A charging and discharging method of energy storage system, energy storage system and storage medium

Abstract

The present application discloses a charging and discharging method of an energy storage system, an energy storage system and a storage medium, and relates to the technical field of energy storage systems; the method comprises the following steps: obtaining time-of-use electricity price data and load demand in real time; predicting future electricity price trends and electricity demand based on the time-of-use electricity price data and the load demand by using a pre-trained deep learning model; obtaining the charging and discharging power and battery energy of a battery pack, and obtaining a profit value based on electricity price information and the charging and discharging power of the battery pack; obtaining a maximum profit value based on an electricity continuity constraint equation, a power balance constraint equation and the calculation formula; constraining the continuity of the battery pack electricity based on the electricity continuity constraint equation, and constraining the corresponding relationship between the load power, the battery pack charging and discharging power and the grid power based on the power balance equation; reducing electricity bill expenditure and increasing electricity sales revenue by accurately predicting electricity prices and demands and adjusting the charging and discharging strategy accordingly.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage systems, and in particular to a charging and discharging method of an energy storage system, an energy storage system, and a storage medium. Background Art

[0002] With the rapid development of renewable energy generation and electric vehicles, the power system is facing increasingly complex power management challenges; dynamic time-of-use electricity price system, as an economic incentive mechanism, has been widely used to regulate the balance between electricity demand and supply.

[0003] However, the management and optimization of existing energy storage systems under dynamic time-of-use electricity price environments still face many technical challenges, such as failing to fully utilize electricity price fluctuations to maximize economic benefits and failing to effectively consider battery life and charging efficiency. Summary of the invention

[0004] To solve the above problems, the present application discloses a charging and discharging method of an energy storage system, an energy storage system and a storage medium, and realizes a maximum profit charging and discharging strategy under a dynamic time-of-use electricity price, realizes intelligent charging and discharging management of battery packs, and improves the economy and stability of the system.

[0005] The first technical solution adopted in this application is to provide a charging and discharging method of an energy storage system, comprising the following steps:

[0006] Acquire time-of-use electricity price data and load demand in real time; use a pre-trained deep learning model to predict future electricity price trends and electricity demand based on the time-of-use electricity price data and load demand;

[0007] The power and battery energy of the battery pack charge and discharge are obtained, and the revenue value is obtained based on the electricity price information and the battery pack charge and discharge power. The calculation formula of the revenue value, the electricity price and the battery pack charge and discharge power is as follows:

[0008] Re=\int ^{T}_{0} {Pri\left ( {t} \right )}×{P}_{Ess}\left ( {t} \right )dt=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}×{P}_{Ess}\left [ {i} \right ]△t ;

[0009] The maximum benefit is obtained based on the power continuity constraint equation, the power balance constraint equation and the calculation formula; the continuity of the battery pack power is constrained based on the power continuity constraint equation, and the corresponding relationship between the load power, the battery pack charging and discharging power and the grid power is constrained based on the power balance equation; the power continuity constraint equation is:

[0010] {E}_{batt}\left [ {i} \right ]={P}_{Ess}\left [ {i} \right ]×△t+{E}_{batt}\left [ {i-1} \right ] ; The power balance constraint equation is: ;

[0011] Re is the revenue value, Pri is the electricity price, The charging and discharging power of the battery pack, is the load power, is the grid power, is the battery pack energy, t is the current time, T is the total duration, △t is the time period, i represents the i-th time period, i≥1, N is the number of time periods, , is the current electricity price, is the current battery pack charge and discharge power, Pri\left [ {i} \right ] is the electricity price in the i-th time period, {P}_{Ess}\left [ {i} \right ] is the battery pack charge and discharge power in the i-th time period, {E}_{batt}\left [ {i} \right ] is the battery pack energy in the i-th time period, {E}_{batt}\left [ {i-1} \right ] is the battery pack energy in the i-1th time period.

[0012] The battery pack has a charging power upper limit and a discharging power upper limit for its charging and discharging power. The charging power of the battery pack is less than the charging power upper limit, and the discharging power of the battery pack is less than the discharging power upper limit.

[0013] The battery pack energy has a capacity upper limit, and the battery pack energy is less than or equal to the capacity upper limit.

[0014] Among them, photovoltaic power generation is also included. The photovoltaic power generation power is , the power balance constraint equation is updated as: ;

[0015] Photovoltaic power generation gives priority to providing load power. > , photovoltaic power generation meets the load power, and the excess energy flows to the battery pack to charge the battery pack. = - , is 0;

[0016] like < < + , the photovoltaic and battery groups discharge the load together. = - , is 0;

[0017] like + < , the photovoltaic, battery and grid jointly discharge the load. = - - .

[0018] The electricity price information includes the electricity consumption time period, and the electricity consumption time period includes the peak electricity price period, the low electricity price period and the flat electricity price period;

[0019] If the electricity consumption time period is a peak electricity price period, the battery pack is discharged;

[0020] If the electricity consumption time period is a low electricity price period, the battery pack is charged;

[0021] If the electricity consumption time period is a flat electricity price period and the power grid price is greater than the battery pack price, the battery pack is discharged;

[0022] If the electricity consumption time period is a flat electricity price period and the power grid electricity price is less than the battery pack electricity price, the battery pack is charged.

[0023] The conversion efficiency of the PCS component is obtained, and the PCS component includes a first PCS and a second PCS, the first PCS is connected to the power grid and the battery pack, and the second PCS is connected to the battery pack and the load; the power grid power is converted based on the conversion efficiency of the first PCS. The battery pack charging and discharging power is modified based on the conversion efficiency of the second PCS. and / or photovoltaic power generation Make corrections.

[0024] The charging and discharging power of the battery pack is controlled based on PID, the change in load power is obtained in real time, and the charging and discharging power of the battery pack is adjusted in real time based on the change in load power.

[0025] The battery life and charging efficiency of the battery pack are obtained to correct the charging and discharging power of the battery pack and the battery energy of the battery pack.

[0026] The second technical solution adopted in the present application is: to provide an energy storage system, including a battery pack, a PCS component and an EMS, wherein the EMS is used to implement the charging and discharging method of the energy storage system as described in any of the above items.

[0027] The third technical solution adopted in the present application is: to provide a computer-readable storage medium, wherein the computer-readable storage medium stores program data, and the program data can be executed by a processor to implement the charging and discharging method of the energy storage system as described in any one of the above items.

[0028] Beneficial effects of the present application: Different from the prior art, the present application discloses a charging and discharging method of an energy storage system, an energy storage system and a storage medium; wherein the charging and discharging method of the energy storage system comprises the following steps: obtaining time-of-use electricity price data and load demand in real time; predicting future electricity price trends and electricity demand based on the time-of-use electricity price data and the load demand by a pre-trained deep learning model; obtaining the charging and discharging power and battery energy of a battery pack, and obtaining a revenue value based on the electricity price information and the charging and discharging power of the battery pack, wherein the calculation formula of the revenue value, the electricity price and the charging and discharging power of the battery pack is as follows: Re=\int ^{T}_{0} {Pri\left ( {t} \right )}×{P}_{Ess}\left ( {t} \right )dt=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}×{P}_{Ess}\left [ {i} \right ]△t ;

[0029] The maximum profit is obtained based on the power continuity constraint equation, the power balance constraint equation and the calculation formula; the continuity of the battery pack power is constrained based on the power continuity constraint equation, and the corresponding relationship between the load power, the battery pack charging and discharging power and the grid power is constrained based on the power balance equation; by accurately predicting electricity prices and demands, and adjusting the charging and discharging strategies accordingly, electricity expenses can be reduced and electricity sales revenue can be increased. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0031] Figure 1 A schematic diagram of a flow chart of an embodiment of a charging and discharging method for an energy storage system provided in the present application;

[0032] Figure 2A curve diagram of the first embodiment of the correspondence between electricity price information, load power and battery pack charging and discharging power provided in this application;

[0033] Figure 3 A curve diagram of the second embodiment of the correspondence between the electricity price information, load power and battery pack charging and discharging power provided in this application;

[0034] Figure 4 A schematic diagram of the structure of an energy storage system according to an embodiment of the present application;

[0035] Figure 5 A schematic diagram of the structure of an embodiment of a computer-readable storage medium provided in this application. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It will be appreciated that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for ease of description, only some but not all structures related to the present application are shown in the drawings. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the art without making creative work are within the scope of protection of the present application.

[0037] The terms "first", "second", etc. in this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0038] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0039] See also Figure 1 As shown, Figure 1 The schematic diagram of a flow chart of an embodiment of a charging and discharging method for an energy storage system provided in the present application includes the following steps:

[0040] Step S11: Obtain time-of-use electricity price data and load demand in real time; receive electricity price information of different time periods in real time through the interface with the electricity supplier or energy market trading platform. The electricity price information includes electricity prices during peak hours, flat hours and off-peak hours; use smart meters, sensors or other monitoring equipment to collect users' electricity consumption in real time; for example, use a gateway meter to obtain load power; the load demand can be the electricity consumption of household users, commercial buildings or industrial facilities.

[0041] The pre-trained deep learning model predicts future electricity price trends and power demand based on time-of-use electricity price data and load demand; select appropriate deep learning models according to task characteristics, such as long short-term memory network (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) combined with RNN structure, or Transformer, etc. Use historical time-of-use electricity price data and load demand as input, and electricity price trends and power demand as output to train the selected model; during the training process, use appropriate loss functions (such as mean square error MSE) and optimization algorithms (such as Adam), and evaluate model performance through cross-validation to avoid overfitting.

[0042] By acquiring time-of-use electricity price data and load demand in real time and using pre-trained deep learning models for prediction, energy storage systems can be made smarter and more efficient, providing users with a better service experience while also helping to achieve broader economic and social benefits.

[0043] Step S12: Obtain the charging and discharging power and battery energy of the battery pack, and obtain the revenue value based on the electricity price information and the charging and discharging power of the battery pack. The calculation formula of the revenue value, the electricity price and the charging and discharging power of the battery pack is as follows:

[0044] Re=\int ^{T}_{0} {Pri\left ( {t} \right )}×{P}_{Ess}\left ( {t} \right )dt=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}\times {P}_{Ess}\left [ {i} \right ]△t .

[0045] The continuous time interval [0, T] is divided into multiple discrete time periods △t. The length of each time period can be set according to actual needs (for example, every 15 minutes, 30 minutes, etc.). For each time period i, the corresponding electricity price Pri[i] and the battery pack charge and discharge power are recorded. ;

[0046] Use the formula Re=\int ^{T}_{0} {Pri\left ( {t} \right )}×{P}_{Ess}\left ( {t} \right )dt=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}\times {P}_{Ess}\left [ {i} \right ]△t To calculate the revenue value Re, the formula represents the charging and discharging power of the battery pack within a period of time T. The electricity price at the corresponding time The sum of the products of

[0047] In the discrete case, it can be simplified to the electricity price Pri\left [ {i} \right ] for each time period i and charging and discharging power {P}_{Ess}\left [ {i} \right ] Sum the products of and multiply by the time period length △t to get the return value Re.

[0048] Step S13: Obtain the maximum benefit based on the power continuity constraint equation, the power balance constraint equation and the calculation formula; constrain the continuity of the battery power based on the power continuity constraint equation, and constrain the corresponding relationship between the load power, the battery charging and discharging power and the grid power based on the power balance equation; the power continuity constraint equation is:

[0049] {E}_{batt}\left [ {i} \right ]={P}_{Ess}\left [ {i} \right ]\times △t+{E}_{batt}\left [ {i-1} \right ] .

[0050] The energy continuity constraint equation ensures that the energy of the battery pack remains continuous between different time points. The battery energy at each time period i is {E}_{batt}\left [ {i} \right ] is the energy of the previous time period i-1 {E}_{batt}\left [ {i-1} \right ] Add the charge and discharge power {P}_{Ess}\left [ {i} \right ] in the current time period Multiplying this by the time interval ∆t ensures that the battery pack is not overcharged or overdischarged, maintaining its healthy state.

[0051] The power balance constraint equation is: ; Re is the revenue value, Pri is the electricity price, The charging and discharging power of the battery pack, is the load power, is the grid power, is the battery pack energy, t is the current time, T is the total duration, △t is the time period, i represents the i-th time period, i≥1, N is the number of time periods, , is the current electricity price, is the current battery pack charge and discharge power, Pri\left [ {i} \right ] is the electricity price in the i-th time period, {P}_{Ess}\left [ {i} \right ] is the battery pack charge and discharge power in the i-th time period, {E}_{batt}\left [ {i} \right ] is the battery pack energy in the i-th time period, {E}_{batt}\left [ {i-1} \right ] is the battery pack energy in the i-1th time period.

[0052] The power balance constraint equation defines the relationship between the load power, the grid power, and the battery pack charge and discharge power; it ensures that the total output power of the system meets the needs of the user, while taking into account the role of the grid as an auxiliary power source; the role of the power balance constraint equation is described below in conjunction with a specific embodiment:

[0053] If the load power is greater than the battery pack charge and discharge power, for example, the load power is 500kw, and the battery pack charge and discharge power is 400kw, the battery pack alone cannot supply power to the load. At this time, the grid provides 100kw of energy to the load as an auxiliary power source; that is, at this time:

[0054] =500kw, =100kw, =400kw.

[0055] If the load power is less than the battery pack charge and discharge power, for example, the load power is 500kw, and the battery pack charge and discharge power is 700kw, the battery pack alone can meet the load demand. At this time, it is necessary to consider whether the grid side allows electricity sales, that is, whether the grid allows the battery pack to input excess electricity to the grid side. If the grid side allows electricity sales, then at this time:

[0056] =500kw, =-200kw, =700kw.

[0057] If the grid side does not allow electricity to be sold, and the grid side does not allow the battery group to input excess electricity to the grid side, then:

[0058] =500kw, =0kw, =500kw.

[0059] Based on Re=\int ^{T}_{0} {Pri\left ( {t} \right )}×{P}_{Ess}\left ( {t} \right )dt=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}×{P}_{Ess}\left [ {i} \right ]△t , get , is the maximum benefit;

[0060] By constructing the linear programming objective inequality Ax< Seek ; A is the coefficient matrix composed of the electric quantity continuity constraint equation and the power balance constraint equation;

[0061] In the above equation, {P}_{Ess}\left [ {i} \right ] ,{E}_{batt}\left [ {i} \right ] and For variables, form the X vector matrix: \left [ {{P}_{Ess}\left ( {1∶i∶N} \right ), {P}_{grid}\left ( {1∶i∶N} \right ), {E}_{batt}\left ( {1∶i∶N} \right )} \right ] , N represents the number of Δt. For example, if the total duration is 12 hours and Δt is 30 minutes, then N is 24.

[0062] Constraint equations organized as matrices .

[0063] For example, the electric quantity continuity constraint equation is expressed as ,in and is the coefficient matrix and constant vector constructed according to the above equation; the power balance constraint equation can be expressed as ,in and are the coefficient matrix and constant vector constructed according to the above equation.

[0064] The linear programming model includes:

[0065] Objective function: Re=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}×{P}_{Ess}\left [ {i} \right ]△t .

[0066] Equality constraints: ,in It is a coefficient matrix composed of the electric quantity continuity constraint equation and the power balance constraint equation, and B is the corresponding constant vector.

[0067] Inequality constraints: ,in is a coefficient matrix consisting of battery pack power, energy and grid power constraints, is the corresponding constant vector; for example, the battery pack charging and discharging power has a charging upper limit and a discharging upper limit, the battery pack energy has a maximum capacity, and the grid power has a maximum power limit. The coefficient matrix based on the inequality will not be repeated here.

[0068] Solve the linear programming model through the LP (linear programming) algorithm, and find the maximum benefit based on the transformation basis iterative replacement ; Then adjust the charging and discharging strategy of the battery pack to maximize the benefits; The process of solving the maximum benefit value is described below in conjunction with a specific embodiment:

[0069] The input data includes:

[0070] Time interval: Δt is 30 minutes, the total duration is 24 hours, and N=48.

[0071] Electricity price data: Time-of-use electricity price for the next 24 hours Pri\left [ {0∶47} \right ] .

[0072] Load demand: load power for the next 24 hours {P}_{load}\left [ {0∶47} \right ] .

[0073] Initial battery energy: {E}_{batt}\left [ {0} \right ] =50% of rated capacity.

[0074] Battery pack parameters: Battery pack charge and discharge power range: -2000kw< <2000kw, negative number means charging, positive number means discharging; battery energy range: 0< <4000kwh.

[0075] Solution process:

[0076] The solver re-enters the objective function, equality constraints and inequality constraints, and solves the optimal X vector, namely \left [ {{P}_{Ess}\left ( {1∶48} \right ), {P}_{grid}\left ( {1∶48} \right ), {E}_{batt}\left ( {1∶48} \right )} \right ] , the optimal X vector includes the battery charging and discharging power, grid power and battery pack energy at the moment [0,47]; based on the X vector, the maximum benefit is obtained, and the calculation formula is as follows: {Re}_{max}=\sum ^{47}_{i=0} {Pri\left [ {i} \right ]}×{P}_{Ess}\left [ {i} \right ]△t .

[0077] By accurately solving the linear programming problem, the optimal charging and discharging strategy can be found while complying with all constraints to maximize the benefit value Re. Strict power continuity and power balance constraints ensure the stable operation of the system and avoid problems caused by insufficient or excessive power. By reasonably arranging the charging and discharging behavior, the energy storage system can provide backup power during peak hours, smooth the power supply curve, and reduce the pressure on the power grid.

[0078] To summarize, the energy storage system charging and discharging method of this embodiment includes the following steps: obtaining time-of-use electricity price data and load demand in real time; predicting future electricity price trends and electricity demand based on the time-of-use electricity price data and load demand using a pre-trained deep learning model; obtaining the charging and discharging power and battery energy of the battery pack, and obtaining the revenue value based on the electricity price information and the charging and discharging power of the battery pack. The calculation formula for the revenue value, the electricity price, and the charging and discharging power of the battery pack is as follows: Re=\int ^{T}_{0} {Pri\left ( {t} \right )}×{P}_{Ess}\left ( {t} \right )dt=\sum ^{N}_{i=0} {Pri\left [ {i} \right ]}×{P}_{Ess}\left [ {i} \right ]△t ;

[0079] The maximum profit is obtained based on the power continuity constraint equation, power balance constraint equation and calculation formula; the continuity of battery power is constrained based on the power continuity constraint equation, and the corresponding relationship between load power, battery pack charging and discharging power and grid power is constrained based on the power balance equation; by accurately predicting electricity prices and demand, and adjusting charging and discharging strategies accordingly, electricity expenses can be reduced and electricity sales revenue can be increased.

[0080] Among them, the battery pack charging and discharging power has a charging power upper limit and a discharging power upper limit. The charging power of the battery pack is less than the charging power upper limit, and the discharging power of the battery pack is less than the discharging power upper limit. For example, the charging power upper limit of the battery pack is 2000kw, and the discharging power upper limit is 2000kw, that is, the charging and discharging range of the battery pack is: -2000kw< <2000kw; add new inequality constraints ,in and is a coefficient matrix and constant vector constructed according to the upper limit of charge / discharge power.

[0081] By strictly controlling the charging and discharging power, we can avoid overcharging or discharging the battery, extend the battery life, reduce the intensity of the chemical reaction inside the battery, reduce the risk of thermal runaway, and improve safety. Different application scenarios (such as home energy storage, commercial buildings, and industrial facilities) may have different power requirements. By flexibly setting the power limit, the system can adapt to various application scenarios. For example, during peak hours, the charging power can be appropriately reduced to give priority to meeting the needs of important loads. During off-peak hours, low-cost electricity can be fully utilized for fast charging.

[0082] Among them, the battery pack energy has a capacity upper limit, and the battery pack energy is less than or equal to the capacity upper limit; add a new inequality constraint ,in and is a coefficient matrix and constant vector constructed according to the capacity upper limit. For example, for each time period i, the battery pack energy satisfies the following inequality:

[0083] 0≤{E}_{batt}\left [ {i} \right ] ≤ , The upper capacity limit.

[0084] Energy limitation ensures that the battery pack will not exceed its designed capacity under any circumstances, reducing the possibility of failure; stable energy management helps maintain the overall performance of the system, especially under high load or extreme conditions. In another embodiment, a minimum energy limit can also be set. , ensuring that the battery is not completely discharged, thus protecting the battery from damage. For example, setting =20% of rated capacity to avoid the impact of deep discharge on battery life.

[0085] In one embodiment, it also includes photovoltaic power generation, and the photovoltaic power generation power is ; The power balance constraint equation is updated as: ;

[0086] Photovoltaic power generation provides load power first. > , photovoltaic power generation meets the load power, and the excess energy flows to the battery pack to charge the battery pack. = - , 0; at this time, the battery charging and discharging power is less than 0, which means the battery pack is charging, and the value indicates the charging power;

[0087] like < < + , the photovoltaic and battery groups discharge the load together. = - , is 0; at this time, the battery charge and discharge power is greater than 0, which means the battery pack is discharging, and the value indicates the discharge power;

[0088] like + < , the photovoltaic, battery and grid jointly discharge the load. = - - .

[0089] During peak electricity price periods, priority is given to using photovoltaic power generation and battery packs to supply power, reducing the need to purchase electricity from the power grid, thereby reducing electricity bills; through reasonable charging and discharging strategies, charging can be done when electricity prices are low, and discharging can be done when electricity prices are peak, maximizing economic benefits; the system can dynamically adjust the charging and discharging strategy based on real-time photovoltaic power generation and load demand to ensure that it is always in the optimal state; for example, when photovoltaic power generation is sufficient, priority is given to meeting load demand and charging the battery pack; when photovoltaic power generation is insufficient, the power output of the battery pack and the power grid is reasonably scheduled.

[0090] Among them, Figure 2-Figure 3 As shown, Figure 2 A curve diagram of the first embodiment of the correspondence between electricity price information, load power and battery pack charging and discharging power provided in this application; Figure 3A curve diagram of the second embodiment of the correspondence between the electricity price information, load power and battery pack charge and discharge power provided in the present application; 1, 2, 3...10 in the figure are interval thresholds, and the time difference between any two adjacent ones is Δt; the electricity price information includes the electricity consumption time period, and the electricity consumption time period includes the peak electricity price period, the low electricity price period and the flat electricity price period;

[0091] If the electricity consumption period is during the peak electricity price period, the battery pack will be discharged;

[0092] If the electricity consumption period is during the low electricity price period, the battery pack will be charged;

[0093] If the electricity consumption period is a flat electricity price period and the grid electricity price is greater than the battery pack electricity price, the battery pack will discharge;

[0094] If the electricity consumption period is a flat electricity price period and the grid electricity price is lower than the battery pack electricity price, the battery pack will be charged.

[0095] Figure 2 Zhongyu Figure 3 The load power curve in is exactly the same. When the load power remains unchanged, the change of electricity price information will cause the change of the charging and discharging state of the battery pack; specifically, when the electricity consumption period is the peak electricity price period, the battery pack will discharge; when the electricity consumption period is the low electricity price period, the battery pack will charge.

[0096] New inequality constraints are added according to the corresponding relationship between electricity price time and electricity price. The specific coefficient matrix and constant vector are not repeated here. By discharging during the peak electricity price period and charging during the low electricity price period, the maximum economic benefit can be obtained during electricity price fluctuations. In the flat electricity price period, the charging and discharging strategy is flexibly adjusted according to the comparison between the grid electricity price and the battery pack electricity price to further optimize the cost.

[0097] In one embodiment, the conversion efficiency of a PCS (power conversion system) component is obtained. The PCS component includes a first PCS and a second PCS. The first PCS is connected to a power grid and a battery pack, and the second PCS is connected to the battery pack and a load. When charging the battery pack from the power grid, the discharge power of the power grid will be lost after passing through the first PCS, so the actual output power of the power grid is greater than ; The discharge power of the battery pack will be lost after passing through the second PCS, so the actual power output to the load will be less than Based on the conversion efficiency of the first PCS to the grid power Correction is made based on the conversion efficiency of the second PCS to adjust the battery pack charging and discharging power and / or photovoltaic power generation Make corrections; for example, the load requires a power of 400kw, the photovoltaic power is not generating electricity at this time, and the conversion efficiency of the second PCS is 80%, then the actual discharge power of the battery pack is 500kw.

[0098] After considering the PCS efficiency correction, the system can control the charging and discharging behavior more accurately to avoid power shortage or overload problems caused by efficiency loss; stable energy management helps to maintain the overall performance of the system, especially under high load or extreme conditions, to ensure the reliable operation of the system; precise efficiency correction enables the system to manage energy flow more finely and support more complex scheduling and optimization strategies; for example, during peak electricity price periods, the system can more accurately determine whether it should discharge from the battery pack to avoid unnecessary electricity expenses.

[0099] In one embodiment, the charge and discharge power of the battery pack is controlled based on a PID (proportional-integral-differential) control method, the change in load power is obtained in real time, and the charge and discharge power of the battery pack is adjusted in real time based on the change in load power; the PID control method is a typical feedback control algorithm and will not be described in detail here.

[0100] The PID controller can respond to changes in load power in real time and quickly adjust the charge and discharge power of the battery pack to ensure the stability and reliability of the system; for example, when the load power suddenly increases, the system can quickly release more energy from the battery pack; when the load power decreases, the system can promptly reduce the discharge power of the battery pack or even switch to charging mode.

[0101] In one embodiment, the battery life and charging efficiency of the battery pack are obtained to correct the charge and discharge power and battery energy of the battery pack; according to the SOH of the battery, the upper and lower safety limits of the charge and discharge power are set. As the battery ages, its maximum charge and discharge power is reduced to extend its service life. SOH represents the ratio of the current maximum capacity of the battery to the rated capacity of a new battery; for example, when the SOH drops to 80%, the maximum charge and discharge power is reduced to 80% of the rated power.

[0102] In this embodiment, the SOH and SOC (state of charge) charging and discharging efficiency of the battery can also be used as inequalities as constraints of the linear programming model, and the specific coefficient matrix and constant vector are not repeated here.

[0103] By obtaining the battery life and charging efficiency of the battery pack and correcting the charging and discharging power and battery energy, the energy storage system can not only extend the battery life and improve the energy management accuracy, but also optimize the economic benefits and enhance the system reliability and user experience.

[0104] like Figure 4 As shown, Figure 4 This is a structural schematic diagram of an embodiment of an energy storage system provided in the present application. The energy storage system includes a battery pack, a PCS component and an EMS (energy management system), wherein the EMS is used to implement the charging and discharging method of the energy storage system provided in the embodiment shown in the present application. Figure 4The energy storage cabinet is only used as an example, and the specific structure is not limited. The location and quantity of the battery pack, PCS components, and EMS included in the energy storage system are also not limited.

[0105] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of an embodiment of a computer-readable storage medium provided by the present application. The computer-readable storage medium stores program data. When the program data is executed by a processor, it is used to implement the following method:

[0106] Obtain time-of-use electricity price data and load demand in real time; use pre-trained deep learning models to predict future electricity price trends and electricity demand based on time-of-use electricity price data and load demand; obtain battery pack charging and discharging power and battery energy, and obtain revenue value based on electricity price information and battery pack charging and discharging power; obtain maximum revenue based on power continuity constraint equations, power balance constraint equations and calculation formulas;

[0107] Among them, the processor in the above embodiment can also be called CPU (Central Processing Unit). The processor may be an integrated circuit chip with signal processing capabilities. The processor can also be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, 15ASIC), a field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In addition, the processor can be implemented by multiple integrated circuit chips.

[0108] Among them, the memory or computer-readable storage medium in the above embodiments can be a medium that can store program data, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or it can also be a server that stores the program data. The server can send the stored program data to other devices for execution, or it can also execute the stored program data by itself.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation described above is only illustrative, for example, the division of the modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0110] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0111] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0112] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A charging and discharging method for an energy storage system, characterized in that: The steps include: Acquire time-of-use electricity price data and load demand in real time; use a pre-trained deep learning model to predict future electricity price trends and electricity demand based on the time-of-use electricity price data and load demand; The power and battery energy of the battery pack charge and discharge are obtained, and the revenue value is obtained based on the electricity price information and the battery pack charge and discharge power. The calculation formula of the revenue value, the electricity price and the battery pack charge and discharge power is as follows: ； The maximum benefit is obtained based on the power continuity constraint equation, the power balance constraint equation and the calculation formula; the continuity of the battery pack power is constrained based on the power continuity constraint equation, and the corresponding relationship between the load power, the battery pack charging and discharging power and the grid power is constrained based on the power balance equation; the power continuity constraint equation is: ； The power balance constraint equation is: ； Re is the revenue value, Pri is the electricity price, The charging and discharging power of the battery pack, is the load power, is the grid power, is the battery pack energy, t is the current time, T is the total duration, △t is the time period, i represents the i-th time period, i≥1, N is the number of time periods, , is the current electricity price, The current battery charge and discharge power, is the electricity price in the i-th time period, is the charging and discharging power of the battery pack in the i-th time period, is the battery pack energy in the i-th time period, is the battery pack energy in the i-1th time period.

2. The charging and discharging method of the energy storage system according to claim 1, characterized in that: The battery pack has a charging power upper limit and a discharging power upper limit for the charging and discharging power. The charging power of the battery pack is less than the charging power upper limit, and the discharging power of the battery pack is less than the discharging power upper limit.

3. The charging and discharging method of the energy storage system according to claim 2, characterized in that: The battery pack energy has a capacity upper limit, and the battery pack energy is less than or equal to the capacity upper limit.

4. The charging and discharging method of the energy storage system according to any one of claims 1 to 3, characterized in that: It also includes photovoltaic power generation, the photovoltaic power generation power is ; The power balance constraint equation is updated as follows: ； Photovoltaic power generation provides load power first. > , photovoltaic power generation meets the load power, and the excess energy flows to the battery pack to charge the battery pack. , is 0; like < < , the photovoltaic and battery groups discharge the load together. , is 0; like < , the photovoltaic, battery and grid jointly discharge the load. .

5. The charging and discharging method of the energy storage system according to claim 4, characterized in that: The electricity price information includes electricity consumption time periods, and the electricity consumption time periods include electricity price peak period, electricity price valley period and electricity price flat period; If the electricity consumption time period is a peak electricity price period, the battery pack is discharged; If the electricity consumption time period is a low electricity price period, the battery pack is charged; If the electricity consumption time period is a flat electricity price period and the power grid price is greater than the battery pack price, the battery pack is discharged; If the electricity consumption time period is a flat electricity price period and the power grid electricity price is less than the battery pack electricity price, the battery pack is charged.

6. The charging and discharging method of the energy storage system according to claim 5, characterized in that: Acquire the conversion efficiency of the PCS component, the PCS component includes a first PCS and a second PCS, the first PCS is connected to the power grid and the battery pack, and the second PCS is connected to the battery pack and the load; based on the conversion efficiency of the first PCS, the power of the power grid is calculated. The battery pack charging and discharging power is modified based on the conversion efficiency of the second PCS. and / or photovoltaic power generation Make corrections.

7. The charging and discharging method of the energy storage system according to claim 6, characterized in that: Based on PID control of the charge and discharge power of the battery pack, the change in load power is obtained in real time, and the charge and discharge power of the battery pack is adjusted in real time based on the change in load power.

8. The charging and discharging method of the energy storage system according to claim 7, characterized in that: The battery life and charging efficiency of the battery pack are acquired to correct the charging and discharging power of the battery pack and the battery energy of the battery pack.

9. An energy storage system, characterized in that: It comprises a battery pack, a PCS component and an EMS, and the EMS is used to implement the charging and discharging method of the energy storage system as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program data, and the program data can be executed by a processor to implement the charging and discharging method of the energy storage system according to any one of claims 1 to 8.

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