Mutual aid regulation and control method and system for multiple power distribution areas considering capacity margin

Abstract

The invention relates to the technical field of power system regulation and control, in particular to a mutual aid regulation and control method and system for multiple power distribution transformer areas considering capacity margin, and the multiple power distribution transformer areas comprise N low-load power distribution transformer areas and M high-load power distribution transformer areas which are connected through N + M interconnection devices; the load rate of the low-load power distribution area is less than or equal to a first load rate threshold, and the load rate of the high-load power distribution area is greater than a second load rate threshold; the regulation and control method comprises the following steps: constructing a comprehensive constraint condition based on an economic operation constraint condition and a mutual aid capacity margin constraint condition of a power distribution area; constructing a multi-objective function based on the power distribution area loss objective function and the economic benefit objective function; building a target optimization model through a comprehensive constraint condition and a multi-target function; and obtaining an optimal power distribution scheme based on the target optimization model, and performing hierarchical cooperative control execution. Through the regulation and control method and system, the problem of insufficient load sensitivity can be effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and in particular to a mutual assistance control method and system for multiple distribution substations taking into account capacity margin. Background Art

[0002] With the large-scale integration of distributed power sources such as wind power and photovoltaics into the distribution network, the optimal dispatch of distribution sub-areas is facing complex, multi-dimensional challenges. The inherent randomness and intermittent nature of distributed power sources has led to the transformation of distribution networks from traditional unidirectional passive networks to bidirectional active networks, resulting in multidirectional and fluctuating power flow distribution. Furthermore, alternating underload and overload operation of transformers is common, and the response to sudden load surges and fluctuations in renewable energy output is insufficient. Existing distribution sub-area dispatch systems are clearly limited in addressing these new challenges.

[0003] In the prior art, a Chinese invention patent document with publication number CN113824120A and publication date December 21, 2021 was proposed. The technical solution disclosed in the patent document is as follows: an optimization control method and system for reducing operating losses in multiple substations, including: obtaining power demand data and characteristic data of different distribution substations; constructing a power balance equation for flexible interconnection operation of multiple substations based on the power demand data and characteristic data; establishing objective functions and operating constraints for control objects of multiple substations, and establishing a multi-period and multi-objective optimization control model for flexible interconnection operation of multiple substations based on the objective function, constraints and power balance equation; solving the optimization control model, obtaining optimization control instructions, and controlling the control objects through the optimization control instructions.

[0004] The above technical solution fails to consider the differences in mutual assistance capabilities between substations with different load factors and lacks load sensitivity. In actual use, this could result in low-load substations experiencing power output exceeding equipment safety margins or high-load substations experiencing voltage drops due to over-reliance on mutual assistance. Furthermore, this technical solution fails to consider the impact of load factor thresholds on power mutual assistance decisions. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a mutual assistance control method and system for multiple distribution substations taking into account capacity margin, which can effectively solve the problem of insufficient load sensitivity and allow low-load distribution substations to dynamically transfer redundant power to high-load distribution substations according to the load rate threshold.

[0006] The present invention is achieved by adopting the following technical solutions:

[0007] A mutual assistance control method for multiple distribution substations taking into account capacity margin, wherein the multiple distribution substations include N low-load distribution substations and M high-load distribution substations connected by N+M interconnection devices; the load rate of the low-load distribution substation is less than or equal to a first load rate threshold β i,ref , the load rate of the high-load distribution station area is greater than the second load rate threshold β j,ref ; The control method comprises the following steps:

[0008] Based on the economic operation constraints of the distribution station area and the mutual capacity margin constraints, a comprehensive constraint condition is constructed;

[0009] Construct a multi-objective function based on the distribution station area loss objective function and the economic benefit objective function;

[0010] Building a target optimization model through the comprehensive constraints and multi-objective functions;

[0011] Based on the target optimization model, the optimal power allocation scheme is obtained, and hierarchical collaborative control is executed to achieve dynamic adjustment of power allocation.

[0012] The economic operation constraints are:

[0013] 1.33β JZ,i ≤β i ≤75%,

[0014] 1.33β JZ,j ≤β j ≤75%,

[0015] Where, β JZ,i is the comprehensive economic load coefficient of the i-th low-load distribution station area, β i is the load rate of the i-th low-load distribution station area, β JZ,j is the comprehensive economic load coefficient of the jth high-load distribution station area, β j is the load rate of the jth high-load distribution station area.

[0016] The calculation method of comprehensive economic load factor is:

[0017]

[0018] Where, P i,1 、P i,2 , σ i , β i are the no-load loss, load loss, load fluctuation standard deviation and load rate of the i-th low-load distribution station area respectively; P j,1 、P j,2 , σ j , β jThey are the no-load loss, load loss, load fluctuation standard deviation and load rate of the j-th high-load distribution station area.

[0019] The mutual aid capacity margin constraint condition is:

[0020] 0≤P i ≤P i，max , P i =cosγ i S i ×β i -P i,load ;

[0021] 0≤P j ≤P j,ref , P j =P j,load -cosγ j S j ×β j ;

[0022]

[0023] Where, P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area, P j P is the actual mutual aid power instruction setting value of the jth high-load distribution station area; i，max is the maximum mutually beneficial power of the i-th low-load distribution station area, P j,ref is the power demand of the jth high-load distribution station area; cosγ i 、S i , β i 、P i,load are the AC side power factor, rated capacity, load rate and current load power value of the i-th low-load distribution station area; P j,load , cosγ j 、S j , β j They are respectively the current load power value, AC side power factor, rated capacity and load rate of the jth high-load distribution station area; when P j,ref >P i When the power shortage is reached, the power grid at the high-load distribution station end will provide the remaining power.

[0024] The maximum mutually supportable power P of the i-th low-load distribution station area i，max The calculation method is:

[0025] P i，max =cosγ i S i ×β i,max -P i,load ,

[0026] Where cosγ i 、S i , β i,max 、P i,load are the AC side power factor, rated capacity, load rate upper limit and current load power value of the i-th low-load distribution station area respectively.

[0027] The power requirement P of the jth high-load distribution station area j,ref The calculation method is:

[0028] P j,ref =P j,load -cosγ j S j ×β j,ref ,

[0029] P j,load , cosγ j 、S j , β j,ref They are the current load power value, AC side power factor, rated capacity and expected load rate of the jth high-load distribution station area.

[0030] The multi-objective function is:

[0031]

[0032] Where, P k,loss is the loss objective function of the kth distribution station area, the kth distribution station area refers to the ith low-load distribution station area or the jth high-load distribution station area; R eco is the economic benefit objective function, λ1 is the distribution area loss weight coefficient, and λ2 is the economic benefit weight coefficient. The distribution area loss weight coefficient λ1 and the economic benefit weight coefficient λ2 are dynamically adjusted based on fuzzy logic, and their calculation methods are as follows:

[0033]

[0034] Where μ i (e) is the membership function, and the input variable e is the urgency of the working condition.

[0035] The objective function of the loss of the k-th distribution station area P k,loss The calculation method is:

[0036]

[0037] Where, P k,out is the output power value of the kth distribution station area, η k Given the efficiency of the kth distribution station area, P k,1 is the no-load loss, P k,2 is the load loss, cosγ kand S k are the AC side power factor and rated capacity of the kth distribution station area respectively.

[0038] Economic benefit objective function R eco The calculation method is:

[0039]

[0040] Where K p is the unit power transmission benefit coefficient, P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area.

[0041] A mutual assistance control system for multiple distribution substations taking into account capacity margins, comprising:

[0042] The distribution substation area division unit divides the distribution substation area into N low-load distribution substation areas and M high-load distribution substation areas, and connects the low-load distribution substation area and the high-load distribution substation area through N+M interconnection devices;

[0043] Data acquisition unit, collecting working parameter information of each low-load distribution substation area and high-load distribution substation area;

[0044] The comprehensive constraint condition construction unit constructs comprehensive constraint conditions based on the economic operation constraint conditions and mutual capacity margin constraint conditions of the distribution station area;

[0045] A multi-objective function construction unit constructs a multi-objective function based on the distribution station area loss objective function and the economic benefit objective function;

[0046] A target optimization model building unit, which builds a target optimization model based on the comprehensive constraint conditions and multi-objective functions;

[0047] The control unit obtains the optimal power allocation plan based on the target optimization model, implements hierarchical collaborative control execution, and realizes dynamic adjustment of power allocation.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. This control method can optimize resource allocation among multiple distribution stations and achieve dynamic adjustment of power distribution.

[0050] Specifically, the present invention classifies multiple distribution station areas, and clearly divides the areas into low-load and high-load types by introducing a load rate threshold, and specifically proposes mutual assistance capacity margin constraints and economic operation constraints, which are used to limit the maximum capacity of power mutual assistance and ensure the economic boundary, respectively, fully reflecting the mutual assistance capacity limitations with differentiated load rates.

[0051] Furthermore, the present invention constructs a dual optimization system of loss objective function (technical objective) and economic benefit objective function (economic objective), and dynamically links technical feasibility (such as equipment capacity limitation) and economic indicators (such as electricity price difference) through mutual assistance margin constraints. This can solve the problem in the existing technology that a single loss optimization objective is difficult to drive operators to actively participate in mutual assistance among substations (interconnection device costs need to be invested) and lacks commercial feasibility.

[0052] Finally, by integrating constraints and multi-objective functions to establish a target optimization model, it is possible to allow low-load areas to dynamically transfer redundant power to high-load areas based on the load rate threshold, rather than simply balancing power, and fully reflect the impact of the load rate threshold on the decision-making direction of power mutual assistance. Specifically, through the mutual coordination of the above schemes, the power mutual assistance direction is upgraded from "passive balance" to "active optimization". For example, when the low-load area meets β i ≤β i,ref When power is supplied to high-load areas with high sensitivity to electricity prices, priority is given to powering high-load areas, achieving the dual benefits of loss reduction and peak-valley arbitrage. This process also prevents low-load areas from experiencing excessive power output, which could lead to a decrease in equipment efficiency. Ultimately, a variety of optional optimization strategy combinations can be provided (such as minimum loss, maximum benefit, and balanced solutions).

[0053] 2. In this invention, when constructing comprehensive constraints, a dynamic coupling mechanism can be used to achieve collaborative optimization of technical feasibility and economic optimality. This collaborative optimization allows for precise segmentation of the solution space. Specifically, the comprehensive constraints use the intersection of the technically feasible domain (equipment safety) and the economically feasible domain (profit compliance) as the optimized solution space, thus avoiding invalid solutions such as "safe but loss-making" or "high-profit but overloaded" under independent constraints.

[0054] 3. In the present invention, distribution substations are managed by load rate zoning, which can achieve a multi-objective balance of safety, economy, and efficiency through risk isolation, resource optimization, and technology adaptation. Low-load substations can release redundant capacity to support high-load substations, avoiding frequent capacity expansion investment in high-load substations; high-load substations reduce overload risks and equipment replacement costs by receiving mutual aid power; after zoning, the mutual aid strategy can be dynamically adjusted according to the time-sharing characteristics of electricity prices (such as low-load substations storing energy during valley hours and supplying power to high-load substations during peak hours), thereby maximizing peak-valley arbitrage benefits.

[0055] Furthermore, this zoning scheme can improve power supply reliability and power quality: after zoning, faults in a single substation can be quickly isolated through interconnected devices, preventing the fault from spreading to the entire distribution network (for example, if a high-load substation shorts, low-load substations can still maintain power supply to critical loads). At the same time, independent control of each substation can reduce voltage fluctuations caused by long-distance power transmission, which is particularly suitable for distributed renewable energy access scenarios (for example, when photovoltaic output fluctuates, the substation can adjust the local load balance).

[0056] This zoning scheme also improves O&M efficiency and streamlines management: Zoning allows for high-load areas to be monitored frequently (e.g., hourly temperature checks) while low-load areas to be monitored less frequently (e.g., daily), optimizing O&M resource allocation. Furthermore, based on load importance (Level 1 loads require dual power supplies, while Level 3 loads can operate on a single power supply), zoning strategies prioritize critical loads (e.g., hospitals and data centers) within high-load areas.

[0057] This zoning scheme also ensures equipment safety and longevity: Long-term operation of high-load zones at high load rates can easily lead to equipment overheating, accelerated insulation aging, and even failures; long-term inefficient operation of low-load zones can increase equipment no-load losses. Through load rate threshold zoning management, customized protection can be implemented for different load states (for example, high-load zones prioritize current limiting protection, while low-load zones enable energy-saving mode).

[0058] 4. When constructing a multi-objective function, dynamic weight adaptation is used, that is, fuzzy logic is used to dynamically adjust λ1 (loss weight) and λ2 (economic weight), and the dominant constraint is automatically switched when the load rate changes to avoid constraint priority conflicts and dynamic operating condition mismatches, and to respond to real-time load rate and electricity price fluctuations. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, wherein:

[0060] Figure 1 It is a structural schematic diagram of the present invention;

[0061] Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0062] Example 1

[0063] As a basic embodiment of the present invention, the present invention includes a mutual assistance control method for multiple distribution substations taking into account capacity margin, wherein the multiple distribution substations include N low-load distribution substations and M high-load distribution substations connected by N+M interconnection devices. The load rate of the low-load distribution substation is less than or equal to a first load rate threshold β i,ref , the load rate of the high-load distribution station area is greater than the second load rate threshold β j,ref Based on the distribution station area, the control method includes the following steps:

[0064] Based on the economic operation constraints of the distribution station area and the mutual capacity margin constraints, comprehensive constraints are constructed.

[0065] Based on the distribution station area loss objective function and the economic benefit objective function, a multi-objective function is constructed.

[0066] Through the comprehensive constraints and multi-objective functions, a target optimization model is built.

[0067] Based on the target optimization model, the optimal power allocation scheme is obtained, and hierarchical collaborative control is executed to achieve dynamic adjustment of power allocation.

[0068] Example 2

[0069] As a preferred embodiment of the present invention, the present invention includes a mutual assistance control method for multiple distribution substations taking into account capacity margin, wherein the multiple distribution substations include N low-load distribution substations and M high-load distribution substations connected by N+M interconnection devices. The load rate of the low-load distribution substation is less than or equal to a first load rate threshold β i,ref , the load rate of the high-load distribution station area is greater than the second load rate threshold β j,ref Based on the distribution station area, the control method includes the following steps:

[0070] Based on the economic operation constraints of the distribution station area and the mutual aid capacity margin constraints, a comprehensive constraint condition is constructed. Among them, the economic operation constraint condition is:

[0071] 1.33β JZ,i ≤β i ≤75%,

[0072] 1.33β JZ,j ≤β j ≤75%,

[0073] Where, β JZ,i is the comprehensive economic load coefficient of the i-th low-load distribution station area, β i is the load rate of the i-th low-load distribution station area, β JZ,j is the comprehensive economic load coefficient of the jth high-load distribution station area, β j is the load rate of the jth high-load distribution station area; P i,1 、P i,2 , σ i , β i are the no-load loss, load loss, load fluctuation standard deviation and load rate of the i-th low-load distribution station area respectively; P j,1 、P j,2 , σ j , β j They are the no-load loss, load loss, load fluctuation standard deviation and load rate of the j-th high-load distribution station area.

[0074] The coordinated optimization of technical feasibility and economic optimality is achieved through a dynamic coupling mechanism, that is, the optimal solution of the load rate is achieved.

[0075] Based on the distribution station area loss objective function and the economic benefit objective function, a multi-objective function is constructed.

[0076] Through the comprehensive constraints and multi-objective functions, a target optimization model is built.

[0077] Based on the target optimization model, the optimal power allocation scheme is obtained, and hierarchical collaborative control is executed to achieve dynamic adjustment of power allocation.

[0078] Example 3

[0079] As another preferred embodiment of the present invention, the present invention includes a mutual assistance control method for multiple distribution substations taking into account capacity margin, wherein the multiple distribution substations include N low-load distribution substations and M high-load distribution substations connected by N+M interconnection devices. The load rate of the low-load distribution substation is less than or equal to a first load rate threshold β i,ref , the load rate of the high-load distribution station area is greater than the second load rate threshold β j,ref Based on the distribution station area, the control method includes the following steps:

[0080] Based on the economic operation constraints of the distribution station area and the mutual capacity margin constraints, comprehensive constraints are constructed.

[0081] Based on the distribution station area loss objective function and the economic benefit objective function, a multi-objective function is constructed, including:

[0082] Construct the loss objective function P of the kth distribution station area k,loss , where the kth distribution station area refers to the ith low-load distribution station area or the jth high-load distribution station area. Specifically, the loss objective function P of the kth distribution station area is k,loss The calculation method is:

[0083]

[0084] Where, P k,out is the output power value of the kth distribution station area, η k Given the efficiency of the kth distribution station area, P k,1 is the no-load loss, P k,2 is the load loss, cosγ k and S k are the AC side power factor and rated capacity of the kth distribution station area respectively.

[0085] Construct the economic benefit objective function, the economic benefit objective function R eco The calculation method is:

[0086]

[0087] Where K p is the unit power transmission benefit coefficient, P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area.

[0088] Through the comprehensive constraints and multi-objective functions, a target optimization model is built.

[0089] Based on the target optimization model, the optimal power allocation scheme is obtained, and hierarchical collaborative control is executed to achieve dynamic adjustment of power allocation.

[0090] Example 4

[0091] As the best embodiment of the present invention, the present invention includes a mutual assistance control method for multiple distribution station areas taking into account capacity margin, wherein, with reference to the attached specification, Figure 1 The multiple distribution stations include N low-load distribution stations and M high-load distribution stations connected by N+M interconnection devices. In this figure, the square part is the interconnection device. The load rate of the low-load distribution station is less than or equal to the first load rate threshold β i,ref , the load rate of the high-load distribution station area is greater than the second load rate threshold β j,ref Based on this distribution area, refer to the attached manual Figure 2 , the control method comprises the following steps:

[0092] Distribution area parameter collection: collect the AC side power factor, rated capacity, load rate upper limit, given efficiency, no-load loss, load loss and current load power value of the distribution area.

[0093] Based on the economic operation constraints and mutual aid capacity margin constraints of the distribution station area, a comprehensive constraint condition is constructed. Specifically, the maximum mutual aid power P of the i-th low-load distribution station area is calculated. i，max :

[0094] P i，max =cosγ i S i ×β i,max -P i,load ,

[0095] Where cosγ i 、S i , β i,max 、P i,load are the AC side power factor, rated capacity, load rate upper limit and current load power value of the i-th low-load distribution station area respectively.

[0096] Calculate the power requirement P of the jth high-load distribution station area j,ref :

[0097] P j,ref =P j,load -cosγ j S j ×β j,ref ,

[0098] P j,load , cosγ j 、S j , β j,ref They are the current load power value, AC side power factor, rated capacity and expected load rate of the jth high-load distribution station area.

[0099] Constructing economic operation constraints:

[0100] 1.33β JZ,i ≤β i ≤75%,

[0101] 1.33β JZ,j ≤β j ≤75%,

[0102] Where, β JZ,i is the comprehensive economic load coefficient of the i-th low-load distribution station area, β i is the load rate of the i-th low-load distribution station area, β JZ,j is the comprehensive economic load coefficient of the jth high-load distribution station area, β j is the load rate of the jth high-load distribution station area. i,1 、P i,2 , σ i , β i are the no-load loss, load loss, load fluctuation standard deviation and load rate of the i-th low-load distribution station area respectively; P j,1 、P j,2 , σ j , β j They are the no-load loss, load loss, load fluctuation standard deviation and load rate of the j-th high-load distribution station area.

[0103] Establish mutual aid capacity margin constraints:

[0104] 0≤P i ≤P i，max , P i =cosγ i S i ×β i -P i,load ;

[0105] 0≤P j ≤P j,ref, P j =P j,load -cosγ j S j ×β j ;

[0106]

[0107] Where, P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area, P j P is the actual mutual aid power instruction setting value of the jth high-load distribution station area; i，max is the maximum mutually beneficial power of the i-th low-load distribution station area, P j,ref is the power demand of the jth high-load distribution station area; cosγ i 、S i , β i 、P i,load are the AC side power factor, rated capacity, load rate and current load power value of the i-th low-load distribution station area; P j,load , cosγ j 、S j , β j They are the current load power value, AC side power factor, rated capacity and load rate of the jth high-load distribution station area.

[0108] If there is one low-load distribution station area and one high-load distribution station area, if the mutually-assisted power of the low-load distribution station area is not less than the required power of the high-load distribution station area, then the actual mutually-assisted power of the low-load distribution station area is the required power of the high-load distribution station area; if the mutually-assisted power of the low-load distribution station area is less than the required power of the high-load distribution station area, then the actual mutually-assisted power of the low-load distribution station area is its mutually-assisted power, and the power shortfall is provided by the power grid at the high-load distribution station area.

[0109] The coordinated optimization of technical feasibility and economic optimality is achieved through a dynamic coupling mechanism. Specifically, with the purpose of solving the load rate, the intersection of the technical feasible domain (equipment safety) and the economic feasible domain (profit compliance) is used as the optimization solution space to obtain comprehensive constraints.

[0110] Based on the distribution station area loss objective function and the economic benefit objective function, a multi-objective function is constructed. Specifically,

[0111] Calculate the loss objective function P of the kth distribution station area k,loss , where the kth distribution station area refers to the ith low-load distribution station area or the jth high-load distribution station area. The specific calculation method is:

[0112]

[0113] Where, Pk,out is the output power value of the kth distribution station area, η k Given the efficiency of the kth distribution station area, P k,1 is the no-load loss, P k,2 is the load loss, cosγ k and S k are the AC side power factor and rated capacity of the kth distribution station area respectively.

[0114] Economic benefit objective function R eco The calculation method is:

[0115]

[0116] Where K p is the unit power transmission benefit coefficient, in yuan / kW; P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area.

[0117] The multi-objective function is:

[0118]

[0119] Where, P k,loss is the target function of the k-th distribution station area loss, R eco is the economic benefit objective function, λ1 is the distribution area loss weight coefficient, and λ2 is the economic benefit weight coefficient. The distribution area loss weight coefficient λ1 and the economic benefit weight coefficient λ2 are dynamically adjusted based on fuzzy logic, and their calculation methods are as follows:

[0120]

[0121] Where μ i (e) is the membership function, and the input variable e is the urgency of the working condition.

[0122] Through the comprehensive constraints and multi-objective functions, a target optimization model is built:

[0123] 1.33β JZ,i ≤β i ≤75%,

[0124] 1.33β JZ,j ≤β j ≤75%,

[0125] 0≤P i ≤P i，max , P i =cosγ i S i ×β i -P i,load ;

[0126] 0≤P j ≤P j,ref , P j =P j,load -cosγ j S j ×β j ;

[0127]

[0128] Based on the target optimization model, an optimal power allocation plan is obtained, and hierarchical collaborative control is implemented to achieve dynamic adjustment of power allocation. Specifically, the Pareto frontier of loss and economic benefits can be solved using the improved NSGA-II algorithm, providing a variety of optional optimization strategy combinations (such as minimum loss, maximum benefit, and balanced solutions). Based on this optimal power allocation plan, hierarchical collaborative control is implemented: the upper-level controller sends the optimal power allocation plan to the lower-level controller for execution, achieving optimal energy distribution within the distribution station area.

[0129] Example 5

[0130] As another preferred embodiment of the present invention, the present invention includes a mutual assistance control system for multiple distribution station areas taking into account capacity margin, comprising:

[0131] The distribution station area division unit divides the distribution station area into N low-load distribution station areas and M high-load distribution station areas, and connects the low-load distribution station areas and the high-load distribution station areas through N+M interconnection devices.

[0132] The data acquisition unit collects the operating parameter information of each low-load distribution substation and high-load distribution substation, including the AC side power factor, rated capacity, load rate upper limit, given efficiency, no-load loss, load loss and current load power value.

[0133] The comprehensive constraint condition construction unit constructs comprehensive constraint conditions based on the economic operation constraint conditions of the distribution station area and the mutual capacity margin constraint conditions.

[0134] The multi-objective function construction unit constructs a multi-objective function based on the distribution station area loss objective function and the economic benefit objective function.

[0135] The target optimization model construction unit builds a target optimization model based on the comprehensive constraints and multi-objective functions.

[0136] The control unit obtains the optimal power allocation plan based on the target optimization model, implements hierarchical collaborative control execution, and realizes dynamic adjustment of power allocation.

[0137] In summary, after reading the present invention document, ordinary technicians in this field can make various other corresponding transformation schemes based on the technical solutions and technical concepts of the present invention without creative mental work, which all fall within the scope of protection of the present invention.

Claims

1. A mutual assistance control method for multiple distribution substations taking into account capacity margin, characterized by: The multiple distribution stations include N low-load distribution stations and M high-load distribution stations connected by N+M interconnection devices; the load rate of the low-load distribution station is less than or equal to the first load rate threshold β i,ref , the load rate of the high-load distribution station area is greater than the second load rate threshold β j,ref ; The control method comprises the following steps: Based on the economic operation constraints of the distribution area and the mutual capacity margin constraints, a comprehensive constraint condition is constructed; based on the loss objective function and economic benefit objective function of the distribution area, a multi-objective function is constructed; Building a target optimization model through the comprehensive constraints and multi-objective functions; Based on the target optimization model, the optimal power allocation scheme is obtained, and hierarchical collaborative control is executed to achieve dynamic adjustment of power allocation.

2. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 1, characterized in that: The economic operation constraints are: 1.33β JZ,i ≤β i ≤75％， 1.33β JZ,j ≤β j ≤75％， Where, β JZ,i is the comprehensive economic load coefficient of the i-th low-load distribution station area, β i is the load rate of the i-th low-load distribution station area, β JZ,j is the comprehensive economic load coefficient of the jth high-load distribution station area, β j is the load rate of the jth high-load distribution station area.

3. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 2, characterized in that: The calculation method of comprehensive economic load factor is: Where, P i,1 、P i,2 , σ i , β i are the no-load loss, load loss, load fluctuation standard deviation and load rate of the i-th low-load distribution station area respectively; P j,1 、P j,2 , σ j , β j They are the no-load loss, load loss, load fluctuation standard deviation and load rate of the j-th high-load distribution station area.

4. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 3, characterized in that: The mutual aid capacity margin constraint condition is: 0≤P i ≤P i，max ,P i =cosγ i S i ×β i -P i,load ; 0≤P j ≤P j,ref ,P j =P j,load -cosγ j S j ×β j ; Where, P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area, P j P is the actual mutual aid power instruction setting value of the jth high-load distribution station area; i，max is the maximum mutually beneficial power of the i-th low-load distribution station area, P j,ref is the power demand of the jth high-load distribution station area; cosγ i 、S i , β i 、P i,load are the AC side power factor, rated capacity, load rate and current load power value of the i-th low-load distribution station area; P j,load , cosγ j 、S j , β j They are respectively the current load power value, AC side power factor, rated capacity and load rate of the jth high-load distribution station area; when P j,ref >P i When the power shortage is reached, the power grid at the high-load distribution station end will provide the remaining power.

5. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 4, characterized in that: The maximum mutually supportable power P of the i-th low-load distribution station area i，max The calculation method is: P i，max =cosγ i S i ×β i,max -P i,load , Where cosγ i 、S i , β i,max 、P i,load are the AC side power factor, rated capacity, load rate upper limit and current load power value of the i-th low-load distribution station area respectively.

6. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 4, characterized in that: The power requirement P of the jth high-load distribution station area j,ref The calculation method is: P j,ref =P j,load -cosγ j S j ×β j,ref , P j,load , cosγ j 、S j , β j,ref They are the current load power value, AC side power factor, rated capacity and expected load rate of the jth high-load distribution station area.

7. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 1 or 4, characterized in that: The multi-objective function is: Where, P k,loss is the loss objective function of the kth distribution station area, the kth distribution station area refers to the ith low-load distribution station area or the jth high-load distribution station area; R eco is the economic benefit objective function, λ1 is the distribution area loss weight coefficient, and λ2 is the economic benefit weight coefficient. The distribution area loss weight coefficient λ1 and the economic benefit weight coefficient λ2 are dynamically adjusted based on fuzzy logic, and their calculation methods are as follows: Where μ i (e) is the membership function, and the input variable e is the urgency of the working condition.

8. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 7, characterized in that: The objective function of the loss of the k-th distribution station area P k,loss The calculation method is: Where, P k,out is the output power value of the kth distribution station area, η k Given the efficiency of the kth distribution station area, P k,1 is the no-load loss, P k,2 is the load loss, cosγ k and S k are the AC side power factor and rated capacity of the kth distribution station area respectively.

9. The mutual assistance control method for multiple distribution substations taking into account capacity margin according to claim 7, characterized in that: Economic benefit objective function R eco The calculation method is: Where K p is the unit power transmission benefit coefficient, P i is the actual mutual aid power instruction setting value of the i-th low-load distribution station area.

10. A mutual assistance control system for multiple distribution substations taking into account capacity margin, characterized by: include: The distribution substation area division unit divides the distribution substation area into N low-load distribution substation areas and M high-load distribution substation areas, and connects the low-load distribution substation area and the high-load distribution substation area through N+M interconnection devices; Data acquisition unit, collecting working parameter information of each low-load distribution substation area and high-load distribution substation area; The comprehensive constraint condition construction unit constructs comprehensive constraint conditions based on the economic operation constraint conditions and mutual capacity margin constraint conditions of the distribution station area; A multi-objective function construction unit constructs a multi-objective function based on the distribution station area loss objective function and the economic benefit objective function; A target optimization model building unit is configured to build a target optimization model based on the comprehensive constraint conditions and the multi-objective function; The control unit obtains the optimal power allocation plan based on the target optimization model, and implements hierarchical collaborative control execution to achieve dynamic adjustment of power allocation.

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