CN117498416B - Method and device for formulating discharge strategy of energy storage battery and electronic equipment - Google Patents
Method and device for formulating discharge strategy of energy storage battery and electronic equipment Download PDFInfo
- Publication number
- CN117498416B CN117498416B CN202410006051.9A CN202410006051A CN117498416B CN 117498416 B CN117498416 B CN 117498416B CN 202410006051 A CN202410006051 A CN 202410006051A CN 117498416 B CN117498416 B CN 117498416B
- Authority
- CN
- China
- Prior art keywords
- electricity consumption
- peak
- electricity
- storage battery
- energy storage
- 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.)
- Active
Links
- 238000004146 energy storage Methods 0.000 title claims abstract description 224
- 238000000034 method Methods 0.000 title claims abstract description 50
- 230000005611 electricity Effects 0.000 claims abstract description 677
- 238000007599 discharging Methods 0.000 claims abstract description 79
- 230000006870 function Effects 0.000 claims description 97
- 238000012937 correction Methods 0.000 claims description 23
- 238000009472 formulation Methods 0.000 claims description 14
- 239000000203 mixture Substances 0.000 claims description 14
- 238000005516 engineering process Methods 0.000 abstract description 7
- 230000008901 benefit Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000010248 power generation Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000002354 daily effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
Classifications
-
- 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
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4207—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells for several batteries or cells simultaneously or sequentially
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/44—Methods for charging or discharging
- H01M10/441—Methods for charging or discharging for several batteries or cells simultaneously or sequentially
-
- 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
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
-
- 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
- H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
- H02J3/0075—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/00032—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries characterised by data exchange
- H02J7/00036—Charger exchanging data with battery
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0047—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries with monitoring or indicating devices or circuits
- H02J7/0048—Detection of remaining charge capacity or state of charge [SOC]
-
- 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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/0068—Battery or charger load switching, e.g. concurrent charging and load supply
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M2220/00—Batteries for particular applications
- H01M2220/10—Batteries in stationary systems, e.g. emergency power source in plant
Abstract
The invention discloses a method and a device for formulating a discharge strategy of an energy storage battery and electronic equipment. Wherein the method comprises the following steps: receiving a discharge strategy making request of the energy storage battery; responding to a discharge strategy making request, and calling a peak electricity consumption period and a flat electricity consumption period which correspond to a target day; determining peak value prediction electricity consumption under a peak value electricity consumption period corresponding to a target day and flat value prediction electricity consumption under a flat value electricity consumption period corresponding to the target day; determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat predicted electricity consumption; and determining a discharging strategy of the energy storage battery in a power utilization period corresponding to the target day according to the stored power quantity of the energy storage battery and the target predicted power consumption quantity. The invention solves the technical problem of unreasonable discharge strategy of the energy storage battery formulated in the related technology.
Description
Technical Field
The invention relates to the technical field of energy storage batteries, in particular to a method and a device for making a discharge strategy of an energy storage battery and electronic equipment.
Background
The related method provided in the related technology has the problem that the formulated discharge strategy of the energy storage battery is unreasonable.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a method and a device for formulating a discharge strategy of an energy storage battery and electronic equipment, which are used for at least solving the technical problem that the discharge strategy of the energy storage battery formulated in the related technology is unreasonable.
According to an aspect of the embodiment of the present invention, there is provided a method for making a discharge strategy of an energy storage battery, including: receiving a discharge strategy formulation request of the energy storage battery, wherein the discharge strategy formulation request carries a target day, and the discharge strategy formulation request of the energy storage battery is used for requesting to determine the discharge strategy of the energy storage battery in a power utilization period corresponding to the target day; responding to a discharge strategy making request, and calling a peak electricity consumption period and a flat electricity consumption period which correspond to a target day; determining peak value prediction electricity consumption under a peak value electricity consumption period corresponding to a target day and flat value prediction electricity consumption under a flat value electricity consumption period corresponding to the target day; determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat predicted electricity consumption; and determining a discharging strategy of the energy storage battery in a power utilization period corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity, wherein the stored electric quantity is the electric quantity stored in the valley power utilization period of the energy storage battery.
Optionally, before determining the peak predicted power consumption under the peak power consumption period corresponding to the target day and the flat predicted power consumption under the flat power consumption period corresponding to the target day, the method further includes: the method comprises the steps of calling a peak electricity function under a peak electricity period corresponding to a target day and a flat value electricity function under a flat value electricity period corresponding to the target day, wherein the peak electricity function is a function which comprises a relation reflecting the corresponding type of day corresponding to the target day and the corresponding peak forecast electricity consumption, and the flat value electricity function is a function which comprises a relation reflecting the corresponding type of day corresponding to the target day and the corresponding flat value forecast electricity consumption; and determining the peak value predicted power consumption according to the peak value power consumption function, and determining the flat value predicted power consumption according to the flat value power consumption function.
Optionally, before the peak electricity function under the peak electricity period corresponding to the target day and the flat value electricity function under the flat value electricity period corresponding to the target day are called, the method further includes: acquiring historical electricity utilization data in a preset period; determining a first historical electricity consumption amount under a preset peak electricity consumption period corresponding to a preset period and a second historical electricity consumption amount under a preset flat electricity consumption period corresponding to the preset period from the historical electricity consumption data; and obtaining a peak value electricity utilization function according to the first historical electricity consumption, and obtaining a flat value electricity utilization function according to the second historical electricity consumption.
Optionally, determining a discharge strategy of the energy storage battery corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity, including at least one of the following:
Under the condition that the target predicted electricity consumption is the sum of the peak predicted electricity consumption and the flat value predicted electricity consumption and the stored electricity consumption of the energy storage battery is larger than the target predicted electricity consumption, determining a discharge strategy to be a strategy comprising a first peak discharge strategy and a first flat value discharge strategy, wherein the first peak discharge strategy is the electricity consumption of the energy storage battery, the peak predicted electricity consumption is discharged in a peak electricity consumption period corresponding to a target day, the first flat value discharge strategy is the electricity consumption of the energy storage battery, the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption, and the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption; under the condition that the target predicted electricity consumption is peak wave electricity consumption and the stored electricity consumption of the energy storage battery is Yu Fengzhi wave electricity consumption, determining a discharge strategy to be a second peak discharge strategy, wherein the second peak discharge strategy is that the energy storage battery discharges the electricity consumption of the stored electricity consumption in a peak electricity consumption period corresponding to a target day, and the peak wave electricity consumption is obtained according to the peak predicted electricity consumption and the fluctuation coefficient; and determining that the discharge strategy is a strategy comprising a third peak discharge strategy and a target discharge strategy under the condition that the target predicted electricity consumption comprises the sum of the peak predicted electricity consumption and the average value predicted electricity consumption and the peak wave electricity consumption and the stored electricity consumption of the energy storage battery is smaller than the sum and larger than the peak wave electricity consumption, wherein the third peak discharge strategy is the energy storage battery, the electricity consumption of the peak predicted electricity consumption is discharged in the peak electricity consumption period corresponding to the target day, the target discharge strategy is the energy storage battery, the electricity consumption of the second difference electricity consumption is discharged in the target electricity consumption period corresponding to the target day, the second difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption, and the target electricity consumption period is the electricity consumption period selected from valley electricity consumption periods corresponding to the average value electricity consumption period corresponding to the target day and the valley electricity consumption period corresponding to the target day.
Optionally, before determining the discharge strategy of the energy storage battery corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity, the method further includes: obtaining a fluctuation coefficient according to the full electricity percentage and the electric quantity fluctuation percentage, wherein the electric quantity fluctuation percentage is the electric quantity percentage caused by electric wave driving of the electric object for sign; and determining the product of the fluctuation coefficient and the peak value predicted power consumption under the peak value power consumption period corresponding to the target day to obtain the peak value predicted power consumption.
Optionally, before determining the discharge strategy as a strategy including the third peak discharge strategy and the target discharge strategy, further includes: predicting whether a period of which the corresponding electricity utilization price is higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day exists in the valley value electricity utilization period corresponding to the target day, and obtaining a prediction result; determining a first sub-period when a period corresponding to the electricity utilization price higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day exists in the valley value electricity utilization period corresponding to the target day as a prediction result, wherein the first sub-period is a period corresponding to the electricity utilization price higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day in the valley value electricity utilization period corresponding to the target day; determining the sub-period prediction electricity consumption corresponding to the first sub-period; under the condition that the predicted power consumption of the subinterval is lower than the second difference power consumption, determining that the difference between the second difference power consumption and the predicted power consumption of the subinterval is the third difference power consumption; selecting a second sub-period of the third difference electricity consumption from the flat value electricity consumption periods corresponding to the target days; and determining the second sub-period and the second sub-period as target power utilization periods.
Optionally, determining a peak electricity consumption period corresponding to the target day of the energy storage battery and a discharging strategy corresponding to a flat electricity consumption period corresponding to the target day according to the stored electricity quantity of the energy storage battery and the target predicted electricity quantity, and further includes: determining a first actual power consumption under a peak power consumption period corresponding to a target day and a second actual power consumption under a flat power consumption period corresponding to the target day; obtaining a peak power correction coefficient according to a first proportion of the first actual power consumption to the peak predicted power consumption, and obtaining a flat power correction coefficient according to a second proportion of the second actual power consumption to the predicted power consumption; and adjusting the peak electricity function according to the peak electricity quantity correction coefficient to obtain an updated peak electricity function, and adjusting the flat electricity function according to the flat electricity quantity correction coefficient to obtain an updated flat electricity function.
According to an aspect of an embodiment of the present invention, a discharge strategy formulation apparatus for an energy storage battery includes: the receiving module is used for receiving a discharge strategy making request of the energy storage battery, wherein the discharge strategy making request carries a target day, and the discharge strategy making request of the energy storage battery is used for requesting to determine the discharge strategy of the energy storage battery in a power utilization period corresponding to the target day; the calling module is used for responding to the discharge strategy making request and calling the peak power utilization period corresponding to the target day and the flat power utilization period; the first determining module is used for determining peak value prediction electricity consumption under the peak value electricity consumption period corresponding to the target day and flat value prediction electricity consumption under the flat value electricity consumption period corresponding to the target day; the second determining module is used for determining target predicted power consumption according to the peak predicted power consumption and the flat predicted power consumption; and the third determining module is used for determining a discharging strategy of the energy storage battery in a power utilization period corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity, wherein the stored electric quantity is the electric quantity stored in the valley power utilization period of the energy storage battery.
According to an aspect of an embodiment of the present invention, there is provided an electronic apparatus including: a processor; a memory for storing processor-executable requests; wherein the processor is configured to execute the request to implement a method of discharging a power storage battery as described in any one of the above.
According to an aspect of an embodiment of the present invention, there is provided a computer-readable storage medium including: the method of discharging the energy storage battery of any one of the above claims is enabled to be performed by the electronic device when the request in the computer readable storage medium is executed by a processor of the electronic device.
In the embodiment of the invention, a discharge strategy making request of the energy storage battery is received, wherein the discharge strategy making request carries a target day, and the discharge strategy making request of the energy storage battery is used for requesting to determine the discharge strategy of the energy storage battery in a power utilization period corresponding to the target day. And in response to a discharge strategy making request, calling a peak electricity consumption period and a flat value electricity consumption period corresponding to a target day, determining peak predicted electricity consumption in the peak electricity consumption period corresponding to the target day and flat value predicted electricity consumption in the flat value electricity consumption period corresponding to the target day, determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat value predicted electricity consumption, and determining a discharge strategy of the energy storage battery in the electricity consumption period corresponding to the target day according to the stored electricity consumption and the target predicted electricity consumption of the energy storage battery, wherein the stored electricity consumption is the electricity consumption of the energy storage battery stored in the valley electricity consumption period. Because the discharging strategy of the energy storage battery in the electricity utilization period corresponding to the target day is determined according to the stored electricity quantity of the energy storage battery and the target predicted electricity consumption, and the target predicted electricity consumption is determined according to the peak predicted electricity consumption and the flat predicted electricity consumption, the electricity utilization requirement information of different electricity utilization periods about the target day can be provided by determining the peak predicted electricity consumption and the flat predicted electricity consumption, the energy storage battery can be helped to formulate the discharging strategy corresponding to the reasonable peak electricity utilization period and the flat electricity utilization period respectively, and the electric energy of the energy storage battery can be released in the required peak period or the stationary period so as to ensure that the maximum benefit can be achieved, and further the technical problem that the discharging strategy of the energy storage battery formulated in the related technology is unreasonable is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
Fig. 1 is a flowchart of a method of discharging strategy formulation of an energy storage battery according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an architecture of an energy storage charge and discharge control method based on load prediction according to an alternative embodiment of the present invention;
Fig. 3 is a block diagram illustrating a structure of a discharge strategy setting device of an energy storage battery according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present invention, there is provided an embodiment of a method of discharging a storage battery, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that herein.
Fig. 1 is a flowchart of a method for setting a discharge strategy of an energy storage battery according to an embodiment of the present invention, as shown in fig. 1, the method includes the steps of:
Step S102, receiving a discharge strategy formulation request of an energy storage battery, wherein the discharge strategy formulation request carries a target day, and the discharge strategy formulation request of the energy storage battery is used for requesting to determine a discharge strategy of the energy storage battery in a power utilization period corresponding to the target day;
In the step S102, a discharge policy making request is received, target day information and an energy storage battery identifier are extracted, and a power consumption period corresponding to the target day is determined according to the target day, where the power consumption period is not limited herein, and may be predefined or dynamically determined according to a user requirement, a power grid load situation or other factors. Further, a discharging strategy of the energy storage battery under the power consumption period corresponding to the target day can be formulated according to the characteristics of the energy storage battery, the energy storage electric quantity and the power consumption period of the target day.
It should be noted that, by receiving a discharge policy specification request of the energy storage battery, a discharge policy of the energy storage battery under the power utilization period corresponding to the target day is further formulated, so that the discharge power and the discharge period can be reasonably distributed according to the power utilization period corresponding to the target day, and the power utilization requirement can be met to the greatest extent.
Step S104, responding to a discharge strategy making request, and calling a peak electricity utilization period and a flat electricity utilization period corresponding to a target day;
in the step S104 provided by the present application, according to the analysis result of the electricity data of the target day, the period in which peak electricity occurs in the target day, for example, the peak electricity period in the daytime, and the determination of the peak electricity period are determined, which is not limited herein, and may be adjusted according to factors such as seasonal variation, electricity consumption mode, and the like.
According to the analysis result of the electricity consumption data of the target day, determining the period belonging to the flat electricity consumption condition in the target day, wherein the flat electricity consumption period generally refers to a period with relatively stable electricity consumption requirement, such as a level stable period in the evening or early morning.
It should be noted that, by calling the peak electricity consumption period and the average electricity consumption period and formulating a corresponding discharging strategy, the load of the power grid can be effectively balanced, and the stability of the power grid can be improved. In the peak electricity utilization period, the discharge of the energy storage battery can reduce the pressure on the power grid and reduce the risk of the power system. During flat power usage periods, the energy storage battery may help the grid balance supply and demand relationships by charging.
Step S106, determining the peak value prediction electricity consumption under the peak value electricity consumption period corresponding to the target day and the flat value prediction electricity consumption under the flat value electricity consumption period corresponding to the target day;
In the step S106 provided by the present application, for the peak electricity consumption period, prediction analysis may be performed based on historical electricity consumption data or other relevant factors, the electricity consumption data in a specific period may be analyzed to obtain the peak electricity consumption predicted in the period, and similarly, under the flat electricity consumption period, prediction analysis may be performed using the historical electricity consumption data or other relevant factors, and the flat electricity consumption predicted in the period may be obtained by performing statistics and analysis on the electricity consumption data in the flat electricity consumption period.
It should be noted that, through determining the peak prediction electricity consumption and the average prediction electricity consumption, the electricity consumption demand information about different electricity consumption periods of the target day can be provided, which is helpful for the energy storage battery to formulate a reasonable discharging strategy corresponding to the peak electricity consumption period and the average electricity consumption period respectively, so that the electric energy of the energy storage battery can be released in the required peak period or stationary period in the electricity consumption peak period, so as to maximally meet the electricity consumption demand, and reduce the electricity consumption cost of the user in the electricity consumption peak period to a certain extent.
Step S108, determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat predicted electricity consumption;
In the step S108, the peak predicted power consumption may represent the power demand predicted in the peak power consumption period of the target day, and the flat predicted power consumption may represent the power demand predicted in the flat power consumption period of the target day, and the target predicted power consumption may be determined according to the peak predicted power consumption and the flat predicted power consumption.
It should be noted that the above-mentioned target predicted electricity consumption may be an estimated value obtained based on the predicted data, and the determined target predicted electricity consumption may provide an estimation of electricity demand in a specific period in the future, which has an important reference value for specifying a discharge strategy of the energy storage battery to some extent.
Step S110, determining a discharging strategy of the energy storage battery in a power utilization period corresponding to a target day according to the stored power quantity of the energy storage battery and the target predicted power consumption quantity, wherein the stored power quantity is the power quantity stored in the energy storage battery in a valley power utilization period.
In the present application provides step S110, first, the stored power of the energy storage battery is compared with the target predicted power consumption. According to the comparison result of the two values, whether the battery has enough electric quantity to meet the target predicted electric quantity can be determined, a discharging strategy of the energy storage battery in the electric utilization period corresponding to the target day is further formulated, in actual operation, the discharging strategy can be adjusted according to the actual electric utilization requirement and the state of the energy storage battery, the discharging strategy is timely modified, the electric utilization requirement can be met, and the stored electric quantity of the energy storage battery is utilized to the maximum extent.
It should be noted that, through the discharging strategy determined in the above steps, on one hand, the stored battery power can be utilized to the maximum in the power consumption period of the target day, which is helpful for providing the required power to satisfy the power consumption requirement to a certain extent, and on the other hand, the reasonable discharging strategy is formulated to provide the power supply in different power consumption periods of the target day. The battery energy is released in the peak power utilization period, so that the power utilization requirement in the high-load period can be met; and the electric quantity is moderately discharged or reserved in other flat electricity consumption periods, so that the balance and adjustment of electricity consumption requirements can be realized, the stable operation of the electric power system can be maintained, and the supply and demand balance can be realized.
Through the steps S102-S110, a discharging policy making request of the energy storage battery is received, where the discharging policy making request carries a target day, and the discharging policy making request of the energy storage battery is used for requesting to determine a discharging policy of the energy storage battery in a power utilization period corresponding to the target day. And in response to a discharge strategy making request, calling a peak electricity consumption period and a flat value electricity consumption period corresponding to a target day, determining peak predicted electricity consumption in the peak electricity consumption period corresponding to the target day and flat value predicted electricity consumption in the flat value electricity consumption period corresponding to the target day, determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat value predicted electricity consumption, and determining a discharge strategy of the energy storage battery in the electricity consumption period corresponding to the target day according to the stored electricity consumption and the target predicted electricity consumption of the energy storage battery, wherein the stored electricity consumption is the electricity consumption of the energy storage battery stored in the valley electricity consumption period. Because the discharging strategy of the energy storage battery in the electricity utilization period corresponding to the target day is determined according to the stored electricity quantity of the energy storage battery and the target predicted electricity consumption, and the target predicted electricity consumption is determined according to the peak predicted electricity consumption and the flat predicted electricity consumption, the electricity utilization requirement information of different electricity utilization periods about the target day can be provided by determining the peak predicted electricity consumption and the flat predicted electricity consumption, the energy storage battery can be helped to formulate the discharging strategy corresponding to the reasonable peak electricity utilization period and the flat electricity utilization period respectively, and the electric energy of the energy storage battery can be released in the required peak period or the stationary period so as to ensure that the maximum benefit can be achieved, and further the technical problem that the discharging strategy of the energy storage battery formulated in the related technology is unreasonable is solved.
As an optional embodiment, before determining the peak predicted power consumption in the peak power consumption period corresponding to the target day and the flat predicted power consumption in the flat power consumption period corresponding to the target day, the method further includes: the method comprises the steps of calling a peak electricity function under a peak electricity period corresponding to a target day and a flat value electricity function under a flat value electricity period corresponding to the target day, wherein the peak electricity function is a function which comprises a relation reflecting the corresponding type of day corresponding to the target day and the corresponding peak forecast electricity consumption, and the flat value electricity function is a function which comprises a relation reflecting the corresponding type of day corresponding to the target day and the corresponding flat value forecast electricity consumption; and determining the peak value predicted power consumption according to the peak value power consumption function, and determining the flat value predicted power consumption according to the flat value power consumption function.
In this embodiment, the peak electricity function is a function describing a relationship between electricity demand and predicted electricity consumption, and according to historical data and analysis, input variables of the function may include time, weather, and the like, and according to a form and parameters of the function, the peak electricity consumption of a target day may be predicted, and then the retrieved peak electricity function may be utilized to input relevant parameters (such as time and weather) corresponding to the target day, and the peak predicted electricity consumption of the target day corresponding to the peak electricity consumption period may be calculated, where the predicted value may represent an estimated value of the peak electricity demand of the target day.
Similarly, a flat electricity function corresponding to the target day is called according to the type of the target day. The flat electricity function is a function describing the relation between electricity demand and predicted electricity consumption, according to historical data and analysis, the input variables of the function can be time, weather, population and the like, the flat electricity consumption of a target day can be predicted according to the form and parameters of the function, then the called flat electricity function can be utilized, relevant parameters (such as time, weather and the like) corresponding to the target day are input, the flat predicted electricity consumption of the flat electricity consumption period corresponding to the target day can be calculated, and the predicted value can embody the estimated value of the flat electricity demand of the target day.
The electricity consumption corresponding to each period can be predicted according to the peak electricity consumption function and the average value electricity consumption function, the electricity consumption demand of the peak value corresponding to the target day and the average value electricity consumption period can be estimated more accurately, the peak electricity consumption function and the average value electricity consumption function are called, the predicted electricity consumption is determined, the accuracy of electricity consumption demand prediction can be improved, the supply and demand balance is optimized, and a more reasonable and efficient discharge strategy is formulated.
As an alternative embodiment, before retrieving the peak electricity function in the peak electricity period corresponding to the target day and the flat value electricity function in the flat value electricity period corresponding to the target day, the method further includes: acquiring historical electricity utilization data in a preset period; determining a first historical electricity consumption amount under a preset peak electricity consumption period corresponding to a preset period and a second historical electricity consumption amount under a preset flat electricity consumption period corresponding to the preset period from the historical electricity consumption data; and obtaining a peak value electricity utilization function according to the first historical electricity consumption, and obtaining a flat value electricity utilization function according to the second historical electricity consumption.
In this embodiment, the power usage profile may be obtained over a period of time by collecting historical power usage data corresponding to a predetermined period, which may include hourly, daily, or monthly power usage records, and other factors that may affect power usage demand, such as time, weather, etc., and then determining a first historical power usage for the period based on the predetermined peak power usage period and the collected historical power usage data, and further using the first historical power usage for the predetermined peak power usage period and other related parameters, a function may be established describing the relationship between peak power usage and predicted power usage. By fitting the historical data, an appropriate functional form can be selected and the peak power usage function determined based on the parameters.
Likewise, a second historical power usage during a predetermined flat power usage period is determined based on the period and the collected historical power usage data. Further, a function describing the relationship between peak power usage and predicted power usage may be established using the first historical power usage and other related parameters for the predetermined peak power usage period. By fitting the historical data, an appropriate functional form can be selected and the peak power usage function determined based on the parameters.
By using the historical electricity consumption data and the related parameters, the peak electricity consumption function and the average value electricity consumption function are established, so that the electricity consumption condition of the peak electricity consumption period and the average value electricity consumption period can be reflected more accurately, the reliability of electricity consumption prediction can be improved, and the two functions can better capture the electricity consumption change trend and characteristics of the peak electricity consumption period and the average value electricity consumption period, so that the electricity consumption of a target day can be predicted more accurately.
As an alternative embodiment, determining a discharge strategy of the energy storage battery corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity includes at least one of the following: under the condition that the target predicted electricity consumption is the sum of the peak predicted electricity consumption and the flat value predicted electricity consumption and the stored electricity consumption of the energy storage battery is larger than the target predicted electricity consumption, determining a discharge strategy to be a strategy comprising a first peak discharge strategy and a first flat value discharge strategy, wherein the first peak discharge strategy is the electricity consumption of the energy storage battery, the peak predicted electricity consumption is discharged in a peak electricity consumption period corresponding to a target day, the first flat value discharge strategy is the electricity consumption of the energy storage battery, the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption, and the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption; under the condition that the target predicted electricity consumption is peak wave electricity consumption and the stored electricity consumption of the energy storage battery is Yu Fengzhi wave electricity consumption, determining a discharge strategy to be a second peak discharge strategy, wherein the second peak discharge strategy is that the energy storage battery discharges the electricity consumption of the stored electricity consumption in a peak electricity consumption period corresponding to a target day, and the peak wave electricity consumption is obtained according to the peak predicted electricity consumption and the fluctuation coefficient; and determining that the discharge strategy is a strategy comprising a third peak discharge strategy and a target discharge strategy under the condition that the target predicted electricity consumption comprises the sum of the peak predicted electricity consumption and the average value predicted electricity consumption and the peak wave electricity consumption and the stored electricity consumption of the energy storage battery is smaller than the sum and larger than the peak wave electricity consumption, wherein the third peak discharge strategy is the energy storage battery, the electricity consumption of the peak predicted electricity consumption is discharged in the peak electricity consumption period corresponding to the target day, the target discharge strategy is the energy storage battery, the electricity consumption of the second difference electricity consumption is discharged in the target electricity consumption period corresponding to the target day, the second difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption, and the target electricity consumption period is the electricity consumption period selected from valley electricity consumption periods corresponding to the average value electricity consumption period corresponding to the target day and the valley electricity consumption period corresponding to the target day.
In this embodiment, a discharge strategy of the energy storage battery corresponding to the target day may be determined, specifically as follows:
1) If the target predicted power consumption is the sum of the peak predicted power consumption and the flat predicted power consumption, and the stored power of the energy storage battery is greater than the target predicted power consumption: the first peak discharging strategy is the electric quantity of the energy storage battery for predicting the electric quantity of the energy storage battery in the peak electricity consumption period corresponding to the target day; the first flat discharging strategy is to discharge the electricity quantity of the first difference electricity consumption in the flat electricity consumption period corresponding to the target day, wherein the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity quantity of the energy storage battery and the peak predictive electricity consumption.
It should be noted that, when the stored electricity quantity of the energy storage battery is greater than the target predicted electricity quantity, a first peak discharge strategy and a first flat discharge strategy are formulated, so that in the peak electricity consumption period, the energy storage battery discharges with the required peak predicted electricity quantity, and in the flat electricity consumption period, the peak predicted electricity quantity is subtracted from the stored electricity quantity, that is, the remaining electricity quantity (same as the first difference electricity quantity) is discharged, so that the first peak discharge strategy and the first flat discharge strategy are formulated, the electricity quantity of the energy storage battery can be maximally utilized, the electricity consumption requirement of the peak period is ensured, the electricity supply condition of the flat period is regulated, and the electricity can be used as low as possible for users in different periods to a certain extent.
2) If the target predicted power consumption is the peak fluctuation power consumption and the stored power of the energy storage battery is less than Yu Fengzhi fluctuation power consumption: the second peak discharging strategy is to discharge the electric quantity of the stored electric quantity of the energy storage battery in the peak electricity consumption period corresponding to the target day, and the peak fluctuation electric quantity is calculated according to the peak prediction electric quantity and the fluctuation coefficient.
It should be noted that, under the condition that the stored electric quantity of the energy storage battery is small Yu Fengzhi wave electricity consumption, the second peak discharge strategy is formulated, so that the electric quantity of the energy storage battery is insufficient to provide the required electric quantity in the peak electricity consumption period, and the stored electric quantity is used for discharging.
3) If the target predicted electricity consumption comprises the sum of the peak predicted electricity consumption and the flat predicted electricity consumption and the peak wave electricity consumption, and the stored electricity consumption of the energy storage battery is smaller than the sum and larger than the peak wave electricity consumption, the third peak discharging strategy is the electricity consumption of the energy storage battery for discharging the peak predicted electricity consumption in the peak electricity consumption period corresponding to the target day; the target discharging strategy is to discharge the energy of the energy storage battery in a target electricity consumption period corresponding to a target day, wherein the second difference electricity consumption is the electricity consumption corresponding to the difference between the stored energy of the energy storage battery and the peak prediction electricity consumption. The target electricity consumption period is selected from the flat value electricity consumption period corresponding to the target day and the valley value electricity consumption period corresponding to the target day.
It should be noted that, under the condition that the sum of the peak predicted electricity consumption and the flat predicted electricity consumption of the stored electricity of the energy storage battery is greater than the peak wave electricity consumption, a third peak discharge strategy is formulated, so that the energy storage battery can discharge with the peak predicted electricity consumption in a peak electricity consumption period, a target discharge strategy is formulated, and the purpose is to discharge with a second difference electricity consumption in a electricity consumption period determined between the flat electricity consumption period and the valley electricity consumption period corresponding to a target day, and the electricity consumption of the energy storage battery can be effectively utilized through the formulated discharge strategy of the sub-period, thereby being beneficial to reducing the dependence of a user on a power grid and ensuring the low-cost electricity consumption of the energy storage battery in the electricity consumption peak period.
It should be further noted that, setting different discharging strategies can schedule the discharging of the energy storage battery at different time periods of the target day so as to meet different electricity requirements, and by distinguishing the peak electricity consumption period, the flat electricity consumption period and the valley electricity consumption period and correspondingly setting the discharging strategies, the supply and demand relationship of the power system can be reasonably balanced, and the situation of energy shortage or low utility electricity is avoided. According to the strategy, the energy storage battery can discharge in different time intervals according to the conditions of the stored electric quantity and the target predicted electric quantity so as to meet the electric power demand, so that the service efficiency of the energy storage battery can be optimized to a certain extent, and the supply and demand balance of an electric power system is improved.
As an optional embodiment, determining the discharge strategy of the energy storage battery corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity further includes: obtaining a fluctuation coefficient according to the full electricity percentage and the electric quantity fluctuation percentage, wherein the electric quantity fluctuation percentage is the electric quantity percentage caused by electric wave driving of the electric object for sign; and determining the product of the fluctuation coefficient and the peak value predicted power consumption in the peak value power consumption period corresponding to the target day to obtain the peak value fluctuation power consumption.
In this embodiment, the electric quantity fluctuation percentage is used to indicate the electric quantity change percentage caused by the electric quantity fluctuation of the electric object, the fluctuation coefficient can be used to represent the influence degree of the electric quantity fluctuation of the electric object on the peak value prediction electric quantity, the electric quantity fluctuation percentage can be determined according to the full electric quantity percentage, the peak value prediction electric quantity under the peak value electricity utilization period corresponding to the target day can be multiplied by the fluctuation coefficient, the peak value prediction electric quantity can be obtained, and the more accurate peak value fluctuation electric quantity can be obtained by considering the influence of the electric quantity fluctuation factor.
It should be noted that, through the above steps, according to the stored electric quantity of the energy storage battery and the target predicted electric quantity, the discharge strategy of the energy storage battery corresponding to the target day can be continuously formulated in combination with the peak predicted electric quantity. The fluctuation of the power consumption object, namely the power fluctuation percentage is determined, so that the power consumption of the peak power consumption period can be predicted more accurately and comprehensively, the discharging strategy of the energy storage battery is adjusted and optimized, the discharging strategy of the energy storage battery can be matched with the actual power consumption requirement better to a certain extent, and the stability of the power requirement is improved.
As an alternative embodiment, before determining the discharge strategy as a strategy including the third peak discharge strategy and the target discharge strategy, the method further includes: predicting whether a period of which the corresponding electricity utilization price is higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day exists in the valley value electricity utilization period corresponding to the target day, and obtaining a prediction result; determining a first sub-period when a period corresponding to the electricity utilization price higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day exists in the valley value electricity utilization period corresponding to the target day as a prediction result, wherein the first sub-period is a period corresponding to the electricity utilization price higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day in the valley value electricity utilization period corresponding to the target day; determining the sub-period prediction electricity consumption corresponding to the first sub-period; under the condition that the predicted power consumption of the subinterval is lower than the second difference power consumption, determining that the difference between the second difference power consumption and the predicted power consumption of the subinterval is the third difference power consumption; selecting a second sub-period of the third difference electricity consumption from the flat value electricity consumption periods corresponding to the target days; and determining the second sub-period and the second sub-period as target power utilization periods.
In this embodiment, for the above steps, the electricity price may be predicted by predicting whether there is a period in which the corresponding electricity price is higher than the electricity price corresponding to the flat value electricity period corresponding to the target day in the valley electricity period corresponding to the target day, and by comparing the electricity prices of the different electricity periods, the prediction result of the electricity price may be obtained in the case of predicting the electricity prices of the different electricity periods of the target day. The first sub-period refers to a period in which the electricity price in the valley electricity period corresponding to the target day is higher than the electricity price corresponding to the flat electricity period corresponding to the target day, and may be determined when the prediction result is that there is a period in which the corresponding electricity price in the valley electricity period corresponding to the target day is higher than the electricity price corresponding to the flat electricity period corresponding to the target day, then the sub-period predicted electricity consumption corresponding to the first sub-period is determined, that is, the value of the predicted electricity consumption in the first sub-period is determined, and when the sub-period predicted electricity consumption is lower than the second difference electricity consumption, a third difference electricity consumption is determined, and the third difference electricity consumption is calculated as the difference between the second difference electricity consumption and the sub-period predicted electricity consumption, and finally, from the flat electricity period corresponding to the target day, the second sub-period for which the use is the third difference electricity consumption is selected as the target electricity consumption period.
It should be noted that, through the above-mentioned step of determining the target electricity consumption period, to a certain extent, it is helpful to fully consider the electricity price, optimize the discharge strategy, accurately predict the electricity consumption, and adjust the discharge amount of the energy storage battery under the adjustment of the discharge strategy, ensure that the energy storage battery discharges in a proper period, so as to meet the requirements of the power grid, and reduce the energy cost in the high-price electricity consumption period.
As an optional embodiment, after determining the discharge strategies corresponding to the peak electricity consumption period corresponding to the target day and the flat electricity consumption period corresponding to the target day according to the stored electricity quantity of the energy storage battery and the target predicted electricity quantity, the method further includes: determining a first actual power consumption under a peak power consumption period corresponding to a target day and a second actual power consumption under a flat power consumption period corresponding to the target day; obtaining a peak power correction coefficient according to a first proportion of the first actual power consumption to the peak predicted power consumption, and obtaining a flat power correction coefficient according to a second proportion of the second actual power consumption to the predicted power consumption; and adjusting the peak electricity function according to the peak electricity quantity correction coefficient to obtain an updated peak electricity function, and adjusting the flat electricity function according to the flat electricity quantity correction coefficient to obtain an updated flat electricity function.
In this embodiment, the first actual power consumption is determined in a peak power consumption period corresponding to the target day, and the second actual power consumption is determined in a flat power consumption period corresponding to the target day, based on the stored power of the energy storage battery and the target predicted power consumption. And then calculating a peak power correction coefficient according to the ratio between the first actual power consumption and the peak predicted power consumption, wherein the coefficient is used for adjusting a peak power consumption function so as to more accurately predict the peak power consumption, and similarly, calculating a flat power correction coefficient according to the ratio between the second actual power consumption and the predicted power consumption, wherein the coefficient is used for adjusting a flat power consumption function so as to more accurately predict the flat power consumption. And finally, adjusting the peak power utilization function according to the peak power correction coefficient to obtain an updated peak power utilization function, and adjusting the flat power utilization function according to the flat power correction coefficient to obtain an updated flat power utilization function.
It should be noted that, through the peak value electric quantity correction coefficient and the flat value electric quantity correction coefficient in the above steps, the peak value and the flat value electric quantity function are corrected according to the proportional relationship between the actual electric consumption condition and the predicted electric consumption, so as to obtain respective fixed update correction coefficients, so as to improve the accuracy of electric consumption prediction, and to a certain extent, the method is helpful for more accurately making a discharge strategy of the energy storage battery, so as to meet the electric consumption requirement and improve the efficiency of energy scheduling.
Based on the foregoing embodiments and optional embodiments, an optional implementation is provided, and is specifically described below.
In the related art, the technical problem that the formulated discharge strategy of the energy storage battery is unreasonable exists.
The background technology for making strategies in the related art is introduced:
The target electricity utilization is implemented by a peak-to-valley electricity price system, which is also called time-of-use electricity price. Peak period: generally refers to the electricity consumption unit is more concentrated, electricity consumption is performed when power supply is stressed, and the valley period is as follows: generally, electricity is used when electricity units are fewer and electricity is supplied sufficiently, for example, at night, electricity prices in peak periods are far higher than those in valley periods, and flat periods: it is also common to focus on daytime, where electricity prices are slightly lower than peak periods, but much higher than valley periods, where the root cause of peak-to-valley electricity prices is due to unequal power generation and power usage. With the rapid development of photovoltaic solar energy, the problem of electric quantity fluctuation during power generation is further aggravated, the peak-to-valley electricity price difference value is gradually increased, the peak-to-valley electricity price difference value of industry and commerce in Shanghai areas exceeds one-element/degree electricity, the energy storage battery has wide application prospect, the energy storage battery can be charged with low-price electricity during the valley value of the electricity and discharged during the peak value of the electricity price, and therefore users are ensured to use the low-price electricity as much as possible, and the electricity consumption cost is greatly reduced.
When the energy storage is configured for the industrial and commercial park, the capacity of the energy storage battery is usually required to be not higher than the chargeable capacity of the park in the electricity price valley period, namely, the energy storage battery is ensured to be full of electricity in the electricity price valley period, and meanwhile, the capacity can meet the electricity consumption requirement of the park in the peak flat period as much as possible, so that the benefit maximization of the energy storage configuration can be realized, but in the practical use process, the situation that the electricity consumption of the park is reduced or increased sharply at a certain moment, such as holiday rest, equipment overhaul, capacity reduction, yield increase and the like, is necessarily present.
Based on the above background, the discharge strategy formulated in the related art does not consider the discharge time of each period, and has unreasonable specified discharge strategy for the situations of inflexible discharge capacity setting and the like.
In view of this, an alternative embodiment of the present application provides a method for setting a discharge strategy of an energy storage battery, and the alternative embodiment of the present application is described in detail below.
S1, a discharge strategy of an energy storage battery is formulated, wherein a discharge strategy formulation request carries a target day, and the discharge strategy formulation request of the energy storage battery is used for requesting to determine the discharge strategy of the energy storage battery in a power utilization period corresponding to the target day;
s2, responding to a discharge strategy making request, and calling a peak electricity consumption period and a flat electricity consumption period corresponding to a target day;
It should be noted that, the electric Energy Management System (EMS) may collect the recent (1-10 days) electricity consumption data of the user in real time through the electric energy meter 2, and obtain the electricity consumption of each period according to the electricity statistics difference of each period of peak, flat and valley; typically, a specific period of time (e.g. 20:00-8:00) at night is a valley value of electricity price, the energy storage battery is charged, the electricity price peak value and the electricity price level value can have a plurality of intervals, the peak-to-average intervals are arranged in a crossing manner, e.g. the peak period (8:00-11:00, 14:00-17:00) is a peak period (11:00-14:00, 17:00-20:00) is a flat period.
S3, acquiring historical electricity utilization data in a preset period, determining a peak electricity utilization function under a peak electricity utilization period corresponding to a target day, and determining a flat value electricity utilization function under a flat value electricity utilization period corresponding to the target day;
It should be noted that, a first historical electricity consumption amount under a predetermined peak electricity consumption period corresponding to a predetermined period and a second historical electricity consumption amount under a predetermined flat electricity consumption period corresponding to the predetermined period are determined from historical electricity consumption data, fig. 2 is a schematic architecture diagram of an energy storage charging and discharging control method based on load prediction according to an alternative embodiment of the present invention, and an upper computer (such as a web page, a mobile phone app, a field operation screen, etc.) of an electric energy management system is used to import peak-average-valley periods and corresponding electricity price tables of a place where an item is located to an EMS, so as to implement a function of inputting external information into an EMS database. As shown in fig. 2: the electric energy management system can collect the recent (1-10 days) electricity consumption data of the user in real time through the electric energy meter 2, store the data into a database, and carry out data fitting by using a function fitting code according to the recent electricity consumption of peak and flat time periods every day, namely, based on the first historical electricity consumption and the second historical electricity consumption, so as to generate an electricity consumption mathematical formula of each time period, and further obtain a peak electricity consumption function and a flat value electricity consumption function.
S4, determining peak value prediction electricity consumption according to a peak value electricity consumption function, and determining flat value prediction electricity consumption according to a flat value electricity consumption function;
It should be noted that, according to the mathematical formula obtained in the previous step, the power consumption of each peak flat period in the next day is calculated, the power consumption Qf1 of the peak period 1, the power consumption Qf2 of the peak period 2, the power consumption Qp1 of the flat period 1, and the power consumption Qp2 of the flat period 2 are calculated, and meanwhile, the total power consumption qf=qf1+qf2 of the peak period is calculated; calculating the total electricity consumption qp=qp 1+qp 2 of the flat period; the total power consumption q=qf+qp of the peak-to-average period is calculated.
And S5, determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat predicted electricity consumption, and determining a discharging strategy of the energy storage battery in an electricity consumption period corresponding to a target day according to the stored electricity consumption of the energy storage battery and the target predicted electricity consumption, wherein the stored electricity consumption is the electricity consumption of the energy storage battery in a valley electricity consumption period.
It should be noted that, the EMS makes a charge and discharge control plan of the energy storage battery according to the stored electric quantity Qcell of the energy storage battery and the calculated power consumption conditions of the peak of the next day and each period. The formulated discharge strategy is as follows:
1) If Qcell < Q, namely the electric quantity of the energy storage battery is lower than Q, the electric quantity of the energy storage battery is indicated to be estimated to be completely consumed, and the next step of judgment is carried out; otherwise, the energy storage battery is discharged in peak and ordinary time periods.
2) If Qcell < Qf (100% - β), it indicates that the electric quantity of the energy storage battery is expected to be completely consumed by peak electricity consumption, and the battery is discharged at peak and is not discharged at flat value, where β is the empirical value manually set according to the field situation and is generally between 0 and 20%, so as to avoid that the electric quantity of the energy storage battery cannot be discharged due to large electric wave motion of a user as much as possible, and to maximize the utilization rate of the energy storage battery, otherwise, qf (100% - β) < Qcell < Q is indicated, and the next step is performed.
3) If there is a peak period from the current time to the valley, discharging the energy storage battery at the peak, and discharging at the flat value with the maximum discharging amount of Qcell-Qf (100% - β) (same as the second difference electricity consumption); otherwise, if the peak period does not exist in the period from the current moment to the valley value and only the flat moment exists, the energy storage battery discharges in the flat value.
It should be further noted that after the above steps are performed, that is, after each period of the peak, the flat and the valley is finished and the next period is entered, determining a first actual power consumption in a peak power consumption period corresponding to the target day and a second actual power consumption in a flat power consumption period corresponding to the target day, obtaining a peak power correction coefficient according to a first ratio of the first actual power consumption to the peak predicted power consumption, obtaining a flat power correction coefficient according to a second ratio of the second actual power consumption to the predicted power consumption, adjusting the peak power consumption function according to the peak power correction coefficient, obtaining an updated peak power consumption function, and adjusting the flat power consumption function according to the flat power correction coefficient, thereby obtaining the updated flat power consumption function. Through the step, a charging and discharging plan is formulated again according to the current energy storage electric quantity Q, so that fine management is achieved, namely, the power consumption of the last day is recorded into an EMS database, the recent power consumption data are intercepted again, and the power consumption function of each period is fitted.
By the alternative embodiments, at least the following advantages can be achieved:
(1) Because the discharging strategy of the energy storage battery in the electricity utilization period corresponding to the target day is determined according to the stored electricity quantity of the energy storage battery and the target predicted electricity consumption, and the target predicted electricity consumption is determined according to the peak predicted electricity consumption and the flat predicted electricity consumption, namely, the electricity utilization requirement information of different electricity utilization periods of the target day can be provided by determining the peak predicted electricity consumption and the flat predicted electricity consumption, the energy storage battery is helped to formulate a discharging strategy corresponding to the reasonable peak electricity utilization period and the flat electricity utilization period respectively, and the electric energy of the energy storage battery is released in the required peak period or the stationary period so as to meet the electricity utilization requirement to the maximum extent;
(2) The peak electricity function and the flat value electricity function are determined according to the historical electricity data, the electricity consumption corresponding to each period is further predicted according to the peak electricity function and the flat value electricity function, the electricity consumption requirements of the peak value corresponding to the target day and the flat value electricity period can be estimated more accurately, the peak electricity function and the flat value electricity function are called, the predicted electricity consumption is determined, the accuracy of electricity consumption requirement prediction can be improved, the supply and demand balance is optimized, and a more reasonable and efficient discharge strategy is formulated;
(3) Because the electric quantity fluctuation percentage is considered in the step of formulating the discharge strategy, namely, the electric quantity of the peak electricity consumption period can be predicted more accurately and comprehensively, the discharge strategy of the energy storage battery is adjusted and optimized, the discharge strategy of the energy storage battery can be matched with the actual electricity consumption requirement better to a certain extent, and the stability of the electricity requirement is improved.
It should be noted that, for simplicity of description, the foregoing method embodiments are all described as a series of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts described, as some steps may be performed in other orders or concurrently in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the various embodiments of the present invention.
Example 2
According to an embodiment of the present invention, there is further provided an apparatus for implementing the above-mentioned method for making a discharge policy of an energy storage battery, and fig. 3 is a block diagram of a structure of the apparatus for making a discharge policy of an energy storage battery according to an embodiment of the present invention, as shown in fig. 3, the apparatus includes: the receiving module 302, the retrieving module 304, the first determining module 306, the second determining module 308, and the third determining module 310 are described in detail below.
The receiving module 302 is configured to receive a discharge policy making request of the energy storage battery, where the discharge policy making request carries a target day, and the discharge policy making request of the energy storage battery is used to request to determine a discharge policy of the energy storage battery in a power utilization period corresponding to the target day;
A retrieving module 304, coupled to the receiving module 302, for retrieving a peak electricity consumption period corresponding to the target day and a flat electricity consumption period in response to a discharge policy making request;
The first determining module 306 is connected to the retrieving module 304, and is configured to determine a peak predicted power consumption amount in a peak power consumption period corresponding to the target day, and a flat predicted power consumption amount in a flat power consumption period corresponding to the target day;
The second determining module 308, coupled to the first determining module 306, is configured to determine a target predicted power consumption according to the peak predicted power consumption and the flat predicted power consumption;
The third determining module 310 is connected to the second determining module 308, and is configured to determine a discharging policy of the energy storage battery in the power utilization period corresponding to the target day according to the stored power of the energy storage battery and the target predicted power consumption, where the stored power is the power stored in the energy storage battery in the valley power utilization period.
It should be noted that the receiving module 302, the retrieving module 304, the first determining module 306, the second determining module 308 and the third determining module 310 correspond to steps S102 to S110 in the method for setting a discharge strategy of the energy storage battery, and the plurality of modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in the foregoing embodiment 1.
Example 3
According to another aspect of the embodiment of the present invention, there is also provided an electronic device including: a processor; a memory for storing processor-executable instructions, wherein the processor is configured to execute the instructions to implement the method of discharging the energy storage battery of any of the above.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, which when executed by a processor of an electronic device, causes the electronic device to perform the method for setting a discharge policy of an energy storage battery of any one of the above.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a read-only memory (ROM), a random access memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (9)
1. A method for establishing a discharge strategy of an energy storage battery, comprising the steps of:
receiving a discharge strategy formulation request of an energy storage battery, wherein the discharge strategy formulation request carries a target day, and the discharge strategy formulation request of the energy storage battery is used for requesting to determine a discharge strategy of the energy storage battery in a power utilization period corresponding to the target day;
responding to the discharge strategy making request, and calling a peak electricity consumption period and a flat electricity consumption period which correspond to the target day;
determining the peak value prediction electricity consumption under the peak value electricity consumption period corresponding to the target day and the flat value prediction electricity consumption under the flat value electricity consumption period corresponding to the target day;
Determining a target predicted power consumption according to the peak predicted power consumption and the flat predicted power consumption;
Determining a discharge strategy of the energy storage battery in a power utilization period corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted electric quantity, wherein the stored electric quantity is the electric quantity stored in a valley power utilization period of the energy storage battery;
the method comprises the steps of determining a discharge strategy of the energy storage battery corresponding to a target day according to the stored electric quantity of the energy storage battery and a target predicted electric quantity, wherein the discharge strategy comprises at least one of the following steps:
Determining the discharging strategy to be a strategy comprising a first peak discharging strategy and a first flat discharging strategy under the condition that the target predicted electricity consumption is the sum of the peak predicted electricity consumption and the flat predicted electricity consumption and the stored electricity consumption of the energy storage battery is larger than the target predicted electricity consumption, wherein the first peak discharging strategy is the electricity consumption of the energy storage battery in a peak electricity consumption period corresponding to the target day, the first flat discharging strategy is the electricity consumption of the energy storage battery in a flat electricity consumption period corresponding to the target day, and the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption;
Determining the discharge strategy as a second peak discharge strategy under the condition that the target predicted electricity consumption is peak wave electricity consumption and the stored electricity consumption of the energy storage battery is smaller than the peak wave electricity consumption, wherein the second peak discharge strategy is the electricity consumption of the energy storage battery, and discharging the stored electricity consumption in a peak electricity consumption period corresponding to the target day, and the peak wave electricity consumption is obtained according to the peak predicted electricity consumption and a fluctuation coefficient;
And determining the discharging strategy to be a strategy comprising a third peak discharging strategy and a target discharging strategy when the target predicted electricity consumption comprises the sum of the peak predicted electricity consumption and the average value predicted electricity consumption and the peak wave electricity consumption and the stored electricity consumption of the energy storage battery is smaller than the sum and larger than the peak wave electricity consumption, wherein the third peak discharging strategy is the electricity consumption of the energy storage battery in a peak electricity consumption period corresponding to the target day, the target discharging strategy is the electricity consumption of the energy storage battery in a second difference electricity consumption in a target electricity consumption period corresponding to the target day, and the second difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption, and the target electricity consumption period is a electricity consumption period selected from valley electricity consumption periods corresponding to the average value electricity consumption period and the target day.
2. The method of claim 1, wherein the determining the peak predicted power usage for the peak power usage period corresponding to the target day and the flat predicted power usage for the flat power usage period corresponding to the target day is preceded by:
The peak electricity function under the peak electricity period corresponding to the target day and the flat value electricity function under the flat value electricity period corresponding to the target day are called, wherein the peak electricity function is a function which comprises a day showing the corresponding type of the target day and a corresponding relation of the corresponding peak forecast electricity consumption, and the flat value electricity function is a function which comprises a day showing the corresponding type of the target day and a corresponding relation of the corresponding flat value forecast electricity consumption;
and determining the peak value prediction electricity consumption according to the peak value electricity consumption function, and determining the flat value prediction electricity consumption according to the flat value electricity consumption function.
3. The method of claim 2, wherein the retrieving the peak power usage function for the peak power usage period corresponding to the target day and the flat power usage function for the flat power usage period corresponding to the target day is preceded by:
Acquiring historical electricity utilization data in a preset period;
Determining a first historical electricity consumption under a preset peak electricity consumption period corresponding to the preset period and a second historical electricity consumption under a preset flat electricity consumption period corresponding to the preset period from the historical electricity consumption data;
And obtaining the peak value electricity utilization function according to the first historical electricity utilization quantity, and obtaining the flat value electricity utilization function according to the second historical electricity utilization quantity.
4. The method of claim 1, wherein determining the discharge strategy of the energy storage battery before the target day based on the stored power of the energy storage battery and the target predicted power consumption further comprises:
Obtaining the fluctuation coefficient according to the full electricity percentage and the electric quantity fluctuation percentage, wherein the electric quantity fluctuation percentage is the electric quantity percentage caused by electric wave motion of the electric object for the sign;
And determining the product of the fluctuation coefficient and the peak value predicted power consumption in the peak value power consumption period corresponding to the target day to obtain the peak value fluctuation power consumption.
5. The method of claim 1, wherein prior to determining the discharge strategy as a strategy comprising a third peak discharge strategy and a target discharge strategy, further comprising:
Predicting whether a period of which the corresponding electricity utilization price is higher than the electricity utilization price corresponding to the flat value electricity utilization period corresponding to the target day exists in the valley value electricity utilization period corresponding to the target day, and obtaining a prediction result;
Determining a first sub-period when the predicted result is that a period corresponding to the electricity consumption period of the valley value corresponding to the target day has a higher electricity consumption price than a period corresponding to the electricity consumption period of the flat value corresponding to the target day, wherein the first sub-period is a period corresponding to the electricity consumption price of the valley value corresponding to the target day, which is higher than the electricity consumption price of the flat value corresponding to the target day;
determining the sub-period prediction electricity consumption corresponding to the first sub-period;
determining that the difference value between the second difference value electricity consumption and the sub-period predicted electricity consumption is a third difference value electricity consumption under the condition that the sub-period predicted electricity consumption is lower than the second difference value electricity consumption;
Selecting a second sub-period for consuming the third difference electricity consumption from the flat value electricity consumption periods corresponding to the target days;
and determining the second sub-period and the second sub-period as the target power utilization period.
6. The method according to claim 2, wherein the determining, according to the stored power of the energy storage battery and the target predicted power consumption, a peak power consumption period corresponding to the target day of the energy storage battery and a discharging strategy corresponding to a flat power consumption period corresponding to the target day respectively further includes:
Determining a first actual power consumption in a peak power consumption period corresponding to the target day and a second actual power consumption in a flat power consumption period corresponding to the target day;
Obtaining a peak power correction coefficient according to a first proportion of the first actual power consumption to the peak predicted power consumption, and obtaining a flat power correction coefficient according to a second proportion of the second actual power consumption to the predicted power consumption;
and adjusting the peak electricity function according to the peak electricity quantity correction coefficient to obtain an updated peak electricity function, and adjusting the flat electricity function according to the flat electricity quantity correction coefficient to obtain an updated flat electricity function.
7. A discharge strategy formulation device for an energy storage battery, comprising:
the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving a discharging strategy making request of the energy storage battery, wherein the discharging strategy making request carries a target day, and the discharging strategy making request of the energy storage battery is used for requesting to determine a discharging strategy of the energy storage battery in a power utilization period corresponding to the target day;
The calling module is used for responding to the discharge strategy making request and calling the peak power utilization period corresponding to the target day and the flat power utilization period;
The first determining module is used for determining the peak value prediction electricity consumption under the peak value electricity consumption period corresponding to the target day and the flat value prediction electricity consumption under the flat value electricity consumption period corresponding to the target day;
the second determining module is used for determining target predicted electricity consumption according to the peak predicted electricity consumption and the flat predicted electricity consumption;
The third determining module is used for determining a discharging strategy of the energy storage battery in a power utilization period corresponding to the target day according to the stored electric quantity of the energy storage battery and the target predicted power consumption, wherein the stored electric quantity is the electric quantity stored in a valley power utilization period of the energy storage battery;
the method comprises the steps of determining a discharge strategy of the energy storage battery corresponding to a target day according to the stored electric quantity of the energy storage battery and a target predicted electric quantity, wherein the discharge strategy comprises at least one of the following steps:
Determining the discharging strategy to be a strategy comprising a first peak discharging strategy and a first flat discharging strategy under the condition that the target predicted electricity consumption is the sum of the peak predicted electricity consumption and the flat predicted electricity consumption and the stored electricity consumption of the energy storage battery is larger than the target predicted electricity consumption, wherein the first peak discharging strategy is the electricity consumption of the energy storage battery in a peak electricity consumption period corresponding to the target day, the first flat discharging strategy is the electricity consumption of the energy storage battery in a flat electricity consumption period corresponding to the target day, and the first difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption;
Determining the discharge strategy as a second peak discharge strategy under the condition that the target predicted electricity consumption is peak wave electricity consumption and the stored electricity consumption of the energy storage battery is smaller than the peak wave electricity consumption, wherein the second peak discharge strategy is the electricity consumption of the energy storage battery, and discharging the stored electricity consumption in a peak electricity consumption period corresponding to the target day, and the peak wave electricity consumption is obtained according to the peak predicted electricity consumption and a fluctuation coefficient;
And determining the discharging strategy to be a strategy comprising a third peak discharging strategy and a target discharging strategy when the target predicted electricity consumption comprises the sum of the peak predicted electricity consumption and the average value predicted electricity consumption and the peak wave electricity consumption and the stored electricity consumption of the energy storage battery is smaller than the sum and larger than the peak wave electricity consumption, wherein the third peak discharging strategy is the electricity consumption of the energy storage battery in a peak electricity consumption period corresponding to the target day, the target discharging strategy is the electricity consumption of the energy storage battery in a second difference electricity consumption in a target electricity consumption period corresponding to the target day, and the second difference electricity consumption is the electricity consumption corresponding to the difference between the stored electricity consumption of the energy storage battery and the peak predicted electricity consumption, and the target electricity consumption period is a electricity consumption period selected from valley electricity consumption periods corresponding to the average value electricity consumption period and the target day.
8. An electronic device, comprising:
A processor;
A memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of discharging a power storage battery as claimed in any one of claims 1 to 6.
9. A computer readable storage medium, characterized in that instructions in the computer readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of discharging a power storage battery according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410006051.9A CN117498416B (en) | 2024-01-03 | 2024-01-03 | Method and device for formulating discharge strategy of energy storage battery and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410006051.9A CN117498416B (en) | 2024-01-03 | 2024-01-03 | Method and device for formulating discharge strategy of energy storage battery and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117498416A CN117498416A (en) | 2024-02-02 |
| CN117498416B true CN117498416B (en) | 2024-04-19 |
Family
ID=89680503
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410006051.9A Active CN117498416B (en) | 2024-01-03 | 2024-01-03 | Method and device for formulating discharge strategy of energy storage battery and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117498416B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101787538B1 (en) * | 2016-04-29 | 2017-10-18 | 서강대학교산학협력단 | Charging and discharging method of energy storage device based on uncertainty of demand load and apparatus thereof |
| CN114142517A (en) * | 2021-09-16 | 2022-03-04 | 国网江苏省电力有限公司南京供电分公司 | Control method for grid-connected operation of light storage and charging integrated system and power grid |
| CN115632426A (en) * | 2022-11-08 | 2023-01-20 | 中国光大绿色技术创新研究院有限公司 | Energy storage control method, device and system and storage medium |
| CN115733161A (en) * | 2022-12-14 | 2023-03-03 | 合肥华宇智航动力能源有限公司 | Small distributed energy storage scheduling system and method |
| CN117200299A (en) * | 2023-11-01 | 2023-12-08 | 合肥国轩高科动力能源有限公司 | Power control method and device of energy storage battery and electronic equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9002531B2 (en) * | 2012-09-28 | 2015-04-07 | Sharp Laboratories Of America, Inc. | System and method for predictive peak load management via integrated load management |
-
2024
- 2024-01-03 CN CN202410006051.9A patent/CN117498416B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101787538B1 (en) * | 2016-04-29 | 2017-10-18 | 서강대학교산학협력단 | Charging and discharging method of energy storage device based on uncertainty of demand load and apparatus thereof |
| CN114142517A (en) * | 2021-09-16 | 2022-03-04 | 国网江苏省电力有限公司南京供电分公司 | Control method for grid-connected operation of light storage and charging integrated system and power grid |
| CN115632426A (en) * | 2022-11-08 | 2023-01-20 | 中国光大绿色技术创新研究院有限公司 | Energy storage control method, device and system and storage medium |
| CN115733161A (en) * | 2022-12-14 | 2023-03-03 | 合肥华宇智航动力能源有限公司 | Small distributed energy storage scheduling system and method |
| CN117200299A (en) * | 2023-11-01 | 2023-12-08 | 合肥国轩高科动力能源有限公司 | Power control method and device of energy storage battery and electronic equipment |
Non-Patent Citations (3)
| Title |
|---|
| Huiqian Guo ; Yating Wang ; Siyuan Liu ; .Research on Capacity Allocation of Grid Side Energy Storage Participating in Power System Peak Shaving.2022 7th International Conference on Power and Renewable Energy (ICPRE).2022,第1-7页. * |
| 光伏储放系统控制策略研究;娄婷婷;郭翔;徐鼎;曹际娜;黄德旭;;山东电力技术;20180825;第45卷(第08期);第5-8页 * |
| 面向商业大厦的储能微网系统及其经济效益分析;李建勇;迟鸣声;朱秉程;李达非;电器工业;20190905(第09期);第47-52页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117498416A (en) | 2024-02-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sevilla et al. | Techno-economic analysis of battery storage and curtailment in a distribution grid with high PV penetration | |
| Zhu et al. | The case for efficient renewable energy management in smart homes | |
| US20090063257A1 (en) | Automated peak demand controller | |
| Casini et al. | A receding horizon approach to peak power minimization for EV charging stations in the presence of uncertainty | |
| CN110676863B (en) | Energy storage optimal configuration method and system | |
| US9727929B2 (en) | Energy management system, energy management method, program, server apparatus, and local server | |
| US20190086983A1 (en) | Energy storage-aware demand charge minimization | |
| CN109830975B (en) | Energy storage battery multifunctional operation optimization method and system and storage medium | |
| CN114938035B (en) | Shared energy storage energy scheduling method and system considering energy storage degradation cost | |
| Solano et al. | Impact of fixed charges on the viability of self-consumption photovoltaics | |
| CN115481905A (en) | Power grid power demand response method participated by user and related device | |
| CN113988444A (en) | Electricity charge optimization control system and method for light storage system | |
| CN115765015A (en) | Source network load storage cooperative interaction scheme making method oriented to power grid practical application scene | |
| CN111859279A (en) | Method and device for evaluating transformer area regulation and control capacity of new energy equipment at client side | |
| CN117200299B (en) | Power control method and device of energy storage battery and electronic equipment | |
| CN111539620B (en) | Energy storage operation method and system for providing energy service | |
| CN117498416B (en) | Method and device for formulating discharge strategy of energy storage battery and electronic equipment | |
| Telaretti et al. | A novel operating strategy for customer-side energy storages in presence of dynamic electricity prices | |
| CN116436048A (en) | Multi-target-driven micro-grid group cloud energy storage optimal configuration method and device | |
| CN115811094A (en) | Novel power system scheduling method and system considering carbon cost conduction | |
| CN111969598B (en) | User side energy storage optimization method and system considering excitation type demand side response | |
| US20220060018A1 (en) | Microgrid system comprising energy management system of energy storage system (ess)-connected photovoltaic power system | |
| JP7303707B2 (en) | Alternate Baseline Calculation Apparatus, Trained Model, Machine Learning Apparatus, Alternative Baseline Calculation Method and Program | |
| CN110048414B (en) | Virtual power plant interactive resource subsidy pricing method | |
| CN111445154A (en) | Power market resource self-scheduling optimization method, system and equipment |
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 | ||
| GR01 | Patent grant |