CN111932406A - Method for evaluating load identification effect under superimposed operation condition - Google Patents
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Abstract
The invention relates to an evaluation method of load identification effect under a superposition operation condition, which comprises the following steps: 1. selecting a load identification product, 2 setting a standard value of the load identification product, 3, classifying electric appliance types, 4, calculating a weighting coefficient of the power consumption ratio of a single electric appliance, 5, calculating the accuracy of the power consumption of the single electric appliance, 6, calculating the overall accuracy under the condition of multi-electric appliance superposition operation, and 7, judging whether the identification effect of the overall accuracy under the condition of multi-electric appliance superposition operation meets the requirement or not. The invention adopts the error calculation principle, and is simple and easy to understand; in the calculation process, the indexes and the weighting quantity are flexibly allocated or deleted through coefficients, so that the accurate identification of the multi-electric appliance under the superposition operation condition is realized; in the identification effect evaluation process, a large number of load event waveforms are not needed, so that a large number of data acquisition is avoided, and the applicability and the practicability in occasions with high timeliness such as network access detection and acceptance detection are high.
Description
Technical Field
The invention relates to an evaluation method of load identification effect under a superposition operation condition, belonging to the technical field of intelligent power utilization.
Background
In recent years, with the development of smart power grids and the continuous improvement of the living standard of people, the demand of resident users on accurate and lean electricity utilization service is continuously increased. At present, a power grid company can only push daily total household power consumption information to a user, the power consumption condition of main electrical appliances is difficult to monitor in a household, and further refined energy utilization services such as household energy efficiency assessment, household appliance working condition acquisition and the like cannot be provided for the user.
The non-intrusive load identification technology is a novel advanced measurement technology, the content and the state of each electric appliance load are sensed by collecting the real-time information of the total current and the voltage of an input bus end of a power load and utilizing measurement data and an intelligent measurement method, meanwhile, the load does not need to enter the indoor of a resident user, construction and deployment are convenient, and the asset attribution is clear. At present, various detection methods and detection system platforms for verification of non-intrusive load identification technical effects have been developed, but the evaluation methods of the load identification effects have large differences, especially the tendentiousness differences of each effect index, and then the evaluation of the load identification technical effects becomes one of the industrial key works so as to facilitate the selection of load identification products.
The analysis effect evaluation difference mainly comes from the difference of a load identification algorithm principle, a load object and a load identification application scene, and the analysis effect evaluation method is used for the identification effect evaluation method aiming at the gap start-stop electric heating load working condition. From the aspects of power grid supply and demand intercommunication application and high-energy-consumption electric appliance fine-grained power consumption behavior identification application in an electricity consumption scene of residents, a power grid company pays attention to the identification capability of high-energy-consumption adjustable controllable loads, residents pay attention to the fine-grained power consumption behaviors of electric appliances with high power consumption proportion in a home, evaluation in the working condition of overlapping operation loads of a plurality of electric appliances in the industry is mostly carried out in a mode of calculating the effect of each electric appliance and then weighting the effect, but the effect evaluation method cannot truly feed back the application requirements in the application scene.
Disclosure of Invention
In order to solve the technical problems, the invention provides an evaluation method for load identification effect under a superposition operation condition, which has the following specific technical scheme:
the method for evaluating the load identification effect under the superposition operation working condition comprises the following steps:
the method comprises the following steps: selecting a load identification product: selecting a load identification product to carry out load identification detection under the condition of multi-electric appliance superposition operation load;
step two: setting a standard value of a load identification product: setting the standard value of the identification effect of the load identification type product as S according to the actual situation;
step three: electric appliance category interval division: the electric appliance category interval is divided into a correct concrete category, a correct large category, an untrusted category, an unknown category, an empty category and an error concrete category;
step four: calculating a weighting coefficient of the power consumption ratio of a single electric appliance:
a. calculating a weighting coefficient of the ratio of the power consumption of the electric appliances of the correct specific category to the power consumption of the electric appliances of the correct general category:
in the formula
The electric quantity of the used electric appliances is the sub-item electric quantity,
the real total power consumption of the used electric appliances under the superposition operation condition;
b. calculating the weighting coefficients of the electric appliance power consumption ratios of the untrusted class, the unknown class, the empty class and the specific error class:
in the formula
The identification subentry electric quantity of the electric appliance is, and alpha is an electric appliance category accuracy coefficient;
step five: calculating the power consumption accuracy of a single electric appliance:
step six: and (3) calculating the overall accuracy under the multi-electric-appliance superposition operation condition:
step seven: judging whether the identification effect of the overall accuracy under the superposition operation condition of the multiple electric appliances meets the requirements or not: when in use
<S, the load identification effect of the current load identification product is not ideal and does not accord with the use standard; when in use
And when the load is more than or equal to S, the load identification effect of the current load identification product is good and meets the use standard.
Further, the electrical appliance category accuracy coefficient α is determined according to the category interval to which the selected electrical appliance belongs, and the value range of the electrical appliance category accuracy coefficient α is [ -1,1 ].
Further, the electric appliance type interval is divided into a correct specific type, a correct large type, an untrusted type, an unknown type, a null type and an incorrect specific type, and the values of the corresponding electric appliance type accuracy coefficients alpha are 1, 0.8, 0.5, 0.2, 0 and-1 in sequence.
Further, the electric quantity of the electric appliance is collected and calculated according to the minute level.
The invention has the beneficial effects that:
the invention adopts the error calculation principle, and is simple and easy to understand; in the calculation process, the indexes and the weighting quantity are flexibly allocated or deleted through coefficients, so that the accurate identification of the multi-electric appliance under the superposition operation condition is realized; in the identification effect evaluation process, a large number of load event waveforms are not needed, so that a large number of data acquisition is avoided, and the applicability and the practicability in occasions with high timeliness such as network access detection and acceptance detection are high.
Drawings
FIG. 1 is a schematic flow diagram of the present invention.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
As shown in fig. 1, the method for evaluating the load identification effect under the superimposed operation condition of the present invention includes the following steps:
the method comprises the following steps: selecting a load identification product: selecting a load identification product to carry out load identification detection under the condition of multi-electric appliance superposition operation load;
step two: setting a standard value of a load identification product: setting the standard value of the identification effect of the load identification type product as S according to the actual situation;
step three: electric appliance category interval division: the electric appliance category interval is divided into a correct concrete category, a correct large category, an untrusted category, an unknown category, an empty category and an error concrete category;
step four: calculating a weighting coefficient of the power consumption ratio of a single electric appliance:
a. calculating a weighting coefficient of the ratio of the power consumption of the electric appliances of the correct specific category to the power consumption of the electric appliances of the correct general category:
in the formula
The electric quantity of the used electric appliances is the sub-item electric quantity,
for the real total power consumption of all the electric appliances under the superposition operation condition；
b. Calculating the weighting coefficients of the electric appliance power consumption ratios of the untrusted class, the unknown class, the empty class and the specific error class:
in the formula
The identification subentry electric quantity of the electric appliance is, and alpha is an electric appliance category accuracy coefficient;
step five: calculating the power consumption accuracy of a single electric appliance:
step six: and (3) calculating the overall accuracy under the multi-electric-appliance superposition operation condition:
step seven: judging whether the identification effect of the overall accuracy under the superposition operation condition of the multiple electric appliances meets the requirements or not: when in use
<S, the load identification effect of the current load identification product is not ideal and does not accord with the use standard; when in use
And when the load is more than or equal to S, the load identification effect of the current load identification product is good and meets the use standard.
The first embodiment is as follows:
as shown in the table 1 below, the following examples,
TABLE 1
The electric appliance category intervals in table 1 are divided into correct specific categories, correct large categories, untrusted categories, unknown categories, empty categories, and incorrect specific categories, the value range of the electric appliance category accuracy coefficient α is [ -1,1], and the values of the corresponding electric appliance category accuracy coefficients α are 1, 0.8, 0.5, 0.2, 0, and-1 in sequence. And setting the standard value of the identification effect of the load identification type product to be S =80 according to the actual situation.
As shown in the table 2 below, the following examples,
TABLE 2
The load identification effect under the superposition operation condition of the fixed-frequency air conditioner and the electric cooker is taken as an example. Firstly, the identification result of each type of electric appliance is calculated by a method for calculating the accuracy of the power consumption of a single electric appliance, namely, the numerical values in the table 2 corresponding to the fixed-frequency air conditioner and the electric cooker are substituted into a formula (3),
namely:
calculated to obtain
，
. When the matched real electric appliances can not be determined by the electric appliances such as the untrusted type, the unknown type, the empty type and the error, the untrusted type, the unknown type, the empty type and the error are utilizedThe method for calculating the weighting coefficient of the specific type of electric appliance power consumption ratio calculates the identification results of the electric appliances of the uncertain type, the unknown type, the empty type and the wrong specific type, namely, the numerical values in the corresponding table 2 of the fixed-frequency air conditioner and the electric cooker are substituted into the formula (2),
namely:
calculated to obtain
，
，
. Finally, the electric appliances in various intervals of the electric appliance interval are integrated, the overall accuracy calculation under the condition of multi-electric appliance superposition operation is carried out, namely, the numerical values in the table 2 corresponding to the fixed-frequency air conditioner and the electric cooker are substituted into the formula (4) by the numerical values obtained by the calculation of the formulas (2) and (3),
namely:
since the standard value of the recognition effect of the load recognition type product is set to S =80 according to the actual situation,
， 
and the load identification effect of the current load identification type product is good and meets the use standard.
The second embodiment is as follows:
as shown in the table 3 below, the following examples,
TABLE 3
The load identification effect under the condition of the superposition operation of the variable frequency air conditioner and the electric kettle is taken as an example. Firstly, the identification result of each type of electric appliance is calculated by a method for calculating the accuracy of the power consumption of a single electric appliance, namely, the numerical values in a table 2 corresponding to the variable-frequency air conditioner and the electric kettle are substituted into a formula (3),
namely:
calculated to obtain
，
. When the matched real electric appliances cannot be determined by the electric appliances such as the untrusted electric appliances, the unknown electric appliances, the empty electric appliances and the wrong specific electric appliances, the identification results of the electric appliances of the untrusted electric appliances, the unknown electric appliances, the empty electric appliances and the wrong specific electric appliances are calculated by using a weighting coefficient calculation method of the power consumption ratio of the electric appliances of the untrusted electric appliances, the unknown electric appliances, the empty electric appliances and the wrong specific electric appliances, namely, the numerical values in the corresponding table 2 of the variable frequency air conditioner and the electric kettle are substituted into the formula (2,
namely:
calculated to obtain
. Finally, the electric appliances in various intervals of the electric appliance interval are integrated, the overall accuracy calculation is carried out under the working condition of multi-electric appliance superposition operation, namely, the numerical values in the table 3 corresponding to the variable frequency air conditioner and the electric kettle are substituted into the numerical values obtained by the calculation of the formulas (2) and (3) into the formula (4),
namely:
since the standard value of the recognition effect of the load recognition type product is set to S =80 according to the actual situation,
， 
<and S, the load identification effect of the current load identification type product does not reach the standard and does not meet the use standard.
The invention adopts the error calculation principle, and is simple and easy to understand; in the calculation process, the indexes and the weighting quantity are flexibly allocated or deleted through coefficients, so that the accurate identification of the multi-electric appliance under the superposition operation condition is realized; in the identification effect evaluation process, a large number of load event waveforms are not needed, so that a large number of data acquisition is avoided, and the applicability and the practicability in occasions with high timeliness such as network access detection and acceptance detection are high.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (4)
1. A method for evaluating load identification effect under a superposition operation condition is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: selecting a load identification product: selecting a load identification product to carry out load identification detection under the condition of multi-electric appliance superposition operation load;
step two: setting a standard value of a load identification product: setting the standard value of the identification effect of the load identification type product as S according to the actual situation;
step three: electric appliance category interval division: the electric appliance category interval is divided into a correct concrete category, a correct large category, an untrusted category, an unknown category, an empty category and an error concrete category;
step four: calculating a weighting coefficient of the power consumption ratio of a single electric appliance:
a. calculating a weighting coefficient of the ratio of the power consumption of the electric appliances of the correct specific category to the power consumption of the electric appliances of the correct general category:
in the formula
The electric quantity of the used electric appliances is the sub-item electric quantity,
the real total power consumption of the used electric appliances under the superposition operation condition;
b. calculating the weighting coefficients of the electric appliance power consumption ratios of the untrusted class, the unknown class, the empty class and the specific error class:
in the formula
The identification subentry electric quantity of the electric appliance is, and alpha is an electric appliance category accuracy coefficient;
step five: calculating the power consumption accuracy of a single electric appliance:
step six: and (3) calculating the overall accuracy under the multi-electric-appliance superposition operation condition:
step seven: judging whether the identification effect of the overall accuracy under the superposition operation condition of the multiple electric appliances meets the requirements or not: when in use
<S, the load identification effect of the current load identification product is not ideal and does not accord with the use standard; when in use
And when the load is more than or equal to S, the load identification effect of the current load identification product is good and meets the use standard.
2. The method for evaluating the load identification effect under the superimposed operation condition according to claim 1, characterized in that: the electric appliance category accuracy coefficient alpha is determined according to the category interval to which the selected electric appliance belongs, and the value range of the electric appliance category accuracy coefficient alpha is [ -1,1 ].
3. The method for evaluating the load identification effect under the superimposed operation condition according to claim 2, characterized in that: the electric appliance type interval is divided into a correct specific type, a correct large type, an untrusted type, an unknown type, an empty type and an incorrect specific type, and the values of the accuracy coefficients alpha of the corresponding electric appliance types are 1, 0.8, 0.5, 0.2, 0 and-1 in sequence.
4. The method for evaluating the load identification effect under the superimposed operation condition according to claim 1, characterized in that: the electric quantity of the electric appliance is collected and calculated according to the minute level.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523134A (en) * | 2018-10-29 | 2019-03-26 | 东北电力大学 | A kind of distributing electric heating load time-shift capability quantitative evaluating method and its modeling based on measured data |
| CN110033395A (en) * | 2019-04-24 | 2019-07-19 | 江苏智臻能源科技有限公司 | Non-intruding terminal identification capability test cases base construction method and analog detection platform |
| US20200049745A1 (en) * | 2014-09-30 | 2020-02-13 | Battelle Memorial Institute | Method of evaluating change in energy consumption due to volt var optimization |
| CN111007450A (en) * | 2019-12-06 | 2020-04-14 | 江苏智臻能源科技有限公司 | Method for detecting result reliability of load identification equipment |
| CN111551889A (en) * | 2020-04-29 | 2020-08-18 | 国网重庆市电力公司营销服务中心 | Load identification electric energy meter detection platform |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200049745A1 (en) * | 2014-09-30 | 2020-02-13 | Battelle Memorial Institute | Method of evaluating change in energy consumption due to volt var optimization |
| CN109523134A (en) * | 2018-10-29 | 2019-03-26 | 东北电力大学 | A kind of distributing electric heating load time-shift capability quantitative evaluating method and its modeling based on measured data |
| CN110033395A (en) * | 2019-04-24 | 2019-07-19 | 江苏智臻能源科技有限公司 | Non-intruding terminal identification capability test cases base construction method and analog detection platform |
| CN111007450A (en) * | 2019-12-06 | 2020-04-14 | 江苏智臻能源科技有限公司 | Method for detecting result reliability of load identification equipment |
| CN111551889A (en) * | 2020-04-29 | 2020-08-18 | 国网重庆市电力公司营销服务中心 | Load identification electric energy meter detection platform |
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