CN115049004A - Power distribution network line loss management aid decision-making system based on multi-source data fusion - Google Patents

Abstract

The invention relates to the technical field of distribution networks, and proposes an auxiliary decision-making system for distribution network line loss management based on multi-source data fusion, including a multi-source data fusion module, a line loss data verification module, a line loss data correction module, and a line loss calculation and analysis module. module, abnormal line loss diagnosis module and multi-level coordination loss reduction module. Through the above technical solutions, the problems of the prior art that the data quality of the line loss calculation of the distribution network is not high, the abnormal diagnosis is difficult, and the loss reduction method is single are solved.

Description

Auxiliary decision-making system for distribution network line loss management based on multi-source data fusion

technical field

The invention relates to the technical field of distribution network, in particular to an auxiliary decision-making system for distribution network line loss management based on multi-source data fusion.

Background technique

Line loss is the abbreviation of active power, reactive power and voltage loss generated in the process of power transmission. With the continuous improvement of the level of lean management of distribution network line loss, the existing distribution network data identification and repair, line loss calculation and analysis, abnormal diagnosis, loss reduction auxiliary decision-making, can no longer meet the requirements of line loss management. And the repair method is solidified, the diagnosis and judgment criteria for abnormal line loss are extensive, and the loss reduction decision is single, which cannot provide useful information for the power grid operation and management personnel to optimize the power grid operation mode and power grid structure. .

SUMMARY OF THE INVENTION

The invention proposes an auxiliary decision-making system for distribution network line loss management based on multi-source data fusion, which solves the problems of low quality of distribution network line loss calculation data, difficulty in abnormal diagnosis and single loss reduction method in the prior art.

The technical scheme of the present invention is as follows:

Auxiliary decision-making system for distribution network line loss management based on multi-source data fusion, including multi-source data fusion module, line loss data verification module, line loss data correction module, line loss calculation and analysis module, line loss abnormal diagnosis module and multi-level coordination loss reduction module,

The multi-source data fusion module is used to analyze and fuse the distribution network data of different departments and different systems;

The line loss data verification module is used to configure different verification types according to the data types of the distribution network, identify abnormal data, and classify and highlight abnormal data in the system;

The line loss data correction module is configured to configure different correction methods to correct the distribution network data according to the distribution network data type and the verification result;

The line loss calculation and analysis module is used to perform theoretical line loss calculation and analysis on the corrected distribution network data, and locate the weak link of the distribution network line loss;

The abnormal line loss diagnosis module is used for calculating and analyzing data according to the line loss, and judging whether the line loss of the distribution network is reasonable;

The multi-level coordination loss reduction module is used to provide auxiliary decision-making for loss reduction for the distribution network according to the abnormal diagnosis result of the line loss.

Further, the distribution network data includes equipment information, user information, operation information and topology information,

The equipment information includes main network equipment information, distribution network equipment information and low-voltage equipment information, the main network equipment information and distribution network equipment information are obtained from the PMS system, and the low-voltage equipment information is obtained from the marketing management system,

The user information includes customer information, and the customer information is obtained from the marketing management system,

The operation information includes electricity charge information, public transformer voltage and current capacity information, line voltage and current load information, telemetry, remote signaling and fault information. The power charge information is obtained from the marketing management system, and the public transformer voltage The current and electric quantity information is obtained from the electricity consumption information collection system, the line voltage and current load information is obtained from the electric energy collection system, and the remote measurement, remote signal quantity and fault information are obtained from the dispatching system,

The topology information includes the in-station topology relationship, the out-station topology relationship, the line-to-line topology relationship, and the low-voltage equipment topology. Obtain.

Further, the multi-source data fusion module includes,

Longitudinal parameter fusion, used to eliminate the parameter differences of the same department on the equipment of the power grid dispatching center of different systems;

Horizontal parameter fusion is used to eliminate the parameter differences in different departments of power grid dispatching center equipment of the same system.

Further, the line loss data verification module includes,

According to the data type of device information and user information, file information is classified, and different verification types are configured respectively, including non-null verification, data type verification, cross-service verification, validity verification, and identification of missing device information. , equipment information error, file information is incomplete and abnormal data, and the abnormal data is classified and highlighted in the system;

According to the type of operation information, the operation information is classified, and different verification types are configured, including non-null verification, data type verification, cross-service verification, false negative verification, validity verification, and cumulative checksum. Trend verification, and classify and highlight abnormal data in the system;

According to the type of topology information, the topology information is classified, and different verification types are configured, including non-null verification, data type verification, logical verification, and validity verification, to accurately locate the abnormal position of the device topology relationship, and graph the Display abnormal data.

Further, the line loss data correction module includes,

Based on the multi-source correlation of wiring files, conductor files, distribution and transformer files, station-line relationship, line-change relationship and station-household relationship, the file information is revised, including the distribution network data parsed by the GIS platform. The name is matched with the distribution network data of the PMS system;

Based on the multi-source connectivity correlation of the power consumption information acquisition system and the power energy acquisition system, combined with historical data, the operation information is corrected, including unified time scale repair, repair according to shielding value, repair according to the average value of adjacent points, and repair according to historical load curve , Repair according to the principle of node power balance, and repair the switching state according to the actual power flow of the power grid;

Based on the distribution network topology connection rules, the voltage correlation analysis method is used to analyze the correlation between the distribution transformer voltage and the wiring outlet voltage, and the voltage correlation between the distribution transformers to correct the topology information.

Further, the line loss calculation and analysis module includes:

Based on the revised distribution network data, the forward-backward power flow method and the equivalent resistance method are used to calculate the loss of the distribution network equipment, locate the abnormal equipment, and calculate the branch losses at all levels of the wiring according to the topology relationship of the equipment, and display it graphically. Calculate and analyze the results;

From the three aspects of calculation model, calculation result and calculation method, the line loss rate and theoretical line loss rate in the same period are compared and analyzed, and the difference of "double rate" is located.

Further, the abnormal line loss diagnosis module includes,

The theoretical line loss benchmark interval is established based on the energy efficiency guidelines, the line loss calculation interval model is established based on the interval arithmetic theory method, and the K-means mean clustering method is used to set the number of clusters to obtain different theoretical line loss scale reference values. The tree method establishes the interval model of big data line loss analysis;

According to the distribution network equipment information in the theoretical line loss benchmark interval model, line loss calculation interval model, and big data line loss analysis interval model, the first interval value, the second interval value and the third interval value are obtained respectively. ;

According to the first interval value, the second interval value and the third interval value, a reasonable interval of the line loss is obtained based on the principle of maximizing the contraction of the interval, and it is judged whether the line loss is reasonable.

Further, the multi-level coordination loss reduction module includes:

Using the active-reactive power optimization model, aiming at the minimum network loss, the minimum abandoned wind and light, and the minimum current unbalance, considering the active-reactive power coordination of the equipment, it provides a loss reduction optimization strategy;

Based on the perception results of the load demand and the development trend of controllable resources, on the medium and long-term time scale, for the transformation of the distribution network, build a medium and long-term line loss control model of the distribution network;

Aiming at the weak point of technical line loss, considering reactive power compensation, controllable load, energy storage device adjustment capability and economical operation of distribution transformers, build a "district-station-line-station" multi-layer linkage and same-level interactive distribution network for real-time energy saving Run the optimization model with loss reduction.

The working principle and beneficial effects of the present invention are:

The multi-source data fusion module of the present invention adopts a configurable and combined power distribution network line loss data verification method to realize more flexible, accurate and comprehensive verification of the power distribution network line loss data. The line loss data verification module uses the voltage correlation analysis method to verify the correctness of the topology relationship of the distribution network, so as to achieve accurate positioning of the abnormal topology relationship. The line loss data correction module corrects the bad data based on the identification results of bad data, and uses the multi-source connection correlation to correct the bad data, so as to effectively improve the data quality of the distribution network. The line loss calculation and analysis module realizes the multi-method calculation and analysis of the theoretical line loss of the distribution network based on the checked and corrected data, and accurately locates the weak link of the line loss of the distribution network. The abnormal line loss diagnosis module integrates three methods for judging the reasonable range of line loss, and is a tool to obtain the reasonable range of line loss based on the principle of maximizing the contraction of the range, and realizes real-time multi-dimensional rapid and accurate line loss diagnosis. The multi-level coordination loss reduction module builds a lean line loss multi-level coordination management mechanism for distribution network with active response, real-time optimization, dynamic adjustment, and regional feedback. It analyzes and judges the rationality of the structure and operation of the power grid. The power grid performs real-time optimization, dynamic adjustment, and feedback tracking to reduce the technical line loss within a reasonable range.

The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

Description of drawings

Fig. 1 is the framework schematic diagram of multi-source data fusion of the present invention;

FIG. 2 is a schematic diagram of the verification and correction of the 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 in a distribution network according to the present invention.

Detailed ways

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. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts are all related to the protection scope of the present invention.

Example 1

This embodiment proposes an auxiliary decision-making system for distribution network line loss management based on multi-source data fusion, including a multi-source data fusion module, a line loss data verification module, a line loss data correction module, a line loss calculation and analysis module, and a line loss abnormality diagnosis. modules and multi-stage coordinated loss reduction modules.

1. Multi-source data fusion module

Eliminate professional barriers, realize the deep integration of data at different levels and different professions, and provide data support for the auxiliary decision-making system for distribution network line loss management based on multi-source data fusion.

Two-level data fusion in the dispatch center. The system analyzes professional CIM files and uses the consistency of attributes such as unit name, voltage level, and equipment name to realize data fusion.

When performing grid parameter fusion, two steps of horizontal and vertical fusion are used to ensure the organic progress of data fusion. Longitudinal parameter fusion refers to eliminating the parameter differences of different levels of power grid dispatching center equipment in the same department. Departments and majors achieve vertical unification of parameters through vertical integration at different levels. Horizontal data fusion refers to the parameter fusion between different professional departments of the same level dispatch center. Since the first step of vertical parameter fusion has taken the Web Service interface to obtain power grid parameters from various sources, the heterogeneity of data parameters is eliminated, which ensures data fusion between different professional departments.

2. Line loss data verification module

Aiming at the problem that the traditional data verification method is solidified and the rules and types are inflexible, the system builds a verification rule library, intelligently configures the data verification types and rules according to the data type of the distribution network, and supports modification to realize the distribution network cable. Damaged data can be configured with combined verification to improve the flexibility and accuracy of data verification. As shown in Table 1:

Table 1 Data verification method

For the distribution network file information, the system classifies the data according to the file information type, and automatically configures different verification types and rules, including non-null verification, data type verification, cross-service verification, and validity verification. It can effectively identify abnormal data such as missing equipment parameters, incorrect equipment parameters, and incomplete files, and classify and highlight abnormal data.

For the operation information of the distribution network, the system classifies the data according to the type of operation information, and automatically configures different verification types and rules, including non-null verification, data type verification, cross-service verification, and validity verification. It can effectively identify abnormal data such as overcapacity data, jump data, missing data, straight line data, etc., and classify and highlight abnormal data in the system.

For the distribution network topology information, the system classifies the data according to the type of topology information, and automatically configures different verification types and rules, including non-null verification, data type, logic verification, validity verification, etc. Identify abnormal data such as device free, loop, open circuit, etc., accurately locate the abnormal position of topological relationship, display abnormal data graphically, and provide abnormal details.

3. Line loss data correction module

Based on the correlation of multi-source data, combined with the abnormal verification results of multi-source data, according to the abnormal type of distribution network line loss data, different correction methods are used to correct file information, topology information, and operation information respectively to improve data quality.

Based on the multi-source correlation of the data of the PMS system, the GIS platform, and the marketing business application system, the system revises the distribution network file information. For example, the equipment file information parsed by the GIS platform can be related to the PMS system through key attributes such as equipment ID and equipment name. The file information is matched to realize the intelligent correction of the distribution network file information.

The system is based on the multi-source connection correlation of the data of the power consumption information acquisition system and the power energy acquisition system, combined with historical data, and provides a variety of correction methods, including: unified time scale repair, repair according to shielding value, repair based on the average value of adjacent points, according to historical data Load curve repair, repair according to the principle of node power balance, repair switch status according to the actual power flow, etc., to realize the correction of distribution network operation information.

Based on the topological connection rules, the system adopts the voltage correlation analysis method, and realizes the intelligent correction of the topological relationship of the distribution network through the analysis of the correlation between the voltage of the distribution transformer and the voltage of the wiring outlet, and the analysis of the voltage correlation between the distribution transformers.

4. Line loss calculation and analysis module

Based on the check and repair results of the distribution network data, the system can calculate and analyze the theoretical line loss of the distribution network, and accurately locate the weak links of the distribution network line loss.

Based on the repaired data, the system provides theoretical line loss calculation functions for distribution networks including forward-returning power flow method, equivalent resistance method, etc. method comparison. The system can accurately calculate the loss of each distribution transformer and each section of wire, accurately locate abnormal equipment, count the losses of all branches of the wiring according to the topological connection relationship, and graphically display the calculation and analysis results.

The system provides a "dual rate" comparative analysis function between the line loss rate and the theoretical line loss rate in the same period, and makes a comparative analysis from the aspects of calculation model, calculation result, calculation method, etc., accurately locates the fundamental difference of "double rate", and helps improve the line loss management.

The system combines the energy efficiency guidelines of the distribution network to evaluate the health of the distribution network from the aspects of the distribution network structure, operation mode, operation, and basic attributes by formulating scoring standards and using a ten-point system. The higher the score, the better The better the health of the distribution network, the lower than 6 points is a key concern, assisting the development of energy saving and loss reduction.

5. Abnormal line loss diagnosis module

The system adopts three methods for diagnosing reasonable interval of line loss, and obtains the reasonable interval of line loss based on the principle of maximum shrinkage of the interval, so as to realize real-time multi-dimensional fast and accurate line loss diagnosis. Three diagnostic methods are: establishing theoretical line loss benchmark interval based on energy efficiency guidelines, line loss interval calculation based on interval arithmetic theory and power flow algorithm, and analysis method of theoretical line loss reasonable benchmark interval value based on clustering and decision tree.

Based on the energy efficiency guidelines, the theoretical line loss benchmark interval value is established, and combined with the empirical value, the preliminary line loss interval can be obtained. as shown in picture 2:

Table 2

Line loss interval calculation based on interval arithmetic theory and power flow algorithm. The system uses the interval arithmetic method to calculate the line loss interval value, and obtains a more objective and reasonable line loss interval than establishing the theoretical line loss benchmark interval value based on energy efficiency guidelines.

Analysis method of reasonable benchmark interval value of theoretical line loss based on clustering and decision tree. The system adopts the clustering method to remove artificial interference, and automatically classifies and divides the theoretical line loss value to obtain a reasonable number of reference clusters. The K-Means clustering method is used to manually set the number of clusters to obtain different theoretical line loss scale reference values and the distance between the sample and the cluster center. In the decision tree method, different power supply areas, different power supply and The influence range of the power supply radius, etc. on the theoretical line loss value. In this way, the interval value of the theoretical line loss in multi-dimension is obtained.

The distribution line first obtains the first interval value according to its area type and power supply radius, then obtains the second reasonable interval value according to the interval arithmetic method, then obtains the third interval value according to the big data analysis method, and finally obtains the interval value according to the interval The principle of maximum shrinkage is to obtain a reasonable range of line loss, and then judge whether the line loss of the wiring is reasonable.

6. Multi-level coordination loss reduction module

Based on the abnormal diagnosis results of line loss, the system adopts a multi-level coordination management mechanism to provide auxiliary decision-making for loss reduction of the distribution network, including: real-time optimization, dynamic adjustment, and feedback tracking.

Real-time optimization, using the active power-reactive power optimization model, with the smallest network loss, the smallest curtailment of wind and light, and the smallest current unbalance, considering the active power-reactive power coordination of various equipment, to realize the comprehensive line loss under new energy consumption Governance.

For the newly invested distributed power generation, fully consider the active power output and reactive power output of the distributed power generation, aiming at the smallest network loss, the smallest curtailment of wind and light, and the smallest current unbalance, and the active power-reactive power synergy, to the distributed power output, Planning the installation location and providing loss reduction optimization strategies;

For the connected distributed power sources, combined with the output characteristics of the distributed power sources, aiming at the smallest network loss, the smallest curtailment of wind and light, and the smallest current unbalance, the active power-reactive power is coordinated to adjust the distributed power output, providing Loss reduction optimization strategy;

Dynamic adjustment, on the basis of real-time optimization, based on the data situational awareness results, on the medium and long-term time scale, for the transformation of the distribution network, to build a medium and long-term line loss control model of the distribution network. The problems that cannot be solved quickly in real-time optimization are analyzed and corresponding optimization models are proposed, including equipment update, distributed power generation and distribution network reconstruction.

There are high-loss equipment and insufficient reactive power compensation in the distribution line, and there are distributed power sources. The system considers load fluctuations and combines the output characteristics of distributed power sources to formulate medium- and long-term loss reduction optimization strategies, so that equipment replacement, reactive power Loss reduction strategies such as gear adjustment are more based and guaranteed to avoid the results of poor results after adjustment.

Feedback tracking, aiming at the weak point of technical line loss, considering reactive power compensation, controllable load, energy storage device adjustment capability and economical operation of distribution transformers, to build a "district-station-line-station" multi-layer linkage and same-level interactive power distribution Network real-time energy saving and loss reduction operation optimization model to achieve efficient generation of loss reduction strategies. Then, the cost-benefit analysis model is used to calculate the cost and benefit of each scheme for various schemes of loss reduction, and the optimal loss reduction strategy is selected.

In an area, such as a substation, there may be many weak points of technical line loss within its power supply range. Loss reduction measures such as reactive power optimization, equipment replacement, distributed power output optimization, and load shedding are required. The system is considering Under the premise of safe and reliable regional power supply, a number of loss reduction strategies are automatically formulated with the goal of optimal regional line loss and minimum abandonment of wind and light, and then the investment return analysis of each loss reduction plan is carried out, including: investment rate of return, investment payback period , power saving, etc., and intelligently select the optimal strategy for regional loss reduction.

The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention. within.

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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