CN117010573A - Intelligent power distribution energy-saving optimization method and system - Google Patents
Intelligent power distribution energy-saving optimization method and system Download PDFInfo
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Abstract
The application discloses an intelligent power distribution energy-saving optimization method and system, belonging to the field of power distribution systems, wherein the method comprises the following steps: the basic information of the electric equipment is called through the electricity file; constructing an electricity utilization curve of the electric equipment by carrying out electricity utilization analysis on the basic information; based on the electric equipment curve, positioning the energy-saving coordinates, and extracting the use amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates; optimizing the power distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining a first power distribution coefficient; reconstructing the power distribution network based on the first power distribution coefficient to obtain a reconstructed power distribution network; and intelligent power distribution is performed on the electric equipment through the reconstruction power distribution network. The application solves the technical problems of low efficiency and poor energy conservation of the power distribution system in the prior art, and achieves the technical effects of improving the operation efficiency of the power distribution system and realizing high energy conservation.
Description
Technical Field
The application relates to the field of power distribution systems, in particular to an intelligent power distribution energy saving optimization method and system.
Background
As the progress of social industrialization and towns increases, the demand for electricity increases. However, in existing power systems, the efficiency and energy saving potential of the power distribution link is still underutilized. Distribution system generally carries out distribution design and operation according to the nominal power of consumer, can't respond to the actual power consumption change of consumer in real time, leads to a large amount of electric power extravagant in distribution process.
Disclosure of Invention
The application provides an intelligent power distribution energy-saving optimization method and system, and aims to solve the technical problems of low efficiency and poor energy conservation of a power distribution system in the prior art.
In view of the above problems, the application provides an intelligent power distribution energy saving optimization method and system.
In a first aspect of the present disclosure, an intelligent power distribution energy saving optimization method is provided, which includes: the basic information of the electric equipment is called through the electricity file, wherein the basic information of the electric equipment comprises the usage amount information of the electric equipment and the power information of the electric equipment; the power utilization curve of the electric equipment is constructed by carrying out power utilization analysis on the using amount information of the electric equipment and the power information of the electric equipment; based on the electric equipment curve, positioning the energy-saving coordinates, and extracting the use amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates; optimizing the power distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining a first power distribution coefficient; reconstructing the power distribution network based on the first power distribution coefficient to obtain a reconstructed power distribution network; and intelligent power distribution is performed on the electric equipment through the reconstruction power distribution network.
In another aspect of the present disclosure, an intelligent power distribution energy saving optimization system is provided, the system comprising: the basic information acquisition module is used for acquiring basic information of the electric equipment through the electricity file, wherein the basic information of the electric equipment comprises the usage amount information of the electric equipment and the power information of the electric equipment; the power consumption curve construction module is used for constructing a power consumption curve of the electric equipment by carrying out power consumption analysis on the usage amount information of the electric equipment and the power information of the electric equipment; the electric equipment information module is used for positioning the energy-saving coordinates based on the electric equipment curves and extracting the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates; the first power distribution coefficient module is used for optimizing the power distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining the first power distribution coefficient; the reconfiguration power distribution network module is used for reconfiguring the power distribution network based on the first power distribution coefficient to obtain a reconfiguration power distribution network; and the intelligent power distribution module is used for intelligently distributing power to the electric equipment through the reconfiguration power distribution network.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the basic information of the electric equipment is called through the electricity file, and the basic information comprises the usage amount information of the electric equipment and the power information of the electric equipment, so that data support is provided for subsequent electricity analysis and power distribution optimization; carrying out electricity analysis on the usage amount information and the power information of the electric equipment, constructing an electricity consumption curve, analyzing the actual electricity consumption characteristics of the electric equipment, and revealing the electricity consumption rule of the electric equipment; based on the electric equipment curve, positioning the energy-saving coordinates, extracting the using amount information and the power information of the electric equipment of the energy-saving coordinates, and providing target parameters for optimizing the power distribution coefficient; optimizing the distribution coefficient, and determining a first distribution coefficient to fulfill the aim of optimizing the distribution coefficient; reconstructing the power distribution network according to the first power distribution coefficient to obtain a reconstructed power distribution network so as to support the realization of intelligent power distribution; by reconstructing the power distribution network to perform intelligent power distribution on the electric equipment, the technical scheme of the performances of the electric equipment and the power distribution network is brought into play to the maximum extent, the technical problems of low efficiency and poor energy conservation of the power distribution system in the prior art are solved, and the technical effects of improving the operation efficiency of the power distribution system and realizing high energy conservation are achieved.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
Fig. 1 is a schematic diagram of a possible flow chart of an intelligent power distribution energy saving optimization method according to an embodiment of the application.
Fig. 2 is a schematic flow chart of a possible output power distribution coefficient in an intelligent power distribution energy saving optimization method according to an embodiment of the application.
Fig. 3 is a schematic diagram of a possible flow of obtaining a reconstructed power distribution network in an intelligent power distribution energy saving optimization method according to an embodiment of the present application.
Fig. 4 is a schematic diagram of a possible structure of an intelligent power distribution energy saving optimization system according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a basic information calling module 11, an electricity utilization curve construction module 12, an electricity utilization equipment information module 13, a first power distribution coefficient module 14, a reconstruction power distribution network module 15 and an intelligent power distribution module 16.
Detailed Description
The technical scheme provided by the application has the following overall thought:
the embodiment of the application provides an intelligent power distribution energy-saving optimization method and system. By constructing the power utilization curve dynamic positioning energy-saving coordinates of the electric equipment in the power distribution network system, the power distribution coefficient is optimized in real time according to the energy-saving coordinates, and the power distribution network is reconfigured, so that the power distribution system can dynamically adjust the power distribution mode according to the actual power utilization of the electric equipment, and can operate efficiently and stably for a long time, and the optimal matching of energy conservation and power supply quality is achieved, thereby solving the technical problems of low efficiency and poor energy conservation of the existing power distribution system.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides an intelligent power distribution energy saving optimization method, which includes:
step S100: the method comprises the steps of calling basic information of electric equipment through an electricity file, wherein the basic information of the electric equipment comprises usage amount information of the electric equipment and power information of the electric equipment;
specifically, in order to realize intelligent power distribution energy saving optimization, basic information of electric equipment needs to be acquired first, and the information is stored in an electricity file. The electric equipment refers to various electric equipment participating in power distribution operation, such as air conditioners, illumination and the like. The electricity file can be deployed on a server serving as an intelligent power distribution control center, electricity data of all electric equipment is uploaded to the server in real time through a communication network, and the server collects and sorts the data of all the equipment to construct the electricity file of the electric power system.
The basic information of the electric equipment is called from the electricity file through a data processing technology, and the basic information comprises the usage amount information of the electric equipment and the power information of the electric equipment. The usage amount information of the electric equipment refers to the electricity consumption amount of the electric equipment in a certain period of time and is used for representing the electricity consumption condition of the electric equipment; the power information of the electric equipment refers to information such as instantaneous power and average power when the electric equipment operates, and the information is used for representing the operation strength of the electric equipment.
And acquiring electricity utilization information of each electric equipment participating in power distribution operation by calling data in the electricity utilization file, wherein the electricity utilization information comprises historical electricity utilization information and equipment operation power information, and providing basic data support for subsequent electricity utilization analysis, power distribution coefficient calculation and the like.
Step S200: the electricity utilization curve of the electric equipment is constructed by carrying out electricity utilization analysis on the usage amount information of the electric equipment and the power information of the electric equipment;
specifically, after the usage amount information and the power information of the electric equipment are obtained, firstly, the usage amount information and the power information are subjected to data cleaning, invalid and abnormal data points are removed, and the data quality is ensured; secondly, carrying out statistical analysis on the usage amount information and the power information respectively to obtain statistical characteristics of average power consumption/power, variation range, fluctuation frequency and the like of the equipment in different time periods, and primarily judging the power consumption rule of the equipment; then, carrying out association analysis on the two pieces of information to find out the rule of simultaneous change of the usage amount and the power, for example, whether the rising/falling of the power causes the increase/decrease of the usage amount, whether the changes have time correlation and the like, and revealing the electricity utilization characteristics in the equipment operation mechanism; then, according to the statistical characteristics and the associated analysis results, extracting important data points representing main electricity utilization characteristics of the equipment in the information, wherein the important data points can intuitively reflect electricity utilization rules of the equipment in the daily operation process; and then, performing curve fitting on the extracted data points, and determining a curve representing the electricity utilization rule, namely an electricity utilization curve.
And constructing an electricity utilization curve of the electric equipment by mining and analyzing the acquired electricity utilization data, and providing visual electricity utilization rule reference for subsequent optimization calculation.
Step S300: based on the electric equipment curve, positioning an energy-saving coordinate, and extracting the use amount information of electric equipment and the power information of the electric equipment of the energy-saving coordinate;
specifically, the shape characteristics of the curve of the electric equipment are analyzed, and the electricity consumption peak and the electricity consumption valley existing on the curve are judged, wherein the peak represents the state of larger electricity consumption amount/power of the equipment, and the valley represents the state of smaller electricity consumption amount/power of the equipment; setting a reference power consumption level by referring to the average power consumption or the rated power consumption of the equipment, comparing the power consumption of each state on the curve with the reference level, and preliminarily judging the low-valley state with smaller power consumption as an energy-saving coordinate; then, respectively calculating the power consumption optimization space in each 'valley' state, namely the power consumption which can be saved in the state, wherein the larger the optimization space is, the larger the energy saving potential of the state is, and the power consumption optimization space is more suitable for being used as an energy saving coordinate; then, judging whether the operation parameters corresponding to the 'valley' states are truly feasible or not according to the operation mechanism of the equipment, and judging whether the operation parameters are matched with the normal operation state of the equipment, for example, the operation time, the environment temperature and the like, wherein only the state with reasonable operation parameters can be used as the energy-saving coordinates; according to the judging result, 1-2 states with the most energy-saving potential and reasonable operation parameters are selected as energy-saving coordinates.
Specific data corresponding to the energy-saving coordinates on the electric equipment curves, such as average power consumption, power peak value, working time and the like in the corresponding time period, are read, and represent the power consumption level and operation parameters of the equipment in the energy-saving coordinate state, wherein the power consumption information and the power information of the electric equipment are the use amount information and the power information of the electric equipment of the energy-saving coordinates.
And identifying a relative energy-saving working state and corresponding parameters by judging the equipment power utilization curve, acquiring power utilization information in the state, and providing an information basis for calculating the power distribution coefficient.
Step S400: optimizing the distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining a first distribution coefficient;
specifically, the first power distribution coefficient refers to a parameter corresponding to the electric equipment in the determined energy-saving coordinate working state, and represents the load degree of the equipment on the power distribution network in the working state.
Firstly, collecting information of all electric equipment participating in power distribution, wherein the information comprises parameters such as average power consumption, average power, working time and the like of the equipment; secondly, constructing a mathematical model of the power distribution system according to the equipment information and the structural data of the power distribution network, wherein the model can simulate the load change condition of the power distribution system under different equipment working states; then, setting a network operation cost calculation function, recording data such as loss, electric quantity loss and the like in a power distribution system under different equipment working states, and converting the data into corresponding economic loss values; then, on the basis of a mathematical model, inputting information of each device in a determined energy-saving coordinate state, calculating the network operation cost in the state, and marking the network operation cost as a reference value; and modifying the information of the input equipment, changing the working state or parameters of the equipment, calculating the network operation cost under different situations, and searching for the situation with the lowest cost, wherein the parameter change amplitude of the equipment is the first power distribution coefficient.
According to the determined energy-saving coordinate state, a first power distribution coefficient capable of optimizing network loss is calculated according to specific information of a plurality of electric equipment, the basis of reconstructing the network to the energy-saving state is realized, and data support is provided for optimizing power distribution and energy saving.
Step S500: reconstructing the power distribution network based on the first power distribution coefficient to obtain a reconstructed power distribution network;
specifically, firstly, the topology structure, the equipment type and the operation parameters of the existing power distribution network are recorded in detail, a network model is constructed, and the model expresses the connection and control logic relation among all the equipment of the network; then, judging whether the current power distribution network can realize control and coordination under the corresponding equipment state according to the first power distribution coefficient requirement and model calculation, and if so, carrying out local updating on the network; if the basic network structure cannot be met, the basic network structure needs to be greatly modified; then, modifying the network structure, such as adjusting the access mode of the master-slave transformer substation, adding or reducing distribution lines and the like, so as to enhance the control flexibility and energy-saving potential of the network; meanwhile, intelligent electrical equipment in the network, such as monitoring equipment and power control equipment, is upgraded, the capability of implementing precise control in a complex network environment is improved, and hardware enhancement, software function improvement, new algorithm addition and the like can be included, so that reconstruction of the power distribution network according to the first power distribution coefficient is realized.
By reconstructing the power distribution network, each device in the power distribution network can operate in a working state corresponding to the first power distribution coefficient, so that the power consumption economy of each device is greatly improved, and high energy conservation is realized.
Step S600: and carrying out intelligent power distribution on the electric equipment through the reconstruction power distribution network.
Specifically, after the reconstructed power distribution network is obtained, intelligent power distribution is required to be carried out on each electric equipment through the network, so that dynamic monitoring and accurate control of the power utilization state of the equipment are realized, and the power supply efficiency of the system is optimized. The reconstructed power distribution network is a new network obtained through structural transformation and function upgrading, and has the condition and the capability of realizing the accurate power distribution control of equipment.
Firstly, an intelligent instrument is deployed to monitor each electric equipment connected to a network on line, and working state data of the equipment are obtained, such as actual electric quantity, working modes and the like. And secondly, collecting data uploaded by the intelligent instrument, and calculating optimal working parameters of each device, such as power regulation and control set values and the like, by utilizing an optimization algorithm in combination with user power consumption information and network operation states. And then, the calculation result is issued to an intelligent instrument or an equipment control terminal, and the equipment power consumption is directly regulated and controlled, so that the intelligent instrument or the equipment control terminal operates in an optimal state. Such as to power down the device, switch modes of operation of the device, etc. And then, repeating the steps of monitoring, calculating and controlling to realize the dynamic optimization of the power utilization state of each device, so that the power supply system can efficiently and stably run at the lowest cost.
The intelligent power distribution is carried out on the electric equipment through the reconstruction power distribution network, the real-time monitoring of the working state and the electric parameters of each electric equipment is realized, the operation of the equipment is accurately regulated and controlled according to the calculation result of the optimization algorithm, the equipment works in the optimal state, the system loss is reduced, and the purposes of improving the operation efficiency of the power distribution system and realizing high energy conservation are achieved.
Further, as shown in fig. 2, the embodiment of the present application further includes:
step S410: building a distribution coefficient evaluation model;
step S420: inputting the usage amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates into the power distribution coefficient evaluation model, and acquiring a power consumption coefficient, a power consumption coefficient and a power consumption load coefficient according to the power distribution coefficient evaluation model;
step S430: performing association influence analysis on the electricity consumption coefficient, the electricity consumption power coefficient and the electricity consumption load coefficient to obtain a first association influence coefficient, a second association influence coefficient and a third association influence coefficient;
the first correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, the second correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, and the third correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption load coefficient.
Step S440: and outputting the power distribution coefficient according to the power consumption coefficient, the power consumption load coefficient, the first association influence coefficient, the second association influence coefficient and the third association influence coefficient.
Specifically, by combining historical operation data of each device, a power distribution coefficient evaluation model is built by adopting algorithms such as a neural network and an optimization algorithm, and the power distribution coefficient evaluation model is used for calculating the influence degree of each electric device on the power distribution network under the determined working state, and evaluating the value of the parameter of each device in the network, which is adopted under the optimal power distribution scheme. The input of the model comprises information of each device such as electricity consumption, power, working time and the like, and the output is a device distribution coefficient.
And the power distribution coefficient evaluation model calculates a power consumption coefficient, a power consumption coefficient and a power consumption load coefficient according to the input using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinate, and represents the power consumption coefficient of each equipment in the power distribution network in the energy-saving state. And then, analyzing the interaction among the electricity consumption coefficient, the electricity consumption power coefficient and the electricity consumption load coefficient by adopting methods such as correlation analysis and the like to obtain a first correlation influence coefficient, a second correlation influence coefficient and a third correlation influence coefficient, and judging the correlation influence of different electricity consumption numbers of the equipment. The first correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, the second correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, and the third correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption load coefficient. The power distribution coefficient evaluation model can simulate the running condition of the network under any equipment state and forecast the influence result caused by the state change. Then, by changing the conditions of the state change of the equipment, such as increasing the power of a certain equipment by 20%, reducing the power utilization time of other equipment by 30%, and the like, the conditions of the state change are simulated, and the degree of interaction among the three coefficients is judged according to the change of the network operation parameters. For one coefficient, the influence change of the coefficient on the output values of the other two coefficients is simulated, and the degree of the influence change is the associated influence coefficient among the coefficients. Three associated influence coefficients are between-1 and 1, the absolute value of the three associated influence coefficients represents the sensitivity degree of parameter change to influence of other parameters, positive values indicate the change amount to enlarge the other parameters, and negative values indicate the other parameters to reduce.
According to the electricity consumption coefficient, the electricity consumption power coefficient, the electricity consumption load coefficient, the first association influence coefficient, the second association influence coefficient and the third association influence coefficient, an optimization algorithm is adopted, a group of equipment working state parameters capable of minimizing network loss is found out through iterative calculation, and the corresponding distribution coefficient is the target value for realizing optimal distribution, and the distribution coefficient is output.
By constructing a power distribution coefficient evaluation model considering multiple parameters of equipment and mutual influence thereof, decomposing and re-associating the information of each equipment, evaluating the comprehensive influence of the working state change of different equipment on the network, obtaining a group of equipment parameter values capable of optimizing the network operation, providing basis for subsequent network reconstruction and intelligent control, and being a key technical means for realizing efficient power distribution.
Further, the embodiment of the application further comprises:
step S450: acquiring the number of preset electric equipment;
step S460: according to the distribution coefficient evaluation model, the distribution coefficient adaptation is respectively carried out on the number of the preset electric equipment, and a plurality of distribution coefficients are obtained;
step S470: and optimizing the plurality of distribution coefficients by comparing the plurality of distribution coefficients, and outputting the first distribution coefficient.
Specifically, the preset number of electric equipment is the total number of equipment considered in network planning design, and equipment number reference is provided for obtaining the optimal first distribution coefficient. The method can be determined according to the current situation of the network and development planning, and is in the order of hundreds to tens of thousands of devices.
And selecting different equipment configuration schemes, such as different types, specifications, numbers and the like, in the range of the determined total number of the equipment, calculating the distribution coefficients of each scheme according to a distribution coefficient evaluation model, and obtaining a series of distribution coefficient values to obtain a plurality of distribution coefficients, wherein the distribution coefficients represent characteristic parameters of the optimal running state of the whole network under different equipment configuration schemes. The distribution coefficient adaptation refers to selecting a group of optimal distribution coefficients on the premise of meeting the constraint of the total quantity of the equipment, so that the network reaches the highest efficiency level under the configuration of the equipment.
After a plurality of distribution coefficients are obtained, a judgment model is established according to the technical and economic indexes, the priority order of each scheme is determined, then the weights of all judgment factors are determined by using a analytic hierarchy process, a fuzzy judgment process and the like, and a criterion system for scheme preference is established; and then, sequencing all schemes by applying a multiple decision algorithm such as a TOPSIS method, a VIKOR method and the like, and finding out an optimal scheme, wherein the corresponding power distribution coefficient is the first power distribution coefficient.
Through carrying out distribution coefficient adaptation to predetermining consumer quantity respectively, optimizing a plurality of distribution coefficients that obtain, realize the high-efficient intelligent screening of distribution coefficient. The method provides basis for network structure transformation and intelligent control of equipment, and improves the optimization efficiency of the power distribution system.
Further, the embodiment of the application further comprises:
step S431: the calculation formula of the distribution coefficient is as follows:
；
wherein,representing the electricity consumption coefficient of the ith electric equipment,/->Indicating the power factor of the i-th electric equipment,/->Indicating the power load factor of the i-th electric equipment,/->Representing the first associated influence coefficient,representing said second associated influence coefficient, +.>Representing the third switchAnd (5) linking the influence coefficients.
In particular, the method comprises the steps of,a preferred calculation formula for calculating the distribution coefficient, wherein +.>Representing the electricity consumption coefficient of the ith electric equipment, < ->Indicating the power factor of the i-th consumer,/-, for the electric power factor of the i-th consumer>Indicating the power load factor of the i-th consumer,/-, for example>Representing a first associated influence coefficient,/->Representing a second associated influence coefficient,/->Representing a third associated influence coefficient,/->The optimal working level of a certain device is reflected on the premise of meeting the electricity service, and the parameter setting when the device and the system reach the optimal coordination state is represented.
Three main coefficients、/>And->The magnitude of the parameter represents the difference of the influence degree on the system when the electrical parameters of the equipment are changed, and the interaction effect generated by the change of the parameters is positive and negative and largeThe final power distribution coefficient value is affected little. Wherein, when->、/>And->When the power distribution coefficient approaches zero, the influence among three main parameters is small, and the power distribution coefficient is mainly determined by a certain parameter; when the absolute values of the three correlation coefficients are larger, the strong interaction exists between the parameters, and the result of the influence of the change on the system needs to be comprehensively judged.
The formula comprehensively considers the degree of influence of three parameters of the power consumption coefficient, the power consumption coefficient and the power consumption load coefficient on a network and the interaction influence among the three parameters, and accurately calculates the optimal control parameters which are adopted by the equipment in a determined working state, thereby realizing efficient and stable power supply configuration.
Further, the embodiment of the application further comprises:
step S471: the calculation formula of the first power distribution coefficient is as follows:
；
wherein,and representing the first power distribution coefficient, wherein n is the number of the preset electric equipment, and n is a positive integer greater than 0.
In particular, the method comprises the steps of,a preferred calculation formula for calculating the first distribution coefficient, wherein +.>And the first power distribution coefficient is represented, n is the number of preset electric equipment, and n is a positive integer greater than 0. By comprehensively judging the distribution coefficient of each of a plurality of devices>A set of parameter settings is selected to achieve the best coordinated distribution coefficient delta for the entire network.
The formula adopts a multi-element scheme decision algorithm, and under the technical and economic constraints, each power distribution coefficient is calculatedAnd (3) performing comprehensive judgment, and selecting a group of optimal parameter setting schemes to generate a first power distribution coefficient delta. First power distribution coefficient->When the optimal power distribution scheme is realized, the target value adopted by the working control parameters of each device is represented, the degree of influence of a plurality of different devices on the system in the power utilization mode is comprehensively considered, and the mutual influence effect among the devices is considered, so that the network loss can be reduced to the maximum extent, the system efficiency is improved, and the requirement of power supply service is met.
The first distribution coefficient is accurately solved through a calculation formula, the basis of intelligent distribution is realized, data support is provided for intelligent distribution, and therefore distribution energy conservation is optimized.
Further, as shown in fig. 3, the embodiment of the present application further includes:
step S510: determining a power distribution network loss value based on the first power distribution coefficient;
step S520: presetting a power distribution objective function value, and constructing a power distribution fitness function based on the preset power distribution objective function value;
step S530: when the power distribution network loss value of the power distribution network is minimum and equal to the preset power distribution objective function value, the power distribution objective function value is calculated by the following formula:
；
wherein,for the fitness function, +.>For the distribution network loss value, +.>The fitness of the consumer in the power distribution network.
And reconstructing the power distribution network according to the adaptability of the electric equipment in the power distribution network to obtain the reconstructed power distribution network.
Specifically, according to the first power distribution coefficient, the working states and control parameter settings of all devices in the network are determined, and then various operation parameters of the network in the state, such as node voltage, line current, power generation amount, power consumption and the like, are obtained based on the working states and the control parameter settings. Calculating active loss and reactive loss in the network by using a line loss calculation formula and the like, and superposing the active loss and the reactive loss to be used as a power distribution network loss valueWherein the power distribution network loss value +.>Smaller indicates that the network is more efficient at operating at the first power distribution coefficient.
Presetting a power distribution objective function value according to technical feasibility and economic benefitThis value is the target constraint for network loss control. For the fitness function F, when the loss value +.>Less than a preset power distribution objective function value->Time->The other cases->。
According to the first power distribution coefficient, calculating the fitness of each device under the parameter setting by using the formula, sorting the fitness of all devices in the network, and selecting the device with lower fitness as a reconstruction object; for the reconstruction target apparatus, a reconstruction scheme thereof is determined. May include changing device types or specifications, adjusting device layout positions, parameter setting changes, etc.; and then, comprehensively judging each reconstruction scheme, selecting a group of schemes to form a reconstruction plan, and reconstructing the power distribution network according to the reconstruction plan to obtain a reconstructed power distribution network.
And judging whether the coefficient meets the optimal requirement or not through high-efficiency network reconstruction based on the first power distribution coefficient and comparing the objective function value with the actual loss, and adjusting a network structure accordingly to realize system efficiency improvement.
Further, the embodiment of the application further comprises:
step S710: setting a control feedback monitoring period of power distribution;
step S720: if the intelligent power distribution is performed on the electric equipment based on the control feedback monitoring period of the power distribution, the electric equipment is short-circuited, and short-circuit alarm information is generated;
step S730: and maintaining the electric equipment according to the short circuit alarm information, and updating the power distribution operation of the electric equipment according to the maintenance information.
Specifically, the power distribution control feedback monitoring period is set according to the equipment characteristics, the network scale and the like, and is a time interval for detecting the running state of the network and adjusting parameters. When setting, proper time length should be selected, if setting too long, fault alarm and response will be delayed, and too short will increase operation difficulty and resource consumption.
And monitoring all electric equipment in the network in real time to acquire parameters such as voltage, current, active power, reactive power and the like of the equipment. According to the monitoring data, judging whether the working state of each device is normal or not by utilizing fault criteria and a device fault knowledge base, and taking the current abrupt change, power abnormal change and the like as criteria of device short circuit. Once the parameters of the equipment are detected to be out of the normal range, judging that the equipment has short-circuit faults and generating short-circuit alarm information, wherein the information comprises fault equipment identification codes, fault occurrence time, fault parameter values, alarm levels and the like, and the alarm levels represent fault severity and are used for guiding the emergency degree of fault treatment of maintenance personnel. The short circuit alarm information is transmitted to the resident maintenance personnel terminal and the master control center through the communication system.
According to the short-circuit warning information, field maintenance personnel firstly conduct field inspection on fault equipment, confirm fault parameters and judge fault types. And secondly, determining a maintenance scheme according to the fault type, wherein the maintenance scheme comprises replacement of damaged equipment elements, internal debugging and calibration of equipment, upgrading and reconstruction of the equipment, replacement of the equipment and the like. Then, a maintenance scheme is implemented, and the overhaul or replacement work of the fault equipment is completed. After maintenance is finished, the operation parameters of the equipment are tested to confirm whether the operation parameters reach the standards, and if the faults are not completely removed, the equipment needs to be continuously tracked, checked and repaired until the equipment is restored to the normal operation state.
And according to the equipment or network structure change caused by maintenance, recalculating the matching relation between the equipment parameters and the first power distribution coefficient, and judging whether the first power distribution coefficient needs to be further optimized. And updating the related data of the equipment in the system model and the control system, and recovering the related data to be in a normal power supply state, so as to realize stable operation of the network after maintenance is finished.
Through the control feedback monitoring period based on the distribution, intelligent distribution is executed on the electric equipment, when the equipment is short-circuited, short-circuit warning information is generated, the electric equipment is maintained, and the distribution operation on the electric equipment is updated according to the maintenance information, so that the intelligent system can automatically judge the fault source, plan the maintenance scheme, control the maintenance device to implement work, recalculate the optimal network parameters after the maintenance is finished, complete the whole fault processing process, greatly reduce manual participation, and achieve the technical effects of improving the operation efficiency of the distribution system and realizing high energy conservation.
In summary, the intelligent power distribution energy-saving optimization method provided by the embodiment of the application has the following technical effects:
the basic information of the electric equipment is called through the electricity file, wherein the basic information of the electric equipment comprises the use amount information of the electric equipment and the power information of the electric equipment, and the basic parameters of the electric equipment are obtained to provide data support for subsequent electricity analysis and power distribution optimization; the electricity consumption analysis is carried out on the usage amount information of the electric equipment and the power information of the electric equipment, so that an electricity consumption curve of the electric equipment is constructed, the actual electricity consumption characteristics of the electric equipment are analyzed, the electricity consumption rule of the electric equipment is revealed, and a basis is provided for positioning energy-saving coordinates and optimizing power distribution; based on the electric equipment curve, positioning the energy-saving coordinates, extracting the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, finding the operating point of the efficient energy-saving operation of the electric equipment, and providing target parameters for optimizing the power distribution coefficient; optimizing a power distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining a first power distribution coefficient to optimize the power distribution coefficient so as to enable the power distribution coefficient to approach the energy-saving coordinates to the maximum extent, thereby realizing efficient operation of a power distribution network; reconstructing the power distribution network based on the first power distribution coefficient to obtain a reconstructed power distribution network, and reconstructing the power distribution network according to the optimized power distribution coefficient to support the realization of intelligent power distribution; the intelligent power distribution is carried out on the electric equipment through the reconfiguration power distribution network, so that the efficient power distribution on the electric equipment is realized, the performances of the electric equipment and the power distribution network are exerted to the maximum extent, and the technical effects of improving the operation efficiency of the power distribution system and realizing high energy conservation are achieved.
Example two
Based on the same inventive concept as the intelligent power distribution energy saving optimization method in the foregoing embodiment, as shown in fig. 4, an embodiment of the present application provides an intelligent power distribution energy saving optimization system, which includes:
the basic information acquisition module 11 is configured to acquire basic information of an electric device through an electricity file, where the basic information of the electric device includes usage information of the electric device and power information of the electric device;
the electricity consumption curve construction module 12 is used for constructing an electricity consumption curve of the electric equipment by carrying out electricity consumption analysis on the usage amount information of the electric equipment and the power information of the electric equipment;
the electric equipment information module 13 is used for positioning energy-saving coordinates based on the electric equipment curves and extracting the using amount information of electric equipment and the power information of the electric equipment of the energy-saving coordinates;
the first power distribution coefficient module 14 is configured to perform optimization of a power distribution coefficient according to usage amount information of the electric equipment and power information of the electric equipment in the energy-saving coordinate, and determine a first power distribution coefficient;
a reconfiguration power distribution network module 15, configured to reconfigure a power distribution network based on the first power distribution coefficient to obtain a reconfiguration power distribution network;
and the intelligent power distribution module 16 is used for intelligently distributing power to the electric equipment through the reconstruction power distribution network.
Further, the embodiment of the application further comprises:
the evaluation model building module is used for building a distribution coefficient evaluation model;
the electricity consumption coefficient acquisition module is used for inputting the usage amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates into the power distribution coefficient evaluation model, and acquiring an electricity consumption coefficient, an electricity consumption power coefficient and an electricity consumption load coefficient according to the power distribution coefficient evaluation model;
the influence coefficient acquisition module is used for carrying out association influence analysis on the electricity consumption coefficient, the electricity consumption power coefficient and the electricity consumption load coefficient to acquire a first association influence coefficient, a second association influence coefficient and a third association influence coefficient;
the first correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, the second correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, and the third correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption load coefficient.
And the power distribution coefficient acquisition module is used for outputting the power distribution coefficient according to the power consumption coefficient, the power consumption load coefficient, the first association influence coefficient, the second association influence coefficient and the third association influence coefficient.
Further, the embodiment of the application further comprises:
the equipment quantity acquisition module is used for acquiring the quantity of preset electric equipment;
the power distribution coefficient modules are used for respectively carrying out power distribution coefficient adaptation on the number of the preset electric equipment according to the power distribution coefficient evaluation model to obtain a plurality of power distribution coefficients;
and the distribution coefficient optimizing module is used for optimizing the plurality of distribution coefficients by comparing the distribution coefficients and outputting the first distribution coefficient.
Further, the embodiment of the application further comprises:
the distribution coefficient formula module is used for calculating the distribution coefficient as follows:
；
wherein,representing the electricity consumption coefficient of the ith electric equipment,/->Indicating the power factor of the i-th electric equipment,/->Indicating the power load factor of the i-th electric equipment,/->Representing the first associated influence coefficient,representing said second associated influence coefficient, +.>Representing the third associated influence coefficient.
Further, the embodiment of the application further comprises:
the first distribution coefficient formula module outputs a calculation formula of the first distribution coefficient as follows:
；
wherein,and representing the first power distribution coefficient, wherein n is the number of the preset electric equipment, and n is a positive integer greater than 0.
Further, the embodiment of the application further comprises:
a network loss value module that determines a power distribution network loss value based on the first power distribution coefficient;
the fitness function construction module is used for presetting a power distribution objective function value and constructing a power distribution fitness function based on the preset power distribution objective function value;
the power distribution network reconstruction module is used for passing the following formula when the power distribution network loss value of the power distribution network is minimum and equal to the preset power distribution objective function value:
；
wherein,for the fitness function, +.>For the distribution network loss value, +.>The fitness of the consumer in the power distribution network.
And reconstructing the power distribution network according to the adaptability of the electric equipment in the power distribution network to obtain the reconstructed power distribution network.
Further, the embodiment of the application further comprises:
the feedback detection period module is used for setting a control feedback monitoring period of power distribution;
the short circuit alarm information module is used for generating short circuit alarm information if the electric equipment is short-circuited when intelligent power distribution is performed on the electric equipment based on the control feedback monitoring period of the power distribution;
and the power distribution operation updating module is used for maintaining the electric equipment according to the short circuit alarm information and updating the power distribution operation of the electric equipment according to the maintenance information.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any method for implementing an embodiment of the present application, without unnecessary limitations.
Further, the first or second element may not only represent a sequential relationship, but may also represent a particular concept, and/or may be selected individually or in whole among a plurality of elements. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
Claims (8)
1. An intelligent power distribution energy saving optimization method, which is characterized by comprising the following steps:
the method comprises the steps of calling basic information of electric equipment through an electricity file, wherein the basic information of the electric equipment comprises usage amount information of the electric equipment and power information of the electric equipment;
the electricity utilization curve of the electric equipment is constructed by carrying out electricity utilization analysis on the usage amount information of the electric equipment and the power information of the electric equipment;
based on the electric equipment curve, positioning an energy-saving coordinate, and extracting the use amount information of electric equipment and the power information of the electric equipment of the energy-saving coordinate;
optimizing the distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining a first distribution coefficient;
reconstructing the power distribution network based on the first power distribution coefficient to obtain a reconstructed power distribution network;
and carrying out intelligent power distribution on the electric equipment through the reconstruction power distribution network.
2. The method of claim 1, wherein outputting the first power distribution coefficient, the method further comprising:
building a distribution coefficient evaluation model;
inputting the usage amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates into the power distribution coefficient evaluation model, and acquiring a power consumption coefficient, a power consumption coefficient and a power consumption load coefficient according to the power distribution coefficient evaluation model;
performing association influence analysis on the electricity consumption coefficient, the electricity consumption power coefficient and the electricity consumption load coefficient to obtain a first association influence coefficient, a second association influence coefficient and a third association influence coefficient;
the first correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, the second correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption coefficient, and the third correlation influence coefficient is the influence of the electricity consumption coefficient and the electricity consumption load coefficient on the electricity consumption load coefficient;
and outputting the power distribution coefficient according to the power consumption coefficient, the power consumption load coefficient, the first association influence coefficient, the second association influence coefficient and the third association influence coefficient.
3. The method of claim 2, wherein the method further comprises:
acquiring the number of preset electric equipment;
according to the distribution coefficient evaluation model, the distribution coefficient adaptation is respectively carried out on the number of the preset electric equipment, and a plurality of distribution coefficients are obtained;
and optimizing the plurality of distribution coefficients by comparing the plurality of distribution coefficients, and outputting the first distribution coefficient.
4. The method of claim 2, wherein the distribution coefficient is calculated as:
；
wherein,representing the electricity consumption coefficient of the ith electric equipment,/->Indicating the power factor of the i-th electric equipment,/->Indicating the power load factor of the i-th electric equipment,/->Representing said first associated influence coefficient, +.>Representing said second associated influence coefficient, +.>Representing the third associated influence coefficient.
5. The method of claim 3, wherein the calculation formula for outputting the first power distribution coefficient is as follows:
；
wherein,and representing the first power distribution coefficient, wherein n is the number of the preset electric equipment, and n is a positive integer greater than 0.
6. The method of claim 1, wherein the reconstructed power distribution network is obtained, the method further comprising:
determining a power distribution network loss value based on the first power distribution coefficient;
presetting a power distribution objective function value, and constructing a power distribution fitness function based on the preset power distribution objective function value;
when the power distribution network loss value of the power distribution network is minimum and equal to the preset power distribution objective function value, the power distribution objective function value is calculated by the following formula:
；
wherein,for the fitness function, +.>For the distribution network loss value, +.>The adaptability of the electric equipment in the power distribution network;
and reconstructing the power distribution network according to the adaptability of the electric equipment in the power distribution network to obtain the reconstructed power distribution network.
7. The method of claim 1, wherein the method further comprises:
setting a control feedback monitoring period of power distribution;
if the intelligent power distribution is performed on the electric equipment based on the control feedback monitoring period of the power distribution, the electric equipment is short-circuited, and short-circuit alarm information is generated;
and maintaining the electric equipment according to the short circuit alarm information, and updating the power distribution operation of the electric equipment according to the maintenance information.
8. An intelligent power distribution energy conservation optimization system, the system comprising:
the system comprises a basic information acquisition module, a power consumption file acquisition module and a power consumption management module, wherein the basic information acquisition module is used for acquiring basic information of electric equipment through the power consumption file, and the basic information of the electric equipment comprises usage amount information of the electric equipment and power information of the electric equipment;
the power consumption curve construction module is used for constructing a power consumption curve of the electric equipment by carrying out power consumption analysis on the usage amount information of the electric equipment and the power information of the electric equipment;
the electric equipment information module is used for positioning energy-saving coordinates based on the electric equipment curves and extracting the using amount information of electric equipment and the power information of the electric equipment of the energy-saving coordinates;
the first power distribution coefficient module is used for optimizing the power distribution coefficient according to the using amount information of the electric equipment and the power information of the electric equipment of the energy-saving coordinates, and determining a first power distribution coefficient;
the reconfiguration power distribution network module is used for reconfiguring a power distribution network based on the first power distribution coefficient to obtain a reconfiguration power distribution network;
the intelligent power distribution module is used for intelligently distributing power to the electric equipment through the reconfiguration power distribution network.
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