CN110739711A - Energy storage equipment optimization control method considering negative peak regulation capability of wind power grid-connected system - Google Patents
Energy storage equipment optimization control method considering negative peak regulation capability of wind power grid-connected system Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
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Abstract
The invention discloses an energy storage device optimization control method and system considering negative peak regulation capacity of a wind power grid-connected system.
Description
Technical Field
The invention relates to the technical field of energy storage equipment optimization, in particular to energy storage equipment optimization control methods and systems considering the negative peak regulation capability of a wind power grid-connected system.
Background
Disturbance brought to a system by wind power integration makes peak shaving of the system tense, and negative peak shaving capacity of the system at the time of low load is a main factor determining the wind power capacity accepted by the system. The energy storage equipment can be regarded as a power supply with high flexibility to participate in system peak regulation, and wind power consumption is promoted.
With the development of wind power generation technology, the proportion of wind power grid-connected capacity in the power generation capacity of a power system is remarkably increased, and the characteristics of randomness, intermittence, uncertainty and the like of wind power bring fixed challenges to safe and reliable operation of the power system.
The existing research shows that the problem brought by wind power integration to the peak load regulation of the power system can be summarized as that the net load level of the system is lower than the minimum output level of the system due to higher wind power level in the load valley period, so that the system is forced to abandon wind or stop. Many scholars at home and abroad carry out a great deal of research on the problems of peak regulation capability, peak regulation optimization strategy and the like of a wind power grid-connected system, and the existing methods comprise: (1) analyzing the system peak regulation demand change before and after wind power integration, and evaluating the system peak regulation adequacy by using a probabilistic method; (2) analyzing key factors influencing system peak regulation by wind power integration, and providing a method for calculating the maximum tracking load capacity of the system after comprehensively considering a wind abandoning strategy and a wind power prediction error; (3) after the peak regulation constraint of the system operation is established by comprehensively considering various power peak regulation depths, the wind power grid-connected capacity is determined by taking the system operation economy as the principle of the optimal: (4) considering the peak regulation coupling relation of a plurality of scheduling periods, providing a wind, water and fire random unit combination model considering peak regulation constraint: (5) analyzing an extreme scene of the influence of wind electric fluctuation on peak regulation, and providing a peak regulation capacity analysis model of a wind power grid-connected system in a low-ebb period; and (6) comprehensively considering the negative peak regulation capacity and the operation cost of the system at the load valley moment, and providing a multi-target unit combination model meeting the requirement of the wind power prediction interval. The inventor finds that although the peak regulation capability and different peak regulation strategies of the wind power grid-connected system are analyzed in the scheme, energy storage equipment serving as a flexible power supply is not considered to be added into the system for peak regulation.
The energy storage system is used as a flexible power source resource with good regulation performance, can be used as a power generation resource and a load resource at the same time, is which is a main mode for a power system to carry out peak clipping and valley filling and smooth a power generation curve, and is developed rapidly in recent years.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides energy storage equipment optimization control methods and systems considering the negative peak regulation capability of a wind power grid-connected system, two scenes influencing the system peak regulation after wind power is connected into a power grid and three scenes of assisting the energy storage equipment in peak regulation are comprehensively considered, an optimization model for increasing the negative peak regulation capability of the wind power storage combined system at the valley moment is provided, the system peak regulation limit in a research period can be obtained through model solution, and reference is provided for the time sequence output arrangement of the energy storage equipment under the condition of accommodating the wind power to the maximum extent.
The invention provides a energy storage equipment optimization control method considering the negative peak regulation capability of a wind power grid-connected system in the aspect of , and the technical scheme is as follows:
energy storage equipment optimization control method considering negative peak regulation capacity of wind power grid-connected system, the method includes the following steps:
acquiring load prediction data and a distribution rule of day-ahead scheduling prediction of wind power, and determining an extreme scene with the maximum peak regulation demand of a system load fluctuation section;
in a load valley period, according to load prediction data and the lowest output level of a unit, considering the maximum output level of energy storage equipment, ensuring that the system can absorb maximum wind power, and constructing an optimization model for analyzing the peak regulation capacity of the wind power grid-connected system under the participation of energy storage;
carrying out linearization processing on the constructed optimization model for analyzing the peak regulation capability of the grid-connected system under the condition that the stored energy participates in the wind power generation;
and acquiring actual operation data of the system in the period, inputting an optimization model for analyzing the peak regulation capability of the energy storage participation grid-connected system, and determining the peak regulation limit downwards in the valley period of the energy storage participation grid-connected system in the period.
And a step , in which the extreme scenarios where the peak shaver requirement of the system load fluctuation section is the largest include a peak shaver requirement up-regulation scenario and a peak shaver requirement down-regulation scenario.
And , analyzing the target functions in the optimization model of the wind power grid-connected system peak regulation capacity under the participation of stored energy as follows:
in the formula, δ represents the system network loss,
represents the lowest output level P of the thermal power generating unit i in the adjustable output rangeE,tRepresenting the output level of the energy storage device at the time of the t-th instance, at representing the duration of each time interval.
And , analyzing constraint conditions in the optimization model of the energy storage participation grid-connected system peak regulation capability under the wind power system, wherein the constraint conditions comprise power balance constraint of the system, upper and lower limit output constraint of the thermal power generating unit, standby constraint of the unit, minimum start-stop time constraint of the unit, system peak regulation response capability constraint and alternate start-stop constraint of the start-stop peak regulation unit.
And , the method for carrying out linearization processing on the constructed optimization model for analyzing the peak shaving capacity of the grid-connected system under the participation of stored energy comprises the following steps:
introducing variable vi,jEquivalently represents ui,jui,j-1And adding the variable vi,jAnd (4) constraint conditions, wherein the constraint in the optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of the stored energy is subjected to linearization treatment.
Step , the variable vi,jThe constraints are:
wherein u isi,jThe starting and stopping states of the thermal power generating unit i at the moment j are set; u. ofi,j-1And the starting and stopping states of the thermal power generating unit i at the moment j-1 are shown.
In addition, the energy storage equipment optimization control system considering the negative peak regulation capability of the wind power grid-connected system provided by the invention in the aspect of has the technical scheme that:
energy storage equipment optimization control system considering wind power grid-connected system negative peak regulation capability, the system includes:
the scene determining module is used for acquiring load prediction data and a distribution rule of the scheduling prediction of wind power in the day ahead and determining an extreme scene with the maximum peak regulation requirement at a system load fluctuation section;
the model building module is used for building an optimization model for analyzing the peak regulation capability of the grid-connected system under the participation of stored energy in wind power generation by considering the maximum output level of the energy storage equipment according to the load prediction data and the minimum output level of the unit during the load valley period;
the linear processing module is used for carrying out linear processing on the constructed optimization model for analyzing the peak regulation capability of the energy storage participation grid-connected system;
and the optimization control module is used for acquiring actual operation data of the system in the period, inputting an optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of the stored energy, and determining the downward peak regulation limit of the wind power grid-connected system in the valley period under the participation of the stored energy in the period.
The computer-readable storage media provided by another aspect of the invention are:
computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps in the method for energy storage device optimization control taking into account wind power grid tie system negative peak shaver capability as described above.
The invention also provides treatment devices in the aspect of , and the technical scheme is as follows:
processing apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method for controlling optimization of energy storage equipment considering the load peak regulation capability of the wind power grid-connected system when executing the program.
Through the technical scheme, the invention has the beneficial effects that:
(1) in order to fully utilize energy storage equipment to improve the peak regulation capability of a wind power grid-connected system, two scenes influencing the system peak regulation after wind power is accessed into a power grid and three scenes assisting the energy storage equipment in peak regulation are comprehensively considered, an optimization model for increasing the negative peak regulation capability of the wind power storage combined system at the valley moment is provided, the peak regulation limit of the system in a research period can be obtained through model solution, and reference is provided for the time sequence output arrangement of the energy storage equipment under the condition of accommodating the wind power to the maximum extent.
(2) After comprehensively considering the uncertainty of the grid-connected wind power and the effect of the energy storage equipment on the aspect of peak clipping and valley filling of the system, establishing an optimization model by taking the maximum negative peak load capacity of the system in the valley period as a target; by comparing the negative peak-shaving capacity of the system during the low-valley period before and after the energy storage equipment is connected to the grid, the effect of the energy storage equipment connected to the grid in the system peak shaving can be explained, and the method can be suitable for analyzing the optimal configuration parameters of the energy storage equipment under the condition of accommodating wind power to the maximum extent.
Drawings
The accompanying drawings, which form a part of the specification , are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description, serve to explain the application and not to limit the invention.
FIG. 1 is a flowchart of an energy storage device optimization control method of embodiment taking into account the negative peak regulation capability of the wind power grid-connected system;
FIG. 2 is a graph of typical daily loads in winter in North China, a certain province in example ;
FIG. 3 is a peak load fluctuation graph in example ;
FIG. 4 is a schematic diagram illustrating the timing of the energy storage device according to the embodiment ;
FIG. 5 is a graph of the full-time system negative peak-shaving capacity in the example ;
FIG. 6 is a graph of the negative peak shaving capacity of the system during the valley period in the example .
Detailed Description
The invention is further illustrated in with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further steps for the present invention unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular is intended to include the plural unless the context clearly dictates otherwise, and it should be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of features, steps, operations, elements, components, and/or combinations thereof.
Example
Fig. 1 is a flowchart of an energy storage device optimization control method considering a negative peak regulation capability of a wind power grid-connected system according to this embodiment. As shown in fig. 1, the energy storage device optimization control method considering the negative peak regulation capability of the wind power integration system comprises the following steps:
and S101, analyzing the peak regulation capability of the grid-connected system of the wind power system under the participation of the energy storage equipment.
The peak shaving of the power system is the behavior that a system scheduling mechanism calls various resources to generate power or adjust power load per se in a planned way to ensure the power and electricity balance of a power supply side and a power utilization side so as to meet the requirement of load fluctuation. Considering the influence of the uncertainty of wind power on the system peak regulation, the embodiment provides two extreme scenes that the wind power integration deteriorates the system peak regulation. For a wind power grid-connected system, wind power output can be regarded as load with a negative value, and the load is superposed with the original load of the system to obtain a fluctuation rule of net load. Compared with the original load fluctuation of the system, the uncertainty disturbance caused by wind power access is mainly shown in two aspects: the inverse peak regulation characteristic of the grid-connected wind turbine generator enables the equivalent load power difference value of the system in the load peak period and the load valley period to be obviously increased; the randomness and the intermittence of the wind power output enable the fluctuation trend of the load ascending stage or the load descending stage to be more prominent, and the peak regulation capacity required to be met in the short term of the system is obviously improved. Because the load peak period and the load valley period belong to the load fluctuation stage with obvious change, the influence of wind power access on system peak regulation can be summarized into two scenes of peak regulation demand up-regulation and peak regulation demand down-regulation. It is assumed that the start times of the kth rising surge segment and the kth falling surge segment of the load surge are respectively represented asAnd
the duration of which is respectively represented as
And
PD,tand Pw,tRespectively representing the system load and the wind power at the t moment,
andthe supremum and the infimum respectively represent that the wind power at the tth moment meets fixed confidence levels, in order to ensure the reliability of the system peak regulation, the system scheduling process needs to meet the condition of the maximum wind fluctuation, and the two scenarios are described as follows:
(1) the peak shaver requirement up-regulates the scene. And in the load rising stage, the wind power is rapidly reduced.
Wherein, PDIs the system load power; pwIs wind power;the starting time of the kth rising wave section of the load fluctuation;
the duration of the kth rising fluctuation section of the load fluctuation;the system load power at the starting moment of the kth rising fluctuation section of the load fluctuation;
the wind power is the wind power at the starting moment of the kth rising fluctuation section of the load fluctuation;
the wind power of time period is the k rising fluctuation period of the load fluctuation.
(2) And adjusting the scene according to the peak-adjusting requirement. And in the load reduction stage, the wind power is rapidly increased.
Wherein, PDIs the system load power; pwIs wind power;
at the beginning of the kth descending wave section of the load fluctuation;
the duration of the kth descending fluctuation section of the load fluctuation;
the system load power at the beginning time of the kth descending fluctuation section of the load fluctuation;
the wind power is the wind power at the beginning moment of the kth descending fluctuation section of the load fluctuation;
the wind power of time intervals which is the kth descending fluctuation period of the load fluctuation.
The two scenes are extreme scenes with the largest peak regulation requirement at the system load fluctuation section and can be determined according to load prediction data and the distribution rule of the day-ahead scheduling prediction of the wind power.
In the dispatching cycle studied, the peak regulation response capacity of the system is determined by the peak regulation depth and the regulation rate of the units in the system, for most of the power grids in the actual operation area in China, the specific weight of a flexible power supply is low, the output of a nuclear power unit, a thermoelectric power unit which uses heat for power fixation in winter and the like is influenced by external conditions and cannot provide the peak regulation response capacity, the peak regulation mainly depends on a thermal power unit, the thermal power unit is limited by the climbing rate and the minimum startup and shutdown time due to the influence of the economic life of the thermal power unit, the limit for the peak regulation response of the system is that the power unit cannot be reliably started and stopped in the peak valley period of the load, the power imbalance between power generation and power utilization is caused, and the change rate in the load fluctuation process in is higher than the regulation response rate of the unit, so that the load.
In addition, the embodiment summarizes the roles of the energy storage device grid-connection participation system peak shaving into three aspects. The influence of the energy storage equipment incorporated into the power grid on the peak regulation response capability of the system is mainly embodied in the following three scenes:
(1) during the load peak period, the energy storage equipment can perform discharging operation, which is equivalent to power supplies, and the load requirement lost due to the fact that the thermal power generating unit cannot be reliably started to operate is compensated.
(2) In the load valley period, the energy storage equipment can be charged, and the electrical load valley level of the system is equivalently increased.
(3) And in the time period of sudden load fluctuation, the energy storage equipment can be flexibly charged and discharged, and the load fluctuation trend is gentle.
The three scenes reflect the influence of grid connection of the energy storage equipment on relieving the peak load pressure of the system and promoting the system to accept wind power, and can be respectively embodied in the process of system power balance and the process of unit output climbing. According to the peak regulation characteristic, the units with adjustable output can be divided into two types and respectively use a set S1And S2And (4) showing. Belong to the set S1The unit has slow peak regulation response speed and long start-stop time, and comprises a conventional thermal power coal-fired unit and the like. Belong to the set S2The unit can start and stop peak shaving and has high response speed, and comprises a gas turbine unit and the like.
S102, an optimization model for analyzing the peak regulation capability of the grid-connected system of the wind power system under the participation of stored energy is constructed.
In a research period, the difference value between the output power of the peak-shaving response resource of the system and the minimum output level in the low-ebb period can reflect the maximum wind power level which can be absorbed by the system under the condition that the peak shaving of the system is met. The influence of the energy storage equipment on the system peak regulation can be reflected by comparing the change of the downward peak regulation space of the system before and after the energy storage is merged into the system in the load valley period, and the promotion effect of the energy storage on the wind power absorption can be reflected at the same time. Therefore, the embodiment aims to increase the negative peak-shaving space of the peak-shaving response resource in the load valley period, considers the scene of rapid fluctuation of the peak-shaving demand, and establishes the optimization model for analyzing the peak-shaving capacity of the grid-connected system of the wind power system under the participation of stored energy.
Specifically, the optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of energy storage comprises the following steps:
(1) objective function
TvRepresenting the load valley period within the study period T, and the peak load adjustment space of the system peak-load response resource valley period can use the peak load adjustment electric quantity summation delta C of the valley period within the study periodwAnd (4) showing. The objective function can be expressed as follows:
in the formula, δ represents the system network loss,
represents the lowest output level P of the thermal power generating unit i in the adjustable output rangeE,tRepresenting the output level of the energy storage device at the time of the t-th instance, at representing the duration of each time interval.
(2) Constraint conditions
a. Power balance constraint of the system:
in the formula, PGi,tThe output of the thermal power generating unit i with the adjustable capacity is shown,
and the sum of the output of thermal power generating units without adjustable capacity is shown.
b. And (3) restraining the upper and lower output limits of the thermal power generating unit:
in the formula (I), the compound is shown in the specification,
to representOutput upper limit u of thermal power generating unit i with load regulation capacityi,tAnd showing the starting and stopping states of the thermal power generating unit i at the study time t.
c. Standby constraint of the unit:
in the formula, α represents the system rotation reserve rate, the energy storage device only participates in system peak shaving, so the system rotation reserve is completely provided by the thermal power generating unit.
d. And (3) minimum start-stop time constraint of a unit i:
in the formula (I), the compound is shown in the specification,
and
respectively representing the minimum running time and the minimum shutdown time of the unit i.
e. And (3) restraining the peak load response capacity of the system:
in the formula, Rt＝(1+δ)PD,t-Pw,tWherein R istRepresenting the peak shaver demand resource power level of the system during time period t,
and
respectively representing the power change of the unit i caused by power climbing and the power change caused by the start and stop of the unit in the kth peak regulation demand rising fluctuation section;respectively representing the power change of the unit i in the kth peak regulation demand drop fluctuation section caused by power climbing and the power change caused by the start and stop of the unit;
and
representing the power change of the energy storage device in the rising fluctuation section and the falling fluctuation section of the kth peak load regulation demand. The expressions for these variables are shown below.
The above variables are specifically expressed as formulas (9) to (14), wherein
And
respectively representing the upward climbing speed and the downward climbing speed of the unit i in unit MW/h.
f. Start and stop peak shaving unit in turn start and stop restraint:
for S2And the similar units can carry out start-stop peak regulation, and avoids a continuous start-stop mode.
g. Energy storage device charge and discharge power constraint and capacity constraint:
in the formula (I), the compound is shown in the specification,
representing the maximum charge-discharge power, ESS, of the energy storage devicetRepresenting the capacity level of the energy storage device during time period t, η representing the charge and discharge power of the energy storage device, ESSminAnd ESSmaxRespectively representing a lower capacity limit and an upper capacity limit of the energy storage device, ESS0andESSTand a respectively represents the capacity of the energy storage device at the beginning and the end of the research period.
And S102, performing linear processing on the constructed optimization model for analyzing the peak regulation capability of the grid-connected system of the wind power system under the participation of stored energy.
As can be known from the description of the model, the model decision variables comprise 0-1 variables and continuous variables, are mixed integer models, and multiplication terms of the 0-1 variables exist in the model, and belong to the nonlinear mixed integer programming problem. To facilitate the solution, a variable v is introducedi,jEquivalently represents ui,jui,j-1And adding the following constraint (17), and converting the model into a mixed integer linear programming problem by carrying out linearization processing on the constraint in the model.
Wherein v isi,jIs a variable; u. ofi,jThe starting and stopping states of the thermal power generating unit i at the moment j are set; u. ofi,j-1For thermal power generating unit i at time j-1And (5) starting and stopping states.
S103, acquiring actual operation data of the system in the period, inputting an optimization model for analyzing the peak regulation capability of the grid-connected system of the wind power system under the participation of the stored energy, and determining the peak regulation limit under the valley period of the grid-connected system of the wind power system under the participation of the stored energy in the period.
Experiments prove that the energy storage equipment optimization control method considering the negative peak regulation capacity of the wind power grid-connected system provided by the embodiment is carried out.
In this embodiment, the actual operation data of a certain power saving network in north China in winter is taken as an example for analysis, T is 24h and is used as research periods, 15 minutes are divided into time periods, and the total time period number N isT96. The load curve and the non-adjustable unit output are shown in FIG. 2.
Adding a day-ahead wind power prediction interval into the load information, and calculating the peak shaving demand resource power according to a formula (6) to obtain the fluctuation upper and lower limits of the peak shaving demand resource, as shown in fig. 3.
It is known that the load trough period in the study period is from 0 am to 3 am, i.e., Tv∈[0,12]. The peak regulation demand upper limit and the peak regulation demand lower limit in the research period are 5 maximum points and 5 minimum points respectively, and the peak regulation demand fluctuation is divided into 10 sections including 5 sections of peak regulation demand up-regulation sections and 5 peak regulation demand down-regulation sections. The standby load of the resource system is 10%, and the network loss rate is 7%. The system starts to set the capacity of the energy storage equipment to 1000MW, and the minimum and maximum states of charge are respectively 10% (100MW) and 90% (900MW) of the capacity. The maximum charge-discharge power is 50MW, the initial capacity is 500MW, and the charge-discharge efficiency is 90%. The calculated negative peak-shaving capacity of the system in each period and the charging and discharging operations of the energy storage device in the research period according to the optimization model are shown in fig. 4.
It can be seen from fig. 4 that the energy storage device selects to perform charging operation to be used as power utilization side equipment when the load is in the low-ebb period and the wind power grid-connected system is under the peak-shaving pressure tension, and performs discharging operation to be used as power supply side equipment when the system power generation resources are abundant in the load peak period, so that the actual operation requirements of the system are met.
The method comprises the following steps of , analyzing the influence of energy storage equipment on the system peak regulation condition after the energy storage equipment participates, and carrying out experimental comparison with an energy storage non-participating system to obtain full-time negative peak regulation capacity comparison and load valley time negative peak regulation capacity comparison in research periods before and after the energy storage participates as shown in figures 5 and 6 respectively, wherein the minimum negative peak regulation capacity of the system before the energy storage non-participating system peak regulation is 218.7MW, the minimum negative peak regulation capacity of the system after the energy storage equipment is incorporated into the system is 231.2MW, and the minimum negative peak regulation capacity of the system is in time period 1 under the two conditions.
In fig. 6, the negative peak regulation capacity of the system in the 8 th period has a significant increase trend, because the start-stop peak regulation unit in the system meets the minimum start-stop time limit in the 8 th period, and the fluctuation conditions of the negative peak regulation capacity of the system before and after the energy storage participates are the same, which indicates that the energy storage device always operates in the charging state of the maximum charge-discharge power, the effect of the energy storage device on the peak regulation of the system is limited by the maximum charge-discharge power, the maximum charge-discharge power of the energy storage device is increased, and the downward adjustment space change of the system in the low-load period is as shown in table 1.
TABLE 1 Effect of varying maximum stored energy charge and discharge power limits on the objective function
The method comprises the steps that pressure brought by wind power grid connection on system peak regulation service is increased by an square body according to the characteristic of reverse peak regulation of wind power, the equivalent load peak-valley difference of a system is increased, in addition, square body is provided according to uncertainty of wind power, so that output change fluctuation of the system to be responded is enhanced, an energy storage device serves as a flexible power source which can be charged and discharged, the adjustment capacity of the system peak regulation power source can be increased in the aspect of , the peak regulation response rate of the system can be improved in the aspect of , in order to research the influence of the energy storage device on the system peak regulation service, the negative peak regulation capacity of a grid connection system of energy storage participation under wind power is analyzed in the embodiment, the change of a downward adjustment space of the wind power grid connection system before and after the energy storage participation under wind power grid connection can be obtained through establishment and solution of an optimization model.
Example two
The embodiment provides kinds of energy storage equipment optimization control systems of considering wind-powered electricity generation grid-connected system negative peak regulation ability, and this system includes:
the scene determining module is used for acquiring load prediction data and a distribution rule of the scheduling prediction of wind power in the day ahead and determining an extreme scene with the maximum peak regulation requirement at a system load fluctuation section;
the model building module is used for building an optimization model for analyzing the peak regulation capability of the grid-connected system under the participation of stored energy in wind power generation by considering the maximum output level of the energy storage equipment according to the load prediction data and the minimum output level of the unit during the load valley period;
the linear processing module is used for carrying out linear processing on the constructed optimization model for analyzing the peak regulation capability of the energy storage participation grid-connected system;
and the optimization control module is used for acquiring actual operation data of the system in the period, inputting an optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of the stored energy, and determining the downward peak regulation limit of the wind power grid-connected system in the valley period under the participation of the stored energy in the period.
EXAMPLE III
The present embodiment provides computer-readable storage media, on which a computer program is stored, which when executed by a processor implements the steps in the energy storage device optimization control method considering the load-peak-shaving capability of the wind power grid-connected system as described above.
Example four
The embodiment provides processing devices, which include a memory, a processor and a computer program stored in the memory and capable of running on the processor, and when the processor executes the program, the processor implements the steps in the method for optimizing and controlling the energy storage device considering the negative peak load regulation capability of the wind power grid-connected system as described above.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (9)
1, energy storage equipment optimization control method considering negative peak regulation capability of wind power grid-connected system, characterized by comprising the following steps:
acquiring load prediction data and a distribution rule of day-ahead scheduling prediction of wind power, and determining an extreme scene with the maximum peak regulation demand of a system load fluctuation section;
in the load valley period, according to the load prediction data and the lowest output level of the unit, considering the maximum output level of the energy storage equipment, and constructing an optimization model for analyzing the peak regulation capability of the grid-connected system of the wind power under the participation of the stored energy;
carrying out linearization processing on the constructed optimization model for analyzing the peak regulation capability of the grid-connected system under the condition that the stored energy participates in the wind power generation;
and acquiring actual operation data of the system in the period, inputting an optimization model for analyzing the peak regulation capability of the grid-connected system of the stored energy participating in the wind power generation in the period, and determining the downward peak regulation limit of the grid-connected system of the stored energy participating in the wind power generation in the period in the valley period.
2. The energy storage device optimization control method considering the negative peak regulation capability of the wind power grid-connected system according to claim 1, wherein the extreme scenes with the maximum peak regulation requirement of the system load fluctuation section comprise a peak regulation requirement up-regulation scene and a peak regulation requirement down-regulation scene.
3. The method for optimally controlling the energy storage equipment considering the negative peak regulation capability of the wind power grid-connected system according to claim 1, wherein an objective function in an optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of energy storage is as follows:
in the formula, δ represents the system network loss,
represents the lowest output level P of the thermal power generating unit i in the adjustable output rangeE,tRepresenting the output level of the energy storage device at the time of the t-th instance, at representing the duration of each time interval.
4. The method for optimally controlling the energy storage equipment considering the negative peak regulation capability of the wind power grid-connected system according to claim 1, wherein the constraint conditions in the optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of the energy storage comprise power balance constraint of the system, upper and lower limit constraint of output of a thermal power generating unit, standby constraint of the unit, minimum start-stop time constraint of the unit, peak regulation response capability constraint of the system and alternate start-stop constraint of the start-stop peak regulation unit.
5. The method for optimally controlling the energy storage equipment considering the negative peak regulation capability of the wind power grid-connected system as claimed in claim 1, wherein the method for carrying out linearization processing on the established optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of energy storage comprises the following steps:
introducing variable vi,jEquivalently represents ui,jui,j-1And adding the variable vi,jAnd (4) constraint conditions, wherein the constraint in the optimization model for analyzing the peak regulation capability of the wind power grid-connected system under the participation of the stored energy is subjected to linearization treatment.
6. The method as claimed in claim 5, wherein the variable v is a variable that is used for optimizing and controlling the energy storage device in consideration of the negative peak load regulation capability of the wind power grid-connected systemi,jThe constraints are:
wherein u isi,jThe state is a starting and stopping state of the thermal power generating unit i at a moment j; u. ofi,j-1The starting and stopping states of the thermal power generating unit i at the moment j-1 are shown.
7, kinds of energy storage equipment optimal control system who considers wind-powered electricity generation grid-connected system load peak regulation ability, characterized by includes:
the scene determining module is used for acquiring load prediction data and a distribution rule of the scheduling prediction of wind power in the day ahead and determining an extreme scene with the maximum peak regulation requirement at a system load fluctuation section;
the model building module is used for building an optimization model for analyzing the peak regulation capability of the grid-connected system under the participation of stored energy in wind power generation by considering the maximum output level of the energy storage equipment according to the load prediction data and the minimum output level of the unit during the load valley period;
the linear processing module is used for carrying out linear processing on the constructed optimization model for analyzing the peak regulation capability of the energy storage participation grid-connected system;
and the optimization control module is used for acquiring actual operation data of the system in the period, inputting an optimization model for analyzing the peak regulation capability of the grid-connected system of the stored energy participating in the wind power generation in the period, and determining the downward peak regulation limit of the grid-connected system of the stored energy participating in the wind power generation in the period in the valley period.
Computer-readable storage medium , on which a computer program is stored, wherein the program, when being executed by a processor, implements the steps of the method for controlling energy storage device optimization considering wind power grid-connected system negative peak load regulation capability according to any of of claims 1 to 6.
Processing apparatus 9, , comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method for controlling energy storage device optimization in consideration of the load peak regulation capability of the wind power grid-connected system as claimed in any of claims 1-6.
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