CN111832829B - Reservoir hydropower station optimal operation method based on big data - Google Patents
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Abstract
The invention provides a reservoir hydropower station optimal operation method based on big data, which forms a big data platform for hydropower station optimal operation by collecting the water level of a reservoir, the power generation flow and the output condition of each unit of the power station operation, and can search the optimal working condition through the big data in the hydropower station operation so as to provide guidance for the hydropower station optimal operation.
Description
Technical Field
The invention relates to hydraulic engineering, in particular to a reservoir hydropower station optimal operation method based on big data.
Background
The reservoir hydropower station is a common hydropower station arrangement form, and the runoff can be redistributed through the adjustment function of the reservoir, so that the utilization efficiency of the reservoir hydropower station on the water energy resource is improved; the power generation water head of the reservoir hydropower station is greatly influenced by the water level of the reservoir, the power generation process is variable water head power generation, the power generation process is greatly different from the radial flow hydropower station, the power generation of the reservoir hydropower station at present mostly adopts empirical power generation or theoretical optimization operation guidance power generation, certain defects exist, the optimization space is generally poor, and the power generation cannot be effectively guided by utilizing the operation data of the power station.
The big data analysis technology is to utilize the data rule of big data to carry out scientific guidance, and for hydropower stations, the big data analysis processing is carried out by utilizing the operation data of the power station, so that the reference can be effectively provided for the optimized operation of the power station. The optimized operation of the reservoir hydropower station lacks big data technical support at present, lacks a reasonable and feasible optimizing method, and even if the optimized operation technology is adopted, a large space still exists for the optimization due to the existence of errors.
Disclosure of Invention
Based on the above, the invention provides a reservoir hydropower station optimizing operation method based on big data, the reservoir hydropower station is arranged at the downstream of the reservoir and is a post-dam hydropower station, the reservoir is provided with a reservoir water level monitoring device, the hydropower station is provided with a power generation flow monitoring device, each unit of the hydropower station is provided with a unit output monitoring device, the reservoir water level monitoring device monitors and collects the reservoir water level, the power generation flow monitoring device monitors and collects the power generation flow, and the unit output monitoring device monitors and collects the unit output, and the method is characterized in that: the optimized operation method comprises the following steps:
s1: collecting output conditions of each unit under the reservoir water level and the power generation flow in different time periods, wherein the power generation flow is the total power generation flow of the starting unit, and the reservoir water level, the power generation flow and the output of each unit are in one-to-one correspondence in time; calculating the sum of the output forces of all the units as the total output force of the units;
s2: processing the power station operation data to form power station operation big data: the processing is as follows: finding out a group corresponding to the maximum total output force of the units corresponding to the same water level of the reservoir and the same power generation flow, recording the output force of each unit corresponding to the maximum total output force of the units, and performing the above processing on all water levels of the reservoir and all power generation flow to form big data, wherein the big data comprises: one-to-one corresponding reservoir water level, power generation flow, maximum unit total output and corresponding unit output; in the subsequent operation process, if the total output force of the units corresponding to the same water level of the reservoir and the same power generation flow rate is relative to the total output force of the units in the big data, replacing the total output force of the units and the output force of each unit in the big data with the larger total output force of the units and the corresponding output force of each unit, and replacing and updating the original big data;
s3: searching big data for any reservoir water level and any current generation amount in the operation of the power station, performing differential processing on the big data to obtain the output of each unit corresponding to the working condition, and performing output adjustment; the differential processing is as follows: searching two groups of reservoir water levels adjacent to any reservoir water level, searching two groups of flow rates adjacent to any generating amount corresponding to the two groups of reservoir water levels on the basis, and obtaining two groups of reservoir water levels, two groups of generating flow rates and four groups of unit output corresponding to the two groups of generating flow rates respectively, wherein the four groups of unit output are obtained by carrying out difference according to a difference principle; when any reservoir water level or any generated current amount is equal to the reservoir water level or generated current amount in the big data, the difference can be directly searched.
Preferably, the monitoring precision of the reservoir water level monitoring device is 1cm, and the time precision is more than 3s.
Preferably, the power generation flow rate monitoring device may be selected as a water inlet gate opening monitoring device, a power generation flow rate measuring device or a tail water level monitoring device, and when the power generation flow rate monitoring device is the water inlet gate opening monitoring device or the tail water level monitoring device, the power generation flow rate is obtained by converting a flow rate opening curve or a tail water level flow rate curve of the gate.
The principle of the invention is as follows:
for the operation of the reservoir hydropower station, a better working condition can be generated in the operation process, the total output of the unit is larger at the moment, and the better data can be reserved through a big data analysis technology, so that a reference is provided for the operation of the hydropower station. Different reservoir water levels and power generation flow rates are collected, and under the working conditions, the historical operation data are utilized to find the optimal working conditions and guide the operation of the power station.
The power generation flow can be directly obtained or converted through the opening of the water diversion gate, the power generation flow measuring device or the tail water level, and the relative error of the same measuring device is small, so that the operation of the power station can be guided.
The invention has the advantages that:
the invention provides a reservoir hydropower station optimal operation method based on big data, which forms a big data platform for hydropower station optimal operation by collecting the water level of a reservoir, the power generation flow and the output condition of each unit of the power station operation, and can search the optimal working condition through the big data in the hydropower station operation so as to provide guidance for the hydropower station optimal operation.
The specific embodiment is as follows: the structure defined by the present invention is specifically explained below with reference to the following embodiments.
The invention provides a reservoir hydropower station optimizing operation method based on big data, wherein the reservoir hydropower station is arranged at the downstream of a reservoir and is a post-dam hydropower station, the reservoir is provided with a reservoir water level monitoring device, the hydropower station is provided with a power generation flow monitoring device, each unit of the hydropower station is provided with a unit output monitoring device, the reservoir water level monitoring device monitors and collects the reservoir water level, the power generation flow monitoring device monitors and collects the power generation flow, and the unit output monitoring device monitors and collects the unit output, and the method is characterized in that: the optimized operation method comprises the following steps:
s1: collecting output conditions of each unit under the reservoir water level and the power generation flow in different time periods, wherein the power generation flow is the total power generation flow of the starting unit, and the reservoir water level, the power generation flow and the output of each unit are in one-to-one correspondence in time; calculating the sum of the output forces of all the units as the total output force of the units;
s2: processing the power station operation data to form power station operation big data: the processing is as follows: finding out a group corresponding to the maximum total output force of the units corresponding to the same water level of the reservoir and the same power generation flow, recording the output force of each unit corresponding to the maximum total output force of the units, and performing the above processing on all water levels of the reservoir and all power generation flow to form big data, wherein the big data comprises: one-to-one corresponding reservoir water level, power generation flow, maximum unit total output and corresponding unit output; in the subsequent operation process, if the total output force of the units corresponding to the same water level of the reservoir and the same power generation flow rate is relative to the total output force of the units in the big data, replacing the total output force of the units and the output force of each unit in the big data with the larger total output force of the units and the corresponding output force of each unit, and replacing and updating the original big data;
s3: searching big data for any reservoir water level and any current generation amount in the operation of the power station, performing differential processing on the big data to obtain the output of each unit corresponding to the working condition, and performing output adjustment; the differential processing is as follows: searching two groups of reservoir water levels adjacent to any reservoir water level, searching two groups of flow rates adjacent to any generating amount corresponding to the two groups of reservoir water levels on the basis, and obtaining two groups of reservoir water levels, two groups of generating flow rates and four groups of unit output corresponding to the two groups of generating flow rates respectively, wherein the four groups of unit output are obtained by carrying out difference according to a difference principle; when any reservoir water level or any generated current amount is equal to the reservoir water level or generated current amount in the big data, the difference can be directly searched.
Preferably, the monitoring precision of the reservoir water level monitoring device is 1cm, and the time precision is more than 3s.
The principle of the invention is as follows:
for the operation of the reservoir hydropower station, a better working condition can be generated in the operation process, the total output of the unit is larger at the moment, and the better data can be reserved through a big data analysis technology, so that a reference is provided for the operation of the hydropower station. Different reservoir water levels and power generation flow rates are collected, and under the working conditions, the historical operation data are utilized to find the optimal working conditions and guide the operation of the power station.
The power generation flow can be directly obtained or converted through the opening of the water diversion gate, the power generation flow measuring device or the tail water level, and the relative error of the same measuring device is small, so that the operation of the power station can be guided.
And carrying out epitaxial differential processing on two adjacent data of the differential data exceeding the big data.
For the actual operation of the reservoir, after long-term operation data of the reservoir are collected, big data analysis is carried out, an optimal starting mode under a certain reservoir water level and a certain power generation flow is found, the mode corresponds to the highest utilization efficiency of the water level and the total power generation flow, and the power generation benefit is maximum, so that the working condition is selected and stored through the big data; in the subsequent power generation process, the database searching is carried out on the power generation flow and the reservoir water level, if no direct value exists, the adjacent value can be searched, and when the difference is carried out, the difference is two-dimensional difference, namely, the difference calculation is carried out under the two dimensions of the reservoir water level and the total power generation flow, the optimal output combination under the reservoir water level and the total power generation flow is found out, and the output combination is the actual operation data of the reservoir hydropower station, so that more accurate reference can be provided for the operation of the reservoir hydropower station, and the operation of the power station can be guided more and more accurately along with the accumulation of the operation time.
The above-described embodiments are only preferred embodiments of the present invention, and the scope of the present invention should not be construed as being limited to the specific forms set forth by the examples, but also includes equivalent technical means as will occur to those skilled in the art based on the inventive concept.
Claims (3)
1. The utility model provides a reservoir hydropower station optimizing operation method based on big data, the hydropower station sets up in the reservoir low reaches, is behind the dam hydropower station, reservoir installs storehouse water level monitoring devices, power flow monitoring devices is installed to the hydropower station, each unit of hydropower station all installs unit output monitoring devices, storehouse water level monitoring devices monitors and gathers the reservoir water level, power flow monitoring devices monitors and gathers the power flow, unit output monitoring devices monitors and gathers each unit output, its characterized in that: the optimized operation method comprises the following steps:
s1: collecting output conditions of each unit under the reservoir water level and the power generation flow in different time periods, wherein the power generation flow is the total power generation flow of the starting unit, and the reservoir water level, the power generation flow and the output of each unit are in one-to-one correspondence in time; calculating the sum of the output forces of all the units as the total output force of the units;
s2: processing the power station operation data to form power station operation big data: the processing is as follows: finding out a group corresponding to the maximum total output force of the units corresponding to the same water level of the reservoir and the same power generation flow, recording the output force of each unit corresponding to the maximum total output force of the units, and performing the above processing on all water levels of the reservoir and all power generation flow to form big data, wherein the big data comprises: one-to-one corresponding reservoir water level, power generation flow, maximum unit total output and corresponding unit output; in the subsequent operation process, if the same water level of the reservoir occurs and the total output force of the units corresponding to the same power generation flow is larger than the total output force of the units in the big data, replacing the total output force of the units and the output force of each unit in the big data by the larger total output force of the units and the corresponding output force of each unit, and replacing and updating the original big data;
s3: searching big data for any reservoir water level and any current generation amount in the operation of the power station, performing differential processing on the big data to obtain the output of each unit corresponding to the working condition, and performing output adjustment; the differential processing is as follows: searching two groups of reservoir water levels adjacent to any reservoir water level, searching two groups of flow rates adjacent to any generating amount corresponding to the two groups of reservoir water levels on the basis, and obtaining two groups of reservoir water levels, two groups of generating flow rates and four groups of unit output corresponding to the two groups of generating flow rates respectively, wherein the four groups of unit output are obtained by carrying out difference according to a difference principle; when any reservoir water level or any generated current amount is equal to the reservoir water level or generated current amount in the big data, the difference can be directly searched.
2. The optimal operation method for the reservoir hydropower station based on big data as claimed in claim 1, wherein: the monitoring precision of the reservoir water level monitoring device is 1cm, and the time precision is more than 3s.
3. The optimal operation method for the reservoir hydropower station based on big data as claimed in claim 1, wherein: the power generation flow monitoring device can be selected as a water inlet gate opening monitoring device or a power generation flow measuring device or a tail water level monitoring device, and when the power generation flow monitoring device is the water inlet gate opening monitoring device or the tail water level monitoring device, the power generation flow is obtained by converting a flow opening curve or a tail water level flow curve of the gate.
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| CN110705784A (en) * | 2019-09-29 | 2020-01-17 | 河南郑大水利科技有限公司 | Optimized operation evaluation method for radial flow type hydropower station |
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| CN108053083B (en) * | 2018-01-16 | 2021-12-24 | 湖南发展集团股份有限公司 | Combined optimized power generation scheduling method for reservoir hydropower station in non-flood season |
| CN108223258B (en) * | 2018-01-16 | 2023-12-15 | 衢州市信安水电开发有限公司 | Automatic optimization method for radial flow hydropower station |
| CN108193653B (en) * | 2018-01-16 | 2024-03-19 | 郑州誉善贸易有限公司 | An automatic optimization system for run-of-river hydropower stations |
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| CN110705784A (en) * | 2019-09-29 | 2020-01-17 | 河南郑大水利科技有限公司 | Optimized operation evaluation method for radial flow type hydropower station |
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