CN115049004A - Power distribution network line loss management aid decision-making system based on multi-source data fusion - Google Patents
Power distribution network line loss management aid decision-making system based on multi-source data fusion Download PDFInfo
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Abstract
The invention relates to the technical field of power distribution networks, and provides a power distribution network line loss management auxiliary decision system based on multi-source data fusion. By the technical scheme, the problems that the power distribution network line loss calculation data quality is low, abnormal diagnosis is difficult and the loss reduction method is single in the prior art are solved.
Description
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a power distribution network line loss management aid decision system based on multi-source data fusion.
Background
The line loss is short for active electric energy, reactive electric energy and voltage loss generated in the transmission process of electric energy. With the continuous improvement of the lean management level of the line loss of the power distribution network, the existing power distribution network data identification and restoration, line loss calculation analysis, abnormity diagnosis and loss reduction auxiliary decision-making cannot meet the requirements of line loss management, the data identification and restoration method is solidified, the line loss abnormity diagnosis judgment standard is extensive, the loss reduction decision-making is single, and beneficial information help cannot be provided for power grid operation managers to optimize the power grid operation mode and the power grid structure. .
Disclosure of Invention
The invention provides a power distribution network line loss management aid decision system based on multi-source data fusion, and solves the problems that in the prior art, the power distribution network line loss calculation data quality is low, abnormal diagnosis is difficult, and a loss reduction method is single.
The technical scheme of the invention is as follows:
a power distribution network line loss management aid decision-making system based on multi-source data fusion comprises a multi-source data fusion module, a line loss data check module, a line loss data correction module, a line loss calculation analysis module, a line loss abnormity diagnosis module and a multi-stage coordination loss reduction module,
the multi-source data fusion module is used for analyzing and fusing power distribution network data of different departments and different systems;
the line loss data checking module is used for configuring different checking types according to the data type of the power distribution network, identifying abnormal data and classifying highlight identification abnormal data in the system;
the line loss data correction module is used for configuring different correction methods to correct the power distribution network data according to the power distribution network data type and the verification result;
the line loss calculation and analysis module is used for performing theoretical line loss calculation and analysis on the corrected power distribution network data and positioning a weak link of line loss of the power distribution network;
the line loss abnormity diagnosis module is used for calculating and analyzing data according to line loss and judging whether the line loss of the power distribution network is reasonable or not;
and the multi-stage coordination loss reduction module is used for providing loss reduction auxiliary decision for the power distribution network according to the line loss abnormity diagnosis result.
Further, the power distribution network data comprises equipment information, user information, operation information and topology information,
the equipment information comprises main network equipment information, distribution network equipment information and low-voltage equipment information, the main network equipment information and the distribution network equipment information are obtained from a PMS (permanent magnet system), the low-voltage equipment information is obtained from a marketing management system,
the user information includes customer information, the customer information is acquired from a marketing management system,
the operation information comprises electric quantity and electric charge information, public and special transformation voltage and current information, line voltage and current load information, remote measurement, remote communication quantity and fault information, the electric quantity and electric charge information is obtained from a marketing management system, the public and special transformation voltage and current information is obtained from an electric energy acquisition system, the line voltage and current load information is obtained from an electric energy acquisition system, the remote measurement, the remote communication quantity and the fault information are obtained from a dispatching system,
the topology information comprises an intra-station topology relation, an extra-station topology relation, a line-to-line topology relation and a low-voltage equipment topology, and the intra-station topology relation, the extra-station topology relation, the line-to-line topology relation and the low-voltage equipment topology are acquired from a GIS platform and a marketing service application system.
Further, the multi-source data fusion module comprises,
the longitudinal parameter fusion is used for eliminating parameter differences of the same department on power grid dispatching center equipment of different systems;
and transverse parameter fusion is used for eliminating parameter differences of power grid dispatching center equipment of the same system in different departments.
Further, the line loss data checking module comprises,
classifying the archive information according to the data types of the equipment information and the user information, respectively configuring different verification types including non-empty verification, data type verification, cross-service verification, validity verification, identifying abnormal data with equipment information loss, equipment information error and incomplete archive information, and classifying highlight identification abnormal data in the system;
classifying the operation information according to the operation information type, respectively configuring different verification types including non-null verification, data type verification, cross-service verification, missing report verification, validity verification, cumulative verification and trend verification, and classifying highlight identification abnormal data in the system;
classifying the topology information according to the topology information type, configuring different check types including non-null check, data type check, logic check and validity check, accurately positioning the abnormal position of the topological relation of the equipment, and graphically displaying abnormal data.
Further, the line loss data modification module comprises,
based on the multi-source through correlation of the distribution file, the lead file, the distribution transformation file, the station line relation, the line transformation relation and the platform family relation, correcting file information, wherein power distribution network data analyzed by the GIS platform are matched with power distribution network data of a PMS through equipment ID and equipment name;
based on the multi-source through correlation of the electricity utilization information acquisition system and the electric energy acquisition system, correcting the operation information by combining historical data, wherein the correction comprises unified time scale repair, repair according to a shielding value, repair according to an average value of a near point, repair according to a historical load curve, repair according to a node power balance principle and repair of a switch state according to actual power flow of a power grid;
and analyzing the correlation between the voltage of the distribution transformer and the voltage of the outlet of the distribution line and analyzing the correlation between the voltages of the distribution transformers by adopting a voltage correlation analysis method based on the topological connection rule of the distribution network to correct topological information.
Further, the line loss calculation and analysis module comprises,
calculating by adopting a forward-backward flow-replacing method and an equivalent resistance method based on the corrected data of the distribution network to obtain the loss condition of the distribution network equipment, positioning abnormal equipment, counting the branch loss of each level of the distribution network according to the topological relation of the equipment, and graphically displaying the calculation analysis result;
comparing and analyzing the synchronous line loss rate and the theoretical line loss rate from three aspects of a calculation model, a calculation result and a calculation method, and positioning the difference of double rates.
Further, the line loss abnormality diagnosis module includes,
establishing a theoretical line loss benchmark interval based on energy efficiency guidance, establishing a line loss calculation interval model based on an interval arithmetic theory method, setting the clustering number to obtain different theoretical line loss scale reference values based on a K-means mean value clustering method, and establishing a big data line loss analysis interval model by a decision tree method;
respectively obtaining a first interval value, a second interval value and a third interval value according to the theoretical line loss benchmarking interval model, the line loss calculation interval model and the big data line loss analysis interval model of the distribution network equipment information;
and acquiring a reasonable line loss interval by taking the maximum interval contraction as a principle according to the first interval value, the second interval value and the third interval value, and judging whether the line loss is reasonable or not.
Further, the multi-level coordination loss reduction module comprises,
an active-reactive power optimization model is utilized, the purposes of minimum network loss, minimum wind and light abandonment and minimum current unbalance are taken as the targets, and the active-reactive power cooperation of equipment is considered to provide a loss reduction optimization strategy;
building a medium-and-long-term line loss control model of the power distribution network aiming at the transformation of the power distribution network on a medium-and-long-term time scale based on the sensing result of the load demand and the development situation of the controllable resources;
aiming at the technical line loss weak point, a power distribution network real-time energy-saving loss-reducing operation optimization model with multi-layer linkage and same-layer interaction of region-station-line-platform is constructed by considering reactive compensation, controllable load, energy storage device adjusting capacity and distribution transformation economic operation.
The working principle and the beneficial effects of the invention are as follows:
the multi-source data fusion module adopts a configurable combined type power distribution network line loss data verification method, and the power distribution network line loss data is verified more flexibly, accurately and comprehensively. And the line loss data checking module checks the correctness of the topological relation of the power distribution network by adopting a voltage correlation analysis method, so that the abnormal and accurate positioning of the topological relation is realized. The line loss data correction module corrects the bad data by utilizing the multi-source through correlation based on the bad data identification result, and the data quality of the power distribution network is practically improved. And the line loss calculation analysis module realizes the calculation and analysis of the theoretical line loss of the power distribution network by a multi-method based on the checked and corrected data, and accurately positions the weak link of the line loss of the power distribution network. The line loss abnormity diagnosis module integrates three line loss reasonable interval judgment methods, and a tool for acquiring the line loss reasonable interval by using the interval maximum contraction as a principle is used for realizing real-time multi-dimensional rapid and accurate line loss diagnosis. The multi-stage coordination loss reduction module constructs a power distribution network lean line loss multi-stage coordination management mechanism with active response, real-time optimization, dynamic adjustment and regional feedback, analyzes and judges the rationality of a power grid structure and operation, performs real-time optimization, dynamic adjustment and feedback tracking on the power distribution network from different time scales, and reduces the technical line loss within a more reasonable range.
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Drawings
FIG. 1 is a schematic diagram of the architecture for multi-source data fusion in accordance with the present invention;
FIG. 2 is a schematic diagram of verification and correction of line loss data of the power distribution network according to the present invention;
fig. 3 is a schematic diagram of a management mechanism for multi-level coordination loss reduction of a power distribution network according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any inventive step, are intended to be within the scope of the present invention.
Example 1
The embodiment provides a power distribution network line loss management aid decision-making system based on multi-source data fusion, which comprises a multi-source data fusion module, a line loss data verification module, a line loss data correction module, a line loss calculation analysis module, a line loss abnormity diagnosis module and a multi-stage coordination loss reduction module.
1. Multi-source data fusion module
Professional barriers are eliminated, different levels and different professional data depth fusion are achieved, and data support is provided for the power distribution network line loss management aid decision-making system based on multi-source data fusion.
And two-stage data fusion of the dispatching center, wherein the system analyzes the professional CIM file and realizes the data fusion by utilizing the consistency of attributes such as unit name, voltage level, equipment name and the like.
When the power grid parameter fusion is carried out, two steps of transverse and longitudinal fusion are adopted to ensure the organic implementation of data fusion. The longitudinal parameter fusion is to eliminate parameter differences of the same department specialty on different levels of power grid dispatching center equipment. And the department professions realize the longitudinal unification of the parameters through respective longitudinal fusion at different levels. The horizontal data fusion refers to the parameter fusion between different professional departments in the same-level scheduling center. As the Web Service interface is adopted to obtain the power grid parameters of each source in the first step of longitudinal parameter fusion, the heterogeneity of the data parameters is eliminated, and the data fusion among different professional departments is ensured.
2. Line loss data checking module
Aiming at the problem that the traditional data verification method is inflexible in solidification and modification of rules and types, the system intelligently configures the data verification types and rules according to the data types of the power distribution network by constructing a verification rule base and supports modification, so that the configurable combined verification of the line loss data of the power distribution network is realized, and the flexibility and the accuracy of data verification are improved. As shown in table 1:
TABLE 1 data verification method
Aiming at the archive information of the power distribution network, the system classifies the data according to the archive information type, automatically configures different verification types and rules respectively, comprises non-empty verification, data type verification, cross-service verification, validity verification and the like, effectively identifies abnormal data such as equipment parameter loss, equipment parameter errors and incomplete archives, and classifies the abnormal data with highlighted identification.
Aiming at the operation information of the power distribution network, the system classifies the data according to the operation information type, automatically configures different check types and rules respectively, comprises non-empty check, data type check, cross-service check, validity check and the like, effectively identifies the abnormal data such as the hyper-capacity data, the jump data, the missing data, the linear data and the like, and classifies the abnormal data with high brightness and identification in the system.
According to the topological information of the power distribution network, the system classifies the data according to the topological information type, different check types and rules are respectively and automatically configured, the check types include non-null check, data types, logic check, validity check and the like, abnormal data such as equipment freeness, loops, broken circuits and the like are effectively identified, the abnormal position of the topological relation is accurately positioned, the abnormal data is graphically displayed, and abnormal details are provided.
3. Line loss data correction module
Based on the through correlation of multi-source data, combining the abnormal checking result of the multi-source data, and according to the abnormal type of the line loss data of the power distribution network, different correction methods are adopted to respectively correct the archive information, the topology information and the operation information, so that the data quality is improved.
The system corrects the distribution network file information based on the multi-source through correlation of data of a PMS system, a GIS platform and a marketing service application system, for example, equipment file information analyzed by the GIS platform can be matched with the PMS system file information through key attributes such as equipment ID, equipment name and the like, and intelligent correction of the distribution network file information is realized.
The system provides a plurality of correction methods based on the multi-source through correlation of the data of the electricity utilization information acquisition system and the electric energy acquisition system and combined with historical data, and the correction methods comprise the following steps: the method comprises the steps of unified time scale repairing, repairing according to a shielding value, repairing according to an average value of a near point, repairing according to a historical load curve, repairing according to a node power balance principle, repairing a switch state according to actual power flow of a power grid and the like, and therefore the operation information of the power distribution network is corrected.
The system is based on a topological connection rule, adopts a voltage correlation analysis method, and realizes intelligent correction of the topological relation of the power distribution network by analyzing the correlation between the voltage of the distribution transformer and the voltage of the outlet of the distribution line and analyzing the correlation between the voltages of the distribution transformers.
4. Line loss calculation analysis module
Based on the power distribution network data checking and repairing results, the system can perform theoretical line loss calculation analysis on the power distribution network, and accurately position the weak link of the line loss of the power distribution network.
The system provides a power distribution network theoretical line loss calculation function comprising a forward-backward flow-replacing method, an equivalent resistance method and other methods based on the repaired data, and different calculation methods can be adopted according to data conditions, and multi-method comparison can also be carried out on calculation results. The system can accurately calculate the loss condition of each distribution transformer and each section of lead, accurately position abnormal equipment, count the branch loss of each section of wiring according to the topological connection relation, and graphically display the calculation and analysis results.
The system provides a double-rate comparison analysis function of the synchronous line loss rate and the theoretical line loss rate, comparison analysis is carried out on the aspects of a calculation model, a calculation result, a calculation mode and the like, the fundamental difference of double rates is accurately positioned, and assisted line loss management is improved.
The system combines the power distribution network energy efficiency guide rule, a grading standard is formulated, a complete system is adopted, the health condition of the power distribution network is evaluated from the aspects of a power distribution network grid structure, an operation mode, an operation condition, basic attributes and the like, the higher the score is, the better the health condition of the power distribution network is represented, the lower the score is, the higher the score is, the focus attention object is divided into 6, and the development of energy-saving and loss-reducing work is assisted.
5. Line loss abnormity diagnosis module
The system adopts three line loss reasonable interval diagnosis methods, obtains the line loss reasonable interval by taking the maximum contraction of the interval as a principle, and realizes real-time multi-dimensional rapid and accurate line loss diagnosis. The three diagnostic methods are: establishing a theoretical line loss benchmarking interval value based on an energy efficiency guide rule, calculating a line loss interval based on an interval arithmetic theory and a tidal current algorithm, and analyzing the theoretical line loss reasonable benchmarking interval value based on a clustering and decision tree.
And establishing a theoretical line loss benchmark interval value based on the energy efficiency guide rule, and combining an empirical value to obtain a preliminary line loss interval. As shown in fig. 2:
TABLE 2
And calculating the line loss interval based on the interval arithmetic theory and the load flow algorithm. The system calculates the line loss interval value by using an interval arithmetic theory method to obtain a line loss interval which is more objective and reasonable than the line loss interval value established based on the energy efficiency guidance rule.
A theoretical line loss reasonable benchmarking interval value analysis method based on clustering and decision trees. The system removes artificial interference by adopting a clustering method, and automatically classifies theoretical line loss values to obtain a reasonable reference clustering number. And (3) manually setting the clustering number to obtain different reference values of the theoretical line loss scale and the distance between the sample and the clustering center by adopting a K-Means mean clustering method, and considering the influence ranges of different power supply areas, different power supply amounts, power supply radiuses and the like on the theoretical line loss value by utilizing a decision tree method. Therefore, the interval value of the theoretical line loss under multiple dimensions is obtained.
The distribution line firstly obtains a first interval value according to the type of the area to which the distribution line belongs and the power supply radius, secondly obtains a second reasonable interval value according to an interval arithmetic method, thirdly obtains a third interval value according to a big data analysis method, and finally obtains a reasonable interval of line loss according to the principle of maximum interval shrinkage, thereby judging whether the line loss of the distribution line is reasonable or not.
6. Multi-stage coordination loss reduction module
Based on the line loss abnormity diagnosis result, the system provides a distribution network loss reduction auxiliary decision by adopting a multi-level coordination management mechanism, and the method comprises the following steps: real-time optimization, dynamic adjustment and feedback tracking.
And (3) optimizing in real time, and realizing comprehensive management of line loss under new energy consumption by using an active-reactive optimization model, considering active-reactive coordination of various devices with minimum network loss, minimum wind and light abandonment and minimum current imbalance degree.
For a newly launched distributed power supply, active power output and reactive power output of the distributed power supply are fully considered, active-reactive coordination is performed by aiming at the minimum network loss, the minimum wind and light abandonment and the minimum current imbalance, the output and installation positions of the distributed power supply are planned, and a loss reduction optimization strategy is provided;
for an accessed distributed power supply, the output of the distributed power supply is adjusted by combining the output characteristics of the distributed power supply and taking the minimum network loss, the minimum wind and light abandonment and the minimum current imbalance as targets through active-reactive coordination, and a loss reduction optimization strategy is provided;
and dynamically adjusting, and building a medium-and-long-term line loss control model of the power distribution network on the basis of real-time optimization and on the basis of data situation perception results and aiming at power distribution network transformation on a medium-and-long-term time scale. And analyzing the problems which cannot be quickly solved in the real-time optimization and correspondingly providing a corresponding optimization model, including the aspects of equipment updating, distributed power supply and power distribution network reconstruction and the like.
Distribution lines have the condition such as high loss equipment, reactive compensation are not enough to the hookup has distributed generator, and the load fluctuation condition is considered to the system, combines distributed generator characteristics of exerting oneself, makes the long-term reduction optimization strategy that decreases for the reduction strategies such as equipment replacement, reactive gear adjustment more have foundation and guarantee, avoids appearing the not good result of effect after the adjustment.
And feedback tracking, namely considering reactive compensation, controllable load, energy storage device adjusting capacity and distribution transformer economic operation aiming at the technical line loss weak point, and constructing a zone-station-line-platform multilayer linkage and same-layer interaction power distribution network real-time energy-saving loss-reducing operation optimization model to realize high-efficiency generation of a loss-reducing strategy. And then, calculating the cost and the income of each scheme aiming at multiple schemes for loss reduction by adopting a cost-benefit analysis model, and selecting an optimal loss reduction strategy.
In an area, for example, a substation, there may be a plurality of technical line loss weak points in its power supply range, loss reduction measures such as reactive power optimization, equipment replacement, distributed power output optimization, load change need to be performed, and under the premise that the safety and reliability of the area power supply are considered, the system automatically makes a plurality of loss reduction strategies with the objective of optimal area line loss, minimum wind and light abandonment, and then performs investment profit analysis on each loss reduction scheme, including: investment yield, investment recovery period, electricity saving amount and the like, and an optimal strategy for reducing loss of the region is intelligently selected.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The power distribution network line loss management aid decision-making system based on multi-source data fusion is characterized by comprising a multi-source data fusion module, a line loss data verification module, a line loss data correction module, a line loss calculation analysis module, a line loss abnormity diagnosis module and a multi-stage coordination loss reduction module,
the multi-source data fusion module is used for analyzing and fusing power distribution network data of different departments and different systems;
the line loss data checking module is used for configuring different checking types according to the data type of the power distribution network, identifying abnormal data and classifying highlight identification abnormal data in the system;
the line loss data correction module is used for configuring different correction methods to correct the power distribution network data according to the power distribution network data type and the verification result;
the line loss calculation and analysis module is used for performing theoretical line loss calculation and analysis on the corrected power distribution network data and positioning a weak link of line loss of the power distribution network;
the line loss abnormity diagnosis module is used for calculating and analyzing data according to line loss and judging whether the line loss of the power distribution network is reasonable or not;
and the multi-stage coordination loss reduction module is used for providing loss reduction auxiliary decision for the power distribution network according to the line loss abnormity diagnosis result.
2. The system of claim 1, wherein the distribution network data comprises equipment information, user information, operation information and topology information,
the device information includes major network device information, distribution network device information, and low voltage device information, the major network device information and the distribution network device information are obtained from a PMS system, the low voltage device information is obtained from a marketing management system,
the user information includes customer information, the customer information is obtained from a marketing management system,
the operation information comprises electric quantity and electric charge information, public and special transformation voltage and current information, line voltage and current load information, remote measurement, remote communication quantity and fault information, the electric quantity and electric charge information is obtained from a marketing management system, the public and special transformation voltage and current information is obtained from an electric energy acquisition system, the line voltage and current load information is obtained from an electric energy acquisition system, the remote measurement, the remote communication quantity and the fault information are obtained from a dispatching system,
the topology information comprises an intra-station topology relation, an extra-station topology relation, a line-to-line topology relation and a low-voltage equipment topology, and the intra-station topology relation, the extra-station topology relation, the line-to-line topology relation and the low-voltage equipment topology are acquired from a GIS platform and a marketing service application system.
3. The power distribution network line loss management aid decision system based on multi-source data fusion of claim 1, wherein the multi-source data fusion module comprises,
the vertical parameter fusion is used for eliminating parameter differences of the same department on power grid dispatching center equipment of different systems;
and transverse parameter fusion is used for eliminating parameter differences of power grid dispatching center equipment of the same system in different departments.
4. The power distribution network line loss management aid decision making system based on multi-source data fusion of claim 2, wherein the line loss data checking module comprises,
classifying the archive information according to the data types of the equipment information and the user information, respectively configuring different verification types including non-empty verification, data type verification, cross-service verification, validity verification, identifying abnormal data with equipment information loss, equipment information error and incomplete archive information, and classifying highlight identification abnormal data in the system;
classifying the operation information according to the operation information type, respectively configuring different verification types including non-null verification, data type verification, cross-service verification, missing report verification, validity verification, cumulative verification and trend verification, and classifying highlight identification abnormal data in the system;
classifying the topology information according to the topology information type, configuring different check types including non-null check, data type check, logic check and validity check, accurately positioning the abnormal position of the topological relation of the equipment, and graphically displaying abnormal data.
5. The power distribution network line loss management aid decision making system based on multi-source data fusion of claim 1, wherein the line loss data modification module comprises,
based on the multi-source through correlation of the distribution file, the lead file, the distribution transformation file, the station line relation, the line transformation relation and the platform family relation, correcting file information, wherein power distribution network data analyzed by the GIS platform are matched with power distribution network data of a PMS through equipment ID and equipment name;
based on the multi-source through correlation of the electricity utilization information acquisition system and the electric energy acquisition system, correcting the operation information by combining historical data, wherein the correction comprises unified time scale repair, repair according to a shielding value, repair according to an average value of a near point, repair according to a historical load curve, repair according to a node power balance principle and repair of a switch state according to actual power flow of a power grid;
and analyzing the correlation between the voltage of the distribution transformer and the voltage of the outlet of the distribution line and analyzing the correlation between the voltages of the distribution transformers by adopting a voltage correlation analysis method based on the topological connection rule of the distribution network to correct topological information.
6. The power distribution network line loss management aid decision-making system based on multi-source data fusion of claim 1, wherein the line loss calculation analysis module comprises,
calculating by adopting a forward-backward flow-replacing method and an equivalent resistance method based on the corrected data of the distribution network to obtain the loss condition of the distribution network equipment, positioning abnormal equipment, counting the branch loss of each level of the distribution network according to the topological relation of the equipment, and graphically displaying the calculation analysis result;
comparing and analyzing the synchronous line loss rate and the theoretical line loss rate from three aspects of a calculation model, a calculation result and a calculation method, and positioning the difference of double rates.
7. The power distribution network line loss management aid decision-making system based on multi-source data fusion of claim 1, wherein the line loss abnormity diagnosis module comprises,
establishing a theoretical line loss benchmark interval based on energy efficiency guidance, establishing a line loss calculation interval model based on an interval arithmetic theory method, setting the clustering number to obtain different theoretical line loss scale reference values based on a K-means mean value clustering method, and establishing a big data line loss analysis interval model by a decision tree method;
respectively obtaining a first interval value, a second interval value and a third interval value according to the theoretical line loss benchmarking interval model, the line loss calculation interval model and the big data line loss analysis interval model of the distribution network equipment information;
and acquiring a reasonable line loss interval by taking the maximum interval contraction as a principle according to the first interval value, the second interval value and the third interval value, and judging whether the line loss is reasonable or not.
8. The system for assisting decision-making for line loss management of power distribution network based on multi-source data fusion of claim 1, wherein the multi-stage coordination loss reduction module comprises,
an active-reactive power optimization model is utilized, the purposes of minimum network loss, minimum wind and light abandonment and minimum current unbalance are taken as the targets, and the active-reactive power cooperation of equipment is considered to provide a loss reduction optimization strategy;
building a medium-and-long-term line loss control model of the power distribution network aiming at the transformation of the power distribution network on a medium-and-long-term time scale based on the sensing result of the load demand and the development situation of the controllable resources;
aiming at the technical line loss weak point, a power distribution network real-time energy-saving loss-reducing operation optimization model with multi-layer linkage and same-layer interaction of region-station-line-platform is constructed by considering reactive compensation, controllable load, energy storage device adjusting capacity and distribution transformation economic operation.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116596348A (en) * | 2023-07-18 | 2023-08-15 | 山东盛德智能科技股份有限公司 | Platform area line loss analysis method based on minute-level acquisition |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103914741A (en) * | 2014-04-04 | 2014-07-09 | 上海君世电气科技有限公司 | Line loss intelligent evaluation and assistant decision-making system for power distribution network |
| CN108020752A (en) * | 2017-11-10 | 2018-05-11 | 国网浙江省电力公司电力科学研究院 | A kind of distribution line loss diagnostic method and system based on multi-source perforation correlation |
| CN110362894A (en) * | 2019-06-28 | 2019-10-22 | 贵州电网有限责任公司 | Distribution line, transformer synthesis decreasing loss and energy saving calculation analysis method and system |
| CN114358505A (en) * | 2021-12-09 | 2022-04-15 | 国网上海市电力公司 | Double-rate-improved line loss management method |
-
2022
- 2022-06-17 CN CN202210688924.XA patent/CN115049004B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103914741A (en) * | 2014-04-04 | 2014-07-09 | 上海君世电气科技有限公司 | Line loss intelligent evaluation and assistant decision-making system for power distribution network |
| CN108020752A (en) * | 2017-11-10 | 2018-05-11 | 国网浙江省电力公司电力科学研究院 | A kind of distribution line loss diagnostic method and system based on multi-source perforation correlation |
| CN110362894A (en) * | 2019-06-28 | 2019-10-22 | 贵州电网有限责任公司 | Distribution line, transformer synthesis decreasing loss and energy saving calculation analysis method and system |
| CN114358505A (en) * | 2021-12-09 | 2022-04-15 | 国网上海市电力公司 | Double-rate-improved line loss management method |
Non-Patent Citations (4)
| Title |
|---|
| 吴鸿亮等: "基于J2EE架构的线损理论计算与诊断分析系统开发与应用", 《电力系统保护与控制》 * |
| 张蓝宇等: "基于数据挖掘技术的台区线损智能诊断研究及应用", 《湖南电力》 * |
| 李正光等: "基于多维特征量融合的配电网拓扑异常溯源与应用模型研究", 《浙江电力》 * |
| 董瑞等: "输电网电能损耗在线评估和节能降损辅助决策技术研究与应用", 《华东电力》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116596348A (en) * | 2023-07-18 | 2023-08-15 | 山东盛德智能科技股份有限公司 | Platform area line loss analysis method based on minute-level acquisition |
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