CN107994609A - Consider the spare setting method of wind-electricity integration and device of compressed-air energy storage - Google Patents
Consider the spare setting method of wind-electricity integration and device of compressed-air energy storage Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H—ELECTRICITY
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Abstract
The present invention proposes a kind of spare setting method of wind-electricity integration and device for considering compressed-air energy storage, wherein, method includes：Wind-powered electricity generation processing is predicted according to wind-powered electricity generation historical data, structure wind-powered electricity generation does not know to gather；Power generation capacity-constrained, power-balance constraint, transmission trend constraint and the reserve level that obtaining electric system each period need to meet constrain；Obtain the units limits and energy storage energy constraint of compressed-air energy-storage system each period；Obtain the minimum cost objective function of the electric system；Structure considers that the robust of compressed-air energy storage is spare and adjusts model；Model is adjusted using mixed integer linear programming conversion and the C＆CG derivation algorithms solution robust are spare, acquisition considers that the robust of compressed-air energy storage is spare and adjusts strategy.This method have give full play to compressed-air energy storage can equivalent increase system spinning reserve characteristic, improve system safety, lifted maintenance level the advantages of.
Description
Technical Field
The invention relates to the technical field of new energy grid-connected scheduling, in particular to a wind power grid-connected standby setting method and device considering compressed air energy storage.
Background
With the continuous deepening of the market reformation of the electric power and the continuous improvement of the power consumption demand of the terminal user, the electric power industry faces unprecedented challenges, and the development of a new generation of smart power grids becomes a necessary choice for the electric power industry to respond to the challenges and develop innovation. However, the explosion of the smart grid also brings the transition of a plurality of fields such as operation, scheduling, control, communication and the like to the traditional power system. On the power generation side, access of large-scale renewable energy sources such as solar energy, wind energy and the like in a power grid is mainly used, so that the uncertainty of power generation is increased, and the challenge is provided for the reliability and safety of the power grid. According to statistics, as of 2014, the installed capacity is increased by 23,196MW in China, the year by year is increased by 44.17%, the installed capacity accounts for 45.36% of the newly increased installed capacity in the current year, and the global ranking is the first. In 2014, the total accumulated wind power installed capacity of China is 114,609MW, which accounts for 31.01 percent of the global accumulated wind power installed capacity and is the third large energy source except for thermal power and hydropower. The development of wind power generation has important significance in meeting energy supply, promoting regional economic development, improving energy structure, saving energy, reducing emission and the like. However, wind energy has intermittency, volatility and randomness, so that energy cannot be stably and continuously output, and difficulties are brought to dispatching personnel of a power system. In real-time scheduling, special reasons such as weather changes and sudden load changes can cause certain impact on real-time scheduling. Therefore, the unit output must be corrected within the day according to the actual operating conditions. It is common practice to reserve a certain spare capacity to prevent sudden impacts in the given case of a day ahead unit combination. The current mainstream standby modes include two types:
and (4) making independent decisions on power generation and standby, wherein the output of the unit is given by an optimal power flow or economic dispatching result, and the standby is set according to a certain criterion and issued for execution. The advantage is decoupling power generation and backup scheduling, and the disadvantage is that economy cannot be optimized. However, with the access of large-scale renewable energy sources such as wind energy, the safety of the power system cannot be guaranteed only by setting with the traditional method due to high uncertainty and low prediction precision.
The method is characterized in that a power generation plan and backup setting are considered as a whole, various constraints are integrated, the optimization problems of power generation and backup are unified into a combined economic dispatching problem, the operation point setting capable of guaranteeing the safety of wind power in each scene is given through robust dispatching, and the method is limited by the adjustable range of system backup. With the rapid development of energy storage technology, especially compressed air energy storage, a new opportunity is provided for the standby setting problem. The compressed air energy storage has a synchronous power generation system with adjustable power and voltage, the response is rapid, the mass application of the system can equivalently increase the system rotation for standby, and the system safety and stability level is improved.
Disclosure of Invention
The present invention is directed to solving, at least in part, one of the technical problems in the related art.
Therefore, the invention aims to provide a wind power grid-connected standby setting method considering compressed air energy storage, which can fully exert the characteristic that the compressed air energy storage can equivalently increase the system rotation standby and improve the system safety and stability level.
The invention aims to provide a wind power grid-connected standby setting device considering compressed air energy storage.
In order to achieve the above object, an embodiment of one aspect of the present invention provides a wind power grid-connected standby setting method considering compressed air energy storage, including the following steps: predicting wind power processing according to wind power historical data, and constructing a wind power uncertain set; acquiring a power generation capacity constraint, a power balance constraint, a transmission flow constraint and a standby quantity constraint which need to be met by each time interval of a power system; acquiring output constraint and energy storage constraint of the compressed air energy storage system in each time period; acquiring a minimum cost objective function of the power system; constructing a robust standby setting model considering compressed air energy storage; and solving the robust backup setting model by using a mixed integer linear programming conversion and C & CG solving algorithm to obtain a robust backup setting strategy considering compressed air energy storage.
According to the wind power grid-connected standby setting method considering compressed air energy storage, the minimum cost objective function of the power system can be obtained by constructing the wind power uncertain set and obtaining the constraint conditions such as the power generation capacity constraint, the power balance constraint, the transmission power flow constraint, the standby amount constraint, the output constraint and the energy storage energy constraint of the compressed air energy storage system in each period of the power system, and then constructing the robust standby setting model considering compressed air energy storage, and finally obtaining the robust standby setting strategy considering compressed air energy storage, so that the characteristic that the compressed air energy storage can equivalently increase the system rotation standby can be fully exerted, and the system safety and the operation stability level can be effectively improved.
In addition, the wind power grid-connected standby setting method considering compressed air energy storage according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the invention, the wind power uncertain set is constructed, and the method further comprises the steps of giving the upper and lower wind power outputs based on a normal distribution function, and giving the uncertain budget considering the time smoothing effect and the uncertain budget considering the space clustering effect respectively based on a central limit theorem and a probability inequality.
Further, in an embodiment of the present invention, the obtaining a minimized cost objective function of the power system further includes: and setting an upper layer objective function taking the minimized cost as a target and a lower layer objective function taking the minimized standby cost as a target of the power system standby setting model, and constructing a min-max-min three-layer model.
Further, in an embodiment of the present invention, the min-max-min three-layer model further includes:
the mathematical expression of the objective function of the upper layer problem is:
mathematical expression of the middle layer problem constraint:
mathematical expression of the objective function of the underlying problem:
wherein,respectively are the upper limit and the lower limit of the wind power output,is half the length of the output prediction interval of the wind farm j at the time t, gamma s To account for the uncertain budget of spatial clustering effects, p jt The output of the wind power j at the moment t,for the spare capacity in the variable unit i,is the standby cost of unit i, c i For the power generation cost of the thermal power generating unit i,is the adjustment quantity in the actual operation of the variable thermal power generating unit i,to represent a wind farmPredicted force of j at time t, Γ T To take into account the uncertain budget of the temporal smoothing effect.
Further, in an embodiment of the present invention, the obtaining a robust backup tuning strategy considering compressed air energy storage further includes: after the actual wind power output is obtained, under the condition that a system operation point in one stage is given, a wind power grid-connected real-time economic dispatching model containing compressed air energy storage is solved, and the power value conditions of the actual thermal power output and the compressed air energy storage are given.
In order to achieve the above object, an embodiment of the present invention provides a wind power grid-connected standby setting device considering compressed air energy storage, including: the construction module is used for predicting the wind power output according to historical data and constructing an uncertain set of the wind power output; the first constraint module is used for acquiring power balance constraint, standby constraint, climbing constraint and line power flow constraint which need to be met in each time interval of the power system; the second constraint module is used for acquiring output constraint and energy storage constraint of the compressed air energy storage system in each time period; the third constraint module is used for acquiring a minimized cost objective function of the power system; the combined module is used for constructing a robust unit combined model considering compressed air energy storage; and the solving module is used for solving the robust backup setting model by using a mixed integer linear programming conversion and C & CG solving algorithm to obtain a robust backup setting strategy considering compressed air energy storage.
According to the wind power grid-connected standby setting device considering compressed air energy storage, a wind power uncertain set can be constructed, constraint conditions such as power generation capacity constraint, power balance constraint, transmission power flow constraint, spare quantity constraint, output constraint and energy storage energy constraint of the compressed air energy storage system in each time period to be met by the power system in each time period are obtained to obtain a target function of the minimum cost of the power system, then a robust standby setting model considering compressed air energy storage is constructed, and finally a robust standby setting strategy considering compressed air energy storage is obtained, so that the characteristic that the compressed air energy storage can equivalently increase the system rotation standby can be fully exerted, and the system safety and the operation stability level are effectively improved.
In addition, the wind power grid-connected standby setting method considering compressed air energy storage according to the embodiment of the invention can also have the following additional technical characteristics:
further, in an embodiment of the present invention, the construction module is further configured to give upper and lower wind power outputs based on a normal distribution function, and give an uncertain budget considering a time smoothing effect and an uncertain budget considering a space clustering effect based on a central limit theorem and a probability inequality respectively.
Further, in an embodiment of the present invention, the third constraint module is further configured to set an upper layer objective function of the power system backup tuning model with a target of minimizing cost and a lower layer objective function with a target of minimizing backup cost, and construct a min-max-min three-layer model.
Further, in an embodiment of the present invention, the min-max-min three-layer model further includes:
the mathematical expression of the objective function of the upper layer problem is:
mathematical expressions for the middle layer problem constraint:
mathematical expression of the objective function of the underlying problem:
wherein,respectively are the upper limit and the lower limit of the wind power output,is half the length of the output prediction interval of the wind farm j at the time t, gamma s To account for the uncertain budget of spatial clustering effects, p jt The output of the wind power j at the moment t,for the spare capacity in the variable unit i,is the standby cost of unit i, c i For the power generation cost of the thermal power generating unit i,is the adjustment quantity in the actual operation of the variable thermal power generating unit i,to represent the predicted contribution, Γ, of the wind farm j at time t T To take into account the uncertain budget of the temporal smoothing effect.
Further, in an embodiment of the present invention, the solving module is further configured to, after the actual output of the wind power is obtained, solve the wind power grid-connected real-time economic scheduling model including the compressed air energy storage under the condition that the operation point of the one-stage system is given, and give the actual output of the thermal power and the power value condition of the compressed air energy storage.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a flow chart of a wind power grid-connected backup setting method considering compressed air energy storage according to an embodiment of the invention;
FIG. 2 is a block diagram of an overall framework of a robust backup tuning model that accounts for compressed air energy storage in accordance with an embodiment of the present invention;
FIG. 3 is a schematic flow diagram of a robust backup tuning problem solving algorithm considering compressed air energy storage according to an embodiment of the present invention;
fig. 4 is a flowchart of a wind power grid-connected backup setting method considering compressed air energy storage according to a specific embodiment of the present invention:
fig. 5 is a schematic structural diagram of a wind power grid-connection standby setting device considering compressed air energy storage according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The wind power grid-connected standby setting method and device considering compressed air energy storage according to the embodiment of the invention are described below with reference to the accompanying drawings, and firstly, the wind power grid-connected standby setting method considering compressed air energy storage according to the embodiment of the invention will be described with reference to the accompanying drawings.
Fig. 1 is a flowchart of a wind power grid-connected backup setting method considering compressed air energy storage according to an embodiment of the present invention.
As shown in fig. 1, the wind power grid-connected standby setting method considering compressed air energy storage includes the following steps:
in step S101, wind power processing is predicted according to wind power historical data, and a wind power uncertain set is constructed.
It can be understood that according to the embodiment of the invention, the wind power output can be predicted according to the historical data, so that an uncertain set of wind power output can be constructed.
Further, in an embodiment of the invention, a wind power uncertain set is constructed, and the method further comprises the steps of giving the upper and lower wind power outputs based on a normal distribution function, and giving an uncertain budget considering a time smoothing effect and an uncertain budget considering a space clustering effect respectively based on a central limit theorem and a probability inequality.
It can be understood that the wind power uncertain set can be constructed according to wind power historical data, and the wind power uncertain set comprises the upper limit and the lower limit of wind power output given based on a normal distribution functionRespectively giving uncertain budget gamma considering time smoothing effect based on central limit theorem and probability inequality T And an uncertainty budget Γ considering spatial clustering effects S The method of selecting (1).
Specifically, the mathematical expression of the wind power uncertain set constraint is as follows:
it will be appreciated that the above-described,recording the lower and upper limits of the output
And (4) limiting the total deviation amount by considering a time smoothing effect, namely the actual output of each time period of a single wind power plant cannot reach an upper limit or a lower limit at the same time.
Considering the space clustering effect, the output of each wind power plant in a certain period of time cannot reach an upper limit or a lower limit, the total deviation amount is limited,
in step S102, a generation capacity constraint, a power balance constraint, a transmission power flow constraint, and a spare amount constraint that the power system needs to satisfy at each time interval are obtained.
It can be understood that the embodiment of the invention can set the generation capacity constraint, the power balance constraint, the transmission line power flow constraint and the spare quantity constraint which need to be met by the power system in each time period.
Specifically, the mathematical expression of the power generation capacity constraint that the power system needs to satisfy per period:
mathematical expression of power system power balance constraints:
mathematical expression of power system transmission line flow constraints:
mathematical expressions for power system inventory constraints:
in step S103, the output constraint and the stored energy constraint of the compressed air energy storage system per time period are obtained.
It is understood that the embodiment of the invention can set the output constraint and the stored energy constraint of the compressed air energy storage system in each time period, and the like.
Specifically, the mathematical expression for the compressed air energy storage system output constraint is:
the energy storage energy constraint of the compressed air energy storage system which needs to be met by the power system in each period of time, wherein the mathematical expression of the energy constraint of the air storage unit in the compressed air energy storage system is as follows:
the mathematical expression of the heat storage energy constraint of the heat storage unit in the compressed air energy storage system is as follows:
the mathematical expression of the energy constraint of the air storage unit is that a compressed air system has the same heat exchange ratio in a compressed air energy storage link and an expansion link:
mathematical expression of the energy constraints of the heat storage unit:
in step S104, a minimum cost objective function of the power system is acquired.
It will be appreciated that embodiments of the invention may set an optimization objective function for the power system with the goal of minimizing costs.
In step S105, a robust backup tuning model that takes compressed air energy storage into account is constructed.
It will be appreciated that embodiments of the invention may then build a robust backup tuning model that takes into account compressed air storage energy. And constructing a wind power standby setting model considering the energy storage of the compressed air according to the uncertain set and each related constraint parameter in the table 1, wherein the table 1 is a list of the uncertain set and each related constraint parameter.
TABLE 1
Further, in an embodiment of the present invention, obtaining a minimized cost objective function of the power system further includes: and setting an upper layer objective function taking the minimized cost as a target and a lower layer objective function taking the minimized standby cost as a target of the standby setting model of the power system, and constructing a min-max-min three-layer model.
It can be understood that, in the embodiment of the present invention, an objective function of the backup setting model of the power system, which aims to minimize the cost, and a mathematical expression of the objective function of the operation of the power system may be set:
objective functionIs to minimize the total costs, including the operating costs and the standby costs of the thermal power generating unit. WhereinIs the spare capacity in the unit i,is the standby cost of unit i. Reserving spare capacity for a certain amount is costly and would compromise the economics of operation if the reserved spare capacity were increased without the capacity being called up in actual operation. Therefore, a spare cost is added to the objective function.
Optionally, in an embodiment of the present invention, the min-max-min three-layer model further includes:
the mathematical expression of the objective function of the upper layer problem is:
mathematical expressions for the middle layer problem constraint:
mathematical expression of the objective function of the underlying problem:
wherein, t is a time interval number,in order to realize the purpose of the method,respectively are the upper limit and the lower limit of the wind power output,is half the length of the output prediction interval of the wind farm j at the time t, gamma s To account for the uncertain budget of spatial clustering effects, p jt For the output of the wind power j at the moment t,for the spare capacity in the variable unit i,is the standby cost of unit i, c i For the cost of power generation of the thermal power generating unit i,is the adjustment quantity in the actual operation of the variable thermal power generating unit i,to represent the predicted contribution, Γ, of the wind farm j at time t T To take into account the uncertain budget of the temporal smoothing effect.
Specifically, a wind power integration standby setting model considering compressed air energy storage is constructed according to the constraint, and the model describesSuch a practical physical process: output according to current prediction of wind power plantAnd the possible variation range of wind power in a period of time in the future to give the output of the current thermal power generating unitSpare capacity of thermal power generating unitWhen the wind power changes, the output of the thermal power generating unit and the energy release/storage power value of the compressed air energy storage system can be adjusted in a standby rangeAll safety constraints are guaranteed to be met, and meanwhile standby cost is minimized. The overall framework of the model is shown in figure 2. In the upper layer problem, a thermal power output plan and a spare capacity are established, and the total cost is minimized. Under the condition that the upper-layer strategy is given, the lower layer minimizes the adjustment cost by adjusting the output of each unit. The whole can be described as a min-max-min problem. The mathematical expression of the wind power integration standby setting model considering compressed air energy storage is as follows:
mathematical expression of the upper-layer problem objective function:
the mathematical expression of the constraint:
mathematical expression of the objective function of the underlying problem:
the mathematical expression of the constraint:
in step S106, a robust backup setting model is solved by using a mixed integer linear programming conversion and C & CG solving algorithm, and a robust backup setting strategy considering compressed air energy storage is obtained.
It can be understood that the embodiment of the invention can utilize a mixed integer linear programming conversion method and a C & CG solving algorithm to solve the model, so that a robust standby setting strategy considering compressed air energy storage can be obtained.
Specifically, as shown in fig. 3, the model is solved by using the C & CG algorithm, and the specific operations are as follows:
and (4) processing the lower layer problem by using a mixed integer linear programming method. The underlying problems are not assumed to be:
its mathematical expression for the dual problem:
for the uncertain set modeling method considering the wind power time-space effect, it is not difficult to know that the optimal solution is necessarily obtained at the boundary of the wind power set, and therefore the uncertain set of wind power is assumed as follows:
substituting an objective function to the dual problemIn (b) can obtain
Order toThe objective function (1) becomes:
next, the embodiment of the invention pairsLinearization is carried out, if the range of u is-M ≦ u ≦ 0, thenThe following linear inequality may be substituted:
when the temperature is higher than the set temperatureWhen there isWhen the temperature is higher than the set temperatureWhen there is
When the temperature is higher than the set temperatureWhen there isWhen in useWhen there is
It can be seen that the objective function (2) isAre equivalent.
The problem can be solved and converted into a mixed integer linear programming problem:
therefore, the wind turbine generator set combined model considering compressed air energy storage is converted into a min-max form, and the C & CG method is adopted to solve the overall form.
For example, as shown in fig. 3, the flow of the robust backup tuning problem solving algorithm considering the compressed air energy storage is as follows:
in step S31, data initialization is performed;
in step S32, an optimal backup tuning problem is performed;
in step S33, the thermal power reserve capacity is set, and robustness feasibility verification is performed, and if R >0, step S32 is performed; if R =0, execute step S34;
in step S34, the process ends.
Further, in an embodiment of the present invention, obtaining a robust backup tuning strategy considering compressed air energy storage further comprises: after the actual output of the wind power is obtained, under the condition that a system operation point in one stage is given, a wind power grid-connected real-time economic dispatching model containing compressed air energy storage is solved, and the actual output of the thermal power and the power value condition of the compressed air energy storage are given.
It can be understood that after the actual output of the wind power is obtained, the wind power grid-connected real-time economic dispatching model containing the compressed air energy storage can be solved under the condition that the operation point of the system at one stage is given, and the power value conditions of the actual output of the thermal power and the compressed air energy storage are given.
In an embodiment of the present invention, as shown in fig. 4, the method specifically includes the following steps:
in step S41, wind power output is predicted according to historical data, and a wind power uncertain set is constructed;
in step S42, setting output constraint and stored energy constraint of the compressed air energy storage system in each time period;
in step S43, a power system minimum cost objective function is set;
in step S44, setting a power balance constraint, a standby constraint, a climbing constraint and a line power flow constraint that need to be satisfied by the power system at each time interval;
in step S45, setting output constraint and minimum startup and shutdown constraint of the thermal power generating unit;
in step S46, a robust backup tuning model considering compressed air energy storage is constructed and solved.
According to the wind power grid-connected standby setting method considering compressed air energy storage, which is disclosed by the embodiment of the invention, a minimum cost target function of the power system can be obtained by constructing a wind power uncertain set and obtaining constraint conditions such as power generation capacity constraint, power balance constraint, transmission power flow constraint, spare quantity constraint, output constraint and energy storage energy constraint of the compressed air energy storage system in each time period which need to be met by the power system, then a robust standby setting model considering compressed air energy storage is constructed, and finally a robust standby setting strategy considering compressed air energy storage is obtained, so that the characteristic that the compressed air energy storage can equivalently increase the system rotation standby can be fully exerted, and the system safety and the operation stability level are effectively improved.
The wind power grid-connected standby setting device considering compressed air energy storage provided by the embodiment of the invention is described next with reference to the attached drawings.
Fig. 5 is a schematic structural diagram of a wind power grid-connected backup setting device considering compressed air energy storage according to an embodiment of the present invention.
As shown in fig. 5, the wind power grid-connected standby setting method 10 considering compressed air energy storage includes: a construction module 100, a first constraint module 200, a second constraint module 300, a third constraint module 400, a combination module 500, and a solution module 600.
The construction module 100 is configured to predict the wind power output according to historical data and construct an uncertain set of wind power outputs. The first constraint module 200 is used for acquiring a power balance constraint, a standby constraint, a climbing constraint and a line power flow constraint which need to be satisfied in each period of the power system. The second constraint module 300 is configured to obtain a force constraint and an energy storage constraint of the compressed air energy storage system for each period. The third constraint module 400 is used to obtain a minimum cost objective function for the power system. The combination module 500 is used to build a robust unit combination model that takes compressed air energy storage into account. The solving module 600 is configured to solve the robust backup setting model by using a mixed integer linear programming transformation and C & CG solving algorithm, and obtain a robust backup setting strategy considering compressed air energy storage. The device 10 of the embodiment of the invention can utilize the characteristic that compressed air energy storage can be equivalent to a synchronous power generation system with adjustable power and voltage, and can equivalently increase the rotating standby characteristic, and improves the economical efficiency of system operation under wind power access, thereby fully playing the characteristic that compressed air energy storage can equivalently increase the rotating standby characteristic of the system, and effectively improving the safety and the operation stability level of the system.
Further, in an embodiment of the present invention, the constructing module 100 is further configured to give upper and lower wind power outputs based on a normal distribution function, and give an uncertain budget considering a time smoothing effect and an uncertain budget considering a space clustering effect based on a central limit theorem and a probability inequality respectively.
Further, in an embodiment of the present invention, the third constraint module 400 is further configured to set an upper layer objective function of the power system backup setting model with a goal of minimizing the cost and a lower layer objective function of the power system backup setting model with a goal of minimizing the backup cost, and construct a min-max-min three-layer model.
Further, in an embodiment of the present invention, the min-max-min three-layer model further comprises:
the mathematical expression of the objective function of the upper layer problem is:
mathematical expressions for the middle layer problem constraint:
mathematical expression of the objective function of the underlying problem:
wherein t is a time period number,in order to realize the purpose of the method,respectively are the upper limit and the lower limit of the wind power output,output prediction for wind farm j at time tHalf the length of the interval, gamma s To account for the uncertain budget of spatial clustering effects, p jt The output of the wind power j at the moment t,for the spare capacity in the variable unit i,is the standby cost of unit i, c i For the power generation cost of the thermal power generating unit i,is the adjustment quantity in the actual operation of the variable thermal power generating unit i,to represent the predicted contribution, Γ, of the wind farm j at time t T To take into account the uncertain budget of the temporal smoothing effect.
Further, in an embodiment of the present invention, the solving module 600 is further configured to, after obtaining the actual wind power output, solve the wind power grid-connected real-time economic scheduling model including the compressed air energy storage under the condition that the operating point of the one-stage system is given, and give the actual thermal power output and the power value condition of the compressed air energy storage.
It should be noted that the explanation of the embodiment of the wind power integration standby setting method considering compressed air energy storage is also applicable to the wind power integration standby setting device considering compressed air energy storage, and is not repeated here.
According to the wind power grid-connected standby setting device considering compressed air energy storage, which is disclosed by the embodiment of the invention, a minimum cost objective function of a power system can be obtained by constructing a wind power uncertain set and obtaining constraint conditions such as power generation capacity constraint, power balance constraint, transmission power flow constraint, spare quantity constraint, output constraint and energy storage energy constraint of the compressed air energy storage system in each time period which need to be met by the power system in each time period, then a robust standby setting model considering compressed air energy storage is constructed, and finally a robust standby setting strategy considering compressed air energy storage is obtained, so that the characteristic that the compressed air energy storage can equivalently increase the system rotation standby can be fully exerted, and the system safety and the operation stability level are effectively improved.
In the description of the present invention, it is to be understood that the terms "central," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," "circumferential," and the like are used in the orientations and positional relationships indicated in the drawings for convenience in describing the invention and to simplify the description, but are not intended to indicate or imply that the device or element so referred to must have a particular orientation, be constructed in a particular orientation, and be operated in a particular manner, and are not to be construed as limiting the invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specified otherwise.
In the present invention, unless otherwise explicitly stated or limited, the terms "mounted," "connected," "fixed," and the like are to be construed broadly, e.g., as being permanently connected, detachably connected, or integral; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
In the present invention, unless expressly stated or limited otherwise, the first feature "on" or "under" the second feature may be directly contacting the second feature or the first and second features may be indirectly contacting each other through intervening media. Also, a first feature "on," "over," and "above" a second feature may be directly or diagonally above the second feature, or may simply indicate that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature may be directly under or obliquely under the first feature, or may simply mean that the first feature is at a lesser elevation than the second feature.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are exemplary and not to be construed as limiting the present invention, and that changes, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A wind power grid-connected standby setting method considering compressed air energy storage is characterized by comprising the following steps:
forecasting wind power processing according to wind power historical data, and constructing a wind power uncertain set;
acquiring a power generation capacity constraint, a power balance constraint, a transmission power flow constraint and a spare quantity constraint which need to be met by each time interval of a power system;
acquiring output constraint and energy storage constraint of the compressed air energy storage system in each time period;
acquiring a minimum cost objective function of the power system;
constructing a robust standby setting model considering compressed air energy storage; and
and solving the robust backup setting model by using a mixed integer linear programming conversion and C & CG solving algorithm to obtain a robust backup setting strategy considering compressed air energy storage.
2. The wind power grid-connected standby setting method considering the compressed air energy storage according to claim 1, wherein the wind power uncertain set is constructed, and further comprising a selection method of giving the upper and lower wind power outputs based on a normal distribution function, and giving the uncertain budget considering the time smoothing effect and the uncertain budget considering the space clustering effect respectively based on a central limit theorem and a probability inequality.
3. The method for setting wind power integration standby considering compressed air energy storage according to claim 1, wherein the obtaining of the minimum cost objective function of the power system further comprises:
and setting an upper layer objective function taking the minimized cost as a target and a lower layer objective function taking the minimized standby cost as a target of the power system standby setting model, and constructing a min-max-min three-layer model.
4. The wind power grid-connected standby setting method considering compressed air energy storage according to claim 3, wherein the min-max-min three-layer model further comprises:
the mathematical expression of the objective function of the upper layer problem is:
mathematical expressions for the middle layer problem constraint:
mathematical expression of the objective function of the underlying problem:
wherein, t is a time interval number,respectively are the upper limit and the lower limit of the wind power output,is half the length of the output prediction interval of the wind farm j at the time t, gamma s To account for the uncertain budget of spatial clustering effects, p jt The output of the wind power j at the moment t,for the spare capacity in the variable unit i,is the standby cost of unit i, c i For the cost of power generation of the thermal power generating unit i,for regulating variable, p, of thermal power generating unit i in actual operation it e To represent the predicted contribution, Γ, of the wind farm j at time t T To take into account the uncertain budget of the temporal smoothing effect.
5. The wind power grid-connected standby setting method considering compressed air energy storage according to claim 1, wherein the obtaining of the robust standby setting strategy considering compressed air energy storage further comprises:
after the actual output of the wind power is obtained, under the condition that a system operation point in one stage is given, a wind power grid-connected real-time economic dispatching model containing compressed air energy storage is solved, and the actual output of the thermal power and the power value condition of the compressed air energy storage are given.
6. A wind power grid-connected standby setting device considering compressed air energy storage is characterized by comprising the following components:
the construction module is used for predicting the wind power output according to historical data and constructing an uncertain set of the wind power output;
the first constraint module is used for acquiring power balance constraint, standby constraint, climbing constraint and line power flow constraint which need to be met in each time interval of the power system;
the second constraint module is used for acquiring output constraint and energy storage constraint of the compressed air energy storage system in each time period;
a third constraint module, configured to obtain a minimum cost objective function of the power system;
the combined module is used for constructing a robust unit combined model considering compressed air energy storage; and
and the solving module is used for solving the robust backup setting model by using a mixed integer linear programming conversion and C & CG solving algorithm to obtain a robust backup setting strategy considering compressed air energy storage.
7. The wind power grid-connected standby setting device considering compressed air energy storage according to claim 6, characterized in that the construction module is further configured to give the upper and lower wind power outputs based on a normal distribution function, and give the selection method of the uncertain budget considering time smoothing effect and the uncertain budget considering space clustering effect based on a central limit theorem and a probability inequality, respectively.
8. The wind power grid-connected standby setting device considering compressed air energy storage according to claim 6, wherein the third constraint module is further configured to set an upper layer objective function of the power system standby setting model with a target of minimized cost and a lower layer objective function with a target of minimized standby cost, and construct a min-max-min three-layer model.
9. The wind power grid-connected standby setting device considering compressed air energy storage according to claim 8, wherein the min-max-min three-layer model further comprises:
the mathematical expression of the objective function of the upper layer problem is:
mathematical expressions for the middle layer problem constraint:
mathematical expression of the objective function of the underlying problem:
wherein, t is a time interval number,in order to realize the purpose of the method,respectively are the upper limit and the lower limit of the wind power output,is half the length of the output prediction interval of the wind farm j at the time t, gamma s To account for the uncertain budget of spatial clustering effects, p jt For the output of the wind power j at the moment t,for the spare capacity in the variable unit i,is the standby cost of unit i, c i For the power generation cost of the thermal power generating unit i,for regulating variable, p, of thermal power generating unit i in actual operation it e Is a representation of the predicted contribution, Γ, of the wind farm j at time t T To account for the uncertain budget of the temporal smoothing effect.
10. The wind power grid-connected standby setting device considering compressed air energy storage according to claim 6, wherein the solving module is further configured to solve a wind power grid-connected real-time economic dispatching model including compressed air energy storage under a given condition of a system operation point in a first stage after obtaining the actual wind power output, and give a power value condition of the actual thermal power output and the compressed air energy storage.
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