CN110417049B - Coordination control method for multi-energy consumption power generation of heat storage system - Google Patents
Coordination control method for multi-energy consumption power generation of heat storage system Download PDFInfo
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Abstract
The invention belongs to the technical field of renewable energy power generation and new energy consumption, and particularly relates to a coordination control method for a heat storage system to consume multi-energy power generation, which is a coordination control method for the heat storage system and a multi-energy power generation system at different moments. Comprises data acquisition; a data processing module; judging whether the wind and light output is in the system running state; the reference speed of the electric heat storage and discharge in the control stage is calculated according to the condition of the used electric heat storage equipment, the three stages are divided according to the energy consumption capability of the electric heat storage, the change process of wind and light output is considered, and the consumption process is accurately coordinated according to the parameter change. The invention can make the execution of the control strategy more accurate, and ensure that the electric heat storage capacity is at the lowest point when a large amount of wind and light are abandoned and need to be consumed; in the period of the lowest point of wind and light output, the electric heat storage capacity is at the highest point, and heat can be released. Better coordinate the consumption problem of thermal load to the wind-solar power generation, the consumption effect after strategy optimization is more outstanding.
Description
Technical Field
The invention belongs to the technical field of renewable energy power generation and new energy consumption, and particularly relates to a coordination control method for a heat storage system to consume multi-energy power generation, which is a coordination control method for the heat storage system and a multi-energy power generation system at different moments.
Background
Wind power photovoltaic power generation increasingly becomes a novel energy source with the greatest development prospect due to the advantages of abundant resources, environmental protection, low carbon and the like. With the access of large-scale wind power and photovoltaic power generation to a power grid, the intermittent and random performance, the difficulty in accurate prediction, the poor stability control and rapid regulation performance of a wind power plant and a photovoltaic power station and the like, urgent requirements are provided for the consumption coordination capacity of the power grid, and the shortage of the peak regulation capacity of the power grid becomes an important factor for restricting the consumption of the wind power and photovoltaic power generation of the power grid.
The prior technical method for solving the problem of wind and light absorption mainly starts from three angles. Firstly, the technical bottleneck is broken through from the angle of equipment manufacturing, the power quality of equipment power generation is improved, the influence of grid connection on a power grid is reduced, and the wind and light absorption capacity is improved. And secondly, combining wind-solar power generation with other types of power supplies, converting unstable wind-solar output into stable combined system output, and improving wind-solar output absorption capacity through grid connection of the combined system. And thirdly, expanding the application market from the perspective of diversified utilization of energy, cooperating with enterprises and governments where power sources are located, actively expanding the local large-load power market, improving the local wind-solar power generation consumption rate, and relieving the grid-connected pressure on the power grid side, so that the overall wind-solar output consumption capacity is improved, which is also the technical perspective adopted herein, and the problem of blocking of renewable energy sources such as wind power and the like is relieved by utilizing energy storage type loads. In the aspect of energy storage technology, the electric heat storage has higher economical efficiency in both power and capacity, and the electric heat storage is the optimal choice in consideration of the efficiency problem of energy interaction between a power grid and a heat supply network.
The existing technical methods for solving the problem of coordination control relation between load and wind-solar power generation are few and not mature.
In the prior art, the research on a microgrid energy storage system control strategy based on an improved cuckoo algorithm, written by Guangxi university, nature science edition, vol 40, no. 6 in 2015. A micro-grid energy storage system mixed integer linear programming model is constructed, an energy storage system optimization result is obtained through an improved cuckoo algorithm, and new energy consumption is promoted to a certain extent. However, the influence of renewable energy characteristics on the absorption effect is not considered in the technology, and the used energy storage system is not suitable for new energy requirements of electric heating network efficiency interchange.
In the second technical scheme of abandoned wind electricity, heat storage and heat supply based on combined heat and power dispatching in the prior art, the 3 rd volume of the intelligent power grid 2015 is No. 10. A scheduling end thermoelectric combined optimization scheduling mode is established according to the high complementary relation between wind power abandoned wind and electric heat storage, and heating power and heat storage capacity which are used by the heat storage device when an electric heating-phase change heat storage material is used as a heat storage medium are given. And the abandoned wind power heat storage and supply trading strategy considering the benefits of each part of a wind power company, a heat supply company and a power grid company is provided. By optimally scheduling the power supply and the electric heat storage and supply in a combined manner, the electric heat storage equipment is started in the wind abandoning period of the power grid, the wind abandoning, the heat storage and supply are realized, and the consumption level of wind power is improved. However, the scheduling model does not correct the system state change changing from moment to moment, and the consumption of wind power by the electric heat storage load is a novel technical attempt, but is not enough to meet the requirement of new energy development of electric power.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a coordination control method for multi-energy consumption power generation of a heat storage system, and aims to solve the problems of strong randomness and intermittency of wind power generation, and particularly the obvious inverse peak regulation characteristic of the wind power generation. Although the randomness and intermittence of wind-solar hybrid output can be improved to a certain extent, the intermittence and the randomness of the wind-solar hybrid output still bring great challenges to the safe and stable operation of a power grid along with the access of large-scale wind power and photovoltaic power generation to the power grid. Therefore, according to the wind and light fluctuation characteristics and the electric-heat conversion capacity of the electric energy storage equipment, if the electric heat storage capacity is at the lowest point at the moment that a large amount of wind and light are abandoned and need to be absorbed, the electric energy can be stored to the maximum extent; through the electric energy storage in the absorption stage, when the level of wind and light output which needs to be absorbed is relatively low, the electric heat storage capacity is at a high point, heat can be released according to the requirement of a heat supply network, namely, the electric energy is absorbed by adjusting the change of heat load, and the wind and light abandoning can be effectively coordinated.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a coordination control method for a heat storage system to absorb multi-energy power generation comprises the following steps:
step 1: collecting data;
step 2: the data processing module is used for respectively establishing acquisition functions of wind speed in a wind power area and equipment temperature in a photovoltaic area and processing data of the acquisition module; the data acquisition and processing module is used for measuring and processing wind speed data of the wind power generation equipment and temperature data of the photovoltaic power generation equipment, respectively establishing standard functions related to the wind speed and the temperature and calculating similarity coefficients of the standard functions to obtain influence data capable of being acquired and calculated;
and 3, step 3: judging the approximate stage of the wind-solar output in the system running state, dividing the wind-solar output into 3 stages according to the change of the system state, and respectively naming the stages as a cold desert stage, a friendly stage and a gentle stage according to corresponding energy storage strategies;
and 4, step 4: according to the total floor area S of the used electric heat storage device h Specific heat capacity c of electric heat storage and heat storage material, and current average temperature T of electric heat storage material h Calculating to obtain the reference speed v of electric heat storage and discharge in the control stage 1 ，
The method is divided into three stages according to the energy consumption of electric heat storage, the change process of wind and light output is considered, and the consumption process is coordinated more accurately according to parameter change.
The step 1: data acquisition, comprising the steps of:
step 1.1: collecting and quantifying, and collecting the occupied area S of the wind turbine generator w And the environmental density rho of the wind turbine generator w The floor area S of the photovoltaic unit i Total floor area S of electric heat storage equipment h The specific heat capacity c of the electric heat storage and heat storage material;
step 1.2: instantly acquiring variable and current total capacity H of electric heat storage equipment t And the relative air humidity rho w of the wind turbine at the current moment t And scheduling L of current illumination intensity of photovoltaic unit h Current average temperature T of electric heat storage material h And collecting two factors which are more critical to influence of wind power photovoltaic power generation, namely the average wind speed and the average temperature of the equipment area.
The step 2 comprises the following steps:
the wind power equipment randomly collects x collection points, and the collected wind speed data is T 1 、T 2 ...T x Form an array f (x), T x Represents the xth measurement data; randomly extracting a plurality of data T from the measured wind speed data 1 、T 2 ...T k Form an array eta (k), T k Represents the kth measurement data;
calculating a similarity coefficient β of η (k) and f (x):
in the formula, e represents the base number of a natural logarithm and is a constant;
the judging module judges, when the similarity coefficient beta of eta (k) and f (x) is larger than or equal to 51.37%, an array eta (k) is extracted to obtain a new array eta (k) ', and the array eta (k)' is used for coordinated operation calculation;
randomly collecting j collection points by photovoltaic equipment, wherein the collected temperature data is z 1 、z 2 ...z j Form an array g (j), z j Represents the jth measurement data; randomly extracting a plurality of data z from measured temperature data 1 、z 2 ...z m Form an array
z m Represents the mth measurement data; computing
A similarity coefficient α to g (x);
the discrimination module discriminates when
When the similarity coefficient alpha of g (x) is more than or equal to 40.58 percent, extracting the array
Resulting arrays
The array is used for coordinated operation calculation;
the technical means used for collecting and processing the data of the wind speed of the wind power generation equipment and the temperature of the photovoltaic power generation equipment is adopted, and the related arrays which finally participate in the operation are selected according to the size of the similarity coefficient.
The step 3 comprises the following steps:
step 3.1: respectively defining a wind power output judgment coefficient delta and a photovoltaic output judgment coefficient omega; wind power output determination coefficient
The floor area S of the wind turbine generator w And the environmental density rho of the wind turbine generator w Relative air humidity ρ w at the present time t And the array η (k) participating in the operation;
wind power output determination coefficient δ:
photovoltaic output determination coefficient omega and photovoltaic unit floor area S i And the current illumination intensity L of the photovoltaic unit h And arrays participating in the operation
(ii) related;
photovoltaic output determination coefficient ω:
step 3.2: selecting a control strategy according to the result obtained in the step 3.1, if delta belongs to (0.23,0.41)' U (0.71,0.81) as a wind power output rising stage and omega belongs to (0.45,0.57) as a photovoltaic output rising stage, satisfying any judgment condition, expressing that the electric heat storage system is in a cold and desert control stage, and starting timing at the moment and executing the control strategy 1; delta and omega e (0.57,0.71) are wind-solar output stress stages, the electric heat storage system is a friendly control stage, timing is started at the moment, and a control strategy 2 is executed; the stage represented by the remaining determination data is a stage of gradual control of the electric heat storage system, and timing is started and a control strategy 3,t represents timing time (t =1min, 2min.. Nmin) is executed.
The step 4 comprises the following steps:
control strategy 1: in the control stage of the cold desert stage, the electric heat storage should accelerate to release self heat and prepare for the energy storage in the emergency stage, the energy release speed in the stage should be higher than the storage speed, and 1.35v is executed 1 ＞v Put ＞1.27v 1 ，0.94v 1 ＞v Store up ＞0.81v 1 (ii) a After the control stage, the electric heat storage capacity state is the lowest point of the full operation process, and sufficient capacity space is left for wind and light absorption;
control strategy 2: in the control stage of the friendly stage, the electric energy storage should present the maximum storage capacity to be completely consumed, at the moment, the residual capacity can be gradually released according to the requirement of a heat supply network, the electric energy storage speed is far higher than the release speed, the electric energy storage capacity reaches the highest point of the full operation process at the moment when the wind and light output force enters the next control stage through the stage, the redundant wind and light output force is obviously coordinated, and the stage is required to execute 2.13v 1 ＞v Store up ＞1.87v 1 ，0.83v 1 ＞v Put ＞0.68v 1 ；
Control strategy 3: in the control stage of the gentle stage, the consumption requirement of wind and light output force is reduced, the electric energy storage releases energy at a constant speed and meets the consumption requirement of output force, and preparation is made for entering the output force rising control stage, the energy storage speed in the stage is lower than the release speed, and the heat release speed v is lower than the release speed Put ＝v 1 。
The coordination control method for the heat storage system to absorb the multi-energy power generation comprises the following steps: the wind power and heat storage combined control system detects the wind and light output consumption and the electric heat storage capacity state in one day and applies the coordination technology;
step 1: collecting data;
step 1.1: collecting and quantifying, and collecting the occupied area S of the wind turbine generator w ＝15306m 2 And the environmental density rho of the wind turbine generator w ＝1.195kg/m 3 The floor area S of the photovoltaic unit i ＝20498m 2 Total floor area S of electric heat storage equipment h ＝270m 2 The specific heat capacity c of the electric heat storage and heat storage material is =4186;
step 1.2: instantly collecting variable and total capacity H of collected current electric heat storage equipment t =32MW · h, relative air humidity ρ w of the wind turbine at the current time t =0.21, current illumination intensity schedule L for photovoltaic unit h ＝627W/m 2 Current average temperature T of electric heat storage material h =53.7 ℃, and collects two key factors, namely the average wind speed and the average temperature of the equipment area, which influence the wind power photovoltaic power generation;
step 2: the data processing module is used for respectively establishing collection functions of wind speed of a wind power region and equipment temperature of a photovoltaic region and processing data of the collection module;
the data acquisition and processing module is used for measuring and processing wind speed data of the wind power generation equipment and temperature data of the photovoltaic power generation equipment, respectively establishing standard functions related to the wind speed and the temperature and calculating similarity coefficients of the standard functions to obtain influence data capable of being acquired and calculated;
the wind power equipment randomly collects 104 collection points, and collected wind speed data is T 1 ＝10.62m/s、T 2 ＝7.3m/s...T 104 =11.6m/s constitutes an array f (x), where x =104; 87 data T are randomly extracted from the measured wind speed data 1 ＝8.9m/s、T 2 ＝9.6m/s...T 87 The =10.8m/s forms an array η (k), T k Representing the kth extraction data, where 87 points of wind speed are extracted, k =87, and calculating a similarity coefficient β of η (k) and f (x);
the judging module judges, when the similarity coefficient beta of eta (k) and f (x) is larger than or equal to 51.37%, an array eta (k) is extracted to obtain eta (k)', and the array is used for coordinated operation calculation;
the photovoltaic equipment randomly collects 86 collection points, and the collected temperature data is z 1 ＝25.3℃、z 2 ＝23.2℃...z 86 =21.8 ℃ making up an array g (j), where j =46; 49 data z were randomly extracted from the measured temperature data 1 ＝23.6℃、z 2 ＝25.3℃...z 49 =24.9 ℃ forming an array
m =49, calculating
A similarity coefficient α to g (x);
the judging module judges when
When the similarity coefficient alpha of g (x) is more than or equal to 40.58 percent, extracting the array
To obtain
The array is used for coordinated operation calculation;
and step 3: judging whether the wind and light output is in the system running state;
step 3.1: respectively defining a wind power output judgment coefficient delta and a photovoltaic output judgment coefficient omega;
and a wind power output judgment coefficient delta is obtained according to the data acquisition result:
photovoltaic output determination coefficient omega and photovoltaic unit floor area S i And scheduling L of current illumination intensity of photovoltaic unit h And arrays participating in the operation
Related to;
photovoltaic output determination coefficient ω:
step 3.2: selecting a control strategy according to the result obtained in the step 3.1, judging the magnitude delta and the magnitude omega e (0.57,0.71) of the result according to the condition to be the wind-solar output stress stage, representing the electric heat storage system as a friendly control stage, starting timing at the moment and executing a control strategy 2; the stage represented by the residual judgment data is a stage of gentle control of the electric heat storage system, timing is started, and a control strategy 3,t represents timing time (t =1min, 2min.. Nmin) is executed;
and 4, step 4: according to the total floor area S of the used electric heat storage device h Specific heat capacity c of electric heat storage material and current average temperature T of electric heat storage material h Calculating to obtain the reference speed v of the electric heat storage and discharge in the control stage 1 ，
The control strategy 2, namely the friendly stage, should be executed, the electric energy storage speed is far higher than the release speed, the electric energy storage capacity at the moment when the wind and light output force passes through the stage and enters the next control stage should reach the highest point of the full operation process, the redundant wind and light output force is obviously coordinated, and 528.2kw/s & gt v & gt at the stage should be executed Store up ＞463.7kw/s，205.8kw/s＞v Put And if the value is more than 168.6kw/s, the accurate value needs to be adjusted according to the running condition of the system.
The invention has the following advantages and beneficial effects:
in the operation process of the multi-energy power generation system, the operation plan of the heat storage system is corrected in real time in the operation process according to the detection and feedback of the judgment parameters of the wind and light operation state at the current moment due to the change of the system state caused by the wind and light fluctuation characteristics. The data acquisition and processing of key influence factors such as wind speed and temperature enable the execution of the control strategy to be more accurate. Ensuring that the electric heat storage capacity is at the lowest point at the moment that a large amount of abandoned wind and abandoned light need to be absorbed; in the period of the lowest point of wind and light output, the electric heat storage capacity is at the highest point, and heat can be released. The technology better coordinates the problem of the heat load on the wind and light power generation, and ensures that the absorption effect after strategy optimization is more excellent.
The invention provides a coordination control method for multi-energy power generation consumed by a heat storage system, aiming at the technical field of renewable energy power generation and new energy consumption. According to the correlation between the similarity coefficient and the influence wind and light absorption state, the judgment coefficient representing the current operation stage can be obtained through operation, a suitable control strategy can be selected according to the judgment coefficient, the storage and release reference speed can be obtained according to the self condition of the electric heat storage device, and different control strategies can be properly adjusted in a suitable speed range. By judging and considering the running state of the multi-source system equipment and the environmental factors influencing the result, the current running strategy of the electric heat storage can be corrected reasonably in time, so that the absorption process is more suitable and rigorous, the storage and the discharge of the electric heat storage equipment are controlled in a variable speed manner, the absorption rule can be better matched at the high and low points of the capacity of the electric heat storage equipment, and the absorption process is more stable and smoother.
Drawings
In order to facilitate the understanding and practice of the present invention for those of ordinary skill in the art, the following detailed description of the present invention is provided in conjunction with the accompanying drawings and the detailed description, the following examples are provided to illustrate the present invention, but it should be understood that the scope of the present invention is not limited by the detailed description.
FIG. 1 is a schematic diagram of the relationship between the electrical heat storage capacity and the wind/solar energy output point of the present invention;
fig. 2 is a control decision diagram of the present invention.
Detailed Description
The invention discloses a coordination control method for a heat storage system to absorb multi-energy power generation, which comprises the following steps as shown in figures 1 and 2:
step 1: and (6) data acquisition.
Step 1.1: collecting and quantifying, and collecting the occupied area S of the wind turbine generator w And the environmental density rho of the wind turbine generator w The floor area S of the photovoltaic unit i Total floor area S of electric heat storage equipment h And the specific heat capacity c of the electric heat storage and heat storage material.
Step 1.2: instantly acquiring variable and current total capacity H of electric heat storage equipment t And the relative air humidity rho w of the wind turbine at the current moment t And scheduling L of current illumination intensity of photovoltaic unit h Current average temperature T of the electric heat storage material h And collecting two factors which are more critical to influence of wind power photovoltaic power generation, namely the average wind speed and the average temperature of the equipment area.
Step 2: and the data processing module is used for respectively establishing acquisition functions of wind speed in a wind power region and equipment temperature in a photovoltaic region and processing the data of the acquisition module. The data acquisition and processing module is used for measuring and processing the wind speed of the wind power generation equipment and the temperature data of the photovoltaic power generation equipment, respectively establishing a standard function related to the wind speed and the temperature and calculating the similarity coefficient of the standard function, so as to obtain influence data which can be acquired and calculated.
The wind power equipment randomly collects x collection points, and the collected wind speed data is T 1 、T 2 ...T x Form an array f (x), T x Representing the xth measurement data. Randomly extracting a plurality of data T from the measured wind speed data 1 、T 2 ...T k Form an array eta (k), T k Representing the kth measurement data.
Calculating a similarity coefficient β of η (k) and f (x):
in the above formula, e represents the base of the natural logarithm and is a constant.
And the judging module is used for judging, when the similarity coefficient beta of the eta (k) and the f (x) is more than or equal to 51.37%, extracting the array eta (k), obtaining a new array eta (k) ', and using the array eta (k)', for the coordinated operation calculation.
Randomly collecting j collection points by photovoltaic equipment, wherein the collected temperature data is z 1 、z 2 ...z j Form an array g (j), z j Represents the jth measurement. Randomly extracting a plurality of data z from the measured temperature data 1 、z 2 ...z m Form an array
z m Representing the mth measurement data. Computing
A similarity coefficient α to g (x).
The discrimination module discriminates when
When the similarity coefficient alpha of g (x) is more than or equal to 40.58 percent, extracting the array
Resulting arrays
This array is used to coordinate the running computations.
The technical means used for collecting and processing the data of the wind speed of the wind power generation equipment and the temperature of the photovoltaic power generation equipment is adopted, and the related arrays which finally participate in the operation are selected according to the size of the similarity coefficient.
And step 3: and judging the approximate stage of the wind-solar output in the system running state, dividing the stage into 3 stages according to the change of the system state, and respectively naming the stages as a indifference stage, a friendly stage and a gentle stage according to corresponding energy storage strategies.
Step 3.1: and respectively defining a wind power output judgment coefficient delta and a photovoltaic output judgment coefficient omega. Wind power output determination coefficient
The floor area S of the wind turbine generator w And the environmental density rho of the wind turbine generator w Relative air humidity ρ w at the present time t And the array η (k) participating in the operation.
Wind power output determination coefficient δ:
photovoltaic output determination coefficient omega and photovoltaic unit floor area S i The current illumination intensity L of the photovoltaic unit h And arrays participating in the operation
It is related.
Photovoltaic output determination coefficient ω:
step 3.2: selecting a control strategy according to the result obtained in the step 3.1, if delta belongs to (0.23,0.41)' U (0.71,0.81) as a wind power output rising stage and omega belongs to (0.45,0.57) as a photovoltaic output rising stage, satisfying any judgment condition, expressing that the electric heat storage system is in a cold and desert control stage, and starting timing at the moment and executing the control strategy 1; delta and omega e (0.57,0.71) are wind-solar output stress stages, the electric heat storage system is a friendly control stage, timing is started at the moment, and a control strategy 2 is executed; the stage represented by the remaining determination data is a stage of gradual control of the electric heat storage system, and timing is started and a control strategy 3,t represents timing time (t =1min, 2min.. Nmin) is executed.
And 4, step 4: according to the total floor area S of the used electric heat storage device h Specific heat capacity c of electric heat storage and heat storage material, and current average temperature T of electric heat storage material h Calculating to obtain the reference speed v of electric heat storage and discharge in the control stage 1 ，
The method is divided into three stages according to the energy consumption capability of the electric heat storage, the change process of wind and light output is considered, and the consumption process is coordinated more accurately according to parameter change.
Control strategy 1: in the control stage of the cold desert stage, the electric heat storage should accelerate to release self heat and prepare for the energy storage in the emergency stage, the energy release speed in the stage should be higher than the storage speed, and 1.35v is executed 1 ＞v Placing the ＞1.27v 1 ，0.94v 1 ＞v Store up ＞0.81v 1 . After the control stage, the electric heat storage capacity state is the lowest point of the full operation process, and sufficient capacity space is left for wind and light absorption.
Control strategy 2: in the control stage of the friendly stage, the electric energy storage should present the maximum storage capacity to be completely consumed, at the moment, the residual capacity can be gradually released according to the requirement of a heat supply network, the electric energy storage speed is far higher than the release speed, the electric energy storage capacity reaches the highest point of the full operation process at the moment when the wind and light output force enters the next control stage through the stage, the redundant wind and light output force is obviously coordinated, and the stage is required to execute 2.13v 1 ＞v Store up ＞1.87v 1 ，0.83v 1 ＞v Put ＞0.68v 1 。
Control strategy 3: in the control stage of the gentle stage, the consumption requirement of wind and light output force is reduced, the electric energy storage releases energy at a constant speed and meets the consumption requirement of output force, and preparation is made for entering the output force rising control stage, the energy storage speed in the stage is lower than the release speed, and the heat release speed v is lower than the release speed Put ＝v 1 。
Example 1:
a certain wind power and heat storage combined control system detects the wind and light output consumption and the electric heat storage capacity state in one day, and the coordination technology is applied.
Step 1: collecting data;
step 1.1: collecting and quantifying, and collecting the occupied area S of the wind turbine generator w ＝15306m 2 And the environmental density rho of the wind turbine generator w ＝1.195kg/m 3 The floor area S of the photovoltaic unit i ＝20498m 2 Total floor area S of electric heat storage equipment h ＝270m 2 And the specific heat capacity c of the electric heat storage and heat storage material is =4186.
Step 1.2: instantly collecting variable and total capacity H of collected current electric heat storage equipment t =32MW · h, relative air humidity ρ w of the wind turbine at the current time t =0.21, current illumination intensity scheduling L of photovoltaic unit h ＝627W/m 2 Current average temperature T of the electric heat storage material h =53.7 ℃, and two factors which are critical to the influence of wind power photovoltaic power generation, namely the average wind speed and the average temperature of the equipment area are collected.
Step 2: and the data processing module is used for respectively establishing acquisition functions of wind speed in a wind power region and equipment temperature in a photovoltaic region and processing the data of the acquisition module.
The data acquisition and processing module is used for measuring and processing the wind speed of the wind power generation equipment and the temperature data of the photovoltaic power generation equipment, respectively establishing a standard function related to the wind speed and the temperature and calculating the similarity coefficient of the standard function, so as to obtain influence data which can be acquired and calculated.
The wind power equipment randomly collects 104 collection points, and the collected wind speed data is T 1 ＝10.62m/s、T 2 ＝7.3m/s...T 104 =11.6m/s constitutes an array f (x), where x =104. Randomly extracting 87 data T from the measured wind speed data 1 ＝8.9m/s、T 2 ＝9.6m/s...T 87 The =10.8m/s forms an array η (k), T k Represents the kth extraction data, where 87 points of wind speed are extracted, k =87, and calculates a similarity coefficient β of η (k) and f (x);
and the judging module is used for judging, and when the similarity coefficient beta of eta (k) and f (x) is more than or equal to 51.37%, extracting an array eta (k) to obtain eta (k)', wherein the array is used for calculating the coordinated operation.
The photovoltaic equipment randomly collects 86 collection points, and the collected temperature data is z 1 ＝25.3℃、z 2 ＝23.2℃...z 86 =21.8 ℃ constitutes an array g (j), where j =46. 49 data z were randomly extracted from the measured temperature data 1 ＝23.6℃、z 2 ＝25.3℃...z 49 =24.9 ℃ forming an array
m =49, calculating
A similarity coefficient α to g (x).
The discrimination module discriminates when
When the similarity coefficient alpha of g (x) is more than or equal to 40.58 percent, extracting the array
To obtain
This array is used to coordinate running computations.
And step 3: and judging that the wind-solar output is in the approximate stage of the system running state.
Step 3.1: and respectively defining a wind power output judgment coefficient delta and a photovoltaic output judgment coefficient omega.
The wind power output judgment coefficient delta is obtained according to the data acquisition result
Photovoltaic output determination coefficient omega and photovoltaic unit floor area S i And scheduling L of current illumination intensity of photovoltaic unit h And arrays participating in the operation
It is related.
Photovoltaic output determination coefficient ω:
step 3.2: selecting a control strategy according to the result obtained in the step 3.1, judging the magnitude delta and the magnitude omega e (0.57,0.71) of the result according to the condition to be the wind-solar output stress stage, representing the electric heat storage system as a friendly control stage, starting timing at the moment and executing a control strategy 2; the stage represented by the remaining determination data is an electric heat storage system slow control stage, timing is started, and a control strategy 3,t is executed to represent timing time (t =1min, 2min.. Nmin).
And 4, step 4: according to the total floor area S of the used electric heat storage device h Specific heat capacity c of electric heat storage and heat storage material, and current average temperature T of electric heat storage material h Calculating to obtain the reference speed v of electric heat storage and discharge in the control stage 1 ，
The control strategy 2, namely the friendly stage, should be executed, the electric energy storage speed is far higher than the release speed, the electric energy storage capacity at the moment when the wind and light output force passes through the stage and enters the next control stage should reach the highest point of the full operation process, the redundant wind and light output force is obviously coordinated, and 528.2kw/s & gt v & gt at the stage should be executed Store up ＞463.7kw/s，205.8kw/s＞v Put And if the value is more than 168.6kw/s, the accurate value needs to be adjusted according to the running condition of the system.
Claims (4)
1. A coordination control method for a heat storage system to absorb multi-energy power generation is characterized by comprising the following steps: the method comprises the following steps: step 1: a data acquisition module; step 2: the data processing module is used for respectively establishing collection functions of wind speed of a wind power region and equipment temperature of a photovoltaic region to process data of the data collection module; the data acquisition module and the data processing module are used for measuring and processing the wind speed of the wind power generation equipment and the temperature data of the photovoltaic power generation equipment, respectively establishing a standard function related to the wind speed and the temperature and calculating the similarity coefficient of the standard function to obtain influence data which can be acquired and calculated; and step 3: judging the stage of the wind-solar output in the system running state, dividing the stage into 3 stages according to the change of the system state, and respectively naming the stage as a cold desert control stage, a friendly control stage and a gentle control stage according to corresponding energy storage strategies; and 4, step 4: according to the total floor area S of the used electric heat storage device h Specific heat capacity c of electric heat storage and heat storage material, and current average temperature T of electric heat storage material h Calculating to obtain the reference speed v of electric heat storage and discharge in the control stage 1 ，
The method is divided into three stages according to the energy consumption capability of the electric heat storage, the change process of wind and light output is considered, and the consumption process is coordinated more accurately according to the parameter change;
the step 2 comprises the following steps: the wind power equipment randomly collects x collection points, and collected wind speed data is T 1 、T 2 ...T x Form an array f (x), T x Represents the xth measurement data; randomly extracting a plurality of data T from the measured wind speed data 1 、T 2 ...T k Form an array eta (k), T k Represents the kth measurement data;
calculating a similarity coefficient β of η (k) and f (x):
in the formula, e represents the base number of a natural logarithm and is a constant;
the judging module judges, when the similarity coefficient beta of eta (k) and f (x) is larger than or equal to 51.37%, an array eta (k) is extracted to obtain a new array eta (k) ', and the array eta (k)' is used for coordinated operation calculation;
randomly collecting j collection points by photovoltaic equipment, wherein the collected temperature data is z 1 、z 2 ...z j Form an array g (j), z j Represents the jth measurement data; randomly extracting a plurality of data z from measured temperature data 1 、z 2 ...z m Form an array
z m Represents the mth measurement data; computing
A similarity coefficient α to g (x);
the judging module judges when
When the similarity coefficient alpha of g (x) is more than or equal to 40.58 percent, extracting the array
Resulting array
The array is used for coordinated operation calculation;
collecting and processing data of wind speed of the wind power generation equipment and temperature of the photovoltaic power generation equipment, and selecting a related array finally participating in operation according to the size of the similarity coefficient;
the step 3 comprises the following steps: step 3.1: respectively defining a wind power output judgment coefficient delta and a photovoltaic output judgment coefficient omega; wind power output determination coefficient delta and wind turbine generator floor area S w And the environmental density rho of the wind turbine generator w Relative air humidity ρ w at the present time t And the array η (k) participating in the operation;
wind power output determination coefficient δ:
photovoltaic output determination coefficient omega and photovoltaic unit floor area S i The current illumination intensity L of the photovoltaic unit h And arrays participating in the operation
(ii) related;
photovoltaic output determination coefficient ω:
step 3.2: selecting a control strategy according to the result obtained in the step 3.1, if delta belongs to (0.23,0.41)' U (0.71,0.81) as a wind power output rising stage and omega belongs to (0.45,0.57) as a photovoltaic output rising stage, satisfying any judgment condition, expressing that the electric heat storage equipment is in a cold and desert control stage, and starting timing at the moment and executing the control strategy 1; delta and omega e (0.57,0.71) are wind and light output tension stages, the electric heat storage equipment is a friendly control stage, timing is started at the moment, and a control strategy 2 is executed; the stage represented by the remaining determination data is a stage of gentle control of the electric heat storage device, and timing is started and a control strategy 3,t represents timing time (t =1min, 2min.. Nmin) is executed.
2. The method of claim 1 wherein the heat storage system is configured to provide coordinated control of the consumption of multi-energy power generation, wherein: the step 1: the data acquisition module comprises the following steps:
step 1.1: collecting and quantifying, and collecting the occupied area S of the wind turbine generator w And the environmental density rho of the wind turbine generator w The floor area S of the photovoltaic unit i Total floor area S of electric heat storage equipment h The specific heat capacity c of the electric heat storage and heat storage material;
step 1.2: instantly acquiring variable and current total capacity H of electric heat storage equipment t And the relative air humidity rho w of the wind turbine at the current moment t And scheduling L of current illumination intensity of photovoltaic unit h Current average temperature T of electric heat storage material h And collecting two factors which are more critical to influence of wind power photovoltaic power generation, namely the average wind speed and the average temperature of the equipment area.
3. The method of claim 1 wherein the heat storage system is configured to provide coordinated control of the consumption of multi-energy power generation, wherein: the step 4 comprises the following steps:
control strategy 1: in the cold and desert control stage, the electric heat accumulation should accelerate to release its heat to prepare for the energy storage in the emergency stage, the energy release speed in this stage should be greater than the storage speed, and 1.35v is executed 1 ＞v Placing the ＞1.27v 1 ，0.94v 1 ＞v Store up ＞0.81v 1 (ii) a After the control stage, the electric heat storage capacity state is the lowest point of the full operation process, and sufficient capacity space is left for wind and light absorption;
control strategy 2: in a friendly control stage, the electric energy storage should present the maximum storage capacity to be completely consumed, at the moment, the residual capacity can be gradually released according to the requirement of a heat supply network, the electric energy storage speed is far higher than the release speed, the electric energy storage capacity reaches the highest point of the full operation process at the moment when the wind and light output force enters the next control stage through the stage, the redundant wind and light output force is obviously coordinated, and the stage should execute 2.13v 1 ＞v Store up ＞1.87v 1 ，0.83v 1 ＞v Put ＞0.68v 1 ；
Control strategy 3: at a gentle step controlAnd in the stage, the wind and light output consumption requirement is reduced, the electric energy storage releases energy at a constant speed and meets the consumption requirement of output, and preparation is made for entering the output rise control stage, the energy storage speed in the stage is lower than the release speed, and the heat release speed v is lower than the release speed Put ＝v 1 。
4. The method of claim 1 wherein the coordinated control of the thermal storage system to absorb the multi-energy power generation is performed by: the control method comprises the following steps:
the wind power and heat storage combined control system detects wind and light output consumption and electric heat storage capacity states in one day and applies the coordination technology;
step 1: a data acquisition module;
step 1.1: collecting and quantifying, and collecting the occupied area S of the wind turbine generator w ＝15306m 2 And the environmental density rho of the wind turbine generator w ＝1.195kg/m 3 The floor area S of the photovoltaic unit i ＝20498m 2 Total floor area S of electric heat storage equipment h ＝270m 2 The specific heat capacity c of the electric heat storage and heat storage material is =4186;
step 1.2: instantly collecting variable and current total capacity H of collected electric heat storage equipment t =32MW · h, relative air humidity ρ w of the wind turbine at the current time t =0.21, current illumination intensity scheduling L of photovoltaic unit h ＝627W/m 2 Current average temperature T of electric heat storage material h =53.7 ℃, and collects two key factors, namely the average wind speed and the average temperature of the equipment area, which influence the wind power photovoltaic power generation;
step 2: the data processing module is used for respectively establishing acquisition functions of wind speed in a wind power region and equipment temperature in a photovoltaic region and processing data of the data acquisition module;
the data acquisition module and the data processing module are used for measuring and processing the wind speed of the wind power generation equipment and the temperature data of the photovoltaic power generation equipment, respectively establishing a standard function related to the wind speed and the temperature and calculating the similarity coefficient of the standard function to obtain influence data which can be acquired and calculated;
wind power equipment104 acquisition points are acquired by the wind speed acquisition machine, and the acquired wind speed data is T 1 ＝10.62m/s、T 2 ＝7.3m/s...T 104 =11.6m/s constitutes an array f (x), where x =104; 87 data T are randomly extracted from the measured wind speed data 1 ＝8.9m/s、T 2 ＝9.6m/s...T 87 The =10.8m/s forms an array η (k), T k Represents the kth extraction data, where 87 points of wind speed are extracted, k =87, and calculates a similarity coefficient β of η (k) and f (x);
the judging module judges, when the similarity coefficient beta of eta (k) and f (x) is larger than or equal to 51.37%, an array eta (k) is extracted to obtain eta (k)', and the array is used for coordinated operation calculation;
the photovoltaic equipment randomly collects 86 collection points and collected temperature data z 1 ＝25.3℃、z 2 ＝23.2℃、...z 86 =21.8 ℃ making up an array g (j), where j =46; 49 data z were randomly extracted from the measured temperature data 1 ＝23.6℃、z 2 ＝25.3℃、...z 49 =24.9 ℃ forming an array
m =49, calculating
A similarity coefficient α to g (x);
the discrimination module discriminates when
When the similarity coefficient alpha of g (x) is more than or equal to 40.58 percent, extracting the array
To obtain
The array is used for coordinated operation calculation;
and step 3: judging whether the wind and light output is in a system running state;
step 3.1: respectively defining a wind power output judgment coefficient delta and a photovoltaic output judgment coefficient omega;
and a wind power output judgment coefficient delta is obtained according to the data acquisition result:
photovoltaic output determination coefficient omega and photovoltaic unit floor area S i And scheduling L of current illumination intensity of photovoltaic unit h And arrays participating in the operation
(ii) related;
photovoltaic output determination coefficient ω:
step 3.2: selecting a control strategy according to the result obtained in the step 3.1, judging the magnitude delta and the magnitude omega e (0.57,0.71) of the result according to the condition to be the wind-solar output stress stage, representing the electric heat storage equipment as a friendly control stage, starting timing at the moment and executing a control strategy 2; the stage represented by the residual judgment data is a stage of gentle control of the electric heat storage equipment, timing is started, and a control strategy 3,t represents timing time (t =1min, 2min.. Nmin) is executed;
and 4, step 4: according to the total floor area S of the used electric heat storage device h Specific heat capacity c of electric heat storage material and current average temperature T of electric heat storage material h Is calculated to obtainReference velocity v of electric heat storage and discharge to this control stage 1 ，
The control strategy 2, namely the friendly control stage, should be executed, the electric energy storage speed is far higher than the release speed, the electric energy storage capacity at the moment when the wind and light output force passes through the control stage and enters the next control stage should reach the highest point of the full operation process, the redundant wind and light output force is obviously coordinated, and 528.2kw/s & gt v & gt at the control stage should be executed Store up ＞463.7kw/s，205.8kw/s＞v Put And if the value is more than 168.6kw/s, the accurate value needs to be adjusted according to the running condition of the system.
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