CN111832829A - Reservoir hydropower station optimized operation method based on big data - Google Patents
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Abstract
The invention provides a reservoir hydropower station optimized operation method based on big data, which forms a big data platform for optimized operation of the hydropower station by acquiring reservoir water level, power generation flow and output conditions of each unit of the hydropower station.
Description
Technical Field
The invention relates to water conservancy projects, in particular to a reservoir hydropower station optimized operation method based on big data.
Background
The reservoir hydropower station is a common hydropower station arrangement form, and the runoff can be redistributed under the regulation action of the reservoir, so that the utilization efficiency of the reservoir hydropower station on water energy resources is improved; the generating head of the reservoir hydropower station is greatly influenced by the reservoir water level, the generating process is variable head generating, which is greatly different from the radial flow type hydropower station.
The big data analysis technology is scientific guidance by using the data rule of big data, and for the hydropower station, the big data analysis processing is performed by using the operation data of the hydropower station, so that reference can be effectively provided for the optimized operation of the hydropower station. The optimization operation of reservoir hydropower stations is lack of large data technical support and reasonable and feasible optimization methods at present, and even if the optimization operation technology is adopted, large space still exists in the optimization due to errors.
Disclosure of Invention
Based on the above, the invention provides a reservoir hydropower station optimized operation method based on big data, wherein the reservoir hydropower station is arranged at the downstream of a reservoir and is a dam-behind 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 acquires the reservoir water level, the power generation flow monitoring device monitors and acquires the power generation flow, and the unit output monitoring device monitors and acquires the output of each unit, and the method is characterized in that: the optimized operation method comprises the following steps:
s1: collecting output conditions of each unit under reservoir water level and power generation flow at different time intervals, wherein the power generation flow is the total power generation flow of a 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 total output of each unit as the total output of the unit;
s2: processing the power station operation data to form power station operation big data: the treatment comprises the following steps: finding out a group of the maximum corresponding units of the total output corresponding to the same reservoir level and the same generating flow, recording the maximum corresponding units of the total output of the unit, and performing the above processing on all the reservoir levels and all the generating flows to form big data, wherein the big data comprises: the reservoir water level, the power generation flow, the maximum unit total output and the corresponding unit outputs are in one-to-one correspondence; in the subsequent operation process, if the total output of the unit corresponding to the same reservoir water level and the same power generation flow is relative to the total output of the unit in the big data, replacing the total output of the unit and the output of each unit in the big data by the greater total output of the unit and the corresponding output of each unit, and replacing and updating the original big data;
s3: searching big data for any reservoir water level and any power generation flow in the operation of the power station, carrying out differential processing on the big data to obtain the output of each unit corresponding to the working condition, and carrying out output adjustment; the difference processing is as follows: searching two groups of reservoir levels adjacent to any reservoir level, and on the basis, searching two groups of flow rates adjacent to any power generation flow rate corresponding to the two groups of reservoir levels, so that the output of the two groups of reservoir levels, the two groups of power generation flow rates and four groups of units corresponding to the two groups of reservoir levels and the two groups of power generation flow rates can be obtained, and the difference is carried out according to the difference principle to obtain the output difference value of each unit; when any reservoir level or any power generation flow is equal to the reservoir level or the power generation flow in the big data, the difference can be directly found without difference.
Preferably, the monitoring precision of the reservoir water level monitoring device is 1cm, and the time precision is more than 3 s.
Preferably, the generated current monitoring device can be selected from a water inlet gate opening degree monitoring device, a generated current measuring device or a tail water level monitoring device, and when the generated current monitoring device is the water inlet gate opening degree monitoring device or the tail water level monitoring device, the generated current needs to be obtained by converting a flow opening degree curve or a tail water level flow curve of a gate.
The principle of the invention is as follows:
for the operation of a reservoir water power station, a better working condition can occur in the operation process, the total output of the unit is larger, and the better data can be reserved through a big data analysis technology, so that reference is provided for the operation of the power station. Different reservoir levels and power generation flows are collected, and under the working conditions, the optimal working conditions can be found by using historical operation data to guide the operation of the power station.
For the generated flow, the generated flow can be directly obtained or converted through the opening of a water diversion gate, a generated flow measuring device or a tail water level, and for the same measuring device, the relative error is small, so that the operation of a power station can be guided.
The invention has the advantages that:
the invention provides a reservoir hydropower station optimized operation method based on big data, which forms a big data platform for optimized operation of the hydropower station by acquiring reservoir water level, power generation flow and output conditions of each unit of the hydropower station.
The specific implementation mode is as follows: the structure defined in the present invention will be explained in detail with reference to the embodiments.
The invention provides a reservoir hydropower station optimized operation method based on big data, wherein a reservoir power station is arranged at the downstream of a reservoir and is a dam-behind 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 output of each unit, and the method is characterized in that: the optimized operation method comprises the following steps:
s1: collecting output conditions of each unit under reservoir water level and power generation flow at different time intervals, wherein the power generation flow is the total power generation flow of a 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 total output of each unit as the total output of the unit;
s2: processing the power station operation data to form power station operation big data: the treatment comprises the following steps: finding out a group of the maximum corresponding units of the total output corresponding to the same reservoir level and the same generating flow, recording the maximum corresponding units of the total output of the unit, and performing the above processing on all the reservoir levels and all the generating flows to form big data, wherein the big data comprises: the reservoir water level, the power generation flow, the maximum unit total output and the corresponding unit outputs are in one-to-one correspondence; in the subsequent operation process, if the total output of the unit corresponding to the same reservoir water level and the same power generation flow is relative to the total output of the unit in the big data, replacing the total output of the unit and the output of each unit in the big data by the greater total output of the unit and the corresponding output of each unit, and replacing and updating the original big data;
s3: searching big data for any reservoir water level and any power generation flow in the operation of the power station, carrying out differential processing on the big data to obtain the output of each unit corresponding to the working condition, and carrying out output adjustment; the difference processing is as follows: searching two groups of reservoir levels adjacent to any reservoir level, and on the basis, searching two groups of flow rates adjacent to any power generation flow rate corresponding to the two groups of reservoir levels, so that the output of the two groups of reservoir levels, the two groups of power generation flow rates and four groups of units corresponding to the two groups of reservoir levels and the two groups of power generation flow rates can be obtained, and the difference is carried out according to the difference principle to obtain the output difference value of each unit; when any reservoir level or any power generation flow is equal to the reservoir level or the power generation flow in the big data, the difference can be directly found without difference.
Preferably, the monitoring precision of the reservoir water level monitoring device is 1cm, and the time precision is more than 3 s.
The principle of the invention is as follows:
for the operation of a reservoir water power station, a better working condition can occur in the operation process, the total output of the unit is larger, and the better data can be reserved through a big data analysis technology, so that reference is provided for the operation of the power station. Different reservoir levels and power generation flows are collected, and under the working conditions, the optimal working conditions can be found by using historical operation data to guide the operation of the power station.
For the generated flow, the generated flow can be directly obtained or converted through the opening of a water diversion gate, a generated flow measuring device or a tail water level, and for the same measuring device, the relative error is small, so that the operation of a power station can be guided.
And for the data with the difference exceeding the big data, carrying out epitaxial difference processing by adopting two adjacent data.
For actual operation of the reservoir, after long-term operation data of the reservoir are collected, big data analysis is carried out, and an optimal starting mode under a certain reservoir water level and a certain generating capacity is found out, wherein the mode has the highest utilization efficiency and the maximum generating benefit corresponding to the water level and the total generating capacity, so that the working condition is selected through big data and stored; in the subsequent power generation process, the database search is carried out on the power generation flow and the reservoir water level, if no direct value exists, the adjacent values 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, the output combination is long series actual operation data of the reservoir hydropower station, more accurate reference can be provided for the operation of the reservoir hydropower station, and the power station can be guided to operate 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 in the examples, but also includes equivalent technical means which can be conceived by those skilled in the art from the present inventive concept.
Claims (3)
1. The utility model provides a reservoir power station optimization operation method based on big data, the reservoir power station sets up in the reservoir low reaches, for dam back formula power station, reservoir installs reservoir water level monitoring devices, power generation flow monitoring devices is installed at the power station, each unit of power station all installs unit monitoring devices that exert oneself, reservoir water level monitoring devices monitors and gathers the reservoir water level, power generation flow monitoring devices monitors and gathers the power generation flow, unit monitoring devices that exert oneself monitors and gathers each unit and exert oneself, its characterized in that: the optimized operation method comprises the following steps:
s1: collecting output conditions of each unit under reservoir water level and power generation flow at different time intervals, wherein the power generation flow is the total power generation flow of a 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 total output of each unit as the total output of the unit;
s2: processing the power station operation data to form power station operation big data: the treatment comprises the following steps: finding out a group of the maximum corresponding units of the total output corresponding to the same reservoir level and the same generating flow, recording the maximum corresponding units of the total output of the unit, and performing the above processing on all the reservoir levels and all the generating flows to form big data, wherein the big data comprises: the reservoir water level, the power generation flow, the maximum unit total output and the corresponding unit outputs are in one-to-one correspondence; in the subsequent operation process, if the total output of the unit corresponding to the same reservoir water level and the same power generation flow is relative to the total output of the unit in the big data, replacing the total output of the unit and the output of each unit in the big data by the greater total output of the unit and the corresponding output of each unit, and replacing and updating the original big data;
s3: searching big data for any reservoir water level and any power generation flow in the operation of the power station, carrying out differential processing on the big data to obtain the output of each unit corresponding to the working condition, and carrying out output adjustment; the difference processing is as follows: searching two groups of reservoir levels adjacent to any reservoir level, and on the basis, searching two groups of flow rates adjacent to any power generation flow rate corresponding to the two groups of reservoir levels, so that the output of the two groups of reservoir levels, the two groups of power generation flow rates and four groups of units corresponding to the two groups of reservoir levels and the two groups of power generation flow rates can be obtained, and the difference is carried out according to the difference principle to obtain the output difference value of each unit; when any reservoir level or any power generation flow is equal to the reservoir level or the power generation flow in the big data, the difference can be directly found without difference.
2. The method for optimizing the operation of a reservoir hydropower station based on big data according to claim 1, characterized by: the monitoring precision of the reservoir water level monitoring device is 1cm, and the time precision is greater than 3 s.
3. The method for optimizing the operation of a reservoir hydropower station based on big data according to claim 1, characterized by: the power generation flow monitoring device can be selected as a water inlet gate opening degree 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 degree monitoring device or the tail water level monitoring device, the power generation flow is obtained by converting a flow opening degree curve or a tail water level flow curve of a gate.
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