CN116247679A - Optimized service recovery method based on soft switch auxiliary power distribution system - Google Patents
Optimized service recovery method based on soft switch auxiliary power distribution system Download PDFInfo
- Publication number
- CN116247679A CN116247679A CN202310256378.7A CN202310256378A CN116247679A CN 116247679 A CN116247679 A CN 116247679A CN 202310256378 A CN202310256378 A CN 202310256378A CN 116247679 A CN116247679 A CN 116247679A
- Authority
- CN
- China
- Prior art keywords
- node
- period
- power
- sop
- soft switch
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000009826 distribution Methods 0.000 title claims abstract description 77
- 238000011084 recovery Methods 0.000 title claims abstract description 48
- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000009471 action Effects 0.000 claims abstract description 19
- 230000006870 function Effects 0.000 claims description 27
- 239000003990 capacitor Substances 0.000 claims description 14
- 125000003275 alpha amino acid group Chemical group 0.000 claims description 6
- 150000001875 compounds Chemical class 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 5
- 230000009466 transformation Effects 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000002347 injection Methods 0.000 claims description 3
- 239000007924 injection Substances 0.000 claims description 3
- 239000008186 active pharmaceutical agent Substances 0.000 abstract description 7
- 238000005457 optimization Methods 0.000 abstract description 3
- 230000007704 transition Effects 0.000 abstract 1
- 238000004458 analytical method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 230000001276 controlling effect Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000192 social effect Effects 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses an optimization service recovery method based on a soft switch auxiliary power distribution system, which comprises the following steps: 1, determining control modes of two voltage source converters in an SOP according to the running state of a power distribution system, and constructing a power scheduling and self-adaptive control mode switching model of the SOP; 2 determining whether one or two VSCs of the SOP are located in the fault region using the virtual power flow, and determining when to perform a control mode transition of the SOP based on the fact that only one side of the VSCs in the SOP are connected to nodes without a parent node; 3, constructing a multi-period DS recovery model, and determining an optimal strategy of the discrete action traditional equipment, wherein the real-time active power, the reactive power and the like of SOP are in the whole recovery period; 4, constructing a coordination strategy with multiple time scales, and optimally utilizing the quick response capability of SOP on a quick time scale, so that the real-time uncertainty is relieved while the service life of a traditional discrete action device is ensured on a slow time scale.
Description
Technical Field
The invention belongs to the field of power distribution network fault optimization, and particularly relates to an optimization service recovery method based on a soft switch auxiliary power distribution system.
Background
In recent years, global climate changes, electric power systems are extremely susceptible to natural disasters and equipment failures, and may bring about serious economic and social effects. The elastic power system becomes a current research hot spot due to the strong fault resistance and the rapid recovery capability. In the power distribution system (distribution system, DS), two of the most common restoration measures are network reconfiguration and microgrid formation, but existing measures rarely take into account active regulation of the system voltage. Thus, there may be some voltage safety risk during the recovery process.
soft-Switching (SOP) has been used in the restoration of power distribution systems as a new type of fully-controlled power electronic equipment. The function of the SOP is based on the control modes of the converters on the two sides of the SOP, and the control modes of the converters need to be adjusted according to the changed network topology. The purpose of DS service restoration is to re-power as much as possible all end users under limited available power conditions. Power saving step down (conservation voltage reduction, CVR) is an idea to achieve power saving and peak load reduction by reducing the system voltage to within an acceptable range. Thus, in a fault scenario, the proportion of end users recovered using CVR is higher and the voltage of DS will also be at a lower level. In extreme cases, when dynamic network reconfiguration is used to achieve rapid recovery of the DS, frequent changes in system topology are likely to cause under-voltage problems at certain nodes, thereby affecting the recovery performance of the system.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an optimized service recovery method based on a soft switch auxiliary power distribution system, so that SOP (system on an active power) can be utilized to have voltage supporting capability and accurate power flow regulating capability during fault operation, thereby effectively eliminating adverse effects caused by voltage violations and further improving the recovery capability of the system.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the invention discloses an optimized service recovery method based on a soft switch auxiliary power distribution system, which is characterized by comprising the following steps:
s1: determining control modes of two voltage source converters in the intelligent soft switch SOP according to the running state of the power distribution system;
s2: constructing constraint conditions of virtual power flow:
s3: judging the direction of the virtual tide according to the constraint condition:
virtual power flow of line ij between node i and node j at time period t
If yes, the flow direction of the virtual power flow is from node i to node j;
virtual power flow of line ij between node i and node j at time period t
Negative, the flow direction of the virtual power flow is from node j to node i;
virtual power flow of line ij between node i and node j at time period t
At 0, the virtual tide is representedThe flow does not flow between the node j and the node i;
s4: if the generator exists in the island of a certain area as a virtual power source, the generator can meet the virtual power requirement in the whole area;
if no generator exists in an island of a certain area as a virtual power source, confirming that the injection virtual power of each node is negative according to a formula (7), providing virtual power for the whole area by an intelligent soft switch SOP, and controlling a control mode by constant direct current voltage-power by taking the intelligent soft switch SOP as a starting point of an island directed graph dc Q-PQ switching to constant DC voltage-passive inversion control V dc Q-Vf；
S5: when the intelligent soft switch SOP is a virtual power source, constructing a multi-period power distribution system recovery model;
s6: objective function for recovering multicycle distribution system model
An objective function divided into two time scales, comprising: objective function of slow time scale STD +.>
And the objective function of the fast time scale RTD +.>
S7: and solving the multi-period power distribution system recovery model to obtain model decision variables including SOP action, OLTC action, CBs action, line break, load and generator set output, and the model decision variables are used for guiding the power distribution system to recover faults.
The invention also provides an optimized service recovery method based on a soft switch auxiliary power distribution system, wherein S1 comprises the following steps:
s1-1: the optimal variables of the intelligent soft switch SOP consisting of active power and reactive power of the two voltage converters are obtained by using the formulas (1) - (4):
in the formulas (1) to (4),
respectively representing the active power and the reactive power injected by the intelligent soft switch SOP at the node i in the period t; />
Is the active power injected by the intelligent soft switch SOP at the node j in the period t; />
Is the active loss of the intelligent soft switch SOP at node i during period t; />
Is the active loss of the intelligent soft switch SOP at node j during period t; />
Is the loss coefficient of the intelligent soft switch SOP at the node i; />
The capacity of the intelligent soft switch SOP at the node i; />
And->
The upper limit and the lower limit of the reactive power of the intelligent soft switch SOP at the node i are respectively;
s1-2: defining the operating state of the power distribution system includes: no fault, line fault on one side of the intelligent soft switch SOP, line fault on both sides of the intelligent soft switch SOP;
if the running state of the power distribution system is fault-free, the control mode of the intelligent soft switch SOP is constant direct current voltage-power control, and is recorded as V dc Q-PQ；
If the running state of the power distribution system is a line fault at one side of the intelligent soft switch SOP, the control mode of the intelligent soft switch SOP is constant direct current voltage-passive inversion control, and is recorded as V dc Q-Vf, and the voltage of the fault side converter satisfies equation (5):
in the formula (5), the amino acid sequence of the compound,
is the voltage amplitude of the fault side converter in the intelligent soft switch SOP at the node i under the period t, U set Is a preset voltage lower limit for the fault side converter in the intelligent soft switch SOP.
S2 is a constraint condition for constructing a virtual power flow by using the formula (6) -formula (10):
in the formulas (6) to (10),
a virtual power flow representing a line ij between a node i and a node j in a period t; />
Representing the virtual injection power flow of node i at time period t; />
Representing the virtual power of the intelligent soft switch SOP port at node i during period t, +.>
Representing virtual power of an intelligent soft switch SOP port at a node j in a period t; />
A virtual power flow representing a line ik between a node i and a node k in a period t; y is t，ij A binary variable representing the connection state of the line ij at the time period t; ρ t，i Is the load recovery at node i for period t; lambda (lambda) t，i Is a binary variable of whether the node i is powered on or not in the period t, and M is a multiplier; omega shape l Representing all branches; omega shape lS Representing a branch node set connected with an intelligent soft switch SOP in a power distribution system; />
Representing the virtual power of the generator at node i for period t; n meterShowing the number of nodes in the power distribution network.
S5, the method comprises the following steps of:
s5-1: constructing an objective function of a recovery model of a multicycle power distribution system using (11)
In the formula (11), ω i The weight of the load at node i;
representing the active load quantity of the node i in the period t; alpha t，i Is the recovery rate of the load at the node i in the period t, and is more than or equal to 0 and less than or equal to alpha t，i ≤1，/>
Epsilon is an adjustable parameter; />
Is the active loss of the intelligent soft switch SOP at node i during period t; r is (r) ij Is the resistance of line ij, < >>
Is the square of the current of line ij; omega shape b Representing a set of nodes in a power distribution system;
s5-2: the constraint condition for constructing the multi-period power distribution system recovery model comprises the following steps: SOP constraint shown in formula (1) -formula (4), on-load tap changer OLTC constraint shown in formula (12), switched capacitor bank CBs constraint shown in formula (13), tide constraint shown in formula (14) -formula (19), and spanning tree constraint shown in formula (20) -formula (23);
in the formula (12), k ij，0 Representing the initial turns ratio, ak, of the on-load tap-changer OLTC on line ij ij Representing an increment of the on-load tap changer OLTC on line ij; k (K) t，ij Is the gear of the transformer transformation ratio on the line ij under the period t; k (K) t-1，ij Is a gear of the transformer transformation ratio on the line ij under the period t-1; u (U) t，j Is the reference voltage at node j for period t; n (N) T Is the total duration;
is the total number of steps of the on-load tap changer OLTC on line ij; />
The number of actions allowed by the on-load tap-changer OLTC;
in the formula (13), the amino acid sequence of the compound,
the reactive power injected at node i by switched capacitor bank CBs during period t; />
Is the number of CBs put into use at node i during period t; />
Is the number of CBs put into use at node i for period t-1;
the number of actions allowed by the switched capacitor bank CBs; />
Is the reactive power capacity of the capacitor at node i; />
The number of switched capacitor banks CBs installed;
in the formulae (14) - (19), P t，i ，Q t，i Active power and reactive power injected at node i in period t; i t，ij Is the current on line ij at time period t;
is the square of the voltage on node i for period t; />
Is the square of the voltage on node j for period t; p (P) t，ij ，Q t，ij Active and reactive power of the line ij in the period t; />
Is the active power of node i at time period tReactive load demand; />
Active power and reactive power injected at the node i by the distributed power supply in the period t respectively; />
Representing the reactive power injected by CBs at node i for period t;
in the formulae (20) - (23), beta t，ij Is a binary variable of whether the node i is a parent node of the node j in the period t, if yes, beta is given t，ij 1, otherwise, let beta t，ij Is 0; omega shape S Representing a set of substations in a power distribution system; c (C) i Is the neighbor node set of node i;
s5-3: in constant DC voltage-passive inversion control V dc Under Q-Vf, the intelligent soft switch SOP is used as a virtual power supply, so that the constraint condition of the fault side converter voltage is obtained by using the formula (24):
s6 is a target function for recovering the multicycle distribution system by using the formulas (25) and (26)Number of digits
An objective function divided into two time scales, comprising: objective function of slow time scale STD +.>
And the objective function of the fast time scale RTD +.>
In formulas (25) and (26), Δt and Δτ are two different time scales;
and->
Representing the objective function of equation (11) on the slow time scale STD and the fast time scale RTD, respectively; k represents a period.
And S4, converting the formulas (2), (4) and (14) to (17) into convex nonlinear formulas by using a second-order cone conversion method, and then solving the multicycle power distribution system recovery model.
The electronic device of the invention comprises a memory and a processor, wherein the memory is used for storing a program for supporting the processor to execute any one of the optimized service restoration methods, and the processor is configured to execute the program stored in the memory.
The invention relates to a computer readable storage medium, on which a computer program is stored, characterized in that the computer program when run by a processor performs any of the steps of the optimized service restoration method.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention adopts an optimized service recovery method based on a soft switch auxiliary power distribution system, combines CVR and SOP power flow regulation, utilizes the load transfer capability of SOP and a multi-time scale coordination strategy, combines positive measures of reducing load consumption and expanding recovery area, and overcomes the problems that the active regulation of system voltage is rarely considered in the prior art and certain voltage safety risk possibly exists in the recovery process, thereby effectively improving the fault recovery capability of the power distribution system and simultaneously better coordinating the power scheduling and control mode switching of CVR and SOP.
2. The invention adopts the method of combining CVR and SOP tide regulation, so that the recovery proportion of the terminal user after power failure is higher, the voltage safety in the recovery process is ensured, and the safety and reliability of the system are improved.
3. The invention uses the load transfer capability of SOP, and the fault side converter can be switched to the virtual power supply to make the affected area electrified again, thereby further improving the recovery capability of the system.
Drawings
FIG. 1 is a schematic diagram of a method of elasticity enhancement of a power distribution system;
FIG. 2 is a schematic diagram of a typical power distribution system fault scenario;
FIG. 3 is a schematic diagram of a two-time scale coordinated optimal recovery strategy;
FIG. 4 is a modified IEEE 33 node failure system topology illustration intent;
FIG. 5 is a graph comparing voltage distributions with CVR;
fig. 6 is a flow chart of a method of optimizing service restoration for a CVR-based SOP auxiliary power distribution system.
Detailed Description
In the embodiment, the optimized service recovery method based on the soft switch auxiliary power distribution system combines the positive measures of reducing load consumption and expanding recovery areas, can effectively improve the fault recovery capacity of the power distribution system, and fully utilizes the multi-time scale coordination strategy, so that the power scheduling and control mode switching of CVR and SOP can be well coordinated, and the practicability of the system is improved. Specifically, as shown in fig. 1, the method comprises the following steps:
s1: a power scheduling and adaptive control mode switching model of an intelligent soft Switch (SOP) is constructed, and the control modes of two voltage source converters (voltage source converter, VSC) in the intelligent soft switch SOP are determined according to the running states of the power distribution system (distribution system, DS):
s1-1: the optimal variables of the intelligent soft switch SOP consisting of active power and reactive power of the two voltage converters are obtained by using the formulas (1) - (4):
in the formulas (1) to (4),
respectively representing the active power and the reactive power injected by the intelligent soft switch SOP at the node i in the period t; />
Is the active power injected by the intelligent soft switch SOP at the node j in the period t; />
Is the active loss of the intelligent soft switch SOP at node i during period t; />
Is the active loss of the intelligent soft switch SOP at node j during period t; />
Is the loss coefficient of the intelligent soft switch SOP at the node i; />
The capacity of the intelligent soft switch SOP at the node i; />
And->
The upper limit and the lower limit of the reactive power of the intelligent soft switch SOP at the node i are respectively;
s1-2: defining the operating state of the power distribution system includes: no fault, line fault on one side of the intelligent soft switch SOP, line fault on both sides of the intelligent soft switch SOP;
in the DS operating state, three situations may occur, as shown in fig. 2:
1) No failure occurs.
2) Faults occur only on one side of the SOP.
3) Faults occur on both sides of the SOP.
Since the SOP itself cannot supply power, it cannot work in the third fault situation. If the running state of the power distribution system is fault-free, the control mode of the intelligent soft switch SOP is constant direct current voltage-power control, and is recorded as V dc Q-PQ；
If the running state of the power distribution system is a line fault at one side of the intelligent soft switch SOP, the control mode of the intelligent soft switch SOP is constant direct current voltage-passive inversion control, and is recorded as V dc Q-Vf, and the voltage of the fault side converter satisfies equation (5):
in the formula (5), the amino acid sequence of the compound,
is the voltage amplitude of the fault side converter in the intelligent soft switch SOP at the node i under the period t, U set The preset voltage lower limit of the fault side converter in the intelligent soft switch SOP; />
S2: constructing a constraint condition of the virtual power flow by using the formulas (6) - (10):
in the formulas (6) to (10),
a virtual power flow representing a line ij between a node i and a node j in a period t; />
Representing the virtual injection power flow of node i at time period t; />
Representing the virtual power of the intelligent soft switch SOP port at node i during period t, +.>
Representing virtual power of an intelligent soft switch SOP port at a node j in a period t; />
A virtual power flow representing a line ik between a node i and a node k in a period t; y is t，ij A binary variable representing the connection state of the line ij at the time period t; ρ t，i Is the load recovery at node i for period t; lambda (lambda) t，i Is a binary variable of whether the node i is powered on or not in the period t, and M is a multiplier; omega shape l Representing all branches; omega shape lS Representing a branch node set connected with an intelligent soft switch SOP in a power distribution system; />
Representing the virtual power of the generator at node i for period t; n represents the number of nodes in the power distribution network;
s3: judging the direction of the virtual tide according to the constraint condition:
when (when)
If yes, the flow direction of the virtual power flow is from node i to node j;
when (when)
Negative, the flow direction of the virtual power flow is from node j to node i;
when (when)
When the value is 0, the virtual power flow does not flow between the node j and the node i;
s4: if the generator exists in the island of a certain area as a virtual power source, the generator can meet the virtual power requirement in the whole area;
if no generator exists in an island of a certain area as a virtual power source, confirming that the injection virtual power of each node is negative according to a formula (7), providing virtual power for the whole area by an intelligent soft switch SOP, and controlling a control mode by constant direct current voltage-power by taking the intelligent soft switch SOP as a starting point of an island directed graph dc Q-PQ switching to constant DC voltage-passive inversion control V dc Q-Vf；
S5: when the intelligent soft switch SOP is a virtual power source, constructing a multi-period power distribution system recovery model;
s5-1: constructing an objective function of a recovery model of a multicycle power distribution system using (11)
In the formula (11), ω i The weight of the load at node i;
representing the active load quantity of the node i in the period t; alpha t，i Is the recovery rate of the load at the node i in the period t, and is more than or equal to 0 and less than or equal to alpha t，i ≤1，/>
Epsilon is an adjustable parameter; />
Is the active loss of the intelligent soft switch SOP at node i during period t; r is (r) ij Is the resistance of line ij, < >>
Is the square of the current of line ij; omega shape b Representing a set of nodes in a power distribution system; />
S5-2: the constraint condition for constructing the multi-period power distribution system recovery model comprises the following steps: SOP constraint shown in formula (1) -formula (4), on-load tap changer OLTC constraint shown in formula (12), switched capacitor bank CBs constraint shown in formula (13), tide constraint shown in formula (14) -formula (19), and spanning tree constraint shown in formula (20) -formula (23);
in the formula (12), k ij，0 Representing the initial turns ratio, ak, of the on-load tap-changer OLTC on line ij ij Representing an increment of the on-load tap changer OLTC on line ij; k (K) t，ij Is the gear of the transformer transformation ratio on the line ij under the period t; k (K) t-1，ij Is a gear of the transformer transformation ratio on the line ij under the period t-1; u (U) t，j Is the reference voltage at node j for period t; n (N) T Is the total duration;
is the total number of steps of the on-load tap changer OLTC on line ij; />
The number of actions allowed by the on-load tap-changer OLTC;
in the formula (13), the amino acid sequence of the compound,
the reactive power injected at node i by switched capacitor bank CBs during period t; />
Is the number of CBs put into use at node i during period t; />
Is the number of CBs put into use at node i for period t-1;
the number of actions allowed by the switched capacitor bank CBs; />
Is the reactive power capacity of the capacitor at node i; />
The number of switched capacitor banks CBs installed;
in the formulae (14) - (19), P t，i ，Q t，i Active power and reactive power injected at node i in period t; i t，ij Is the current on line ij at time period t;
is the square of the voltage on node i for period t; />
Is the square of the voltage on node j for period t; p (P) t，ij ，Q t，ij Active and reactive power of the line ij in the period t; />
Is the active and reactive load demand of node i at time period t; />
Active power and reactive power injected at the node i by the distributed power supply in the period t respectively; />
Representing the reactive power injected by CBs at node i for period t;
in the formulae (20) - (23), beta t，ij Is a binary variable of whether the node i is a parent node of the node j in the period t, if yes, beta is given t，ij 1, otherwise, let beta t，ij Is 0; omega shape S Representing a set of substations in a power distribution system; c (C) i Is the neighbor node set of node i;
s5-3: in constant DC voltage-passive inversion control V dc Under Q-Vf, the intelligent soft switch SOP is used as a virtual power supply, so that the constraint condition of the fault side converter voltage is obtained by using the formula (24):
s6: as shown in fig. 3, at the slow time scale, the decision of OLTC and CBs decision variables is proposed, and the action decision of SOP is regenerated simultaneously at the fast time scale by using the decision of OLTC and CBs at the previous slow scale, and the objective function is calculated by using the equation (25) and the equation (26)
An objective function divided into two time scales, comprising: objective function of slow time scale STD +.>
And the objective function of the fast time scale RTD +.>
In formulas (25) and (26), Δt and Δτ are two different time scales;
and->
Respectively expressed by the expression (11) on a slow time scale STD and a fast timeAn objective function on a scale RTD; k represents a period;
s5: and (3) converting the formulas (2), (4) and (14) to (17) into convex nonlinear formulas by using a second-order cone conversion method, and then solving a multi-period power distribution system recovery model to obtain model decision variables including SOP action, OLTC action, CBs action, line break, load and generator set output, wherein the model decision variables are used for guiding the power distribution system to recover faults.
In this embodiment, an electronic device includes a memory for storing a program supporting the processor to execute the above method, and a processor configured to execute the program stored in the memory.
In this embodiment, a computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the method described above.
For a better understanding of the present invention, the example analysis includes the following components:
1. example description and simulation result analysis
In order to verify the validity of the invention, the system shown in fig. 4 is used for carrying out calculation analysis. This example contains 6 photovoltaic arrays, two SOPs, 19 RCSs, one OLTC and two CBs. Omega during the test analysis i ，
Are all set to 1.M is set to 1000. Suppose the active CVR coefficient of the customer load is 1.769 and the reactive CVR coefficient is 2.215. In this test system, a natural disaster causes a failure of 4 lines. The voltage amplitude is [0.93,1.07 ]]p.u. The two time scales Δt and Δτ were set to 1 hour and 15 minutes, respectively. The prediction errors of solar energy and general load respectively obey normal distribution N (0,0.15) 2 ) And N (0,0.05) 2 )。
The voltage distribution of whether or not CVR is shown in fig. 5, and in order to fully embody the effectiveness of the proposed method, a mode is additionally set for comparison simulation analysis:
1) Mode 1: the SOP auxiliary service recovery strategy with CVR is applied.
2) Mode 2: service restoration policy without CVR.
The simulation program is implemented in Matlab environment in a computer with Windows10, intel (R) CoreTM i5 CPU@3.5GHz,8GB memory. The voltage distributions of the two key nodes in the system in the above 2 modes of operation are calculated and compared, respectively. The voltage distribution in both modes is shown in fig. 6, and specific statistics are shown in table 1.
TABLE 1
As can be seen from fig. 6 and table 1, mode 1 can reduce the voltage at most nodes of the system to a lower value due to the accurate power flow regulation capability of the SOP. Under the action of the CVR, the load of mode 1 is reduced by 2.2379MWh, and additional 1.4966MWh load is recovered further. Therefore, the SOP auxiliary recovery strategy with the CVR provided by the invention can improve the recovery performance of the power distribution system in a fault scene.
In this description, the schematic representations of the present invention are not necessarily for the same embodiment or example, and those skilled in the art may combine and combine the different embodiments or examples described in this description. Furthermore, the contents of the embodiments of the present specification are merely an enumeration of implementation forms of the inventive concept, and the scope of protection of the present invention should not be construed as being limited to the specific forms set forth in the embodiments, but also include equivalent technical means as will occur to those skilled in the art based on the inventive concept.
Claims (8)
1. An optimized service restoration method based on a soft switch auxiliary power distribution system is characterized by comprising the following steps:
s1: determining control modes of two voltage source converters in the intelligent soft switch SOP according to the running state of the power distribution system;
s2: constructing constraint conditions of virtual power flow:
s3: judging the direction of the virtual tide according to the constraint condition:
virtual power flow of line ij between node i and node j at time period t
If yes, the flow direction of the virtual power flow is from node i to node j;
virtual power flow of line ij between node i and node j at time period t
Negative, the flow direction of the virtual power flow is from node j to node i;
virtual power flow of line ij between node i and node j at time period t
When the value is 0, the virtual power flow does not flow between the node j and the node i;
s4: if the generator exists in the island of a certain area as a virtual power source, the generator can meet the virtual power requirement in the whole area;
if no generator exists in an island of a certain area as a virtual power source, confirming that the injection virtual power of each node is negative according to a formula (7), providing virtual power for the whole area by an intelligent soft switch SOP, and controlling a control mode by a constant direct current voltage-power control V by taking the intelligent soft switch SOP as a starting point of an island directed graph dc Q-PQ switching to constant DC voltage-passive inversion control V dc Q-Vf；
S5: when the intelligent soft switch SOP is a virtual power source, constructing a multi-period power distribution system recovery model;
s6: objective function for recovering multicycle distribution system model
An objective function divided into two time scales, comprising: objective function of slow time scale STD +.>
And the objective function of the fast time scale RTD +.>
S7: and solving the multi-period power distribution system recovery model to obtain model decision variables including SOP action, OLTC action, CBs action, line break, load and generator set output, and the model decision variables are used for guiding the power distribution system to recover faults.
2. The method for optimizing service restoration of a soft-switching-aided power distribution system of claim 1, wherein S1 comprises the steps of:
s1-1: the optimal variables of the intelligent soft switch SOP consisting of active power and reactive power of the two voltage converters are obtained by using the formulas (1) - (4):
in the formulas (1) to (4),
respectively representing the active power and the reactive power injected by the intelligent soft switch SOP at the node i in the period t; />
Is the active power injected by the intelligent soft switch SOP at the node j in the period t; />
Is the active loss of the intelligent soft switch SOP at node i during period t; />
Is the active loss of the intelligent soft switch SOP at node j during period t; />
Is the loss coefficient of the intelligent soft switch SOP at the node i; />
The capacity of the intelligent soft switch SOP at the node i;
and->
The upper limit and the lower limit of the reactive power of the intelligent soft switch SOP at the node i are respectively;
s1-2: defining the operating state of the power distribution system includes: no fault, line fault on one side of the intelligent soft switch SOP, line fault on both sides of the intelligent soft switch SOP;
if the running state of the power distribution system is fault-free, the control mode of the intelligent soft switch SOP is constant direct current voltage-power control, and is marked as V dc Q-PQ；
If the running state of the power distribution system is a line fault at one side of the intelligent soft switch SOP, the intelligent soft switchSOP is controlled by constant DC voltage-passive inversion control, and is marked as V dc Q-Vf, and the voltage of the fault side converter satisfies equation (5):
in the formula (5), the amino acid sequence of the compound,
is the voltage amplitude of the fault side converter in the intelligent soft switch SOP at the node i under the period t, U set Is a preset voltage lower limit for the fault side converter in the intelligent soft switch SOP.
3. The method for recovering optimized services of a soft-switching auxiliary power distribution system according to claim 2, wherein the constraint condition for constructing the virtual power flow by using the formula (6) -formula (10) is as follows:
formula (6) -formula (10)In the process, 
a virtual power flow representing a line ij between a node i and a node j in a period t; />
Representing the virtual injection power flow of node i at time period t; />
Representing the virtual power of the intelligent soft switch SOP port at node i during period t, +.>
Representing virtual power of an intelligent soft switch SOP port at a node j in a period t; />
A virtual power flow representing a line ik between a node i and a node k in a period t; y is t,ij A binary variable representing the connection state of the line ij at the time period t; ρ t,i Is the load recovery at node i for period t; lambda (lambda) t,i Is a binary variable of whether the node i is powered on or not in the period t, and M is a multiplier; omega shape l Representing all branches; omega shape lS Representing a branch node set connected with an intelligent soft switch SOP in a power distribution system; />
Representing the virtual power of the generator at node i for period t; n represents the number of nodes in the power distribution network.
4. A method of optimizing service restoration for a soft-switching-aided power distribution system as recited in claim 3, wherein S5 comprises the steps of:
s5-1: constructing an objective function of a recovery model of a multicycle power distribution system using (11)
In the formula (11), ω i The weight of the load at node i;
representing the active load quantity of the node i in the period t; alpha t,i Is the recovery rate of the load at node i at time period t,/->
Epsilon is an adjustable parameter; />
Is the active loss of the intelligent soft switch SOP at node i during period t; r is (r) ij Is the resistance of line ij, < >>
Is the square of the current of line ij; omega shape b Representing a set of nodes in a power distribution system;
s5-2: the constraint condition for constructing the multi-period power distribution system recovery model comprises the following steps: SOP constraint shown in formula (1) -formula (4), on-load tap changer OLTC constraint shown in formula (12), switched capacitor bank CBs constraint shown in formula (13), tide constraint shown in formula (14) -formula (19), and spanning tree constraint shown in formula (20) -formula (23);
in the formula (12), k ij,0 Representing the initial turns ratio, ak, of the on-load tap-changer OLTC on line ij ij Representing an increment of the on-load tap changer OLTC on line ij; k (K) t,ij Is under period tA gear of the transformer ratio on line ij; k (K) t-1,ij Is a gear of the transformer transformation ratio on the line ij under the period t-1; u (U) t,j Is the reference voltage at node j for period t; n (N) T Is the total duration;
is the total number of steps of the on-load tap changer OLTC on line ij; />
The number of actions allowed by the on-load tap-changer OLTC;
in the formula (13), the amino acid sequence of the compound,
the reactive power injected at node i by switched capacitor bank CBs during period t; />
Is the number of CBs put into use at node i during period t; />
Is the number of CBs put into use at node i for period t-1; />
The number of actions allowed by the switched capacitor bank CBs; />
Is the reactive power capacity of the capacitor at node i; />
Is installed switching powerThe number of container groups CBs;
in the formulae (14) - (19), P t,i ，Q t,i Active power and reactive power injected at node i in period t; i t,ij Is the current on line ij at time period t;
is the square of the voltage on node i for period t; />
Is the square of the voltage on node j for period t; p (P) t,ij ，Q t,ij Active and reactive power of the line ij in the period t; />
Is the active and reactive load demand of node i at time period t; />
Active power and reactive power injected at the node i by the distributed power supply in the period t respectively; />
Representing the reactive power injected by CBs at node i for period t; />
In the formulae (20) - (23), beta t,ij Is a binary variable of whether the node i is a parent node of the node j in the period t, if yes, beta is given t,ij 1, otherwise, let beta t,ij Is 0; omega shape S Representing a set of substations in a power distribution system; c (C) i Is the neighbor node set of node i;
s5-3: in constant DC voltage-passive inversion control V dc Under Q-Vf, the intelligent soft switch SOP is used as a virtual power supply, so that the constraint condition of the fault side converter voltage is obtained by using the formula (24):
5. the method for optimizing service restoration of a soft-switching-aided power distribution system of claim 4, wherein in S6 is an objective function of a multi-cycle power distribution system restoration model using equation (25) and equation (26)
An objective function divided into two time scales, comprising: objective function of slow time scale STD +.>
And the objective function of the fast time scale RTD +.>
In formulas (25) and (26), Δt and Δτ are two different time scales;
and->
Representing the objective function of equation (11) on the slow time scale STD and the fast time scale RTD, respectively; k represents a period.
6. The method for recovering optimized service based on soft-switching auxiliary power distribution system according to claim 4, wherein in S4, after the formulas (2), (4), (14) and (17) are converted into convex nonlinear formulas by using a second-order cone conversion method, the multicycle power distribution system recovery model is solved.
7. An electronic device comprising a memory and a processor, wherein the memory is configured to store a program that supports the processor to perform the optimized service restoration method of any one of claims 1-6, the processor being configured to execute the program stored in the memory.
8. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor performs the steps of the optimized service restoration method according to any of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310256378.7A CN116247679A (en) | 2023-03-16 | 2023-03-16 | Optimized service recovery method based on soft switch auxiliary power distribution system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310256378.7A CN116247679A (en) | 2023-03-16 | 2023-03-16 | Optimized service recovery method based on soft switch auxiliary power distribution system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116247679A true CN116247679A (en) | 2023-06-09 |
Family
ID=86631238
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310256378.7A Pending CN116247679A (en) | 2023-03-16 | 2023-03-16 | Optimized service recovery method based on soft switch auxiliary power distribution system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116247679A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118017507A (en) * | 2024-04-09 | 2024-05-10 | 合肥工业大学 | Virtual power flow-based fault recovery method for intelligent soft switch-containing power distribution system |
-
2023
- 2023-03-16 CN CN202310256378.7A patent/CN116247679A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118017507A (en) * | 2024-04-09 | 2024-05-10 | 合肥工业大学 | Virtual power flow-based fault recovery method for intelligent soft switch-containing power distribution system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Coordinated control for voltage regulation of distribution network voltage regulation by distributed energy storage systems | |
| Xiao et al. | Available transfer capability enhancement using FACTS devices | |
| CN108988322B (en) | Microgrid operation strategy optimization method considering system time-varying property | |
| CN109830976B (en) | Elastic operation regulation and control method for alternating current/direct current hybrid power distribution network | |
| Sutikno et al. | A review of recent advances on hybrid energy storage system for solar photovoltaics power generation | |
| CN114448228B (en) | Redundancy control method and system for direct-hanging energy storage converter based on port voltage state discrimination | |
| Selim et al. | Fast quasi‐static time‐series analysis and reactive power control of unbalanced distribution systems | |
| CN106875127B (en) | Unified power flow controller reliability modeling and access power grid reliability assessment method thereof | |
| CN103746388A (en) | Electric distribution network reactive-voltage three-level coordination control method | |
| CN116247679A (en) | Optimized service recovery method based on soft switch auxiliary power distribution system | |
| Zhang et al. | High-economic PV power compensation algorithm to mitigate voltage rise with minimal curtailment | |
| CN115133573A (en) | Power distribution network fault recovery rolling optimization method considering load photovoltaic randomness | |
| CN116706926A (en) | SOP auxiliary flexible power distribution system fault recovery method considering voltage regulation and control | |
| CN117375070A (en) | Distributed photovoltaic power coordination control method, system, medium and equipment | |
| Liu et al. | Risk assessment of cascading failure of distribution network with flexible multi-state switch | |
| CN109412192B (en) | Self-energy-storage multi-end back-to-back flexible straight device operation method | |
| CN114665500A (en) | Coordination control method and system for restraining overvoltage of power grid | |
| CN110098754B (en) | MMC redundancy submodule effective utilization rate calculation method considering standby redundancy | |
| CN113541138A (en) | Fan switching method and device suitable for mode conversion of direct-current power transmission system | |
| Kisengeu et al. | Under Voltage Load Shedding using Hybrid Metaheuristic Algorithms for Voltage Stability Enhancement: A Review | |
| CN105977993B (en) | A kind of reactive-load compensation method of the intelligent distribution system based on load | |
| Wang | Construction of coordinated operation control system of distribution network based on electric energy router | |
| Joshi et al. | Power oscillation damping using ultracapcitor and voltage source based FACTS controllers | |
| CN107681670A (en) | Power network distribution idle work optimization method | |
| Manju et al. | Intelligent control of Unified Power Flow Controller for stability enhancement of transmission systems |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |