CN112993982B - Limit value parameter acquisition method and device of automatic voltage control system and terminal equipment - Google Patents
Limit value parameter acquisition method and device of automatic voltage control system and terminal equipment Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H—ELECTRICITY
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Abstract
The invention is applicable to the technical field of power systems, and provides a method, a device and terminal equipment for acquiring limit parameters of an automatic voltage control system, wherein the method for acquiring the limit parameters of the automatic voltage control system comprises the following steps: obtaining limit value parameters under various voltage levels; taking limit value parameters under various voltage levels as simulation samples, and performing full-day automatic voltage control simulation on a target power system according to a preset typical daily power grid operation mode to obtain power grid state indexes corresponding to the limit value parameters under each voltage level after simulation; establishing a multiple linear regression analysis model according to the limit value parameters and the corresponding power grid state indexes under various voltage levels by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables; and obtaining the optimized limit value parameters according to the multiple linear regression analysis model and a preset limit value parameter optimization model. The invention can solve the problem of unreasonable setting of the limit value parameters.
Description
Technical Field
The invention belongs to the technical field of power systems, and particularly relates to a method, a device and terminal equipment for acquiring limit value parameters of an automatic voltage control system.
Background
An automatic voltage control (Automatic Voltage Control, AVC) system is an important means for realizing safe, economical and high-quality operation of a power system, and the basic principle is to realize reasonable distribution of reactive voltage in a power grid by coordinately controlling reactive output of a generator, a transformer tap and reactive compensation equipment.
So far, there are three main modes of automatic voltage control in the mainstream world:
the first mode is a two-level control mode represented by the germany RWE electric company, which has no so-called zone control, and the result of the optimization calculation of the Optimal Power Flow (OPF) is directly sent to the primary voltage controllers of each power plant to be controlled. However, the OPF model is computationally intensive and takes a long time to calculate. When large disturbance, load steep rise or steep drop occurs in the system, if the OPF is completely relied on, the response speed of AVC is insufficient, and the dynamic quality of control is difficult to ensure.
The second mode is a three-stage voltage control mode represented by French EDF, the research and implementation of which starts in the 70 s of the last century, and has been studied, developed and applied for over thirty years, and is currently internationally recognized as the most advanced voltage control system. This control mode is well applied but still has drawbacks because the Secondary Voltage Control (SVC) of the zones is developed based on the locality of the reactive voltage of the power system, whereas the reactive voltage between the zones is coupled, and the quality of the control system is therefore fundamentally dependent on the degree of coupling of the reactive voltage control between the zones. However, with the development of the power system and the real-time change of the operation condition, the area which is relatively decoupled is not considered to be invariable in design, and the control sensitivity existing in the form of fixed control parameters is changed in real time with the operation condition, so that the area controller fixed in the form of hardware is difficult to adapt to the continuous development of the power system and the large-scale change of the real-time operation condition, and a good control effect is difficult to be permanently ensured.
The third mode is a three-level voltage control mode based on soft partition, which is proposed by a motor system dispatching automation laboratory of Qinghua university, overcomes the defect of hard partition in EDF three-level voltage control through soft partition, has been widely applied to power grids in twenty or more areas and provincial power grids in China, and is successfully popularized to voltage control of North American PJM power grids. In this mode, the AVC application software of the dispatch center is composed of a tertiary control module and a secondary control module. Three-level control is an Optimal Power Flow (OPF) of global reactive power optimization, and a voltage optimization control target of whole network coordination is given; the secondary control is the control strategy calculation of partition decoupling, the optimization control targets of the central buses in each partition given by the tertiary control are taken as input, reactive power regulation equipment such as power plants in the partition are considered, the control strategies of various reactive power resources in the partition are calculated, and the reactive power regulation equipment is issued to the power plants and substations; the substation device at the station end completes the primary control, receives the control strategy issued by the dispatching master station and executes the control strategy.
At present, an AVC control system of a regional power grid generally adopts a three-level voltage control system based on soft partition, in the AVC control system, the upper and lower limit values of bus voltage and the upper and lower limit values of main transformer power factors are main limit value parameters, and the upper and lower limit values of bus voltage and the upper and lower limit values of main transformer power factors are reasonable, so that the AVC control effect is directly influenced. However, in engineering practice, the phenomenon of unreasonable setting of limit value parameters often occurs, so that unreasonable reactive power flows, and the safe and stable operation of the power grid voltage is further affected.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a method, an apparatus, and a terminal device for obtaining a limit parameter of an automatic voltage control system, so as to solve the problem of unreasonable setting of the limit parameter in the prior art.
A first aspect of an embodiment of the present invention provides a method for obtaining a limit value parameter of an automatic voltage control system, including:
obtaining limit parameters under various voltage classes, wherein the limit parameters under each voltage class at least comprise bus voltage limit parameters and main transformer power factor limit parameters under the corresponding voltage class;
taking limit value parameters under various voltage levels as simulation samples, and performing full-day automatic voltage control simulation on a target power system according to a preset typical daily power grid operation mode to obtain power grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
establishing a multiple linear regression analysis model according to the limit value parameters and the corresponding power grid state indexes under various voltage levels by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables;
and obtaining the optimized limit value parameters according to the multiple linear regression analysis model and a preset limit value parameter optimization model.
Optionally, the power grid state index at least comprises a total active power grid loss value, a total reactive power grid loss value, a reactive power exchange value between the whole grid and an upper power grid, an upper limit percentage of the whole grid voltage, a lower limit percentage of the whole grid voltage and the action times of the whole grid reactive power equipment.
Optionally, the objective function of the preset limit parameter optimization model at least includes one of the following:
min{‖Y3‖ 2 }；
alternatively, min { W p ·‖Y1‖ 2 +W q ·‖Y2‖ 2 +W q ·‖Y3‖ 2 }；
Wherein II Y1 II 2 Representing absolute value of total active network loss value of whole network, and II Y2 II 2 Representing absolute value of total reactive power loss value of whole network, and II Y3 II 2 Representing reactive exchange value of the whole network and the upper power grid, W p Representing the active coefficient, W q Representing the reactive coefficient, representing the multiplication.
Optionally, the constraint conditions of the preset limit parameter optimization model include:
0≤C1≤C1 avg ；
0≤C2≤C2 avg ；
0≤C3≤C3 avg ；
wherein C1 represents the upper limit percentage of the whole network voltage, C1 avg Representing the average value of the upper limit percentages of all the full network voltages obtained after simulation; c2 represents the percentage of the lower limit of the total network voltage, C2 avg Representing the average value of the lower limit percentages of all the full network voltages obtained after simulation; c3 represents the action times of the whole network reactive power equipment, C3 avg And (5) representing the average value of the action times of all the whole-network reactive equipment obtained after simulation.
Optionally, obtaining the optimized limit parameter according to the multiple linear regression analysis model and the preset limit parameter optimization model includes:
calculating coefficients of each regression equation in the multiple linear regression analysis model according to the least square method and the grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
and combining the objective function and constraint conditions to obtain the optimized limit value parameters.
A second aspect of an embodiment of the present invention provides a limit value parameter obtaining apparatus of an automatic voltage control system, including:
the acquisition module is used for acquiring limit value parameters under various voltage classes, wherein the limit value parameters under each voltage class at least comprise bus voltage limit value parameters and main transformer power factor limit value parameters under the corresponding voltage class;
the simulation module is used for carrying out full-day automatic voltage control simulation on the target power system according to a preset typical daily power grid operation mode by taking limit value parameters under various voltage levels as simulation samples, and obtaining power grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
the construction module is used for establishing a multiple linear regression analysis model according to the limit value parameters under various voltage levels and the corresponding power grid state indexes by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables;
and the optimization module is used for obtaining the optimized limit value parameters according to the multiple linear regression analysis model and the preset limit value parameter optimization model.
Optionally, the power grid state index at least comprises a total active power grid loss value, a total reactive power grid loss value, a reactive power exchange value between the whole grid and an upper power grid, an upper limit percentage of the whole grid voltage, a lower limit percentage of the whole grid voltage and the action times of the whole grid reactive power equipment.
Optionally, the objective function of the preset limit parameter optimization model at least includes one of the following:
min{‖Y3‖ 2 }；
alternatively, min { W p ·‖Y6‖ 2 +W q ·‖Y2‖ 2 +W q ·‖Y3‖ 2 }；
Wherein II Y6 II 2 Representing absolute value of total active network loss value of whole network, and II Y2 II 2 Representing absolute value of total reactive power loss value of whole network, and II Y3 II 2 Representing reactive exchange value of the whole network and the upper power grid, W p Representing the active coefficient, W q Representing the reactive coefficient, representing the multiplication.
Optionally, the constraint conditions of the preset limit parameter optimization model include:
0≤C6≤C6 avg ；
0≤C2≤C2 avg ；
0≤C3≤C3 avg ；
wherein C6 represents the upper limit percentage of the whole network voltage, C6 avg Representing the average value of the upper limit percentages of all the full network voltages obtained after simulation; c2 represents the percentage of the lower limit of the total network voltage, C2 avg Representing the average value of the lower limit percentages of all the full network voltages obtained after simulation; c3 represents the action times of the whole network reactive power equipment, C3 avg And (5) representing the average value of the action times of all the whole-network reactive equipment obtained after simulation.
Optionally, obtaining the optimized limit parameter according to the multiple linear regression analysis model and the preset limit parameter optimization model includes:
calculating coefficients of each regression equation in the multiple linear regression analysis model according to the least square method and the grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
and combining the objective function and constraint conditions to obtain the optimized limit value parameters.
A third aspect of an embodiment of the present invention provides a terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to the first aspect when executing the computer program.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
according to the embodiment of the invention, the limit value parameters under various voltage levels can be obtained firstly, then the limit value parameters under various voltage levels are taken as simulation samples, the full-day automatic voltage control simulation is carried out on the target power system according to the preset typical daily power grid operation mode, the power grid state index corresponding to the limit value parameters under each voltage level after the simulation is obtained, then the limit value parameters are taken as independent variables, the power grid state index is taken as dependent variables, a multiple linear regression analysis model is established according to the limit value parameters under various voltage levels and the corresponding power grid state index, and finally the optimized limit value parameters can be obtained according to the multiple linear regression analysis model and the preset limit value parameter optimization model. Therefore, the optimized limit value parameter is used as the limit value parameter for actual use, the unreasonable limit value parameter setting condition can be improved, the reactive layering and partition balance of the power grid is realized, the voltage control effect is further improved, and the requirements of safe and economic operation of the power grid are met.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of steps of a method for obtaining a limit value parameter of an automatic voltage control system according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a limit value parameter obtaining device of an automatic voltage control system according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
As described in the background art, at present, an AVC control system of a regional power grid generally adopts a three-level voltage control system based on "soft partition", in the AVC control system, an upper limit value and a lower limit value of a bus voltage and an upper limit value and a lower limit value of a main transformer power factor are main limit value parameters, and the rationality of the upper limit value and the lower limit value of the bus voltage and the upper limit value and the lower limit value of the main transformer power factor directly affect AVC control effects. However, in engineering practice, the phenomenon of unreasonable setting of limit value parameters often occurs, so that unreasonable reactive power flows, and the safe and stable operation of the power grid voltage is further affected.
In order to solve the problems in the prior art, the embodiment of the invention provides a method, a device and terminal equipment for acquiring limit value parameters of an automatic voltage control system. The method for acquiring the limit value parameter of the automatic voltage control system provided by the embodiment of the invention is first described below.
First, the principle of regression analysis used in the embodiments of the present invention will be described.
Linear regression is a statistical analysis method for determining the quantitative relationship of mutual dependence between two or more variables by using regression analysis in mathematical statistics, in which regression analysis is called unitary linear regression analysis if only one independent variable and one dependent variable are included and the relationship between the two can be approximated by a straight line, and multiplex linear regression analysis if two or more independent variables are included in regression analysis and the dependent variable and the independent variable are in linear relationship.
In linear regression, data is modeled using linear prediction functions, and unknown model parameters are also estimated from the data. For example, let x be 1 ,x 2 ,x 3 ,…,x p Is p (p)>1) The linear independent controllable variables, y is a random variable, and the relationship between them is:
wherein b 0 ,b 1 ,…,b p And σ2 are all equal to x 1 ,x 2 ,x 3 ,…,x p The unknown parameters are irrelevant, epsilon is a random error, which is a p-ary linear regression model. Mathematical expectations are taken from the two ends of the upper part, and the method can obtain
Ey＝b 0 +b 1 x 1 +…+x p x p
Wherein the method comprises the steps ofEy is x 1 ,x 2 ,x 3 ,…,x p Function b of (b) 0 ,b 1 ,…,b p Called regression coefficients.
N independent observations of the variables x1, x2, x3, …, xp and y give a sample x of capacity n i1 ,x i2 ,…,x ip ，y i (i=1, 2 …, n), i.e.:
wherein each epsilon in the above formula is independent of each other and obeys normal distribution, namely:
after conversion, the above can be written as
Y＝XB+ε；
Solving unknown parameter b by least square method 0 ,b 1 ,…,b p The parameter estimation of the regression model is:
the p-ary linear regression model is:
the above equation may be referred to as a p-ary linear regression equation,is a coefficient of the regression equation.
Next, an execution subject of the limit value parameter acquisition method of the automatic voltage control system will be described.
The execution subject of the method for obtaining the limit value parameter of the automatic voltage control system may be a device for obtaining the limit value parameter of the automatic voltage control system, where the device for obtaining the limit value parameter of the automatic voltage control system may be a terminal device with data processing capability, such as a notebook computer, a personal computer, etc., and the embodiment of the invention is not limited specifically.
As shown in fig. 1, the method for obtaining the limit value parameter of the automatic voltage control system according to the embodiment of the present invention may include the following steps:
step S110, obtaining limit value parameters under various voltage classes, wherein the limit value parameters under each voltage class at least comprise bus voltage limit value parameters and main transformer power factor limit value parameters under the corresponding voltage class.
In some embodiments, the voltage level may be a 110kV, 220kV, etc. voltage level.
And step S120, taking limit value parameters under various voltage levels as simulation samples, and performing full-day automatic voltage control simulation on the target power system according to a preset typical daily power grid operation mode to obtain power grid state indexes corresponding to the limit value parameters under each voltage level after simulation.
In some embodiments, during simulation, AVC control simulation calculation can be performed at 288 times of a period of 5 minutes throughout the day to obtain a reactive voltage index of the power grid with the capacity of N, i.e. a power grid state index.
In some embodiments, the grid status indicator includes at least a total active grid loss value, a total reactive grid loss value, a total and upper grid reactive exchange value, a total grid voltage upper limit percentage, a total grid voltage lower limit percentage, and a total grid reactive equipment action number.
And S130, establishing a multiple linear regression analysis model according to the limit value parameters under various voltage levels and the corresponding power grid state indexes by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables.
In some embodiments, multiple linear regression analysis models of various power grid state indexes can be established, such as multiple linear regression analysis models of total active network loss values of a whole network, multiple linear regression analysis models of total reactive network loss values of a whole network, multiple linear regression analysis models of reactive exchange values of a whole network and an upper power grid, multiple linear regression analysis models of higher limit percentage of whole network voltage, multiple linear regression analysis models of lower limit percentage of whole network voltage and multiple linear regression analysis models of the action times of whole network reactive equipment.
And step 140, obtaining optimized limit parameters according to the multiple linear regression analysis model and a preset limit parameter optimization model.
In some embodiments, the coefficient of each regression equation in each multiple linear regression analysis model may be calculated according to the least square method and the grid state index corresponding to the limit value parameter at each voltage level after simulation. And then, combining an objective function and constraint conditions of a preset limit parameter optimization model to obtain the optimized limit parameter.
Specifically, the objective function of the preset limit parameter optimization model at least includes one of the following:
min{‖Y3‖ 2 -a }; alternatively, min { W p ·‖Y1‖ 2 +W q ·‖Y2‖ 2 +W q ·‖Y3‖ 2 }；
Wherein II Y1 II 2 Representing absolute value of total active network loss value of whole network, and II Y2 II 2 Representing absolute value of total reactive power loss value of whole network, and II Y3 II 2 Representing reactive exchange value of the whole network and the upper power grid, W p Representing the active coefficient, W q Representing the reactive coefficient, representing the multiplication.
The constraint conditions of the preset limit parameter optimization model may include:
0≤C1≤C1 avg ；
0≤C2≤C2 avg ；
0≤C3≤C3 avg ；
wherein C1 represents the upper limit percentage of the whole network voltage, C1 avg Representing the average value of the upper limit percentages of all the full network voltages obtained after simulation; c2 represents the percentage of the lower limit of the total network voltage, C2 avg Representing the average value of the lower limit percentages of all the full network voltages obtained after simulation; c3 represents the action times of the whole network reactive power equipment, C3 avg Representation simulationAnd obtaining the average value of the action times of all the whole-network reactive equipment.
In order to better understand the method for acquiring the limit value parameter of the automatic voltage control system provided in the foregoing embodiment, an implementation manner is provided below, where the implementation manner includes the following steps:
1) Selecting different power grid control variables (limit parameters) of a target power system as simulation samples, and performing all-day AVC simulation in a typical daily power grid mode to obtain reactive voltage indexes of the power grid, namely state variables (power grid state indexes), wherein the method specifically comprises the following steps:
1-1) selecting the upper limit of all 220kV bus voltages of a power grid as a control variable X 1 (X 1 The value range is 235-229, the step length is 0.5kV, 13 steps are added), and the upper limit of the voltage of all 110kV buses is the control variable X 2 (X 2 The value range is 120-114, the step length is 0.5kV, 13 steps are added), and the power factor lower limit value X of all 220kV and 110kV main transformers 3 (X 3 The value range is 0.99-0.93, the step length is 0.005, and the total is 13 steps), wherein, the variable X is controlled 1 Is the minimum value X of (2) 1_min =229, maximum value X 1_max =235, control variable X 2 Is the minimum value X of (2) 2_min =114, maximum value X 2_max =120, control variable X 3 Is the minimum value X of (2) 3_min =0.93, maximum value X 3_max =0.99, so that possible combinations of all control variables n=2197 can be obtained, n= 13 x 13 the number of the active components, wherein N is xi (i=1, 2, 3) is the control variable X i The number of the values of (a) is N respectively x1 ＝13，N x2 ＝13，N x3 ＝13。
1-2) taking the combination of the control variables N=2197 in 1-1) as simulation samples, performing AVC control simulation calculation at 288 times of a period of 5 minutes throughout the day to obtain reactive voltage operation indexes of the power grid with the capacity of N=2197, and dividing the indexes into Y n (n= … N) and C n (n= … N), the index data adopts a per unit value mode, wherein, the basic value of 220kV voltage adopts 230, the basic value of 110kV voltage adopts 115, and the reactive equipment action times are divided by 100, so that the following table can be obtained:
2) Taking the control variable in the step 1) as an independent variable and the state variable as a dependent variable, establishing a multiple linear regression analysis model, and calculating coefficients of a regression equation by using a least square method, wherein the method specifically comprises the following steps:
2-1) establishing the respective state variables and the control variables X i (i=1, 2, 3) multiple linear regression analysis model as follows:
2-1-1) total active network loss y1=β of the whole network 0_y1 +β 1_y1 *X 1 +β 2_y1 *X 2 +β 3_y1 *X 3 ；
2-1-2) total reactive power loss y2=β 0_y2 +β 1_y2 *X 1 +β 2_y2 *X 2 +β 3_y2 *X 3 ；
2-1-3) full network and superior 500kV power grid reactive power exchange y3=beta 0_y3 +β 1_y3 *X 1 +β 2_y3 *X 2 +β 3_y3 *X 3 ；
2-1-4) full network 10kV voltage over upper limit ratio c1=β 0_c1 +β 1_c1 *X 1 +β 2_c1 *X 2 +β 3_c1 *X 3 ；
2-1-5) full network 10kV voltage lower limit ratio c2=β 0_c2 +β 1_c2 *X 1 +β 2_c2 *X 2 +β 3_c2 *X 3 ；
2-1-6) the number of actions c3=β of the whole network reactive equipment 0_c3 +β 1_c3 *X 1 +β 2_c3 *X 2 +β 3_c3 *X 3 。
2-2) calculating the coefficient β of the regression equation by using the simulation data with the capacity of n=2197 obtained in the step 1-2) as a sample by using a least square method i_y1 ，β i_y2 ，β i_y3 ，β i_c1 ，β i_c2 ，β i_c3 (i=0, 1,2, 3), the regression equation is obtained as follows;
2-2-1) total active network loss y1= 0.30222-0.0632 x 1 -0.02883*X 2 -0.01311*X 3 ；
2-2-2) total reactive power loss of the whole network y2= 5.59381-1.38264 x 1 -0.37192*X 2 -0.21284*X 3 ；
2-2-3) full network and upper 500kV grid reactive exchange y3= -36.64304+31.40875 x 1 +0.00680*X 2 +4.92455*X 3 ；
2-2-4) full network 10kV voltage over upper limit ratio c1= -0.57161+0.40314 x 1 +0.22228*X 2 -0.02885*X 3 ；
2-2-5) full network 10kV voltage lower limit ratio c2= 0.34364-0.03778 x 1 -0.22995*X 2 -0.05956*X 3 ；
2-2-6) the number of full-network reactive equipment actions c3=22.24256+20.92729 x 1 -31.47578*X 2 -6.27635*X 3 。
3) Based on the regression equation obtained in the step 2), the indexes Y1, Y2 and Y3 are taken as target functions, the indexes C1, C2 and C3 are taken as constraint conditions, a quadratic programming optimization model of a single target or a composite target is constructed, and an optimal limit value is calculated, and the method specifically comprises the following steps:
3-1) a single optimization target, wherein the minimum absolute value of reactive exchange between the region and the upper power grid is considered, and the method specifically comprises the following steps:
3-1-1) quadratic programming objective function and inequality constraints as follows:
min||Y3|| 2 ；
0≤C1≤0.033；
0≤C2≤0.014；
0≤C3≤5.300；
0.93≤X 3 ≤0.99；
wherein constraint C1 avg 、C2 avg 、C2 avg Taking the average of all n=2197 indices, i.e. C1 avg ＝0.033，C2 avg ＝0.014，C3 avg ＝5.300。
3-1-2) calculating an optimum limit, i.e. optimum X 1 ＝1.011210(232.58kV)，X 2 ＝1.013187(116.52kV)，X 3 ＝0.99。
In this way, the calculated limit results can ensure that reactive exchanges with the upper grid are minimized.
3-2) a composite optimization target, wherein the minimum absolute value of the active network loss of the whole network, the minimum absolute value of the reactive network loss and the minimum reactive exchange with the upper layer are considered, and the method comprises the following steps:
3-2-1) quadratic programming objective function and inequality constraints as follows:
min{W p ·||Y1|| 2 +W q ·||Y2|| 2 +W q ·||Y3|| 2 }
0≤C1≤0.033；
0≤C2≤0.014；
0≤C3≤5.300；
0.93≤X 3 ≤0.99；
wherein W is p 、W q The values of the active weight coefficient and the reactive weight coefficient are respectively 1.0 and 0.1; constraint C1 avg 、C2 avg 、C2 avg Taking the average value C1 of all N=2197 indexes avg ＝0.033，C2 avg ＝0.014，C3 avg ＝5.300。
3-2-2) calculating an optimum limit, i.e. optimum X 1 ＝1.011756(232.70kV)，X 2 ＝1.013550(116.56kV)，X 3 The limit result given in this way ensures, on the one hand, that the active and reactive losses are minimized and that the reactive flows are reasonable, and on the other hand, that the bus voltage out-of-limit ratio and the number of actions are constrained.
In the embodiment of the invention, limit parameters under various voltage levels can be acquired firstly, then the limit parameters under various voltage levels are taken as simulation samples, an automatic voltage control simulation is carried out on a target power system all the day according to a preset typical daily power grid operation mode, a power grid state index corresponding to the limit parameters under each voltage level after the simulation is obtained, then the limit parameters are taken as independent variables, the power grid state index is taken as dependent variables, a multiple linear regression analysis model is established according to the limit parameters under various voltage levels and the corresponding power grid state indexes, and finally the optimized limit parameters can be obtained according to the multiple linear regression analysis model and a preset limit parameter optimization model. Therefore, the optimized limit value parameter is used as the limit value parameter for actual use, the unreasonable limit value parameter setting condition can be improved, the reactive layering and partition balance of the power grid is realized, the voltage control effect is further improved, and the requirements of safe and economic operation of the power grid are met.
Based on the method for acquiring the limit value parameter of the automatic voltage control system provided by the embodiment, correspondingly, the invention further provides a specific implementation mode of the device for acquiring the limit value parameter of the automatic voltage control system, which is applied to the method for acquiring the limit value parameter of the automatic voltage control system. Please refer to the following examples.
As shown in fig. 2, there is provided a limit value parameter acquisition device of an automatic voltage control system, the device comprising:
the obtaining module 210 is configured to obtain limit parameters under multiple voltage classes, where the limit parameter under each voltage class at least includes a bus voltage limit parameter and a main transformer power factor limit parameter under the corresponding voltage class;
the simulation module 220 is configured to perform full-day automatic voltage control simulation on the target power system according to a preset typical daily power grid operation mode by taking limit parameters under multiple voltage levels as simulation samples, so as to obtain a power grid state index corresponding to the limit parameters under each voltage level after simulation;
the construction module 230 is configured to establish a multiple linear regression analysis model according to the limit value parameters and the corresponding power grid state indexes under various voltage levels by using the limit value parameters as independent variables and the power grid state indexes as dependent variables;
the optimization module 240 is configured to obtain an optimized limit parameter according to the multiple linear regression analysis model and a preset limit parameter optimization model.
Optionally, the power grid state index at least comprises a total active power grid loss value, a total reactive power grid loss value, a reactive power exchange value between the whole grid and an upper power grid, an upper limit percentage of the whole grid voltage, a lower limit percentage of the whole grid voltage and the action times of the whole grid reactive power equipment.
Optionally, the objective function of the preset limit parameter optimization model at least includes one of the following:
min{‖Y3‖ 2 }；
alternatively, min { W p ·‖Y6‖ 2 +W q ·‖Y2‖ 2 +W q ·‖Y3‖ 2 }；
Wherein II Y6 II 2 Representing absolute value of total active network loss value of whole network, and II Y2 II 2 Representing absolute value of total reactive power loss value of whole network, and II Y3 II 2 Representing reactive exchange value of the whole network and the upper power grid, W p Representing the active coefficient, W q Representing the reactive coefficient, representing the multiplication.
Optionally, the constraint conditions of the preset limit parameter optimization model include:
0≤C6≤C6 avg ；
0≤C2≤C2 avg ；
0≤C3≤C3 avg ；
wherein C6 represents the upper limit percentage of the whole network voltage, C6 avg Representing the average value of the upper limit percentages of all the full network voltages obtained after simulation; C2C 2Represents the lower limit percentage of the whole network voltage, C2 avg Representing the average value of the lower limit percentages of all the full network voltages obtained after simulation; c3 represents the action times of the whole network reactive power equipment, C3 avg And (5) representing the average value of the action times of all the whole-network reactive equipment obtained after simulation.
Optionally, obtaining the optimized limit parameter according to the multiple linear regression analysis model and the preset limit parameter optimization model includes:
calculating coefficients of each regression equation in the multiple linear regression analysis model according to the least square method and the grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
and combining the objective function and constraint conditions to obtain the optimized limit value parameters.
In the embodiment of the invention, limit parameters under various voltage levels can be acquired firstly, then the limit parameters under various voltage levels are taken as simulation samples, an automatic voltage control simulation is carried out on a target power system all the day according to a preset typical daily power grid operation mode, a power grid state index corresponding to the limit parameters under each voltage level after the simulation is obtained, then the limit parameters are taken as independent variables, the power grid state index is taken as dependent variables, a multiple linear regression analysis model is established according to the limit parameters under various voltage levels and the corresponding power grid state indexes, and finally the optimized limit parameters can be obtained according to the multiple linear regression analysis model and a preset limit parameter optimization model. Therefore, the optimized limit value parameter is used as the limit value parameter for actual use, the unreasonable limit value parameter setting condition can be improved, the reactive layering and partition balance of the power grid is realized, the voltage control effect is further improved, and the requirements of safe and economic operation of the power grid are met.
Fig. 3 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 3, the terminal device 3 of this embodiment includes: a processor 30, a memory 31 and a computer program 32 stored in said memory 31 and executable on said processor 30. The processor 30, when executing the computer program 32, implements the steps of the above-described embodiments of the method for obtaining the limit value parameter of each automatic voltage control system. Alternatively, the processor 30, when executing the computer program 32, performs the functions of the modules/units of the apparatus embodiments described above.
Illustratively, the computer program 32 may be partitioned into one or more modules/units that are stored in the memory 31 and executed by the processor 30 to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 32 in the terminal device 3. For example, the computer program 32 may be divided into an acquisition module, a simulation module, a construction module, and an optimization module, each of which functions as follows:
the acquisition module is used for acquiring limit value parameters under various voltage classes, wherein the limit value parameters under each voltage class at least comprise bus voltage limit value parameters and main transformer power factor limit value parameters under the corresponding voltage class;
the simulation module is used for carrying out full-day automatic voltage control simulation on the target power system according to a preset typical daily power grid operation mode by taking limit value parameters under various voltage levels as simulation samples, and obtaining power grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
the construction module is used for establishing a multiple linear regression analysis model according to the limit value parameters under various voltage levels and the corresponding power grid state indexes by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables;
and the optimization module is used for obtaining the optimized limit value parameters according to the multiple linear regression analysis model and the preset limit value parameter optimization model.
The terminal device 3 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 30, a memory 31. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the terminal device 3 and does not constitute a limitation of the terminal device 3, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, etc.
The processor 30 may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may be an internal storage unit of the terminal device 3, such as a hard disk or a memory of the terminal device 3. The memory 31 may be an external storage device of the terminal device 3, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the terminal device 3. The memory 31 is used for storing the computer program as well as other programs and data required by the terminal device. The memory 31 may also be used for temporarily storing data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment 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, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., 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 may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
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 invention 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 integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (8)
1. A method for obtaining a limit value parameter of an automatic voltage control system, comprising:
obtaining limit parameters under various voltage classes, wherein the limit parameters under each voltage class at least comprise bus voltage limit parameters and main transformer power factor limit parameters under the corresponding voltage class;
taking the limit value parameters under the multiple voltage levels as simulation samples, and performing full-day automatic voltage control simulation on a target power system according to a preset typical daily power grid operation mode to obtain power grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
establishing a multiple linear regression analysis model according to the limit value parameters under the multiple voltage levels and the corresponding power grid state indexes by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables;
obtaining an optimized limit value parameter according to the multiple linear regression analysis model and a preset limit value parameter optimization model, wherein an objective function of the preset limit value parameter optimization model at least comprises one of the following: min { |Y 3 | 2 -a }; alternatively, min { W p ·‖Y1‖ 2 +W q ·‖Y2‖ 2 +W q ·‖Y3‖ 2 -a }; wherein II Y1 II 2 Representing absolute value of total active network loss value of whole network, and II Y2 II 2 Representing absolute value of total reactive power loss value of whole network, and II Y3 II 2 Representing reactive exchange value of the whole network and the upper power grid, W p Representing the active coefficient, W q Representing the reactive coefficient, representing the multiplication.
2. The method for obtaining limiting value parameters of an automatic voltage control system according to claim 1, wherein the power grid state index at least comprises a total active power grid loss value of the whole grid, a total reactive power grid loss value of the whole grid, a reactive power exchange value of the whole grid and an upper power grid, an upper limit percentage of the whole grid voltage, a lower limit percentage of the whole grid voltage and the number of times of actions of the whole grid reactive power equipment.
3. The method for obtaining the limiting value parameter of the automatic voltage control system according to claim 2, wherein the constraint condition of the preset limiting value parameter optimization model includes:
0≤C1≤C1 avg ；
0≤C2≤C2 avg ；
0≤C3≤C3 avg ；
wherein C1 represents the upper limit percentage of the whole network voltage, C1 avg Representing the average value of the upper limit percentages of all the full network voltages obtained after simulation; c2 represents the percentage of the lower limit of the total network voltage, C2 avg Representing the average value of the lower limit percentages of all the full network voltages obtained after simulation; c3 represents the action times of the whole network reactive power equipment, C3 avg And (5) representing the average value of the action times of all the whole-network reactive equipment obtained after simulation.
4. The method for obtaining the limiting value parameter of the automatic voltage control system according to claim 3, wherein obtaining the optimized limiting value parameter according to the multiple linear regression analysis model and a preset limiting value parameter optimization model comprises:
calculating coefficients of each regression equation in the multiple linear regression analysis model according to the least square method and the grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
and combining the objective function and the constraint condition to obtain the optimized limit value parameter.
5. A limit value parameter acquisition device of an automatic voltage control system, characterized by comprising:
the acquisition module is used for acquiring limit value parameters under various voltage classes, wherein the limit value parameters under each voltage class at least comprise bus voltage limit value parameters and main transformer power factor limit value parameters under the corresponding voltage class;
the simulation module is used for carrying out full-day automatic voltage control simulation on the target power system according to a preset typical daily power grid operation mode by taking the limit value parameters under the multiple voltage levels as simulation samples, and obtaining power grid state indexes corresponding to the limit value parameters under each voltage level after simulation;
the construction module is used for constructing a multiple linear regression analysis model according to the limit value parameters under the multiple voltage levels and the corresponding power grid state indexes by taking the limit value parameters as independent variables and the power grid state indexes as dependent variables;
the optimization module is used for obtaining optimized limit parameters according to the multiple linear regression analysis model and a preset limit parameter optimization model, and the objective function of the preset limit parameter optimization model at least comprises one of the following: min { |Y 3 | 2 -a }; alternatively, min { W p ·‖Y1‖ 2 +W q ·‖Y2‖ 2 +W q ·‖Y3‖ 2 -a }; wherein II Y1 II 2 Representing absolute value of total active network loss value of whole network, and II Y2 II 2 Representing absolute value of total reactive power loss value of whole network, and II Y3 II 2 Representing reactive exchange value of the whole network and the upper power grid, W p Representing the active coefficient, W q Representing the reactive coefficient, representing the multiplication.
6. The device for obtaining limiting value parameters of an automatic voltage control system according to claim 5, wherein the power grid state index at least comprises a total active power grid loss value of the whole grid, a total reactive power grid loss value of the whole grid, a reactive power exchange value of the whole grid and an upper power grid, an upper limit percentage of the whole grid voltage, a lower limit percentage of the whole grid voltage and the number of times of actions of the whole grid reactive power equipment.
7. The apparatus for obtaining limiting value parameters of an automatic voltage control system according to claim 6, wherein the constraint conditions of the preset limiting value parameter optimization model include:
0≤C6≤C6 avg ；
0≤C2≤C2 avg ；
0≤C3≤C3 avg ；
wherein C6 represents the upper limit percentage of the whole network voltage, C6 avg Representing the average value of the upper limit percentages of all the full network voltages obtained after simulation; c2 represents the percentage of the lower limit of the total network voltage, C2 avg Representing the average value of the lower limit percentages of all the full network voltages obtained after simulation; c3 represents the action times of the whole network reactive power equipment, C3 avg And (5) representing the average value of the action times of all the whole-network reactive equipment obtained after simulation.
8. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 4 when the computer program is executed.
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