CN109510238B - Coordinated dispatching unit combination method for efficiently solving hydroelectric power, thermal power and wind power - Google Patents

Coordinated dispatching unit combination method for efficiently solving hydroelectric power, thermal power and wind power Download PDF

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CN109510238B
CN109510238B CN201811492254.4A CN201811492254A CN109510238B CN 109510238 B CN109510238 B CN 109510238B CN 201811492254 A CN201811492254 A CN 201811492254A CN 109510238 B CN109510238 B CN 109510238B
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周博然
鲁海威
刘波
林春清
蔡秀梅
文静
潘峰
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State Grid Liaoning Electric Power Co Ltd
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Abstract

The invention discloses a unit combination method for efficiently solving coordinated dispatching of water, electricity, thermal power and wind power. Compared with the existing unit combination method, the method fully considers the characteristics of the cascade hydroelectric generating set, combines the power generation dispatching and the flood storage dispatching of the cascade reservoir, and designs the unit combination method for coping with the large-scale access of uncertain wind power. The specific method comprises the following steps: 1. inputting related data of thermal power, wind power and a hydroelectric generating set; 2. selecting a target function and establishing a mixed integer linear programming equation set according to an equation and inequality constraint in the power system; 3. dividing the mixed integer linear equation system problem into 4 subproblems; 4. according to the set combination sub-problems which do not contain the power flow constraint under the expected situation, the starting and stopping sequence and the active power operating point of the generator set are obtained and are sequentially brought into other three tester sub-problems for circular test; 5. and obtaining a unit combination result meeting all 4 subproblems and using the unit combination result as a unit scheduling scheme. The invention provides a targeted simplification method based on the robust backup algorithm under the worst condition, greatly reduces the calculated amount and lays a solid foundation for the application of the method in the actual power system.

Description

Coordinated dispatching unit combination method for efficiently solving hydroelectric power, thermal power and wind power
Technical Field
The invention belongs to the technical field of operation, analysis and scheduling of power systems, and particularly relates to a coordinated scheduling unit combination method for efficiently solving hydroelectric power-thermal power-wind power.
Background
With the large amount of new energy such as wind power and the like being combined with the grid for power generation, the uncertainty of a power grid is obviously enhanced, and the power generation of a system and the scheduling of spare capacity face new challenges. The power system comprises various generator sets, such as a thermal power generating set and a hydroelectric generating set, the power generation and standby characteristics of the generator sets are different, different generator sets are cooperatively scheduled, and the method has important significance for the system to consume wind power.
This patent proposes multiple reserve form according to the uncertainty of wind-powered electricity generation. And designing a unit combination model according to respective characteristics of water, electricity and thermal power. And a robust unit combination algorithm solving model based on the worst interval planning condition is provided, and the wind power is safely consumed by the system.
In addition, the cascade hydropower dispatching and reservoir capacity dispatching integrated system comprehensively considers cascade hydropower dispatching and reservoir capacity dispatching, uniformly dispatches power generation resources and reservoir water resources, and improves reservoir capacity safety while guaranteeing system power supply safety.
Disclosure of Invention
The invention aims to provide a coordinated dispatching unit combination method for efficiently solving hydroelectric power-thermal power-wind power aiming at the defects of the prior art, and the method ensures that the combination result of the units of a power system meets the load requirement and ensures the tidal current safety of the system under the condition of wind power fluctuation.
The purpose of the invention is realized by the following technical scheme: a coordinated dispatching unit combination method for efficiently solving hydropower, thermal power and wind power comprises the following steps:
s1, receiving load demand data of a system in the future 24 hours and output prediction data of a wind power plant, which are obtained by a power dispatching center; receiving the storage capacity data of the cascade hydropower station and the natural inflow prediction data of each future time period; receiving system line parameters and parameters of a hydroelectric power generating unit and a thermal power generating unit; the specific data are as follows:
p i,t outputting the power of the thermal power generating unit i at the moment t; p is a radical of h,t The output power of the hydroelectric generating set h at the moment t is obtained; p is a radical of k,t Generating or storing energy for the energy storage unit k in a time period t; pw k,t The power output of the wind power plant k at the moment t is obtained; vs, t is the storage capacity of the reservoir s at the time t; nq (n q) j The natural water inflow of the reservoir j at the time t; s2, carrying out linear modeling on the unit combination problem of the power system, and selecting a target function and constraint conditions including equality constraint conditions and inequality constraint conditions according to the operation requirements to form a mixed integer linear programming problem;
s3, decomposing the mixed integer linear programming problem in the step 2 into a unit combination inspection subproblem without power flow constraint under the expected scene, a unit combination inspection subproblem with line power flow constraint under the expected scene, a unit combination inspection subproblem without power flow constraint under the worst scene and a unit combination inspection subproblem with line power flow constraint under the worst scene;
s4, solving the problem of the unit combination checker without the power flow constraint under the expected situation, and solving the start-stop sequence and the active power operating point of the generator unit, wherein the operating point represents the active power of the generator;
s5, bringing the unit operation point obtained in the step 4 into a unit combination syndrome problem containing line power flow constraint under an expected situation, and checking whether the power flow is out of limit; if the current constraints are all satisfied, entering the next step, otherwise, generating Benders cuts by using the current constraints which cannot be satisfied and returning to the step 4 as constraint conditions;
s6, bringing the starting and stopping sequence of the generator set in the step 4 into the problem of the combined checker without the power flow constraint unit under the worst condition for solving, if all constraint conditions are met, obtaining the unit operating point under the worst condition and entering the next step, and if not, using the Benders cut generated by the constraint which cannot be met as the constraint condition to return to the step 4;
s7, bringing the unit operation point under the worst scene obtained in the step 6 into a tester problem containing line power flow constraint under the worst scene, and testing whether the power flow is out of limit; if the current constraints are all satisfied, entering the next step, otherwise, generating Benders cuts by using the current constraints which cannot be satisfied and returning to the step 6 as constraint conditions;
s8, taking the unit combination result obtained in the step 4 as a generator unit scheduling scheme;
s9, in the step 1, determining the wind power output interval of the given confidence degree by using a function based on the prediction probability density;
s10, the objective function and the constraint conditions of the mixed integer linear equation in the step 2 and the constraint conditions of the 4 syndrome problems in the step 3 are as follows:
the objective function is to reduce the system power generation cost under the expected situation (wind power output is an expected value Pwf):
Figure GDA0003799058410000021
wherein F is the thermal power generation cost, ST is the thermal power start-stop cost, and N is g Number of thermal power generating units, N t The number of time sections for the combination of the units; because the hydroelectric power generation cost is very low, the power generation cost is not considered;
the constraints under the expected scenario are:
Figure GDA0003799058410000022
Figure GDA0003799058410000023
Figure GDA0003799058410000031
Figure GDA0003799058410000032
Figure GDA0003799058410000033
Figure GDA0003799058410000034
Q h,t ≥QS h (I h,t -I h,t-1 )，Q h,t ≥0 (8)
Figure GDA0003799058410000035
Figure GDA0003799058410000036
p h,t ＝f(q h,t ,V j,t ) (11)
Figure GDA0003799058410000037
Figure GDA0003799058410000038
Figure GDA0003799058410000039
Figure GDA00037990584100000310
where equation (2) is the system power balance constraint, p i,t Outputting the power of the thermal power generating unit i at the moment t; p is a radical of formula h,t The output power of the hydroelectric generating set h at the moment t is obtained; p is a radical of formula k,t The method is characterized in that the generated power or the stored power of an energy storage unit k in a t period is represented by a positive value, and the stored power is represented by a negative value; pl l,t Load for node l during time t; pw k,t The power output of the wind power plant k at the moment t is obtained; equation (3) is system line power flow constraint, and Ts represents a line power flow transmission distribution coefficient matrix; FL l Represents the maximum power flow that the line l can bear; equation (4) represents maximum and minimum output constraints of the hydroelectric generating set;I h,t the running state of the hydroelectric generating set h at the moment t is represented by 1, and the off-line state is represented by 0;P h 、
Figure GDA00037990584100000311
the minimum and maximum output allowed by the unit h; equation (5) represents the maximum and minimum water flow constraints of the hydroelectric generating set; q. q.s h,t The output power of the hydroelectric generating set h at the moment t is obtained;q h 、
Figure GDA00037990584100000312
the minimum and maximum water passing amount of the hydroelectric generating set h in unit time interval; equation (6) represents reservoir capacity constraints; vs, t is the storage capacity of the reservoir s at the time t;V s 、
Figure GDA0003799058410000041
the allowable reservoir capacity and upper limit of the reservoir s; equation (7) represents the remaining capacity constraint after scheduling is finished; v s,T+1 、V s,T+1 The upper limit and the lower limit of the residual storage capacity after the scheduling time interval is ended; equation (8) represents the hydro-power unit startup water usage, where Q h,t For the actual starting water consumption, QS, of the unit h at time t h The actual starting water consumption comprises starting water consumption and water abandoning amount; equation (9) represents the reservoir balance constraint, where nq j The natural water inflow of the reservoir j at the time t; reservoir j is the direct downstream reservoir of reservoir i, the water discharge of reservoir i being over a time interval Δ t i Reaches a reservoir j; equation (10) represents the maximum allowable discharge amount per unit time period of the reservoir, qv s The maximum allowable water discharge amount of the reservoir s in unit time interval; equation (11) represents the relationship between the output of the hydroelectric generating set and the water consumption and reservoir water level; equation (12) represents the thermal power unit output constraint; u. u i,t 1 represents an online state and 0 represents an offline state for the operation state of the thermal power generating unit i at the moment t;P i ，
Figure GDA0003799058410000042
the minimum and maximum output limits of the thermal power generating unit i are set; equation (13) represents the minimum start-stop time of the thermal power generating unitInter-constraint, T i,on 、T i,off For the unit i to have been continuously on-line and off-line time, T i,up 、T i,down The minimum continuous online and offline time of the unit i is set; equation (14) represents the thermal power unit climbing capability constraint, where Up i 、Dp i The maximum up-down climbing capacity of the generator set i in a period of time; SU i The maximum output is obtained in the first time period after the generator set i is started; SD i The maximum output of the generator set i in a period before shutdown;
the standby constraint conditions based on the worst scenario are:
Figure GDA0003799058410000043
Figure GDA0003799058410000044
Figure GDA0003799058410000045
Figure GDA0003799058410000046
Figure GDA0003799058410000047
Figure GDA0003799058410000048
Figure GDA0003799058410000049
Figure GDA00037990584100000410
Figure GDA00037990584100000411
Figure GDA0003799058410000051
Figure GDA0003799058410000052
Figure GDA0003799058410000053
Figure GDA0003799058410000054
the upper standard l (u) and the upper standard u (l) respectively correspond to the situation that the wind power output is the lower limit and the upper limit of the predicted interval; equations (15) - (18) are reserve for generating capacity to cope with wind uncertainty; equation (19) is for standby for the climbing capability to cope with the wind power uncertainty; equations (20) - (21) reserve line delivery capacity for wind uncertainty, when Ts>At time 0, TP max(min) ＝Ts×Pw u(l) (ii) a When Ts<At 0, TP max(min) ＝Ts×Pw l(u) (ii) a After specific decomposition, the objective function of the unit combination problem without the power flow constraint under the expected situation is equation (1), and the constraint conditions are equations (2), (4) - (14); the constraint condition corresponding to the line power flow syndrome problem under the expected situation is an equation (3); the constraint conditions corresponding to the unit combination syndrome problem without the power flow constraint under the worst condition are equations (15) - (19); the constraint conditions corresponding to the line flow verifier problem in the worst scenario are equations (20) - (21).
The method has the advantages that the combined result of the hydropower-thermal power-wind power coordinated dispatching unit can better absorb wind power, the economical efficiency and the safety of the system are improved, in addition, the solving speed is improved through a line trend simplifying method under the worst condition, and a solid foundation is laid for the application of the method in an actual power system.
Drawings
FIG. 1 is a wind farm output distribution probability graph;
FIG. 2 is an overall process flow;
FIG. 3 is an embodiment system;
FIG. 4 is a diagram of reservoir capacity overrun in a rich water period;
FIG. 5 is a system energy gap during dry season;
FIG. 6 is a system line power flow violation;
Detailed Description
The first step is as follows: receiving load demand data of a system in the future 24 hours obtained by a power dispatching center, wherein the output prediction data of the wind power plant comprises predicted wind power output and a probabilistic deviation interval; receiving the storage capacity data of the cascade hydropower station and the natural inflow prediction data of each future time period;
the output distribution of a general wind power plant is approximate to Gaussian distribution, as shown in figure 1; according to weather forecast and historical data, a predicted output Pwf of the wind power plant and an output interval [ Pwl, pwu ] with a confidence degree of alpha can be obtained, wherein alpha represents the probability that the output of the actual wind power plant is in the interval [ Pwl, pwu ];
the second step is that: carrying out linear modeling on the unit combination problem of the power system, and selecting a target function and constraint conditions including equality constraint conditions and inequality constraint conditions according to operation requirements to form a mixed integer linear programming problem;
the third step: decomposing the mixed integer linear programming problem in the second step into a unit combination inspection subproblem without flow constraint under a predicted scene, a line flow inspection subproblem under the predicted scene, a unit combination inspection subproblem without flow constraint under the worst scene and a line flow inspection subproblem under the worst scene;
the objective function of the unit combination syndrome problem without the power flow constraint under the predicted situation is the minimum running cost of the system under the predicted wind power output situation; the equality constraint comprises system node power balance constraint, cascade water and electricity storage capacity balance constraint, and cascade water and electricity output and storage capacity and water consumption balance constraint; the inequality constraints comprise maximum and minimum technical output constraints of the water and thermal power generating units, climbing constraints of the thermal power generating units, minimum starting and stopping time constraints of the thermal power generating units, upper and lower limit constraints of the storage capacity of the step hydroelectric reservoir and water discharge constraints of the step hydroelectric reservoir in unit time period;
the constraint condition of the line power flow checker problem under the expected situation is the line power flow under the expected situation;
the equality constraints of the syndrome problem without the power flow constraint under the worst condition comprise system node power balance constraints, step hydropower storage capacity balance constraints, step hydropower output, storage capacity and water consumption balance constraints; the inequality constraints comprise maximum and minimum technical output constraints of the hydroelectric power generating unit and the thermal power generating unit, climbing constraints of the thermal power generating unit, upper and lower limits of the storage capacity of the cascade hydroelectric water reservoir and water discharge constraints of the cascade hydroelectric water reservoir in unit time interval;
the constraint condition of the line power flow inspection sub-problem under the worst condition is the line power flow under the worst condition;
the fourth step: solving the problem of the unit combination syndrome checker which does not contain the power flow constraint under the predicted scene, and solving the starting and stopping sequence and the operating point of the generator unit under the predicted scene;
the fifth step: bringing the unit operating point obtained in the fourth step into a line power flow tester problem under an expected situation, and testing whether the power flow is out of limit; if the current constraints are all satisfied, entering the next step, otherwise, generating Benders cuts by using the current constraints which cannot be satisfied and returning to the fourth step as constraint conditions;
and a sixth step: bringing the starting and stopping sequence of the generator set in the fourth step into the problem of the combined checker without the power flow constraint unit under the worst condition for solving, if all constraint conditions are met, obtaining the unit operating point under the worst condition and entering the next step, and if not, using the Benders cut generated by the unsatisfiable constraint as the constraint conditions to return to the fourth step;
the seventh step: bringing the unit operation point under the worst scene obtained in the sixth step into a line power flow checker problem under the worst scene, and checking whether the power flow exceeds the limit; if the current constraints are all satisfied, entering the next step, otherwise, generating Benders cuts by using the current constraints which cannot be satisfied and returning to the sixth step as constraint conditions;
the constraint conditions are simplified by the line power flow syndrome problem under the worst condition; each wind power plant has 2 worst scenes (output is two endpoints of a prediction interval) in each time period, for a system with n wind power plants, 2n scenes need to be considered in each time period, the calculation amount of the scenes increases exponentially along with the increase of the wind power plants, and the calculation amount of the wind power plants is overlarge for a large-scale power system; the invention uses the simplified technology to ensure that only 2 extreme scenes are considered in each time interval, and the mathematical transformation of the line power flow constraint ensures the power flow safety of the system, thereby finally achieving the purpose of obviously reducing the calculated amount;
the eighth step: and taking the unit combination result obtained in the fifth step as a generator unit scheduling scheme, and determining a starting and stopping sequence and an operating point of the generator unit under the prediction scene so as to improve the overall economy and safety of the system.
Example (b):
the objective function is to reduce the system power generation cost under the expected situation (wind power output is an expected value Pwf):
Figure GDA0003799058410000071
wherein F is the thermal power generation cost, ST is the thermal power start-stop cost, and N is g Number of thermal power generating units, N t The number of time sections for unit combination; because the hydroelectric power generation cost is very low, the power generation cost is not considered;
the constraints under the expected scenario are:
Figure GDA0003799058410000072
Figure GDA0003799058410000073
Figure GDA0003799058410000074
Figure GDA0003799058410000075
Figure GDA0003799058410000076
Figure GDA0003799058410000077
Q h,t ≥QS h (I h,t -I h,t-1 )，Q h,t ≥0 (8)
Figure GDA0003799058410000078
Figure GDA0003799058410000079
p h,t ＝f(q h,t ,V j,t ) (11)
Figure GDA0003799058410000081
Figure GDA0003799058410000082
Figure GDA0003799058410000083
Figure GDA0003799058410000084
where equation (2) is the system power balance constraint, p i,t Outputting the power of the thermal power generating unit i at the moment t; p is a radical of formula h,t The output power of the hydroelectric generating set h at the moment t is obtained; p is a radical of k,t The method is characterized in that the generated power or the stored power of an energy storage unit k in a t period is represented by a positive value, and the stored power is represented by a negative value; pl l,t Load for node l during time t; pw k,t The power output of the wind power plant k at the moment t is obtained; equation (3) is system line power flow constraint, and Ts represents a line power flow transmission distribution coefficient matrix; FL l Represents the maximum power flow that the line l can bear; equation (4) represents maximum and minimum output constraints of the hydroelectric generating set; i is h,t The running state of the hydroelectric generating set h at the moment t is represented by 1, and the off-line state is represented by 0;P h 、
Figure GDA0003799058410000085
the minimum and maximum output allowed by the unit h; equation (5) represents the maximum and minimum water passing amount constraints of the hydroelectric generating set; q. q.s h,t The output power of the hydroelectric generating set h at the moment t;q h 、
Figure GDA0003799058410000086
the minimum and maximum water passing amount of the hydroelectric generating set h in unit time interval; equation (6) represents reservoir capacity constraints; vs, t is the storage capacity of the reservoir s at the time t;V s 、
Figure GDA0003799058410000087
the allowable reservoir capacity and upper limit of the reservoir s; equation (7) represents the remaining capacity constraint after scheduling is finished;
Figure GDA0003799058410000088
V s,T+1 the upper limit and the lower limit of the residual storage capacity after the scheduling time interval is ended; equation (8) represents the hydro-power unit startup water usage, where Q h,t For the actual starting water consumption, QS, of the unit h at time t h The actual starting water consumption comprises the starting water consumption and the abandoned water consumption; equation (9) represents the reservoir balance constraint, where nq j The natural water inflow of the reservoir j at the time t; reservoir j is the direct downstream reservoir of reservoir i, the water discharge of reservoir i being over a time interval Δ t i Reaches a reservoir j; equation (10) represents the maximum allowable discharge amount per unit time period of the reservoir, qv s The maximum allowable water discharge amount of the reservoir s in unit time interval; equation (11) represents the relationship between the output of the hydroelectric generating set and the water consumption and reservoir water level; equation (12) represents the thermal power unit output constraint; u. of i,t The method comprises the following steps that 1 is the running state of a thermal power generating unit i at the moment t, and represents an online state, and 0 represents an offline state;P i ，
Figure GDA0003799058410000089
the minimum and maximum output limits of the thermal power generating unit i are set; equation (13) represents the minimum on-off time constraint, T, for a thermal power unit i,on 、T i,off For the time that the unit i has been continuously online and offline, T i,up 、T i,down The minimum continuous online and offline time of the unit i is set; equation (14) represents the thermal power unit climbing capability constraint, wherein Up i 、Dp i The maximum up-down climbing capacity of the generator set i in a period of time; SU i The maximum output is obtained in the first time interval after the generator set i is started; SD i The maximum output of the generator set i in a period before shutdown;
the standby constraint conditions based on the worst scenario are:
Figure GDA0003799058410000091
Figure GDA0003799058410000092
Figure GDA0003799058410000093
Figure GDA0003799058410000094
Figure GDA0003799058410000095
Figure GDA0003799058410000096
Figure GDA0003799058410000097
Figure GDA0003799058410000098
Figure GDA0003799058410000099
Figure GDA00037990584100000910
Figure GDA00037990584100000911
Figure GDA00037990584100000912
Figure GDA00037990584100000913
the upper standard l (u) and the upper standard u (l) respectively correspond to the situation that the wind power output is the lower limit and the upper limit of the predicted interval; equations (15) - (18) are reserve for generating capacity to cope with wind uncertainty; equation (19) is for standby for the climbing capability to cope with the wind power uncertainty; equations (20) - (21) reserve line delivery capacity for wind uncertainty, when Ts>At 0, TP max(min) ＝Ts×Pw u(l) (ii) a When Ts<At time 0, TP max(min) ＝Ts×Pw l(u) 。
After specific decomposition (see fig. 2), the objective function of the unit combination problem without the power flow constraint under the expected situation is equation (1), and the constraint conditions are equations (2), (4) - (14);
the constraint condition corresponding to the line power flow checker problem under the expected situation is an equation (3); the constraint conditions corresponding to the unit combination syndrome problem without the power flow constraint under the worst condition are equations (15) - (19); the constraints corresponding to the line flow verifier problem in the worst scenario are equations (20) - (21). Firstly, solving a unit combination problem without power flow constraint under the expected scene, and substituting the unit operation points under the expected scene into a circuit power flow inspection subproblem under the expected scene. If the line power flow syndrome problem under the expected scene cannot be met, generating a corresponding Benders cut as a new constraint condition, adding the Benders cut into a unit combination problem without power flow constraint under the expected scene, and recalculating; and if all constraint conditions of the line power flow inspection subproblems under the expected scene are met, substituting the unit start-stop sequence obtained by the unit combination problem without the power flow constraint under the expected scene into the unit combination inspection subproblem without the power flow constraint under the worst scene. If the start-stop sequence can not meet the constraint condition of the unit combination syndrome problem without the power flow constraint under the worst situation by adjusting the operation point of the online unit, generating a corresponding Benders cut as a new constraint condition, adding the Benders cut into the unit combination problem without the power flow constraint under the expected situation, and recalculating; and if the constraint condition of the unit combination inspection subproblem which does not contain the power flow constraint under the worst scene is met, substituting the unit operation point under the worst scene, which is obtained by the unit combination inspection subproblem which does not contain the power flow constraint under the worst scene, into the line power flow inspection subproblem under the worst scene. If the constraint conditions of the line power flow checker problems under the worst condition cannot be met, generating a corresponding Benders cut as a new constraint condition, adding the Benders cut into a unit combination problem without power flow constraint under the worst condition, and recalculating; and if all constraint conditions of the line power flow inspection subproblems under the worst scene are met, outputting a set starting and stopping sequence and a set operation point which are obtained by a set combination problem without power flow constraint under the predicted scene as results.
The system (3 thermal power generating units, G1, G2 and G3; step hydropower stations H1 and H2; and wind power plants W1 and W2) in the invention is used for comparing the condition of the system when the wind power output deviates from the expected value by using the method in the invention and the traditional method. Compared with two typical seasons of a rich water period and a dry water period, the method provided by the invention and the traditional method (only the capacity of the hydroelectric generating set is scheduled without considering the reservoir capacity scheduling) are used, and the running condition of the system is realized when different wind power outputs are generated. Fig. 4 compares whether reservoir capacity violation occurs or not when wind power output changes according to the unit combination results of different methods in the rich water period, and it can be seen that the reservoir capacity standby is considered by the method provided by the invention to ensure the safety of the reservoir capacity of the cascade hydropower station in the rich water period. Fig. 5 compares the combination results of the units in different methods in the dry season with the system energy gap when the wind power output changes, and it can be seen that the method of the invention considers the reserve storage capacity of the reservoir to ensure that the cascade hydropower station reservoir in the dry season has sufficient storage capacity and hydraulic resources to generate power and ensure sufficient energy supply of the system. Fig. 6 compares whether line power flow overruns occur in the unit combination result system of different methods when wind power output changes, wherein the traditional unit combination result without considering line transmission capacity standby has obvious line power flow overruns to endanger the system safety, and the method of the invention ensures that the system power flow safety does not exceed the limits under various wind power output conditions.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.

Claims (3)

1. A coordinated dispatching unit combination method for efficiently solving hydroelectric power, thermal power and wind power is characterized by comprising the following steps:
s1, receiving load demand data of a system in the future 24 hours and output prediction data of a wind power plant, which are obtained by a power dispatching center; receiving the storage capacity data of the cascade hydropower station and the natural inflow prediction data of each future time period; receiving system line parameters and parameters of a hydroelectric power generating unit and a thermal power generating unit; the specific data are as follows:
p i,t outputting the power of the thermal power generating unit i at the moment t; p is a radical of h,t The output power of the hydroelectric generating set h at the moment t; p is a radical of formula k,t Generating or storing energy power of the energy storage unit k in a time period t; pw k,t The power output of the wind power plant k at the moment t is obtained; vs, t is the storage capacity of the reservoir s at the time t; nq (n q) j The natural water inflow amount of the reservoir j at the time t;
s2, carrying out linear modeling on the unit combination problem of the power system, and selecting a target function and constraint conditions including equality constraint conditions and inequality constraint conditions according to the operation requirements to form a mixed integer linear programming problem;
s3, decomposing the mixed integer linear programming problem in the step 2 into a unit combination inspection subproblem without power flow constraint under the expected scene, a unit combination inspection subproblem with line power flow constraint under the expected scene, a unit combination inspection subproblem without power flow constraint under the worst scene and a unit combination inspection subproblem with line power flow constraint under the worst scene;
s4, solving the problem of the unit combination checker without the power flow constraint under the expected situation, and solving the start-stop sequence and the active power operating point of the generator unit, wherein the operating point represents the active power of the generator;
s5, bringing the unit operation point obtained in the step 4 into a unit combination inspection subproblem containing line power flow constraint under an expected situation, and inspecting whether the power flow is out of limit or not; if the current constraints are all satisfied, entering the next step, otherwise, generating Benders cuts by using the current constraints which cannot be satisfied and returning to the step 4 as constraint conditions;
s6, bringing the starting and stopping sequence of the generator set in the step 4 into the problem of the combined checker without the power flow constraint unit under the worst condition for solving, if all constraint conditions are met, obtaining the unit operating point under the worst condition and entering the next step, and if not, using the Benders cut generated by the constraint which cannot be met as the constraint condition to return to the step 4;
s7, bringing the unit operation point under the worst scene obtained in the step 6 into a syndrome problem containing line power flow constraint under the worst scene, and checking whether the power flow is out of limit; if the power flow constraints are all satisfied, entering the next step, otherwise, generating Benders cuts by using the power flow constraints which cannot be satisfied and returning to the step 6 as constraint conditions;
and S8, taking the unit combination result obtained in the step 4 as a generator unit scheduling scheme.
2. The method for efficiently solving the coordinated scheduling unit combination method for the hydroelectric, thermal, electric and wind power generation units according to claim 1 is characterized in that in the step 1, the wind power output interval with a given confidence degree is determined by using a function based on a prediction probability density.
3. The method for efficiently solving the coordinated dispatching unit combination method for the hydroelectric power, the thermal power and the wind power as claimed in claim 1, wherein the objective function and the constraint condition of the mixed integer linear equation in the step 2 and the constraint conditions of the 4 syndrome problems in the step 3 are as follows:
the objective function is to reduce the system power generation cost under the expected scenario:
Figure FDA0003799058400000021
f is the thermal power generation cost, ST is the thermal power starting and stopping cost, ng is the number of thermal power generating units, and Nt is the number of combined time periods of the units; because the hydroelectric power generation cost is very low, the power generation cost is not considered;
the constraints under the expected scenario are:
Figure FDA0003799058400000022
Figure FDA0003799058400000023
Figure FDA0003799058400000024
Figure FDA0003799058400000025
Figure FDA0003799058400000026
Figure FDA0003799058400000027
Q h,t ≥QS h (I h,t -I h,t-1 )，Q h,t ≥0 (8)
Figure FDA0003799058400000028
Figure FDA0003799058400000029
p h,t ＝f(q h,t ,V j,t ) (11)
Figure FDA00037990584000000210
Figure FDA0003799058400000031
Figure FDA0003799058400000032
Figure FDA0003799058400000033
where equation (2) is the system power balance constraint, p i,t Outputting the power of the thermal power generating unit i at the moment t; p is a radical of formula h,t The output power of the hydroelectric generating set h at the moment t; p is a radical of formula k,t The method is characterized in that the generated power or the stored power of an energy storage unit k in a t period is represented by a positive value, and the stored power is represented by a negative value; pl l,t Load for node l during time t; pw k,t The power output of the wind power plant k at the moment t is obtained; equation (3) is system line power flow constraint, and Ts represents a line power flow transmission distribution coefficient matrix; FL l Represents the maximum power flow that the line l can bear; equation (4) represents the maximum and minimum output constraints of the hydroelectric generating set; I.C. A h,t The running state of the hydroelectric generating set h at the moment t is represented by 1, and the off-line state is represented by 0;P h 、
Figure FDA0003799058400000034
the minimum and maximum output allowed by the unit h; equation (5) represents the maximum and minimum water flow constraints of the hydroelectric generating set; q. q of h,t The output power of the hydroelectric generating set h at the moment t;q h 、
Figure FDA0003799058400000035
the minimum and maximum water passing amount of the hydroelectric generating set h in unit time interval; equation (6) represents reservoir capacity constraints; vs, t is the storage capacity of the reservoir s at the time t;V s 、
Figure FDA0003799058400000036
the allowable storage capacity and the upper limit of the reservoir s; equation (7) represents the remaining storage capacity constraint after scheduling is finished;
Figure FDA0003799058400000037
V s,T+1 the upper limit and the lower limit of the residual storage capacity after the scheduling time interval is ended; equation (8) represents the hydro-power unit startup water usage, where Q h,t For the actual starting water consumption, QS, of the unit h at time t h The actual starting water consumption comprises the starting water consumption and the abandoned water consumption; equation (9) represents the reservoir balance constraint, where nq j The natural water inflow of the reservoir j at the time t; reservoir j is the direct downstream reservoir of reservoir i, the water discharge of reservoir i being over a time interval Δ t i To reservoir j; equation (10) represents the maximum allowable discharge volume of the reservoir per unit time period, qv s The maximum allowable water discharge amount of the reservoir s in unit time interval; equation (11) represents the relationship between the output of the hydroelectric generating set and the water consumption and reservoir water level; equation (12) represents the thermal power unit output constraint; u. u i,t The method comprises the following steps that 1 is the running state of a thermal power generating unit i at the moment t, and represents an online state, and 0 represents an offline state; p is i ，
Figure FDA0003799058400000038
The minimum and maximum output limits of the thermal power generating unit i are set; equation (13) represents the minimum on-off time constraint, T, of the thermal power generating unit i,on 、T i,off For the time that the unit i has been continuously online and offline, T i,up 、T i,down The minimum continuous online and offline time of the unit i is set; equation (14) represents the thermal power unit climbing capability constraint, wherein Up i 、Dp i The maximum up-down climbing capacity of the generator set i in a period of time; SU i The maximum output is obtained in the first time interval after the generator set i is started; SD i The maximum output is obtained in a period before the power generator set i is shut down;
the standby constraint conditions based on the worst scenario are:
Figure FDA0003799058400000041
Figure FDA0003799058400000042
Figure FDA0003799058400000043
Figure FDA0003799058400000044
Figure FDA0003799058400000045
Figure FDA0003799058400000046
Figure FDA0003799058400000047
Figure FDA0003799058400000048
Figure FDA0003799058400000049
Figure FDA00037990584000000410
Figure FDA00037990584000000411
Figure FDA00037990584000000412
Figure FDA00037990584000000413
the upper scale l (u) and the upper scale u (l) respectively correspond to the situation that the wind power output is the lower limit and the upper limit of the predicted interval; equations (15) - (18) are reserve for generating capacity to cope with wind uncertainty; equation (19) is a reserve for the climbing capability to cope with wind power uncertainty; equations (20) - (21) reserve line delivery capacity for wind uncertainty, when Ts>At 0, TP max(min) ＝Ts×Pw u(l) (ii) a When Ts<At 0, TP max(min) ＝Ts×Pw l(u) (ii) a After specific decomposition, the objective function of the unit combination problem without the power flow constraint under the expected situation is equation (1), and the constraint conditions are equations (2), (4) - (14); the constraint condition corresponding to the line power flow syndrome problem under the expected situation is an equation (3); the constraint conditions corresponding to the unit combination syndrome problem without the power flow constraint under the worst condition are equations (15) - (19); the constraints corresponding to the line flow verifier problem in the worst scenario are equations (20) - (21).
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