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CN108154268B - Method for rapidly estimating group power generation quantity of small hydropower stations - Google Patents

Method for rapidly estimating group power generation quantity of small hydropower stations Download PDF

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CN108154268B
CN108154268B CN201711425984.8A CN201711425984A CN108154268B CN 108154268 B CN108154268 B CN 108154268B CN 201711425984 A CN201711425984 A CN 201711425984A CN 108154268 B CN108154268 B CN 108154268B
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relation curve
precipitation
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王昕�
林峰
黄光斌
陈志�
杨里
林家辉
陈建南
郑金泰
刘浦
池惠
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State Grid Fujian Electric Power Co Ltd
Fujian Shuikou Power Generation Group Co Ltd
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Fujian Shuikou Power Generation Group Co Ltd
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Abstract

The invention provides a method for quickly estimating the group power generation quantity of small hydropower stations, which skillfully holds the essential objective attribute of the power generation quantity by combining the analysis and application of historical data through the technical support data with higher level and the area precipitation data which is easy to obtain and can be mastered in real time by a power scheduling department, thereby estimating the real-time data of the power generation quantity of the small hydropower stations which are scattered and are inconvenient to collect. Compared with the prior art, the method can relatively accurately estimate the whole daily generated energy of the small hydropower station group under the condition of not increasing hardware resources and reducing the working pressure of a first-line meter reading person, and greatly improves the efficiency of the current generated energy data summarization of the small hydropower stations.

Description

Method for rapidly estimating group power generation quantity of small hydropower stations
Technical Field
The invention belongs to the field of power generation amount statistics, and particularly relates to a method for quickly estimating the power generation amount of a small hydropower station group.
Background
The small hydropower station refers to a hydropower station or a hydroelectric power generation device with smaller installed capacity, and the second international research and research conference on the development and application of small hydropower station in 1980 suggests: small hydropower stations are defined as hydropower stations under 12000 kW.
In areas with abundant small hydropower resources, such as the south of China, the base number of small hydropower stations is large, so that the whole power generation amount cannot be ignored statistically although the capacity of a single station is small.
In areas where the power generation capacity of small hydropower stations accounts for a large proportion, the power dispatching department needs to count the data of the whole power generation capacity of the small hydropower stations every day. However, due to the fact that technical support means of small hydropower stations are backward and the distribution is wide, real-time generated energy data cannot be collected through automatic means at the present stage, and the small hydropower stations are unrealistic and uneconomical to install automatic collection equipment in a unified mode in operation.
Therefore, the current small hydropower station electric quantity data reporting adopts a manual meter reading method and a step-by-step reporting method, although the data is accurate, the time delay of 1-2 days exists, the interference of human factors is serious, and other errors can be generated.
Disclosure of Invention
Aiming at the problems in the prior art, the invention adopts the following technical scheme:
a method for rapidly estimating the group power generation quantity of small hydropower stations is characterized by comprising the following steps:
the method comprises the following steps: dividing a measuring and calculating area according to the distribution of a water network and the distribution of hydropower stations, wherein large and medium hydropower stations and small hydropower stations are distributed in the same water network in the measuring and calculating area;
step two: calculating the daily runoff precipitation W in N days in the measuring and calculating arean(ii) a The daily runoff precipitation amount WnObtaining the actual precipitation R in the measuring and calculating area through weighting conversion; the method for the weighted conversion comprises the following steps:
Figure BDA0001522468660000011
wherein R isiIs the actual precipitation on day i; r isi-1Is the actual precipitation on the day before the ith day; ri2Is the actual precipitation two days before day i; wiRunoff precipitation on day i;
step three: according to the measurement and calculation of the daily generated energy D of large and medium hydropower stations in the region in N daysnAnd corresponding daily runoff precipitation WnObtaining a D-W relation curve through quadratic curve fitting; generating capacity D of the large and medium hydropower station on the j day through the D-W relation curvejThe corresponding runoff precipitation W on the j day can be obtainedj
Step four: according to the daily generated energy X of the small hydropower stations in the measuring area in N daysnAnd corresponding daily runoff precipitation WnObtaining an X-W relation curve through quadratic curve fitting; wherein the daily power generation amount X of the small hydropower station in N daysnObtaining the data through manual meter reading; through the X-W relation curve, the runoff precipitation W on the j dayjThe corresponding power generation quantity X of the small hydropower station on the jth day can be obtainedj
Preferably, the method further comprises the following steps:
step five: obtaining a D-X relation curve according to the D-W relation curve and the X-W relation curve; generating capacity D of the large and medium hydropower station on the j day through the D-X relation curvejThe method can directly obtain the power generation X of the small hydropower station in the same measuring and calculating area on the j th dayj
Preferably, N-30.
Preferably, the method of weighting and scaling in step two is:
Figure BDA0001522468660000021
wherein R isiIs the actual precipitation on day i; ri-1Is the actual precipitation, R, of the day before the i-th dayi-2Is the actual precipitation, R, two days before the i-th dayi-mIs the actual precipitation m days before the ith day; wiIs the diameter of the ith dayAnd (6) water is drained.
Preferably, the D-W relation curve is a D-W relation table; the X-W relation curve is an X-W relation table.
Preferably, the D-W relation curve and the X-W relation curve are updated according to months, and the N days are all dates of the last natural month.
The method is economical and efficient, and by the technical support that an electric power dispatching department can master in real time, the large and medium hydropower station generating capacity data with higher level and the area precipitation data which are easy to obtain are combined with the analysis and application of historical data, the essential objective attribute of the generating capacity is held ingeniously, so that the real-time data of the generating capacity of the small hydropower stations which are scattered and inconvenient in data collection is estimated. Compared with the prior art, the method can relatively accurately estimate the whole daily generated energy of the small hydropower station group under the condition of not increasing hardware resources and reducing the working pressure of a first-line meter reading person, and greatly improves the efficiency of the current generated energy data summarization of the small hydropower stations.
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The invention is described in further detail below with reference to the following figures and detailed description:
FIG. 1 is a schematic flow chart of an embodiment of the present invention.
Detailed Description
In order to make the features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail as follows:
as shown in fig. 1, the method of this embodiment includes the following steps:
the method comprises the following steps: dividing a measuring and calculating area according to the distribution of the water network and the distribution of the hydropower stations, wherein large and medium hydropower stations and small hydropower stations are distributed in the same water network in the measuring and calculating area;
step two: calculating the daily runoff precipitation W in N days in the measuring and calculating arean(ii) a Daily runoff precipitation WnObtaining the actual precipitation R in the measurement and calculation area through weighting conversion; the method for weight conversion is as follows:
Figure BDA0001522468660000031
wherein R isiIs the actual precipitation on day i; ri-1Is the actual precipitation for the day before the ith day; ri-2Is the actual precipitation two days before day i; wiRunoff precipitation on day i;
step three: according to the measurement and calculation of the daily generated energy D of large and medium hydropower stations in the region in N daysnAnd corresponding daily runoff precipitation WnObtaining a D-W relation curve through quadratic curve fitting; generating capacity D of the large and medium hydropower station on the j day through a D-W relation curvejThe corresponding runoff precipitation W on the j day can be obtainedj
Step four: according to the daily generated energy X of the small hydropower stations in the measuring area in N daysnAnd corresponding daily runoff precipitation WnObtaining an X-W relation curve through quadratic curve fitting; wherein the daily generated energy X of the small hydropower station in N daysnThe method is obtained through manual meter reading, and although the efficiency of the manual meter reading is low and the reporting time delay exists, the precision of the manual meter reading is guaranteed; through an X-W relation curve, the runoff precipitation W on the j dayjThe power generation amount X of the corresponding small hydropower station on the j day can be obtainedj
Step five: obtaining a D-X relation curve according to the D-W relation curve and the X-W relation curve; generating capacity D of the large and medium hydropower station on the j day through a D-X relation curvejThe method can directly obtain the power generation X of the small hydropower station in the same measuring and calculating area on the j th dayj
In this embodiment, in order to improve the accuracy of estimation, the method of weighting and scaling in step two may be replaced by:
Figure BDA0001522468660000041
wherein R isiIs the actual precipitation on day i; ri-1Is the actual precipitation, R, of the day before the i-th dayi-2Is the actual precipitation, R, two days before the i-th dayi-mIs the actual precipitation m days before the ith day; wiIs runoff precipitation on day i. The actual precipitation data of more days are introduced, the measurement precision of the runoff precipitation is improved, and the calculation burden is increased to delay the efficiency.
In order to further simplify the operation difficulty of estimation, in this embodiment, the D-W relationship curve may be converted into a discrete D-W relationship table; and converting the X-W relation curve into a discrete X-W relation table, wherein the D-X relation curve in the fifth step can also directly obtain the D-X relation table through the D-W relation table and the X-W relation table. The precision of the relation table can be established according to actual conditions and precision requirements.
In the embodiment, the D-W relation curve and the X-W relation curve are updated according to months, and N days are all dates of the last natural month, because the small hydropower stations are in more production and shutdown changes.
The present invention is not limited to the above preferred embodiments, and any other various methods for rapidly estimating the power generation of small hydropower stations can be obtained from the teaching of the present invention.

Claims (2)

1. A method for rapidly estimating the group power generation quantity of small hydropower stations is characterized by comprising the following steps:
the method comprises the following steps: dividing a measuring and calculating area according to the distribution of a water network and the distribution of hydropower stations, wherein large and medium hydropower stations and small hydropower stations are distributed in the same water network in the measuring and calculating area;
step two: calculating the daily runoff precipitation W in N days in the measuring and calculating arean(ii) a The daily runoff precipitation amount WnObtaining the actual precipitation R in the measurement and calculation area through weighting conversion; the method for the weighted conversion comprises the following steps:
Figure FFW0000023381660000011
wherein R isiIs the actual precipitation on day i; ri-1Is the actual precipitation, R, of the day before the i-th dayi-2Is the actual precipitation, R, two days before the ith dayi-mIs the actual precipitation m days before the ith day; wiRunoff precipitation on day i;
step three: according to the measurement and calculation of the daily generated energy D of large and medium hydropower stations in the region in N daysnAnd corresponding daily runoff precipitation WnObtaining a D-W relation curve through quadratic curve fitting; generating capacity D of the large and medium hydropower station on the j day through the D-W relation curvejThe corresponding runoff precipitation W on the j day can be obtainedj
Step four: according to the daily generated energy X of the small hydropower stations in the measuring area in N daysnAnd corresponding daily runoff precipitation WnObtaining an X-W relation curve through quadratic curve fitting; wherein the daily power generation amount X of the small hydropower station in N daysnObtaining the data through manual meter reading; through the X-W relation curve, the runoff precipitation W on the j dayjThe power generation amount X of the corresponding small hydropower station on the j day can be obtainedj
Step five: obtaining a D-X relation curve according to the D-W relation curve and the X-W relation curve; generating capacity D of the large and medium hydropower station on the j day through the D-X relation curvejThe method can directly obtain the power generation X of the small hydropower station in the same measuring and calculating area on the j th dayj
The D-W relation curve is a D-W relation table; the X-W relation curve is an X-W relation table;
and updating the D-W relation curve and the X-W relation curve according to months, wherein the N days are all dates of the last natural month.
2. The method for rapidly estimating the group power generation capacity of small hydropower stations according to claim 1, wherein the method comprises the following steps: n is 30.
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103854073A (en) * 2014-03-24 2014-06-11 昆明理工大学 Method for comprehensively predicting generation capacity of multi-radial flow type small hydropower station group area
CN104463358A (en) * 2014-11-28 2015-03-25 大连理工大学 Small hydropower station power generation capacity predicating method combining coupling partial mutual information and CFS ensemble forecast
CN104809532A (en) * 2015-05-25 2015-07-29 海南汉能薄膜太阳能有限公司 Method for predicting generating capacity of photovoltaic system
CN105354416A (en) * 2015-10-26 2016-02-24 南京南瑞集团公司 Representative power station based basin rainfall runoff power macro-forecasting method
CN106192863A (en) * 2016-07-06 2016-12-07 贵州东方世纪科技股份有限公司 A kind of power station installed capacity and annual electricity generating capacity evaluation method

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI352201B (en) * 2008-04-14 2011-11-11 Inventec Appliances Corp A method and recording medium for early warning of
JP2012118207A (en) * 2010-11-30 2012-06-21 Sanyo Electric Co Ltd Display system
CN102867222B (en) * 2012-08-14 2016-03-09 贵州乌江水电开发有限责任公司 A kind of checking energy of power station and the measuring method of storehouse charge capacity and device
CN102855393B (en) * 2012-08-14 2017-02-22 贵州乌江水电开发有限责任公司 Method and system for measuring and calculating hydroenergy utilization improvement rate of cascaded hydropower stations
JP5907018B2 (en) * 2012-09-14 2016-04-20 富士通株式会社 Optical output level controller
US9534236B2 (en) * 2013-03-08 2017-01-03 Regents Of The University Of Minnesota Membranes for wastewater-generated energy and gas
CN104537436B (en) * 2014-12-18 2017-11-10 大连理工大学 A kind of regional small power station's generating capacity Forecasting Methodology
CN105096216B (en) * 2015-09-01 2018-07-31 中国长江电力股份有限公司 A kind of method of quick calculating hydropower station amount
CN105553405B (en) * 2016-01-14 2017-08-15 阿尔特汽车技术股份有限公司 Vehicular solar cell power generation amount estimation apparatus and method
CN105976067A (en) * 2016-05-21 2016-09-28 华能澜沧江水电股份有限公司 Cascade hydropower station group long-term generating scheduling method based on bidding strategies
CN107016496A (en) * 2017-03-22 2017-08-04 贵州乌江水电开发有限责任公司 Hydropower Stations water level control carries the measuring method and system of efficiency
CN107341570B (en) * 2017-06-26 2018-10-16 华中科技大学 Reservoir filling phase runoff grading control power generation dispatching method under the conditions of a kind of random water

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103854073A (en) * 2014-03-24 2014-06-11 昆明理工大学 Method for comprehensively predicting generation capacity of multi-radial flow type small hydropower station group area
CN104463358A (en) * 2014-11-28 2015-03-25 大连理工大学 Small hydropower station power generation capacity predicating method combining coupling partial mutual information and CFS ensemble forecast
CN104809532A (en) * 2015-05-25 2015-07-29 海南汉能薄膜太阳能有限公司 Method for predicting generating capacity of photovoltaic system
CN105354416A (en) * 2015-10-26 2016-02-24 南京南瑞集团公司 Representative power station based basin rainfall runoff power macro-forecasting method
CN106192863A (en) * 2016-07-06 2016-12-07 贵州东方世纪科技股份有限公司 A kind of power station installed capacity and annual electricity generating capacity evaluation method

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