CN114462648A - Power distribution network fault reconstruction based on SNOP - Google Patents

Power distribution network fault reconstruction based on SNOP Download PDF

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CN114462648A
CN114462648A CN202210314937.0A CN202210314937A CN114462648A CN 114462648 A CN114462648 A CN 114462648A CN 202210314937 A CN202210314937 A CN 202210314937A CN 114462648 A CN114462648 A CN 114462648A
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吴敏
王亚伟
于浩淼
尹忠东
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North China Electric Power University
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Abstract

The invention provides a fault recovery optimization method for an SNOP-containing power distribution network, which comprises the following steps: and establishing an optimization model on the basis of calculating the maximum power supply capacity of the SNOP by taking the minimum system load loss as an objective function, and solving by adopting a particle swarm optimization algorithm by taking the SNOP control target as a decision variable. The invention utilizes the fault recovery method of the power distribution network containing the SNOP to reduce the power loss load of the power distribution network, provide reliable voltage support for the power distribution network and improve the flexibility and the economical efficiency of the operation of the power distribution network.

Description

Power distribution network fault reconstruction based on SNOP
Technical Field
The invention belongs to the field of power distribution network fault recovery, and relates to a fault recovery optimization method for a power distribution network containing an SNOP.
Background
The distribution network is arranged at the tail end of the power system, directly serves different types and grades of power users, and plays the roles of distributing electric energy and serving customers. The proportion of nonlinear and impact loads in the power distribution network is continuously increased, and the permeability of distributed power generation and demand side resources is higher and higher, so that the operation of the power distribution system is increasingly complicated. In the existing fault processing and recovery technology under the power distribution automation level, after the fault is rapidly positioned and isolated, network reconstruction is carried out through the cooperation of a plurality of rows of switch actions, and power supply recovery of the power loss load in a non-fault section is completed. During this period, the fixed on/off time of the interconnection switch can cause a short-time power failure problem, and the repeated on/off operations of the switch can also cause great impact on the system. In recent years, students gradually propose power supply recovery methods to improve the fault recovery capability of the power distribution network. For example, a multi-terminal power supply ring network is formed by adopting feeders from different buses or substations, and an advanced power distribution automation system is matched, so that the operation economy and reliability of the power distribution system can be improved to a certain extent during fault treatment, but the power distribution system is easily influenced by factors such as multi-side power supply voltage difference, system equivalent impedance, load distribution and the like during power supply restoration to a non-fault area, and short-circuit current and a fault range are easily expanded due to the absence of corresponding tide control measures.
Therefore, the problem of fault recovery of the power distribution network is difficult to solve well only by means of the traditional power supply recovery method and power distribution automation means, and the development of one-time equipment which can be flexibly regulated and controlled on the power distribution network level is becoming increasingly urgent. With the continuous development of flexible technologies, new flexible power distribution equipment represented by dynamic voltage restorers, active power filters, solid-state transformers and the like is playing more and more important roles. The intelligent soft Switch (SNOP) facing the power distribution layer provides a new development direction for operation regulation and control of the power distribution network.
The invention can utilize the fault recovery optimization method of the power distribution network containing the SNOP, and the fault recovery optimization method can accurately control the active power and the reactive power of the feeder lines connected with the fault recovery optimization method, thereby realizing the power flow optimization of the power distribution network and improving the running economy of the power distribution network.
Disclosure of Invention
The applicant researches and improves the prior art and provides an optimization method for fault recovery of a power distribution network containing an SNOP.
In order to solve the problems, the invention adopts the following scheme:
a fault recovery optimization method for an SNOP-containing power distribution network is characterized by comprising the following steps:
(1) randomly extracting the state of the system selected to be in fault.
(2) And operating a system switch according to the position of the fault by combining the topological structure and the element characteristics of the system, realizing fault isolation and determining a power loss area and a normal power supply area.
(3) And analyzing the control mode of the SNOP under different operating conditions.
(4) And calculating the transfer capacity of the SNOP in the active power distribution network.
(5) And establishing a fault recovery optimization model containing the SNOP, performing load flow calculation by taking the minimum risk of system load loss as a target function and the output voltage of a VSC port at the SNOP fault side as a control variable, and verifying whether a system constraint condition is met.
(6) If the output of the SNOP port connected with the power loss area can meet the requirements of all loads in the power loss area, and the system power constraint, the node voltage and the branch current are not out of limit, all the loads in the power loss area can recover power supply, the average time of power failure of all the loads in the power loss area is the load transfer time, the risk of the load loss of the system is obtained, and if the load loss risk cannot be obtained, the next step of load shedding operation is carried out.
(7) In the process of load shedding, the section switch of the corresponding scheme needs to be selected to be switched off by calculating the comprehensive load priority of various schemes and selecting the scheme with the lowest level.
(8) And solving by using the SNOP control target as a decision variable and adopting a particle swarm optimization algorithm.
In the step (3), the control mode determination mode of SNOP under different operating conditions is as follows:
(1) the power distribution network operates under normal conditions;
SNOP operating in a power distribution network typically employs a PQ control mode, i.e., PQ control on one side and U on one sidedcAnd (5) controlling the Q.
(2) The power distribution network operates under fault conditions.
1) Both ends of the SNOP are networking side sub-networks
I.e. the power-off area can be connected with the upper part through the communication switchThe stage power supply is directly connected, the fault is rapidly isolated through the circuit breaker, then the interconnection switch is closed, and the SNOP normal side keeps UdcAnd the Q control mode and the fault side are set as the PQ control mode so as to realize real-time accurate adjustment of power flow between the connected feeders.
2) One end of the SNOP is a networking side sub-network, and the other end is an unconnection side sub-network
That is, the power-off area can not be directly connected with the superior power supply through the interconnection switch, the traditional interconnection switch is replaced by the SNOP, and the U is kept on the normal side of the SNOPdcQ control mode, SNOP fault side control mode set to VfAnd a control mode for providing voltage and frequency support for the offline side sub-network. At this time, SNOP is equivalent to a power supply of the offline side subnet.
In the step (4), the method for calculating the supply capacity of the power distribution network SNOP comprises the following steps:
(1) the objective function for solving the SNOP transfer capability is expressed as:
Pmax＝max P2 (1)
in the formula (1), PmaxFor transmitting maximum power, P, to the off-line side sub-network under the normal operating conditions of the sub-network on the on-line side2The active power output by the SNOP fault side.
(2) Solving the constraints of the SNOP transfer capability comprises the following steps:
node voltage constraint:
Vi.min≤Vi≤Vi.max (2)
and (3) branch current constraint:
Figure BDA0003569409870000021
in the formula (2), ViIs the I-node voltage, in formula (3), IjiThe branch current flowing to node i for node j.
Power flow constraint of the power distribution network:
Figure BDA0003569409870000022
Figure BDA0003569409870000023
Figure BDA0003569409870000024
node v is a node directly connected to the SNOP fault side exit, and in equation (4), ψvSet of branch end nodes, φ, for node v as head-endvA set of branch head nodes with node v as a terminal; p isjv、QjvActive and reactive power, R, respectively, transmitted to node v for node jjv、 XjvResistance and reactance, P, respectively, on branch jvv、QvRespectively the active power and the reactive power which flow into the node v except the branch vj; in the formula (5), ZvjIs the branch impedance, SvjIs the head end capacity of branch vj.
Figure BDA0003569409870000025
In the formula (7), Pv，SNOP、Qv，SNOPActive and reactive power, P, respectively, provided to node v for SNOPv,DG、Qv,DGActive power and reactive power respectively transmitted to the node v by the optical storage system connected with the node vv,LOAD、Qv,LOADRespectively the active power and the reactive power consumed by the load on node v.
Active power balance at two ends of the SNOP:
P1+P2＝0 (8)
capacity constraints at both ends of SNOP:
Figure BDA0003569409870000026
in formulae (8) to (9), P1、P2Respectively SNOP active power, Q1、Q2For reactive power on both sides of SNOP, S1、S2Capacity is accessed for both sides of SNOP.
And (4) solving by adopting a second-order cone programming method in combination with a series of constraint conditions.
In the step (4), the objective function is:
Figure BDA0003569409870000031
in the formula (10), αkThe load is divided into a first-level load, a second-level load and a third-level load as a load weight coefficient, wherein the first-level load weight coefficient is 2.0, the second-level load is 1.5, the third-level load is 1.0, and P iskThe load loss amount of the node k is shown, and N is the total load loss amount.
The constraint conditions are as follows:
(1) SNOP operation constraints and rotational power:
P1+P2＝0 (11)
Figure BDA0003569409870000032
P2≤Pmax (13)
(2) and (3) power flow constraint:
Figure BDA0003569409870000033
Figure BDA0003569409870000034
Figure BDA0003569409870000035
(3) node voltage constraint:
Vi.min≤Vi≤Vi.max (17)
(4) and (3) branch current constraint:
Figure BDA0003569409870000036
(5) radial distribution network restraint:
g∈G (19)
in the formula (19), G is a reconstructed network topology structure, and G is a radial network topology structure set;
in the step (7), the priority level of each cutting scheme may be calculated
Figure BDA0003569409870000037
Is ordered by the value of (a)kAs priority of load point k, EkCut for the severity of the load loss at load point k caused by a failure of device iiSet of points of removed load under the scenario), a larger value indicates a higher priority for the scenario and a larger loss of removed load. And preferentially cutting the load node with the smallest calculated value, checking whether the constraint condition is met, if not, continuously selecting a scheme to cut according to the sequence of the calculated values from small to large until all the constraint conditions are met, wherein the average power failure time of the cut load is the repair time of the fault element, and the average power failure time of the load which is not cut is the load transfer time, so that the load loss of the system is obtained.
In the step (8), the SNOP control target is used as a decision variable, a particle swarm optimization algorithm is adopted for solving, the number of particles, the iteration times and the population dimension are set, and the particle speed and the particle initial speed are initialized; in the binary particle swarm algorithm, the velocity vector iterative formula of the particles is the same as the particle swarm algorithm, and the position vectors are determined by adopting a Sigmoid function and a segmented comparison method.
Sigmoid function:
Figure BDA0003569409870000041
and (3) segment comparison:
Figure BDA0003569409870000042
the velocity vector iteration process is still:
Figure BDA0003569409870000043
in formulae (21) to (22), Pi t+1Is the position of the ith particle generation t +1, vi t+1Is the speed of the ith particle generation t +1, rand is a random number whose value is [0, 1 ]]In between, ω is the particle inertia coefficient, taken as 0.6, c1And c2Is the particle learning coefficient, 2.0, pbesti t、gbesti tRespectively an individual optimal solution and a global optimal solution in the current iteration process.
In the fault recovery process, the step of minimizing the load loss amount of the system is essentially to search for a proper SNOP terminal voltage, so that the influence of various random faults on the load loss of the system is minimum overall at the voltage level. And taking the voltage of the SNOP fault end as a decision control variable, performing multiple iterations on the particle swarm, and outputting an optimal solution and a corresponding objective function value after the iteration times are reached.
Drawings
FIG. 1 is a flow chart of the steps of a fault recovery optimization with SNOP
FIG. 2 is a topological diagram of an IEEE33 node system with SNOP in the embodiment
Detailed Description
The specific embodiments are further described with reference to the drawings and the control scheme.
Taking an IEEE-33 node as an example, the total load of a line is (3200+ j2300) kVA, the SNOP is arranged on interconnection switches 24-28, the VSC capacity at two ends of the SNOP is 1000kVA, the nodes 14 and 19 are provided with optical storage systems, the recovery condition after the fault occurs is verified, and the solution is carried out by using the scheme of the invention:
(1) randomly extracting the state of the system selected to be in fault.
(2) And operating a system switch according to the position of the fault by combining the topological structure and the element characteristics of the system, realizing fault isolation and determining a power loss area and a normal power supply area.
(3) And analyzing the control mode of the SNOP under different operating conditions.
1) The power distribution network operates under normal conditions;
SNOP operating in a power distribution network typically employs a PQ control mode, i.e., PQ control on one side and U on one sidedcAnd (5) controlling the Q.
2) The power distribution network operates under fault conditions.
One case is that both ends of SNOP are networking side subnets.
The area of losing the electricity promptly can be through interconnection switch and higher level power direct connection, and is kept apart the trouble through the circuit breaker rapidly, then closed interconnection switch can, SNOP normal side keeps UdcAnd the Q control mode and the fault side are set as the PQ control mode so as to realize real-time accurate adjustment of power flow between the connected feeders.
In another case, one end of the SNOP is a networking side sub-network, and the other end of the SNOP is a non-networking side sub-network
That is, the power-off area can not be directly connected with the superior power supply through the interconnection switch, the traditional interconnection switch is replaced by the SNOP, and the U is kept on the normal side of the SNOPdcQ control mode, SNOP fault side control mode set to VfAnd a control mode for providing voltage and frequency support for the offline side sub-network. At this time, SNOP is equivalent to a power supply of the offline side subnet.
If a fault occurs in a branch 19-20, the SNOP control mode is set to: fault side VfControl mode, normal side UdcAnd (3) controlling the mode by Q.
(4) And calculating the transfer capacity of the SNOP in the active power distribution network. The VSC capacity at both ends of SNOP is 1000 kVA.
The objective function for solving the SNOP transfer capability is expressed as:
Pmax＝max P2
in the formula, PmaxIn order to realize the connection loss under the normal operation condition of the sub-network on the networking sideMaximum power, P, of side subnet transmission2The active power output by the SNOP fault side.
Solving the constraints of the SNOP transfer capability comprises the following steps:
node voltage constraint:
Vi.min≤Vi≤Vi.max
and (3) branch current constraint:
Figure BDA0003569409870000051
in the formula, ViIs the I node voltage, IjiThe branch current flowing to node i for node j.
Power flow constraint of the power distribution network:
Figure BDA0003569409870000052
Figure BDA0003569409870000053
Figure BDA0003569409870000054
node v is the node directly connected to the SNOP fault side exit, wherevSet of branch end nodes, φ, for node v as head-endvA set of branch head nodes with node v as a terminal; pjv、QjvActive and reactive power, R, respectively, transmitted to node v for node jjv、XjvResistance and reactance, P, respectively, on branch jvv、QvRespectively the active power and the reactive power which flow into the node v except the branch vj; zvjIs the branch impedance, SvjIs the head end capacity of branch vj.
Figure BDA0003569409870000055
In the formula, Pv，SNOP、Qv，SNOPActive and reactive power, P, respectively, provided to node v for SNOPv,DG、Qv,DGActive power and reactive power respectively transmitted to the node v by the optical storage system connected with the node vv,LOAD、Qv,LOADRespectively the active power and the reactive power consumed by the load on node v.
Active power balance at two ends of the SNOP:
P1+P2＝0
capacity constraints at both ends of SNOP:
Figure BDA0003569409870000056
in the formula, P1、P2Respectively SNOP active power, Q1、Q2For reactive power on both sides of SNOP, S1、S2Capacity is accessed for both sides of SNOP.
And (4) solving by adopting a second-order cone programming method in combination with a series of constraint conditions.
(5) And establishing a fault recovery optimization model containing the SNOP, performing load flow calculation by taking the minimum risk of system load loss as a target function and the output voltage of a VSC port at the SNOP fault side as a control variable, and verifying whether a system constraint condition is met.
(6) If the output of the SNOP port connected with the power loss area can meet the requirements of all loads in the power loss area, and the system power constraint, the node voltage and the branch current are not out of limit, all the loads in the power loss area can recover power supply, the average time of power failure of all the loads in the power loss area is the load transfer time, the risk of the load loss of the system is obtained, and if the load loss risk cannot be obtained, the next step of load shedding operation is carried out.
(7) In the process of load shedding, the section switch of the corresponding scheme needs to be selected to be switched off by calculating the comprehensive load priority of various schemes and selecting the scheme with the lowest level. The priority level of each ablation scheme can be calculated
Figure BDA0003569409870000061
Is ordered by the value of (a)kAs the priority of load point k, EkCut for the severity of the load loss at load point k caused by a failure of device iiSet of points of removed load under the scenario), a larger value indicates a higher priority for the scenario and a larger loss of removed load. And preferentially cutting the load node with the smallest calculated value, checking whether the constraint condition is met, if not, continuously selecting a scheme to cut according to the sequence of the calculated values from small to large until all the constraint conditions are met, wherein the average power failure time of the cut load is the repair time of the fault element, and the average power failure time of the load which is not cut is the load transfer time, so that the load loss of the system is obtained.
(8) And solving by using the SNOP control target as a decision variable and adopting a particle swarm optimization algorithm. Setting the number of particles, the iteration times and the population dimension, and initializing the particle speed and the particle initial speed; in the binary particle swarm algorithm, the speed vector iterative formula of the particles is the same as the particle swarm algorithm, and the position vector is determined by adopting a Sigmoid function and a piecewise comparison method.
Sigmoid function:
Figure BDA0003569409870000062
and (3) segment comparison:
Figure BDA0003569409870000063
the velocity vector iteration process is still:
Figure BDA0003569409870000064
in the formula, Pi t+1Is the position of the ith particle generation t +1, vi t+1For the ith particleSpeed of t +1 generation, rand is a random number, whose value is taken to be [0, 1 ]]In between, ω is the particle inertia coefficient, taken as 0.6, c1And c2Is the particle learning coefficient, 2.0, pbesti t、gbesti tRespectively an individual optimal solution and a global optimal solution in the current iteration process.
In the fault recovery process, the step of minimizing the load loss amount of the system is essentially to search for a proper SNOP terminal voltage, so that the influence of various random faults on the load loss of the system is minimum overall at the voltage level. And taking the voltage of the SNOP fault end as a decision control variable, performing multiple iterations on the particle swarm, and outputting an optimal solution and a corresponding objective function value after the iteration times are reached.
The failure recovery strategy results are shown in the following table:
TABLE 1 Fault recovery policy results
Figure BDA0003569409870000065
According to the table, the SNOP replaces a traditional interconnection switch in a line, and the fault recovery capability of the power distribution network can be effectively improved. The invention adopts a binary particle swarm algorithm and combines SNOP to carry out optimization solution on the main network reconstruction scheme in a targeted manner, and can combine the steps to form an effective and implementable fault recovery scheme.

Claims (6)

1. A fault recovery optimization method for an SNOP-containing power distribution network is characterized by comprising the following steps:
(1) randomly extracting the state of the system selected to be in fault.
(2) And operating a system switch according to the position of the fault by combining the topological structure and the element characteristics of the system, realizing fault isolation and determining a power loss area and a normal power supply area.
(3) And analyzing the control mode of the SNOP under different operating conditions.
(4) And calculating the transfer capacity of the SNOP in the active power distribution network.
(5) And establishing a fault recovery optimization model containing the SNOP, performing load flow calculation by taking the minimum risk of system load loss as a target function and the output voltage of a VSC port at the SNOP fault side as a control variable, and verifying whether a system constraint condition is met.
(6) If the output of the SNOP port connected with the power loss area can meet the requirements of all loads in the power loss area, and the system power constraint, the node voltage and the branch current are not out of limit, all the loads in the power loss area can recover power supply, the average time of power failure of all the loads in the power loss area is the load transfer time, the risk of the load loss of the system is obtained, and if the load loss risk cannot be obtained, the next step of load shedding operation is carried out.
(7) In the process of load shedding, the section switch of the corresponding scheme needs to be selected to be switched off by calculating the comprehensive load priority of various schemes and selecting the scheme with the lowest level.
(8) And solving by using the SNOP control target as a decision variable and adopting a particle swarm optimization algorithm.
2. The method for optimizing fault recovery of a power distribution network containing SNOP according to claim 1, wherein in the step (3), the control modes of SNOP under different operating conditions are determined as follows:
(1) the power distribution network operates under normal conditions;
SNOP operating in a power distribution network typically employs a PQ control mode, i.e., PQ control on one side and U on one sidedcAnd (5) controlling the Q.
(2) The power distribution network operates under fault conditions.
1) Both ends of the SNOP are networking side sub-networks
The area of losing the electricity promptly can be through interconnection switch and higher level power direct connection, and is kept apart the trouble through the circuit breaker rapidly, then closed interconnection switch can, SNOP normal side keeps UdcAnd the Q control mode and the fault side are set as the PQ control mode so as to realize real-time accurate adjustment of power flow between the connected feeders.
2) One end of the SNOP is a networking side sub-network, and the other end is an unconnection side sub-network
That is, the power-off area can not be connected with the upper level through the communication switchThe power supplies are directly connected, the traditional interconnection switch is replaced by the SNOP, and the normal side of the SNOP keeps UdcQ control mode, SNOP fault side control mode set to VfAnd a control mode for providing voltage and frequency support for the disconnected side sub-network. At this time, SNOP is equivalent to a power supply of the offline side subnet.
3. The fault recovery optimization method for the power distribution network containing the SNOP according to claim 1, wherein in the step (4), the method for calculating the supply capacity of the power distribution network SNOP comprises the following steps:
(1) the objective function to solve for SNOP transfer capability is expressed as:
Pmax＝max P2 (1)
in the formula (1), PmaxFor transmitting maximum power, P, to the off-line side sub-network under the normal operating conditions of the sub-network on the on-line side2The active power output by the fault side of the SNOP.
(2) Solving the constraints of the SNOP transfer capability comprises the following steps:
node voltage constraint:
Vi.min≤Vi≤Vi.max (2)
and (3) branch current constraint:
Figure FDA0003569409860000011
in the formula (2), ViIs the I-node voltage, in formula (3), IjiThe branch current flowing to node i for node j.
Power flow constraint of the power distribution network:
Figure FDA0003569409860000021
Figure FDA0003569409860000022
Figure FDA0003569409860000023
node v is a node directly connected to the SNOP fault side exit, and in equation (4), ψvSet of branch end nodes, φ, for node v as head-endvA set of branch head nodes with node v as a terminal; pjv、QjvActive and reactive power, R, respectively, transmitted to node v for node jjv、XjvResistance and reactance, P, respectively, on branch jvv、QvRespectively the active power and the reactive power which flow into the node v except the branch vj; in the formula (5), ZvjIs the branch impedance, SvjIs the head end capacity of branch vj.
Figure FDA0003569409860000024
In the formula (7), Pv，SNOP、Qv，SNOPActive and reactive power, P, respectively, provided to node v for SNOPv,DG、Qv,DGActive power and reactive power respectively transmitted to the node v by the optical storage system connected with the node vv,LOAD、Qv,LOADRespectively the active power and the reactive power consumed by the load on node v.
Active power balance at two ends of the SNOP:
P1+P2＝0 (8)
capacity constraints at both ends of SNOP:
Figure FDA0003569409860000025
in formulae (8) to (9), P1、P2Respectively SNOP active power, Q1、Q2For reactive power on both sides of SNOP, S1、S2Capacity is accessed for both sides of SNOP.
And (4) solving by adopting a second-order cone programming method in combination with a series of constraint conditions.
4. The fault recovery optimization method for the power distribution network containing the SNOP of claim 1, wherein in the step (4), the objective function is as follows:
Figure FDA0003569409860000026
in the formula (10), αkThe load is divided into a first-level load, a second-level load and a third-level load as a load weight coefficient, wherein the first-level load weight coefficient is 2.0, the second-level load is 1.5, the third-level load is 1.0, and P iskThe load loss amount of the node k is shown, and N is the total load loss amount.
The constraint conditions are as follows:
(1) SNOP operation constraints and rotational power:
P1+P2＝0 (11)
Figure FDA0003569409860000031
P2≤Pmax (13)
(2) and (3) flow constraint:
Figure FDA0003569409860000032
Figure FDA0003569409860000033
Figure FDA0003569409860000034
(3) node voltage constraint:
Vi.min≤Vi≤Vi.max (17)
(4) and (3) branch current constraint:
Figure FDA0003569409860000035
(5) radial distribution network restraint:
in the G belongs to the G (19) formula (19), G is the reconstructed network topology, and G is the radial network topology set.
5. The fault recovery optimization method for the power distribution network with the SNOP of claim 1, wherein in the step (7), the priority level of each cutting scheme can be calculated
Figure FDA0003569409860000036
Is ordered by the value of (a)kAs the priority of load point k, EkCut for the severity of the load loss at load point k caused by a failure of device iiSet of points of removed load under the scenario), a larger value indicates a higher priority for the scenario and a larger loss of removed load. And preferentially cutting the load node with the smallest calculated value, checking whether the constraint condition is met, if not, continuously selecting a scheme to cut according to the sequence of the calculated values from small to large until all the constraint conditions are met, wherein the average power failure time of the cut load is the repair time of the fault element, and the average power failure time of the load which is not cut is the load transfer time, so that the load loss of the system is obtained.
6. The method for optimizing fault recovery of the power distribution network containing the SNOP of claim 1, wherein in the step (8), the SNOP control target is used as a decision variable, a particle swarm optimization algorithm is adopted for solving, the number of particles, the iteration times and the population dimension are set, and the particle speed and the initial particle speed are initialized; in the binary particle swarm algorithm, the velocity vector iterative formula of the particles is the same as the particle swarm algorithm, and the position vectors are determined by adopting a Sigmoid function and a segmented comparison method.
Sigmoid function:
Figure FDA0003569409860000037
and (3) segment comparison:
Figure FDA0003569409860000041
the velocity vector iteration process is still:
Figure FDA0003569409860000042
in formulae (21) to (22), Pi t+1Is the position of the ith particle generation t +1, vi t+1Is the speed of the ith particle generation t +1, rand is a random number whose value is [0, 1 ]]In between, ω is the particle inertia coefficient, taken as 0.6, c1And c2Is the particle learning coefficient, 2.0, pbesti t、gbesti tRespectively an individual optimal solution and a global optimal solution in the current iteration process.
In the fault recovery process, the step of minimizing the load loss amount of the system is essentially to search for a proper SNOP terminal voltage, so that the influence of various random faults on the load loss of the system is minimum overall at the voltage level. And taking the voltage of the SNOP fault end as a decision control variable, performing multiple iterations on the particle swarm, and outputting an optimal solution and a corresponding objective function value after the iteration times are reached.
CN202210314937.0A 2022-03-29 2022-03-29 Power distribution network fault reconstruction based on SNOP Pending CN114462648A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116388206A (en) * 2023-06-07 2023-07-04 国网天津市电力公司滨海供电分公司 Load shedding calculation method, system and readable medium under transformer N-1 fault

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116388206A (en) * 2023-06-07 2023-07-04 国网天津市电力公司滨海供电分公司 Load shedding calculation method, system and readable medium under transformer N-1 fault
CN116388206B (en) * 2023-06-07 2023-08-18 国网天津市电力公司滨海供电分公司 Load shedding calculation method, system and readable medium under transformer N-1 fault

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