CN113723683A - Wind power plant profit prediction method and system - Google Patents

Wind power plant profit prediction method and system Download PDF

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CN113723683A
CN113723683A CN202111006026.3A CN202111006026A CN113723683A CN 113723683 A CN113723683 A CN 113723683A CN 202111006026 A CN202111006026 A CN 202111006026A CN 113723683 A CN113723683 A CN 113723683A
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韩斌
孔繁新
李颖峰
刘瑞
赵勇
王新
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Xian Thermal Power Research Institute Co Ltd
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Xian Thermal Power Research Institute Co Ltd
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Abstract

The invention provides a method and a system for budget profit budget of a wind power plant, which comprises the following steps: step 1, predicting the actual power generation amount of each unit and predicting the power generation income of each unit in a prediction period; step 2, calculating the total predicted profit of each unit in the prediction period; step 3, calculating the total predicted profit of the wind power plant in the prediction period; the method and the device have the advantages that the generated energy, income and profit of the fan are predicted based on the wind speed data of each machine position, the difference of the wind speeds of the machine positions is fully considered, and the prediction precision is higher.

Description

Wind power plant profit prediction method and system
Technical Field
The invention belongs to the field of wind power generation, and particularly relates to a method and a system for predicting profit of a wind power plant.
Background
Along with the continuous deepening of the degree that new forms of energy participated in electric power market competition, new forms of energy power generation enterprise faces the realistic problem how to seek survival, conspire to develop, and urgent need improves refined management and accurate profit prediction through implementing lean management to the biggest output is obtained to minimum input, realizes the maximize of administrative value and benefit, promotes comprehensive market competition. In addition, in order to meet the requirements of digitalization and intellectualization of the wind power plant, new requirements are provided for the profit prediction method of each power station. By improving the profit prediction precision of the wind power plant, the method is beneficial for a wind power plant manager to make a better decision, arrange a production plan in advance, improve the yield of the wind power plant and reduce the operation and maintenance cost. And moreover, the profit prediction data of different projects are transversely compared and longitudinally compared, and the operation management of the new energy project is optimized by combining factors such as weather, personnel, capital, inventory, power grid operation and the like, so that the production benefit of a company is maximized.
The wind power plant profit prediction method also utilizes the generated energy, the online electricity price and the historical cost of the past year to carry out prediction, and the prediction method has larger error and can not meet the requirement of fine management proposed by the wind power plant at present; the method is inconsistent with the digitization and the intellectualization of the management, the operation and the maintenance of the new energy power station; the future profit and income of the power station can not be predicted in time according to the actual wind conditions of each year, and difficulty is brought to management decision.
Disclosure of Invention
The invention aims to provide a method and a system for budgeting profit of a wind power plant, which solve the defects in the prior art.
In order to achieve the purpose, the invention adopts the technical scheme that:
the invention provides a wind power plant profit budget method which comprises the following steps:
step 1, predicting the actual power generation amount of each unit and predicting the power generation income of each unit in a prediction period;
step 2, calculating the total predicted profit of each unit in the prediction period according to the actual generated energy and the generated income obtained in the step 1;
and 3, calculating the predicted total profit of the wind power plant in the prediction period according to the predicted total profit obtained in the step 2.
Preferably, in step 1, the actual power generation amount of each unit is predicted, and the power generation income in the prediction period of each unit is predicted, and the specific method is as follows:
s11, determining a functional relation between the wind speed of each unit of the wind power plant and the wind speed of the anemometer tower at the corresponding moment;
s12, calculating the wind speed of each unit position according to the functional relation in the S11 and the wind speed prediction data;
s13, predicting the theoretical power generation amount of each unit according to the wind speed of each unit position obtained in the S12;
and S14, predicting the actual power generation amount of each unit according to the theoretical power generation amount of each unit obtained in the S13.
Preferably, in S11, determining a functional relationship between the wind speed at each unit of the wind farm and the wind speed at the anemometer tower at the corresponding time, the specific method is:
s11, obtaining wind speed data V measured at the time t of the anemometer towerT-tAnd wind speed data V at time t of each unit positionWi-t；
S12, determining the wind speed V at each unit position through a data fitting methodWi-tCorresponding to the wind speed data V at the position of the anemometer tower at the momentT-tFunctional relationship of (a):
VWi-t＝f(VT-t)。
preferably, in S12, the wind speed at each unit position is calculated according to the functional relationship in S11 and the wind speed prediction data, and the specific method is as follows:
obtaining future t from wind power prediction systemiWind speed prediction data V of timeTy-ti；
According to the obtained future tiWind speed prediction data V of timeTy-tiCombining the functional relation obtained in S11, calculating to obtain the future tiWind speed V of each unit position at any momentWi-ti。
Preferably, in S13, the theoretical power generation amount of each unit is predicted according to the wind speed at the machine position of each unit obtained in S12, and the specific method is as follows:
calculating to obtain the future t of each unit according to the wind speed of each unit position obtained in the S12 and the standard power curve of the unit obtained by the SCADA systemiTheoretical power generation amount Q at timeWi-ti。
Preferably, in step 1, the power generation income of each unit in the prediction period is predicted, and the specific method is as follows:
acquiring maintenance log data in a wind power plant operation management system, and estimating fault downtime and maintenance time in a prediction period T;
calculating the loss electric quantity Q in the wind field prediction period according to the estimated fault shutdown time and maintenance time in the prediction period and by combining the predicted wind speed and the unit standard power curveWi-ys-T；
According to the known on-line electricity price P, the income W of each unit in the prediction period T is calculated according to the following formulay-Wi-t：
Wy-Wi-t＝(QWi-T-QWi-ys-T)*P
Wherein Q isWi-TPredicting the actual power generation amount in the period T for the unit; p is the known price of electricity on the internet.
Preferably, in step 2, the predicted total profit of each unit in the prediction period is calculated by the following specific method:
s21, acquiring fixed cost data and variable cost data from the financial system;
s22, calculating to obtain a fixed cost shared value of each unit according to the fixed cost data;
s23, calculating the fixed cost shared value C of each unit in the prediction period T according to the total fixed cost value C of the wind field of the financial systemyg-wi-T；
S24, estimating the variation cost G of each unit in the prediction period T according to the historical overhaul data of the previous yearyb-Wi-T；
S25, calculating the total profit of each unit in the prediction period by the following formula:
Ly-wi-T＝Wy-Wi-T-Cyg-wi-T-Cyb-Wi-T
wherein, Wy-Wi-TFor predicting the income of each unit in the period T.
A wind farm profit budgeting system capable of operating the method comprising:
the prediction unit is used for predicting the actual power generation amount of each unit and predicting the power generation income of each unit in the prediction period;
the calculating subunit is used for calculating the predicted total profit of each unit in the prediction period;
and the calculating unit is used for calculating the predicted total profit of the wind power plant in the prediction period.
Compared with the prior art, the invention has the beneficial effects that:
according to the wind power plant profit prediction method provided by the invention, the generated energy, income and profit of the wind turbine are predicted based on the wind speed data of each machine position, the difference of the wind speed of each machine position is fully considered, and the prediction precision is higher; the invention can realize automatic calculation of data, avoid manual calculation process and improve working efficiency; meanwhile, the budget method is convenient for converting the wind power plant into digitalization and intellectualization.
Furthermore, the generated energy of the wind power plant is accurately predicted by utilizing wind speed prediction data, historical overhaul data, fault shutdown time, financial data and the like, so that the profit of the wind power plant is predicted, and references are provided for investment decision, overhaul arrangement and other work of the wind power plant.
Furthermore, the invention utilizes the historical data of the anemometer tower and the unit to establish the functional relationship between the anemometer tower and the unit, so as to definitely predict the conversion relationship between the anemometer tower and the unit, and further accurately predict the wind speed of each unit.
Furthermore, the accurate actual generating capacity of the unit and the loss electric quantity of the unit are obtained through calculation, and the generating capacity income of the wind power plant is accurately predicted.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in FIG. 1, the wind farm profit budgeting method provided by the invention comprises the following steps:
step 1, determining a functional relation between wind speeds of all units of a wind power plant and wind speeds of a wind measuring tower at corresponding moments;
step 2, calculating the wind speed of each unit position according to the functional relation in the step 1 and wind speed prediction data;
step 3, predicting the theoretical power generation amount of each unit according to the wind speed of the unit position of each unit obtained in the step 2;
step 4, predicting the actual power generation amount of each unit according to the theoretical power generation amount of each unit obtained in the step 3;
step 5, predicting the generating income of each unit in the prediction period according to the actual generating capacity of each unit obtained in the step 4;
step 6, calculating the total predicted profit of each unit in the prediction period according to the generated income of each unit obtained in the step 5;
and 7, calculating the predicted total profit of the wind power plant in the prediction period according to the predicted total profit of each unit obtained in the step 6.
Specifically, in step 1, a functional relationship between the wind speed of each unit of the wind farm and the wind speed of the anemometer tower at the corresponding moment is determined, and the specific method is as follows:
s11, obtaining wind speed data V measured at the time t of the anemometer towerT-tAnd wind speed data V at time t of each unit positionWi-t；
S12, determining the wind speed V at each unit position through a data fitting methodWi-tCorresponding to the wind speed data V at the position of the anemometer tower at the momentT-tFunctional relationship of (a):
VWi-t＝f(VT-t)。
in the prior art, wind field wind speed prediction can be calculated according to wind measuring tower detection data, and the wind field wind speed prediction cannot be accurate to a unit; the invention utilizes the historical data of the anemometer tower and the unit to establish the functional relationship between the anemometer tower and the unit, and definitely predicts the conversion relationship between the wind speed of the anemometer tower and the wind speed of the unit.
In step 2, the wind speed at the machine position of each unit is calculated according to the function in the step 1 and wind speed prediction data, and the specific method is as follows:
s21, obtaining future t from wind power prediction systemiWind speed prediction data V of timeTy-ti；
S22, obtaining the future t according to the obtained futureiWind speed prediction data V of timeTy-tiCombining the functional relation obtained in the step 1, calculating to obtain the future tiWind speed V of each unit position at any momentWi-ti。
In the prior art, wind field wind speed prediction can be calculated according to wind measuring tower detection data, and the wind field wind speed prediction cannot be accurate to a unit; the invention utilizes the historical data of the anemometer tower and the unit to establish the functional relationship between the anemometer tower and the unit, and utilizes the real-time anemometer tower data to calculate the predicted wind speed of the unit.
In step 3, the theoretical power generation amount of each unit is predicted according to the wind speed of the unit position of each unit obtained in step 2, and the specific method is as follows:
calculating to obtain the future t of each unit according to the wind speed of each unit position obtained in the step 2 and the standard power curve of the unit obtained by the SCADA systemiTheoretical power generation amount Q at timeWi-ti。
The predicted wind speed is converted into the predicted theoretical generated energy, and the predicted production capacity of the unit can be visually displayed.
In step 4, according to the theoretical generated energy Q of each unit obtained in step 3Wi-tiAnd further calculating the actual generated energy Q in the unit prediction period TWi-TThe specific method comprises the following steps:
Figure BDA0003237072990000061
in step 5, generating income of each unit in the prediction period is predicted, and the specific method is as follows:
s51, acquiring maintenance log data in the wind power plant operation management system, and estimating fault shutdown time and maintenance time in the prediction period T; and analyzing the fault downtime and the overhaul time according to the statistical data of the overhaul log in two years, performing accounting on annual cycle data, and calculating the predicted fault downtime and the overhaul time in the prediction period T.
S52, calculating the loss electric quantity Q in the wind field prediction period according to the fault shutdown time and the overhaul time in the prediction period estimated in the S51 and the combination of the predicted wind speed and the standard power curve of the unitWi-ys-T；
S53, calculating income W of each unit in the prediction period T according to the known on-line electricity price P and the following formulay-Wi-t：
Wy-Wi-t＝(QWi-T-QWi-ys-T)*P
The existing method is that a predicted power curve is calculated according to predicted wind speed, which is not converted into more visual generated energy and income, and the loss electric quantity of a wind field is not considered, so that the obtained prediction result has larger deviation; according to the method, accurate actual generating capacity of the unit and the loss electric quantity of the unit are obtained through calculation, and generating capacity income of the wind power plant is accurately predicted.
In step 6, the total predicted profit of each unit in the prediction period is calculated according to the generated income of each unit obtained in step 5, and the specific method is as follows:
s61, acquiring fixed cost data and variable cost data from the financial system;
s62, calculating to obtain a fixed cost shared value of each unit according to the fixed cost data;
s63, calculating the fixed cost shared value C of each unit in the prediction period according to the total fixed cost value C of the wind field of the financial systemyg-wi-T(ii) a According to the total installed capacity R of the wind power plant and the single machine capacity R thereofiDistributing the total fixed cost value C of the wind field according to the single-machine capacity proportion to obtain the fixed cost value C of each unityg-wi-T；
Figure BDA0003237072990000071
Calculating to obtain a fixed cost value C of each unityg-wi-TAs a computer in S65The group prediction profit provides a data basis, and the system realizes the analysis of the fixed cost of each unit and achieves the aims of digital and fine management.
S64, obtaining historical overhaul data from the wind power plant operation management system, and estimating the variation cost C of each unit in the prediction period Tyb-Wi-T；
The fluctuating cost includes a material fee and a service fee, wherein:
and acquiring unit maintenance information through the wind field maintenance record, and calculating the material cost through accounting the material price and the material consumption.
The overhaul cost is calculated by the overhaul working hours and the operators through accounting.
The change cost reflects real-time business activities, financial data association is carried out, fusion linkage of business and finance is promoted, an information link is communicated, analysis of 'wind power plant profit accounting' is promoted, and maximum and comprehensive benefit optimal service is created for realizing value.
S65, calculating the total profit of each unit in the prediction period by the following formula:
Iy-wi-T＝Wy-Wi-T-Cyg-wi-T-Cyb-Wi-T。
the total predicted generating profit of the unit is obtained through calculation, the operation result of the prediction period can be reflected, reference is provided for work such as investment decision, arrangement and maintenance of the wind power plant, and meanwhile, the requirements of users on real-time management and analysis of the production cost and the profit of the wind power plant are met.
And 7, calculating the predicted total profit of the wind power plant in the prediction period according to the predicted total profit of each unit obtained in the step 6 by combining the following formula:
Figure BDA0003237072990000081
and N is the total number of the wind field fans.
The wind power plant profit prediction system stores the calculated amount at each moment into a database, and can display the generated energy, income and profit of each fan and the wind field and the predicted generated energy, income and profit by taking the period of minutes, days, weeks, months and years as a period through a data query mode.
The invention has the following effects:
(1) the background calculation engine of the wind power plant profit prediction system realizes automatic calculation and storage of data, saves a manual calculation process and improves the working efficiency;
(2) the generated energy, income and profit of each fan predicted based on the wind speed data of each machine position fully consider the difference of the wind speed of each machine position, and the prediction precision is higher.
(3) The method realizes the prediction of the generated energy, income and profit of each fan and wind field.

Claims (8)

1. A wind farm profit budgeting method is characterized by comprising the following steps:
step 1, predicting the actual power generation amount of each unit and predicting the power generation income of each unit in a prediction period;
step 2, calculating the total predicted profit of each unit in the prediction period according to the actual generated energy and the generated income obtained in the step 1;
and 3, calculating the predicted total profit of the wind power plant in the prediction period according to the predicted total profit obtained in the step 2.
2. The method for budgeting profit of a wind farm according to claim 1, wherein in step 1, the actual power generation of each unit is predicted, and the power generation income of each unit in the prediction period is predicted by the following specific method:
s11, determining a functional relation between the wind speed of each unit of the wind power plant and the wind speed of the anemometer tower at the corresponding moment;
s12, calculating the wind speed of each unit position according to the functional relation in the S11 and the wind speed prediction data;
s13, predicting the theoretical power generation amount of each unit according to the wind speed of each unit position obtained in the S12;
and S14, predicting the actual power generation amount of each unit according to the theoretical power generation amount of each unit obtained in the S13.
3. The method for budgeting profit of a wind farm according to claim 2, wherein in S11, a functional relationship between wind speeds at each unit of the wind farm and wind speeds at a anemometer tower at a corresponding time is determined, and the specific method is as follows:
s11, obtaining wind speed data V measured at the time t of the anemometer towerT-tAnd wind speed data V at time t of each unit positionWi-t；
S12, determining the wind speed V at each unit position through a data fitting methodWi-tCorresponding to the wind speed data V at the position of the anemometer tower at the momentT-tFunctional relationship of (a):
VWi-t＝f(VT-t)。
4. the method for profit budgeting of a wind farm according to claim 2, wherein in S12, the wind speed at each unit position is calculated according to the functional relationship in S11 by combining the wind speed forecast data, and the specific method is as follows:
obtaining future t from wind power prediction systemiWind speed prediction data V of timeTy-ti；
According to the obtained future tiWind speed prediction data V of timeTy-tiCombining the functional relation obtained in S11, calculating to obtain the future tiWind speed V of each unit position at any momentWi-ti。
5. The method for budgeting profit of a wind farm according to claim 2, wherein in S13, the theoretical power generation of each unit is predicted according to the wind speed at the position of each unit obtained in S12, and the method comprises the following steps:
calculating to obtain the future t of each unit according to the wind speed of each unit position obtained in the S12 and the standard power curve of the unit obtained by the SCADA systemiTheoretical power generation amount Q at timeWi-ti。
6. The method for budgeting profit of a wind farm according to claim 1, wherein in step 1, generating income of each unit in a prediction period is predicted by the following specific method:
acquiring maintenance log data in a wind power plant operation management system, and estimating fault downtime and maintenance time in a prediction period T;
calculating the loss electric quantity Q in the wind field prediction period according to the estimated fault shutdown time and maintenance time in the prediction period and by combining the predicted wind speed and the unit standard power curveWi-ys-T；
According to the known on-line electricity price P, the income W of each unit in the prediction period T is calculated according to the following formulay-Wi-t：
Wy-Wi-t＝(QWi-T-QWi-ys-T)*P
Wherein Q isWi-TPredicting the actual power generation amount in the period T for the unit; p is the known price of electricity on the internet.
7. The method for budgeting profit of a wind farm according to claim 1, wherein in the step 2, the predicted total profit of each unit in the prediction period is calculated by:
s21, acquiring fixed cost data and variable cost data from the financial system;
s22, calculating to obtain a fixed cost shared value of each unit according to the fixed cost data;
s23, calculating the fixed cost shared value C of each unit in the prediction period T according to the total fixed cost value C of the wind field of the financial systemyg-wi-T；
S24, estimating the variation cost C of each unit in the prediction period T according to the historical overhaul data of the previous yearyb-Wi-T；
S25, calculating the total profit of each unit in the prediction period by the following formula:
Iy-wi-T＝Wy-Wi-T-Cyg-wi-T-Cyb-Wi-T
wherein, Wy-Wi-TFor predicting the income of each unit in the period T.
8. A wind farm profit budgeting system capable of operating the method of any one of claims 1 to 7 and comprising:
the prediction unit is used for predicting the actual power generation amount of each unit and predicting the power generation income of each unit in the prediction period;
the calculating subunit is used for calculating the predicted total profit of each unit in the prediction period;
and the calculating unit is used for calculating the predicted total profit of the wind power plant in the prediction period.
CN202111006026.3A 2021-08-30 2021-08-30 Wind power plant profit prediction method and system Pending CN113723683A (en)

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Citations (8)

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