CN103795088B - A kind of hydroenergy storage station Optimization Scheduling quantized based on load curve - Google Patents
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Abstract
The invention discloses a kind of hydroenergy storage station Optimization Scheduling quantized based on load curve, it comprises the following steps: first arrange unit maintenance scheduling; Then Load Prediction In Power Systems data are gathered; Set up hydroenergy storage station state transition equation and constraints thereof afterwards; Set up fired power generating unit load curve quantizating index again, be minimised as target function with fired power generating unit load curve quantizating index, use dynamic programming to run hydroenergy storage station and be optimized scheduling.Present invention reduces the degree of fluctuation of the load curve that fired power generating unit is born, improve its power generation load rate, reduce the net coal consumption rate of fired power generating unit.
Description
Technical Field
The invention relates to a pumped storage power station technology, in particular to a pumped storage power station optimal scheduling method based on load curve quantization.
Background
The pumped storage power station is a hydropower station which utilizes redundant electric energy in an electric power system to pump water in a reservoir (generally called a lower reservoir) with low elevation into a reservoir (generally called an upper reservoir) with high elevation to store the water in a potential energy mode, and when the system needs electric power, the system discharges water from the upper reservoir to the lower reservoir to generate electricity. The pumped storage power station can provide active power support at a rate meeting the stability requirement of the system when the power grid is required no matter the pumped storage power station is used for frequency modulation, accident standby or load tracking so as to maintain the safety and stability of the operation of the system. Over the last ten years, pumped storage power stations have developed rapidly in China and are increasingly used in power systems.
The operation cost of the power system mainly relates to the cost of coal consumption fuel of the thermal power generating unit, and is influenced by the load and the change speed borne by the thermal power generating unit. The evaluation basis of the fuel cost of the thermal power generating unit is centrally embodied on the load curve borne by the thermal power generating unit.
The load curve of the thermal power generating unit is formed by connecting the discrete values of the borne loads by straight lines. The load curve quantization is divided into two parts, one part is composed of the angle (expressed by theta) between the load of each scheduling interval and the horizontal axis, and the other part is composed of the angle (expressed by psi) between each scheduling interval, as shown in fig. 1. The two parts reflect the requirements of the load curve on the output and the climbing speed of the thermal power generating unit, and the larger the included angle is, the larger the adjustment of the thermal power generating unit is required to be, the higher the corresponding coal consumption rate is, and the higher the fuel cost is.
From the perspective of power grid dispatching, how to optimize the operation of a pumped storage power station to enable the pumped storage power station to play the function that a thermal power generating unit does not have or is not economical is a problem which needs to be solved urgently. At present, the starting point or the objective function for optimally scheduling the pumped storage power station is the economic index such as the most economic system operation and the lowest power generation operation cost, the economic evaluation is carried out through the set fuel cost, the power shortage loss and the like, and the optimization result is influenced to a certain extent by different set values, so that the optimization is to be further improved.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the defects of the existing method, the invention aims to provide a pumped storage power station optimal scheduling method based on load curve quantization.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the following technical scheme:
a pumped storage power station optimal scheduling method based on load curve quantization is characterized by comprising the following steps:
(1) arranging a unit maintenance plan: determining the number of available thermal power generating units and the number of generating units of a pumped storage power station; inputting parameters of an available thermal power generating unit and a pumped storage power station generator unit; the parameters comprise rated power generation power of each thermal power generating unit, rated power generation power of each pumped storage power station generator set, pumped storage-power generation cycle efficiency of the pumped storage power station, given water storage capacity and maximum storage capacity;
(2) collecting load prediction data of a power system: the time interval of the power system load prediction data is fixed to deltatThe unit is h, and N points are shared; connecting two adjacent points of the power system load prediction data by using a straight line under a time-power system load prediction value coordinate system to form a power system load curve; the power system load prediction data is to generate powerDividing a system load curve into N scheduling intervals;
(3) establishing a state transition equation of the pumped storage power station:
(1)
in the formula (1)x t The unit of the water storage capacity of the upper reservoir of the pumped storage power station at the end moment of the tth dispatching interval is MWh,the state set X is:
(2)
in the formula (2), the compound represented by the formula (2),p h for pumped storage power stationshThe rated capacity of the unit is MW,h=1,2,3…H，Hthe number of the generator sets of the pumped storage power station,Pthe unit is the maximum common divisor of the capacity of each generator set of the pumped storage power station, MW,x maxthe unit is the maximum storage capacity of the pumped storage power station and is MWh; the number of state set elements M is determined by:
；（3）
in the formula (1)d t A decision variable for the t-th scheduling interval, in MW,；ηwhen the influence of natural water is neglected, the pumping-power generation cycle efficiency of the pumped storage power station is improved; the t-th scheduling interval decision variabled t At t for pumped storage power stationsThe power generation amount or the pumping power consumption amount in the dispatching interval,d t when the voltage is more than zero, the generator is in a power generation state;d t when the value is less than zero, the water pumping state is achieved, and the state set D is as follows:
；(4)
the constraints of the state transition equation are:
(5)
in the formula (5)x 0The unit of the water storage capacity of an upper reservoir of the pumped storage power station at the starting moment of the 1 st dispatching interval is MWh, and the unit of C is the given water storage capacity of the pumped storage power station and is MWh;
(4) establishing a thermal power generating unit load curve quantization index Q:
；（6）
in the formula (6), the compound represented by the formula (6),is composed ofT thThe unit of the included angle between the load curve of the thermal power generating unit and the horizontal coordinate axis of each scheduling interval is degree， Is composed ofT thScheduling interval andt-1, scheduling an included angle between load curves of the thermal power generating unit in a section, wherein the unit is degree; the load curve of the thermal power generating unit is obtained by subtracting a pumped storage power station benefit-storage optimized output curve from a power system load curve;
(5) establishing an objective functionPerforming optimized scheduling on the pumped storage power station by using a dynamic programming method, and sequentially executing the following substeps from a 1 st scheduling interval to an Nth scheduling interval:
1) establishing a t-th scheduling interval index functiong t (x t ,d t )，：
；（7）
2) Establishing a process indicator functionThe recurrence formula of (c):
，；（8）
whereinThe process index function of the t-th scheduling interval is represented by degree;
3) solving the t-th scheduling interval decision variable by taking the formula (8) as an objective functiond t Optimum value of (2)d t * The state variable of the t-th dispatching interval is obtained by substituting the state variable into a state transfer equation (1) of the pumped storage power stationx t Optimum value of (2)x t * ；
4) Will be described ind t * Andx t * substituting the process index functions into the process index function recurrence formula (8) to obtain the process index function of the t-th scheduling intervalOf (2) an optimal solutionAnd preparing for carrying out optimized dispatching by using a dynamic programming method in the t +1 th dispatching interval.
The first mentionedtIncluded angle between load curve and horizontal coordinate axis of thermal power generating unit in dispatching intervalθ t The calculation method comprises the following steps:
(9)
wherein，Is composed oftThe load curve of the thermal power generating unit is taken at the moment, the unit is MW,t=1,2,3…N，and is；
The first mentionedtScheduling interval andt-1 included angle between load curves of thermal power generating unit in dispatching intervalψ t The calculation method comprises the following steps:
（10）
wherein。
The beneficial effects produced by the technical scheme are as follows:
1. the method and the system have the advantages that the pumped storage power station can bear the changed part of the time sequence load curve as much as possible during optimized scheduling, the fluctuation degree of the load curve borne by the thermal power unit is effectively reduced, the load borne by the thermal power unit is more stable, and frequent primary and secondary frequency modulation actions in a large degree are avoided.
2. The invention optimizes the load curve of the thermal power generating unit by optimizing and dispatching the pumped storage power station, realizes minimum adjustment of the thermal power generating unit, reduces the coal consumption rate and saves the fuel cost.
Drawings
FIG. 1 is a flow chart of the optimized scheduling of the present invention;
FIG. 2 is a diagram illustrating a load curve quantization index of a thermal power generating unit according to the present invention;
FIG. 3 is a graph of the power system load curve and the optimized pumped-storage power station output of the present invention;
FIG. 4 is a thermal power generating unit load curve after the pumped storage power station is optimally scheduled.
Detailed Description
The present invention will be further described with reference to the following specific examples.
Example (b):
a pumped storage power station optimal scheduling method based on load curve quantization comprises the following steps, as shown in figure 1:
(1) arranging a unit maintenance plan: determining the number of available thermal power generating units and the number of generating units of a pumped storage power station; inputting parameters of an available thermal power generating unit and a pumped storage power station generator unit; the parameters comprise rated power generation power of each thermal power generating unit, rated power generation power of each pumped storage power station generator set, pumped storage-power generation cycle efficiency of the pumped storage power station, given water storage capacity and maximum storage capacity;
(2) collecting load prediction data of a power system: the time interval of the power system load prediction data is fixed to deltatThe unit is h, and N points are shared; connecting two adjacent points of the power system load prediction data by using a straight line under a time-power system load prediction value coordinate system to form a power system load curve; the power system load prediction data divides a power system load curve into N scheduling intervals;
(3) establishing a state transition equation of the pumped storage power station:
(1)
in the formula (1)x t The unit of the water storage capacity of the upper reservoir of the pumped storage power station at the end moment of the tth dispatching interval is MWh,the state set X is:
(2)
in the formula (2), the compound represented by the formula (2),p h for pumped storage power stationshThe rated capacity of the unit is MW,h=1,2,3…H，Hthe number of the generator sets of the pumped storage power station,Pthe unit is the maximum common divisor of the capacity of each generator set of the pumped storage power station, MW,x maxfor pumped storage power stationsThe maximum storage capacity of (1) is MWh; the number of state set elements M is determined by:
；（3）
in the formula (1)d t A decision variable for the t-th scheduling interval, in MW,；ηwhen the influence of natural water is neglected, the pumping-power generation cycle efficiency of the pumped storage power station is improved; the t-th scheduling interval decision variabled t The generated energy or pumped-storage power consumption of the pumped-storage power station in the t dispatching interval,d t when the voltage is more than zero, the generator is in a power generation state;d t when the value is less than zero, the water pumping state is achieved, and the state set D is as follows:
；(4)
the constraints of the state transition equation are:
(5)
in the formula (5)x 0The unit of the water storage capacity of an upper reservoir of the pumped storage power station at the starting moment of the 1 st dispatching interval is MWh, and the unit of C is the given water storage capacity of the pumped storage power station and is MWh;
(4) establishing a thermal power generating unit load curve quantization index Q:
；（6）
as shown in fig. 2, in the formula (6),is composed ofT thThe unit of the included angle between the load curve of the thermal power generating unit and the horizontal coordinate axis of each scheduling interval is degree， Is composed ofT thScheduling interval andt-1, scheduling an included angle between load curves of the thermal power generating unit in a section, wherein the unit is degree; the load curve of the thermal power generating unit is obtained by subtracting a pumped storage power station benefit-storage optimized output curve from a power system load curve;
(5) establishing an objective functionPerforming optimized scheduling on the pumped storage power station by using a dynamic programming method, and sequentially executing the following substeps from a 1 st scheduling interval to an Nth scheduling interval:
1) establishing a t-th scheduling interval index functiong t (x t ,d t )，：
；（7）
2) Establishing a process indicator functionThe recurrence formula of (c):
，；（8）
whereinThe process index function of the t-th scheduling interval is represented by degree;
3) solving the t-th scheduling interval decision variable by taking the formula (8) as an objective functiond t Optimum value of (2)d t * The state variable of the t-th dispatching interval is obtained by substituting the state variable into a state transfer equation (1) of the pumped storage power stationx t Optimum value of (2)x t * ；
4) Will be described ind t * Andx t * substituting the process index functions into the process index function recurrence formula (8) to obtain the process index function of the t-th scheduling intervalOf (2) an optimal solutionAnd preparing for carrying out optimized dispatching by using a dynamic programming method in the t +1 th dispatching interval.
The first mentionedtAn included angle theta between a load curve of the thermal power generating unit in the dispatching interval and a horizontal coordinate axis t The calculation method comprises the following steps:
(9)
wherein，Is composed oftThe load curve of the thermal power generating unit is taken at the moment, the unit is MW,t=1,2,3…N，and is；
The first mentionedtScheduling interval andt-1 scheduling interval thermal power generating unit load curve included angle psi t The calculation method comprises the following steps:
（10）
wherein。
In this embodiment, the power system includes 1 equivalent thermal power generating unit, and the rated power generation power is 60000 MW; the pumping-power generation cycle efficiency of 1 pumped storage power station is 79.90 percent, the given water storage capacity of the pumped storage power station is 1000MWh, the maximum storage capacity is 12000MWh, the rated power generation of 8 pumped storage power station generator sets is 300MW, and the total installed capacity is 2400 MW.
The power system load prediction curve in the embodiment is formed by short-term load prediction data of Guangdong province in 1 month and 3 days 2012. The power system load prediction interval isFixed at 0.25h, i.e. 15 minutes, there were 96 total power system load forecast data for a day, as shown in table 1. And connecting two adjacent points of the power system load prediction data by using a straight line under a time-power system load prediction value coordinate system to form a power system load prediction curve. The 96 power system load prediction data divides the power system load curve into N scheduling intervals. The method of the invention is used for carrying out optimized dispatching on the pumped storage power station to obtain a series of optimal valuesd t I.e. pumped storage power stationScheduling scheme at the end of each scheduling interval. The optimization results of this example are shown in fig. 3. In order to draw the power system load prediction curve and the pumped storage power station optimized output curve in a graph, the power system load prediction value is shown by being reduced by 10 times in the graph.
FIG. 4 is a thermal power generating unit load curve after optimized dispatching of a pumped storage power station; it can be seen that after the pumped storage power station is optimally scheduled by the method, the fluctuation degree of the thermal power unit load curve is reduced compared with the power system load prediction curve.
Table 2 compares the results of whether the present invention is used to optimize the operation of pumped storage power plants. The 'non-preferential storage' means that the pumped storage power station does not participate in the load distribution of the power grid; the 'after experiential operation of the impoundment is realized' means that the pumped storage power station is dispatched in an experiential operation mode; the method is used for carrying out optimized dispatching on the pumped storage power station. The invention can be seen in that the load pulsation quantization index is reduced and the power generation load rate is increased when the pumped storage power station is optimally adjusted. The optimization of the two indexes means that the running cost of the fired electric generator set is reduced, and the method has important guiding significance in actual production.
The influence of the load curve of the thermal power generating unit on the power supply coal consumption is related to the power generation load rate and the fluctuation degree of the load curve. Even under the same average load rate, the stable operation of the unit is more beneficial to reducing the coal consumption of power supply than the load fluctuation. The influence of the fluctuation degree of the load curve of the power system and the load curve of the thermal power generating unit on the power supply coal consumption is quantitatively calculated, and the practicability of the method is verified.
For convenience of calculation, after the load curve value of the thermal power generating unit is reduced by 100 times, the load curve value is borne by a 600MW supercritical thermal power generating unit, and the power supply coal consumption of the 600MW supercritical thermal power generating unit is reducedu(x) See table 3. Performing polynomial fitting of degree 2 on the data in the table 3, wherein the fitting result is as follows:
u(x)=0.0003x 2-0.3701x+422.4429
let the electric power system burdenThe load prediction curve isL’1(t) The load curve of the thermal power generating unit isL’2(t). The power supply coal consumption calculation formula for one day is as follows:
wherein,H 1in order to optimize the power supply coal consumption of the day before the dispatching,H 2the power supply coal consumption of one day after the dispatching is optimized.
Thereby obtainingH 1=3.5362×109The weight of the raw materials is gram,H 2=3.4978×109and g, after the optimized scheduling is carried out by using the method, 38.4 tons of coal can be saved in one day.
TABLE 1 electric power system load data
| Load point | Load value (MW) | Load point | Load value (MW) |
| 1 | 38000 | 49 | 49000 |
| 2 | 37400 | 50 | 46300 |
| 3 | 36900 | 51 | 45700 |
| 4 | 36500 | 52 | 45600 |
| 5 | 36100 | 53 | 45500 |
| 6 | 35700 | 54 | 47000 |
| 7 | 35300 | 55 | 48600 |
| 8 | 34900 | 56 | 51200 |
| 9 | 34600 | 57 | 51800 |
| 10 | 34300 | 58 | 52400 |
| 11 | 34100 | 59 | 52600 |
| 12 | 33800 | 60 | 52700 |
| 13 | 33600 | 61 | 52800 |
| 14 | 33400 | 62 | 53000 |
| 15 | 33200 | 63 | 53200 |
| 16 | 33100 | 64 | 53400 |
| 17 | 33000 | 65 | 53900 |
| 18 | 33000 | 66 | 54400 |
| 19 | 33000 | 67 | 54900 |
| 20 | 33000 | 68 | 55400 |
| 21 | 33100 | 69 | 55600 |
| 22 | 33200 | 70 | 55700 |
| 23 | 33400 | 71 | 54400 |
| 24 | 33700 | 72 | 54000 |
| 25 | 34000 | 73 | 54700 |
| 26 | 34700 | 74 | 55900 |
| 27 | 35400 | 75 | 56700 |
| 28 | 36400 | 76 | 57000 |
| 29 | 37400 | 77 | 56700 |
| 30 | 38900 | 78 | 56400 |
| 31 | 40100 | 79 | 56000 |
| 32 | 41900 | 80 | 55500 |
| 33 | 44900 | 81 | 55000 |
| 34 | 49200 | 82 | 54700 |
| 35 | 51100 | 83 | 54400 |
| 36 | 52400 | 84 | 54100 |
| 37 | 53000 | 85 | 53700 |
| 38 | 53600 | 86 | 53100 |
| 39 | 54000 | 87 | 52300 |
| 40 | 54400 | 88 | 51500 |
| 41 | 54800 | 89 | 50700 |
| 42 | 55200 | 90 | 49800 |
| 43 | 55600 | 91 | 48700 |
| 44 | 56000 | 92 | 47500 |
| 45 | 56300 | 93 | 45900 |
| 46 | 56500 | 94 | 44300 |
| 47 | 55500 | 95 | 42700 |
| 48 | 53500 | 96 | 41300 |
TABLE 2 comparison of optimization results
| Index (I) | Non-economical storage | After the experience of economical storage is run | After optimization of the benefits and storage |
| Load pulsation quantization index | 550.96 | 538.74 | 524.64 |
| Load factor of power generation | 81.79% | 84.13% | 85.96% |
Power supply coal consumption of meter 3600MW thermal power generating unit
| Load(s)x（MW） | Coal consumption of power supplyu(x)（g/kw·h） | Load(s)x（MW） | Coal consumption of power supplyu(x)（g/kw·h） |
| 350 | 330 | 500 | 313 |
| 400 | 322 | 550 | 310 |
| 450 | 316 | 600 | 308 |
Claims (2)
1. A pumped storage power station optimal scheduling method based on load curve quantization is characterized by comprising the following steps:
(1) arranging a unit maintenance plan: determining the number of available thermal power generating units and the number of generating units of a pumped storage power station; inputting parameters of an available thermal power generating unit and a pumped storage power station generator unit; the parameters comprise rated power generation power of each thermal power generating unit, rated power generation power of each pumped storage power station generator set, pumped storage-power generation cycle efficiency of the pumped storage power station, given water storage capacity and maximum storage capacity;
(2) collecting load prediction data of a power system: the time interval of the power system load prediction data is fixed to deltatThe unit is h, and N points are shared; connecting two adjacent points of the power system load prediction data by using a straight line under a time-power system load prediction value coordinate system to form a power system load curve; the power system load prediction data divides a power system load curve into N scheduling intervals;
(3) establishing a state transition equation of the pumped storage power station:
in the formula (1)x t The unit of the water storage capacity of the upper reservoir of the pumped storage power station at the end moment of the tth dispatching interval is MWh,the state set X is:
in the formula (2), the compound represented by the formula (2),p h for pumped storage power stationshThe rated capacity of the unit is MW,h=1,2,3…H，Hthe number of the generator sets of the pumped storage power station,Pthe unit is the maximum common divisor of the capacity of each generator set of the pumped storage power station, MW,x maxthe unit is the maximum storage capacity of the pumped storage power station and is MWh; the number of state set elements M is determined by:
in the formula (1)d t A decision variable for the t-th scheduling interval, in MW,；ηwhen the influence of natural water is neglected, the pumping-power generation cycle efficiency of the pumped storage power station is improved; the t-th scheduling interval decision variabled t The generated energy or pumped-storage power consumption of the pumped-storage power station in the t dispatching interval,d t when the voltage is more than zero, the generator is in a power generation state;d t when the value is less than zero, the water pumping state is achieved, and the state set D is as follows:
the constraints of the state transition equation are:
in the formula (5)x 0The unit of the water storage capacity of an upper reservoir of the pumped storage power station at the starting moment of the 1 st dispatching interval is MWh, and the unit of C is the given water storage capacity of the pumped storage power station and is MWh;
(4) establishing a thermal power generating unit load curve quantization index Q:
in the formula (6), the compound represented by the formula (6),is composed ofT thThe unit of the included angle between the load curve of the thermal power generating unit and the horizontal coordinate axis of each scheduling interval is degree， Is composed ofT thScheduling interval andt-1, scheduling an included angle between load curves of the thermal power generating unit in a section, wherein the unit is degree; the load curve of the thermal power generating unit is obtained by subtracting the optimized output curve of the pumped storage power station from the load curve of the power system;
(5) establishingObjective functionPerforming optimized scheduling on the pumped storage power station by using a dynamic programming method, and sequentially executing the following substeps from a 1 st scheduling interval to an Nth scheduling interval:
1) establishing a t-th scheduling interval index functiong t (x t ,d t )，：
2) Establishing a process indicator functionThe recurrence formula of (c):
whereinThe process index function of the t-th scheduling interval is represented by degree;
3) solving the t-th scheduling interval decision variable by taking the formula (8) as an objective functiond t Optimum value of (2)d t * The state variable of the t-th dispatching interval is obtained by substituting the state variable into a state transfer equation (1) of the pumped storage power stationx t Optimum value of (2)x t * ；
4) Will be described ind t * Andx t * substituting the first and second process index function into the recursive formula (8) to obtain the first and second process index functiont procedure index function of scheduling intervalOf (2) an optimal solutionAnd preparing for carrying out optimized dispatching by using a dynamic programming method in the t +1 th dispatching interval.
2. The pumped storage power station optimized dispatching method based on load curve quantization of claim 1 is characterized in that: the first mentionedtIncluded angle between load curve and horizontal coordinate axis of thermal power generating unit in dispatching intervalθ t The calculation method comprises the following steps:
wherein，Is composed oftThe load curve of the thermal power generating unit is taken at the moment, the unit is MW,t=1,2,3…N，and is；
The first mentionedtScheduling interval andt-1 included angle between load curves of thermal power generating unit in dispatching intervalψ t The calculation method comprises the following steps:
wherein。
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