Disclosure of Invention
The invention solves the technical problem of unreasonable cooperative adjustment of the energy storage system in the prior art by providing the working method, the device, the equipment and the medium of the molten salt energy storage system based on the power prediction of the energy utilization end, and realizes the technical effect of reasonably adjusting the operation of the molten salt energy storage system.
In a first aspect, the invention provides a molten salt energy storage system working method based on energy consumption end power prediction, the method comprising:
Acquiring energy consumption data of a target area in a historical time period, and dividing the historical time period by weather data in the historical time period to obtain a plurality of energy consumption time periods, wherein the duration n of each energy consumption time period is greater than 1h, n is an integer, and the weather data comprise rainfall data, illumination data and wind power data;
for each energy usage period, steps S121-S123 are performed, including:
Step S121, obtaining the capacity to be stored in the energy using period according to the sum of the energy using periods and the unit output force of the target area in the energy using period;
Step S122, dividing the target area of the energy using period with energy using characteristics to obtain energy using type distribution of the energy using period, wherein the energy using characteristics comprise single life energy, single business energy, single processing and manufacturing energy, life and business energy, life and processing and manufacturing energy, business and processing and manufacturing energy and business, life and processing and manufacturing mixed energy;
step S123, the energy storage operation strategy of the molten salt energy storage system of the energy consumption period is redetermined according to the energy storage state of the molten salt energy storage system of the energy consumption period, the energy storage capacity to be stored of the energy consumption period, the energy storage states of the other energy storage systems of the energy consumption period, the energy consumption type distribution of the energy consumption period and the meteorological characteristics of the energy consumption period;
and determining the energy storage operation strategy of the molten salt energy storage system of the target area in a preset time period according to the energy storage operation strategies of the molten salt energy storage systems of the energy consumption time periods.
Further, dividing the target area of the energy use period by the energy use characteristics to obtain the energy use type distribution of the energy use period, including:
dividing a target area of the energy utilization period by energy utilization characteristics to obtain subareas corresponding to each energy utilization characteristic;
Determining the energy consumption of the subarea under each energy consumption characteristic in the energy consumption period;
and determining the energy utilization ratio of the energy utilization features in the energy utilization period according to the energy utilization of the subregions under the energy utilization features in the energy utilization period, and taking the energy utilization ratio of the energy utilization period as the energy utilization type distribution of the energy utilization period.
Further, the energy storage operation strategy of the molten salt energy storage system of the energy using period is redetermined according to the energy storage state of the molten salt energy storage system of the energy using period, the energy storage capacity to be stored of the energy using period, the energy storage states of the rest energy storage systems of the energy using period, the energy using type distribution of the energy using period and the meteorological characteristics of the energy using period, and the method comprises the following steps:
When (when)>0 AndWhen (1):
Wherein if itIf the energy is smaller than 0, no energy storage is performed, ifIf the energy is greater than 0, energy storage is carried out;
When (when)>0 AndWhen (1):
Wherein, theIs the firstA charging and discharging strategy of the molten salt energy storage system in each energy utilization period,Is the firstThe energy storage capacity to be stored in each energy utilization period,Is the firstThe energy storage state of the fused salt energy storage system in each energy utilization period,Is the firstThe energy storage states of the remaining energy storage systems of the respective energy usage periods,The weather characteristic of the energy utilization period is recorded as 0.9 when the weather characteristic is a sunny day, and the other weather characteristics are recorded as 0.5; In order to preset constant for energy consumption type distribution, when the energy consumption ratio of the sum of single processing energy, life energy and processing energy, business energy and processing energy and mixed energy of business energy, life energy and processing energy in the energy consumption period is larger than a preset threshold value,Record as 0.3, otherwise record as 0.8;
When (when)At 0:
Wherein, theIs the maximum capacity of the molten salt energy storage system.
Further, the historical time period is divided by the meteorological data in the historical time period to obtain a plurality of energy consumption time periods, which comprises the following steps:
Carrying out data preprocessing on meteorological data in a historical time period, wherein the data preprocessing comprises missing value processing, abnormal value processing and data standardization processing;
constructing a plurality of typical meteorological features, wherein the typical meteorological features at least comprise a rainy day feature, a sunny day feature, a cloudy feature and a snowy feature;
determining the number of preset clusters;
under the K-means algorithm, the historical time period is divided into a plurality of energy using time periods according to a plurality of typical meteorological features and the number of preset clusters.
Further, determining the energy storage operation strategy of the molten salt energy storage system of the target area in the preset time period according to the energy storage operation strategies of the molten salt energy storage systems of the energy utilization time periods, wherein the energy storage operation strategy comprises the following steps:
Binding an energy storage operation strategy of a molten salt energy storage system in an energy use period, meteorological features of the energy use period and energy use type distribution of the energy use period into a data set, and obtaining a plurality of data sets in total;
Inputting a plurality of data sets into a neural network to be trained so as to train the neural network to be trained, and when the training requirement is met, storing the latest neural network parameters and obtaining a target neural network, wherein the neural network to be trained is used for predicting an energy storage operation strategy of a fused salt energy storage system;
And acquiring the predicted meteorological features and the predicted energy type distribution of the preset time period, and inputting the predicted meteorological features and the predicted energy type distribution into a target neural network to obtain an energy storage operation strategy of the molten salt energy storage system of the preset time period.
Further, determining the energy storage operation strategy of the molten salt energy storage system of the target area in the preset time period according to the energy storage operation strategies of the molten salt energy storage systems of the energy utilization time periods, and further comprising:
Dividing a preset time period into m preset time sub-periods, wherein the length of each preset time sub-period is 1h;
The method comprises the steps of sequentially matching weather similarity of predicted weather data of each preset time sub-section with weather features of a plurality of energy utilization periods, and screening out a plurality of target energy utilization periods, wherein one preset time sub-section corresponds to the plurality of target energy utilization periods;
Performing energy distribution similarity matching according to the predicted energy type distribution corresponding to the preset time sub-section and the energy type distribution of a plurality of energy use periods to obtain target energy type distribution of the preset time sub-section;
determining an energy storage operation strategy of the molten salt energy storage system corresponding to each preset time sub-section according to the corresponding target energy use time period and the corresponding target energy use type distribution;
And determining the energy storage operation strategy of the molten salt energy storage system corresponding to the preset time period according to the energy storage operation strategy of the molten salt energy storage system corresponding to the plurality of preset time periods.
Further, according to the sum of the energy consumption period and the unit output force of the target area in the energy consumption period, the energy storage capacity to be stored in the energy consumption period is obtained, and the method comprises the following steps:
Wherein, theIs the firstThe energy storage capacity to be stored in each energy utilization period,Is the firstThe sum of the energy usage of the individual energy usage periods,Is the firstThe unit output of each energy consumption period.
In a second aspect, the invention provides a molten salt energy storage system working device based on energy consumption end power prediction, the device comprising:
The data acquisition module is used for acquiring energy utilization data of the target area in a historical time period, and dividing the historical time period by weather data in the historical time period to obtain a plurality of energy utilization time periods, wherein the duration n of each energy utilization time period is greater than 1h, n is an integer, and the weather data comprise rainfall data, illumination data and wind power data;
The first strategy module is used for executing steps S121-S123 for each energy using period, and comprises the steps that S121 is used for obtaining the capacity to be stored in the energy using period according to the sum of energy using periods and the unit output force of a target area in the energy using period; step S122, dividing the target area of the energy using period with energy using characteristics to obtain energy using type distribution of the energy using period, wherein the energy using characteristics comprise single life energy, single business energy, single processing and manufacturing energy, life and business energy, life and processing and manufacturing energy, business and processing and manufacturing energy and business, life and processing and manufacturing mixed energy; step S123, the energy storage operation strategy of the molten salt energy storage system of the energy consumption period is redetermined according to the energy storage state of the molten salt energy storage system of the energy consumption period, the energy storage capacity to be stored of the energy consumption period, the energy storage states of the other energy storage systems of the energy consumption period, the energy consumption type distribution of the energy consumption period and the meteorological characteristics of the energy consumption period;
And the second strategy module is used for determining the energy storage operation strategy of the molten salt energy storage system in the target area in a preset time period according to the energy storage operation strategies of the molten salt energy storage system in the energy use time periods.
In a third aspect, the present invention provides an electronic device, comprising:
A processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to execute to implement the molten salt energy storage system operating method based on energy end power prediction as provided in the first aspect.
In a fourth aspect, the invention provides a non-transitory computer readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform a molten salt energy storage system operating method implementing energy use end power prediction as provided in the first aspect.
One or more technical schemes provided by the invention have at least the following technical effects or advantages:
According to the invention, according to the time periods divided by different weather features, the energy consumption rules under different weather modes can be identified, and the charging and discharging strategies can be formulated for the molten salt energy storage system more accurately by combining the energy consumption rules under different weather modes.
The invention is realized by redefining the firstThe charging and discharging strategy of the molten salt energy storage system in the individual energy utilization period can provide more accurate guidance for the prediction of the charging and discharging strategy of the molten salt energy storage system.
According to the invention, the energy storage state, the capacity to be stored and the multi-system cooperative data are integrated, so that the energy storage/release rhythm can be optimized, the advantage of large heat capacity of the molten salt system is fully utilized, the heat storage efficiency is optimized in the low valley period of the power grid, and the high-grade energy consumption requirements of industrial heat supply and the like are precisely matched in the peak period.
According to the invention, the energy consumption type of the area and the period meteorological characteristics are combined, the multi-energy coupling supply is realized, the states of other energy storage systems are monitored in real time, a complementary mechanism is established, and the peak regulation capacity of molten salt energy storage is exerted when the short-time energy storage system is overloaded.
The dynamic optimization processing provided by the invention can effectively solve the problems of heat storage waste or insufficient energy supply caused by the traditional fixed strategy. Because the thermal response of the molten salt system is slower, the invention is based on multi-source data modeling prediction, can avoid the delay effect caused by thermal inertia, and simultaneously remarkably improves the renewable energy consumption capability and the overall economy through multi-system cooperative scheduling.
According to the method, the time period is split, and the similarity calculation is carried out by using the weather and the characteristics, so that an accurate basis can be provided for the prediction of the energy storage operation strategy of the future molten salt energy storage system.
Detailed Description
The embodiment of the invention solves the technical problem of unreasonable cooperative adjustment of the energy storage system in the prior art by providing the working method of the molten salt energy storage system based on the power prediction of the energy utilization end.
The technical scheme of the invention aims to solve the technical problems, and the general idea is as follows:
the method comprises the steps of obtaining energy consumption data of a target area in a historical time period, dividing the historical time period by meteorological data in the historical time period to obtain a plurality of energy consumption time periods, wherein the duration n of each energy consumption time period is greater than 1h, n is an integer, the meteorological data comprise rainfall data, illumination data and wind power data, executing steps S121-S123 for each energy consumption time period, determining the energy storage capacity to be stored of the energy consumption time period according to the sum of the energy consumption time periods and the unit output capacity of a target area in the energy consumption time period, determining the energy storage capacity to be stored of the energy consumption time period according to the energy storage system in the energy consumption time period, determining the operation strategy of the energy storage system in the energy storage time period according to the energy consumption time period, determining the energy storage system operation strategy of the energy storage system in the energy consumption time period, and the rest time period, and determining the energy storage system operation strategy of the energy storage system in the energy storage time period according to the energy consumption time period, and the energy storage system operation strategy of the energy storage system in the energy consumption time period.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
First, the term "and/or" appearing herein is merely an association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B, and may mean that a exists alone, while a and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
The invention provides a working method of a molten salt energy storage system based on energy consumption end power prediction as shown in fig. 1, which comprises the following steps of S11-S13:
Step S11, energy utilization data of a target area in a historical time period are obtained, the historical time period is divided according to meteorological data in the historical time period, and a plurality of energy utilization time periods are obtained, wherein the duration n of each energy utilization time period is greater than 1h, n is an integer, and the meteorological data comprise rainfall data, illumination data and wind power data.
The target area can be a complete distribution sleeve facility and has large scale, and in the target area, the energy consumption can be obtained through various generator sets, such as a thermal power generating set, a hydroelectric generating set, a wind generating set, a solar energy generating set and the like.
In the target area, there may be several types of energy storage facilities for conditioning energy usage, such as battery energy storage systems, pumped storage power stations, compressed air energy storage, and thermal energy storage systems (molten salt energy storage systems are one of the thermal energy storage systems).
Molten salt energy storage systems are an energy storage technology that utilizes molten salt as a thermal energy storage medium by converting solar radiation into thermal energy and using the molten salt to store such energy for conversion to electrical energy when needed.
The method comprises the steps of dividing a historical time period by meteorological data in the historical time period to obtain a plurality of energy consumption time periods, wherein the steps comprise:
And carrying out data preprocessing on the meteorological data in the historical time period, wherein the data preprocessing comprises missing value processing, abnormal value processing and data standardization processing.
The weather data for the historical time period may be weather data for years past the target area. The meteorological data may include temperature, humidity, barometric pressure, wind speed, wind direction, precipitation, cloud and clouds, sun and radiation, visibility, extreme weather phenomena, air quality, and the like.
A number of typical weather features are constructed including at least a rainy day feature, a sunny day feature, a cloudy feature, and a snowy feature.
A typical weather feature is a feature that represents different weather conditions.
For example:
rainy day characteristics is the average rainfall over a period or day.
Sunny day characteristics, the cumulative number of hours of sunny day or period.
Snowy character: average snowfall over a day or period of time.
Cloudiness features-cloud coverage over a day or period of time.
In addition, combined features such as clear index (combined light and rainfall), extreme weather index (heavy rainfall and strong wind, etc.) can be constructed to better capture complex weather patterns.
It will be appreciated that several typical weather features are constructed not only to distinguish weather for each time period, but also to combine each unit with weather features. (the output efficiency of each type of machine set is different under different weather conditions)
Under K-means algorithm, dividing the historical time period into a plurality of energy using time periods according to a plurality of typical meteorological features and the preset cluster number.
K-means is a common clustering algorithm, and the K-means distributes data points into K clusters by an iterative optimization method so as to minimize intra-cluster squaring errors
The clustering effect at different k values can be evaluated by an elbow method (Elbow Method) or a contour coefficient (Silhouette Score) or the like, so that the optimal preset cluster number is selected.
The method comprises the steps of selecting k data points randomly as initial centroids, calculating the distance from each data point to all centroids, assigning the distance to the nearest cluster, and then recalculating the positions of the centroids according to all points in the cluster. This process is repeated until no significant change in centroid occurs.
After clustering is completed, the characteristics of each cluster (i.e., the typical weather features represented by each cluster) can be analyzed, thereby defining the typical weather features for each hour during the historical period, and dividing the hours that are consecutive and have the same typical weather features into one energy usage period.
According to the invention, according to the time periods divided by different weather features, the energy consumption rules under different weather modes can be identified, and the charging and discharging strategies can be formulated for the molten salt energy storage system more accurately by combining the energy consumption rules under different weather modes.
Step S12, steps S121 to S123 are performed for each energy use period.
Step S121, obtaining the capacity to be stored in the energy using period according to the sum of the energy using periods and the unit output force of the target area in the energy using period.
The method specifically comprises the following steps:
Wherein, theIs the firstThe energy storage capacity to be stored in each energy utilization period,Is the firstThe sum of the energy usage of the individual energy usage periods,Is the firstThe unit output of each energy consumption period.
The sum of the energy consumption period refers to all the energy consumption of the target area in the energy consumption period, and the unit output of the energy consumption period refers to the unit output of the generator unit of the target area in the energy consumption period.
When (when)When >0, the energy storage system is required to store energyWhen <0, the energy storage system is required to send energy, whenWhen the value is equal to 0, the data is not stored and not sent.
In step S122, the target area of the energy consumption period is divided by the energy consumption characteristics to obtain the energy consumption type distribution of the energy consumption period, wherein the energy consumption characteristics include single life energy, single business energy, single processing energy, life and business energy, life and processing energy, business and processing energy, and business, life and processing energy. (municipal energy can be recorded as the energy for life)
The energy utilization characteristic refers to the energy utilization type of a certain area. For example, taking a floor A in a certain area as an example, A has a plurality of floors, when all floors of A are residential buildings, the area occupied by A is single life energy, if the first floor A is business, more than floor 2 is residential, the area occupied by A is life and business energy, if the first floor A is business, 2-5 floors are production lines, and 6 floors and more are life areas, the area occupied by A is business, life and manufacturing hybrid energy.
Dividing the target area of the energy using period by the energy using characteristics to obtain the energy using type distribution of the energy using period, comprising the following steps:
dividing the target area of the energy utilization period by energy utilization characteristics to obtain subareas corresponding to each energy utilization characteristic.
According to the above example, the target area is divided in turn, and several sub-areas are obtained.
The energy consumption of the subregion under each energy consumption characteristic in the energy consumption period is determined in sequence, and specifically, the energy consumption of the subregion with the same energy consumption characteristic in the energy consumption period can be summed to obtain the energy consumption of the subregion under each energy consumption characteristic in the energy consumption period.
And determining the energy utilization ratio of the energy utilization features in the energy utilization period according to the energy utilization of the subregions under the energy utilization features in the energy utilization period, and taking the energy utilization ratio of the energy utilization period as the energy utilization type distribution of the energy utilization period.
And comparing the energy consumption of each energy consumption characteristic in a certain energy consumption period to obtain the energy consumption duty ratio.
For example, at a certain energy period, the energy consumption ratio of single life energy, single business energy, single manufacturing energy, life and business energy, life and manufacturing energy, business and manufacturing energy, and business, life and manufacturing energy is=0.15:0.08:0.21:0.34:0.03:0.17:0.02.
Step S123, the energy storage operation strategy of the molten salt energy storage system of the energy consumption period is redetermined according to the energy storage state of the molten salt energy storage system of the energy consumption period, the energy storage capacity to be stored of the energy consumption period, the energy storage states of the other energy storage systems of the energy consumption period, the energy consumption type distribution of the energy consumption period and the meteorological characteristics of the energy consumption period.
It should be noted that the target area is a city with more mature development, which means that the energy storage facilities are more complete. For molten salt energy storage systems, the molten salt energy storage system has significant advantages in large-scale and long-time energy storage, especially in the field of solar thermal power generation. However, in terms of energy conversion efficiency and response speed (because there is a secondary conversion), it is lower than, for example, a battery energy storage system. Therefore, other energy storage systems are considered to be provided in the present invention in a much larger ratio than molten salt energy storage systems, and inWhen the number of the components is greater than 0,>。
The method specifically comprises the following steps:
When (when)>0 AndWhen (1):
Wherein if itIf the energy is smaller than 0, no energy storage is performed, ifIf the energy is greater than 0, energy storage is carried out;
When (when)>0 AndWhen (1):
Wherein, theIs the firstA charging and discharging strategy of the molten salt energy storage system in each energy utilization period,Is the firstThe energy storage capacity to be stored in each energy utilization period,Is the firstThe energy storage state of the fused salt energy storage system in each energy utilization period,Is the firstThe energy storage states of the remaining energy storage systems of the respective energy usage periods,The weather characteristic of the energy utilization period is recorded as 0.9 when the weather characteristic is a sunny day, and the other weather characteristics are recorded as 0.5; In order to preset constant for energy consumption type distribution, when the energy consumption ratio of the sum of single processing energy, life energy and processing energy, business energy and processing energy and mixed energy of business energy, life energy and processing energy in the energy consumption period is larger than a preset threshold value,And the preset threshold value is 0.5, and the like, and can be specifically determined according to actual conditions.
When (when)At 0:
Wherein, theIs the maximum capacity of the molten salt energy storage system.
The energy storage state of the molten salt energy storage system refers to the energy storage capacity of the molten salt energy storage system which is remained, namely the capacity which can store energy, and the energy storage state of the rest energy storage system refers to the energy storage capacity of the rest energy storage system which is remained.
It should be noted that, the firstThe charge-discharge strategy of the molten salt energy storage system for each energy usage period does not mean that the first time has occurred in the pastCharging and discharging strategy of molten salt energy storage system in individual energy using period, and re-aligning the firstA charge-discharge strategy of the molten salt energy storage system in the individual energy usage period is determined.
The invention is realized by redefining the firstThe charging and discharging strategy of the molten salt energy storage system in the individual energy utilization period can provide more accurate guidance for the prediction of the charging and discharging strategy of the molten salt energy storage system.
According to the invention, the energy storage state, the capacity to be stored and the multi-system cooperative data are integrated, so that the energy storage/release rhythm can be optimized, the advantage of large heat capacity of the molten salt system is fully utilized, the heat storage efficiency is optimized in the low valley period of the power grid, and the high-grade energy consumption requirements of industrial heat supply and the like are precisely matched in the peak period.
According to the invention, the multi-energy coupling supply is realized by combining the regional energy utilization type and the time period characteristics, the states of other energy storage systems are monitored in real time, a complementary mechanism is established, and the peak regulation capacity of molten salt energy storage is exerted when the short-time energy storage system is overloaded.
The dynamic optimization processing provided by the invention can effectively solve the problems of heat storage waste or insufficient energy supply caused by the traditional fixed strategy. Because the thermal response of the molten salt system is slower, the invention is based on multi-source data modeling prediction, can avoid the delay effect caused by thermal inertia, and simultaneously remarkably improves the renewable energy consumption capability and the overall economy through multi-system cooperative scheduling.
Step S13, determining the energy storage operation strategy of the molten salt energy storage system of the target area in a preset time period according to the energy storage operation strategies of the molten salt energy storage systems of the energy consumption time periods.
[ Method 1]
Binding an energy storage operation strategy of a molten salt energy storage system in an energy use period, meteorological features of the energy use period and energy use type distribution of the energy use period into a data set, and obtaining a plurality of data sets in total;
Inputting a plurality of data sets into a neural network to be trained so as to train the neural network to be trained, and when the training requirement is met, storing the latest neural network parameters and obtaining a target neural network, wherein the neural network to be trained is used for predicting an energy storage operation strategy of a fused salt energy storage system;
And acquiring the predicted meteorological features and the predicted energy type distribution of the preset time period, and inputting the predicted meteorological features and the predicted energy type distribution into a target neural network to obtain an energy storage operation strategy of the molten salt energy storage system of the preset time period.
The preset training requirements may be a maximum training number, a standard reaching rate threshold, etc., without limitation. The preset time period may be a future time period that should be not far from the current time to facilitate predicting meteorological features and energy usage type distribution.
[ Method 2]
Dividing the preset time period into m preset time sub-periods, wherein the length of each preset time sub-period is 1h, sequentially matching the predicted meteorological data of each preset time sub-period with meteorological features of a plurality of energy utilization periods, and screening out a plurality of target energy utilization periods, wherein one preset time sub-period can correspond to the plurality of target energy utilization periods.
When the similarity of certain predicted meteorological data and meteorological features of the energy utilization period is matched with the weather similarity threshold value, the predicted meteorological data and the weather similarity threshold value can be matched.
And performing energy distribution similarity matching according to the predicted energy type distribution corresponding to the preset time sub-section and the energy type distribution of the plurality of energy use periods to obtain the target energy type distribution of the preset time sub-section.
Based on the similar processing mode, when the predicted energy type distribution corresponding to a certain preset time sub-period and the energy type distribution of a certain energy period are larger than the preset energy distribution similarity threshold, the predicted energy type distribution and the energy type distribution are matched. Also the target energy usage type distribution for the preset time period may comprise several.
And specifically, a plurality of target energy consumption time periods screen out the target energy consumption type distribution of the preset time sub-period, and the highest value of the product of the similarity of the target energy consumption time periods and the target energy consumption type distribution is used as the energy storage operation strategy corresponding to the final energy consumption time period.
For example, the target energy consumption period is 150 segments in total, wherein 50 energy consumption types belonging to the energy consumption period are distributed, that is, in 50 energy consumption types, the highest value is determined according to the similarity of meteorological features and the similarity of the energy consumption distribution, the corresponding energy consumption period of the highest value is taken as the final energy consumption period, and the energy storage operation strategy of the energy storage system corresponding to the final energy consumption period, that is, the energy storage operation strategy of the molten salt energy storage system corresponding to the preset time period is determined.
And determining the energy storage operation strategy of the molten salt energy storage system corresponding to the preset time period according to the energy storage operation strategy of the molten salt energy storage system corresponding to the plurality of preset time periods.
According to the method, the time period is split, and the similarity calculation is carried out by using the weather and the characteristics, so that an accurate basis can be provided for the prediction of the energy storage operation strategy of the future molten salt energy storage system.
In summary, the invention provides a working method of a molten salt energy storage system based on energy consumption end power prediction, which comprises the steps of obtaining energy consumption data of a target area in a historical time period, dividing the historical time period by meteorological data in the historical time period to obtain a plurality of energy consumption time periods, wherein the duration n of each energy consumption time period is greater than 1h and is an integer, the meteorological data comprise rainfall data, illumination data and wind power data, executing steps S121-S123 for each energy consumption time period, wherein the steps comprise the step S121 of determining the energy storage capacity of the energy storage system according to the sum of the energy consumption time periods and the unit output capacity of the target area in the energy consumption time period, the step S122 of dividing the target area in the energy consumption time period by the energy consumption characteristics to obtain the energy consumption type distribution of the energy consumption time period, and the energy consumption characteristics comprise single life energy consumption, single commercial energy consumption, single processing molten salt manufacturing energy consumption, life and commercial and processing manufacturing energy consumption, and life and manufacturing mixed energy, determining the energy storage system running strategy of the energy storage system in the energy storage time period according to the energy storage system in the energy storage time period, the energy storage system in the energy storage time period, and the energy storage system in the rest time period, and the energy storage system in the energy storage system running time of the energy storage system in the energy storage time period.
According to the invention, according to the time periods divided by different weather features, the energy consumption rules under different weather modes can be identified, and the charging and discharging strategies can be formulated for the molten salt energy storage system more accurately by combining the energy consumption rules under different weather modes.
The invention is realized by redefining the firstThe charging and discharging strategy of the molten salt energy storage system in the individual energy utilization period can provide more accurate guidance for the prediction of the charging and discharging strategy of the molten salt energy storage system.
According to the invention, the energy storage state, the capacity to be stored and the multi-system cooperative data are integrated, so that the energy storage/release rhythm can be optimized, the advantage of large heat capacity of the molten salt system is fully utilized, the heat storage efficiency is optimized in the low valley period of the power grid, and the high-grade energy consumption requirements of industrial heat supply and the like are precisely matched in the peak period.
According to the invention, the multi-energy coupling supply is realized by combining the regional energy utilization type and the time period characteristics, the states of other energy storage systems are monitored in real time, a complementary mechanism is established, and the peak regulation capacity of molten salt energy storage is exerted when the short-time energy storage system is overloaded.
The dynamic optimization processing provided by the invention can effectively solve the problems of heat storage waste or insufficient energy supply caused by the traditional fixed strategy. Because the thermal response of the molten salt system is slower, the invention is based on multi-source data modeling prediction, can avoid the delay effect caused by thermal inertia, and simultaneously remarkably improves the renewable energy consumption capability and the overall economy through multi-system cooperative scheduling.
According to the method, the time period is split, and the similarity calculation is carried out by using the weather and the characteristics, so that an accurate basis can be provided for the prediction of the energy storage operation strategy of the future molten salt energy storage system.
Based on the same inventive concept, the invention provides a molten salt energy storage system working device based on energy consumption end power prediction as shown in fig. 2, wherein the device comprises:
The data acquisition module 21 is configured to acquire energy consumption data of the target area in a historical time period, and divide the historical time period by weather data in the historical time period to obtain a plurality of energy consumption time periods, where a duration n of each energy consumption time period is greater than 1h, n is an integer, and the weather data includes rainfall data, illumination data and wind power data;
The first strategy module 22 is configured to perform steps S121-S123 for each energy use period, including step S121 of obtaining a to-be-stored energy capacity of the energy use period according to a sum of energy use periods and a set output of a target area in the energy use period, step S122 of dividing the target area of the energy use period by energy use characteristics to obtain an energy use type distribution of the energy use period, wherein the energy use characteristics include single life energy, single business energy, single process manufacturing energy, life and business energy, life and process manufacturing energy, business and process manufacturing energy, and business, life and process manufacturing mixed energy;
The second policy module 23 is configured to determine an energy storage operation policy of the molten salt energy storage system in a preset time period in the target area according to the energy storage operation policies of the molten salt energy storage system in the energy use periods.
Based on the same inventive concept, the application also provides the electronic equipment, which comprises:
A processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to execute to implement the molten salt energy storage system operating method based on energy end power prediction as provided previously.
Based on the same inventive concept, the application also provides a non-transitory computer readable storage medium, which when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute the molten salt energy storage system working method based on the energy use end power prediction, which is provided by the application.
Since the electronic device described in this embodiment is an electronic device used to implement the method for processing information in the embodiment of the present invention, those skilled in the art will be able to understand the specific implementation of the electronic device in this embodiment and various modifications thereof based on the method for processing information described in the embodiment of the present invention, so how the method in the embodiment of the present invention is implemented in this electronic device will not be described in detail herein. Any electronic device used by those skilled in the art to implement the information processing method in the embodiment of the present invention is within the scope of the present invention.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.