A method for evaluating the reliability of power supply in a microgrid network with flexible connection equipment

Abstract

A method for evaluating the reliability of power supply of a microgrid network with flexible connection equipment is proposed. The method first constructs a probability distribution model of the output of a distributed power source and a probability distribution model of the load power, and then establishes a two-state model of "working-fault" of the component equipment in the microgrid network. Then, based on the constructed model, a sequential simulation method is used to simulate the operation of the microgrid network frame and calculate the power supply reliability of the frame. This method realizes the accurate evaluation of the power supply reliability of a microgrid network with flexible connection equipment.

Description

Technical Field

[0001] The present invention belongs to the field of distribution network planning, and in particular relates to a method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device. Background Art

[0002] As energy crisis and environmental problems gradually emerge, the grid-connected capacity of distributed power sources represented by wind power and photovoltaic power generation continues to increase. Microgrids built based on distributed power sources, energy storage equipment and community loads have the advantages of unified control of source, load and storage, auxiliary grid regulation, comprehensive utilization of multiple energy sources, economic safety and greenness, and will serve as the basic unit of future power distribution. However, some microgrids represented by distributed power sources have strong uncertainty and are prone to endanger the reliability of power system operation. With the increasing requirements of modern users for power quality, in order to study the operation and planning of future distribution network frameworks of multi-microgrid networks, it is more important to evaluate the power supply reliability of multi-microgrid network frameworks after considering the access of multiple new elements. Summary of the invention

[0003] The purpose of the present invention is to overcome the above-mentioned problems existing in the prior art and to provide a method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device.

[0004] To achieve the above objectives, the present invention provides the following technical solutions:

[0005] A method for evaluating the reliability of power supply of a microgrid network including a flexible connection device comprises the following steps in sequence:

[0006] Step A, respectively constructing a distributed power output probability distribution model and a load power probability distribution model;

[0007] Step B, establishing a "working-fault" two-state model of component equipment in the microgrid network;

[0008] Step C: Based on the model constructed in steps A and B, a sequential simulation method is used to simulate the operation of the microgrid network framework and calculate the power supply reliability of the framework.

[0009] The step C comprises the following steps in sequence:

[0010] Step C1: Based on the model constructed in steps A and B, simulate and generate system operation scenarios within the set operation period;

[0011] Step C2, simulating the system operation according to the set operation step length, and entering step C3 when the component equipment fails;

[0012] Step C3, determining the operation status before the fault by optimizing and calculating the network flow before the fault;

[0013] Step C4, determining the load shedding amount, location and shedding time based on the network flow optimization under the fault state;

[0014] Step C5, judging whether the simulated operation time reaches the operation life, if so, proceeding to step C6, if not, returning to step C2;

[0015] Step C6: Calculate the power supply reliability of the microgrid network according to the load shedding amount, location and shedding time of each fault within the operating life.

[0016] In step C4, the network power flow optimization under the fault state includes two stages: emergency power support by flexible connection equipment and network reconstruction by switching operation;

[0017] For the first stage, it is determined whether the two parts of the grid connected by the flexible connection device can operate normally. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated;

[0018] For the second stage, it is determined whether the restored grid can operate normally under the condition that the flexible connection equipment works. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated.

[0019] The load shedding amount and power shedding amount are calculated by the following method:

[0020] For the line with overload, determine whether the end node of the line is a power sending end or a power receiving end. If it is a power receiving end, reduce the load of the end node until it runs normally, and record the load reduction amount; if it is a power sending end, cut off the distributed power supply of the end node until it runs normally, and record the power reduction amount;

[0021] For lines whose loads are within the limit, determine whether the voltages of each node are beyond the limit. If the node voltage is higher than the upper limit, the distributed power supply of the node is reduced until it operates normally, and the amount of power cut is recorded; if the node voltage is lower than the lower limit, the load of the node is reduced until it operates normally, and the amount of load cut is recorded.

[0022] In step C3, the network power flow optimization target before the fault is:

[0023]

[0024]

[0025]

[0026]

[0027] In the above formula, P L,j is the line loss of the jth line in the network, fu,i 、f fL,j They are penalty terms f punish The voltage exceeds the limit, the load exceeds the limit, U i is the voltage of the ith node, U N is the rated voltage of the network node, f L,j is the load rate of the jth line;

[0028] In step C4, the network power flow optimization target under the fault state is:

[0029] minf punish

[0030]

[0031]

[0032]

[0033] The flexible connection device is a flexible multi-state switch;

[0034] The constraints of the network power flow optimization objective before the fault are:

[0035]

[0036] In the above formula, sb j is the circuit breaker status of the jth line. When it is 0, it means the circuit breaker is open, and when it is 1, it means the circuit breaker is closed. flex,i , Q flex,i , S N,i are the output active power, output reactive power and rated capacity of the i-th port of the flexible multi-state switch respectively;

[0037] The constraints of the network power flow optimization objective under the fault state are:

[0038]

[0039] In step A, the distributed power output probability model includes a photovoltaic power generation output probability distribution model and a wind power generation output probability distribution model. The photovoltaic power generation output probability distribution model adopts a Beta distribution function, the wind power generation output probability distribution model adopts a Weibull distribution function, and the load power probability model adopts a normal distribution function.

[0040] In step B, the "working-fault" two-state model is:

[0041]

[0042]

[0043] In the above formula, TTF and TTR are the normal operation time and fault duration of the component equipment, λ and μ are the failure rate and repair rate of the component equipment, and R1 and R2 are random variables that obey the uniform distribution of [0,1].

[0044] The grid structure of the microgrid networking includes: circuit breakers, transmission lines, node busbars, transformers, and flexible connection equipment.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention provides a method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device. The method first constructs a distributed power output probability distribution model and a load power probability distribution model respectively, and then establishes a "working-fault" two-state model of the component equipment in the microgrid network. Then, based on the constructed model, a sequential simulation method is used to simulate the operation of the microgrid network grid frame to calculate the power supply reliability of the grid frame. The method not only realizes the evaluation of the reliability of power supply of the microgrid network, but also considers the emergency response of the flexible connection device in the event of a fault, thereby ensuring the accuracy of the evaluation result. Therefore, the present invention realizes the accurate evaluation of the reliability of power supply of a microgrid network containing a flexible connection device. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of the present invention.

[0048] Figure 2 The figure is the calculation flow of load shedding amount and power shedding amount in the present invention.

[0049] Figure 3 This is the grid structure of the microgrid network in Example 1.

[0050] Figure 4 It is the system microgrid connected to the microgrid network in Example 1. DETAILED DESCRIPTION

[0051] The present invention will be further described below in conjunction with specific drawings and implementation modes.

[0052] See also Figure 1 , Figure 2 A method for evaluating the reliability of power supply of a microgrid network including a flexible connection device comprises the following steps in sequence:

[0053] Step A, respectively constructing a distributed power output probability distribution model and a load power probability distribution model;

[0054] Step B, establishing a "working-fault" two-state model of component equipment in the microgrid network;

[0055] Step C: Based on the model constructed in steps A and B, a sequential simulation method is used to simulate the operation of the microgrid network framework and calculate the power supply reliability of the framework.

[0056] The step C comprises the following steps in sequence:

[0057] Step C1: Based on the model constructed in steps A and B, simulate and generate system operation scenarios within the set operation period;

[0058] Step C2, simulating the system operation according to the set operation step length, and entering step C3 when the component equipment fails;

[0059] Step C3, determining the operation status before the fault by optimizing and calculating the network flow before the fault;

[0060] Step C4, determining the load shedding amount, location and shedding time based on the network flow optimization under the fault state;

[0061] Step C5, judging whether the simulated operation time reaches the operation life, if so, proceeding to step C6, if not, returning to step C2;

[0062] Step C6: Calculate the power supply reliability of the microgrid network according to the load shedding amount, location and shedding time of each fault within the operating life.

[0063] In step C4, the network power flow optimization under the fault state includes two stages: emergency power support by flexible connection equipment and network reconstruction by switching operation;

[0064] For the first stage, it is determined whether the two parts of the grid connected by the flexible connection device can operate normally. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated;

[0065] For the second stage, it is determined whether the restored grid can operate normally under the condition that the flexible connection equipment works. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated.

[0066] The load shedding amount and power shedding amount are calculated by the following method:

[0067] For the line with overload, determine whether the end node of the line is a power sending end or a power receiving end. If it is a power receiving end, reduce the load of the end node until it runs normally, and record the load reduction amount; if it is a power sending end, cut off the distributed power supply of the end node until it runs normally, and record the power reduction amount;

[0068] For lines whose loads are within the limit, determine whether the voltages of each node are beyond the limit. If the node voltage is higher than the upper limit, the distributed power supply of the node is reduced until it operates normally, and the amount of power cut is recorded; if the node voltage is lower than the lower limit, the load of the node is reduced until it operates normally, and the amount of load cut is recorded.

[0069] In step C3, the network power flow optimization target before the fault is:

[0070]

[0071]

[0072]

[0073]

[0074] In the above formula, P L,j is the line loss of the jth line in the network, f u,i 、f fL,j They are penalty terms f punish The voltage exceeds the limit, the load exceeds the limit, U i is the voltage of the ith node, U N is the rated voltage of the network node, f L,j is the load rate of the jth line;

[0075] In step C4, the network power flow optimization target under the fault state is:

[0076] minf punish

[0077]

[0078]

[0079]

[0080] The flexible connection device is a flexible multi-state switch;

[0081] The constraints of the network power flow optimization objective before the fault are:

[0082]

[0083] In the above formula, sb j is the circuit breaker status of the jth line. When it is 0, it means the circuit breaker is open, and when it is 1, it means the circuit breaker is closed. flex,i , Q flex,i , S N,i are the output active power, output reactive power and rated capacity of the i-th port of the flexible multi-state switch respectively;

[0084] The constraints of the network power flow optimization objective under the fault state are:

[0085]

[0086] In step A, the distributed power output probability model includes a photovoltaic power generation output probability distribution model and a wind power generation output probability distribution model. The photovoltaic power generation output probability distribution model adopts a Beta distribution function, the wind power generation output probability distribution model adopts a Weibull distribution function, and the load power probability model adopts a normal distribution function.

[0087] In step B, the "working-fault" two-state model is:

[0088]

[0089]

[0090] In the above formula, TTF and TTR are respectively the normal operation time and fault duration of the component equipment, λ and μ are respectively the failure rate and repair rate of the component equipment, and R1 and R2 are random variables that obey the uniform distribution of [0,1]. The grid structure of the microgrid network includes: circuit breakers, transmission lines, node buses, transformers, and flexible connection equipment.

[0091] Embodiment 1:

[0092] See also Figure 1 , a method for evaluating the reliability of power supply of a microgrid network including a flexible connection device, wherein the grid structure of the microgrid network includes: a circuit breaker, a transmission line, a node bus, a transformer, a flexible connection device (see Figure 3 ), the system microgrid structure connected to the microgrid network mainly includes distributed power sources, energy storage equipment, loads (see Figure 4 ), follow these steps in order:

[0093] 1. Construct a photovoltaic power generation output probability distribution model, a wind power generation output probability distribution model, and a load power probability distribution model respectively, wherein the photovoltaic power generation output probability distribution model is constructed by:

[0094] Taking one day as a cycle, the uncertainty model of active power output is established for each 24-hour period, and the establishment process of the output uncertainty model for each period can be divided into two parts: light intensity probability distribution description and active power conversion. First, the light intensity probability distribution uses Beta distribution to describe its uncertainty:

[0095]

[0096] Where f(r) is the probability density function of light intensity r, Γ(·) is the gamma function, and r m is the light intensity corresponding to the maximum active output of photovoltaic power, b and c are the shape parameter and scale parameter of Beta distribution to be determined, which can be solved by the mean and variance calculation formula of Beta distribution;

[0097] Secondly, converting the light intensity into the maximum output of photovoltaic power generation can obtain the probability distribution of the maximum output of photovoltaic power generation:

[0098]

[0099] In the above formula, P solar is the maximum output of photovoltaic power generation, P M The installed effective capacity of photovoltaic distributed power sources;

[0100] The method for constructing the wind power generation output probability distribution model is as follows:

[0101] Similar to photovoltaic power generation, the process of establishing the uncertainty model of wind power output can be divided into two parts: wind speed probability distribution description and active power output conversion. First, the historical wind speed data at the location of the wind power plant is used in combination with the Weibull distribution of the wind speed probability model to describe the randomness of wind power output:

[0102]

[0103] In the above formula, f(v) is the probability density function of wind speed v, a and k are the scale parameter and shape parameter of Weibull distribution respectively. The parameters of Weibull distribution can be estimated by the least squares method;

[0104] Secondly, the probability distribution model of wind speed is transformed into "wind speed-wind power output" to obtain the maximum output probability distribution of wind power generation:

[0105]

[0106] In the above formula, P wind is the maximum output of wind power generation, v ci 、v co are the cut-in and cut-out wind speeds, v r is the rated output wind speed, P r The installed effective capacity of wind power distributed generation;

[0107] The method for constructing the load power probability model is:

[0108] Since the load power changes are cyclical, a load uncertainty model is established for each period within 24 hours based on historical load statistics, with one day as the cycle. The load uncertainty can be described by normal distribution:

[0109]

[0110] In the above formula, f(P) is the probability density function of load power P, μ P , σ P are the mean and standard deviation of the load, μ P and σ P The distribution parameters of can be calculated through historical data;

[0111] 2. Use the component failure rate λ and the component repair rate μ to establish a "working-failure" two-state model of component equipment in the microgrid network. The components used to describe the operating status here include but are not limited to: transmission lines, distributed power sources, energy storage systems, distribution transformers, and flexible connection equipment:

[0112]

[0113]

[0114] In the above formula, TTF and TTR are the normal operation time and fault duration of the component equipment, respectively; λ and μ are the failure rate and repair rate of the component equipment, respectively; R1 and R2 are random variables that obey the uniform distribution of [0,1];

[0115] 3. Simulate and generate system operation scenarios within the set operating life. Specifically, based on the constructed distributed power output and load power probability distribution model, the output value at each moment is generated through multiple sampling, so as to obtain a long-term power curve; based on the "working-fault" two-state model of the component equipment in the microgrid networking, multiple normal operation durations and fault durations of each component equipment are generated through multiple samplings. The switching time of each component state can be determined by accumulation, so as to determine the fault start time;

[0116] 3. Simulate the system operation according to the set operation step length, and go to step 4 when the component equipment fails;

[0117] 4. Determine the operation status before the fault by optimizing and calculating the network flow before the fault, wherein the network flow optimization target is:

[0118]

[0119]

[0120]

[0121]

[0122] In the above formula, P L,jis the line loss of the jth line in the network, f u,i 、f fL,j They are penalty terms f punish The voltage exceeds the limit, the load exceeds the limit, U i is the voltage of the ith node, U N is the rated voltage of the network node, f L,j is the load rate of the jth line;

[0123] Assuming that the flexible connection device is a flexible multi-state switch, the constraints of the above optimization objective are:

[0124]

[0125] In the above formula, the first one is the open-loop operation constraint, sb j is the circuit breaker state of the jth line. When it is 0, it means the circuit breaker is open, and when it is 1, it means the circuit breaker is closed. The second is the power constraint of the flexible multi-state switch, P flex,i , Q flex,i , S N,i are the output active power, output reactive power and rated capacity of the i-th port of the flexible multi-state switch respectively. The third one is the power balance constraint of the flexible multi-state switch.

[0126] 5. Take into account the load transfer strategy and optimize the calculation of the power flow under fault conditions.

[0127] The power flow under the fault state can be divided into two stages: emergency power support by flexible equipment and network reconstruction by switching operation. In the first stage, "emergency power support by flexible equipment", when the flexible equipment is not working, the network grid line trips due to a fault, resulting in partial formation of an island. The island is powered by the connected microgrid, and the energy storage device inside the microgrid provides emergency power support. When there is a power shortage inside the island, the connected flexible equipment starts to operate to realize load transfer. The duration of this stage is the time from the occurrence of the fault until the switching operation instruction is issued. For this stage, it is necessary to determine whether the two parts of the grid connected by the flexible connection device can operate normally. If not, calculate the load shedding amount, removal time and power shedding amount in this stage. In the second stage, "network reconstruction by switching operation", the operation and maintenance personnel reconstruct the network after determining the power supply restoration plan through calculation, so that the island in the first stage is reconnected to the grid. The duration of this stage is the time from the issuance of the switching operation instruction until the grid operates normally after the fault component is repaired. For this stage, it is determined whether the restored grid can operate normally under the condition that the flexible connection equipment works. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated.

[0128] The power flow optimization objectives in the above two stages are:

[0129] minf punish

[0130]

[0131]

[0132]

[0133]

[0134] In the above formula, f punish The expression is consistent with that in step 4. The difference lies in the topological structure of the grid. For example, the circuit breakers on both sides of the line where the fault occurs are disconnected, forming the network structure of the first stage. The flexible connection device in the middle of the grid becomes the only link connecting the two parts of the network. After the network reconstruction in the second stage, in addition to the flexible connection device in the middle, the various parts of the grid are also connected by lines.

[0135] See also Figure 2 The load shedding amount and power shedding amount are calculated by the following method:

[0136] For lines with overload, determine whether the end node of the line is a power sending end or a power receiving end. If it is a power receiving end, reduce the load of the end node until it operates normally; if it is a power sending end, cut off the distributed power supply of the end node until it operates normally.

[0137] For lines with loads that are not over the limit, determine whether the voltage of each node is over the limit. If the node voltage is higher than the upper limit, the distributed power supply of the node is reduced until normal operation; if the node voltage is lower than the lower limit, the load of the node is reduced until normal operation;

[0138] 6. Taking into account the microgrid operation strategy, record the load shedding amount, location and shedding time;

[0139] 7. Determine whether the simulated operation time has reached the operation life. If so, proceed to step 8. If not, return to step 3.

[0140] 8. Calculate the power supply reliability of the microgrid network based on the load shedding amount, location and shedding time of each fault within the operating life.

Claims

1. A method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device, characterized in that: The flexible connection device is a flexible multi-state switch; The evaluation method comprises the following steps in sequence: Step A, respectively constructing a distributed power output probability distribution model and a load power probability distribution model; Step B: Establish a "working-fault" two-state model of component equipment in the microgrid network; Step C: Based on the model constructed in steps A and B, a sequential simulation method is used to simulate the operation of the microgrid network frame to calculate the power supply reliability of the frame, which includes the following steps in sequence: Step C1: Based on the model constructed in steps A and B, simulate and generate system operation scenarios within the set operation period; Step C2, simulating the system operation according to the set operation step length, and entering step C3 when the component equipment fails; Step C3: Determine the running state before the fault by optimizing and calculating the network flow before the fault. The optimization target of the network flow before the fault is: In the above formula, P L,j is the line loss of the jth line in the network, f u,i 、f fL,j They are penalty terms f punish The voltage exceeds the limit, the load exceeds the limit, U i is the voltage of the ith node, U N is the rated voltage of the network node, f L,j is the load rate of the jth line; The constraints are: In the above formula, sb j is the circuit breaker status of the jth line. When it is 0, it means the circuit breaker is open, and when it is 1, it means the circuit breaker is closed. flex,i , Q flex,i , S N,i are the output active power, output reactive power and rated capacity of the i-th port of the flexible multi-state switch respectively; Step C4: Determine the load shedding amount, location and shedding time based on the network flow optimization under the fault state. The network flow optimization target under the fault state is: minf punish The constraints are: Step C5, judging whether the simulated operation time reaches the operation life, if so, proceeding to step C6, if not, returning to step C2; Step C6: Calculate the power supply reliability of the microgrid network according to the load shedding amount, location and shedding time of each fault within the operating life.

2. A method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device according to claim 1, characterized in that: In step C4, the network power flow optimization under the fault state includes two stages: emergency power support by flexible connection equipment and network reconstruction by switching operation; For the first stage, it is determined whether the two parts of the grid connected by the flexible connection device can operate normally. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated; For the second stage, it is determined whether the restored grid can operate normally under the condition that the flexible connection equipment works. If not, the load shedding amount, shedding time and power shedding amount in this stage are calculated.

3. A method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device according to claim 2, characterized in that: The load shedding amount and power shedding amount are calculated by the following method: For the line with overload, determine whether the end node of the line is a power sending end or a power receiving end. If it is a power receiving end, reduce the load of the end node until it runs normally, and record the load reduction amount; if it is a power sending end, cut off the distributed power supply of the end node until it runs normally, and record the power reduction amount; For lines whose loads are within the limit, determine whether the voltages of each node are beyond the limit. If the node voltage is higher than the upper limit, the distributed power supply of the node is reduced until it operates normally, and the amount of power cut is recorded; if the node voltage is lower than the lower limit, the load of the node is reduced until it operates normally, and the amount of load cut is recorded.

4. A method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device according to claim 1, characterized in that: In step A, the distributed power output probability model includes a photovoltaic power generation output probability distribution model and a wind power generation output probability distribution model. The photovoltaic power generation output probability distribution model adopts a Beta distribution function, the wind power generation output probability distribution model adopts a Weibull distribution function, and the load power probability model adopts a normal distribution function.

5. A method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device according to claim 1, characterized in that: In step B, the "working-failure" two-state model is: In the above formula, TTF and TTR are the normal operation time and fault duration of the component equipment, λ and μ are the failure rate and repair rate of the component equipment, and R1 and R2 are random variables that obey the uniform distribution of [0,1].

6. A method for evaluating the reliability of power supply of a microgrid network containing a flexible connection device according to claim 1, characterized in that: The grid structure of the microgrid networking includes: circuit breakers, transmission lines, node busbars, transformers, and flexible connection equipment.

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