CN112636340A - Optimized operation method of wind power-pumped storage combined power generation system - Google Patents
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Abstract
The invention discloses an optimized operation method of a wind power-pumped storage combined power generation system, which specifically comprises the following steps: establishing a wind power-pumped storage combined operation model; establishing a wind power-pumped storage combined output power minimum fluctuation optimization target; establishing a wind power-pumped storage optimal economic model considering peak-valley electricity prices; establishing a wind energy maximum utilization rate optimization target; determining constraint conditions of a wind power-pumped storage combined operation model; and determining a coordination scheme under the priority order of the optimization targets. On the basis of analyzing the significance and the principle of the combined power generation of the wind power generation and the pumped storage power station, the optimization objectives of maximizing the energy utilization rate of the wind power generation, minimizing the grid-connected power fluctuation and maximizing the economic benefit of the combined power generation are established, and the wind power-pumped storage combined power generation three-objective optimization model is established, so that the operation scheme has the best comprehensive benefit and performance.
Description
Technical Field
The invention belongs to the technical field of power system optimization, and particularly relates to an optimized operation method of a wind power-pumped storage combined power generation system.
Background
The wind power-pumped storage combined power generation system comprises two parts of wind power generation and pumped storage power generation. In recent years, wind energy has become a hot spot of renewable energy research in various countries. However, because wind energy has the characteristics of intermittence and randomness, the output power of the wind power generation system fluctuates greatly along with the change of the wind energy, and at the moment, if the power grid is directly connected with the wind power with large specific gravity, the safe and stable operation of the power grid is influenced. In order to convert wind power with large specific gravity into high-quality electric energy to be input into a power grid, the method of combining wind power and pumped storage for power generation is a better method.
Related research on wind power-water pumping and energy storage in China is in a state of rapid research and development at present. In China, a lot of intensive research is carried out in the technical field, and under the unified control of a power grid, a wind power-pumped storage operation optimization model is provided by Kaitong and the like of Huazhong science and technology university to find an optimal method to use wind power to the maximum extent so as to ensure that the air abandonment amount under the peak valley price is minimum and the economic benefit is maximum. Analysis shows that in different wind power plants, the best scheduling scheme is researched by calculation through simulating a wind power-pumped storage operation mode, so that the efficiency of the system is improved, and the stability is improved. Overseas related researchers believe that pumped storage can reduce the cost of power production through non-dynamic analysis based on the electrical system. Comparing and simulating three models by Shuxu, Deng Changhong, Huang Du and the like proves that the frequency of a large-scale wind power generation network can be inhibited from being greatly reduced by effectively utilizing the wind energy-pumped storage combined operation.
Besides the need to adopt a certain method to meet the stability requirement of the combined operation system, the optimization of other related systems is also needed. Relevant researchers carry out corresponding optimization aiming at large-scale production of wind power-pumped storage combined operation. In order to maximize the benefit of combined operation, the optimization scheme performs peak clipping and valley filling through pumped storage, and performs corresponding example calculation after adopting mixed integer linear programming analysis.
The method has more or less defects in the aspects of comprehensively considering wind power utilization maximization, grid-connected power fluctuation minimization and combined power generation economic benefit maximization, and is difficult to meet the constraint conditions of power balance of a generator set and a power grid and the like. The wind power-pumped storage combined power generation system needs to operate under stable, reliable and safe conditions, and needs to consider the conditions of economic cost and benefit to ensure the continuity and stability of the output electric energy of the combined power generation system. Part of the research results fall into the problem of local optimization, and most of the research uses a single target for optimization, and although a more reasonable performance optimization scheme can be obtained, based on the contradiction between targets (such as economy and reliability), obviously more targets need to be considered.
Disclosure of Invention
Based on the defects of the prior art, the technical problem solved by the invention is to provide an optimized operation method of a wind power-pumped storage combined power generation system, which solves the difficult problem that wind power generation has instability and volatility due to randomness and instability of wind energy, and a pumped storage power station is additionally built near a wind power generation field, so that on one hand, the utilization efficiency of the wind energy can be improved, on the other hand, the power output of the wind power generation can be smoothed, and the power of the wind power generation can be conveniently accessed to the network; the method comprises the steps of minimizing the fluctuation of the wind power-pumped storage combined output power, considering the peak-valley electricity price, optimizing targets such as a wind energy utilization rate maximization target and the like, and meeting constraint conditions such as a generator set and power grid power balance and the like, and converting a combined operation optimization problem into a multi-objective constraint optimization problem to solve.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention discloses an optimized operation method of a wind power-pumped storage combined power generation system, which specifically comprises the following steps:
and 6, determining a coordination scheme under the priority order of each optimization target.
Further, in the step 2, the standard deviation of the output power is adopted to measure the fluctuation of the output power of the wind power-pumped storage combined power generation system, so as to establish an optimization target as follows:
in the formula: f1Representing a first objective function, PeiFor combined power system grid-connected power, PeiavgIs the average thereof; sigmapIs the smoothness of the output power of the combined power generation system, and the smaller the numerical value, the higher the smoothness.
Further, in the step 4, in order to maximize the utilization rate of wind energy, the wind power generation utilization rate is defined as the ratio of the wind power generation power utilized in the wind power-pumped storage combined power generation optimal scheduling period to the available wind power, and is recorded as RWindThe calculation formula is as follows:
in the formula: pWindused(t) and PWindmax(t) the wind power generation power used at the moment t and the maximum power which can be output by the wind power station are respectively, the wind power utilization rate is taken as a target, the discretization is carried out, and the target function can be obtained as follows:
in the formula: f3Representing a third objective function, PviRepresenting the available wind energy of the wind farm during the period i; pDLiRepresenting wind power rejected during the i-th period.
Further, in the step 5, in the wind power-pumped storage combined generation operation optimization model, the optimization variables must meet the relevant constraint conditions; the constraints are divided into equality constraints and inequality constraints, wherein equality constraints are shown in the following first formula, and another inequality constraint is shown in the following second formula:
in the formula: pwi、Ppi、PhiRespectively corresponding to the power of the ith time interval of the point; pgRepresenting installed capacity of a wind farm; eiRepresenting the reservoir energy storage of the ith time period; etaPThe water pumping efficiency of the water pump is shown; etahRepresenting the efficiency of hydroelectric generation; t represents each period length; pmin、PmaxRespectively representing the minimum output power and the maximum output power of the wind power plant; pgmin、PmaxRespectively representing the minimum installed capacity and the maximum installed capacity of the wind power plant; phmin、PhmaxRespectively representing the minimum and maximum power of the hydroelectric generation; ppmin、PPmaxRespectively representing the minimum and maximum water pumping of the water pump; emaxIndicating maximum of reservoirStoring energy;
in the model, n is 24, i.e. representing that the optimized simulation duration is 24 periods of a day, and the power P can be seen from the above two formulaswi、Phi、PPi(1. ltoreq. i.ltoreq.24) are not independent variables, and they are restricted with each other;
when the original wind energy available in the wind power plant is known, the power P of the pumping unit in each time period in the optimization cycle can be determined according to the constraint conditions of the power grid and the pumping unit power listed in the above two formulasPiThen by P of each time intervalPiThe generated power P of the fan in each time interval can be obtained by calculationwi(ii) a Finally, can be represented by PPiAnd PwiCan find each time interval PhiThe value range of (a);
the optimal scheduling model of the wind power-pumped storage combined power generation is obtained as shown in the following formula:
therefore, the optimized operation method of the wind power-pumped storage combined power generation system provided by the invention at least has the following beneficial effects:
1. in order to solve the difficult problem that wind power generation has instability and volatility due to randomness and instability of wind energy, a pumped storage power station is additionally built near a wind power generation field, so that the utilization efficiency of the wind energy can be improved, the power output of the wind power generation can be smoothed, and the power grid of the wind power generation is convenient.
2. The wind power plant and the pumped storage power station form a combined power generation system, so that the combined power generation system can play a role of peak clipping and valley filling, namely, the residual electric energy is stored through pumped storage in the low-price valley period, and is converted into electric energy to be transmitted to a power grid user when the electricity price is in the high-price peak period, the wind power output power can be smoother, and the economic benefit of the power generation system can be improved.
3. Compared with other optimization scheduling schemes, the method has better smoothing effect on the output power, is only inferior to the optimization scheme which singly aims at smoothness, and is only inferior to the optimization scheme which singly aims at economic benefit, but can obtain the maximum wind energy utilization rate in all schemes, and the maximum wind energy utilization rate can reach 96.6 percent, so that the method has good comprehensive benefit and performance and high feasibility.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood, the present invention may be implemented in accordance with the content of the description, and in order to make the above and other objects, features, and advantages of the present invention more clearly understood, the following detailed description is given in conjunction with the preferred embodiments, together with the accompanying drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments will be briefly described below.
FIG. 1 is a model diagram of the combined operation of a wind power-pumped storage power station of the present invention;
FIG. 2 is a graph of wind energy available from a wind farm;
FIG. 3 is a graph of the output power of various portions of the combined power generation system;
FIG. 4 is a graph of the output power of the cogeneration system at different destinations.
Detailed Description
Other aspects, features and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which form a part of this specification, and which illustrate, by way of example, the principles of the invention. In the referenced drawings, the same or similar components in different drawings are denoted by the same reference numerals.
Referring to fig. 1-4, the optimal operation method of the wind power-pumped storage combined power generation system specifically comprises the following steps:
A wind power-pumped storage combined power generation system is formed by configuring a pumped storage power station for a wind power station, as shown in figure 1. When the wind energy is surplus, the surplus electric energy output by the wind generation set is used for the water pumping set to pump the water in the lower reservoir to the upper reservoir, and the surplus wind energy is converted into the gravitational potential energy of the water to be stored. And when the wind energy can not completely meet the load demand at the peak of power utilization, the water stored in the upper reservoir can be utilized to drive the hydroelectric generating set of the pumped storage power station to generate power, so that the fluctuation of the wind power output power is well inhibited, and the wind energy is time-shifted, so that greater economic benefit can be obtained.
Measuring the fluctuation of the output power of the wind power-pumped storage combined power generation system by adopting the standard deviation of the output power, and establishing an optimization target as the formula (1):
in the formula: f1Representing a first objective function, PeiFor combined power system grid-connected power, PeiavgIs the average thereof; sigmapIs the smoothness of the output power of the combined power generation system, and the smaller the numerical value, the higher the smoothness.
If the available wind energy of the location of the wind power plant is known, and the optimal economic benefit of the wind power-pumped storage power station combined power generation system within 24 hours a day is taken as a target, an optimization model is established according to the formula (2):
in the formula: f2Representing a second objective function, PwFor power P of wind-driven generator setpPower P for pumping water of water pumphFor hydroelectric power, Pwi、Ppi、PhiAre respectively corresponding toPower of point ith period; c represents the price of power on the Internet, CiThe electricity price in the ith time period; cpRepresents the cost of the electric energy consumed by the water pumping unit, CPiIs the cost of the ith time period. Considering the difference of the wind power peak-valley electricity prices, the prices in different periods are determined as follows:
CPi＝0.25Ci (3)
In order to improve the utilization rate of wind energy to the maximum extent, the wind power generation utilization rate is defined as the proportion of the wind power generation power utilized in the wind power-pumped storage combined power generation optimization scheduling period to the available wind energy, and is recorded as RWindThe calculation formula is shown as formula (4):
in the formula: pWindused(t) and PWindmaxAnd (t) respectively representing the wind power generation power utilized at the moment t and the maximum power which can be output by the wind power station, and discretizing the formula (4) by taking the wind power utilization rate as a target to obtain a target function as shown in the formula (5).
In the formula: f3Representing a third objective function, PviRepresenting the available wind energy of the wind farm during the period i; pDLiRepresenting wind power rejected during the i-th period.
In the wind power-pumped storage combined generation operation optimization model, optimization variables must meet related constraint conditions. The constraints are divided into equality constraints and inequality constraints, wherein equality constraints are shown in formula (6), and another inequality constraints are shown in formula (7).
In the formula: pgRepresenting installed capacity of a wind farm; eiRepresenting the reservoir energy storage of the ith time period; etaPThe water pumping efficiency of the water pump is shown; etahRepresenting the efficiency of hydroelectric generation; t represents each period length; pmin、PmaxRespectively representing the minimum output power and the maximum output power of the wind power plant; pgmin、PmaxRespectively representing the minimum installed capacity and the maximum installed capacity of the wind power plant; phmin、PhmaxRespectively representing the minimum and maximum power of the hydroelectric generation; ppmin、PPmaxRespectively representing the minimum and maximum water pumping of the water pump; emaxIndicating the maximum energy stored in the reservoir.
The model has n of 24, which represents that the optimization simulation duration is 24 periods of a day. From the expressions (6) and (7), the power P can be seenwi、Phi、PPi(1. ltoreq. i.ltoreq.24) are not independent variables, and they are restricted to each other.
When the original wind energy available in the wind power plant is known, the power P of the water pumping unit in each time period in the optimization cycle can be determined according to the power constraint conditions of the power grids listed in the formulas (6) and (7) and the constraint conditions of the power of the water pumping unitPiThe value range of (a). Then by P of each time intervalPiThe generated power P of the fan in each time interval can be obtained by calculationwi. Finally, can be represented by PPiAnd PwiCan find each time interval PhiThe value range of (a).
And (3) integrating the formulas (1) to (7), and obtaining an optimal scheduling model of wind power-pumped storage combined power generation as shown in a formula (8).
S.T.
Taking a certain wind power-pumped storage combined operation system as an example, a multi-objective optimization model is established, and the model is solved.
1. Can use original wind energy
The raw wind energy available to the wind farm refers to the power generated by the wind farm when the wind farm is not equipped with any energy storage device, as shown in FIG. 2.
Because the invention mainly researches the problem of optimizing and scheduling the fan power and the pumped storage power in the wind power-pumped storage combined power generation system, how to obtain the wind speed data and the data of the initial power of the fan is not the key consideration of the invention, the wind energy which can be used by the wind power plant is assumed to be known in the example analysis used by the invention, and a normal distribution curve (the average value is assumed to be 6MW, and the variance is 4MW) is used for carrying out approximate simulation on the curve shown in FIG. 2.
2. Wind farm output power
Currently, national interconnection of power grids is being prepared in China, and the scale of the power grids is getting larger and larger. The proportion of the capacity of the grid-connected wind power plant in the total installed capacity of the power grid is not large, so that the influence of the input of the wind power on the power grid is not large. Meanwhile, the population quantity of a place with relatively rich wind energy resources is relatively small, the electric power load is relatively small, the power grid structure is relatively simple, and the tidal current distribution of the power grid can be changed due to the input of wind power, so that a local power grid can be greatly influenced, and the wind power grid becomes an important problem for restricting the scale of a wind power plant. At the same time, the uncontrollable power capacity is gradually increased in the power system, so that the method is suitable for some power systemsIn the case of a blocked network branch, which is also a reason for the large grid to accept less wind power, some limitations of the power exchange between the wind farm and the grid are generally considered when discussing the wind power operation method. There is also a need in the power market for improving and enhancing controllability of wind power output, and for improving the market share of the energy in the power system with respect to the amount of energy. Because the limit of the power grid and the market demand and other aspects need to be considered, the power limit transmitted to the power grid by the wind power plant is set in advance, the output power of the wind power plant is set to be P, and the limit power of the power grid is set to be PlWind farm installed capacity is set to PgThen there is Pmin≤P≤Pmax. At the same time, the wind farm is also limited by the installation capacity of the wind farm when delivering power to the grid, i.e. Pgmin≤P≤Pgmax。
3. Model parameter setting
The invention assumes that the initial energy storage E1 of the reservoir is 0, and the power limit of the power grid is 3 MW-PiLess than or equal to 8MW, and the original wind energy P capable of being used by wind power plantVThe approximate simulation was performed by the random normal distribution curve shown in fig. 2, and the settings of the relevant model parameters are shown in table 1 below.
TABLE 1 model parameters
4. Analysis of simulation results
(1) Scheduling scheme comparison
In the simulation result, the optimal solution corresponding point is the corresponding optimal scheduling scheme, and the power P of the wind generating set is obtainedwWater pump water pumping power PpHydroelectric power PhAnd the grid-connected power P of the combined power generation systemeIn the optimizationThe variation over the period is shown in fig. 3.
In order to embody the advantages of the three-target optimization scheme established by the invention, the results are correspondingly compared with the results of single-target optimization and double-target optimization. Under the scheduling scheme obtained by various optimization targets, the output power change curve of the wind power-pumped storage combined power generation system is shown in fig. 4.
In fig. 4, a curve F1 represents a curve in which only the system output power fluctuation target is considered, a curve F2 represents a curve in which only the system power generation economic benefit target is considered, a curve F12 represents a curve in which both the output power fluctuation target and the economic benefit target are considered, and a curve F123 represents a curve in which the three targets of the output power fluctuation target, the economic benefit target, and the wind energy utilization rate target are considered in combination.
In order to better represent the difference of output power fluctuation of the wind power-pumped storage combined power generation system under different optimization targets, the optimization results of the wind power-pumped storage combined power generation system under different optimization targets can be obtained according to the calculation formula of each index, as shown in table 2.
TABLE 2 comparison of Performance indicators
(2) Conclusion
After a wind power plant and a pumped storage power station form a combined power generation system, no matter single-target, double-target or three-target optimization, the combined power generation system can play a role of peak clipping and valley filling, namely, the residual electric energy is stored through pumped storage in the low price valley period, and is converted into electric energy to be transmitted to a power grid user after the high price peak period, so that the wind power output power is smoother, and the economic benefit of the power generation system can be improved.
Secondly, scheduling schemes which respectively and independently take power smoothing and economic benefit as targets have emphasis, optimization schemes of the power smoothing and economic benefit are considered at the same time, and the output power fluctuation and economic benefit optimization result is between two single-target optimization results. And the three-target optimized scheduling scheme of wind energy utilization is considered at the same time, compared with other three optimized scheduling schemes, the smooth effect on the output power is better, the economic benefit is only second to the optimized scheme which takes smoothness as the target alone, and the economic benefit is only second to the optimized scheme which takes economic benefit as the target alone, but the maximum wind energy utilization rate in all the schemes can be obtained, and the maximum wind energy utilization rate can reach 96.6%. Therefore, in conclusion, the three-target optimization operation scheme provided by the invention has the best comprehensive benefit and performance.
On the basis of analyzing the significance and the principle of the combined power generation of the wind power generation and the pumped storage power station, the optimization target is the maximization of the energy utilization rate of the wind power generation, the minimization of the grid-connected power fluctuation and the maximization of the economic benefit of the combined power generation, and the problems of constraint conditions and the like in the aspects of power balance of a wind power generator set and a power grid are considered, so that a wind power-pumped storage combined power generation three-target optimization model is established. And (3) carrying out example analysis on the established three-target optimization model for wind power-pumped storage combined operation, and verifying that the three-target optimization operation scheme has the best comprehensive benefit and performance.
While the foregoing is directed to the preferred embodiment of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Claims (4)
1. An optimized operation method of a wind power-pumped storage combined power generation system is characterized by comprising the following steps:
step 1, establishing a wind power-pumped storage combined operation model;
step 2, establishing a wind power-pumped storage combined output power minimum fluctuation optimization target;
step 3, establishing a wind power-pumped storage optimal economic model considering peak-valley electricity prices;
step 4, establishing a wind energy maximum utilization rate optimization target;
step 5, determining constraint conditions of the wind power-pumped storage combined operation model;
and 6, determining a coordination scheme under the priority order of each optimization target.
2. The method for optimizing the operation of the wind-pumped storage combined power generation system according to claim 1, wherein in the step 2, the standard deviation of the output power is used to measure the fluctuation of the output power of the wind-pumped storage combined power generation system, so as to establish the optimization objective as follows:
in the formula: f1Representing a first objective function, PeiFor combined power system grid-connected power, PeiavgIs the average thereof; sigmapIs the smoothness of the output power of the combined power generation system, and the smaller the numerical value, the higher the smoothness.
3. The method for optimizing the operation of a wind-pumped storage combined power generation system according to claim 2, wherein in step 4, in order to maximize the utilization rate of wind energy, the wind power utilization rate is defined as the ratio of the wind power generation power utilized in the optimal scheduling period of wind-pumped storage combined power generation to the available wind power, which is denoted as RWindThe calculation formula is as follows:
in the formula: pWindused(t) and PWindmax(t) the wind power generation power used at the moment t and the maximum power which can be output by the wind power station are respectively, the wind power utilization rate is taken as a target, the discretization is carried out, and the target function can be obtained as follows:
in the formula: f3Representing a third objective function, PviRepresenting the available wind energy of the wind farm during the period i; pDLiRepresenting wind power rejected during the i-th period.
4. The method for optimizing the operation of the wind power-pumped storage combined power generation system according to claim 1, wherein in the step 5, in the wind power-pumped storage combined power generation operation optimization model, the optimization variables must satisfy the relevant constraint conditions; the constraints are divided into equality constraints and inequality constraints, wherein equality constraints are shown in the following first formula, and another inequality constraint is shown in the following second formula:
in the formula: pwi、Ppi、PhiRespectively corresponding to the power of the ith time interval of the point; pgRepresenting installed capacity of a wind farm; eiRepresenting the reservoir energy storage of the ith time period; etaPThe water pumping efficiency of the water pump is shown; etahRepresenting the efficiency of hydroelectric generation; t represents each period length; pmin、PmaxRespectively representing the minimum output power and the maximum output power of the wind power plant; pgmin、PmaxRespectively representing the minimum installed capacity and the maximum installed capacity of the wind power plant; phmin、PhmaxRespectively representing the minimum and maximum power of the hydroelectric generation; ppmin、PPmaxRespectively representing the minimum and maximum water pumping of the water pump; emaxRepresenting the maximum energy storage of the reservoir;
in the model, n is 24, i.e. representing that the optimized simulation duration is 24 periods of a day, and the power P can be seen from the above two formulaswi、Phi、PPi(1. ltoreq. i.ltoreq.24) are not independent variables, and they are restricted with each other;
when the original wind energy available in the wind power plant is known, the power P of the pumping unit in each time period in the optimization cycle can be determined according to the constraint conditions of the power grid and the pumping unit power listed in the above two formulasPiThen by P of each time intervalPiThe generated power P of the fan in each time interval can be obtained by calculationwi(ii) a Finally, can be represented by PPiAnd PwiCan find each time interval PhiThe value range of (a);
the optimal scheduling model of the wind power-pumped storage combined power generation is obtained as shown in the following formula:
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113392506A (en) * | 2021-05-21 | 2021-09-14 | 苏州市排水有限公司 | Optimal configuration method for regional sewage pump station joint scheduling based on flow |
| CN114109725A (en) * | 2021-11-22 | 2022-03-01 | 吕艾龙 | Novel comprehensive equipment and method for full-wind power generation and wind energy storage power generation |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104362671A (en) * | 2014-10-27 | 2015-02-18 | 国家电网公司 | Multi-objective optimization coordination method for combined supply of large-scale wind power and pumped storage |
| CN106602591A (en) * | 2015-10-20 | 2017-04-26 | 上海交通大学 | Seawater pumped storage wind power combination control method for multi-target optimized control |
| CN111431213A (en) * | 2020-03-13 | 2020-07-17 | 郑州大学 | Plant network coordination method for exciting combined operation of wind power plant and pumped storage power station and combined scheduling method thereof |
-
2020
- 2020-12-11 CN CN202011458849.5A patent/CN112636340A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104362671A (en) * | 2014-10-27 | 2015-02-18 | 国家电网公司 | Multi-objective optimization coordination method for combined supply of large-scale wind power and pumped storage |
| CN106602591A (en) * | 2015-10-20 | 2017-04-26 | 上海交通大学 | Seawater pumped storage wind power combination control method for multi-target optimized control |
| CN111431213A (en) * | 2020-03-13 | 2020-07-17 | 郑州大学 | Plant network coordination method for exciting combined operation of wind power plant and pumped storage power station and combined scheduling method thereof |
Non-Patent Citations (1)
| Title |
|---|
| 盛四清等: "风电-抽水蓄能联合运行优化模型", 《电力***及其自动化学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113392506A (en) * | 2021-05-21 | 2021-09-14 | 苏州市排水有限公司 | Optimal configuration method for regional sewage pump station joint scheduling based on flow |
| CN114109725A (en) * | 2021-11-22 | 2022-03-01 | 吕艾龙 | Novel comprehensive equipment and method for full-wind power generation and wind energy storage power generation |
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