CN113904330B - Power grid emergency power supply configuration method and device, storage medium and electronic equipment - Google Patents
Power grid emergency power supply configuration method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The application provides a power grid emergency power supply configuration method, a power grid emergency power supply configuration device, a storage medium and electronic equipment. The power grid emergency power supply configuration method comprises the following steps: according to the first objective function and the weight parameters for recovering various load value quantities; determining constraint conditions of uninterrupted power supply of each class of loads and class II loads with preset proportion under the expected fault time; determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum of configuration costs for the emergency power supply. According to the application, on the premise that each type of load and a certain proportion of the type of loads are not powered off in the expected failure time, the configuration cost recovery of the self-provided emergency power supply and the cost input by integrating the load value quantity to time and calling various energy sources are comprehensively considered, so that the optimal configuration of the emergency power supply at the user side is realized, the configuration cost can be reduced, and the toughness level requirement is met.
Description
Technical Field
The application relates to the technical field of power distribution of power grids, in particular to a power grid emergency power supply configuration method, a device, a storage medium and electronic equipment.
Background
With the continuous development of cities, the scale and complexity of power distribution network construction are increasing, the technology is innovative, but the power distribution network is still fragile when facing extreme natural disaster accidents, so that in the extreme accident background, the power distribution network is required to have certain toughness, the toughness of the power distribution network is the preparation and adaptability of the power distribution network to changing conditions and the capability of bearing disturbance and quickly recovering, and the toughness of an emergency power supply configuration scheme in the power distribution network on the market is low.
Disclosure of Invention
In view of the above, the application aims to provide a power grid emergency power supply configuration method, a storage medium and an electronic device, which comprehensively consider the configuration cost recovery of a self-provided emergency power supply and the cost input by integrating the load value quantity and time and calling various energy sources to realize the optimal configuration of a user side emergency power supply on the premise of ensuring that each type of load and a certain proportion of second type of load are not powered off in the expected failure time, can reduce the configuration cost, and meets the requirement of toughness level.
The embodiment of the application provides a power grid emergency power supply configuration method, which comprises the following steps:
According to the first objective function and the weight parameters for recovering various load value quantities; determining constraint conditions of uninterrupted power supply of each class of loads and class II loads with preset proportion under the expected fault time; the first objective function is a function taking the minimum difference between the integral of each load value quantity and time and the weighting of each energy scheduling cost as an objective;
determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum configuration cost of the emergency power supply.
Further, before determining constraint conditions that each class of load and the class of loads with preset proportion are not powered off under the expected fault time according to the first objective function and the weight parameters for recovering the value quantities of the various loads, the power grid emergency power supply configuration method further comprises the following steps:
determining an initial output curve of power generation of the distributed power supply according to fluctuation data of power generation of the distributed power supply under faults;
based on the energy storage facilities and the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, performing pre-scheduling processing on the initial output curve, and determining a target output curve of the maximum power supply area of each energy source;
Dividing the target output curve according to preset time intervals, determining the minimum electric quantity output value in the preset time intervals, and adjusting the value of each type of load in the preset time intervals according to the minimum electric quantity output value in each preset time interval to obtain the value recovery data of each type of load;
and determining a first objective function according to the minimum value of the difference between the various load value quantity recovery data and the energy scheduling cost weighting.
Further, the pre-scheduling processing is performed on the initial output curve based on the energy storage facility and the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, and the determining of the target output curve of the maximum power supply area of all the energy sources includes:
adjusting the fluctuation of the initial output curve based on the dispatchable electric quantity output of the energy storage facility under the fault, and determining an intermediate output curve;
and adjusting the fluctuation of the intermediate output curve based on the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, and determining the target output curve of the maximum power supply area of all the energy sources.
Further, the formula of the first objective function is:
max f 1 -α[f 2 ]；
F1 is the integral of the recovered load value quantity with respect to time; f2 is the scheduling cost of each energy source; alpha is an economic index weighting coefficient.
Further, the determining the configuration scheme of the emergency power supply according to the constraint condition and the second objective function includes:
acquiring a minimum function value of the second objective function and a maximum function value of the first objective function;
according to the minimum function value, calculating and obtaining a first configuration result of the self-provided emergency power supply to each special-grade load;
calculating to obtain a second configuration result of each energy source for each class-one load and a preset proportion class-two load according to the maximum function value;
and determining a configuration scheme of the emergency power supply according to the first configuration result and the second configuration result.
Further, the formula of the second objective function is:
minh(z)；
h is the amount consumed by configuring the self-contained emergency power supply; z is a decision variable for each superfine load needing to be configured with an emergency power supply.
Further, the configuration cost of the emergency power supply is calculated by:
and calculating the configuration cost of the emergency power supply according to the product of the probability of configuring the emergency power supplies of different types by each load and the configuration cost of the emergency power supply of the type.
The embodiment of the application also provides an emergency power supply configuration device with strong local power grid toughness, which comprises:
the first determining module is used for recovering weight parameters of various load value quantities according to a first objective function; determining a first constraint condition that each class of loads and a preset proportion of class II loads are not powered off under the expected fault time; the first objective function is a function taking the minimum difference between the integral of each load value quantity and time and the weighting of each energy scheduling cost as an objective;
the configuration module is used for determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum configuration cost of the emergency power supply.
The embodiment of the application also provides electronic equipment, which comprises: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, the processor and the memory are communicated through the bus when the electronic device is running, and the machine-readable instructions are executed by the processor to perform the steps of the power grid emergency power supply configuration method.
The embodiment of the application also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to execute the steps of the power grid emergency power supply configuration method.
Compared with the prior art, the power grid emergency power supply configuration method provided by the embodiment of the application comprehensively considers the configuration cost recovery of the self-provided emergency power supply and the cost input by integrating the load value quantity and calling various energy sources on the premise of ensuring that each type of load and a certain proportion of the second type of load are not powered off in the expected failure time, so that the optimal configuration of the user side emergency power supply is realized, the configuration cost can be reduced, and the toughness level requirement is met.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 shows a flowchart of a power grid emergency power supply configuration method according to an embodiment of the present application;
FIG. 2 is a flow chart illustrating another method for configuring an emergency power supply for a power grid according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an emergency power supply configuration device for a power grid according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of another power grid emergency power supply configuration device according to an embodiment of the present application;
FIG. 5 is a block flow diagram of a final solution of a first objective function in a power grid emergency power supply configuration method according to an embodiment of the present application;
fig. 6 is a flowchart illustrating a calculation manner of a K value in a power grid emergency power supply configuration method according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
In the figure, 300-emergency power supply configuration device; 310-a first determination module; 320-configuring a module; 330-a second determination module; 340-a third determination module; 350-a preprocessing module; 360-a fourth determination module; 700-an electronic device; 710-a processor; 720-memory; 730-bus.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of 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 described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without making any inventive effort falls within the scope of protection of the present application.
Firstly, researches show that with the continuous development of cities, the scale and complexity of power distribution network construction are increased, the technology is innovated continuously, but the power distribution network is still fragile when facing to extreme natural disaster accidents, so that in the extreme accident background, the power distribution network is required to have certain toughness, namely the preparation and adaptation capability of the power distribution network to changing conditions and the capability of bearing disturbance and quickly recovering, and the toughness of an emergency power supply configuration scheme in the power distribution network on the market is low.
Based on the above, the embodiment of the application provides a power grid emergency power supply configuration method, a device, an electronic device, a storage medium and an electronic device, which comprehensively consider the configuration cost recovery of a self-provided emergency power supply and the cost of integrating the load value quantity and time and calling various energy sources to realize the optimal configuration of a user side emergency power supply on the premise of ensuring that each type of load and a certain proportion of second type of loads are not powered off in the expected failure time, can reduce the configuration cost, and meets the requirement of toughness level.
Referring to fig. 1, fig. 1 is a flowchart of a power grid emergency power supply configuration method according to an embodiment of the application. As shown in fig. 1, the power grid emergency power supply configuration method provided by the embodiment of the application includes:
S101, recovering weight parameters of various load value quantities according to a first objective function; determining constraint conditions of uninterrupted power supply of each class of loads and class II loads with preset proportion under the expected fault time; the first objective function is a function which aims at minimizing the difference between the integral of each load value quantity and time and each energy scheduling cost weighting.
In the step, the emergency power supply configuration method of the power grid needs to meet certain constraint conditions, and configures each special-grade load, each class of load and the class-II load of a preset proportion according to the minimum value of a first objective function meeting the constraint conditions, so that the optimal configuration of the emergency power supply at the user side is realized, wherein the first objective function is a function aiming at recovering the minimum difference between the integral of each load value quantity to time and the weighting of each energy scheduling cost.
The formula of a first objective function taking the minimum difference between the integral of each load value quantity and time and each energy scheduling cost weighting as the objective function is as follows:
f1 is the integral of the recovered load value quantity to time; f2 is the scheduling cost of each energy source; α is a weighting coefficient of an economic index, where the first objective function is solved by using a solver, and there are many choices for the specifications of the solver, where the specifications of the solver provided by the present application include, but are not limited to, selecting a gurobi solver for solving, where f1 and f2 are two types of uncertain variable factors, and the uncertain variable factors affecting f1 are fluctuation of distributed power generation under a fault, fluctuation of energy storage facility load, and fluctuation of gas turbine load in a natural gas network, where a formula of constraint conditions of load fluctuation and uncertainty of distributed power fluctuation is as follows:
-1≤μ DG ≤1；
-1≤μ L ≤1；
Wherein P is DG,i 、μ DG Sigma (sigma) i The actual power generation output, the expected power generation output, the deviation fluctuation control quantity of the power generation output and the maximum deviation value of the power generation output of the distributed power supply are respectively; p (P) L,i 、/>μ L And v i The actual load, the predicted load, the load deviation fluctuation control amount and the load maximum deviation value of the i node are respectively.
In the above steps, the uncertain variables affecting f2 are gas turbine constraint, interruptible load capacity constraint, constraint between flexible load temperature and power and energy storage facility power constraint in natural gas network constraint, and f2 relates to parameters but not to decision variables, so that a change interval of recovery cost investment is determined by adopting a mode of combining an interval linear programming method and a robust method, and a first objective function is divided into a first objective function with optimal price and a first objective function with worst price.
Price optimal first sub objective function:
the first sub-objective function of the worst price:
the configuration scheme of the emergency power supply provided by the application takes the recovery of the value quantity of the load as a main target and reduces the energy scheduling cost as a secondary target, so alpha is set to be a smaller value, the cost of various energy recovery is ensured to be reduced as much as possible on the premise of ensuring the maximum recovery of various loads, on the basis, the first sub-objective function with the optimal price and the first sub-objective function with the worst price are respectively solved to obtain a recovery cost input change interval, and the change of the uncertain parameter m only affects the final value of f2, so that f1 and related decision variables thereof obtained by the final solving of the two first sub-objective functions are consistent and only play a role in each energy call, and [ f2] + and [ f2] -, namely the change interval of the final recovery cost input, can be respectively obtained through the two sub-models.
Further, for gas turbine constraints in natural gas network constraints in callable energy sources among factors affecting the uncertainty of f2, the flow equation for an absolutely ideal natural gas pipeline is as follows:
wherein f k，ij For the natural gas flow of i flow direction j in the natural gas pipeline k, the nodes at the two ends of the pipeline k are i nodes and j nodes, and c ij Pi is a constant corresponding to the pipeline k i Is the air pressure at the ith node, s ij To characterize the natural gas flow direction.
Here, the energy consumed by the compressor k and the equivalent flow rate are as follows:
here, f com，k For natural gas flow through compressor k, τ com，k Is the consumption flow rate of the compressor k. H com，k For the energy consumed by the compressor k, B k 、Z k Is a constant related to the efficiency of the compressor k, the heating value of natural gas, etc.; alpha k 、β k 、γ k Is an energy conversion efficiency constant.
In the power system environment provided by the application, the flow balance equation of the natural gas network is as follows:
(A+U)f+w-Tτ＝0；
here, a is a node-pipe association matrix; u is a node-compressor association matrix; t is the energy consumption correlation matrix of the node and the compressor; τ is the compressor consumption flow vector; w is the node injection flow vector.
The following formula is an inequality constraint in the natural gas network:
w min，i ≤w i ≤w max，i ；
π min，i ≤π i ≤π max，i ；
R min，k ≤R k ≤R max，k ；
Here, the three inequalities above are, from top to bottom, node flow injection constraints, node air pressure constraints, and compressor compression ratio constraints, respectively.
From this, the gas unit consumption formula in the natural gas network is:
here, pgas, j, t is the electrical energy converted by the gas turbine at time t; phi GT, j, t is the conversion efficiency of gas turbine j; hg is the heat value of natural gas, 39MJ/m3 is taken; and QGT, j and t are the natural gas flow consumed by the gas turbine j at the moment t.
Moreover, aiming at the fact that the flexible load in the factor affecting the uncertain variable f2 has different degrees of electric energy demand at different temperatures, a virtual battery can be built accordingly, and the weight is recovered according to dynamic change of the residual electric quantity of the virtual battery, wherein the flexible load has flexible characteristics, can interact with power grid, and is a flexible demand side resource.
The flexible load constraint provided by the embodiment takes a Heating Ventilation Air Conditioning (HVAC) in summer as an example, a virtual battery of the flexible load is established, the degree of demand of the flexible load for electric energy at different temperatures is quantized, and here, the relationship between the temperature and the power of the HVAC thermodynamic equivalent formula after discretization is as follows:
Wherein a=1/(RC), R is thermal resistance, and C is heat capacity; b=cop/C, COP being the energy efficiency coefficient;electric power for air conditioner, theta o Is the ambient temperature, θ t The indoor temperature at the moment t; s is S t Is a 0/1 switch. />The self-loss of the virtual battery is the power consumption of the HVAC to maintain the temperature at the previous time.
According to the formula, a virtual battery of the flexible load is established, and the load weight of the flexible load is determined according to the residual capacity of the virtual battery in a fault processing state and is used for expressing dynamic change of the urgent degree of load power consumption. The weight change coefficient is as follows:
wherein E is max The maximum electric quantity of the virtual battery is; e (E) c And (t) is the equivalent electric quantity of the virtual battery at the moment t. According to the requirement, when the electric quantity of the virtual battery is minimized, the weight coefficient should be 1.
And, for the interruptible load in the factor affecting the uncertainty variable f2, the constraint formula of the interruptible load is as follows:
P IL，imin ≤P IL，i ≤PI L，imax ；
T IL，imin ≤T IL，i ≤T IL，imax ；
Γ IL，imin ≤T IL，i ；
N IL，imin ≤N IL，i ≤N IL，imax ；
here, P IL，i Interrupt capacity for the i-th interruptible load; t (T) IL，i The interruption time length of the ith interruptible load; Γ -shaped structure IL，i A time interval of two interruptions for the ith interruptible load; n (N) IL，i To interrupt the load for a frequency of interruptible load.
And, for the constraint condition of the energy storage facility power in the factor affecting the f2 uncertain variable, the following formula is the constraint condition of the energy storage facility power:
0≤P dc (i，t)≤P DC (i)；
0≤P ch (i，t)≤P CH (i)；
E es，i，min ≤E es，i (t)≤E es，i，max ；
P dc (i，t)P ch (i，t)＝0；
Here, P dc And P ch Charging and discharging power of the energy storage facility; e (E) es (0) For storing the facility electric quantity at the initial moment E es (t) is the electric quantity of the energy storage facility i at the moment t; ρ c And ρ d Is charge and discharge efficiency; e (E) es，i，max 、E es，i，min Maximum and minimum charge for the energy storage facility.
Here, among the two constraints related to the first objective function, the G constraint is expressed as an equality constraint, specifically including, but not limited to, a power balance constraint, a flow constraint of the natural gas pipeline, a constraint between the flexible load temperature and the power, and an interruptible load capacity constraint; the H constraint condition is expressed as inequality constraint, and specifically comprises voltage amplitude constraint, power flow power constraint and radial constraint; x is a decision variable, namely a controllable variable of various load recovery amounts and various energy modulation amounts, y is an uncertainty parameter related to various loads and distributed power supplies, z is an initial configuration result of a self-provided emergency power supply, and m is a price change interval parameter of various energy sources.
The first constraint condition comprises an electric power recovery operation constraint condition and each energy source constraint condition, wherein the electric power recovery operation constraint condition comprises a power balance constraint, a voltage amplitude constraint, a tide power constraint and a radial constraint, and each energy source constraint condition comprises a natural gas network constraint, a constraint between a flexible load temperature and power, an interruptible load capacity constraint and an energy storage facility power constraint, and the constraint condition for ensuring that the power distribution network can safely operate in a recovery process comprises the voltage amplitude constraint, the tide constraint and the radial constraint.
Thus, the formula for the voltage magnitude constraint is specifically as follows:
U imin ≤U i′t ≤U imax ；
M＝(1-x jk )M 0 ；
U j，t -U k，t ≤2(P jk，t R jk，t +Q jk，t X jk，t )+M；
U j，t -U k，t ≥2(P jk，t R jk，t +Q jk，t X jk，t )-M；
here, U i，t The voltage amplitude of the node i; u (U) imax 、U imin Respectively the upper limit value and the lower limit value of the voltage amplitude of the node i; x is x jk Selecting a variable for a branch (j, k), wherein if the branch is selected, the variable is 1, otherwise, the variable is 0; m is M 0 Is a larger positive number; r is R jk And X jk The resistance and reactance of the branches (j, k), respectively.
The flow constraint formula is specifically as follows:
wherein P is jk 、Q jk 、And->Active power, reactive power, minimum power allowed to pass and maximum power allowed to pass on the branches (j, k), respectively.
The formula of the radial constraint is specifically as follows:
in this way the first and second light sources,decision variables for the nth recovery path of the ith node, via which path recovery is then +.>Otherwise, 0. Otherwise, 0./>Indicating the branch passing condition of the nth path of the ith node, the branch corresponding element of the path passing by is set to 1,/-or>The number of branches included in the nth path at the time of planning and solving is represented.
In the above, the first objective function and the weight parameter for recovering the value of each type of load determine the constraint condition that the second type of load meeting each type of load and the preset proportion is not powered off under the expected fault time, and the expression of the constraint condition is as follows:
s.t.K 1，2 (z，x，y)≤0；
wherein z is a decision variable of the self-contained emergency power supply configured for each superfine load. K represents two constraints formed to meet the toughness index requirements.
Here, the second objective function is related to the constraint condition, and the specific relationship is as follows:
in the above formula, K1 is the power supply area recovery requirement of the primary load (namely, the integral of the recovery load with respect to time), K2 is the power supply area recovery requirement of the secondary load, NL1 and NL2 are the number of nodes of the primary load and the secondary load; zeta type 1 And zeta 2 The primary load recovery ratio is characterized by primary load recovery ratio and secondary load recovery ratio;indicating whether the i node t is connected to the grid for recovery, and restoring the node +.>Is 1, P L，i And (t) is the load power of the node i at the moment t.
Through the setting of the constraint conditions of multiple types of energy sources, a specific first objective function provided by the embodiment of the application is determined, and the formula of the first objective function provided by the application is as follows:
the first objective function is that the maximum difference between the integral of various load recovery value quantities and the weighting of various energy scheduling cost is the toughness index of the power distribution network.
Here the number of the elements is the number,indicating whether the i node t is connected to the grid for recovery, and restoring the node +.>1. The force to set 1 is when the emergency power supply equipped load node is powered directly from the self-contained power supply. Lambda (lambda) i Recovering a value weight for the load of the node i; η (eta) i The coefficient of the flexible load weight coefficient is set to be 1 for the non-flexible load node; p (P) L,i (t) is the load power of the node i at the time t; alpha is the economic index weight. [ Γ ]]Is an economic loss interval [ C ] IL,i ]、[C rx,i ][ C ] gas ]Unit compensation electricity price and natural gas price parameter for interruptible load and flexible load respectively, m B Maintaining a cost coefficient, P, for operation of a unit electric quantity of the energy storage system es,dc And P es,ch Charging power of battery energy storage and discharging power of battery energy storage respectively, Q gas,i Is natural gas consumption.
S102, determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum configuration cost of the emergency power supply.
Here, the determining the configuration scheme of the emergency power supply according to the constraint condition and the second objective function includes:
and acquiring the minimum function value of the second objective function and the maximum function value of the first objective function.
And calculating and obtaining a first configuration result of the self-contained emergency power supply to each special-grade load according to the minimum function value.
Here, the first configuration result for each super load is a configuration result of the self-contained emergency power supply load.
And calculating to obtain a second configuration result of each energy source for each class-one load and the class-two loads with preset proportion according to the maximum function value.
And determining a configuration scheme of the emergency power supply according to the first configuration result and the second configuration result.
According to the second configuration result of each energy source to each class load and the preset proportion class load and the first configuration result to each special class load, stable supply and demand balance of each special class load, each primary load and the preset proportion secondary load under the expected fault time is realized until the toughness level requirement is met.
In this step, the specific expression of the second objective function is:
thus, h is the amount consumed by the emergency power supply, and z is the decision variable of the emergency power supply required to be configured for each special-level load.
The particle swarm algorithm is adopted to configure the emergency power supply, and whether each special-level load is configured with an emergency power supply of a certain model is a variable of 0-1.
Here, as shown in fig. 5, the upper layer model is solved by using a reference discrete binary particle swarm algorithm in the particle swarm algorithm, so as to determine a configuration scheme of the emergency power supply, where the particle swarm algorithm is a random search algorithm based on group collaboration developed by simulating the foraging behavior of a bird swarm. It is generally considered one of the intelligence of clustering. It may be incorporated into a multi-body optimization system.
Firstly, initializing a binary particle swarm by adopting a discrete binary particle swarm algorithm, wherein initialized particles c (i, j) represent the probability of configuring a j-th type emergency power supply by an inode, and determining the probability of configuring the emergency power supply by each special load in a first objective function according to the particles c (i, j), namely, the probability that a decision variable z (i, j) is 1.
After determining the z value in the constraint, the K value in the constraint needs to be determined, where the K value needs to satisfy a constraint sub-condition, and a formula of the constraint sub-condition is as follows:
in the above description, K1 is a power supply area recovery requirement for the primary load, and K2 is a power supply area recovery requirement for the secondary load; lambda (lambda) 1 、λ 2 Restoring weight for the lower model of the primary and secondary loads, when K1>At 0, the primary load recovery is not satisfied, when K2>When 0 represents that the secondary load recovery does not meet the requirement, it is known from the above formula that when K is larger than or equal to 0, for two different particles, particles with smaller K values are always prioritized, and only when the K values of the two particles are all smaller than 0 or the K values are equal positive values, the more optimal particles are judged according to the fitness function.
And when the K values of the two particles are determined to be smaller than 0 or the K values are equal to positive values, determining a fitness function, namely a constraint condition, wherein the fitness function takes a first objective function. If the j-type emergency power supply configuration probability at the i node is the largest, 1 is taken corresponding to z (i, j), and the rest z at the i node is taken as 0.
After the constraint condition is determined, continuously iterating the first objective function according to the fitness function, judging whether the maximum iteration times are reached, if so, determining a z value, further determining the amount consumed by configuring the emergency power supply, determining a final solution of the second objective function, if not, re-updating the speed position of the binary particles, and re-determining a K value according to the updated particles, and re-determining the final solution of the upper model.
In the above description, the K value is determined according to fig. 6, and fig. 6 is a flowchart illustrating a calculation manner of the K value in the final solution of the redetermining the first objective function.
Firstly, determining a target output curve of the maximum power supply area of each energy source according to a distributed power source, an energy storage facility and a gas turbine in a natural gas network, then recovering the value of each type of load at preset time intervals according to the target output curve, before recovering the value of each type of load, firstly judging whether each type of load needing to recover the value comprises an interruptible load or not, if the load needing to recover the value does not comprise the interruptible load, recovering the value of each type of current coincidence at preset time intervals according to the currently determined target output curve, and further calculating the K value.
If the load needing to recover the value quantity comprises an interruptible load, determining that the distributed power supply, the energy storage facility and the gas turbines in the natural gas network contain the interruptible load, determining and marking the type and the position of the interruptible load, redefining a target output curve corresponding to the maximum power supply area of each energy source according to the gas turbines in the distributed power supply, the energy storage facility and the natural gas network except for the interruptible load, recovering the value quantity which is met by the current various preset time intervals according to the redetermined target output curve, and further computing the K value again.
Here, taking the embodiment provided by the present application as an example, the expression of the second objective function of the present embodiment is:
m j ＝m j,INESS +m j,RESS ；
here, z i,j A decision variable of a j-th type emergency power supply which is configured at the i node or not; m is m j Configuring cost for the j-th type emergency power supply; m is m j,INESS The primary investment cost of the j-th emergency power supply; m is m j,RESS The operation and maintenance cost for the emergency power supply; min sigma t∈T |(M 2,t+2 -M 2,t+1 )-(M 2,t+1 -M 2,t ) The I is the percentage of annual operation maintenance cost to total investment cost; s is the discount rate; y represents the service life of the emergency power supply.
Further, the configuration cost of the emergency power supply is calculated according to the product of the probability of configuring the emergency power supply of different types by each load and the configuration cost of the emergency power supply of the type.
Wherein the second objective function characterizes the configuration cost of the emergency power supply by the product of the probability of configuring the emergency power supply of different types by each load and the configuration cost of the emergency power supply of the type, and the configuration cost of the emergency power supply is the sum of the investment cost of configuring the emergency power supply of the type once and the operation maintenance cost of the emergency power supply of the type.
In the above, in order to ensure the safety of the power distribution network in the load recovery process, balance constraint is performed on power:
wherein P is L，i N is the active load at the i node L N is the number of loads UPS The load number is the load number of the self-contained emergency power supply; p (P) IL，l Interrupting power for an interruptible load t period; p (P) gas The output of the gas turbine is output for a period t; p (P) ch Discharging power for the energy storage facility t period; p (P) dc Charging power for the energy storage facility t period; p (P) ups And (t) is the total output of the self-contained emergency power supply.
It is worth noting that when the node provided with the emergency power supply is powered by the emergency power supply, the node exits the network, and the corresponding load power is set to zero at the moment.
Compared with the prior art, the power grid emergency power supply configuration method provided by the embodiment of the application comprehensively considers the configuration cost recovery of the self-provided emergency power supply and the cost input by integrating the load value quantity and calling various energy sources on the premise of ensuring that each type of load and a certain proportion of the second type of load are not powered off in the expected failure time, so that the optimal configuration of the user side emergency power supply is realized, the configuration cost can be reduced, and the toughness level requirement is met.
Referring to fig. 2, fig. 2 is a flowchart of a power grid emergency power supply configuration method according to another embodiment of the application. As shown in fig. 2, the power grid emergency power supply configuration method provided by the embodiment of the application includes:
s201, determining an initial output curve of the distributed power supply for power generation according to fluctuation data of the distributed power supply for power generation under faults.
In this step, the expression of the initial force curve is:
min∑ t∈T |(M 2，t+2 -M 2，t+1 )-(M 2，t+1 -M 2，t )|；
M 2，t ＝M 1，t +P es，t t＝1，2，3....；
P es，t ＝P ch，t -P dc，t ；
the power output resolution of the embodiment of the application is 5min, so that 5min is taken as a preset time interval, M 1，t The DG output curve in the t-th time step after the fault; m is M 2，t The model objective function is the minimum sum of absolute values of slope changes of output of each time step; p (P) dc And P ch Is the charge and discharge power of the energy storage facility.
S202, based on the energy storage facilities and the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, performing pre-scheduling processing on the initial output curve, and determining a target output curve of the maximum power supply area of each energy source.
Further, the method for determining the target output curve of the maximum power supply area of all energy sources based on the energy storage facility and the dispatchable electric quantity output of the gas turbine in the natural gas network under the fault, and the method for determining the target output curve of the maximum power supply area of all energy sources comprises the following steps:
And adjusting the fluctuation of the initial output curve based on the dispatchable electric quantity output of the energy storage facility under the fault, and determining an intermediate output curve.
In the step, the gas turbine is used for filling the valley with the reference of P1, so that the output of the power supply in the whole time period is higher than P1, the requirement of toughness level is met, the curve at the moment is called an intermediate output curve M3 curve, and a plurality of formulas for determining the intermediate output curve M3 are as follows:
min∑ t∈T P gas，t ；
M 3，t ＝M 2，t +P gas，t t＝1，2，3....；
M 3，t ≥P 1 t＝1，2，3....；
P gas，t ≤P gas，max ；
if the output of the full-time power supply cannot be raised to P1, step 4 is directly performed, the fluctuation of the initial output curve is adjusted, and the target output curve of the maximum power supply area of all the power supplies is determined.
Further, based on the dispatchable electric quantity output of the gas turbine in the natural gas network under the fault, the fluctuation of the intermediate output curve is adjusted, and the target output curve of the maximum power supply area of all the energy sources is determined.
The expression of the target output curve is as follows:
M 4,τ,1 ＝M 4,τ,2 ＝...＝M 4,τ,12 τ＝1,2,3....8；
here, the remaining output of the gas turbine is used to determine the target output curve, in this embodiment, 30min is taken as a stage, the adjusted intermediate output curve is kept consistent at each 30min period, and the recovery decision of the period is performed according to the lowest output of each period of the target output curve.
And S203, dividing the target output curve according to preset time intervals, determining the minimum electric quantity output value in the preset time intervals, and adjusting the value quantity of various loads in the preset time intervals according to the minimum electric quantity output value in each preset time interval to obtain various load value quantity recovery data.
Here, the present embodiment sets the failure time to 8h, each 1h is a period, there are 12 time steps in each period, and in this step, the sum of the power output of each period is the maximum and the variance of the power output of 8 periods is the minimum as the objective function, and the power output of each period is maintained stable.The output of the combustion engine in the step; />And discarding the wind and the light power for the distributed power supply. M is M 4,τ,1 For the power output value of the M4 curve at time 1 step in hour τ, the last constraint indicates that the power pre-output remains constant for each hour.
S204, determining a first objective function according to the minimum value of the difference between the various load value quantity recovery data and the energy scheduling cost weighting.
S205, determining constraint conditions of uninterrupted power supply of the second class load meeting each class of loads and preset proportion under the expected fault time according to the first objective function and the weight parameters for recovering the value quantities of the various loads; the first objective function is a function which aims at minimizing the difference between the integral of each load value quantity and time and each energy scheduling cost weighting.
S206, determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum configuration cost of the emergency power supply.
The descriptions of S205 to S206 may refer to the descriptions of S101 to S102, and the same technical effects can be achieved, which will not be described in detail.
Compared with the prior art, the power grid emergency power supply configuration method provided by the embodiment of the application comprehensively considers the configuration cost recovery of the self-provided emergency power supply and the cost input by integrating the load value quantity and calling various energy sources on the premise of ensuring that each type of load and a certain proportion of the second type of load are not powered off in the expected failure time, so that the optimal configuration of the user side emergency power supply is realized, the configuration cost can be reduced, and the toughness level requirement is met.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an emergency power supply configuration device with strong local power grid toughness according to an embodiment of the present application. As shown in fig. 3, the emergency power supply configuration apparatus 300 with strong local power grid toughness includes:
a first determining module 310, configured to determine, according to a first objective function and a weight parameter for recovering the value amounts of the various loads, constraint conditions that the two types of loads satisfying the respective types of loads and the preset proportion are not powered off in the expected failure time; the first objective function is a function which aims at minimizing the difference between the integral of each load value quantity and time and each energy scheduling cost weighting.
A configuration module 320, configured to determine a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum configuration cost of the emergency power supply.
Compared with the prior art, the emergency power supply configuration device provided by the embodiment of the application comprehensively considers the configuration cost recovery of the self-provided emergency power supply and the cost input by integrating the load value quantity to time and calling various energy sources on the premise of ensuring that each type of load and a certain proportion of second type of loads are not powered off in the expected failure time, so that the optimal configuration of the emergency power supply at the user side is realized, the configuration cost can be reduced, and the toughness level requirement is met.
Referring to fig. 4, fig. 4 is a schematic structural diagram of another emergency power supply configuration device with strong local power grid toughness according to an embodiment of the present application. As shown in fig. 4, the emergency power supply configuration apparatus 300 with strong local power grid toughness includes:
a first determining module 310, configured to determine, according to a first objective function and a weight parameter for recovering the value amounts of the various loads, constraint conditions that the two types of loads satisfying the respective types of loads and the preset proportion are not powered off in the expected failure time; the first objective function is a function which aims at minimizing the difference between the integral of each load value quantity and time and each energy scheduling cost weighting.
A configuration module 320, configured to determine a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function that targets a minimum configuration cost of the emergency power supply.
The second determining module 330 is configured to determine an initial output curve of the distributed power supply according to fluctuation data of the distributed power supply generated under the fault.
The third determining module 340 performs prescheduling processing on the initial output curve based on the energy storage facility and the schedulable electric output of the gas turbine in the natural gas network under the fault, and determines a target output curve of the maximum power supply area of each energy source.
The preprocessing module 350 is configured to divide the target output curve according to preset time intervals, determine a minimum electric quantity output value in the preset time intervals, and adjust the value quantities of various loads in the preset time intervals according to the minimum electric quantity output value in each preset time interval, so as to obtain various load value quantity recovery data.
A fourth determining module 360, configured to determine a first objective function according to the minimum value of the difference between the load value recovery data and the energy scheduling cost weights.
Compared with the prior art, the emergency power supply configuration device provided by the embodiment of the application comprehensively considers the configuration cost recovery of the self-provided emergency power supply and the cost input by integrating the load value quantity to time and calling various energy sources on the premise of ensuring that each type of load and a certain proportion of second type of loads are not powered off in the expected failure time, so that the optimal configuration of the emergency power supply at the user side is realized, the configuration cost can be reduced, and the toughness level requirement is met.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the application. As shown in fig. 7, the electronic device 700 includes a processor 710, a memory 720, and a bus 730.
The memory 720 stores machine-readable instructions executable by the processor 710, when the electronic device 700 is running, the processor 710 communicates with the memory 720 through the bus 730, and when the machine-readable instructions are executed by the processor 710, the steps of the power grid emergency power supply configuration method in the method embodiments shown in fig. 1 and fig. 2 can be executed, and detailed implementation manners can refer to the method embodiments and are not repeated herein.
The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the power grid emergency power supply configuration method in the method embodiments shown in fig. 1 and fig. 2 may be executed, and a specific implementation manner may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as self-contained emergency products, may be stored on a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform 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 (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (8)
1. The utility model provides a power grid emergency power supply configuration method which is characterized in that the power grid emergency power supply configuration method comprises the following steps:
determining constraint conditions of uninterrupted power under the expected fault time of the two kinds of loads meeting the respective kinds of loads and the preset proportion according to the first objective function and the weight parameters for recovering the value quantities of the various loads; the first objective function is a function taking the minimum difference between the integral of each load value quantity and time and the weighting of each energy scheduling cost as an objective;
Determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function which aims at minimizing the configuration cost of the emergency power supply;
before determining constraint conditions that each class of loads and the class II loads with preset proportion are not powered off under the expected fault time according to the first objective function and the weight parameters for recovering the value quantities of the various loads, the power grid emergency power supply configuration method further comprises the following steps:
determining an initial output curve of power generation of the distributed power supply according to fluctuation data of power generation of the distributed power supply under faults;
based on the energy storage facilities and the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, performing pre-scheduling processing on the initial output curve, and determining a target output curve of the maximum power supply area of each energy source;
dividing the target output curve according to preset time intervals, determining the minimum electric quantity output value in the preset time intervals, and adjusting the value of each type of load in the preset time intervals according to the minimum electric quantity output value in each preset time interval to obtain the value recovery data of each type of load;
determining a first objective function according to the minimum value of the difference between the various load value quantity recovery data and the energy scheduling cost weighting;
The determining the configuration scheme of the emergency power supply according to the constraint condition and the second objective function comprises the following steps:
acquiring a minimum function value of the second objective function and a maximum function value of the first objective function;
calculating a first configuration result of the self-provided emergency power supply to each special-grade load according to the minimum function value,
calculating to obtain a second configuration result of each energy source for each class-one load and a preset proportion class-two load according to the maximum function value;
and determining a configuration scheme of the emergency power supply according to the first configuration result and the second configuration result.
2. The method for configuring an emergency power supply of a power grid according to claim 1, wherein the pre-scheduling the initial output curve based on the energy storage facility and the schedulable electric output of the gas turbine in the natural gas network under the fault, determining the target output curve of the maximum power supply area of all the energy sources comprises:
adjusting the fluctuation of the initial output curve based on the dispatchable electric quantity output of the energy storage facility under the fault, and determining an intermediate output curve;
and adjusting the fluctuation of the intermediate output curve based on the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, and determining the target output curve of the maximum power supply area of all the energy sources.
3. The power grid emergency power supply configuration method according to claim 1, wherein the formula of the first objective function is:
maxf 1 -α[f 2 ]；
f1 is the integral of the recovered load value quantity with respect to time; f2 is the scheduling cost of each energy source; alpha is an economic index weighting coefficient.
4. The power grid emergency power supply configuration method according to claim 1, wherein the formula of the second objective function is:
minh(z)；
h is the amount consumed by configuring the self-contained emergency power supply; z is a decision variable for each superfine load needing to be configured with an emergency power supply.
5. The power grid emergency power supply configuration method according to claim 1, wherein the configuration cost of the emergency power supply is calculated by:
and calculating the configuration cost of the emergency power supply according to the product of the probability of configuring the emergency power supplies of different types by each load and the configuration cost of the emergency power supply of the type.
6. An electrical grid emergency power supply configuration device, characterized in that the electrical grid emergency power supply configuration device comprises:
the first determining module is used for determining constraint conditions of uninterrupted power under the expected fault time of the second class load meeting each class of loads and the preset proportion according to the first objective function and the weight parameters for recovering the value quantities of various loads; the first objective function is a function taking the minimum difference between the integral of each load value quantity and time and the weighting of each energy scheduling cost as an objective;
The configuration module is used for determining a configuration scheme of the emergency power supply according to the constraint condition and the second objective function; the second objective function is a function which aims at minimizing the configuration cost of the emergency power supply;
before determining constraint conditions that each class of loads and the class II loads with preset proportion are not powered off under the expected fault time according to the first objective function and the weight parameters for recovering the value quantities of the various loads, the power grid emergency power supply configuration method further comprises the following steps:
determining an initial output curve of power generation of the distributed power supply according to fluctuation data of power generation of the distributed power supply under faults;
based on the energy storage facilities and the schedulable electric quantity output of the gas turbine in the natural gas network under the fault, performing pre-scheduling processing on the initial output curve, and determining a target output curve of the maximum power supply area of each energy source;
dividing the target output curve according to preset time intervals, determining the minimum electric quantity output value in the preset time intervals, and adjusting the value of each type of load in the preset time intervals according to the minimum electric quantity output value in each preset time interval to obtain the value recovery data of each type of load;
Determining a first objective function according to the minimum value of the difference between the various load value quantity recovery data and the energy scheduling cost weighting;
the determining the configuration scheme of the emergency power supply according to the constraint condition and the second objective function comprises the following steps:
acquiring a minimum function value of the second objective function and a maximum function value of the first objective function;
calculating a first configuration result of the self-provided emergency power supply to each special-grade load according to the minimum function value,
calculating to obtain a second configuration result of each energy source for each class-one load and a preset proportion class-two load according to the maximum function value;
and determining a configuration scheme of the emergency power supply according to the first configuration result and the second configuration result.
7. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory in communication via the bus when the electronic device is running, the machine readable instructions when executed by the processor performing the steps of the grid emergency power supply configuration method of any one of claims 1 to 5.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the grid emergency power supply configuration method according to any one of claims 1 to 5.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108123439A (en) * | 2018-01-03 | 2018-06-05 | 燕山大学 | A kind of repairing of active distribution network multiple faults and restoration methods based on multi-agent system |
| CN110445190A (en) * | 2019-08-01 | 2019-11-12 | 高东锋 | A kind of photo-thermal power station heat storage capacity configuration method and system |
| CN110826847A (en) * | 2019-09-19 | 2020-02-21 | 广州供电局有限公司 | Mobile emergency power supply scheduling method and device and computer equipment |
| CN111125887A (en) * | 2019-12-04 | 2020-05-08 | 广东电网有限责任公司 | Resource optimization configuration model establishment method for emergency recovery of power distribution network |
| CN112257944A (en) * | 2020-10-29 | 2021-01-22 | 山东大学 | Electric power emergency material optimal configuration method and system in elastic power distribution network |
| CN113011670A (en) * | 2021-03-30 | 2021-06-22 | 国网河北省电力有限公司电力科学研究院 | Power distribution network fault emergency repair dispatching-fault recovery coordination method and device |
| CN113178864A (en) * | 2021-04-19 | 2021-07-27 | 国网河北省电力有限公司 | Power distribution network power supply fault recovery method and device and terminal equipment |
| CN113346488A (en) * | 2021-06-09 | 2021-09-03 | 北京交通大学 | Urban distribution network recovery method considering mobile emergency resource scheduling |
-
2021
- 2021-11-02 CN CN202111286092.0A patent/CN113904330B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108123439A (en) * | 2018-01-03 | 2018-06-05 | 燕山大学 | A kind of repairing of active distribution network multiple faults and restoration methods based on multi-agent system |
| CN110445190A (en) * | 2019-08-01 | 2019-11-12 | 高东锋 | A kind of photo-thermal power station heat storage capacity configuration method and system |
| CN110826847A (en) * | 2019-09-19 | 2020-02-21 | 广州供电局有限公司 | Mobile emergency power supply scheduling method and device and computer equipment |
| CN111125887A (en) * | 2019-12-04 | 2020-05-08 | 广东电网有限责任公司 | Resource optimization configuration model establishment method for emergency recovery of power distribution network |
| CN112257944A (en) * | 2020-10-29 | 2021-01-22 | 山东大学 | Electric power emergency material optimal configuration method and system in elastic power distribution network |
| CN113011670A (en) * | 2021-03-30 | 2021-06-22 | 国网河北省电力有限公司电力科学研究院 | Power distribution network fault emergency repair dispatching-fault recovery coordination method and device |
| CN113178864A (en) * | 2021-04-19 | 2021-07-27 | 国网河北省电力有限公司 | Power distribution network power supply fault recovery method and device and terminal equipment |
| CN113346488A (en) * | 2021-06-09 | 2021-09-03 | 北京交通大学 | Urban distribution network recovery method considering mobile emergency resource scheduling |
Non-Patent Citations (2)
| Title |
|---|
| 云南电网应急恢复在线决策支持系统研究;黄伟等;《能源技术经济》;第23卷(第3期);第54-58页 * |
| 考虑柔性负荷的并网型微电网系统容量优化配置;杨丽君等;《太阳能学报》;第42卷(第2期);第309-316页 * |
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