CN116565842A - Power distribution network toughness assessment method, system and equipment based on multi-source collaborative strategy - Google Patents
Power distribution network toughness assessment method, system and equipment based on multi-source collaborative strategy Download PDFInfo
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- 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
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- 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
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract
The invention discloses a method, a system and equipment for evaluating toughness of a power distribution network based on a multi-source collaborative strategy, which relate to the technical field of power distribution network toughness evaluation and comprise the following steps: firstly, receiving electric topology information, line time sequence fault state, node power supply and load time sequence active power of a power distribution network; then, according to a pre-established system performance function of the power distribution network, obtaining a power distribution network toughness evaluation index; inputting an algorithm based on the maximum spanning tree and electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy; rolling optimization is carried out on the line time sequence fault state, the node power supply and the load time sequence active power by utilizing a multi-source cooperative operation strategy, so as to obtain power supply load time sequence power in each period; and finally, obtaining a power distribution network toughness evaluation result optimized by the multi-source collaborative operation strategy by using the power supply load time sequence power and the power distribution network toughness evaluation index.
Description
Technical Field
The invention relates to the technical field of power distribution network toughness assessment, in particular to a power distribution network toughness assessment method, system and equipment based on a multi-source collaborative strategy.
Background
In recent years, the frequency of occurrence of extreme natural disasters, damage to the power grid and outage losses have been rapidly increasing. In the face of power grid faults caused by extreme disasters and with extremely low probability and extremely high harm, traditional safety judgment criteria such as 'N-1' criteria based on reliability and the like are not suitable for evaluating the power distribution network capacity in extreme scenes because the 'large average' characteristics under the long time scale are more strengthened and concerned, and the operation characteristics of the power system in the extreme scenes can not be comprehensively and scientifically explained and described. Different from reliability, toughness focuses on the load loss condition of the power distribution network under the condition of small probability fault, and the system has the characteristics of short time, low frequency, strong sporadic property and the like, so that a set of new index system is needed to quantify the characteristics of the system under a new scene so as to compare the capability of each power distribution network system for resisting extreme faults, and a specific guiding standard is provided for improving the toughness and improving the system performance.
At present, the research on the toughness evaluation of the power distribution network mainly focuses on the establishment of toughness evaluation indexes, mainly aims at the overall loss condition of the load, does not deeply consider the damage caused by important load power loss, and does not measure the toughness performance from different angles. In addition, in the toughness evaluation, the resources in the network cannot be fully called, and the obtained result cannot objectively reflect the toughness performance of the power distribution network.
Disclosure of Invention
In order to solve the defects in the background art, the invention aims to provide a method, a system and equipment for evaluating the toughness of a power distribution network based on a multi-source collaborative strategy, which solve the problems that the toughness evaluation index of the power distribution network is incomplete, resources in the power distribution network are not fully scheduled during evaluation, and the solving efficiency of an optimization strategy model is low.
The aim of the invention can be achieved by the following technical scheme: a method for evaluating toughness of a power distribution network based on a multi-source cooperative strategy comprises the following steps:
receiving electrical topology information, line time sequence fault state, node power supply and load time sequence active power of a power distribution network;
obtaining a toughness evaluation index of the power distribution network according to a pre-established system performance function of the power distribution network;
inputting an algorithm based on the maximum spanning tree and electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy;
rolling optimization is carried out on the line time sequence fault state, the node power supply and the load time sequence active power by utilizing a multi-source cooperative operation strategy, so as to obtain power supply load time sequence power in each period;
and (3) utilizing the obtained power supply load time sequence power and the power distribution network toughness evaluation index to obtain a power distribution network toughness evaluation result after the optimization of the multi-source cooperative operation strategy.
Preferably, the system performance function of the power distribution network is as follows:
wherein R is s (t) providing a level for the weighted load; n (N) B Representing the number of all nodes in the power grid; omega i Dividing the load at the node i into an important load and a general load according to the importance level, and respectively assigning different weight coefficients;the amount of active load supplied to node i at time t.
Preferably, the power distribution network toughness evaluation index includes:
weighted load loss index:
maximum load loss index:
toughness recovery coefficient index:
important load average interrupt time index:
in the formula (2), R op (t) is a weighted load loss amount; r is R 0 The value of the system performance function in a normal state is a constant; t is t oe For faults to occur, the performance of the distribution network begins to decline after being influenced; t is t or The moment when the system starts to take the recovery strategy;
in the formula (3), the amino acid sequence of the compound,is the maximum load loss; r is R pd The lowest value of the performance function of the power distribution network system after the fault occurs;
in the formulas (4) and (5), RRC represents a toughness recovery coefficient; n represents the number of extreme scenes extracted; θ n Representing the occurrence probability of the nth scene; b (B) n Representing the equivalent loss rate of the load in the nth scene; t (T) n Representing the duration of the fault in the nth scenario; lambda (lambda) cr And lambda (lambda) co Weight coefficients respectively representing important loads and general loads;and->Respectively representing the power requirements of an important load and a general load in an nth scene at the time t; />And->Active power lost by an important load and a general load at the time t in the nth scene respectively;
in the formulas (6) and (7), MITCL represents an important load average interruption time; MITCL (MITCL) n Indicating the average interruption time of all important loads in the nth scene;indicating the time of the ith critical load interruption; omega shape cr Represent all of the importanceA set of loads; n (N) cr Indicating the number of important loads.
Preferably, the multi-source collaborative strategy optimization model is:
min f＝min(f 1 +w 0 f 2 ) (8)
wherein f 1 Representing the normalized weighted load loss amount, and taking the sum of the power demands of the loads of all nodes in all time periods as a reference value; f (f) 2 Representing the normalized system operation network loss, and taking the sum of the actual active power of each power supply in each period as a reference value; omega 0 Representing the weight coefficient.
Preferably, said f 1 And f 2 The calculation formula of (2) is as follows:
in the formula, N total The delta t number corresponding to the total duration of the occurrence process of the extreme scene is represented, namely the total period number of the study;representing the active power lost by the node load i in the period t; />The active power requirement of the node load i in the period t under the normal state is met; />Representing the total network loss of the system in a period t; n (N) G Representing the number of all power sources in the power distribution network, including distributed generation and energy storage; />Representing the actual active power output of the ith in-network power supply in a period t; n (N) uB The method comprises the steps of representing the number of nodes connected with an upper power grid in a power distribution network; />Active power injected in period t for the upper level power supply connected at node j.
Preferably, the process of inputting the maximum spanning tree based algorithm and the electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model comprises the following steps:
processing and optimizing integer variables representing the opening and closing states of the lines by adopting an algorithm based on a maximum spanning tree, aiming at forming a maximum power supply path, obtaining a new topology of the power distribution network, and defining the connection state of each line;
and optimizing the output power and the load loss power of each power supply by taking the minimum multi-objective weighting function as an optimization target based on the obtained new topology of the power distribution network to obtain a power supply output scheme and a load reduction scheme.
Preferably, the step of obtaining the time sequence power of the power supply load in each period includes the following steps:
setting the execution period of the multi-source cooperative strategy as delta T, wherein the minimum time interval for research is delta T, and delta T is more than delta T;
the following steps are performed in each deltat in turn;
inputting line fault state, power supply time sequence power and load time sequence power data of each delta T in delta T;
carrying out network reconstruction according to the line fault state in the first delta t, and establishing a maximum power supply path under a fault scene;
optimizing the source charge state in each delta t based on the reconstructed power supply unit network;
outputting the network state after the delta T is finished as the initial state of the next delta T;
and outputting all the power load time sequence power in delta t.
Preferably, the multi-source collaborative strategy optimization model needs to satisfy the following constraint conditions:
topology constraints:
β ij ，β ji ，z ij ∈{0，1} (15)
system operation constraints:
voltage relaxation constraint:
line power transfer constraints:
node load shedding constraint:
node voltage upper and lower limit constraints:
injection power constraint of superior power supply:
real-time internet power constraint of distributed photovoltaic:
distributed wind powerReal-time internet power constraint:
energy storage discharge power constraint:
energy storage state of charge constraints:
energy storage electric quantity balance constraint:
energy storage initial electric quantity constraint:
in the formulae (12) to (15), z ij To represent the 0-1 variable of the line connection state, when z ij When=1, it indicates that the line is operating normally and can be used as a branch in the spanning tree; when z ij When=0, the line fault is in the off state, and the maximum spanning tree consideration cannot be taken into consideration, and the complete graph needs to be excluded. Beta ij And beta ji Are all 0-1 variables, represent father-son relationship of node i and node j, and when node j is father node of node i, beta is ij =1 and β ji =0; on the contrary, beta ij =0 and β ji =1; if node i and node j are not connected with each other, then ij ＝β ji ＝z ij =0. B represents a set of all nodes in the power distribution network, B (i) represents a set formed by all nodes nearby the node i, and B/1 represents all nodes except the node 1;
in formula (16): i, j, s each represent a node, and delta (j) and pi (j) represent a downstream node set and an upstream node set of the node j, respectively; p (P) ij，t And Q ij，t Respectively representing real-time active power and reactive power flowing on a line ij in a period t;andrespectively representing active power and reactive power output by energy storage at a node j in a period t; />And->Respectively representing the active power of the photovoltaic power generation and the wind power generation at the node j in the period t; />Representing reactive power requirements of the load at the node j in a period t under a normal state; />Representing the reactive power lost by the load at node j during period t;
in formula (17): v (V) i，t And V j，t Respectively representing the voltage values of the node i and the node j in the period t; v (V) 0 Representing the rated voltage value of the node; m represents a very large constant; z ij，t Meaning of (1) and z ij Meaning the same, the value in each period is indicated by increasing the subscript t only
In formula (18): to restrict the flow of power to 0 when the line is disconnected, wherein,maximum transmission capacity for line ij;
in the formula (20):and->Respectively the maximum value and the minimum value of the voltage allowed at the node j;
in the formula (21):and->Representing maximum values of active power and reactive power allowed to be injected, respectively;
in formulae (22) - (23):and->Respectively representing real-time active power of photovoltaic power and wind power at a node j in a period t;
in formulas (24) - (27):and->Nominal values respectively representing the energy storage power and the capacity at the node j; SOC (State of Charge) min And SOC (System on chip) max The minimum value and the maximum value respectively represent the charge state of the stored energy, and are generally set to be 0.1 and 0.9; />Representing the residual quantity of energy stored at the node j in a period t; η (eta) d Representing the discharge efficiency of the stored energy; />And->And respectively representing the electric quantity value and the state of charge value of the energy stored at the node j at the initial moment of the extreme scene.
Preferably, a power distribution network toughness evaluation system based on a multi-source cooperative strategy comprises:
and a data receiving module: the method comprises the steps of receiving electrical topology information, line time sequence fault states, node power supplies and load time sequence active power of a power distribution network;
the index generation module is used for: the method comprises the steps of obtaining a toughness evaluation index of a power distribution network according to a pre-established system performance function of the power distribution network;
the strategy generation module: the method comprises the steps of inputting an algorithm based on a maximum spanning tree and electrical topology information of a power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy;
policy use module: the method comprises the steps of performing rolling optimization on line time sequence fault states, node power supplies and load time sequence active power by utilizing a multi-source cooperative operation strategy to obtain power supply load time sequence power in each period;
the index calculation module is used for: the method is used for utilizing the obtained power supply load time sequence power and the power distribution network toughness evaluation index, and optimizing the power distribution network toughness evaluation result through the multi-source cooperative operation strategy.
An apparatus, comprising:
one or more processors;
a memory for storing one or more programs;
when one or more of the programs are executed by one or more of the processors, the one or more of the processors implement a multi-source collaborative policy-based power distribution network toughness assessment method as described above.
The invention has the beneficial effects that:
according to the invention, the weighted load supply level is selected as a system performance function according to the toughness definition, indexes such as weighted load loss, maximum load loss, toughness recovery coefficient, important load average interruption time and the like are established from different dimensions, so that the toughness performance of the power distribution network can be more comprehensively evaluated; the invention adopts a two-stage solving method to implement the solution scheme of 'determining a new network first and optimizing the whole network operation' by decoupling the network reconstruction scheme formulation and the power load power optimization, thereby greatly reducing the complexity of the problem, improving the solving efficiency of the model and meeting the timeliness requirement of real-time rolling optimization.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to those skilled in the art that other drawings can be obtained according to these drawings without inventive effort;
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a topology structure diagram of a power distribution network based on an actual power supply unit improvement according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, a method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy includes the following steps:
receiving electrical topology information, line time sequence fault state, node power supply and load time sequence active power of a power distribution network;
obtaining a toughness evaluation index of the power distribution network according to a pre-established system performance function of the power distribution network;
inputting an algorithm based on the maximum spanning tree and electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy;
rolling optimization is carried out on the line time sequence fault state, the node power supply and the load time sequence active power by utilizing a multi-source cooperative operation strategy, so as to obtain power supply load time sequence power in each period;
and (3) utilizing the obtained power supply load time sequence power and the power distribution network toughness evaluation index to obtain a power distribution network toughness evaluation result after the optimization of the multi-source cooperative operation strategy.
The system performance function of the power distribution network is as follows:
wherein R is s (t) providing a level for the weighted load; n (N) B Representing the number of all nodes in the power grid; omega i Dividing the load at the node i into an important load and a general load according to the importance level, and respectively assigning different weight coefficients;the amount of active load supplied to node i at time t.
The toughness evaluation index of the power distribution network comprises the following components:
weighted load loss index:
maximum load loss index:
toughness recovery coefficient index:
important load average interrupt time index:
in the formula (2), R op (t) is a weighted load loss amount; r is R 0 The value of the system performance function in a normal state is a constant; t is t oe For faults to occur, the performance of the distribution network begins to decline after being influenced; t is t or The moment when the system starts to take the recovery strategy;
in the formula (3), the amino acid sequence of the compound,is the maximum load loss; r is R pd The lowest value of the performance function of the power distribution network system after the fault occurs;
in the formulas (4) and (5), RRC represents a toughness recovery coefficient; n represents the number of extreme scenes extracted; θ n Representing the occurrence probability of the nth scene; b (B) n Representing the equivalent loss rate of the load in the nth scene; t (T) n Representing the duration of the fault in the nth scenario; lambda (lambda) cr And lambda (lambda) co Weight coefficients respectively representing important loads and general loads;and->Respectively representing the power requirements of an important load and a general load in an nth scene at the time t; />And->Active power lost by an important load and a general load at the time t in the nth scene respectively;
in the formulas (6) and (7), MITCL represents an important load average interruption time; MITCL (MITCL) n Indicating the average interruption time of all important loads in the nth scene;indicating the time of interruption of the ith critical load；Ω cr Representing a set of all important loads; n (N) cr Indicating the number of important loads.
The multi-source collaborative strategy optimization model is as follows:
min f＝min(f 1 +w 0 f 2 ) (8)
wherein f 1 Representing the normalized weighted load loss amount, and taking the sum of the power demands of the loads of all nodes in all time periods as a reference value; f (f) 2 Representing the normalized system operation network loss, and taking the sum of the actual active power of each power supply in each period as a reference value; omega 0 Representing the weight coefficient.
Said f 1 And f 2 The calculation formula of (2) is as follows:
in the formula, N total The delta t number corresponding to the total duration of the occurrence process of the extreme scene is represented, namely the total period number of the study;representing the active power lost by the node load i in the period t; />The active power requirement of the node load i in the period t under the normal state is met; />Representing the total network loss of the system in a period t; n (N) G Representing the number of all power sources in the power distribution network, including distributed generation and energy storage; />Representing the actual active power output of the ith in-network power supply in a period t; n (N) uB The method comprises the steps of representing the number of nodes connected with an upper power grid in a power distribution network; />Active power injected in period t for the upper level power supply connected at node j.
The process of inputting the maximum spanning tree-based algorithm and the electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model comprises the following steps:
processing and optimizing integer variables representing the opening and closing states of the lines by adopting an algorithm based on a maximum spanning tree, aiming at forming a maximum power supply path, obtaining a new topology of the power distribution network, and defining the connection state of each line;
and optimizing the output power and the load loss power of each power supply by taking the minimum multi-objective weighting function as an optimization target based on the obtained new topology of the power distribution network to obtain a power supply output scheme and a load reduction scheme.
The step of obtaining the time sequence power of the power supply load in each period comprises the following steps:
setting the execution period of the multi-source cooperative strategy as delta T, wherein the minimum time interval for research is delta T, and delta T is more than delta T;
the following steps are performed in each deltat in turn;
inputting line fault state, power supply time sequence power and load time sequence power data of each delta T in delta T;
carrying out network reconstruction according to the line fault state in the first delta t, and establishing a maximum power supply path under a fault scene;
optimizing the source charge state in each delta t based on the reconstructed power supply unit network;
outputting the network state after the delta T is finished as the initial state of the next delta T;
and outputting all the power load time sequence power in delta t.
The multisource collaborative strategy optimization model needs to meet the following constraint conditions:
topology constraints:
β ij ，β ji ，z ij ∈{0，1} (15)
system operation constraints:
voltage relaxation constraint:
line power transfer constraints:
node load shedding constraint:
node voltage upper and lower limit constraints:
injection power constraint of superior power supply:
real-time internet power constraint of distributed photovoltaic:
real-time internet power constraint of distributed wind power:
energy storage discharge power constraint:
energy storage state of charge constraints:
energy storage electric quantity balance constraint:
energy storage initial electric quantity constraint:
in the formulae (12) to (15), z ij To represent the 0-1 variable of the line connection state, when z ij When=1, it indicates that the line is operating normally and can be used as a branch in the spanning tree; when z ij When=0, the line fault is in the off state, and the maximum spanning tree consideration cannot be taken into consideration, and the complete graph needs to be excluded. Beta ij And beta ji Are all 0-1 variables, represent father-son relationship of node i and node j, and when node j is father node of node i, beta is ij =1 and β ji =0; on the contrary, beta ij =0 and β ji =1; if node i and node j are not connected with each other, then ij ＝β ji ＝z ij =0. B represents a set of all nodes in the power distribution network, B (i) represents a set formed by all nodes nearby the node i, and B/1 represents all nodes except the node 1;
in formula (16): i, j, s each represent a node, and delta (j) and pi (j) represent a downstream node set and an upstream node set of the node j, respectively; p (P) ij，t And Q ij，t Respectively representing real-time active power and reactive power flowing on a line ij in a period t;andrespectively representing active power and reactive power output by energy storage at a node j in a period t; />And->Respectively representing the active power of the photovoltaic power generation and the wind power generation at the node j in the period t; />Representing reactive power requirements of the load at the node j in a period t under a normal state; />Representing the reactive power lost by the load at node j during period t;
in formula (17): v (V) i，t And V j，t Respectively representing the voltage values of the node i and the node j in the period t; v (V) 0 Representing the rated voltage value of the node; m represents a very large constant; z ij，t Meaning of (1) and z ij Meaning the same, the value in each period is indicated by increasing the subscript t only
In formula (18): to restrict the flow of power to 0 when the line is disconnected, wherein,maximum transmission capacity for line ij;
in the formula (20):and->Respectively the maximum value and the minimum value of the voltage allowed at the node j;
in the formula (21):and->Representing maximum values of active power and reactive power allowed to be injected, respectively;
in formulae (22) - (23):and->Respectively representing real-time active power of photovoltaic power and wind power at a node j in a period t;
in formulas (24) - (27):and->Nominal values respectively representing the energy storage power and the capacity at the node j; SOC (State of Charge) min And SOC (System on chip) max The minimum value and the maximum value respectively represent the charge state of the stored energy, and are generally set to be 0.1 and 0.9; />Representing the residual quantity of energy stored at the node j in a period t; η (eta) d Representing the discharge efficiency of the stored energy; />And->And respectively representing the electric quantity value and the state of charge value of the energy stored at the node j at the initial moment of the extreme scene.
It should be further described that, in a specific implementation process, the invention also provides a system for evaluating toughness of a power distribution network based on a multi-source collaborative strategy, which comprises:
and a data receiving module: the method comprises the steps of receiving electrical topology information, line time sequence fault states, node power supplies and load time sequence active power of a power distribution network;
the index generation module is used for: the method comprises the steps of obtaining a toughness evaluation index of a power distribution network according to a pre-established system performance function of the power distribution network;
the strategy generation module: the method comprises the steps of inputting an algorithm based on a maximum spanning tree and electrical topology information of a power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy;
policy use module: the method comprises the steps of performing rolling optimization on line time sequence fault states, node power supplies and load time sequence active power by utilizing a multi-source cooperative operation strategy to obtain power supply load time sequence power in each period;
the index calculation module is used for: the method is used for utilizing the obtained power supply load time sequence power and the power distribution network toughness evaluation index, and optimizing the power distribution network toughness evaluation result through the multi-source cooperative operation strategy.
The invention takes an improved power distribution network based on an actual power supply unit as an embodiment for testing, and the grid structure of the power distribution network is shown in figure 2. In the examples, the time period of the study was set to 20:00-24:00, and 20:00, the time interval delta T is 15min, and delta T is 1h; node 1 is a bus node in a 220kV transformer substation and is connected with an upper-level transformer substation through a same-pole double-circuit 220kV power transmission line; the nodes 2 to 7 are bus nodes in the 110kV transformer substation; the nodes 10, 15, 18, 22, 23 and 27 are important load nodes, are marked by red virtual frame triangles and red dots, and are required to be preferentially ensured to supply power during extreme scene occurrence due to serious loss caused by power failure, so that the weight factor is set to be 100; the rest nodes are general load nodes, marked by black dots, and the weight factor is set to be 1; the rated power of photovoltaic power generation accessed at the nodes 8, 12 and 18 is 1MW; the rated power of wind power accessed at the nodes 16 and 26 is 1MW; the rated power of the energy storage accessed by the nodes 22 and 23 is 0.5MW, and the rated capacity is 1MWh; the reference voltage is 10kV, and the range of the allowable fluctuation of the node voltage is 0.9-1.1 pu; the maximum transmission power of the line is 10MW.
The test results of the embodiment show that when the power distribution network faces extreme faults, after the power distribution network is optimized by the multi-source collaborative strategy, the results of each toughness evaluation index are as follows: the weighted load loss is 2029.3MW, the general load maximum loss is 9.5792MW, the important load maximum loss is 2.6296MW, the average interruption time of the important load is 1.25h, the toughness recovery coefficient is 0.6701, the power supply capacity of the power distribution network for supporting the load and guaranteeing uninterrupted power supply of the important load under the current resource configuration condition is comprehensively reflected, and the toughness of the power distribution network is effectively evaluated. The results verify the feasibility and effectiveness of the evaluation method provided by the invention.
Based on the same inventive concept, the present invention also provides a computer apparatus comprising: one or more processors, and memory for storing one or more computer programs; the program includes program instructions and the processor is configured to execute the program instructions stored in the memory. The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application SpecificIntegrated Circuit, ASIC), field-Programmable gate arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computational core and control core of the terminal for implementing one or more instructions, in particular for loading and executing one or more instructions within a computer storage medium to implement the methods described above.
It should be further noted that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which when executed by a processor performs the above method. The storage media may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing has shown and described the basic principles, principal features, and advantages of the present disclosure. It will be understood by those skilled in the art that the present disclosure is not limited to the embodiments described above, which have been described in the foregoing and description merely illustrates the principles of the disclosure, and that various changes and modifications may be made therein without departing from the spirit and scope of the disclosure, which is defined in the appended claims.
Claims (10)
1. A power distribution network toughness assessment method based on a multi-source cooperative strategy is characterized by comprising the following steps:
receiving electrical topology information, line time sequence fault state, node power supply and load time sequence active power of a power distribution network;
obtaining a toughness evaluation index of the power distribution network according to a pre-established system performance function of the power distribution network;
inputting an algorithm based on the maximum spanning tree and electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy;
rolling optimization is carried out on the line time sequence fault state, the node power supply and the load time sequence active power by utilizing a multi-source cooperative operation strategy, so as to obtain power supply load time sequence power in each period;
and (3) utilizing the obtained power supply load time sequence power and the power distribution network toughness evaluation index to obtain a power distribution network toughness evaluation result after the optimization of the multi-source cooperative operation strategy.
2. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 1, wherein a system performance function of the power distribution network is as follows:
wherein R is s (t) providing a level for the weighted load; n (N) B Representing the number of all nodes in the power grid; omega i Dividing the load at the node i into an important load and a general load according to the importance level, and respectively assigning different weight coefficients;the amount of active load supplied to node i at time t.
3. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 1, wherein the power distribution network toughness evaluation index comprises:
weighted load loss index:
maximum load loss index:
toughness recovery coefficient index:
important load average interrupt time index:
in the formula (2), R op (t) is a weighted load loss amount; r is R 0 The value of the system performance function in a normal state is a constant; t is t oe For faults to occur, the performance of the distribution network begins to decline after being influenced; t is t or The moment when the system starts to take the recovery strategy;
in the formula (3), the amino acid sequence of the compound,is the maximum load loss; r is R pd The lowest value of the performance function of the power distribution network system after the fault occurs;
in the formulas (4) and (5), RRC represents a toughness recovery coefficient; n represents the number of extreme scenes extracted; θ n Representing the occurrence probability of the nth scene; b (B) n Representing the equivalent loss rate of the load in the nth scene; t (T) n Representing the duration of the fault in the nth scenario; lambda (lambda) cr And lambda (lambda) co Weight coefficients respectively representing important loads and general loads;and->Respectively representing the important load and the general load in the nth scene at tPower requirements for the etch; />And->Active power lost by an important load and a general load at the time t in the nth scene respectively;
in the formulas (6) and (7), MITCL represents an important load average interruption time; MITCL (MITCL) n Indicating the average interruption time of all important loads in the nth scene;indicating the time of the ith critical load interruption; omega shape cr Representing a set of all important loads; n (N) cr Indicating the number of important loads.
4. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 1, wherein the multi-source collaborative strategy optimization model is:
minf＝min(f 1 +w 0 f 2 )(8)
wherein f 1 Representing the normalized weighted load loss amount, and taking the sum of the power demands of the loads of all nodes in all time periods as a reference value; f (f) 2 Representing the normalized system operation network loss, and taking the sum of the actual active power of each power supply in each period as a reference value; omega 0 Representing the weight coefficient.
5. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 4, wherein f is 1 And f 2 The calculation formula of (2) is as follows:
in the formula, N total The delta t number corresponding to the total duration of the occurrence process of the extreme scene is represented, namely the total period number of the study;representing the active power lost by the node load i in the period t; />The active power requirement of the node load i in the period t under the normal state is met; />Representing the total network loss of the system in a period t; n (N) G Representing the number of all power sources in the power distribution network, including distributed generation and energy storage; />Representing the actual active power output of the ith in-network power supply in a period t; n (N) uB The method comprises the steps of representing the number of nodes connected with an upper power grid in a power distribution network; />Active power injected in period t for the upper level power supply connected at node j.
6. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 1, wherein the process of inputting the maximum spanning tree based algorithm and the electrical topology information of the power distribution network into a pre-established multi-source collaborative strategy optimization model comprises the steps of:
processing and optimizing integer variables representing the opening and closing states of the lines by adopting an algorithm based on a maximum spanning tree, aiming at forming a maximum power supply path, obtaining a new topology of the power distribution network, and defining the connection state of each line;
and optimizing the output power and the load loss power of each power supply by taking the minimum multi-objective weighting function as an optimization target based on the obtained new topology of the power distribution network to obtain a power supply output scheme and a load reduction scheme.
7. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 1, wherein the obtaining the time-series power of the power load in each period comprises the following steps:
setting the execution period of the multi-source cooperative strategy as delta T, wherein the minimum time interval for research is delta T, and delta T is more than delta T;
the following steps are performed in each deltat in turn;
inputting line fault state, power supply time sequence power and load time sequence power data of each delta T in delta T;
carrying out network reconstruction according to the line fault state in the first delta t, and establishing a maximum power supply path under a fault scene;
optimizing the source charge state in each delta t based on the reconstructed power supply unit network;
outputting the network state after the delta T is finished as the initial state of the next delta T;
and outputting all the power load time sequence power in delta t.
8. The method for evaluating toughness of a power distribution network based on a multi-source collaborative strategy according to claim 4, wherein the multi-source collaborative strategy optimization model is required to satisfy the following constraint conditions:
topology constraints:
β ij ，β ji ，z ij ∈{0，1} (15)
system operation constraints:
voltage relaxation constraint:
line power transfer constraints:
node load shedding constraint:
node voltage upper and lower limit constraints:
injection power constraint of superior power supply:
real-time internet power constraint of distributed photovoltaic:
real-time internet power of distributed wind powerConstraint:
energy storage discharge power constraint:
energy storage state of charge constraints:
energy storage electric quantity balance constraint:
energy storage initial electric quantity constraint:
in the formulae (12) to (15), z ij To represent the 0-1 variable of the line connection state, when z ij When=1, it indicates that the line is operating normally and can be used as a branch in the spanning tree; when z ij When=0, it indicates that the line fault is in an off state, the maximum spanning tree consideration cannot be taken into account, the complete graph needs to be eliminated, β ij And beta ji Are all 0-1 variables, represent father-son relationship of node i and node j, and when node j is father node of node i, beta is ij =1 and β ji =0; on the contrary, beta ij =0 and β ji =1; if node i and node j are not connected with each other, then ij ＝β ji ＝z ij =0, B represents a set of all nodes in the distribution network, B (i) represents a set of all nodes in the vicinity of node i, and B/1 represents all nodes except node 1;
in formula (16): i, j, s each represent a node, and delta (j) and pi (j) represent a downstream node set and an upstream node set of the node j, respectively; p (P) ij，t And Q ij，t Separate tableReal-time active power and reactive power flowing on line ij in period t are shown;and->Respectively representing active power and reactive power output by energy storage at a node j in a period t; />And->Respectively representing the active power of the photovoltaic power generation and the wind power generation at the node j in the period t; />Representing reactive power requirements of the load at the node j in a period t under a normal state; />Representing the reactive power lost by the load at node j during period t;
in formula (17): v (V) i，t And V j，t Respectively representing the voltage values of the node i and the node j in the period t; v (V) 0 Representing the rated voltage value of the node; m represents a very large constant; z ij，t Meaning of (1) and z ij Meaning the same, the value in each period is indicated by increasing the subscript t only
In formula (18): to restrict the flow of power to 0 when the line is disconnected, wherein,maximum transmission capacity for line ij;
in the formula (20):and->Respectively the maximum value and the minimum value of the voltage allowed at the node j;
in the formula (21):and->Representing maximum values of active power and reactive power allowed to be injected, respectively;
in formulae (22) - (23):and->Respectively representing real-time active power of photovoltaic power and wind power at a node j in a period t;
in formulas (24) - (27):and->Nominal values respectively representing the energy storage power and the capacity at the node j; SOC (State of Charge) min And SOC (System on chip) max The minimum value and the maximum value respectively represent the charge state of the stored energy, and are generally set to be 0.1 and 0.9; />Representing the residual quantity of energy stored at the node j in a period t; η (eta) d Representing the discharge efficiency of the stored energy; />And->And respectively representing the electric quantity value and the state of charge value of the energy stored at the node j at the initial moment of the extreme scene.
9. A distribution network toughness assessment system based on a multi-source cooperation strategy is characterized by comprising:
and a data receiving module: the method comprises the steps of receiving electrical topology information, line time sequence fault states, node power supplies and load time sequence active power of a power distribution network;
the index generation module is used for: the method comprises the steps of obtaining a toughness evaluation index of a power distribution network according to a pre-established system performance function of the power distribution network;
the strategy generation module: the method comprises the steps of inputting an algorithm based on a maximum spanning tree and electrical topology information of a power distribution network into a pre-established multi-source collaborative strategy optimization model to obtain a multi-source collaborative operation strategy;
policy use module: the method comprises the steps of performing rolling optimization on line time sequence fault states, node power supplies and load time sequence active power by utilizing a multi-source cooperative operation strategy to obtain power supply load time sequence power in each period;
the index calculation module is used for: the method is used for utilizing the obtained power supply load time sequence power and the power distribution network toughness evaluation index, and optimizing the power distribution network toughness evaluation result through the multi-source cooperative operation strategy.
10. An apparatus, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by one or more of the processors, causes the one or more processors to implement a multi-source collaborative policy-based power distribution network toughness assessment method as claimed in any one of claims 1-8.
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| CN117394311B (en) * | 2023-09-26 | 2024-05-24 | 国网宁夏电力有限公司经济技术研究院 | Power distribution network toughness assessment and emergency control method based on multi-source information fusion |
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| CN117394311A (en) * | 2023-09-26 | 2024-01-12 | 国网宁夏电力有限公司经济技术研究院 | Power distribution network toughness assessment and emergency control method based on multi-source information fusion |
| CN117394311B (en) * | 2023-09-26 | 2024-05-24 | 国网宁夏电力有限公司经济技术研究院 | Power distribution network toughness assessment and emergency control method based on multi-source information fusion |
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