-connected entities in the power distribution network, the dispatching management responsibility boundary of the new grid-connected entities in the power distribution network is adjusted to obtain the optimal dispatching management responsibility boundary, including:

[0035] Based on the dynamic feedback mechanism, a grid operation objective function is set. The grid operation objective function is used to minimize the power difference between the actual power output of the grid and the grid demand power and optimize the grid voltage so that the grid voltage reaches the desired target;

[0036] The power deviation and voltage deviation are obtained by real-time detecting the grid operation objective function, and the value of the dispatching management responsibility boundary of the new grid-connected entities in the power distribution network is adjusted;

[0037] According to the value of the adjusted dispatching management responsibility boundary, the dispatching responsibility matrix Y is updated;

[0038] The optimal dispatching management responsibility boundary is obtained according to the updated dispatching responsibility matrix Y.

[0039] Furthermore, the expression of the grid operation objective function is:

[0040]

[0041] Among them, P total (t) is the actual output power of the power grid at time t, and P demand is the power demand of the power grid, V total is the power grid voltage, and V target is the expected target of the power grid voltage. w1 and w2 are preset weight coefficients.

[0042] Furthermore, the power deviation and voltage deviation are obtained by real-time detecting the power grid operation objective function, and the value of the scheduling management responsibility boundary of the new grid-connected entity in the distribution network is adjusted, including:

[0043] The power grid operation objective function is detected in real time to obtain the power deviation e p (t) = P total (t) - P demand (t) and the voltage deviation e v (t) = V total (t) - V target (t);

[0044] According to the power deviation e p (t) and the voltage deviation e v (t), the adjustment amount Δy i (t) for adjusting the scheduling management responsibility boundary of the new grid-connected entity in the distribution network is obtained. The expression of the adjustment amount Δy i (t) is:

[0045]

[0046] Among them, Kp, Ki, and Kd are the preset proportional coefficient, preset integral coefficient, and preset differential coefficient respectively. ∑ t e(t)·Δt represents the preset long-term deviation accumulation, represents the deviation change rate;

[0047] According to the adjustment formula y i (t) = y i (t - 1) + α·Δty i (t), the value y i (t - 1) of the scheduling management responsibility boundary is adjusted by inputting the adjustment amount Δy i (t) to obtain y i (t).

[0048] In the second aspect, a system for defining the responsibility boundary of a new grid-connected entity in the distribution network is provided, including:

[0049] A feature analysis module, which is used to analyze the features of new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities;

[0050] A data processing module, which is used to collect the operation parameters of new grid-connected entities in the distribution network and preprocess the operation parameters to obtain data in a standard format;

[0051] A model construction module, which is used to construct a dispatching management responsibility boundary model for new grid-connected entities in the distribution network according to the features and the data in the standard format;

[0052] A dispatching management responsibility boundary definition module, which is used to obtain the dispatching management responsibility boundary of new grid-connected entities in the distribution network according to the dispatching management responsibility boundary model;

[0053] A dispatching management responsibility boundary optimization module, which is used to adjust the dispatching management responsibility boundary of new grid-connected entities in the distribution network based on a dynamic feedback mechanism according to the grid operation state and the real-time change data of new grid-connected entities in the distribution network to obtain an optimal dispatching management responsibility boundary.

[0054] The beneficial effects achieved by the present invention:

[0055] Analyze the features of new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities; collect the operation parameters of new grid-connected entities in the distribution network and preprocess the operation parameters to obtain data in a standard format; construct a dispatching management responsibility boundary model for new grid-connected entities in the distribution network according to the features and the data in the standard format; obtain the dispatching management responsibility boundary of new grid-connected entities in the distribution network according to the dispatching management responsibility boundary model; based on a dynamic feedback mechanism, adjust the dispatching management responsibility boundary of new grid-connected entities in the distribution network according to the grid operation state and the real-time change data of new grid-connected entities in the distribution network to obtain an optimal dispatching management responsibility boundary. By dynamically allocating the dispatching management responsibility boundary of new grid-connected entities in the distribution network and optimizing the feedback mechanism, the problems of fuzzy dispatching management responsibilities and uneven resource allocation in a complex distribution network environment are solved, and the dispatching efficiency and operation stability of the distribution network are improved. Description of the Drawings

[0056] Figure 1 It is a flowchart of a method for defining the responsibility boundary of a new grid-connected entity in the distribution network according to the present invention;

[0057] Figure 2 It is a structural diagram of a system for defining the responsibility boundary of a new grid-connected entity in the distribution network according to the present invention. Detailed Embodiments

[0058] The present invention will be further described below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and cannot be used to limit the protection scope of the present invention.

[0059] AsFigure 1 As shown in Figure 1 , an embodiment of the present invention provides a method for defining the responsibility boundary of a new grid-connected entity in a distribution network, including:

[0060] 101. Analyze the characteristics of the new grid-connected entity in the distribution network to determine the characteristics for defining the responsibility boundary of dispatching management;

[0061] Obtain the dispatching management responsibility boundaries of known grid-connected entities; the known grid-connected entities include grid operators and power plants; in a traditional distribution network, the dispatching management responsibilities are mainly shared by entities such as grid operators, power plants, and consumers; grid operators are responsible for the stability and operation dispatching of the power grid, power plants are responsible for power generation, and consumers rely on the stable power provided by the power grid; therefore, the known grid-connected entities are mainly grid operators and power plants;

[0062] The dispatching management responsibilities of grid operators are:

[0063]

[0064] Among them, P grid (t) is the power supply power of the power grid at time t; P gen，i (t) is the output power of the i-th power generation source at time t; P load (t) is the total load demand at time t;

[0065] The dispatching management responsibilities of power plants are:

[0066]

[0067] is the maximum output power of the i-th power generation source; is the minimum output power of the i-th power generation source;

[0068] Analyze different types of new grid-connected entities in the distribution network from four dimensions of technology, economy, management, and responsibility, rights, and interests to obtain the dispatching management responsibilities of different types of new grid-connected entities in the distribution network; ensure that new grid-connected entities in the distribution network can efficiently participate in the flexible dispatching process of the distribution network;

[0069] Technical requirements: Each new grid-connected entity in the distribution network needs to have certain technical capabilities to ensure its real-time response in the distribution network dispatching; for example, distributed power sources need to have the ability to automatically adjust output, and energy storage systems need to have the function of fast charging and discharging;

[0070] P out (t)=f(Weather t , P in (t), Controller t );

[0071] P out (t) represents the output power of the grid-connected entity at time t; Weather t represents the meteorological conditions at time t, such as solar radiation, wind speed, etc.; Controller t represents the adjustment strategy of the controller, which is used to adjust the output power;

[0072] Economic requirements: The new grid-connected entities in the distribution network participating in dispatching should have a certain economic incentive mechanism; for example, a virtual power plant can optimize the allocation of resources through the market mechanism, while an energy storage system can arbitrage through the electricity price difference;

[0073] C total (t) = C gen (t) + C maint (t) + C op (t);

[0074] C total (t) represents the total cost at time t; C gen (t) represents the production cost, which depends on the power generation and regulation capacity; C maint (t) represents the equipment maintenance cost, which is usually related to the operation cycle and failure rate of the equipment; C op (t) represents the operation cost, which may include grid connection fees, electricity market trading fees, etc.;

[0075] Management requirements: Each new grid-connected entity in the distribution network needs to be reasonably managed and coordinated; the distribution network operator needs to effectively manage each entity through means such as dispatching instructions and supervision systems;

[0076] MgmtDecision(t) = g(P load (t), P gen (t), GridState(t));

[0077] P load (t) represents the load forecast, indicating the load demand; P gen (t) represents the power generation forecast, indicating the power generation capacity; GridState(t)) represents the grid state, including important grid parameters such as voltage and frequency;

[0078] Responsibility, right and interest requirements: Clearly define the rights and responsibilities of the new grid-connected entities in the distribution network to ensure that they can fulfill their obligations and enjoy the due benefits during the dispatching process;

[0079] R subjecy (i, j) = α * Tech i，j + β * Econ i，j + γ * Mgmt i，j ;

[0080] Tech i，j represents technical requirement parameters, Econ i，j represents economic requirement parameters, Mgmt i，j represents management requirement parameters, where α, β, and γ are weight values;

[0081] Analyze each new grid - connected entity in the distribution network, which are respectively:

[0082] Distributed power analysis: Analyze the power generation capacity, operating status, and power regulation range of distributed power;

[0083] New - type energy storage analysis: Analyze the charge - discharge capacity, energy conversion efficiency, and charge - discharge strategy of energy storage units;

[0084] Virtual power plant analysis: Model the coordination ability of each resource in the virtual power plant to ensure that the output of the virtual power plant meets the dispatching requirements;

[0085] Micro - grid analysis: Analyze the independent operation ability, load demand, and response characteristics when connecting to the grid externally of the micro - grid;

[0086] Based on the above analysis, construct a dispatching model for each new grid - connected entity in the distribution network, and extract features that can be used for boundary definition, such as maximum power output, load regulation ability, response time, etc.;

[0087] Technical requirements:

[0088] T 能力 = f(C 最大 , T 响应 , E 稳定性 );

[0089] Among them, C is the maximum capacity, T is the response time, and E is the stability of power quality;

[0090] Economic requirements:

[0091] E 激励 = α * P 市场 - β * C 运营 ;

[0092] Management requirements:

[0093] M 要求 = γ * P 管理 + δ * T 监控 ;

[0094] Responsibility, right, and interest requirements:

[0095] R 权利 = α * (P 权利 - P 责任 );

[0096] By analyzing the boundary of traditional dispatching management responsibilities and the characteristic requirements of new grid-connected entities in the distribution network, the differences between the two can be clearly identified; the following formula is used to compare the responsibility boundaries between the two:

[0097] Traditional dispatching management model:

[0098] R traditional = f(P gen (t), P load (t), P grid (t));

[0099] The traditional model mainly focuses on the power balance of power generation sources, loads, and the power grid. The dispatching management boundary is relatively simple, and the division of powers and responsibilities among entities is relatively fixed;

[0100] New dispatching management model:

[0101] R new = f(P out (t), C total (t), MgmtDecision(t), R subject (i, j));

[0102] The new model takes into account the dynamic characteristics, economic costs, management decisions, and distribution of powers, responsibilities, and interests of new grid-connected entities in the distribution network. The dispatching management is more complex and flexible;

[0103] By comparison, it can be found that the traditional one focuses on power dispatching within the power grid, while the new one considers the complexity and multi-dimensional characteristics of new grid-connected entities in the distribution network, with more adjustment freedom and flexibility in management decisions;

[0104] Compare and analyze the dispatching management responsibility boundaries of known grid-connected entities and the dispatching management responsibilities of each new grid-connected entity in the distribution network to determine the characteristics of each new grid-connected entity in the distribution network for defining the dispatching management responsibility boundaries;

[0105] 102. Collect the operation parameters of new grid-connected entities in the distribution network and preprocess the operation parameters to obtain data in standard format;

[0106] Obtain the operation parameters of new grid-connected entities in the distribution network. The operation parameters can be power, energy storage power, voltage, current, load prediction, etc.; in addition to the operation parameters, it is also necessary to collect distribution network topology data and meteorological data; the distribution network topology data includes information such as nodes, lines, transformers, etc. of the power system; the meteorological data includes external conditions such as light intensity, temperature, wind speed, etc. that affect renewable energy power generation;

[0107] Perform noise removal processing and missing value filling processing on the operation parameters, and use interpolation or other methods to ensure data integrity;

[0108] Normalize the operating parameters after noise removal processing and missing value filling processing to convert them into standard format data in a unified standard format.

[0109] 103. Based on the features and standard format data, construct a dispatching management responsibility boundary model for new grid-connected entities in the distribution network;

[0110] Determine the location of each new grid-connected entity in the distribution network according to the features; define the roles and functions of new grid-connected entities in the distribution network; The specific locations are as follows:

[0111] Distributed power source: Provide local power supply and participate in the power regulation of the power grid;

[0112] New energy storage: Regulate the peak-valley difference of power and participate in the flexible dispatching of the power market;

[0113] Virtual power plant: Improve the operating efficiency of the power grid by optimizing the dispatching of multiple distributed resources;

[0114] Microgrid: As an independent operating unit, it can switch to the main power grid when needed;

[0115] Divide the dispatching management responsibilities of each new grid-connected entity in the distribution network under different operating states according to the location;

[0116] Distributed power source: When operating normally, be responsible for local power supply; in case of emergency, participate in the regulation of power grid frequency and voltage;

[0117] New energy storage: Release the stored electric energy during the peak power demand; absorb the excess electric energy during the low power demand;

[0118] Virtual power plant: Cooperate with the dispatching instructions to optimize the distributed resources under its management;

[0119] Microgrid: In the off-grid state, be responsible for the internal power balance; after grid connection, follow the main grid dispatching instructions.

[0120] The division of the handling responsibilities of each new grid-connected entity in the distribution network under the power grid fault state is as follows:

[0121] Distributed power source: Respond quickly and participate in the regulation of frequency and voltage;

[0122] New energy storage: Quickly release the stored electric energy to provide emergency support;

[0123] Virtual power plant: Optimize the dispatching of the distributed resources under its management to ensure the stable recovery of the power grid;

[0124] Microgrid: Act according to the degree of the fault, switch to off-grid operation; cooperate with the dispatching for grid connection when necessary to absorb or provide electric energy;

[0125] According to the standard format data and dispatching management responsibilities;

[0126] Divide the dispatching management responsibilities of each time period and different new grid-connected entities in the distribution network into multiple dispatching responsibility groups;

[0127] Establish a dispatching responsibility matrix Y for each dispatching responsibility group, and Y is:

[0128]

[0129] Among them, y ij represents the value of the dispatching management responsibility of the new grid-connected entity j in the distribution network at time period ti; m is the number of time periods; n represents the number of new grid-connected entities in the distribution network;

[0130] Adopt the K-means clustering algorithm to construct a dispatching management responsibility boundary model, and allocate the data points composed of time periods and dispatching management responsibilities to k clusters, so that the similarity of data points within each cluster is the largest, and the similarity of data points between clusters is the smallest. Each cluster corresponds to a dispatching responsibility matrix Y;

[0131]

[0132] Among them, J is the clustering loss function; k is the number of clusters; C i is the i-th cluster; x j is the data point belonging to the cluster C i , representing the dispatching management responsibility of time period t i and the new grid-connected entity i in the distribution network, x j =[y j1 , y j2 , …, y jn ; μ i is the center point of the cluster C i , representing the average value of all data points in the cluster; S i is the set of data points of the i-th clustering, and |S i | represents the number of data points;

[0133] The steps of the K-means clustering are as follows:

[0134] 1. Initialize the clustering center μ i ;

[0135] 2. Allocate data points: Allocate the dispatching values x j of each time period and each grid-connected entity to the cluster center μ i nearest to it;

[0136] 3. Update the clustering center: Calculate the average value of all data points in each cluster as the new cluster center;

[0137] 4. Iterate until convergence: Repeat steps 2 and 3 until the cluster centers no longer change or the specified number of iterations is reached;

[0138] The clustering algorithm distributes the dispatching responsibilities of each time period and grid-connected entities to k clusters, and each cluster corresponds to a set of dispatching responsibility matrices; the dispatching responsibility matrix Y output by the model reflects the responsibility boundaries in dispatching management according to the attribution of different time periods and grid-connected entities in different clusters.

[0139] 104. Obtain the dispatching management responsibility boundary of the new type of grid-connected entity in the distribution network according to the dispatching management responsibility boundary model;

[0140] 105. Based on the dynamic feedback mechanism, adjust the dispatching management responsibility boundary of the new type of grid-connected entity in the distribution network according to the grid operation status and real-time change data of the new type of grid-connected entity in the distribution network to obtain the optimal dispatching management responsibility boundary.

[0141] Taking the power supply guarantee scenario as the object, clarify the responsibility boundaries between the power grid and the distribution network entities in this scenario. During the operation of the power system, receive system data in real time, analyze it using the intelligent boundary definition model, use time periods as the basic interval, use distributed power sources as emergency backup power, adjust the load demand through the energy storage system, update the dispatching management boundary, and quickly dispatch the new type of grid-connected entity in the distribution network to provide support;

[0142] Real-time monitoring: Obtain the status information of each new type of grid-connected entity in the distribution network in real time through sensors and monitoring systems. When the grid load reaches the critical value, trigger the dynamic adjustment mechanism;

[0143] Dynamic calculation: According to the real-time demand of the power grid in the triggered state, automatically adjust the output of distributed power sources. According to the frequency and voltage conditions of the power grid, use dispatching algorithms (such as linear programming, dynamic programming, etc.) to dynamically allocate dispatching management responsibilities according to the real-time status of each entity (such as power output, energy storage power, load demand, etc.), and dynamically adjust the charging and discharging strategies of the energy storage system to ensure the balance of the power grid;

[0144] Based on the dynamic feedback mechanism, set the power grid operation objective function. The power grid operation objective function is used to minimize the power difference between the actual power output of the power grid and the power demand of the power grid, and optimize the power grid voltage so that the power grid voltage reaches the desired target; the expression of the power grid operation objective function is:

[0145]

[0146] Among them, P total (t) is the actual power output of the power grid at time t, P demand is the power demand of the power grid, V total is the power grid voltage, V target is the desired target of the power grid voltage, and w1 and w2 are preset weight coefficients;

[0147] Real-time detect the power grid operation objective function to obtain the power deviation e p (t) = P total (t) - P demand (t) and the voltage deviation e v (t) = V total (t) - V target (t);

[0148] According to the power deviation e p (t) and the voltage deviation e v (t), obtain the adjustment amount Δy i (t) of the dispatching management responsibility boundary for adjusting the new grid-connected entity in the distribution network by using PID control. The expression of the adjustment amount Δy i (t) is:

[0149]

[0150] wherein, Kp, Ki, and Kd are respectively the preset proportional coefficient, the preset integral coefficient, and the preset differential coefficient, and ∑ t e(t)·Δt represents the preset long-term deviation accumulation, represents the deviation change rate;

[0151] According to the adjustment formula y i (t) = y i (t - 1) + α·Δty i (t), input the adjustment amount Δy i (t) to adjust the value y i (t - 1) of the dispatching management responsibility boundary to obtain y i (t);

[0152] According to the adjusted value of the dispatching management responsibility boundary, update the dispatching responsibility matrix Y;

[0153] Obtain the optimal dispatching management responsibility boundary according to the updated dispatching responsibility matrix Y.

[0154] The beneficial effects achieved by the embodiments of the present invention:

[0155] Conduct feature analysis on the new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities; collect the operation parameters of the new grid-connected entities in the distribution network, and preprocess the operation parameters to obtain data in a standard format; construct a dispatching management responsibility boundary model for the new grid-connected entities in the distribution network according to the features and the standard format data; obtain the dispatching management responsibility boundary of the new grid-connected entities in the distribution network according to the dispatching management responsibility boundary model; based on the dynamic feedback mechanism, adjust the dispatching management responsibility boundary of the new grid-connected entities in the distribution network according to the grid operation status and the real-time change data of the new grid-connected entities in the distribution network to obtain the optimal dispatching management responsibility boundary. Through the dynamic allocation and feedback mechanism optimization of the dispatching management responsibility boundary of the new grid-connected entities in the distribution network, the problems of fuzzy dispatching management responsibilities and uneven resource allocation in the complex distribution network environment are solved, and the dispatching efficiency and operation stability of the distribution network are improved.

[0156] Combined with the method for defining the responsibility boundary of a new grid-connected entity in the distribution network described in the above embodiments, the system for defining the responsibility boundary of a new grid-connected entity in the distribution network will be described below through embodiments.

[0157] As Figure 2 shown, the embodiment of the present invention provides a system for defining the responsibility boundary of a new grid-connected entity in the distribution network, including:

[0158] A feature analysis module 201, configured to conduct feature analysis on the new grid-connected entity in the distribution network to determine the features for defining the boundary of dispatching management responsibilities;

[0159] A data processing module 202, configured to collect the operation parameters of the new grid-connected entity in the distribution network, and preprocess the operation parameters to obtain data in a standard format;

[0160] A model construction module 203, configured to construct a dispatching management responsibility boundary model for the new grid-connected entity in the distribution network according to the features and the standard format data;

[0161] A dispatching management responsibility boundary definition module 204, configured to obtain the dispatching management responsibility boundary of the new grid-connected entity in the distribution network according to the dispatching management responsibility boundary model;

[0162] A dispatching management responsibility boundary optimization module 205, configured to, based on the dynamic feedback mechanism, adjust the dispatching management responsibility boundary of the new grid-connected entity in the distribution network according to the grid operation status and the real-time change data of the new grid-connected entity in the distribution network to obtain the optimal dispatching management responsibility boundary.

[0163] The beneficial effects achieved by the embodiment of the present invention:

[0164] The feature analysis module 201 analyzes the features of the new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities; the data processing module 202 collects the operation parameters of the new grid-connected entities in the distribution network and preprocesses the operation parameters to obtain data in a standard format; the model construction module 203 constructs a dispatching management responsibility boundary model for the new grid-connected entities in the distribution network based on the features and the data in the standard format; the dispatching management responsibility boundary definition module 204 obtains the dispatching management responsibility boundary of the new grid-connected entities in the distribution network according to the dispatching management responsibility boundary model; the dispatching management responsibility boundary optimization module 205 adjusts the dispatching management responsibility boundary of the new grid-connected entities in the distribution network based on a dynamic feedback mechanism according to the grid operation status and the real-time change data of the new grid-connected entities in the distribution network to obtain the optimal dispatching management responsibility boundary. Through the dynamic allocation of the dispatching management responsibility boundary of the new grid-connected entities in the distribution network and the optimization of the feedback mechanism, the problems of fuzzy dispatching management responsibilities and uneven resource allocation in a complex distribution network environment are solved, and the dispatching efficiency and operation stability of the distribution network are improved.

[0165] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0166] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0167] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in Figure 1 one or more of the processes or multiple processes and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0168] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are executed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the steps of the process Figure 1 one process or a plurality of processes and / or blocks Figure 1 steps of the functions specified in one block or a plurality of blocks.

[0169] The above are only embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention pending approval of the application.

Claims

1. A method for defining the responsibility boundary of a new grid-connected entity in a distribution network, characterized in that, Including: Conduct a feature analysis on the new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities; Collect the operation parameters of the new grid-connected entities in the distribution network and preprocess the operation parameters to obtain data in a standard format; Construct a dispatching management responsibility boundary model for the new grid-connected entities in the distribution network according to the features and the data in the standard format; Obtain the dispatching management responsibility boundary of the new grid-connected entities in the distribution network according to the dispatching management responsibility boundary model; Based on a dynamic feedback mechanism, adjust the dispatching management responsibility boundary of the new grid-connected entities in the distribution network according to the grid operation status and the real-time change data of the new grid-connected entities in the distribution network to obtain the optimal dispatching management responsibility boundary.

2. The method for defining the responsibility boundary of the new grid-connected entity in the distribution network according to claim 1, characterized in that, The feature analysis on the new grid-connected entities in the distribution network to determine the features for defining the boundary of dispatching management responsibilities includes: Obtain the dispatching management responsibility boundaries of known grid-connected entities; the known grid-connected entities include grid operators and power plants; Analyze different types of new grid-connected entities in the distribution network from four dimensions of technology, economy, management, and responsibilities, rights, and interests to obtain the dispatching management responsibilities of different types of new grid-connected entities in the distribution network; Compare and analyze the dispatching management responsibility boundaries of the known grid-connected entities and the dispatching management responsibilities of each new grid-connected entity in the distribution network to determine the features for each new grid-connected entity in the distribution network to define the boundary of dispatching management responsibilities.

3. The method for defining the responsibility boundary of the new grid-connected entity in the distribution network according to claim 1, characterized in that, The collection of the operation parameters of the new grid-connected entities in the distribution network and the preprocessing of the operation parameters to obtain data in a standard format includes: Obtain the operation parameters of the new grid-connected entities in the distribution network; Perform noise removal processing and missing value filling processing on the operation parameters; Normalize the operation parameters after noise removal processing and missing value filling processing and convert them into standard format data in a unified standard format.

4. The method for defining the responsibility boundary of the new grid-connected entity in the distribution network according to claim 3, wherein, The construction of the dispatching management responsibility boundary model for the new grid-connected entities in the distribution network according to the features and the data in the standard format includes: Determine the location of each new grid-connected entity in the distribution network according to the features; Divide the dispatching management responsibilities of each new grid-connected entity in different operation states according to the location; Construct a dispatching management responsibility boundary model based on the K-means clustering algorithm of machine learning according to the data in the standard format and the dispatching management responsibilities.

5. The method for defining the responsibility boundary of the new grid-connected entity in the distribution network according to claim 4, characterized in that The construction of the dispatching management responsibility boundary model based on the K-means clustering algorithm of machine learning according to the data in the standard format and the dispatching management responsibilities includes: According to the data in the standard format and the dispatching management responsibilities; Divide the dispatching management responsibilities of each time period and different new grid-connected entities into multiple dispatching responsibility groups; Establish a dispatching responsibility matrix Y for each dispatching responsibility group, and the Y is: Among them, the said y ij represents the value of the dispatching management responsibility of the new grid-connected entity j of the distribution network at time t i ; m is the number of time periods; n represents the number of new grid-connected entities of the distribution network; Adopt the K-means clustering algorithm to construct a dispatching management responsibility boundary model, and allocate the data points composed of time periods and dispatching management responsibilities into k clusters, so that the data points within each cluster have the greatest similarity and the data points between clusters have the smallest similarity, and each cluster corresponds to a dispatching responsibility matrix Y; Wherein, the J is a clustering loss function; the k is the number of clusters; C i is the i-th cluster; x j is a data point belonging to the cluster C i , representing the scheduling management responsibilities of the time period t i and the new grid-connected entity j of the distribution network, x j = [y j1 , y j2 , …, y jn ; μ i is the center point of the cluster C i , representing the average value of all data points in the cluster; S i is the set of data points of the i-th clustering, |S i | represents the number of data points.

6. The method for defining the responsibility boundary of the new grid-connected entity in the distribution network according to claim 5, characterized in that, Based on the dynamic feedback mechanism, according to the grid operation status, different scenario requirements, and the real-time change data of the new grid-connected entities in the distribution network, adjust the boundary of the dispatching management responsibilities of the new grid-connected entities in the distribution network to obtain the optimal boundary of the dispatching management responsibilities, including: Based on the dynamic feedback mechanism, set the grid operation objective function, which is used to minimize the power difference between the actual power output of the grid and the grid demand power, and optimize the grid voltage to make the grid voltage reach the desired target; Detect the grid operation objective function in real time to obtain the power deviation and voltage deviation, and adjust the value of the boundary of the dispatching management responsibilities of the new grid-connected entities in the distribution network; According to the adjusted value of the boundary of the dispatching management responsibilities, update the dispatching responsibility matrix Y; Obtain the optimal boundary of the dispatching management responsibilities according to the updated dispatching responsibility matrix Y.

7. The method for defining the responsibility boundary of the new grid-connected main body in the distribution network according to claim 6, wherein The expression of the grid operation objective function is: Among them, the P total (t) is the actual output power of the power grid at time t, the P demand is the power grid demand power, the V total is the power grid voltage, the V target is the desired target of the power grid voltage, and the w1 and the w2 are preset weight coefficients.

8. The method for defining the responsibility boundary of the new grid-connected entity in the distribution network according to claim 7, characterized in that, The real-time detection of the grid operation objective function to obtain the power deviation and voltage deviation, and adjust the value of the boundary of the dispatching management responsibilities of the new grid-connected entities in the distribution network, including: Detect the power grid operation objective function in real time to obtain the power deviation e p (t) = P total (t) - P demand (t) and the voltage deviation e v (t) = V total (t) - V target (t); According to the power deviation e p (t) and the voltage deviation e v (t), the adjustment amount Δy i (t) for adjusting the dispatching management responsibility boundary of the new grid-connected entity in the distribution network by using PID control is obtained. i (t) The expression of the adjustment amount Δy Among them, the K p , the K i and the K d are a preset proportionality coefficient, a preset integral coefficient, and a preset differential coefficient respectively. The ∑ t e(t)·Δt represents the preset long-term deviation accumulation, and the represents the deviation change rate; According to the adjustment formula y i (t) = y i (t - 1)+α·Δty i (t), input the adjustment amount Δy i (t) for the value y of the boundary of the scheduling management responsibility i (t - 1) is adjusted to obtain y i (t).

9. A system for defining the responsibility boundary of a new grid-connected entity in a distribution network, characterized in that, Including: A feature analysis module, which is used to analyze the features of the new grid-connected entities in the distribution network to determine the features for defining the boundary of the dispatching management responsibilities; A data processing module, which is used to collect the operation parameters of the new grid-connected entities in the distribution network and preprocess the operation parameters to obtain data in a standard format; A model construction module, which is used to construct a model for the boundary of the dispatching management responsibilities of the new grid-connected entities in the distribution network according to the features and the data in the standard format; A boundary definition module for the dispatching management responsibilities, which is used to obtain the boundary of the dispatching management responsibilities of the new grid-connected entities in the distribution network according to the model for the boundary of the dispatching management responsibilities; A boundary optimization module for the dispatching management responsibilities, which is used to adjust the boundary of the dispatching management responsibilities of the new grid-connected entities in the distribution network based on the dynamic feedback mechanism according to the grid operation status and the real-time change data of the new grid-connected entities in the distribution network to obtain the optimal boundary of the dispatching management responsibilities.

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