CN118174362B - An island operation scheduling method considering the differences of distributed generation in different fault areas - Google Patents

Abstract

The present invention relates to an island operation scheduling method that takes into account the differentiation of distributed power sources in different fault areas, belongs to the technical field of robust optimization scheduling of energy storage resources under fault scenarios, and solves the problem of the lack of island operation scheduling methods that take into account the differentiation of distributed power sources in different fault areas in the prior art. The method includes: determining a number of fault areas according to an electrical topology diagram and the location of the circuit breaker where the circuit breaker is broken; constructing an island operation scheduling model for each fault area respectively; the island operation scheduling model for each fault area takes the maximization of the sum of the SOCs of all energy storage power stations in the corresponding fault area as the objective function, and the operation constraints of the energy storage power station as the common constraints; and according to the distributed power source settings of each fault area, construct corresponding flow constraints and distributed power source output uncertainty constraints as individual constraints for each fault area; based on the island operation scheduling model of each fault area, the island operation scheduling of each fault area is realized.

Description

An island operation scheduling method considering the differences of distributed generation in different fault areas

Technical Field

The present invention relates to the technical field of robust optimization scheduling of energy storage resources under fault scenarios, and in particular to an island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas.

Background technique

With the development of technology and the improvement of people's living standards, the form of power grids has become more diversified. In addition to the basic distribution network, wind, light, and storage resources will also be applied. In actual application, when the distribution network fails, the power grid is in an isolated operation state, and energy storage power stations can be used to improve the stability of power supply output. In addition, distributed power sources have the advantages of flexible power generation, low investment, and environmental friendliness, and can serve as an effective supplement to centralized power supply.

However, in the scenario of a distribution network failure, the settings of distributed power sources in different fault areas are not the same, making it difficult to perform real-time scheduling through a unified scheduling model. At the same time, in practical applications, there are many uncertain factors in the power supply of distributed power sources such as wind power and photovoltaic power, such as uncertainty in light intensity disturbance and wind speed disturbance, which has caused certain troubles in the use of distributed power sources in the optimization scheduling process under fault scenarios.

Therefore, how to design an island operation scheduling method that takes into account the differentiated distributed power sources in different fault areas and comprehensively considers the impact of uncertain light intensity disturbances and uncertain wind speed disturbances is a problem that needs to be solved urgently.

Summary of the invention

In view of the above analysis, an embodiment of the present invention aims to provide an island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas, so as to solve the problem of lack of island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas in the prior art.

The present invention discloses an island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas, the method comprising:

When a distribution network fault occurs in the area to be analyzed, the circuit breaker on the corresponding line is disconnected. According to the electrical topology of the area to be analyzed and the location of the circuit breaker where the disconnection occurs, several fault areas are determined, and the corresponding fault areas are in an isolated grid operation state; each fault area includes an energy storage power station; according to the location of the circuit breaker where the disconnection occurs, the corresponding fault area does not include a distributed power source, or includes at least one distributed power source of a wind turbine and a photovoltaic generator;

An island operation dispatching model is constructed for each fault area respectively; in each island operation dispatching model, the objective function is to maximize the sum of the SOCs of all energy storage power stations in the corresponding fault area, and the operation constraints of the energy storage power stations are used as common constraints; and according to the distributed power source settings in each fault area, the corresponding power flow constraints and distributed power source output uncertainty constraints are constructed as individual constraints for each fault area;

The node injection power and node outflow power of all users in each fault area are collected in real time, and the island operation scheduling of each fault area is realized based on the island operation scheduling model of each fault area.

On the basis of the above scheme, the present invention also makes the following improvements:

Further, according to the electrical topology of the area to be analyzed and the location of the circuit breaker where the circuit breaker is broken, several fault areas are determined; executing:

If the circuit breaker on the main line is disconnected, the entire circuit controlled by the circuit breaker in the electrical topology diagram is regarded as a fault area;

If a circuit breaker on the same branch line is tripped, the area controlled by the circuit breaker in the electrical topology diagram is regarded as a fault area;

If multiple circuit breakers on the same branch are tripped, the area between two adjacent circuit breakers on the branch in the electrical topology diagram is regarded as a fault area, and the area controlled by the circuit breaker at the end of the branch is also regarded as a fault area.

Furthermore, when a certain fault area does not include a distributed power source, the individual constraint condition only includes a power flow constraint, and the power flow constraint is that the sum of the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area;

When the distributed power sources in a certain fault area include both wind turbines and photovoltaic generators, the output uncertainty constraint of the distributed power sources includes the output uncertainty constraint of the wind turbines and the output uncertainty constraint of the photovoltaic generators, and the power flow constraint is that the sum of the output power of each photovoltaic generator, the output power of the photovoltaic generator, and the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area;

When the distributed power sources in a certain fault area only include wind turbines, the output uncertainty constraint of the distributed power sources only includes the output uncertainty constraint of the wind turbines, and the power flow constraint is that the sum of the output power of each wind turbine and the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area;

When the distributed power sources in a fault area only include photovoltaic power generation groups, the distributed power output uncertainty constraint only includes the output uncertainty constraint of the photovoltaic power generation group, and the power flow constraint is that the sum of the output power of each photovoltaic power generation group and the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area.

Furthermore, the objective function of maximizing the sum of SOC of all energy storage power stations is expressed as:

(1)

in, Energy storage power station exist The state of charge at the moment, is the total number of energy storage power stations.

Furthermore, the wind turbine output uncertainty constraint is expressed as:

(2)

In the formula, Represents wind turbine exist The output power at the moment, Represents wind turbine Rated output power, Represents wind turbine The cut-in wind speed, Represents wind turbine The cut-off wind speed, Represents wind turbine Rated wind speed, Represents wind turbine exist Real-time wind speed at the moment; Represents wind turbine exist The reference wind speed at the time, Represents wind turbine exist Uncertain disturbance variable of wind speed at the moment; , Respectively The uncertainty interval The upper and lower bounds of , Respectively represent wind turbines The minimum and maximum values of the reference wind speed.

Furthermore, the output uncertainty constraint of the photovoltaic generator set is expressed as:

(3)

In the formula, Represents photovoltaic generator set exist The output power at the moment, Represents photovoltaic generator set Rated output power, Photovoltaic generator Under standard conditions, the light intensity Represents photovoltaic generator set exist The actual light intensity at the moment, Represents photovoltaic generator set The temperature coefficient of the solar photovoltaic array in Photovoltaic generator The temperature of the solar photovoltaic array under standard conditions, Photovoltaic generator Solar photovoltaic arrays in The actual temperature at the moment; Represents photovoltaic generator set exist The reference light intensity at the moment, Represents photovoltaic generator set exist The uncertainty disturbance variable of the light intensity at time, , Respectively The uncertainty interval The upper and lower bounds of , Respectively represent photovoltaic generators The minimum and maximum values of the reference light intensity.

Furthermore, the energy storage power station operation constraints are expressed as:

(4)

In the formula, Energy storage power station exist The state of charge at the moment, For energy storage power station The self-discharge rate, Energy storage power station exist The discharge power at the moment, ; Energy storage power station The discharge efficiency, Energy storage power station The capacity, is the time scale; To characterize energy storage power stations exist A 0-1 variable indicating whether the state is in discharge state at the moment; , in a discharging state; , not in a discharge state; For energy storage power station The upper limit of the discharge power.

Furthermore, when a fault area does not include distributed generation, the power flow constraint is expressed as:

(5)

When the distributed generation in a fault area includes both wind turbines and photovoltaic generators, the power flow constraint is expressed as:

(6)

In the formula, Indicates Users in The power consumption at the time, Indicates Rated power per user; Indicates Users in The node injection power at time Indicates Users in The node outflow power at time, , All data are collected in real time; Indicates the total number of users on the user side in the fault area. represents the total number of wind turbines in the fault area, Indicates the total number of photovoltaic generators in the fault area.

Furthermore, when the distributed generation in a fault area only includes wind turbines, the power flow constraint is expressed as:

(7)

When the distributed generation in a fault area only includes photovoltaic generators, the power flow constraint is expressed as:

(8).

Furthermore, for each fault area, the island operation scheduling of the fault area is implemented based on the island operation scheduling model of the fault area, and the following is executed:

The node injection power and node outflow power of all users at the current moment collected in real time are substituted into the island operation scheduling model of the fault area, and the Gurobi solver is called by MATLAB to solve the island operation scheduling model to obtain the optimal scheduling result of the user-side energy storage resources at the current moment; wherein, the optimal scheduling result of the user-side energy storage resources at each moment refers to the discharge power of each energy storage power station when the objective function at the corresponding moment takes the maximum value; and based on the optimal scheduling result of the user-side energy storage resources at the current moment, the discharge power of each energy storage power station in the fault area at the current moment is controlled.

Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

The island operation scheduling method provided by the present invention, which takes into account the differentiation of distributed power sources in different fault areas, fully considers the impact of the uncertainty of the output of distributed power sources on the optimization scheduling process, and constructs an island operation scheduling model with the maximization of the sum of the SOCs of all energy storage power stations as the objective function and the constraints of satisfying the power flow constraints and the uncertainty constraints of the output of distributed power sources as the constraints. At the same time, in the process of solving the actual wind speed, when the reference wind speed is within a certain fault area range, the wind speed uncertainty disturbance variable can be randomly selected. When the reference wind speed exceeds the preset range, the wind speed uncertainty disturbance variable is determined by configuration. The solution of the actual light intensity is similar. Both combine uncertainty with boundary restrictions to better simulate the actual situation of the uncertainty of the output of distributed power sources. Finally, by calling the Gurobi solver to solve the model, the optimal scheduling results of the user-side energy storage resources at each moment can be obtained, thereby realizing the real-time optimal scheduling of energy storage resources. The optimal scheduling method is more robust and provides a good technical guidance for realizing the optimal scheduling of energy storage resources.

In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings are only used for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. In the entire drawings, the same reference symbols represent the same components;

FIG1 is a flow chart of an island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas provided by an embodiment of the present invention;

FIG2 is an electrical topology diagram of wind, solar, and storage resources of a 126-node system provided by an embodiment of the present invention;

FIG3 is a schematic diagram of a variation law of light intensity in summer provided by an embodiment of the present invention;

FIG4 is a schematic diagram of a wind speed variation rule in summer provided by an embodiment of the present invention;

FIG5 is a diagram showing the average reliability index of users for each customized fault area provided by an embodiment of the present invention;

FIG6 shows the maximum margin required at each moment for each energy storage power station provided by an embodiment of the present invention.

Detailed ways

The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

A specific embodiment of the present invention discloses a method for scheduling island operation taking into account the differentiation of distributed power sources in different fault areas, and the flow chart is shown in FIG1. The method comprises the following steps:

Step S1: When a distribution network fault occurs in the area to be analyzed, the circuit breaker on the corresponding line is disconnected. According to the electrical topology of the area to be analyzed and the location of the circuit breaker where the disconnection occurs, several fault areas are determined, and the corresponding fault areas are in an isolated grid operation state; wherein each fault area includes an energy storage power station; according to the location of the circuit breaker where the disconnection occurs, the corresponding fault area does not include a distributed power source, or includes at least one distributed power source of a wind turbine or a photovoltaic power generation group.

Step S2: construct the island operation dispatching model of each fault area under the island operation state of the power grid respectively; wherein, in the island operation dispatching model of each fault area, the objective function is to maximize the sum of SOCs of all energy storage power stations in the corresponding fault area, and the operation constraints of the energy storage power stations are the common constraints; and according to the distributed power source settings of each fault area, the corresponding power flow constraints and distributed power source output uncertainty constraints are constructed as the individual constraints of each fault area.

Step S3: collecting the node injection power and node outflow power of all users in each fault area in real time, and implementing the island operation scheduling of each fault area based on the island operation scheduling model of each fault area.

Preferably, in step S1, several fault areas are determined according to the electrical topology of the area to be analyzed and the location of the circuit breaker where the circuit breaker is broken; and the following is performed: if the circuit breaker on the main line is broken, the entire circuit controlled by the circuit breaker in the electrical topology is taken as a fault area; if a circuit breaker on the same branch is broken, the area controlled by the circuit breaker in the electrical topology is taken as a fault area; if multiple circuit breakers on the same branch are broken, the area between two adjacent circuit breakers on the branch in the electrical topology is taken as a fault area, and the area controlled by the circuit breaker at the end of the branch is also taken as a fault area.

Preferably, in this embodiment, when a certain fault area does not include distributed power sources, the individual constraint condition only includes power flow constraint, and the power flow constraint is that the sum of the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area; when the distributed power sources in a certain fault area include both wind turbines and photovoltaic generators, the output uncertainty constraint of the distributed power source only includes the output uncertainty constraint of the wind turbine and the output uncertainty constraint of the photovoltaic generator, and the power flow constraint is that the output power of each photovoltaic generator, the output power of the photovoltaic generator, and the sum of the discharge power of each energy storage power station is greater than or equal to the power consumption of all users in the fault area. The sum of the electric power; when the distributed power sources in a certain fault area only include wind turbines, the distributed power output uncertainty constraint only includes the wind turbine output uncertainty constraint, and the power flow constraint is that the sum of the output power of each wind turbine and the discharge power of each energy storage power station is greater than or equal to the sum of the electric power of all users in the fault area; when the distributed power sources in a certain fault area only include photovoltaic power generation groups, the distributed power output uncertainty constraint only includes the photovoltaic power generation group output uncertainty constraint, and the power flow constraint is that the sum of the output power of each photovoltaic power generation group and the discharge power of each energy storage power station is greater than or equal to the sum of the electric power of all users in the fault area.

Next, by analyzing the output characteristics of wind turbines and photovoltaic generators during the grid islanding process and the charging and discharging model of the energy storage power station, an islanding operation scheduling model for each fault area is constructed.

Preferably, in this embodiment, by establishing a probability model that takes into account the output characteristics of distributed power sources and taking into account the improvement of reliability measures such as energy storage circuits, an island operation scheduling model that takes into account dual uncertainty is constructed, and a solution strategy for the island operation scheduling model is given. The specific introduction is as follows:

(1) Distributed power generation output characteristics analysis and uncertainty modeling

1) Probabilistic model of wind turbine output characteristics (referred to as “output model”)

The output of wind turbines is mainly affected by wind speed. Considering the operating characteristics of wind turbines, exist Output power at all times Expressed as:

(1)

In the formula, Represents wind turbine Rated output power, Represents wind turbine The cut-in wind speed, Represents wind turbine The cut-off wind speed, Represents wind turbine Rated wind speed, Represents wind turbine exist Real-time wind speed at the moment.

2) Probabilistic model of photovoltaic generator output characteristics

The output of the photovoltaic generator set is mainly affected by the light intensity and the temperature of the solar photovoltaic array. Assuming that the photovoltaic generator set adopts the maximum power point tracking strategy, the photovoltaic generator set exist Output power at all times Expressed as:

(2)

In the formula, Represents photovoltaic generator set Rated output power, Photovoltaic generator Under standard conditions, the light intensity Represents photovoltaic generator set exist The actual light intensity at the moment, Represents photovoltaic generator set The temperature coefficient of the solar photovoltaic array in Photovoltaic generator The temperature of the solar photovoltaic array under standard conditions, Photovoltaic generator Solar photovoltaic arrays in The actual temperature at the moment.

3) Charging and discharging model of energy storage power station

The charging and discharging model of the energy storage power station can be described by the following six parameters, namely capacity, power, charging efficiency, discharging efficiency, self-discharge rate and state of charge. The details are as follows:

charging:

(3)

Discharge status:

(4)

In the formula, , Respectively represent energy storage power stations exist time, The state of charge at the moment, i.e. SOC; For energy storage power station The self-discharge rate, Energy storage power station exist Charging power at the moment, Energy storage power station exist The discharge power at the moment, , ; , Respectively represent energy storage power stations The charging efficiency and discharging efficiency of Energy storage power station The capacity, For the time scale.

For a single energy storage power station, and Mutual exclusion, that is, charging and discharging cannot be performed at the same time, can be linearly expressed as follows:

(5)

In the formula, To characterize energy storage power stations exist A 0-1 variable indicating whether the battery is in charging state at the moment. , in charging state; , not in charging state; For energy storage power station The upper limit of charging power; To characterize energy storage power stations exist A 0-1 variable indicating whether the state is in discharge state at the moment; , in a discharging state; , not in a discharge state; For energy storage power station The upper limit of the discharge power.

(2) Island operation scheduling model

Based on the above two types of distributed power sources, wind and solar, and energy storage power stations, a user-side control resource, an island operation scheduling model taking into account the uncertainty of wind and solar output is established to solve the objective function of maximizing the sum of SOC of all energy storage power stations when wind power and photovoltaic output fluctuate. As shown below:

1) Objective function: Maximize the sum of the SOC of the energy storage power station. It can be expressed by the following formula:

(6)

In the formula, is the total number of energy storage power stations. It should be emphasized that during the grid island operation, all energy storage power stations cannot be charged and can only be in a discharging state, or in an inoperative state (i.e., a non-discharging state).

2) Constraints:

(a) Power flow constraints

When a fault area does not include distributed generation, the power flow constraint is expressed as:

(7)

When the distributed generation in a fault area includes both wind turbines and photovoltaic generators, the power flow constraint is expressed as:

(8)

In the formula, Indicates Users in The power consumption at the time, Indicates Rated power per user; Indicates Users in The node injection power at time Indicates Users in The node outflow power at time, , All data are collected in real time; Indicates the total number of users on the user side in the fault area. represents the total number of wind turbines in the fault area, Indicates the total number of photovoltaic generators in the fault area.

When the distributed generation in a fault area only includes wind turbines, the power flow constraint is expressed as:

(9)

When the distributed generation in a fault area only includes photovoltaic generators, the power flow constraint is expressed as:

(10)

(b) Distributed power generation operation constraints

Distributed power sources include wind power and photovoltaic power.

For the uncertainty of distributed wind power output, the following constraints are considered:

(11)

Considering the impact of wind speed uncertainty on wind power output, a box-type uncertainty set is used to describe the uncertainty of wind power output. exist Real-time wind speed at the moment By wind turbine exist Reference wind speed at the time and wind turbines exist Uncertain disturbance variable of wind speed at the moment decided together. It can be obtained based on the meteorological data of the area. The uncertainty interval The upper bound of , Nether It can be obtained by analyzing the local wind speed historical data. In the specific implementation process, the wind speed disturbance baseline value of the corresponding wind turbine can be obtained by analyzing the local wind speed historical data, and then The fluctuation range of the The upper bound of , Nether . , Respectively represent wind turbines Considering the actual operation of the wind turbine, in this embodiment, it is preferred that , .

For the uncertainty of photovoltaic output, there are:

(12)

Considering the impact of the uncertainty of light intensity on photovoltaic output, a box-type uncertainty set is used to describe the uncertainty of photovoltaic output. exist The actual light intensity at the moment Photovoltaic generators exist Reference light intensity at the moment and photovoltaic generators exist The uncertainty disturbance variable of the light intensity at the moment Decide. It can be obtained based on the meteorological data of the area. The uncertainty interval The upper bound of , Nether This can be obtained by analyzing the historical data of light intensity in the area. In the specific implementation process, the light intensity disturbance baseline value of the corresponding wind turbine can be obtained by analyzing the historical data of light intensity in the area, and then The fluctuation range of the The upper bound of , Nether . , Respectively represent photovoltaic generators The minimum and maximum values of the reference light intensity.

(c) Energy storage power station operation constraints

For energy storage power stations, since all energy storage power stations cannot be charged during the grid island operation, they can only be in a discharging state, or in a non-working state (i.e., non-discharging state). Therefore, the operation constraints of the energy storage power station do not need to consider the charging model. At this time, the operation constraints of the energy storage power station are expressed as:

(13)

It should be noted that the optimal scheduling result of the user-side energy storage resources at each moment refers to the discharge power of each energy storage power station when the objective function at the corresponding moment takes the maximum value.

Preferably, in the specific implementation process of step S3, for each fault area, the island operation scheduling of the fault area is implemented based on the island operation scheduling model of the fault area, and the following is performed:

The node injection power and node outflow power of all users at the current moment collected in real time are substituted into the island operation scheduling model of the fault area, and the Gurobi solver is called by MATLAB to solve the island operation scheduling model to obtain the optimal scheduling result of the user-side energy storage resources at the current moment; wherein, the optimal scheduling result of the user-side energy storage resources at each moment refers to the discharge power of each energy storage power station when the objective function at the corresponding moment takes the maximum value; and based on the optimal scheduling result of the user-side energy storage resources at the current moment, the discharge power of each energy storage power station in the fault area at the current moment is controlled.

In summary, the island operation scheduling method provided by this embodiment, which takes into account the differentiation of distributed power sources in different fault areas, fully considers the impact of the uncertainty of distributed power output on the optimization scheduling process, and constructs an island operation scheduling model with the maximum sum of SOC of all energy storage power stations as the objective function and the constraint conditions of satisfying the power flow constraint and the uncertainty constraint of distributed power output. At the same time, in the process of solving the actual wind speed, when the reference wind speed is within a certain fault area range, the wind speed uncertainty disturbance variable can be randomly selected, and when the reference wind speed exceeds the preset range, the wind speed uncertainty disturbance variable is determined by configuration. The solution of actual light intensity is similar. Both combine uncertainty with boundary restrictions to better simulate the actual situation of uncertainty in the output of distributed power sources. Finally, by calling the Gurobi solver to solve the model, the optimal scheduling results of the user-side energy storage resources at each moment can be obtained, thereby realizing the real-time optimal scheduling of energy storage resources. The optimal scheduling method is more robust and provides a good technical guidance for realizing the optimal scheduling of energy storage resources.

In order to further verify the effectiveness of the robust optimization scheduling method and its solution strategy proposed in the above embodiment, another embodiment of the present invention carries out verification work based on the following example. The electrical topology diagram of wind, light, and storage resources of the 126-node system is shown in Figure 2, specifically:

1) Node 34 (fault area B), node 55 (fault area H), node 75, and node 116 are connected to distributed wind turbines WT34, WT55, WT75, and WT116, respectively, with rated generating capacities of 150kW, 200kW, 120kW, and 200kW, respectively. Assume that the change of their output over time follows the change law of summer wind speed. The schematic diagram of the change law of summer wind speed is shown in Figure 3, and all of them are in fluctuates within a range.

In Figure 3, the wind speed when the wind turbine has the maximum output is taken as the standard value, and the wind speed coefficient, which is the ratio of the actual wind speed to the standard value, is used to reflect the wind speed on the windward side of the wind turbine, thereby affecting the ratio of wind power generation output.

2) Node 15, node 40 (fault area A), node 60 (fault area H), node 85 (fault area K) are connected to distributed photovoltaic generators PV15, PV40, PV60 and PV85, respectively, with rated generating capacities of 150kW, 200kW, 120kW and 200kW, respectively. Assuming that the change of their output over time follows the change law of summer light intensity, the schematic diagram of the change law of summer light intensity is shown in Figure 4, and they are also in fluctuates within a range.

In Figure 4, the light intensity when the photovoltaic generator set has the maximum output is taken as the standard value, and the ratio of the actual light intensity to the standard value, that is, the light coefficient, is used to reflect the size of the light intensity received by the photovoltaic generator set, thereby affecting the proportion of photovoltaic output.

3) In terms of energy storage, an energy storage station is added at each node 31, node 41 and node 67 to ensure that each customized fault area has energy storage resources that can be dispatched. At the same time, the rated charging and discharging power of each energy storage station is set to 350kW, and the rated capacity is 1500kWh. The upper limit and capacity of the charging and discharging power of each energy storage station after the addition are shown in Table 1:

Table 1 Installation nodes, rated charge and discharge power and capacity of energy storage power stations

In this embodiment, the line failure rate is 0.025 times/year/km, the fault isolation time is 1h, and the fault repair time is simulated by the sequential Monte Carlo simulation method. When a fault occurs, the circuit breaker at the head end of the affected fault area is automatically disconnected, and the fault area containing distributed power sources forms an island. The uncertain output of distributed power sources improves the reliability of users in the fault area. For energy storage, the change process of its SOC with charging and discharging is simulated, and the reliability of users in the fault area is synergistically improved with wind and light resources.

In order to obtain more accurate simulation results, this embodiment generates 100 scenarios, solves the model and obtains the average reliability index of industrial users in each fault area A, B, H, K, and O, as shown in Table 2:

Table 2 Average reliability index of users in each fault area

In order to more clearly reflect the data in the table, a line graph of the average reliability index of users in each fault area is drawn from Table 2 as shown in Figure 5. As shown in Figure 5, for users in each fault area, the increase and decrease trends of the two results remain consistent.

In the island operation scheduling link, user reliability needs are mainly met through distributed power sources (including wind power and photovoltaic power) and energy storage power stations. That is, for each reliability indicator, users produce the results in Figure 5 based on the use of three resources: wind, light and storage.

By solving the island operation scheduling model, the maximum margin required by the energy storage power stations in the five fault areas at 24 times a day is shown in Figure 6. As shown in Figure 6, the robust interval solved by the island operation scheduling model is the maximum SOC margin required by each fault area at each time. In Figure 6, the maximum SOC margin change curves required by fault areas A, H, and K at each time are similar in shape, and all require a larger margin at night (between 20:00 and 4:00). This is mainly because the three fault areas are all connected to photovoltaic power generation groups, and photovoltaic power does not work at night due to lack of light, so the result shown in Figure 6 appears. For fault area B, since it is connected to a wind turbine generator set and the summer wind speed reaches its peak at 17:00, the maximum SOC margin required for energy storage at 17:00 is reduced to 0; for fault area O, since it is not connected to photovoltaic or wind turbines, the maximum SOC margin required for energy storage at each time has been maintained at a high level. For other user-side controllable resources other than energy storage, the calculation method of the robust control interval taking into account the reliability of power supply is similar to that of energy storage. At the same time, for the other two types of users, namely commercial and community users, the calculation method of the robust control interval of various types of controllable resources is also consistent with that of industrial users. So far, this embodiment provides a method for analyzing the user-side resource control potential of various types of users, as well as a method for calculating the robust control interval of various types of controllable resources, and provides example analysis, which lays the foundation for the subsequent reasonable planning of various types of controllable resources such as energy storage.

Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims (7)

1. A method for island operation scheduling taking into account the differentiation of distributed power sources in different fault areas, characterized in that the method comprises: When a distribution network fault occurs in the area to be analyzed, the circuit breaker on the corresponding line is disconnected. According to the electrical topology of the area to be analyzed and the location of the circuit breaker where the disconnection occurs, several fault areas are determined, and the corresponding fault areas are in an isolated grid operation state; each fault area includes an energy storage power station; according to the location of the circuit breaker where the disconnection occurs, the corresponding fault area does not include a distributed power source, or includes at least one distributed power source of a wind turbine and a photovoltaic generator; An island operation dispatching model is constructed for each fault area respectively; in each island operation dispatching model, the objective function is to maximize the sum of the SOCs of all energy storage power stations in the corresponding fault area, and the operation constraints of the energy storage power stations are used as common constraints; and according to the distributed power source settings in each fault area, the corresponding power flow constraints and distributed power source output uncertainty constraints are constructed as individual constraints for each fault area; Collect the node injection power and node outflow power of all users in each fault area in real time, and implement the island operation scheduling of each fault area based on the island operation scheduling model of each fault area; Determine several fault areas according to the electrical topology of the area to be analyzed and the location of the circuit breaker where the circuit breaker is broken; execute: If the circuit breaker on the main line is disconnected, the entire circuit controlled by the circuit breaker in the electrical topology diagram is regarded as a fault area; If a circuit breaker on the same branch line is tripped, the area controlled by the circuit breaker in the electrical topology diagram is regarded as a fault area; If multiple circuit breakers on the same branch are disconnected, the area between two adjacent circuit breakers on the branch in the electrical topology diagram is regarded as a fault area, and the area controlled by the circuit breaker at the end of the branch is also regarded as a fault area; When the distributed power sources in a certain fault area include both wind turbines and photovoltaic generators, the output uncertainty constraint of the distributed power sources includes the output uncertainty constraint of the wind turbines and the output uncertainty constraint of the photovoltaic generators, and the power flow constraint is that the sum of the output power of each photovoltaic generator, the output power of the photovoltaic generator, and the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area; The wind turbine output uncertainty constraint is expressed as: (1) In the formula, Represents wind turbine exist The output power at the moment, Represents wind turbine Rated output power, Represents wind turbine The cut-in wind speed, Represents wind turbine The cut-off wind speed, Represents wind turbine Rated wind speed, Represents wind turbine exist Real-time wind speed at the moment; Represents wind turbine exist The reference wind speed at the time, Represents wind turbine exist Uncertain disturbance variable of wind speed at the moment; , Respectively The uncertainty interval The upper and lower bounds of , Respectively represent wind turbines The minimum and maximum values of the reference wind speed; The uncertainty constraint of the photovoltaic generator set output is expressed as: (2) In the formula, Represents photovoltaic generator set exist The output power at the moment, Represents photovoltaic generator set Rated output power, Photovoltaic generator Under standard conditions, the light intensity Represents photovoltaic generator set exist The actual light intensity at the moment, Represents photovoltaic generator set The temperature coefficient of the solar photovoltaic array in Photovoltaic generator The temperature of the solar photovoltaic array under standard conditions, Photovoltaic generator Solar photovoltaic arrays in The actual temperature at the moment; Represents photovoltaic generator set exist The reference light intensity at the moment, Represents photovoltaic generator set exist The uncertainty disturbance variable of the light intensity at time, , Respectively The uncertainty interval The upper and lower bounds of , Respectively represent photovoltaic generators The minimum and maximum values of the reference light intensity. 2. The island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas according to claim 1 is characterized in that: When a fault area does not include a distributed power source, the individual constraint condition only includes a power flow constraint, and the power flow constraint is that the sum of the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area; When the distributed power sources in a certain fault area only include wind turbines, the output uncertainty constraint of the distributed power sources only includes the output uncertainty constraint of the wind turbines, and the power flow constraint is that the sum of the output power of each wind turbine and the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area; When the distributed power sources in a fault area only include photovoltaic power generation groups, the distributed power output uncertainty constraint only includes the output uncertainty constraint of the photovoltaic power generation group, and the power flow constraint is that the sum of the output power of each photovoltaic power generation group and the discharge power of each energy storage power station is greater than or equal to the sum of the power consumption of all users in the fault area. 3. The island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas according to claim 2 is characterized in that the objective function is expressed as follows: (3) in, Energy storage power station exist The state of charge at the moment, is the total number of energy storage power stations. 4. The island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas according to claim 3 is characterized in that the operation constraints of the energy storage power station are expressed as: (4) In the formula, Energy storage power station exist The state of charge at the moment, For energy storage power station The self-discharge rate, Energy storage power station exist The discharge power at the moment, ; Energy storage power station The discharge efficiency, Energy storage power station The capacity, is the time scale; To characterize energy storage power stations exist A 0-1 variable indicating whether the state is in discharge state at the moment; , in a discharging state; , not in a discharge state; For energy storage power station The upper limit of the discharge power. 5. The island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas according to claim 4 is characterized in that: When a fault area does not include distributed generation, the power flow constraint is expressed as: (5) When the distributed generation in a fault area includes both wind turbines and photovoltaic generators, the power flow constraint is expressed as: (6) In the formula, Indicates Users in The power consumption at the time, Indicates Rated power per user; Indicates Users in The node injection power at time Indicates Users in The node outflow power at time, , All data are collected in real time; Indicates the total number of users on the user side in the fault area. represents the total number of wind turbines in the fault area, Indicates the total number of photovoltaic generators in the fault area. 6. The island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas according to claim 5 is characterized in that: When the distributed generation in a fault area only includes wind turbines, the power flow constraint is expressed as: (7) When the distributed generation in a fault area only includes photovoltaic generators, the power flow constraint is expressed as: (8). 7. The island operation scheduling method taking into account the differentiation of distributed power sources in different fault areas according to claim 6 is characterized in that, for each fault area, the island operation scheduling of the fault area is implemented based on the island operation scheduling model of the fault area, and the following is executed: The node injection power and node outflow power of all users at the current moment collected in real time are substituted into the island operation scheduling model of the fault area, and the Gurobi solver is called by MATLAB to solve the island operation scheduling model to obtain the optimal scheduling result of the user-side energy storage resources at the current moment; wherein, the optimal scheduling result of the user-side energy storage resources at each moment refers to the discharge power of each energy storage power station when the objective function at the corresponding moment takes the maximum value; and based on the optimal scheduling result of the user-side energy storage resources at the current moment, the discharge power of each energy storage power station in the fault area at the current moment is controlled.