CN115411735A - Method, system and equipment for calculating expected non-supplied electric quantity of power distribution network - Google Patents
Method, system and equipment for calculating expected non-supplied electric quantity of power distribution network Download PDFInfo
- Publication number
- CN115411735A CN115411735A CN202211119436.3A CN202211119436A CN115411735A CN 115411735 A CN115411735 A CN 115411735A CN 202211119436 A CN202211119436 A CN 202211119436A CN 115411735 A CN115411735 A CN 115411735A
- Authority
- CN
- China
- Prior art keywords
- power
- load
- distribution network
- model
- branch
- 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
- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000004364 calculation method Methods 0.000 claims abstract description 63
- 238000009434 installation Methods 0.000 claims abstract description 50
- 238000005457 optimization Methods 0.000 claims abstract description 46
- 238000010248 power generation Methods 0.000 claims abstract description 29
- 239000011159 matrix material Substances 0.000 claims abstract description 23
- 238000006243 chemical reaction Methods 0.000 claims description 21
- 238000010276 construction Methods 0.000 claims description 9
- 230000008439 repair process Effects 0.000 claims description 9
- 239000013256 coordination polymer Substances 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 4
- 230000008901 benefit Effects 0.000 abstract description 3
- 238000011156 evaluation Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000014509 gene expression Effects 0.000 description 3
- 238000011144 upstream manufacturing Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000007727 cost benefit analysis Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000006467 substitution reaction 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
-
- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/388—Islanding, i.e. disconnection of local power supply from the network
-
- 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
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution 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
- 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]
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Power Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Computing Systems (AREA)
- Computer Hardware Design (AREA)
- Computer Networks & Wireless Communication (AREA)
- Operations Research (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The method comprises the steps of obtaining a network topology model of the power distribution network containing the distributed power supply and forming a node incidence matrix for the topology connection relation of the network topology model; acquiring the load demand of each bus node and the installation capacity of each distributed power generation device in the network topology model and constructing a virtual tidal flow balance model; constructing an actual power supply shortage load model of the power distribution network according to the fault condition and the virtual power flow balance model and calculating the actual power supply shortage load; acquiring fault parameters of electrical elements in the power distribution network, and constructing an expected non-supplied electric quantity calculation model according to actual power shortage loads and the fault parameters; and constructing a linear programming optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supplied electric quantity calculation model, and calculating the expected non-supplied electric quantity of the power distribution network. The method has the advantages of high speed, accurate calculation and high efficiency in calculating the expected non-supplied electric quantity of the power distribution network.
Description
Technical Field
The application relates to the technical field of power distribution networks, in particular to a method, a system and equipment for calculating expected non-supplied electric quantity of a power distribution network.
Background
The power distribution network is used as a part of a power system directly connected with users, and the power supply reliability of the power distribution network directly influences the power utilization experience of the users. Reliability for a power distribution network is typically quantitatively evaluated by using quantified reliability indicators. According to the reliability evaluation result, hidden dangers existing in the power distribution network can be found out, the hidden dangers are removed in a targeted mode, the reliability of the system is improved, and cost benefit analysis of the reliability of the evaluation system can be carried out. The reliability indexes of the power distribution network comprise expected values of power shortage time, expected values of power shortage, average system outage frequency, average annual outage time, average user outage frequency, average power supply availability rate, average power shortage and the like of each load point, a transformer substation and the power distribution network.
Most of the existing reliability evaluation algorithms for the power distribution network are traditional reliability evaluation algorithms such as an analytic method or a Monte Carlo algorithm, and usually comprise complex topology search and logic judgment, and are difficult to use mathematical analytic expression to express explicitly, so that the solving efficiency is not high, and the method is difficult to be effectively combined with a mathematical planning model.
Disclosure of Invention
The embodiment of the application provides a method, a system and equipment for calculating the expected and unprovided electric quantity of a power distribution network, which are used for solving the technical problems that the existing solving mode for the reliability index of the power distribution network is difficult to combine with a mathematical programming model, and the efficiency is low.
In order to achieve the above object, the embodiments of the present application provide the following technical solutions:
a method for calculating the expected non-supplied electric quantity of a power distribution network comprises the following steps:
acquiring a network topology model of a power distribution network containing a distributed power supply, and forming a node incidence matrix according to the topological connection relation of the network topology model;
acquiring the load demand of each bus node and the installation capacity of each distributed power generation device in the network topology model, and constructing a virtual tide balance model according to all the load demands and the installation capacity;
according to the fault condition and the virtual tide balance model, constructing an actual power supply shortage load model of each branch downstream when a line element fault occurs in the power distribution network, and acquiring the actual power supply shortage load of each branch downstream when the line element fault occurs in the power distribution network based on the actual power supply shortage load model;
acquiring fault parameters of electrical elements in the power distribution network, and constructing an expected non-supplied electric quantity calculation model according to the actual power shortage load and the fault parameters;
and constructing a linear programming optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supplied electric quantity calculation model, and performing optimization solution on the linear programming optimization model to obtain the expected non-supplied electric quantity of the power distribution network.
Preferably, the optimization solution of the linear programming optimization model is performed, and obtaining the expected non-supplied electric quantity of the power distribution network includes: optimizing and solving the linear programming optimization model by adopting a Gurobi branch-and-bound method and target conditions to obtain the expected non-supplied electric quantity of the power distribution network; wherein the target condition is that the minimum value of the actual power shortage load and the distance between the relaxation solution and the convergence solution in Gurobi are selected to be 0.1%.
Preferably, the virtual power flow balancing model comprises: the load demand virtual power flow balancing equation comprises the following steps:
the capacity virtual power flow balance equation is as follows:
in the formula, omega is the branch set of the distribution network, D b For the total maximum load demand downstream of branch b,
for the virtual load demand flow in the positive direction for branch b,
for the virtual load demand flow in the negative direction of branch b, M D The virtual power flow balance equation takes a large enough positive integer for the load demand,
is a first auxiliary binary variable, A i,b The numerical value of an element corresponding to the ith row and the mth column in the node incidence matrix is psi, the collection of nodes i of the power distribution network is D i Is the load demand of the load node i; d s Is the load demand of the power node s; g s For the total load demand downstream of the supply node s, CDG b The power capacity of the conversion efficiency is accounted for in all distributed generators downstream of branch b,
capacity flow is installed for the virtual load in the forward direction for branch b,
capacity flow is installed for the virtual load in the negative direction for branch b,
is a second auxiliary binary variable, M DG A positive integer which is large enough is taken for the capacity virtual power flow balance equation;
the ac installation capacity of the distributed generation apparatus installed for the load node i,
the dc installation capacity of the distributed power generation apparatus installed for the load node i,
the ac installation capacity of the distributed power generation apparatus installed for the power source node i,
DC installation capacity, η, of distributed power plants installed for a power node i ivt For the conversion efficiency of an inverter in a power distribution network,
the total installed capacity of the distributed generation unit is taken into account downstream of the power source node s and with the conversion efficiency.
Preferably, the actual power supply shortage load model is represented by a loss load equation, and the loss load equation is as follows:
in the formula, omega is the branch set of the distribution network, D b For the total maximum load demand downstream of branch b, CDG b Taking into account the supply capacity, H, of the conversion efficiency for all distributed generators downstream of branch b b Loss of downstream load power, M, due to failure of branch b of the distribution network CP To get a sufficiently large positive integer for the loss load equation,
is a third auxiliary binary variable.
Preferably, the expected non-supplied electric quantity calculation model includes: an electric quantity calculation equation for calculating an expected non-supplied electric quantity of the distribution network, the electric quantity calculation equation being:
in the formula, E EENS For the expected non-supply of electric power, λ, to the distribution network b 、λ ivt 、λ DCB Are respectively the upper line of the branch b of the power distribution networkFault rates of inverters and dc breakers, tau line 、τ ivt 、τ DCB The fault repair time of the line, the inverter and the direct current breaker on the branch b of the power distribution network is respectively, omega is the branch set of the power distribution network,
DC installation capacity, H, of distributed power plants installed for load node i b And psi is a node i set of the power distribution network for the loss amount of the downstream load power caused by the fault of the branch b of the power distribution network.
The application also provides a system for calculating the expected non-supplied electric quantity of the power distribution network, which comprises a matrix construction module, a load flow model construction module, a power supply load calculation module, an electric quantity model construction module and a supply quantity calculation module;
the matrix construction module is used for acquiring a network topology model of the power distribution network containing the distributed power supply and constructing a node incidence matrix according to the topological connection relation of the network topology model;
the power flow model building module is used for obtaining the load requirements of each bus node and the installation capacity of each distributed power generation device in the network topology model and building a virtual power flow balance model according to all the load requirements and the installation capacity;
the power supply load calculation module is used for constructing an actual power supply lacking load model of the downstream of each branch when a line element fault occurs in the power distribution network according to a fault condition and the virtual tide balance model, and acquiring the actual power supply lacking load of the downstream of each branch when the line element fault occurs in the power distribution network based on the actual power supply lacking load model;
the electric quantity model building module is used for obtaining fault parameters of electric elements in the power distribution network and building an expected non-supplied electric quantity calculation model according to the actual power shortage load and the fault parameters;
and the supply quantity calculation module is used for constructing a linear programming optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supply electric quantity calculation model, and performing optimization solution on the linear programming optimization model to obtain the expected non-supply electric quantity of the power distribution network.
Preferably, the supply quantity calculation module is further configured to perform optimization solution on the linear programming optimization model by using a Gurobi self-contained branch-and-bound method and a target condition to obtain an expected non-supply electric quantity of the power distribution network; wherein the target condition is that the minimum value of the actual power shortage load and the distance between the relaxation solution and the convergence solution in Gurobi are selected to be 0.1%.
Preferably, the virtual power flow balancing model comprises: the load demand virtual power flow balance equation comprises the following steps:
the capacity virtual power flow balance equation is as follows:
in the formula, omega is a branch set of the power distribution network, D b For the total maximum load demand downstream of branch b,
for the virtual load demand flow in the positive direction for branch b,
for the virtual load demand flow in the negative direction of branch b, M D The virtual power flow balance equation takes a large enough positive integer for the load demand,
is a first auxiliary binary variable, A i,b The numerical value of an element corresponding to the ith row and the mth column in the node incidence matrix is psi, the collection of nodes i of the power distribution network is D i Is the load demand of the load node i; d s Is the load demand of the power node s; g s For the total load demand downstream of the supply node s, CDG b The power supply capacity of the conversion efficiency is taken into account for all distributed power generation units downstream of branch b,
capacity flow is installed for the virtual load in the positive direction for branch b,
capacity flow is installed for the virtual load in the negative direction for branch b,
is a second auxiliary binary variable, M DG A positive integer which is large enough is taken for the capacity virtual power flow balance equation;
the ac installation capacity of the distributed power generation apparatus installed for the load node i,
the dc installation capacity of the distributed power generation apparatus installed for the load node i,
the ac installation capacity of the distributed generation apparatus installed for the power source node i,
DC installation capacity, η, of distributed power plants installed for a power node i ivt For the efficiency of the conversion of the inverter in the distribution network,
the total installed capacity of the converter efficiency distributed power plant is accounted for downstream of the power source node s.
Preferably, the actual power supply shortage load model is represented by a loss load equation, and the loss load equation is as follows:
in the formula, omega is the branch set of the distribution network, D b For the total maximum load demand downstream of branch b, CDG b Taking into account the supply capacity, H, of the conversion efficiency for all distributed generators downstream of branch b b Loss of downstream load power, M, due to failure of branch b of the distribution network CP A sufficiently large positive integer to be taken by the lost load equation,
is a third auxiliary binary variable;
the expected non-supplied electric quantity calculation model includes: an electric quantity calculation equation for calculating an expected non-supplied electric quantity of the distribution network, the electric quantity calculation equation being:
in the formula, E EENS For the expected non-supply of electricity, lambda, of the distribution network b 、λ ivt 、λ DCB Fault rates, τ, of lines, inverters and dc breakers in the branch b of the distribution network line 、τ ivt 、τ DCB The fault repair time of the line, the inverter and the direct current breaker on the branch b of the power distribution network is respectively, omega is the branch set of the power distribution network,
DC installation capacity, H, of distributed power plants installed for load node i b And psi is a node i set of the power distribution network for the loss amount of the downstream load power caused by the fault of the branch b of the power distribution network.
The application also provides a terminal device, which comprises a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the method for calculating the expected and un-supplied electric quantity of the power distribution network according to the instructions in the program codes.
According to the technical scheme, the embodiment of the application has the following advantages: the method comprises the steps of obtaining a network topology model of the power distribution network containing the distributed power supply, and forming a node incidence matrix according to the topological connection relation of the network topology model; acquiring the load demand of each bus node and the installation capacity of each distributed power generation device in the network topology model, and constructing a virtual tide balance model according to all the load demands and the installation capacities; according to the fault condition and the virtual tide balance model, constructing an actual power supply shortage load model of each branch downstream when a line element fault occurs in the power distribution network, and acquiring the actual power supply shortage load of each branch downstream when the line element fault occurs in the power distribution network based on the actual power supply shortage load model; acquiring fault parameters of electrical elements in the power distribution network, and constructing an expected non-supplied electric quantity calculation model according to actual power shortage load and the fault parameters; and constructing a linear planning optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supplied electric quantity calculation model, and carrying out optimization solution on the linear planning optimization model to obtain the expected non-supplied electric quantity of the power distribution network. The linear programming optimization model established by the power distribution network expected non-supplied electric quantity calculation method considers the condition that the upstream of the distributed power supply is in fault isolated island power supply, is composed of mathematical expressions, facilitates calculation of expected non-supplied electric quantity of the power distribution network, enables the power distribution network expected non-supplied electric quantity calculation method to be fused with a mathematical programming module, enables the speed of calculating the expected non-supplied electric quantity of the power distribution network to be high, is accurate in calculation and high in efficiency, and solves the technical problems that an existing power distribution network reliability index solving mode is difficult to combine with the mathematical programming model, and is low in efficiency.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a flowchart illustrating steps of a method for calculating an expected amount of power to be supplied to a distribution network according to an embodiment of the present disclosure;
fig. 2 is a block diagram of a system for calculating an expected amount of power to be supplied to a power distribution network according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more apparent and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the embodiments described below are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The application provides a method, a system and equipment for calculating expected non-supplied electric quantity of a power distribution network, which are used for solving the technical problems that the existing solving mode for reliability indexes of the power distribution network is difficult to combine with a mathematical programming model and the efficiency is low.
The first embodiment is as follows:
fig. 1 is a flowchart illustrating steps of a method for calculating an expected amount of power not supplied to a power distribution network according to an embodiment of the present disclosure.
As shown in fig. 1, the present application provides a method for calculating an expected amount of power not supplied to a distribution network, comprising the following steps:
s10, a network topology model of the power distribution network containing the distributed power supply is obtained, and a node incidence matrix is formed according to the topological connection relation of the network topology model.
In step S10, the node association matrix a is mainly constructed according to the topological connection relationship in the network topology model of the power distribution network. In this embodiment, the element corresponding to the ith row and the b th column in the node correlation matrix a is denoted as a i,b ，A i,b For the connection of node i and branch b, A i,b The numerical value rule is as follows: and taking 1 when the branch is far away from the node, taking-1 when the branch faces the node, and taking 0 when the branch is not connected with the node.
S20, acquiring the load requirements of each bus node and the installation capacity of each distributed power generation device in the network topology model, and constructing a virtual tide balance model according to all the load requirements and the installation capacity.
In step S20, the load demand of each bus node in the network topology model of the power distribution network and the installation capacity of the distributed power generation apparatus installed on each node are obtained; and then respectively constructing a virtual power flow balance equation for the acquired load demand and each installation capacity of each node.
Further, the virtual tidal current balance model comprises a load demand virtual tidal current balance equation and a capacity virtual tidal current balance equation, and the load demand virtual tidal current balance equation is as follows:
the capacity virtual power flow balance equation is as follows:
in the formula, omega is the branch set of the distribution network, D b For the total maximum load demand downstream of branch b,
for the virtual load demand flow in the positive direction for branch b,
for the virtual load demand flow in the negative direction of branch b, M D The virtual power flow balance equation takes a sufficiently large positive integer for the load demand,
is a first auxiliary binary variable, A i,b The numerical value of an element corresponding to the ith row and the b th column in the node incidence matrix is psi, a node i set of the power distribution network is represented, and D i Is the load demand of the load node i; d s Is the load demand of the power node s; g s For the total load demand downstream of the supply node s, CDG b The power supply capacity of the conversion efficiency is taken into account for all distributed power generation units downstream of branch b,
capacity flow is installed for the virtual load in the forward direction for branch b,
capacity flow is installed for the virtual load of branch b in the negative direction,
is a second auxiliary binary variable, M DG A positive integer which is large enough is taken for the capacity virtual power flow balance equation;
the ac installation capacity of the distributed generation apparatus installed for the load node i,
the dc installation capacity of the distributed power generation apparatus installed for the load node i,
the ac installation capacity of the distributed power generation apparatus installed for the power source node i,
DC installation capacity, η, of distributed power plants installed for a power node i ivt For the efficiency of the conversion of the inverter in the distribution network,
the total installed capacity of the distributed generation unit is taken into account downstream of the power source node s and with the conversion efficiency.
It should be noted that the virtual power flow balance equation is constructed based on the load demand of the distribution network without considering the power supply of the distributed generation devices DG, where the load demand isFirst auxiliary binary variable in virtual power flow balance equation
Is used for restraining
And
only one takes a value other than 0. The capacity virtual power flow balance equation is constructed based on the installation capacity of the power distribution network under the condition of only considering the power supply of the distributed generation devices DG. Second auxiliary binary variable of capacity virtual power flow balance equation
Is used for restraining
And
only one takes a value other than 0.
And S30, constructing an actual power supply shortage load model of the downstream of each branch when a line element fault occurs in the power distribution network according to the fault condition and the virtual tide balance model, and obtaining the actual power supply shortage load of the downstream of each branch when the line element fault occurs in the power distribution network based on the actual power supply shortage load model.
In step S30, an actual power shortage load model of each branch downstream when a line component fault occurs in the power distribution network is mainly constructed, and an actual power shortage load of each branch downstream when a line component fault occurs in the power distribution network is calculated through the actual power shortage load model. In this embodiment, after the fault condition is an upstream line fault of the distribution network, the distributed generation apparatus DG supplies power to the distribution network in an island manner. The actual power shortage load obtained through calculation is the actual power shortage of the power distribution network under the condition that the distributed power generation device DG supplies power to the power outage region after the fault is considered.
Further, the actual power shortage load model is expressed by a loss load equation, which is:
in the formula, omega is a branch set of the power distribution network, D b For the total maximum load demand downstream of branch b, CDG b Supply capacity, H, taking into account the conversion efficiency for all distributed generators downstream of branch b b Loss of downstream load power, M, due to failure of branch b of the distribution network CP To get a sufficiently large positive integer for the loss load equation,
is a third auxiliary binary variable.
It should be noted that the third auxiliary binary variable is used in the loss load equation
Is used for ensuring H b Non-negative when D b Greater than CDG b At the time, only
All inequality constraints in the virtual power flow balance equation, the capacity virtual power flow balance equation and the loss load equation can be met by taking 1, and then H b Is constrained to be D b -CDG b That is, the power loss amount of the downstream load caused by the fault of the line b is equal to the difference between the total amount of the downstream maximum load demand and the power supply amount of the distributed generation device DG; when D is b Smaller than CDG b At the time, only
If 0 is taken, all inequality constraints of the virtual power flow balance equation and the capacity virtual power flow balance equation which can meet the load demand can be obtained, and at the moment, H is b Is constrained to 0 and H does not occur b Taking a negative number is not practical.
S40, obtaining fault parameters of electric elements in the power distribution network, and constructing an expected non-supplied electric quantity calculation model according to actual power shortage load and the fault parameters.
In step S40, the actual power shortage load H obtained in step S3 is obtained based on the acquired failure parameter b And constructing an expected non-supplied electric quantity calculation model by combining a state enumeration method, and providing data for the subsequent calculation of the expected non-supplied electric quantity of the power distribution network. The fault parameters of the electrical elements in the power distribution network refer to line fault rate, inverter fault rate, direct-current breaker fault rate, line fault repair time, inverter fault repair time and direct-current breaker fault repair time.
Further, the expected non-supplied electric quantity calculation model includes: an electric quantity calculation equation for calculating the expected non-supplied electric quantity of the distribution network, the electric quantity calculation equation being:
in the formula, E EENS For the expected non-supply of electric power, λ, to the distribution network b 、λ ivt 、λ DCB Fault rates, τ, of lines, inverters and dc breakers in the branch b of the distribution network line 、τ ivt 、τ DCB The fault repair time of the line, the inverter and the direct current breaker on the branch b of the power distribution network is respectively, omega is the branch set of the power distribution network,
DC installation capacity, H, of distributed power plants installed for load node i b The amount of power loss of the downstream load due to the failure of distribution network branch b,psi is the set of nodes i of the distribution network.
And S50, constructing a linear planning optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supplied electric quantity calculation model, and performing optimization solution on the linear planning optimization model to obtain the expected non-supplied electric quantity of the power distribution network.
It should be noted that, in step S50, a linear programming optimization model is mainly formed according to the load demand virtual power flow balance equation, the capacity virtual power flow balance equation, the loss load equation and the electric quantity calculation equation obtained in steps S20 to S40, and then the linear programming optimization model is optimized and solved to obtain the expected un-supplied electric quantity of the power distribution network through calculation.
Further, the optimization solution is performed on the linear planning optimization model, and obtaining the expected non-supplied electric quantity of the power distribution network comprises: optimizing and solving the linear planning optimization model by using a Gurobi self-contained branch-and-bound method and target conditions to obtain the expected non-supplied electric quantity of the power distribution network; wherein the target condition is that the minimum value of the actual power supply shortage load is selected and the distance between the relaxation solution and the convergence solution in Gurobi is 0.1%.
It should be noted that, the optimization solution of the linear programming optimization model may also be performed under a target condition by using other commercial solvers having the same function as the branch-and-bound method of Gurobi.
The method for calculating the expected non-supplied electric quantity of the power distribution network comprises the steps of obtaining a network topology model of the power distribution network containing the distributed power supply, and forming a node incidence matrix according to the topological connection relation of the network topology model; acquiring the load demand of each bus node and the installation capacity of each distributed power generation device in the network topology model, and constructing a virtual tide balance model according to all the load demands and the installation capacities; according to the fault condition and the virtual tide balance model, constructing an actual power supply shortage load model of each branch downstream when a line element fault occurs in the power distribution network, and acquiring the actual power supply shortage load of each branch downstream when the line element fault occurs in the power distribution network based on the actual power supply shortage load model; acquiring fault parameters of electrical elements in the power distribution network, and constructing an expected non-supplied electric quantity calculation model according to actual power shortage load and the fault parameters; and constructing a linear planning optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supplied electric quantity calculation model, and carrying out optimization solution on the linear planning optimization model to obtain the expected non-supplied electric quantity of the power distribution network. The linear programming optimization model established by the power distribution network expected non-supplied electric quantity calculation method considers the condition that the upstream of the distributed power supply is in fault isolated island power supply, is composed of mathematical expressions, facilitates calculation of expected non-supplied electric quantity of the power distribution network, enables the power distribution network expected non-supplied electric quantity calculation method to be fused with a mathematical programming module, enables the speed of calculating the expected non-supplied electric quantity of the power distribution network to be high, is accurate in calculation and high in efficiency, and solves the technical problems that an existing power distribution network reliability index solving mode is difficult to combine with the mathematical programming model, and is low in efficiency.
In the embodiment of the application, the method for calculating the expected non-supplied electric quantity of the power distribution network can also be used for calculating the average power failure frequency index of the power distribution network system and the average power failure time index of the power distribution network system, constructing a virtual power flow balance equation aiming at the number of users and finally solving the power distribution network system by using a state enumeration thought. The method for calculating the expected and non-supplied electric quantity of the power distribution network can be used for quickly calculating the expected and non-supplied electric quantity of the radial power distribution network due to faults, so that the reliability degree of the power distribution network is evaluated. The method for calculating the expected non-supplied electric quantity of the power distribution network can be further optimized conveniently along with the continuous improvement of the refinement degree of the constructed model, for example, when different load importance degrees are considered, only the weighted calculation of each load is needed.
Example two:
fig. 2 is a block diagram of a system for calculating an expected amount of power not supplied to a power distribution grid according to an embodiment of the present disclosure.
As shown in fig. 2, the present application further provides a system for calculating an expected non-supplied electric quantity of a power distribution network, which includes a matrix building module 10, a power flow model building module 20, a power supply load calculating module 30, an electric quantity model building module 40, and a supply quantity calculating module 50;
the matrix construction module 10 is used for acquiring a network topology model of a power distribution network containing a distributed power supply, and constructing a node incidence matrix according to a topological connection relation of the network topology model;
the power flow model building module 20 is used for obtaining the load requirements of each bus node and the installation capacity of each distributed power generation device in the network topology model, and building a virtual power flow balance model according to all the load requirements and the installation capacity;
the power supply load calculation module 30 is configured to construct an actual power supply shortage load model of each branch downstream when a line element fault occurs in the power distribution network according to the fault condition and the virtual tidal current balance model, and obtain an actual power supply shortage load of each branch downstream when a line element fault occurs in the power distribution network based on the actual power supply shortage load model;
the electric quantity model building module 40 is used for obtaining fault parameters of electric elements in the power distribution network and building an expected non-supplied electric quantity calculation model according to actual power supply shortage loads and the fault parameters;
and the supply quantity calculation module 50 is used for constructing a linear planning optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supply electric quantity calculation model, and performing optimization solution on the linear planning optimization model to obtain the expected non-supply electric quantity of the power distribution network.
In the embodiment of the present application, the supply quantity calculation module 50 is further configured to perform optimization solution on the linear planning optimization model by using a Gurobi self-contained branch-and-bound method and a target condition, so as to obtain an expected non-supply electric quantity of the power distribution network; wherein the target condition is that the minimum value of the actual power supply shortage load is selected and the distance between the relaxation solution and the convergence solution in Gurobi is 0.1%.
In the embodiment of the present application, the virtual power flow balancing model includes: the load demand virtual power flow balance equation and the capacity virtual power flow balance equation are as follows:
the capacity virtual power flow balance equation is as follows:
in the formula, omega is the branch set of the distribution network, D b For the total maximum load demand downstream of branch b,
for the virtual load demand flow in the positive direction for branch b,
for the virtual load demand flow in the negative direction of branch b, M D The virtual power flow balance equation takes a large enough positive integer for the load demand,
is a first auxiliary binary variable, A i,b The numerical value of an element corresponding to the ith row and the b th column in the node incidence matrix is psi, a node i set of the power distribution network is represented, and D i Is the load demand of the load node i; d s Is the load demand of the power node s; g s For the total load demand downstream of the supply node s, CDG b Accounting for and swapping out all distributed power plants downstream of branch bThe power supply capacity of the flow efficiency is,
capacity flow is installed for the virtual load in the positive direction for branch b,
capacity flow is installed for the virtual load of branch b in the negative direction,
is a second auxiliary binary variable, M DG A positive integer which is large enough is taken for the capacity virtual power flow balance equation;
the ac installation capacity of the distributed power generation apparatus installed for the load node i,
the dc installation capacity of the distributed power generation apparatus installed for the load node i,
the ac installation capacity of the distributed power generation apparatus installed for the power source node i,
DC installation capacity, η, of distributed power plants installed for a power node i ivt For the efficiency of the conversion of the inverter in the distribution network,
the total installed capacity of the distributed generation unit is taken into account downstream of the power source node s and with the conversion efficiency.
In the embodiment of the present application, the actual power shortage load model is expressed by using a loss load equation, where the loss load equation is:
in the formula, omega is a branch set of the power distribution network, D b For the total maximum load demand downstream of branch b, CDG b Taking into account the supply capacity, H, of the conversion efficiency for all distributed generators downstream of branch b b Loss of downstream load power, M, due to failure of branch b of the distribution network CP To get a sufficiently large positive integer for the loss load equation,
is a third auxiliary binary variable;
the expected non-supplied electric quantity calculation model includes: an electric quantity calculation equation for calculating the expected non-supplied electric quantity of the distribution network, the electric quantity calculation equation being:
in the formula, E EENS For the expected non-supply of electricity, lambda, of the distribution network b 、λ ivt 、λ DCB Fault rates, τ, of lines, inverters and dc breakers in the branch b of the distribution network line 、τ ivt 、τ DCB The fault repair time of the line, the inverter and the direct current breaker on the branch b of the power distribution network is respectively, omega is the branch set of the power distribution network,
DC installation capacity, H, of distributed power plants installed for load node i b And psi is a node i set of the power distribution network for the loss amount of the downstream load power caused by the fault of the branch b of the power distribution network.
It should be noted that the contents of the modules in the second embodiment correspond to the steps in the first embodiment, the contents of the steps in the first embodiment have been described in detail in the first embodiment, and the contents of the modules in the system are not repeated in the second embodiment.
Example three:
the application also provides a terminal device, which comprises a processor and a memory;
a memory for storing the program code and transmitting the program code to the processor;
and the processor is used for executing the method for calculating the expected and un-supplied electric quantity of the power distribution network according to the instructions in the program codes.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A method for calculating the expected non-supplied electric quantity of a power distribution network is characterized by comprising the following steps:
acquiring a network topology model of a power distribution network containing a distributed power supply, and forming a node incidence matrix according to a topological connection relation of the network topology model;
acquiring the load demand of each bus node and the installation capacity of each distributed power generation device in the network topology model, and constructing a virtual tide balance model according to all the load demands and the installation capacity;
according to the fault condition and the virtual tide balance model, constructing an actual power supply shortage load model of each branch downstream when a line element fault occurs in the power distribution network, and acquiring the actual power supply shortage load of each branch downstream when the line element fault occurs in the power distribution network based on the actual power supply shortage load model;
acquiring fault parameters of electrical elements in the power distribution network, and constructing an expected non-supplied electric quantity calculation model according to the actual power shortage load and the fault parameters;
and constructing a linear programming optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supplied electric quantity calculation model, and performing optimization solution on the linear programming optimization model to obtain the expected non-supplied electric quantity of the power distribution network.
2. The method for calculating the expected non-supplied electric quantity of the power distribution network according to claim 1, wherein the step of performing optimization solution on the linear programming optimization model to obtain the expected non-supplied electric quantity of the power distribution network comprises the following steps: optimizing and solving the linear programming optimization model by adopting a Gurobi branch-and-bound method and target conditions to obtain the expected non-supplied electric quantity of the power distribution network; wherein the target condition is that the minimum value of the actual power shortage load and the distance between the relaxation solution and the convergence solution in Gurobi are selected to be 0.1%.
3. The method for calculating the expected amount of the electric power not supplied to the power distribution network according to claim 1, wherein the virtual load flow balancing model comprises: the load demand virtual power flow balancing equation comprises the following steps:
the capacity virtual power flow balance equation is as follows:
in the formula, omega is a branch set of the power distribution network, D b For the total maximum load demand downstream of branch b,
for the virtual load demand flow in the positive direction for branch b,
for the virtual load demand flow in the negative direction of branch b, M D The virtual power flow balance equation takes a sufficiently large positive integer for the load demand,
is a first auxiliary binary variable, A i,b The numerical value of an element corresponding to the ith row and the mth column in the node incidence matrix is psi, the collection of nodes i of the power distribution network is D i Is the load demand of the load node i; d s Is the load demand of the power node s; g s For the total load demand downstream of the supply node s, CDG b The power supply capacity of the conversion efficiency is taken into account for all distributed power generation units downstream of branch b,
capacity flow is installed for the virtual load in the positive direction for branch b,
capacity flow is installed for the virtual load in the negative direction for branch b,
is a second auxiliary binary variable, M DG A positive integer which is large enough is taken for the capacity virtual power flow balance equation;
the ac installation capacity of the distributed power generation apparatus installed for the load node i,
the dc installation capacity of the distributed power generation apparatus installed for the load node i,
the ac installation capacity of the distributed generation apparatus installed for the power source node i,
DC installation capacity, η, of distributed power plants installed for a power node i ivt For the conversion efficiency of an inverter in a power distribution network,
the total installed capacity of the converter efficiency distributed power plant is accounted for downstream of the power source node s.
4. The method for calculating the expected non-supplied electric quantity of the power distribution network according to claim 1, wherein the actual power shortage load model is expressed by a loss load quantity equation, and the loss load quantity equation is as follows:
in the formula, omega is a branch set of the power distribution network, D b For the total maximum load demand downstream of branch b, CDG b Taking into account the supply capacity, H, of the conversion efficiency for all distributed generators downstream of branch b b Loss of downstream load power, M, due to failure of branch b of the distribution network CP To get a sufficiently large positive integer for the loss load equation,
is a third auxiliary binary variable.
5. The method of claim 1, wherein the model comprises: an electric quantity calculation equation for calculating an expected non-supplied electric quantity of the distribution network, the electric quantity calculation equation being:
in the formula, E EENS For the expected non-supply of electricity, lambda, of the distribution network b 、λ ivt 、λ DCB Fault rates, τ, of lines, inverters and dc breakers in the branch b of the distribution network line 、τ ivt 、τ DCB The fault repair time of the line, the inverter and the direct current breaker on the branch b of the power distribution network is respectively, omega is the branch set of the power distribution network,
DC installation capacity, H, of distributed power plants installed for load node i b And psi is a node i set of the power distribution network for the loss amount of the downstream load power caused by the fault of the branch b of the power distribution network.
6. A power distribution network expected non-supplied electric quantity calculation system is characterized by comprising a matrix construction module, a power flow model construction module, a power supply load calculation module, an electric quantity model construction module and a supply quantity calculation module;
the matrix construction module is used for acquiring a network topology model of the power distribution network containing the distributed power supply and constructing a node incidence matrix according to the topological connection relation of the network topology model;
the power flow model building module is used for obtaining the load requirements of each bus node and the installation capacity of each distributed power generation device in the network topology model and building a virtual power flow balance model according to all the load requirements and the installation capacity;
the power supply load calculation module is used for constructing an actual power supply lacking load model of the downstream of each branch when a line element fault occurs in the power distribution network according to a fault condition and the virtual tide balance model, and acquiring the actual power supply lacking load of the downstream of each branch when the line element fault occurs in the power distribution network based on the actual power supply lacking load model;
the electric quantity model building module is used for obtaining fault parameters of electric elements in the power distribution network and building an expected non-supplied electric quantity calculation model according to the actual power shortage load and the fault parameters;
and the supply quantity calculation module is used for constructing a linear programming optimization model according to the virtual current balance model, the actual power shortage load model and the expected non-supply electric quantity calculation model, and performing optimization solution on the linear programming optimization model to obtain the expected non-supply electric quantity of the power distribution network.
7. The system for calculating the expected non-supplied electric quantity of the power distribution network according to claim 6, wherein the supply quantity calculating module is further configured to perform optimization solution on the linear programming optimization model by using a Gurobi's own branch-and-bound method and target conditions to obtain the expected non-supplied electric quantity of the power distribution network; wherein the target condition is that the minimum value of the actual power shortage load and the distance between the relaxation solution and the convergence solution in Gurobi are selected to be 0.1%.
8. The system for calculating the expected amount of un-supplied power of the power distribution network according to claim 6, wherein the virtual power flow balancing model comprises: the load demand virtual power flow balance equation comprises the following steps:
the capacity virtual power flow balance equation is as follows:
in the formula, omega is the branch set of the distribution network, D b For the total maximum load demand downstream of branch b,
for the virtual load demand flow in the positive direction for branch b,
for the virtual load demand flow in the negative direction of branch b, M D The virtual power flow balance equation takes a large enough positive integer for the load demand,
is a first auxiliary binary variable, A i,b The numerical value of an element corresponding to the ith row and the b th column in the node incidence matrix is psi, a node i set of the power distribution network is represented, and D i Is the load demand of the load node i; d s Is the load demand of power node s; g s For the total load demand downstream of the supply node s, CDG b The power supply capacity of the conversion efficiency is taken into account for all distributed power generation units downstream of branch b,
capacity flow is installed for the virtual load in the positive direction for branch b,
capacity flow is installed for the virtual load in the negative direction for branch b,
is a second auxiliary binary variable, M DG A positive integer which is large enough is taken for the capacity virtual power flow balance equation;
the ac installation capacity of the distributed power generation apparatus installed for the load node i,
the dc installation capacity of the distributed power generation apparatus installed for the load node i,
the ac installation capacity of the distributed power generation apparatus installed for the power source node i,
DC installation capacity, η, of distributed power plants installed for a power node i ivt For the conversion efficiency of an inverter in a power distribution network,
the total installed capacity of the distributed generation unit is taken into account downstream of the power source node s and with the conversion efficiency.
9. The system for calculating the expected amount of un-supplied power to the power distribution network according to claim 6, wherein the actual power shortage load model is expressed by a loss load equation, and the loss load equation is as follows:
in the formula, omega is a branch set of the power distribution network, D b For the total maximum load demand downstream of branch b, CDG b Supply capacity, H, taking into account the conversion efficiency for all distributed generators downstream of branch b b Loss of downstream load power, M, due to failure of branch b of the distribution network CP A sufficiently large positive integer to be taken by the lost load equation,
is a third auxiliary binary variable;
the expected non-supplied electric quantity calculation model includes: an electric quantity calculation equation for calculating an expected non-supplied electric quantity of the distribution network, the electric quantity calculation equation being:
in the formula, E EENS For the expected non-supply of electricity, lambda, of the distribution network b 、λ ivt 、λ DCB Fault rates, τ, of lines, inverters and dc breakers in the branch b of the distribution network line 、τ ivt 、τ DCB The fault repair time of the line, the inverter and the direct current breaker on the branch b of the power distribution network is respectively, omega is the branch set of the power distribution network,
DC installation capacity, H, of distributed power plants installed for load node i b And psi is a node i set of the power distribution network, wherein the downstream load power loss caused by the fault of the branch b of the power distribution network is a downstream load power loss amount.
10. A terminal device comprising a processor and a memory;
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to execute the method for calculating the expected amount of un-supplied power of the power distribution network according to any one of claims 1 to 6 according to the instructions in the program code.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211119436.3A CN115411735A (en) | 2022-09-14 | 2022-09-14 | Method, system and equipment for calculating expected non-supplied electric quantity of power distribution network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211119436.3A CN115411735A (en) | 2022-09-14 | 2022-09-14 | Method, system and equipment for calculating expected non-supplied electric quantity of power distribution network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115411735A true CN115411735A (en) | 2022-11-29 |
Family
ID=84166651
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211119436.3A Pending CN115411735A (en) | 2022-09-14 | 2022-09-14 | Method, system and equipment for calculating expected non-supplied electric quantity of power distribution network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115411735A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116526480A (en) * | 2023-07-05 | 2023-08-01 | 山西中控绿源科技有限公司 | Distributed power supply system and method based on intelligent energy management platform |
| CN118137510A (en) * | 2024-05-06 | 2024-06-04 | 国网天津市电力公司城西供电分公司 | Power supply capacity mining method and equipment for multi-type load recombination-oriented power distribution network |
-
2022
- 2022-09-14 CN CN202211119436.3A patent/CN115411735A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116526480A (en) * | 2023-07-05 | 2023-08-01 | 山西中控绿源科技有限公司 | Distributed power supply system and method based on intelligent energy management platform |
| CN116526480B (en) * | 2023-07-05 | 2023-10-13 | 北京中芯标准科技有限公司 | Distributed power supply system and method based on intelligent energy management platform |
| CN118137510A (en) * | 2024-05-06 | 2024-06-04 | 国网天津市电力公司城西供电分公司 | Power supply capacity mining method and equipment for multi-type load recombination-oriented power distribution network |
| CN118137510B (en) * | 2024-05-06 | 2024-07-09 | 国网天津市电力公司城西供电分公司 | Power supply capacity mining method and equipment for multi-type load recombination-oriented power distribution network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115411735A (en) | Method, system and equipment for calculating expected non-supplied electric quantity of power distribution network | |
| CN102214922B (en) | Evaluation system of power network planning scheme | |
| Gu et al. | Reliability-based distribution network pricing | |
| CN106709651B (en) | Electric power system security evaluation system based on risk theory | |
| CN103514570A (en) | Expansion planning comprehensive optimization method of power distribution network with distributed power supply | |
| CN109728579B (en) | Evaluation method, evaluation device and evaluation equipment for operation efficiency of power distribution network | |
| CN112183855A (en) | Regional power spot market clearing method and device and electronic equipment | |
| Nayak et al. | Optimal allocation of energy storage system and its benefit analysis for unbalanced distribution network with wind generation | |
| CN110676839A (en) | Method and system for evaluating reliability of alternating current-direct current hybrid power distribution network | |
| CN110929220A (en) | Power distribution network index weight calculation method and device | |
| Yin et al. | Operational reliability assessment of distribution network with energy storage systems | |
| Shayesteh et al. | System reduction techniques for storage allocation in large power systems | |
| CN107179688B (en) | Power system reliability analysis method considering Monte Carlo state sampling truncation | |
| Ebrahimi et al. | A conditional value at risk based stochastic allocation of SOP in distribution networks | |
| Shaaban et al. | A multi-objective approach for optimal DG allocation | |
| CN106960262B (en) | Active reserve capacity evaluation method and device for expected faults of extra-high voltage direct current line | |
| CN111311433A (en) | Method, device and equipment for standby discharge in day-ahead electric power spot market operation | |
| Pan et al. | A flexible black‐start network partitioning strategy considering subsystem recovery time balance | |
| CN115907163A (en) | Power system operation state prediction method and device and computer equipment | |
| Mahdavi et al. | Evaluation of GA performance in TNEP considering voltage level, network losses and number of bundle lines | |
| CN112016838B (en) | Contribution rate calculation method, system and terminal equipment of power distribution network energy efficiency index system | |
| Kim et al. | Flexible risk control strategy based on multi-stage corrective action with energy storage system | |
| Zhu | A new methodology of analytical formula deduction and sensitivity analysis of EENS in bulk power system reliability assessment | |
| CN111401729A (en) | Newly-increased black start unit distribution point determining method and system | |
| Khodayari et al. | Customer reliability based energy & SR scheduling at hierarchical level II |
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 |