CN115409411A - Energy storage and electricity utilization method and system - Google Patents
Energy storage and electricity utilization method and systemDownload PDFInfo
- Publication number
- CN115409411A CN115409411ACN202211154893.6ACN202211154893ACN115409411ACN 115409411 ACN115409411 ACN 115409411ACN 202211154893 ACN202211154893 ACN 202211154893ACN 115409411 ACN115409411 ACN 115409411A
- Authority
- CN
- China
- Prior art keywords
- target enterprise
- peak
- power consumption
- electricity
- power
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for AC mains or AC distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Power Engineering (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Description
Technical Field
The invention relates to the technical field of power grids, in particular to a method and a system for storing and using energy.
Background
In 29 months 7 in 2021, the national reform and commission released "the notification of the national reform and development commission on further improving the time-of-use electricity price mechanism", starting in 9 months, the electricity was limited by switching off across the country, a large number of manufacturing and processing enterprises were too diligent, many enterprises even started diesel generators, and the production was maintained without cost, and the support was too bitter. The full utilization of energy storage technology, especially electricity storage technology, is the key direction of the enterprise transformation hoped by the new government of the current country.
In the traditional pure electricity storage scheme, cost is reduced by peak clipping and valley filling, namely, the electricity is fully stored in the valley time, so that the stored electric energy can be used in the peak time, and the electricity price is calculated according to the valley time in the peak time. However, the daily electricity prices include flat-section electricity prices in addition to the valley time and the peak time. The traditional method only utilizes the peak-to-valley electricity price difference with the largest difference and does not utilize the flat-section electricity price. Ideally, the optimal scheme is that the electricity is fully charged at the valley time and is used up at the peak time, but in actual situations, the electricity utilization of enterprises can be in off seasons. The reasonable arrangement of the storage device is not based on the minimum power consumption of individual dates, but is considered by integrating the whole production time, so that the reasonable configuration of the storage device is inevitably lower than the demand of off seasons and higher than the demand of off seasons. In a slack season, the charging can be guaranteed to be used up every day, but in the slack season, the cost of the power accumulator which is shared every day is not changed, and the cost reduction efficiency is greatly reduced.
How to better distribute the electric energy charge-discharge time can not only promote the utilization ratio of the accumulator and further reduce the cost, but also can make the battery purchasing scheme more flexible.
Disclosure of Invention
Therefore, the embodiment of the application provides an energy storage and power utilization method and system, and more comprehensive energy storage and cost reduction than the traditional peak clipping and valley filling are realized by reasonably distributing the power utilization time.
In order to achieve the above object, the embodiments of the present application provide the following technical solutions:
according to a first aspect of embodiments of the present application, there is provided a method for storing and using electricity, the method including:
determining a peak off-season estimated peak power utilization ratio of the target enterprise, a peak daily average power consumption of the target enterprise and a target enterprise power storage amount according to historical power utilization data of the target enterprise;
determining the power consumption of the target enterprise when the off-season peak is reserved according to the peak power consumption ratio of the target enterprise when the off-season peak is estimated and the daily average peak power consumption of the target enterprise;
determining the current average power consumption of the target enterprise according to the reserved off-peak power consumption of the target enterprise and the power storage quantity of the target enterprise;
and carrying out power utilization in the current period of time based on the current period of power consumption of the target enterprise.
Optionally, determining the power consumption of the target enterprise when the off-season peak is reserved according to the power consumption ratio of the target enterprise when the peak is estimated in off-season and the power consumption of the target enterprise when the peak is averaged daily, and the determining includes:
and multiplying the power consumption ratio of the target enterprise peak-off estimation time with the target enterprise peak-per-day average power consumption to obtain the target enterprise peak-off reserved power consumption.
Optionally, the power consumption ratio of the target enterprise during off-season peak forecasting is determined according to the power consumption ratio of the target enterprise during off-season peak forecasting.
Optionally, the electricity utilization ratio during the industry-wide peak estimation is determined according to the following formula:
wherein m is the enterprise number of the historical data counted in the whole industry, r (i, t) is the electricity consumption change of each time period t by taking the annual average electricity consumption data of the enterprise i as a reference, and Q (i, t) represents the electricity consumption counted by the enterprise i under the condition of t.
Optionally, the determining the current average segment power consumption of the target enterprise according to the reserved off-season peak power consumption of the target enterprise and the power storage amount of the target enterprise includes:
and subtracting the electricity storage quantity of the target enterprise from the electricity consumption quantity of the target enterprise reserved in the off-season peak to obtain the current-level electricity consumption quantity of the target enterprise.
Optionally, the daily average peak time electricity consumption of the target enterprise is determined as follows:
determining the average value of the daily average peak time electricity consumption in the set date as the daily average peak time electricity consumption of the target enterprise; or alternatively
Determining the maximum peak power consumption in the set date as the average peak power consumption of the target enterprise; or
Determining the power consumption with the probability distribution of peak-time power consumption in the set date in the set confidence interval as the average daily peak-time power consumption of the target enterprise; or
Determining the daily average peak time power consumption of the target enterprise according to the estimated value of a linear fit line of the power consumption in the set date; or alternatively
And predicting the daily average peak time power consumption of the target enterprise by utilizing an algorithm model based on historical data.
Optionally, the historical electricity consumption data of the target enterprise is counted according to the following mode:
if the historical electricity utilization data of the target enterprise has hour-level historical electricity utilization data, directly adopting the hour-level historical electricity utilization data; and if the historical electricity consumption data of the target enterprise only comprises daily data and cannot distinguish peak time and average sections, determining the historical electricity consumption data of the target enterprise according to the peak time electricity consumption or the total electricity consumption of the industry statistical average ratio.
According to a second aspect of embodiments of the present application, there is provided an energy storage and utilization system, the system including:
the data statistics module is used for determining the off-season estimated peak power utilization ratio of the target enterprise, the daily average peak power consumption of the target enterprise and the target enterprise power storage amount according to the historical power utilization data of the target enterprise;
the power consumption module for reserving off-season peak time is used for determining the power consumption of the target enterprise for reserving off-season peak time according to the peak time power consumption ratio of the target enterprise for off-season prediction and the target enterprise daily average peak time power consumption;
the power consumption module is used for determining the current average power consumption of the target enterprise according to the reserved off-peak power consumption of the target enterprise and the power storage quantity of the target enterprise;
and the power utilization module is used for carrying out power utilization in the current level period based on the current level power consumption of the target enterprise.
According to a third aspect of embodiments of the present application, there is provided an electronic apparatus, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the computer program to implement the method of the first aspect.
According to a fourth aspect of embodiments herein, there is provided a computer readable storage medium having stored thereon computer readable instructions executable by a processor to implement the method of the first aspect described above.
In summary, the embodiment of the application provides an energy storage and power utilization method and system, wherein a peak electricity utilization ratio, a peak daily average power consumption and a target enterprise electricity storage quantity of a target enterprise are determined in slack season according to historical electricity utilization data of the target enterprise; determining the power consumption of the target enterprise when the off-season peak is reserved according to the peak power consumption ratio of the target enterprise when the off-season peak is estimated and the daily average peak power consumption of the target enterprise; determining the current average power consumption of the target enterprise according to the power consumption of the target enterprise when the target enterprise reserves off-season peak and the power storage amount of the target enterprise; and carrying out power utilization in the current period of time based on the current period of power consumption of the target enterprise. Through rational distribution of power utilization time, more comprehensive energy storage and cost reduction than the traditional peak clipping and valley filling are realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
The structures, ratios, sizes, and the like shown in the present specification are only used for matching with the contents disclosed in the specification, so that those skilled in the art can understand and read the present invention, and do not limit the conditions for implementing the present invention, so that the present invention has no technical significance, and any structural modifications, changes in the ratio relationship, or adjustments of the sizes, without affecting the functions and purposes of the present invention, should still fall within the scope of the present invention.
Fig. 1 is a schematic flow chart of a method for storing energy and using electricity according to an embodiment of the present disclosure;
fig. 2 is a block diagram of an energy storage and power utilization system according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;
fig. 4 shows a schematic diagram of a computer-readable storage medium provided by an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish one element from another.
The common grade 3 electricity price distribution can be divided into the following 3 cases:
case 1: only a single peak time electricity price period; since low-cost charging cannot be performed until the power is used up from the peak, there is no room for further cost reduction. Are not within the scope of the discussion of the embodiments of the present application.
Case 2: there are multiple peak hour electricity price time slots, but there is valley hour electricity price time slot in the middle of two peaks; for example, the time-of-use electricity price of large industry is more than 220 kilovolts in Zhejiang from 10 and 15 months in 2021; and assuming that the charging speed is enough, the accumulator is charged by default when the valley is met, and the accumulator is used for storing electricity when the peak is met, so that the optimal charging and discharging scheme is realized. The multimodal scene at this time is equivalent to the splicing of single-modal scenes, and as incase 1, the space is not further reduced, and is not discussed in the scope of the embodiments of the present application.
Case 3: there are multiple peak-time electricity price time periods, and there is no valley-time electricity price time period between peaks, but there is a flat-time electricity price time. For example, in 3 months in 2022, the time-of-use electricity price of large industry over 220 kv in Jiangsu province is taken as an example: the valley time electricity price is 0.2453 yuan/degree, the flat section electricity price is 0.5862 yuan/degree, and the peak time electricity price is 1.0080 yuan/degree; this situation is within the scope of the discussion of the embodiments of the present application.
In the daily charging, when there is a valley in the middle of the day, if the accumulator is refilled in consideration of the valley, the two peak times can be considered according to two independent power cycles, which is not discussed in the embodiment of the present application. In order to facilitate understanding of the functions provided by the embodiment of the application, daytime power supply situations are not considered.
The method provided by the embodiment of the application focuses on how to change the charging and discharging decision of the power storage device after the power storage device is deployed, so that the further cost reduction is realized, therefore, the calculation process focuses on the additional cost reduction effect, and the deployment cost of the power storage device is not considered any more.
The embodiment of the application considers the conditions that the last valley is finished and the next valley is finished, and the electric accumulator is in a full state at the beginning when the peak exists.
Fig. 1 illustrates an energy storage and power utilization method provided in an embodiment of the present application, where the method includes:
step 101: determining a peak off-season estimated peak power utilization ratio of the target enterprise, a peak daily average power consumption of the target enterprise and a target enterprise power storage amount according to historical power utilization data of the target enterprise;
step 102: determining the electricity consumption of the target enterprise when the off-season peak is reserved according to the electricity consumption ratio of the target enterprise when the off-season peak is estimated and the electricity consumption of the target enterprise when the daily average peak is reached;
step 103: determining the current average power consumption of the target enterprise according to the reserved off-peak power consumption of the target enterprise and the power storage quantity of the target enterprise;
step 104: and carrying out power utilization in the current period of time based on the current period of power consumption of the target enterprise.
In a possible implementation manner, in step 102, determining the power consumption of the target enterprise when the off-season peak is reserved according to the power consumption ratio of the target enterprise when the peak is estimated in off-season and the power consumption of the target enterprise when the peak is averaged daily, includes:
and multiplying the power consumption ratio of the target enterprise peak-off estimation time with the target enterprise peak-per-day average power consumption to obtain the target enterprise peak-off reserved power consumption.
In one possible implementation mode, the off-season estimated peak-time electricity utilization ratio of the target enterprise is determined according to the industry-wide estimated peak-time electricity utilization ratio.
In one possible embodiment, the industry-wide estimated peak power utilization ratio is determined according to the following formula:
wherein m is the enterprise number of the historical data counted in the whole industry, r (i, t) is the electricity consumption change of each time period t by taking the annual average electricity consumption data of the enterprise i as a reference, and Q (i, t) represents the electricity consumption counted by the enterprise i under the condition of t.
In a possible implementation manner, in step 103, the determining the current average electricity consumption of the target enterprise according to the reserved off-season peak-time electricity consumption of the target enterprise and the electricity storage amount of the target enterprise includes:
and subtracting the electricity storage quantity of the target enterprise from the electricity consumption quantity of the target enterprise reserved in the off-season peak to obtain the current-level electricity consumption quantity of the target enterprise.
In one possible implementation, the target business day-average peak-time electricity consumption is determined as follows:
determining the average value of the daily average peak time electricity consumption in the set date as the daily average peak time electricity consumption of the target enterprise; or determining the maximum peak-time electricity consumption in the set date as the average peak-time electricity consumption of the target enterprise; or determining the power consumption with the peak time power consumption probability distributed in the set confidence interval as the average daily peak time power consumption of the target enterprise; or determining the daily average peak power consumption of the target enterprise according to the estimated value of the linear fit line of the power consumption in the set date; or predicting the daily average peak time power consumption of the target enterprise by utilizing an algorithm model based on historical data.
In one possible implementation mode, the historical electricity consumption data of the target enterprise is counted according to the following mode:
if the historical electricity utilization data of the target enterprise has hour-level historical electricity utilization data, directly adopting the hour-level historical electricity utilization data; and if the historical electricity consumption data of the target enterprise only comprises daily data and cannot distinguish peak time and average sections, determining the historical electricity consumption data of the target enterprise according to the peak time electricity consumption or the total electricity consumption of the industry statistical average ratio.
The embodiment of the application considers the conditions that the last valley is finished and the next valley is finished, and the electric accumulator is in a full state at the beginning when the peak exists.
The following describes the energy storage and power utilization method provided in the embodiments of the present application in further detail. The scheme of the embodiment of the application mainly discusses the 2-peak condition with the most daily condition, and the 2-peak condition can be discussed sequentially according to two adjacent peaks, and so on.
The background situation of the embodiment of the present application in practical application is described, specifically as follows: 1. the electricity price is approximately 0.3 yuan/degree at the valley time, 0.8 yuan/degree at the flat section and 1.1 yuan/degree at the peak time. 2. The charge-discharge efficiency is approximately 100%. 3. The battery drain rate is approximately 0%, i.e., the day's use of the unused electricity can continue the next day without increasing costs, so a full charge is taken as an initial state every day, and the case where an under-charge is started is not discussed. 4. Suppose that a business A uses 200 degrees of electricity per hour during flat time and 400 degrees of electricity per hour during peak time in off season. 5. Suppose that the enterprise uses electricity Q (A, average peak time of the whole year) =1400 (degree) in the whole year day and the off season is more than 1400 degree) in the whole year day, and the electrical storage device and the reserve E are deployed according to the electricity Q, the reserve EA =1400 (degree) (note: E)A = Q (a, when peak is averaged throughout the year), and therefore cannot be used in the formula).
Therefore, in combination with the above background, the initial electricity cost when the peak clipping and the valley filling are performed without using the battery is as follows:
Coriginal cost ＝CFlat segment +CPeak =0.8 × 200 × (3+7) +1.1 × 400 × 2=2480 (yuan)
The traditional peak clipping and valley filling method is based on peak clipping and valley filling, and the unit cost reduction result on the same day is calculated as follows:
Ctradition of ＝CFlat section +CPeak clipping and valley filling at peak time
=0.8 × 200 × (3+7) +0.3 × 400 × 2=1840 (yuan);
cost reduction rate: dTradition of the invention ＝(2480-1840)/2480＝25.8％。
It can be seen that the electricity is used up all the time in the peak period and cannot be used up because the electricity storage requirement is larger than the electricity consumption in the peak period in the off season.
Firstly, the following parameters are defined in the embodiment of the application:
q (i, t) represents the statistical power usage of the enterprise i under the condition of t.
Or alternatively
m represents the number of enterprises in the industry counted by sampling; the mean represents the general rise and fall law throughout the industry. m represents the statistical business range and t represents the statistical time range. And assume that at the first peak, power Q has been used (business, peak 1), and 0<Q (a business, 1 peak time)<E (a business).
Ei represents the storage capacity that business i has purchased.
Q (1 valley power consumption today for a company) = min (Q (1 peak today for a company), E (a company)).
The energy storage and power utilization method provided by the embodiment of the application comprises two methods, specifically as follows:
the first energy storage and power utilization method provided by the embodiment of the application is as follows:
1. based on industry statistical information, counting the power utilization ratio R (industry wide, off-season peak time) = x% in the process of estimating the peak in the industry, wherein x% is more than 100%; considering the difference of enterprise individuals, in order to avoid waste and extra cost caused by excessive power supply, the estimated peak power utilization ratio R (target enterprise, off-season peak time) of the target enterprise is set to be between 100% and R (whole industry, off-season peak time), for example, R (target enterprise, off-season peak time) = (x% + 100%)/2. Counting the electricity consumption Q of the target enterprise when the annual daily peak is averaged (the target enterprise when the annual daily peak is averaged); counting the electric storage quantity E (target enterprise) of the target enterprise;
2. calculating the electricity consumption when the target enterprise needs to reserve the off-season peak:
q (target enterprise, peak off season) = R (target enterprise, peak off season) × Q (target enterprise, peak average time all year around);
3. calculating the available electric quantity Q (target enterprise, flat electricity utilization) = E (target enterprise) -Q (target enterprise, off-season peak time);
4. and the cost can be reduced by finding any flat time (in the case of 3, any flat time between two peaks) in advance for power utilization.
Using the above method, in practical applications, taking enterprise a in the foregoing as an example, it is assumed that R (trade-wide, off-season) =3/7=42.8%; the reserved peak power consumption ratio of the enterprise a is R (enterprise a, off-peak time) = (R (trade-wide, off-peak time) + 100%)/2=5/7 =71.43%, the corresponding reserved power consumption is 1000 degrees, and the peak power consumption can be guaranteed when the reserved power consumption exceeds the actual peak power consumption by 800 degrees. Therefore, the flat segment available power 1400-R (enterprise a, off-peak) × 1400= (1-5/7) × 1400=400 degrees. Finally, an optional flat time uses 400 degrees of electricity.
The scheme of the embodiment of the application is applied to how to change the charging and discharging decision of the accumulator after the accumulator is deployed so as to further reduce the cost. Therefore, in the calculation process, an additional cost reduction effect is focused, and the deployment cost of the power accumulator is not considered any more.
The cost after the first method of the embodiment of the application is utilized is as follows:
Cscheme one ＝CRemaining flat section +CFlat section peak clipping and valley filling +CPeak clipping and filling in peak time
=0.8 x (200 x (3+7) -400) +0.3 x 400+0.3 x 800=1640 (yuan);
cost reduction rate DScheme one ＝(2480-1640)/2480＝33.87％>DTradition of the invention
Therefore, under the condition that the peak clipping and valley filling electric quantity is enough during peak clipping, the residual electric storage device stores the electric quantity, and the cost is reduced as long as the residual electric storage device is used in a flat section.
In a possible implementation manner, the embodiment of the present application further provides a second method for energy storage and power utilization, which specifically includes:
1. obtaining the daily peak time electricity consumption of the target enterprise history, wherein the obtaining method comprises the following steps of:
a) If historical electricity consumption data accurate to hours or even minutes exist, the electricity consumption at peak time can be directly counted.
b) If only the daily data cannot distinguish the peak time flat section, the daily historical data is approximately converted into the peak time historical data according to the industry statistical average ratio 'peak time electricity consumption/total electricity consumption'.
2. And selecting a certain statistical predicted value as an estimated value Q (target enterprise, the peak time of the day) of reserved peak time electricity consumption based on the recent historical peak time electricity consumption. Specific prediction methods include, but are not limited to:
a) Taking the average peak electricity consumption in the last few days as the peak electricity consumption in the present day;
b) Taking the maximum peak electricity consumption in the last few days as the peak electricity consumption in the present day;
c) Taking the position of a 95% confidence interval of the probability distribution of the electricity consumption at the peak of the recent days as the electricity consumption at the peak of the present day;
d) Drawing a linear fit line of the electricity consumption in recent days, and taking the estimated value of the current day as the electricity consumption of the current day;
e) And predicting the current peak electricity consumption by using an algorithm model based on historical data.
3. Then E (target enterprise) -Q (target enterprise, this day) is the electric quantity that the enterprise can use in advance in flat time, and it can realize cost reduction by finding any flat time to use.
Applying the second method to the actual calculation, taking enterprise A as an example, assuming that the power consumption obtained when enterprise A passes the peak of 3 working days is 790 degrees, 820 degrees and 790 degrees in sequence; taking the average value of 800 degrees as the peak power consumption prediction of the current day; the energy storage capacity which can be used in advance in a flat time is estimated to be 1400-800=600 ℃; in any flat time, 600 degrees of electricity is used.
After implementation of scheme two, the cost is calculated as follows: cScheme two ＝COther flat sections +CPeak clipping and valley filling in the last period +CPeak clipping and leveling off at peak time +CFinal flat section residue =0.8 x (200 x (3+7) -600) +0.3 x 600+0+0.3 x 800=1540 (yuan);
cost reduction rate DScheme two ＝(2480-1540)/2480＝37.9％>DScheme one 。
The cost is reduced completely during peak time, and simultaneously, the residual electric energy is used for reducing the cost in a flat section, so that the current calculation result represents the maximum cost reduction rate which can be realized by using the power consumption in the flat section under the ideal condition.
In one possible implementation, the peak hour power consumption of the target enterprise historical per day is obtained by methods including, but not limited to: if historical electricity consumption data accurate to hours or even minutes exist, the electricity consumption at peak time can be directly counted. If only the daily data cannot distinguish the peak time flat section, the daily historical data is approximately converted into the peak time historical data according to the industry statistical average ratio 'peak time electricity consumption/total electricity consumption'.
In one possible implementation, based on recent historical peak time power usage, a statistical prediction is selected as an estimate Q of reserved peak time power usage (target enterprise, peak time today). Specific prediction methods include, but are not limited to:
a) Taking the average peak electricity consumption in the last few days as the peak electricity consumption in the present day;
b) Taking the maximum peak electricity consumption in the last few days as the peak electricity consumption in the present day;
c) Taking the position of a 95% confidence interval of the probability distribution of the electricity consumption at the peak of the recent days as the electricity consumption at the peak of the present day;
d) Drawing a linear fit line of the electricity consumption in the recent days, and taking the estimated value of the current day as the electricity consumption at the peak of the day;
e) And predicting the current peak electricity consumption by using an algorithm model based on historical data.
The embodiment of the application also provides an energy storage and power utilization method, which comprises the following steps:
step 1: determining a peak off-season estimated peak power utilization ratio of the target enterprise, a peak daily average power consumption of the target enterprise and a target enterprise power storage amount according to historical power utilization data of the target enterprise;
step 2: multiplying the power consumption ratio of the target enterprise peak-off estimation time with the target enterprise peak-per-day average power consumption to obtain the target enterprise peak-off reserved power consumption;
and 3, step 3: subtracting the electricity storage quantity of the target enterprise from the electricity consumption quantity of the target enterprise reserved in the off-peak season to obtain the current average electricity consumption quantity of the target enterprise;
and 4, step 4: and carrying out power utilization in the current ordinary period time period based on the current ordinary period power consumption of the target enterprise.
In a possible implementation mode, the off-season estimated peak power utilization ratio of the target enterprise is determined according to the industry-wide estimated peak power utilization ratio.
In one possible embodiment, the industry-wide estimated peak power utilization ratio is determined according to the following formula:
wherein m is the enterprise number of the historical data counted in the whole industry, r (i, t) is the electricity consumption change of each time period t by taking the annual average electricity consumption data of the enterprise i as a reference, and Q (i, t) represents the electricity consumption counted by the enterprise i under the condition of t.
In one possible implementation, the target business day-average peak-time electricity consumption is determined as follows:
determining the average value of the daily average peak time electricity consumption in the set date as the daily average peak time electricity consumption of the target enterprise; or
Determining the maximum peak power consumption in the set date as the average peak power consumption of the target enterprise; or
Determining the power consumption with the peak time power consumption probability distributed in the set confidence interval as the average daily peak time power consumption of the target enterprise; or
Determining the daily average peak power consumption of the target enterprise according to the estimated value of a linear fit line of the power consumption in the set date; or
And predicting the daily average peak time power consumption of the target enterprise by utilizing an algorithm model based on historical data.
In one possible implementation mode, the historical electricity consumption data of the target enterprise is counted according to the following mode:
if the historical electricity utilization data of the target enterprise has hour-level historical electricity utilization data, directly adopting the hour-level historical electricity utilization data; and if the historical electricity consumption data of the target enterprise only comprises daily data and cannot distinguish peak time and average sections, determining the historical electricity consumption data of the target enterprise according to the peak time electricity consumption or the total electricity consumption of the industry statistical average ratio.
In summary, the embodiment of the application provides an energy storage and power utilization method, which includes determining a peak electricity utilization ratio of a target enterprise in off season, a peak daily average electricity consumption of the target enterprise and a target enterprise electricity storage amount according to historical electricity utilization data of the target enterprise; determining the power consumption of the target enterprise when the off-season peak is reserved according to the peak power consumption ratio of the target enterprise when the off-season peak is estimated and the daily average peak power consumption of the target enterprise; determining the current average power consumption of the target enterprise according to the reserved off-peak power consumption of the target enterprise and the power storage quantity of the target enterprise; and carrying out power utilization in the current period of time based on the current period of power consumption of the target enterprise. Through rational distribution of power utilization time, more comprehensive energy storage and cost reduction than the traditional peak clipping and valley filling are realized.
Based on the same technical concept, the embodiment of the present application further provides an energy storage and power utilization system, as shown in fig. 2, the system includes:
thedata statistics module 201 is used for determining a peak-time electricity utilization ratio of the target enterprise in off-season forecast, a peak-time electricity consumption of the target enterprise per day and a target enterprise electricity storage amount according to the historical electricity utilization data of the target enterprise;
thepower consumption module 202 for reserving peak time in off-season is used for determining the power consumption of the target enterprise when peak time in off-season is reserved according to the power consumption ratio of the target enterprise when peak time is estimated in off-season and the power consumption of the target enterprise when peak time is averaged in day;
thepower consumption module 203 is used for determining the current average power consumption of the target enterprise according to the power consumption of the target enterprise reserved in off-season peak and the power storage amount of the target enterprise;
and the power utilization module 204 is used for utilizing power in the current period of time based on the current period power utilization amount of the target enterprise.
In a possible implementation, the reserve off-peakelectricity consumption module 202 is specifically configured to:
and multiplying the power consumption ratio of the target enterprise peak-off estimation time with the target enterprise peak-per-day average power consumption to obtain the target enterprise peak-off reserved power consumption.
In one possible implementation mode, the off-season estimated peak-time electricity utilization ratio of the target enterprise is determined according to the industry-wide estimated peak-time electricity utilization ratio.
In one possible embodiment, the industry-wide estimated peak power utilization ratio is determined according to the following formula:
wherein m is the enterprise number of the historical data counted in the whole industry, r (i, t) is the electricity consumption change of each time period t by taking the annual average electricity consumption data of the enterprise i as a reference, and Q (i, t) represents the electricity consumption counted by the enterprise i under the condition of t.
In a possible implementation manner, thepower consumption module 203 is specifically configured to:
and subtracting the electricity storage quantity of the target enterprise from the electricity consumption quantity of the target enterprise reserved in the off-season peak to obtain the current-level electricity consumption quantity of the target enterprise.
In one possible implementation, the target business day-average peak-time electricity consumption is determined as follows:
determining the average value of the daily average peak time electricity consumption in the set date as the daily average peak time electricity consumption of the target enterprise; or alternatively
Determining the maximum peak power consumption in the set date as the average peak power consumption of the target enterprise; or
Determining the power consumption with the probability distribution of peak-time power consumption in the set date in the set confidence interval as the average daily peak-time power consumption of the target enterprise; or alternatively
Determining the daily average peak power consumption of the target enterprise according to the estimated value of a linear fit line of the power consumption in the set date; or alternatively
And predicting the daily average peak time power consumption of the target enterprise by utilizing an algorithm model based on historical data.
In one possible implementation mode, the historical electricity consumption data of the target enterprise is counted according to the following mode:
if the historical electricity utilization data of the target enterprise has hour-level historical electricity utilization data, directly adopting the hour-level historical electricity utilization data; and if the historical electricity consumption data of the target enterprise only comprises daily data and cannot distinguish peak time and average sections, determining the historical electricity consumption data of the target enterprise according to the peak time electricity consumption or the total electricity consumption of the industry statistical average ratio.
The embodiment of the application also provides electronic equipment corresponding to the method provided by the embodiment. Please refer to fig. 3, which illustrates a schematic diagram of an electronic device according to some embodiments of the present application. Theelectronic device 20 may include: the system comprises aprocessor 200, amemory 201, abus 202 and acommunication interface 203, wherein theprocessor 200, thecommunication interface 203 and thememory 201 are connected through thebus 202; thememory 201 stores a computer program that can be executed on theprocessor 200, and theprocessor 200 executes the computer program to perform the method provided by any one of the foregoing embodiments.
TheMemory 201 may include a high-speed Random Access Memory (RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one physical port 203 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
Theprocessor 200 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in theprocessor 200. TheProcessor 200 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in thememory 201, and theprocessor 200 reads the information in thememory 201 and completes the steps of the method in combination with the hardware thereof.
The electronic equipment provided by the embodiment of the application and the method provided by the embodiment of the application are based on the same inventive concept, and have the same beneficial effects as the method adopted, operated or realized by the electronic equipment.
Referring to fig. 4, the computer readable storage medium is anoptical disc 30, on which a computer program (i.e., a program product) is stored, and when the computer program is executed by a processor, the computer program performs the method provided in any of the foregoing embodiments.
It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memories (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory, or other optical and magnetic storage media, which are not described in detail herein.
The computer-readable storage medium provided by the above-mentioned embodiments of the present application and the method provided by the embodiments of the present application have the same advantages as the method adopted, executed or implemented by the application program stored in the computer-readable storage medium.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose devices may be used with the teachings herein. The required structure for constructing such a device will be apparent from the description above. In addition, this application is not directed to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present application as described herein, and any descriptions of specific languages are provided above to disclose the best modes of the present application.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the application may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the application and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this invention pertains. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.
Those skilled in the art will appreciate that the modules in the devices in an embodiment may be adaptively changed and arranged in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the application and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in the creation apparatus of a virtual machine according to embodiments of the present application. The present application may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present application may be stored on a computer readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the computer program is executed. The storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random Access Memory (RAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of storing energy and using electricity, the method comprising:
determining a peak off-season estimated peak power utilization ratio of the target enterprise, a peak daily average power consumption of the target enterprise and a target enterprise power storage amount according to historical power utilization data of the target enterprise;
determining the power consumption of the target enterprise when the off-season peak is reserved according to the peak power consumption ratio of the target enterprise when the off-season peak is estimated and the daily average peak power consumption of the target enterprise;
determining the current average power consumption of the target enterprise according to the reserved off-peak power consumption of the target enterprise and the power storage quantity of the target enterprise;
and carrying out power utilization in the current period of time based on the current period of power consumption of the target enterprise.
2. The method as claimed in claim 1, wherein the step of determining the power consumption of the target enterprise when the off-season peak is reserved according to the power consumption ratio of the target enterprise when the off-season peak is estimated and the power consumption of the target enterprise when the daily average peak is estimated comprises the following steps:
and multiplying the power consumption ratio of the target enterprise peak-off estimation time with the target enterprise peak-per-day average power consumption to obtain the target enterprise peak-off reserved power consumption.
3. The method of claim 1, wherein the off-season peak forecast power usage value for the target enterprise is determined based on an industry-wide peak forecast power usage value.
4. The method of claim 3, wherein the industry wide estimated peak time power usage ratio is determined according to the following equation:
wherein m is the enterprise number of the historical data counted in the whole industry, r (i, t) is the electricity consumption change of each time period t by taking the annual average electricity consumption data of the enterprise i as a reference, and Q (i, t) represents the electricity consumption counted by the enterprise i under the condition of t.
5. The method of claim 1, wherein determining the current average power consumption of the target enterprise based on the off-season power consumption reserved by the target enterprise and the power storage capacity of the target enterprise comprises:
and subtracting the electricity storage quantity of the target enterprise from the electricity consumption quantity of the target enterprise reserved in the off-peak season to obtain the current average electricity consumption quantity of the target enterprise.
6. The method of claim 1, wherein the target business peak-per-day electricity usage is determined as follows:
determining the average value of the daily average peak time power consumption in the set date as the daily average peak time power consumption of the target enterprise; or
Determining the maximum peak power consumption in the set date as the average peak power consumption of the target enterprise; or
Determining the power consumption with the peak time power consumption probability distributed in the set confidence interval as the average daily peak time power consumption of the target enterprise; or
Determining the daily average peak power consumption of the target enterprise according to the estimated value of a linear fit line of the power consumption in the set date; or
And predicting the daily average peak time power consumption of the target enterprise by utilizing an algorithm model based on historical data.
7. The method of claim 1, wherein the historical electricity usage data of the target enterprise is statistically calculated as follows:
if the historical electricity utilization data of the target enterprise has hour-level historical electricity utilization data, directly adopting the hour-level historical electricity utilization data; and if the historical electricity consumption data of the target enterprise only comprises daily data and cannot distinguish peak time and average sections, determining the historical electricity consumption data of the target enterprise according to the peak time electricity consumption or the total electricity consumption of the industry statistical average ratio.
8. An electrical energy storage system, the system comprising:
the data statistics module is used for determining the off-season estimated peak power utilization ratio of the target enterprise, the daily average peak power consumption of the target enterprise and the target enterprise power storage amount according to the historical power utilization data of the target enterprise;
the power consumption module for reserving off-season peak time is used for determining the power consumption of the target enterprise for reserving off-season peak time according to the peak time power consumption ratio of the target enterprise for off-season prediction and the target enterprise daily average peak time power consumption;
the power consumption module is used for determining the current average power consumption of the target enterprise according to the reserved off-peak power consumption of the target enterprise and the power storage quantity of the target enterprise;
and the power utilization module is used for carrying out power utilization in the current level period based on the current level power consumption of the target enterprise.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor executes when executing the computer program to implement the method according to any of claims 1-7.
10. A computer readable storage medium having computer readable instructions stored thereon which are executable by a processor to implement the method of any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211154893.6ACN115409411A (en) | 2022-09-21 | 2022-09-21 | Energy storage and electricity utilization method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211154893.6ACN115409411A (en) | 2022-09-21 | 2022-09-21 | Energy storage and electricity utilization method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115409411Atrue CN115409411A (en) | 2022-11-29 |
Family
ID=84166895
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211154893.6APendingCN115409411A (en) | 2022-09-21 | 2022-09-21 | Energy storage and electricity utilization method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115409411A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116760087A (en)* | 2023-05-25 | 2023-09-15 | 中科聚(北京)能源科技有限公司 | Comprehensive energy management method, system and storage medium based on distributed power supply |
- 2022
- 2022-09-21CNCN202211154893.6Apatent/CN115409411A/enactivePending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116760087A (en)* | 2023-05-25 | 2023-09-15 | 中科聚(北京)能源科技有限公司 | Comprehensive energy management method, system and storage medium based on distributed power supply |
| CN116760087B (en)* | 2023-05-25 | 2024-02-27 | 中科聚(北京)能源科技有限公司 | Comprehensive energy management method, system and storage medium based on distributed power supply |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111126740B (en) | Shared automobile charging scheduling method, electronic equipment and storage medium | |
| CN112434974A (en) | Block chain-based power scheduling method and device, electronic equipment and storage medium | |
| CN107482656B (en) | Power planning method, device and equipment for microgrid and computer readable storage medium | |
| CN111126703A (en) | Method and device for predicting maximum power consumption demand of enterprise | |
| CN108923536A (en) | Schedulable Potentials method, system, computer equipment and storage medium | |
| CN115409411A (en) | Energy storage and electricity utilization method and system | |
| CN117175729A (en) | Method and device for controlling electric quantity of energy storage equipment and computer equipment | |
| CN114239956A (en) | Resource allocation method and device of virtual power plant and terminal | |
| CN115912360A (en) | Power supply control method and device, computer equipment and storage medium | |
| CN117922346A (en) | A new energy vehicle orderly charging method, device and storage medium | |
| CN116565833B (en) | Prediction method, device and storage medium based on typical solar network load supply curve | |
| CN115514020A (en) | Cross-regional power dispatching method, device, computer equipment and storage medium | |
| CN116247644A (en) | Charging and discharging method and device based on energy storage system, storage medium and terminal | |
| CN112510679B (en) | Distributed energy storage optimization scheduling method and device, computer equipment and storage medium | |
| CN110048421B (en) | Energy storage device capacity selection method and device | |
| CN118082595A (en) | Electric automobile charging control method, device, system and storage medium | |
| CN115347653B (en) | Energy storage and electricity supplementing method and system | |
| CN117301934A (en) | Charging pile charging method and device combined with photovoltaic | |
| CN114844059A (en) | Double-layer optimization control method for participating in peak shaving of electric vehicle cluster | |
| CN114331002B (en) | Energy scheduling method, system, computer device and storage medium | |
| CN118849856B (en) | A charging strategy optimization method and device for energy storage charging pile | |
| CN115347653A (en) | Energy storage and electricity supplementing method and system | |
| CN120357460B (en) | Intelligent energy management method and device for multi-port energy routers for oil fields | |
| CN118508526B (en) | Virtual power plant control method, system and equipment based on neural network | |
| CN120588846B (en) | Intelligent charging and discharging control method for coordinated operation of energy storage charging piles and buses |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |