CN108054834A - A kind of multistage energy coordinated control system - Google Patents
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Abstract
The present invention relates to a kind of multistage energy coordinated control systems, the sensing module will carry out a series of monitoring to distribution network, include voltage checking chip and power meter disk in sensing module, and the voltage data and current data that monitor are transferred to message processing module, there is database chip in message processing module for information matches, described information processing module receives to come from carries out analysis and optimization after the data of sensing module by processor, and pass through wire transmission and instruct to control and execution module, the control is adjusted and optimizes to distribution network after receiving instruction with execution module, including adjusting and optimizing information database, manual operation execution module.The advantage of the invention is that：New energy at different levels can be synthesized and coordinated, Distributed Autonomous, coordination optimization operation between reaching at different levels meet Future New Energy Source development trend, and possibility is provided for the zonal new energy of operation on a large scale.
Description
Technical Field
The invention belongs to the field of energy control systems, and particularly relates to a multi-stage energy coordination control system.
Background
At present, the rapid consumption of fossil energy resources such as coal, oil, natural gas and the like, the ecological environment is continuously deteriorated, particularly, the global climate change which is increasingly severe is caused by the emission of greenhouse gases, and the sustainable development of the human society is seriously threatened. Energy technology develops towards low carbon and no carbonization, and along with the popularization and application of electric vehicles with power having random fluctuation characteristics, wind power, solar power generation and other power sources connected to power grids in large quantity, mobile loads and energy storage characteristics and the strict requirements of modern society on power supply reliability and electric energy quality, electric power systems closely related to human life face more and more challenges. The method has the advantages that the construction of the multi-level energy system of the smart power grid is implemented, the development of industries related to the smart power grid is accelerated, and the method has important practical significance for changing economic development modes, promoting the optimization and upgrade of industrial structures and accelerating the integration of informatization and industrialization.
In summary, the problems of the prior art are as follows: the rapid consumption of fossil energy resources such as coal, oil, natural gas and the like, the ecological environment is continuously deteriorated, particularly, the sustainable development of the human society is seriously threatened due to increasingly severe global climate change caused by the emission of greenhouse gases.
Disclosure of Invention
The invention provides a multi-stage energy coordination control system which is simple in structure and capable of improving working efficiency for solving the technical problems in the prior art.
The technical scheme adopted by the invention for solving the technical problems in the prior art is as follows:
the invention is realized in this way, a multi-stage energy coordination control system, which comprises:
the sensing module is used for carrying out a series of monitoring on the power distribution network, comprises a voltage detection chip and a watt-hour meter dial, and transmitting the monitored voltage data and current data to the information processing module;
the calculation method of the sensing module positioning node coordinate receiving module comprises the following steps:
firstly, selecting a differential correction point, determining a coordinate of a positioning intersection point and a plurality of positioning intersection points, and calculating the distance between the positioning intersection points; :
from d' i (i =0,1,2, …, n) selecting anchor node a with the smallest distance value 0 For the differential correction points, the 3 smallest distance values are then taken from the remaining distance values, these 3 being the distance values d' 1 、d′ 2 And d' 3 The coordinates of the corresponding anchor nodes are respectively A 1 x 1 ,y 1 、A 2 x 2 ,y 2 And A 3 x 3 ,y 3 Respectively with anchor nodes A i x i ,y i Is the circle center d' i Making three positioning circles i for the radius, wherein i =1,2,3, the intersection conditions of the three positioning circles are 6 in total, two intersection points exist between the two circles, and the two intersection points are two equal real number intersection points, or two unequal real number intersection points, or two complex number intersection points; selecting one intersection point with a smaller distance from a coordinate of the center of the third positioning circle from two intersection points of the two positioning circles as a positioning intersection point to participate in positioning of the node to be positioned; determining the number m of three positioning intersection points and a plurality of positioning intersection points by using 3 positioning circles, wherein the coordinates of the positioning intersection points determined by the positioning circles 2 and 3 are A 'x' 1 ,y′ 1 And the coordinates of the positioning intersection points determined by the positioning circle 1 and the positioning circle 3 are B 'x' 2 ,y′ 2 The coordinates of the positioning intersection defined by the positioning circle 1 and the positioning circle 2 are C 'x' 3 ,y′ 3 Location of intersection A'
The distances from B ', B ' and C ', A ' and C ' are d 12 、d 23 、d 13 ：
Secondly, setting a threshold T, an individual difference coefficient correction coefficient omega, a parameter lambda (lambda is larger than 0), setting T =0.5, omega =1500 and lambda =0.001, and setting the distance d between the three positioning intersection points 12 ＜T、d 23 ＜T、d 13 If T is less than T, executing the fourth step;
third, d is corrected according to the following adaptive distance correction formula 1 、d′ 2 、d′ 3 Obtaining a corrected distance d 1 、d′ 2 、d′ 3 ：
Wherein d is i Representing the node to be positioned and the anchor node A i Corrected distance between d 0i Representing a differential correction point A 0 And anchor node A i Actual distance between, d' 0i Representing a differential correction point A 0 And anchor node A i A measured distance therebetween, ω represents an individual difference coefficient correction coefficient, λ i Representing a directional correction factor, exp representing an exponential function;
according to the corrected distance d 1 、d 2 、d 3 Re-solving the distance d between the three corrected positioning intersections 12 、 d 23 、d 13 Returning to the second step;
fourthly, calculating the positioning coordinates O x of the node to be positioned according to the following formula 0 ,y 0 ：
Wherein alpha is 1 、α 2 、α 3 Respectively represent x' 1 、x′ 2 、x′ 3 Weight of (b), beta 1 、β 2 、β 3 Are respectively y' 1 、y′ 2 、 y′ 3 The weight of (a) is calculated,
the information processing module is used for receiving the data from the sensing module, analyzing and optimizing the data and transmitting an instruction to the control and execution module;
the data packet of the information processing module adopts a double-layer bloom filter;
the bloom filter adopts a bit array V with the length of m and k mutually independent Haxi function numbers h 1 、h 2 、…、h k (ii) a When an element s needs to be stored to the bloom filter, the settings h are calculated separately 1 (s)、 h 2 (s)、…、h k (s) and setting the bit value of the corresponding position in V to be '1'; when the element u needs to be judged whether to be in the bloom filter or not, checking the h-th element in the V 1 (u)、h 2 (u)、…、h k (u) whether the bit values of the positions are all 1, if all 1, the element u is in S with a high probability, and if not all 1, u is not in the bloom filter;
the signal processing method of the information processing module comprises the following steps: obtaining x 1 And x 2 I.e. the power ratio k of the interfering signal to the desired signal i (i =1,2), signal-to-noise ratioAnd the spatial correlation cos of the interference with the desired signal 2 Theta, and calculate x i Receive criteria of
Wherein i =1,2,for the purpose of the signal-to-noise ratio,for a case where i =1, the number of the terminals is set to zero,for i =2,E 2 ＝H 2 p 2 ，
The control and execution module is used for adjusting and optimizing the power distribution network after receiving the instruction;
the continuous data preprocessing method of the control and execution module specifically comprises the following steps:
step one, training subset selection and generation: a plurality of groups of observation data and information of the categories are obtained to be used as the basis for establishing an algorithm model, each piece of information is called a training sample, and a plurality of training samples form a training set; if the training samples have k types, k is more than or equal to 2; then according to the training sample category, it is composed of two types of samplesA training subset, training subset X n Expressed as:
X n ＝{{x i }，{x j }}，
wherein the content of the first and second substances,i, j ∈ {1,2, …, n } with i ≠ j, { x i And { x } j Respectively representing the set of ith and jth samples in the training set;
step two, fisher classifier group:
using training subsets X n Generating Fisher discriminant model y n ＝f n (x) The method mainly comprises the following steps:
1) Finding X n In the middle of i, jMean of class samplesAndthe mean and formula are:
2) Solving an intra-class divergence matrix S wn ：
WhereinIs thatThe transposed matrix of (2).
3) Solving an inter-class divergence matrix S bn ：
4) Calculating the projection direction W n ：
W n ＝S wn -1 ·s bn
5) Computing Fisher discrimination threshold value w 0n ：
Then get the training subset X n The corresponding discrimination model is as follows: y is n ＝f n (x)＝W n ·x-w 0n ；
6) Solving Fisher discrimination models corresponding to each training subset according to the methods from step 1) to step 5) to generateAnd Fisher classifiers forming a Fisher classifier group, wherein the nth classifier can be expressed as:
step three, nonlinear continuous function mapping:
output y of Fisher classifier set by using nonlinear continuous function n Carry out mapping ifNon-linear mapping of the output of the nth Fisher classifierComprises the following steps:
wherein a (a)>, 0) is a relaxation variable introduced to enhance the generalization performance of the algorithm; if the Fisher classifier group consists of k classifiers, thenIs the result of data preprocessing.
Furthermore, the information processing module adopts a DSP digital processor and comprises instruction sequence control, operation control, time control and data processing;
the information processing module specifically acquires the coordinates of the electronic map of the unit path, and the method includes:
performing step counting operation by using an accelerometer and a gyroscope in the inertial navigation equipment, calculating the number of steps and the linear length of walking by a condition detection method, calculating the coordinate of an electronic map of each step, and recording the time t generated by the kth step coordinate s (k) K =1,2, L represents the total walking steps on the path, and the triaxial acceleration values collected by the accelerometer at the time k are a k (1)、a k (2)、a k (3) The three-axis angular velocities acquired by the gyroscope are respectively omega k (1)、ω k (2)、ω k (3) The condition detection method uses three conditions C 1 ，C 2 And C 3 To judge whether the feet of the person are in a static state;
the condition C 1 ，C 2 And C 3 ：
Condition C 1 As a magnitude of accelerationBetween two given thresholds are met:
condition C 2 For local acceleration variances larger than a given threshold,
the local acceleration variance is calculated in the manner that,
whereinIs the local average acceleration calculated ass is the window length of the mean;
condition C 3 For the size of the gyroscope measurementSatisfying below a given threshold:
the conditions are in a logical AND relationship, namely the condition detection result is C 1 &C 2 &C 3 Outputting logic '1' to represent a stop state and logic '0' to represent a walking state by a median filter with the window length of 11, counting as one step of walking when the condition detection result changes from the stop state to the walking state, wherein the total number of steps of walking on the current path is m (k), and the calculation formula of the linear length d (k) of the current walking is as follows by regarding the step length of the person walking as the fixed length l approximately:
d (k) = m (k) × l or d (k) = d (k-1) + l.
Furthermore, the sensing module also comprises a voltage detection chip and an electric meter dial and transmits the monitoring data to the information processing module.
The invention has the advantages and positive effects that: the invention is beneficial to realizing the optimal configuration of energy and power resources and improving the reliability and the operation management level of power supply of a power grid. The method lays a solid foundation for establishing a perfect smart power grid production chain, provides a platform for realizing energy optimization configuration in a larger range, and has important significance for promoting the upgrade and spanning of the power grid in China from the traditional power grid to the efficient, economic, clean and interactive modern power grid; the comprehensive coordination of all levels of new energy can be realized, the distribution autonomy and the coordination optimization operation among all levels can be realized, the development trend of new energy in the future is met, and the possibility of regional large-scale operation of new energy is provided; the use of the DSP makes the information processing module have strong digital signal processing capacity, simplifies the hardware structure of signal processing and improves the precision of the sensor.
Drawings
FIG. 1 is a schematic structural diagram of a multi-stage energy coordination control system according to an embodiment of the present invention;
in the figure: 1. a sensing module; 2. an information processing module; 3. a control and execution module; 4. a power distribution network; 5. A voltage detection chip; 6. a watt-hour meter dial; 7. a database chip.
Detailed Description
For further understanding of the contents, features and effects of the invention, the following examples are given in conjunction with the accompanying drawings.
The system of the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a multi-stage energy coordination control system provided in an embodiment of the present invention includes: the system comprises a sensing module 1, an information processing module 2, a control and execution module 3, a power distribution network 4, a voltage detection chip 5, an electric meter dial 6 and a database chip 7.
The sensing module 1 is used for carrying out a series of monitoring on a power distribution network and comprises a voltage detection chip and a watt-hour meter panel, monitoring voltage data and current data, and transmitting the monitoring data to the information processing module.
The information processing module 2 receives the data from the sensing module, analyzes and optimizes the data, and transmits instructions to the control and execution module.
And the control and execution module 3 adjusts and optimizes the power distribution network after receiving the instruction.
The sensing module 1 also comprises a voltage detection chip 5 and an electric meter dial 6, and transmits monitoring data to the information processing module.
The information processing module 2 adopts a DSP digital processor and comprises instruction sequence control, operation control, time control and data processing.
And the control and execution module 3 adjusts and optimizes the power distribution network after receiving the instruction.
The calculation method of the sensing module positioning node coordinate receiving module comprises the following steps:
firstly, selecting a differential correction point, determining a coordinate of a positioning intersection point and a plurality of positioning intersection points, and calculating the distance between the positioning intersection points; :
from d' i (i =0,1,2, …, n) selecting anchor node a with the smallest distance value 0 For the differential correction points, the 3 smallest distance values are then taken from the remaining distance values, these 3 being the distance values d' 1 、d′ 2 And d' 3 The coordinates of the corresponding anchor nodes are respectively A 1 x 1 ,y 1 、A 2 x 2 ,y 2 And A 3 x 3 ,y 3 Respectively with anchor nodes A i x i ,y i Is the center of a circle, d' i Making three positioning circles i for the radius, wherein i =1 , 2,3, the intersection conditions of the three positioning circles are 6 in total, two intersection points exist between the two circles, and the two intersection points are two equal real number intersection points, or two unequal real number intersection points, or two complex number intersection points; selecting one intersection point with a smaller distance from a coordinate of the center of the third positioning circle from two intersection points of the two positioning circles as a positioning intersection point to participate in positioning of the node to be positioned; determining the number m of three positioning intersection points and a plurality of positioning intersection points by using 3 positioning circles, wherein the coordinates of the positioning intersection points determined by the positioning circles 2 and 3 are A 'x' 1 ,y′ 1 And the coordinates of the positioning intersection points determined by the positioning circle 1 and the positioning circle 3 are B 'x' 2 ,y′ 2 The coordinates of the positioning intersection determined by the positioning circle 1 and the positioning circle 2 are C 'x' 3 ,y′ 3 Location of intersection A'
The distances from B ', B ' and C ', A ' and C ' are d 12 、d 23 、d 13 ：
Secondly, setting a threshold T, an individual difference coefficient correction coefficient omega, a parameter lambda (lambda is larger than 0), setting T =0.5, omega =1500 and lambda =0.001, and setting the distance d between the three positioning intersection points 12 ＜T、d 23 ＜T、d 13 If T is less than T, executing the fourth step;
thirdly, d 'is corrected according to the following adaptive distance correction formula' 1 、d′ 2 、d′ 3 Obtaining a corrected distance d 1 、 d 2 、d 3 ：
Wherein d is i Representing the node to be positioned and the anchor node A i Corrected distance between d 0i Representing a differential correction point A 0 And anchor node A i Actual distance between, d' 0i Representing a differential correction point A 0 And anchor node A i A measured distance therebetween, ω represents an individual difference coefficient correction coefficient, λ i Representing a directional correction factor, exp representing an exponential function;
according to the corrected distance d 1 、d 2 、d 3 Re-solving the distance d between the three corrected positioning intersections 12 、 d 23 、d 13 Returning to the second step;
fourthly, calculating the positioning coordinates O x of the node to be positioned according to the following formula 0 ,y 0 ：
Wherein alpha is 1 、 2 And alpha 3 each represents x' 1 、x′ 2 、x′ 3 Weight of (1), beta 1 、β 2 、β 3 Are respectively y' 1 、y′ 2 、 y′ 3 The weight of (a) is determined,
the data packet of the information processing module adopts a double-layer bloom filter;
the bloom filter adopts a bit array V with the length of m and k mutually independent Haxi function numbers h 1 、h 2 、…、h k (ii) a When the element s needs to be stored to the bloom filter, the setting h is calculated separately 1 (s)、 h 2 (s)、…、h k (s) and setting the bit value of the corresponding position in V to be '1'; when the element u needs to be judged whether to be in the bloom filter or not, checking the h-th element in the V 1 (u)、h 2 (u)、…、h k (u) whether the bit values of the positions are all 1, if all 1, the element u is in S with a high probability, and if not all 1, u is not in the bloom filter;
the signal processing method of the information processing module comprises the following steps: obtaining x 1 And x 2 I.e. the power ratio k of the interfering signal to the desired signal i (i =1,2), signal-to-noise ratioAnd the spatial correlation cos of the interference with the desired signal 2 Theta, and calculate x i Receive criteria of
Wherein i =1,2,for the purpose of the signal-to-noise ratio,for a value of i =1, the value of i =1,for i =2,E 2 ＝H 2 p 2 ，
The continuous data preprocessing method of the control and execution module specifically comprises the following steps:
step one, training subset selection and generation: a plurality of groups of observation data and information of the category are obtained to be used as a basis for establishing an algorithm model, each piece of information is called a training sample, and a plurality of training samples form a training set; if the training samples have k types, k is more than or equal to 2; then according to the training sample category, it is composed of two types of samplesA training subset, training subset X n Expressed as:
X n ＝{{x i }，{x j }}，
wherein, the first and the second end of the pipe are connected with each other,i, j ∈ {1,2, …, n } and i ≠ j, { x i And { x } j Respectively representing the set of ith and jth samples in the training set;
step two, a Fisher classifier group:
using training subsets X n Generating Fisher discriminant model y n ＝f n (x) The method mainly comprises the following steps:
1) Finding X n Mean value of two kinds of samples of middle i, jAndthe mean and formula are:
2) Solving an intra-class divergence matrix S wn ：
WhereinIs thatThe transposed matrix of (2).
3) Solving an inter-class divergence matrix S bn ：
4) Calculating the projection direction W n ：
W n ＝S wn -1 ·s bn
5) Computing Fisher discrimination threshold value w 0n ：
Then get the training subset X n The corresponding discrimination model is as follows: y is n ＝f n (x)＝W n ·x-w 0n ；
6) Solving Fisher discrimination models corresponding to each training subset according to the methods from step 1) to step 5) to generateAnd Fisher classifiers forming a Fisher classifier group, wherein the nth classifier can be expressed as:
step three, nonlinear continuous function mapping:
outputting y to Fisher classifier group by using nonlinear continuous function n Carry out mapping ifNon-linear mapping of the output of the nth Fisher classifierComprises the following steps:
wherein a (a)>, 0) is a relaxation variable introduced to enhance the generalization performance of the algorithm; if the Fisher classifier group consists of k classifiers, thenIs the result of data preprocessing.
The information processing module specifically acquires the coordinates of the electronic map of the unit path, and the method includes:
performing step counting operation by using an accelerometer and a gyroscope in the inertial navigation equipment, calculating the number of steps and the linear length of walking by a condition detection method, calculating the coordinate of an electronic map of each step, and recording the time t generated by the kth step coordinate s (k) K =1,2, L represents the total walking steps on the path, and the triaxial acceleration values collected by the accelerometer at the time k are a k (1)、a k (2)、a k (3) The three-axis angular velocities acquired by the gyroscope are respectively omega k (1)、ω k (2)、ω k (3) The condition detection method uses three conditions C 1 ，C 2 And C 3 To judge whether the feet of the person are in a static state;
the condition C 1 ，C 2 And C 3 ：
Condition C 1 As a magnitude of accelerationBetween two given thresholds are met:
condition C 2 For local acceleration variances larger than a given threshold,
the local acceleration variance is calculated in the manner that,
whereinIs the local average acceleration calculated ass is the window length of the mean;
condition C 3 For the magnitude of the gyroscope measurementSatisfying below a given threshold:
the conditions are in a logical AND relationship, namely the condition detection result is C 1 &C 2 &C 3 Outputting logic '1' to represent a stop state and logic '0' to represent a walking state by a median filter with a window length of 11 according to the condition detection result, counting as walking one step when the condition detection result changes from the stop state to the walking state, wherein the total number of steps of walking on the current path is m (k), the step length of walking of a person is approximately regarded as a fixed length l, and the length of a straight line of the current walking is calculatedd (k) is calculated by the formula:
d (k) = m (k) × l or d (k) = d (k-1) + l.
As shown in fig. 1, the sensing module 1 monitors various information of the power distribution network 4, including a voltage detection chip 5 and a watt-hour meter dial 6, and feeds back the information to the information processing module 2, the information processing module processes and optimizes the information after receiving the information from the sensing module, a database chip 7 is arranged in the information processing module for information matching, and then sends an instruction to the control and execution module 3, and the control and execution module 3 performs reasonable hierarchical regulation and control on the power distribution network 4 after receiving the instruction.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent variations and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (3)
1. A multi-stage energy coordination control system, comprising:
the sensing module is used for carrying out a series of monitoring on the power distribution network, comprises a voltage detection chip and an electric meter dial, and transmitting the monitored voltage data and current data to the information processing module;
the calculation method of the sensing module positioning node coordinate receiving module comprises the following steps:
firstly, selecting a differential correction point, determining a coordinate of a positioning intersection point and a plurality of positioning intersection points, and calculating the distance between the positioning intersection points; :
from d' i (i =0,2.., n) selecting anchor node a with the smallest distance value 0 For the differential correction point, the 3 smallest distance values are extracted from the remaining distance values, these 3 being the distance values d' 1 、d′ 2 And d' 3 The coordinates of the corresponding anchor nodes are respectively A 1 x 1 ,y 1 、A 2 x 2 ,y 2 And A 3 x 3 ,y 3 Respectively by anchor nodesA i x i ,y i Is the center of a circle, d' i Three positioning circles i are made for the radius, wherein i =1,2,3, 6 intersecting conditions of the three positioning circles are provided, two intersection points exist between the two circles, and the two intersection points are two equal real number intersection points, or two unequal real number intersection points, or two complex number intersection points; selecting one intersection point with smaller distance with the center coordinate of the third positioning circle from two intersection points of the two positioning circles as a positioning intersection point to participate in positioning of the node to be positioned; determining the number m of three positioning intersection points and a plurality of positioning intersection points by using 3 positioning circles, wherein the coordinates of the positioning intersection points determined by the positioning circles 2 and 3 are A 'x' 1 ,y′ 1 And the coordinates of the positioning intersection points determined by the positioning circle 1 and the positioning circle 3 are B 'x' 2 ,y′ 2 The coordinates of the positioning intersection determined by the positioning circle 1 and the positioning circle 2 are C 'x' 3 Y '3, the distances of the positioning intersection points A ' and B ', B ' and C ', A ' and C ' are d respectively 12 、d 23 、d 13 ：
Secondly, setting a threshold T, an individual difference coefficient correction coefficient omega, a parameter (lambda is larger than 0), setting T =0.5, omega =1500 and lambda =0.001, and setting the distance d between three positioning intersection points 12 ＜T、d 23 ＜T、d 13 If T is less than T, executing the fourth step;
thirdly, d 'is corrected according to the following self-adaptive distance correction formula' 1 、d′ 2 、d′ 3 Obtaining a corrected distance d 1 、d 2 、d 3 ：
Wherein d is i Represents the node to be positioned and the anchor node A i Corrected distance between d 0i Representing a differential correction point A 0 And anchor node A i Actual distance between, d' 0i Representing a differential correction point A 0 And anchor node A i A measured distance therebetween, ω represents an individual difference coefficient correction coefficient, λ i Representing the directional correction factor, exp · representing an exponential function;
according to the corrected distance d 1 、d 2 、d 3 Re-solving the distance d between the three corrected positioning intersections 12 、d 23 、d 13 Returning to the second step;
fourthly, calculating the positioning coordinates O x of the node to be positioned according to the following formula 0 ,y 0 ：
Wherein alpha is 1 、α 2 、α 3 Respectively represent x 1 、x′ 2 、x′ 3 Weight of (1), beta 1 、β 2 、β 3 Are respectively y' 1 、y′ 2 、y′ 3 The weight of (a) is determined,
the information processing module is used for receiving the data from the sensing module, analyzing and optimizing the data and transmitting an instruction to the control and execution module;
the data packet of the information processing module adopts a double-layer bloom filter;
the bloom filter adopts a bit array V with the length of m and k mutually independent Ha Xi functions h 1 、h 2 、…、h k (ii) a When the element s needs to be stored to the bloom filter, the setting h is calculated separately 1 (s)、h 2 (s)、…、h k (s) and setting the bit value of the corresponding position in V to be '1'; when the element u needs to be judged whether to be in the bloom filter or not, checking the h-th element in the V 1 (u)、h 2 (u)、…、h k (u) whether the bit values of the positions are all 1, if all 1, the element u is in S with a high probability, and if not all 1, u is not in the bloom filter;
the signal processing method of the information processing module comprises the following steps: obtaining x 1 And x 2 I.e. the power ratio k of the interfering signal to the desired signal i (i =1,2), signal-to-noise ratioAnd the spatial correlation cos of the interference with the desired signal 2 Theta, and calculate x i Receive criteria of
Wherein i =1,2,for the purpose of the signal-to-noise ratio,for i =1,E 1 ＝H 1 p 1 ，For i =2,E 2 ＝H 2 p 2 ，
The control and execution module is used for adjusting and optimizing the power distribution network after receiving the instruction;
the continuous data preprocessing method of the control and execution module specifically comprises the following steps:
step one, training subset selection and generation: a plurality of groups of observation data and information of the categories are obtained to be used as the basis for establishing an algorithm model, each piece of information is called a training sample, and a plurality of training samples form a training set; if the training samples have k types, k is more than or equal to 2; then according to the training sample category, it is composed of two types of samplesA training subset, training subset X n Expressed as:
X n ＝{{x i }，{x j }}，
wherein the content of the first and second substances,and i ≠ j, { x i And { x } j Denotes the set of class i and j samples in the training set, respectively;
step two, fisher classifier group:
using training subsets X n Generating Fisher discriminant model y n ＝f n (x) The method mainly comprises the following steps:
1) Finding X n Mean value of two kinds of samples of middle i, jAndthe mean and formula are:
2) Solving an intra-class divergence matrix S wn ：
WhereinIs thatThe transposed matrix of (2);
3) Solving an inter-class divergence matrix S bn ：
4) Calculating the projection direction W n ：
W n ＝S wn -1 ·S bn
5) Computing Fisher discrimination threshold value w 0n ：
Then get the training subset X n The corresponding discrimination model is as follows: y is n ＝f n (x)＝W n ·x-w 0n ；
6) Solving Fisher discriminant models corresponding to the training subsets according to the methods from step 1) to step 5) to generateAnd Fisher classifiers forming a Fisher classifier group, wherein the nth classifier can be expressed as:
step three, nonlinear continuous function mapping:
output y of Fisher classifier set by using nonlinear continuous function n Carry out mapping ifNon-linear mapping of the output of the nth Fisher classifierComprises the following steps:
wherein a (a)>, 0) is a relaxation variable introduced to enhance the generalization performance of the algorithm; if the Fisher classifier group consists of k classifiers, thenIs the result of data preprocessing.
2. The multi-stage energy coordination control system according to claim 1, wherein said information processing module employs a DSP digital processor, including command sequence control, operation control, time control, data processing;
the information processing module specifically acquires the electronic map coordinates of the unit path, and the method comprises the following steps:
performing step counting operation by using an accelerometer and a gyroscope in the inertial navigation equipment, calculating the number of steps and the linear length of walking by a condition detection method, calculating the coordinate of an electronic map of each step, and recording the time t generated by the kth step coordinate s (k) K =1,2, L represents the total number of walking steps on the path, and the triaxial acceleration values acquired by the accelerometer at the time k are a k (1)、a k (2)、a k (3) The three-axis angular velocities acquired by the gyroscope are respectively omega k (1)、ω k (2)、ω k (3) The condition detection method uses three conditions C 1 ，C 2 And C 3 To judge whether the feet of the person are in a static state;
the condition C 1 ，C 2 And C 3 ：
Condition C 1 As a magnitude of accelerationBetween two given thresholds are met:
condition C 2 For local acceleration variances larger than a given threshold,
the local acceleration variance is calculated in the manner that,
whereinIs the local average acceleration calculated ass is the window length of the mean;
condition C 3 For the magnitude of the gyroscope measurementBelow a given threshold is satisfied:
the conditions are in a logical AND relationship, namely the condition detection result is C 1 &C 2 &C 3 The result of the condition detection is passed through a median filter with a window length of 11, and a logic '1' is output to indicate a stop state, logic '0' represents a walking state, and the walking state is counted as one step when the walking state is changed from a stop state to a walking state, the total step number of the walking on the current path is m (k), the step length when the person walks is approximately regarded as a fixed length l, and the calculation formula of the linear length d (k) of the current walking is as follows:
d (k) = m (k) × l or d (k) = d (k-1) + l.
3. The multi-stage energy coordination control system according to claim 1, wherein said sensing module further comprises a voltage detection chip and an electric meter dial, and transmits the monitoring data to the information processing module.
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