CN113673851B - Provincial power grid day-ahead power generation planning method based on data driving - Google Patents
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Abstract
The invention relates to the field of power generation scheduling of an electric power system, and discloses a date-ahead power generation scheduling method of a provincial power grid based on data driving. The technical scheme is as follows: determining an initial output plan of the power station by using the load similarity, and verifying the feasibility of the initial output process by using the fixed output; according to the historical electric quantity similarity, the output plan is further updated, and finally, the hydropower station with better adjusting performance is selected as a balance power station to realize daily load balance of the power grid.
Description
Technical Field
The invention relates to the field of power generation scheduling of power systems, in particular to a provincial power grid day-ahead power generation planning method based on data driving.
Background
In the past two decades, large-scale centralized development and production of hydropower in China are realized, two provincial power grids with the largest hydropower scale are formed in the southwest region, namely a Yunnan power grid and a Sichuan power grid, the hydropower installation of a single provincial power grid exceeds 7500 ten thousand kW, the number of power stations participating in provincial dispatching balance exceeds 200, and the power grids also comprise hundreds of wind power stations and photovoltaic power stations.
For example, in a Yunnan power grid, the general regulation 180 hydropower stations are distributed in a plurality of watersheds and comprise a plurality of regulation types, such as multi-year regulation, annual regulation, seasonal regulation, weekly regulation, daily regulation, radial-flow type and the like, the power stations with different regulation performances have different operation characteristics, the warehousing flow and the faced scheduling requirements have larger difference, so that the working positions of the hydropower stations in a load diagram are different, various differentiated characteristic power supplies of coal power, wind power and photovoltaic are considered, a practical power generation operation plan is difficult to obtain by adopting a traditional optimization scheduling modeling method, such as the maximum generated energy, the maximum peak regulation power and the like, and the calculation efficiency is very low due to the large scale and prominent dimension disaster problem of the power stations. Therefore, it is necessary to design an efficient and practical scheduling method for the day-ahead power generation scheduling balance problem of such a power grid.
Therefore, the invention takes the Yunnan power grid overall transfer of more than 300 power stations as the background, develops research aiming at the day-ahead load balance problem of the high-proportion hydropower and provincial power grid by relying on the national science fund (52079014), and provides a provincial power grid day-ahead power generation planning method with important practical value based on the load and power generation long series data drive.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method for compiling a day-ahead power generation plan of a provincial power grid based on data driving, wherein an initial output plan of a power station is determined by utilizing load similarity, and the feasibility of an initial output process is verified by adopting a fixed output; according to the historical electric quantity similarity, the output plan is further updated, and finally, the hydropower station with better adjusting performance is selected as a balance power station to realize daily load balance of the power grid.
The technical scheme of the invention is as follows:
a provincial power grid day-ahead power generation plan compilation method based on data driving is characterized in that the compilation of a power grid day-ahead power generation plan is completed according to the following steps 1-5:
step 1, comparing the loads of the power grids, and determining an initial output plan of each power station. Inputting the predicted load process of the planned day and the historical load data of the long-series power grid, comparing and analyzing the predicted load and the historical load, specifically finding out the date with the closest load according to the following formula, and taking the output process of the day as the initial output of each power station.
In the formula: COE n The correlation coefficient of the predicted load and the actual load is obtained; c t ' is the historical load of the grid in time period t, in units MW;
is the actual load mean, unit MW;
is the predicted load mean, in MW.
And 2, analyzing the incoming water of the power station. And inputting the predicted warehousing flow of each hydropower station planned day, carrying out fixed output calculation by time intervals by taking the obtained output process as a target, and analyzing whether each hydropower station can meet the initial planned output under the condition of predicting the incoming water.
p m,t ＝N(Z m,t-1 ,Q m,t ,q m,t ,Ql m,t ,Δt) (2)
In the formula: p is a radical of m,t Output of reservoir m in t period(ii) a N (-) is a function for calculating the output of the power station according to the water level and the flow; z m,t-1 The water level of the reservoir m in the t-1 period; q m,t ，q m,t ，Ql m,t Respectively the warehousing flow, the power generation flow and the power generation flow of the reservoir m in the time period t,
Water reject flow; Δ t is the number of hours encompassed by the t period.
And 3, analyzing the generated energy of the power station. For a power station which cannot meet the planned output process, the power generation amount is counted according to the output process obtained by the power station, and the method is specifically as follows:
and 4, updating the initial plan of the power station. And (4) according to the generated energy of part of the power stations obtained in the step (3), finding out the date with the closest electric energy from the historical generated energy data, and using the generating process at the date as an updating plan of the power stations.
And 5, carrying out power grid load balancing. Deducting the initial planned output process of the power station from the initial load of the power grid to obtain unbalanced electric quantity demand, selecting partial hydropower stations with better regulation performance as balanced power stations, determining the generated energy of each power station according to equal utilization hours (see formula (4)), and calculating a formula (see formula (5)). And according to the generated energy, adopting a load shedding method to successively determine the output process of each power station according to the upstream and downstream sequences.
In the formula: j is the number of selected balancing power stations;
is m j Maximum output of the power station;
is m j The output of a power station;
is m c Average load rate of power station number.
Compared with the prior art, the technical scheme of the invention can realize the following beneficial effects: the method provided by the invention can avoid constructing a complex power grid power generation scheduling optimization model and solving algorithm by utilizing data such as long-series load, output, electric quantity and the like, and the mode takes historical operation data of a power grid and a power station as drive, thereby greatly simplifying the complexity of power generation scheduling, and simultaneously improving the efficiency of power grid day-ahead planning and the practicability of planning. Compared with the traditional optimization model which takes the maximum generated energy, the maximum peak load and the like as the targets, the method can greatly reduce the optimization calculation scale, improve the calculation efficiency and improve the feasibility of the daily plan of the power station, and is a practical and practical day-ahead planning method.
Drawings
FIG. 1 is a provincial grid load balancing diagram;
FIG. 2 is a plot of the output process for a bay balance station;
FIG. 3 is a graph of the output process of a gulf-diffuse balanced power plant;
fig. 4 is a graph of the output process of a Dachaoshan hydroelectric power station.
Detailed Description
The invention relates to a date-ahead power generation planning method for a provincial power grid based on data driving, which is further described by combining the accompanying drawings and examples.
The once complete provincial power grid day-ahead power generation planning method based on data driving can be expressed by the following steps:
(1) And comparing the loads of the power grids, and determining an initial output plan of each power station.
Inputting the predicted load process of the planned day and the historical load data of the long-series power grid, performing comparative analysis on the predicted load and the historical load, finding out the date with the closest load, and taking the output process of the day as the initial output of each power station.
Step 1: the following formula is adopted to calculate the comparison coefficient of two load data sequences
Step 2: and finding out the date corresponding to the maximum coefficient value, and extracting the output process of each power station on the date as the initial output process of the planning date.
(2) Power station incoming water analysis. And inputting the predicted warehousing flow of each hydropower station planned day, carrying out fixed output calculation by time intervals by taking the obtained output process as a target, and analyzing whether each hydropower station can meet the initial planned output under the condition of predicting the incoming water.
Step 1: the initial water level of the power station is used as the initial water level of the power station, the predicted warehousing flow is used as incoming water, the output of the power station is calculated by time intervals by adopting the following formula, and meanwhile, the power generation flow, the water discharge flow and the time interval end water level of the power station in each time interval can be obtained.
p m,t ＝N(Z m,t-1 ,Q m,t ,q m,t ,Ql m,t ,Δt) (7)
And 2, step: and (3) comparing the output obtained in the step (1) with the initial planned output, wherein if the output and the initial planned output are equal, the predicted warehousing flow can meet the initial output plan of the power station, and if the output is smaller than the initial planned output, the predicted warehousing flow cannot meet the requirement.
And step 3: and finding out all power stations which cannot meet the initial planned output according to the method of the first two steps.
(3) And analyzing the power generation capacity of the power station.
And (3) calculating the electricity generation amount of the power station by adopting an equation (8) for the power station which cannot meet the planned output process.
(4) The initial plan of the plant is updated.
Step 1: historical from power stationMatching and E in model power generation amount data m The most recent date;
and 2, step: the power station output process of the date is extracted and updated to the planned output process of the power station.
(5) And balancing the load of the power grid.
Step 1: deducting the initial planned output process of the power station from the initial load of the power grid to obtain unbalanced electric quantity demand;
step 2: selecting part of hydropower stations with better regulation performance as balance power stations, and generally selecting the hydropower stations with better regulation performance;
and step 3: determining the power generation amount of each power station according to the equal utilization hours;
and 4, step 4: and according to the generated energy, adopting a load shedding method to successively determine the output process of each power station according to the upstream and downstream sequences.
When the result is not balanced, the balance power station needs to be further adjusted, and then the steps are carried out again until the power balance of the power grid in the whole period is realized.
Application example:
the method is verified by taking 190 water power stations, thermal power stations, wind power stations and photovoltaic power stations of the Yunnan power grid as examples to perform power generation balance. Historical load, output and electric quantity data are analyzed by adopting actual operation data of the last year and taking 96-point power output plans of a certain day as an example. Table 1 lists the raw load data of the grid and the output process data of various power stations.
As can be seen from fig. 1, by using the data-driven load balancing method provided by the present invention, it can be ensured that the generated power of the hydropower station, the thermal power station, the wind power station, and the photovoltaic power station completely meets the load demand of the system, that is, the power balance at 96 points on the planned day is realized. Fig. 2-4 show the output process of three representative balancing power stations, and it can be seen that the output operation process of these hydropower stations is reasonable, and as a balancing power plant of the power grid, the load fluctuation of the system effectively balanced by the automatic generator set can be effectively confirmed by the output fluctuation of the balancing power station in the figure, and the reasonability of the result is verified. According to the table 1, the total output of the hydropower system and the main regulation hydropower station play a good peak regulation role, the output at the early peak and late peak periods is obviously higher than that at the valley period, the peak regulation effect is obvious, and the peak power balance requirement of a power grid is met.
In addition, the method has the advantages that the calculation time consumption is small, the calculation time is reduced by about 50% compared with that of the traditional method, and the timeliness requirement of power generation scheduling planning in the actual production of the power grid is completely met.
TABLE 1 Power grid load Balancing data
Claims (1)
1. A provincial power grid day-ahead power generation planning method based on data driving is characterized by comprising the following steps:
step 1, comparing the loads of the power grid, and determining an initial output plan of each power station: inputting a predicted load process of a planned day and historical load data of a long-series power grid, performing comparative analysis on the predicted load and the historical load, specifically finding out a date with the closest load according to a formula (1), and taking the output process of the day as the initial output of each power station;
in the formula: COE n A correlation coefficient of the predicted load and the actual load; c' t The historical load of the power grid in a time period t is unit MW;
is the actual load mean value, unit MW;
is the predicted load mean, unit MW;
step 2, power station incoming water analysis: inputting the predicted warehousing flow of each hydropower station planned day, carrying out fixed output calculation time period by taking the output process obtained in the step (1) as a target, and analyzing whether each hydropower station can meet the initial planned output under the condition of predicting the incoming water;
p m,t ＝N(Z m,t-1 ,Q m,t ,q m,t ,Ql m,t ,Δt) (2)
in the formula: p is a radical of m,t The output of the reservoir m in the time period t; n (-) is a function for calculating the power station output according to the water level and the flow; z is a linear or branched member m,t-1 Is the water level of the reservoir m in the t-1 period; q m,t ，q m,t ，Ql m,t The flow rate of the reservoir m is the warehousing flow rate, the power generation flow rate and the water discharge rate in the time period t; Δ t is the number of hours included in the t period;
step 3, power station power generation amount analysis: for the power station which can not meet the planned output process, the electricity generation quantity E can be counted according to the output process obtained by the power station m Specifically, the following formula:
and 4, updating the initial plan of the power station: according to the generated energy of the partial power station obtained in the step 3, finding out the date with the closest electric quantity from the historical generated energy data, and taking the generating process of the date as an updating plan of the power station;
step 5, carrying out power grid load balancing: deducting the initial planned output process of the power stations from the initial load of the power grid to obtain unbalanced electric quantity requirements, selecting partial hydropower stations with good adjusting performance as balanced power stations, determining the generated energy of each power station according to the equal utilization hours, and calculating a formula (5), wherein the equal utilization hours are obtained through a formula (4); according to the generated energy, adopting a load shedding method to successively determine the output process of each power station according to the upstream and downstream sequences;
in the formula: j is the number of selected balancing power stations;
is m j Maximum output of the power station;
is m j The output of a power station;
is m c Average load rate of power station number.
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| CN105427017A (en) * | 2015-10-29 | 2016-03-23 | 大连理工大学 | Water power concentration power grid extra large scale power station group short period plan compiling method |
| CN109492861A (en) * | 2018-09-27 | 2019-03-19 | 昆明电力交易中心有限责任公司 | A kind of Hydropower Stations mid-term electricity trading program decomposition method |
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