CN117081219A - EMS energy storage energy management system - Google Patents
EMS energy storage energy management system Download PDFInfo
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- CN117081219A CN117081219A CN202311336759.2A CN202311336759A CN117081219A CN 117081219 A CN117081219 A CN 117081219A CN 202311336759 A CN202311336759 A CN 202311336759A CN 117081219 A CN117081219 A CN 117081219A
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- 238000004146 energy storage Methods 0.000 title claims abstract description 69
- 238000005457 optimization Methods 0.000 claims abstract description 58
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- 238000012544 monitoring process Methods 0.000 claims abstract description 20
- 230000007613 environmental effect Effects 0.000 claims abstract description 14
- 238000012423 maintenance Methods 0.000 claims abstract description 11
- 230000008569 process Effects 0.000 claims description 14
- 238000007599 discharging Methods 0.000 claims description 13
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- 238000007781 pre-processing Methods 0.000 claims description 3
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Classifications
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- 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
- H02J7/0013—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries acting upon several batteries simultaneously or sequentially
- H02J7/0014—Circuits for equalisation of charge between batteries
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- 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]
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- 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
- H02J7/007—Regulation of charging or discharging current or voltage
- H02J7/0071—Regulation of charging or discharging current or voltage with a programmable schedule
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- 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
- H02J7/007—Regulation of charging or discharging current or voltage
- H02J7/007188—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters
- H02J7/007192—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters in response to temperature
- H02J7/007194—Regulation of charging or discharging current or voltage the charge cycle being controlled or terminated in response to non-electric parameters in response to temperature of the battery
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- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The application relates to the technical field of energy storage management, and particularly discloses an EMS energy storage energy management system which comprises an energy storage equipment information collection module, an equalization strategy module, an energy management module, a control and execution module and an upgrading maintenance module; according to the application, an equalization strategy is designed according to the battery type, system requirements, performance targets and environmental factors of the energy storage device, an equalization method and trigger conditions are used for equalizing the charge duration and energy loss, an energy loss monitoring model is established through an energy management module for monitoring the energy loss value, and a gradient descent optimization model is used for finding out the optimal charge curve and charge multiplying power meeting the optimization targets, so that the service life of the energy storage device is prolonged.
Description
Technical Field
The application relates to the technical field of energy storage management, in particular to an EMS energy storage energy management system.
Background
When the intelligent power grid cannot stably run due to the influence of external factors, the problem can be effectively solved by adding the energy storage management equipment, the maximum energy utilization rate of the energy storage management equipment is realized through battery management, and when the energy balance of the battery is researched, the two angles of the balance speed and the energy loss are considered, and the research discovers that the balance speed is high, the balance effect is poor, and more energy is lost in the charging process; in order to solve the above problems, an in-depth study is needed to solve the problem of the allocation between the equalizing charge duration and the energy loss.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, the present application provides an EMS energy storage energy management system, which designs an equalization strategy according to a battery type, a system requirement, a performance target and an environmental factor of an energy storage device, equalizes a charge duration and an energy loss by using an optimization algorithm according to an equalization method and a trigger condition, monitors an energy loss value by using an energy loss monitoring model established by an energy management module, finds an optimal charge curve and a charge multiplying power meeting the optimization target by using a gradient descent optimization model, and can improve the service life of the energy storage device, reduce the energy loss, improve the stability of the energy storage system, and facilitate upgrade and maintenance, so as to solve the problems set forth in the background art.
In order to achieve the above purpose, the present application provides the following technical solutions:
the utility model provides an EMS energy storage energy management system, includes energy storage equipment information collection module, balanced tactics module, energy management module, control and execution module and upgrades maintenance module, and balanced tactics module designs balanced tactics according to energy storage equipment's battery type, system demand, performance target and environmental factor, and the specific step that balanced tactics were formulated is:
step one, setting an equalization target: equalization objectives include maximizing battery life, maximizing system efficiency, and minimizing energy loss;
step two, selecting an equalization method: selecting an equalization method according to an equalization target, wherein the equalization method comprises active equalization, passive equalization and mixed equalization;
setting an equilibrium triggering condition: setting a voltage difference threshold trigger based on the voltage difference, and setting a battery state of charge threshold trigger based on the battery state of charge;
fourth, constructing an equilibrium control algorithm: according to the equalization method and the triggering condition, equalizing the charge duration and the energy loss by using an optimization algorithm;
step five, strategy adjustment: and adjusting the balancing strategy according to the real-time requirements and the load of the system.
As a further scheme of the application, a equalization control algorithm is constructed in the fourth step, and according to an equalization method and trigger conditions, the charge duration and the energy loss are equalized by using an optimization algorithm, and the specific steps of equalizing the charge duration and the energy loss by using the optimization algorithm are as follows:
step Q1, setting an objective function: defining objective function by integrating charging duration and energy lossWherein the objective function->The formula of (2) is:
；
wherein:for equalizing the coefficient of the charge duration, +.>To equalize the coefficients of energy loss, +.>For the charging period +.>Is the energy loss;
step Q2, introducing constraint conditions: constraint conditions of charging duration and energy loss are introduced to ensure that the equalization strategy does not exceed the limit while meeting the performance requirement, and the constraint conditions are as follows:
；
；
wherein:is the maximum allowable value of energy loss, < ->The maximum allowable value of the charging duration is set;
step Q3, equalization optimization: constructing an equalization optimization model by combining the objective function and the constraint condition, wherein the formula of the equalization optimization model is as follows:
；
wherein:is a trade-off between charge duration and energy loss.
As a further scheme of the application, each module has the following functions:
the energy storage device information collection module is used for collecting real-time data of the energy storage device, including voltage, current, battery type, system demand, performance targets and environmental factors, and transmitting the data to the data processing module;
the data processing module is used for preprocessing, extracting features and analyzing the acquired data and providing data support for the equalization strategy and the energy management strategy;
the equalization strategy module designs an equalization strategy according to the battery type, the system requirement, the performance target and the environmental factors of the energy storage device;
the energy management module is used for establishing an energy loss monitoring model to monitor an energy loss value, and finding out an optimal charging curve and charging multiplying power meeting an optimization target by using a gradient descent optimization model;
the control and execution module is used for controlling the energy storage equipment in real time according to the equalization strategy module and the energy management module, and comprises charging control and discharging control;
the upgrade maintenance module is used for periodically maintaining and upgrading the EMS energy storage energy management system.
Performance objectives include maximizing system efficiency, maximizing battery life, and minimizing energy loss, where maximizing system efficiency refers to the proportion of useful energy output given input energy, and where the formula for maximizing system efficiency is expressed as: system efficiency = (useful output energy/input energy) x100%; maximizing battery life is achieved by limiting the battery's charge and discharge rate, reducing the battery's heat loss and chemical stress, thereby extending the battery's life or limiting the battery's deep charge and discharge to reduce the capacity loss in each cycle; minimizing energy loss is related to charge-discharge efficiency of the battery and system loss, and methods for reducing energy loss are as follows: (1) improving the charge and discharge efficiency of the battery: by optimizing the charging and discharging strategy, the energy loss in the battery is reduced; (2) reducing system losses: by selecting efficient electronic components and circuit designs, energy loss in the system is reduced; dynamically adjusting a charging and discharging strategy: the charge and discharge strategy is adjusted to minimize losses based on real-time conditions, including temperature, battery status, and load requirements.
As a further scheme of the application, the energy management module is used for establishing an energy loss monitoring model to monitor an energy loss value, wherein monitoring indexes of the energy loss monitoring model comprise battery internal resistance, battery temperature, charging efficiency, discharging efficiency, battery charge and discharge cycle times and duration of a charging process, and a formula of the energy loss monitoring model is as follows:
；
wherein:for internal resistance of battery->For the battery temperature +.>For charging efficiency, +.>For discharging efficiency>For the number of charge and discharge cycles of the battery, < > for>For the duration of the charging process.
As a further scheme of the application, the energy management module uses the gradient descent optimization model to find the optimal charging curve and the optimal charging multiplying power meeting the optimization target, and the specific steps are as follows:
r1, establishing a connection model based on a gradient descent optimization model, and connecting a charging curve and a charging multiplying power with an optimization target, wherein the connection model has the following formula:
；
；
wherein:for optimization purposes, < >>For the total time of the charging process, +.>For the charging curve +.>For charging multiplying power->For the energy loss function at a given charging curve and charging rate +.>As a function of the energy loss rate, the energy loss rate per unit time given a charging curve and a charging rate is expressed,/->Is the time step;
and R2, differentiating the optimized objective function to calculate the gradient relative to the charging curve and the charging multiplying power:
；
；
；
wherein:as a Lagrangian density function, +.>In order to be a lagrange multiplier,for constraint function->For Lagrangian density function relative to +.>Variation of->Is relative to->Variation of derivative of>Is->Derivative with respect to time, < >>Relative to Lagrangian density functionVariation of->Is relative to->Variation of derivative of>Is->Derivative with respect to time;
r3, solving the Lagrangian density function equation to obtain a charging curveAnd charging multiplying power->And (3) solving a differential equation by using a normal differential equation solver to find an optimal charging curve and charging multiplying power.
As a further scheme of the application, the energy storage equipment information collection module is connected with the balance strategy module, the balance strategy module is connected with the energy management module, the energy management module is connected with the control and execution module, and the control and execution module is connected with the upgrade maintenance module.
The application discloses a technical effect and advantages of an EMS energy storage energy management system, which are as follows:
1. by balancing the charging duration and the energy loss, the application can reduce the inconsistency of the battery pack, improve the performance and the service life of the energy storage equipment, reduce the energy loss of the energy storage equipment in the charging process and improve the efficiency of the energy storage system;
2. according to the application, an energy loss monitoring model is established through an energy management module, an energy loss value is monitored, and an optimal charging curve and charging multiplying power meeting an optimization target are found through a gradient descent optimization model, so that the energy loss is reduced;
3. according to the application, the gradient descent optimization model is used to accurately find the optimal charging curve and charging multiplying power meeting the optimization target, so that the optimal management of the energy storage equipment is realized.
Drawings
Fig. 1 is a schematic structural diagram of an EMS stored energy management system according to the present application.
Detailed Description
The technical solutions of the present embodiment will be clearly and completely described below with reference to the drawings in the embodiment of the present application, and it is apparent that the described embodiment is only a part of the embodiment of the present application, not all the embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Example 1
The utility model provides an EMS energy storage energy management system, includes energy storage equipment information collection module, balanced tactics module, energy management module, control and execution module and upgrades maintenance module, and balanced tactics module designs balanced tactics according to energy storage equipment's battery type, system demand, performance target and environmental factor, and the specific step that balanced tactics were formulated is:
step one, setting an equalization target: equalization objectives include maximizing battery life, maximizing system efficiency, and minimizing energy loss;
step two, selecting an equalization method: selecting an equalization method according to an equalization target, wherein the equalization method comprises active equalization, passive equalization and mixed equalization;
maximizing battery life uses passive equalization: the voltage is balanced through the passive balancing circuit in the battery, and the extra energy loss of the battery in the balancing process is reduced. The system efficiency is maximized, and the voltage difference between the batteries can be controlled more accurately by using active equalization through an external circuit or an electronic control unit, so that the energy loss in the batteries is reduced, and the system efficiency is improved; minimizing energy loss hybrid equalization is used: the hybrid equalization method combines the advantages of active and passive equalization to balance the equalization speed and energy loss, with active equalization when needed and passive equalization when not needed.
Setting an equilibrium triggering condition: setting a voltage difference threshold trigger based on the voltage difference, and setting a battery state of charge threshold trigger based on the battery state of charge;
triggering a trigger voltage difference threshold when the voltage difference between the battery cells or modules exceeds a preset threshold, setting the voltage difference threshold to be 5 millivolts, and starting the trigger voltage difference threshold when the voltage difference between the two battery cells exceeds 5 mV; the triggering condition based on the battery state of charge is to trigger the equalization operation according to the state of charge of the battery cells, when the difference of the battery states of charge between the battery cells exceeds a threshold value, the triggering of the battery state of charge threshold value is started, when the difference of the battery states of charge threshold value is 1%, the SOC difference between the two battery cells exceeds 1%, and the triggering of the battery state of charge threshold value is started.
Fourth, constructing an equilibrium control algorithm: according to the equalization method and the triggering condition, equalizing the charge duration and the energy loss by using an optimization algorithm;
step five, strategy adjustment: and adjusting the balancing strategy according to the real-time requirements and the load of the system.
In the embodiment of the application, a equalization control algorithm is constructed in the fourth step, and according to an equalization method and a triggering condition, the charge duration and the energy loss are equalized by using an optimization algorithm, and the specific steps of equalizing the charge duration and the energy loss by using the optimization algorithm are as follows:
step Q1, setting an objective function: defining objective function by integrating charging duration and energy lossWherein the objective function->The formula of (2) is:
；
wherein:for equalizing the coefficient of the charge duration, +.>To equalize the coefficients of energy loss, +.>For the charging period +.>Is the energy loss;
step Q2, introducing constraint conditions: constraint conditions of charging duration and energy loss are introduced to ensure that the equalization strategy does not exceed the limit while meeting the performance requirement, and the constraint conditions are as follows:
；
；
wherein:is the maximum allowable value of energy loss, < ->The maximum allowable value of the charging duration is set;
step Q3, equalization optimization: constructing an equalization optimization model by combining the objective function and the constraint condition, wherein the formula of the equalization optimization model is as follows:
；
wherein:is a trade-off between charge duration and energy loss.
The conditional inequality is embedded in an optimization algorithm to meet given performance objectives and constraints to achieve an optimal tradeoff between equalizing charge duration and energy loss.
The method has the advantages that the inconsistency of the battery pack can be reduced through equalizing the charging duration and the energy loss, the performance and the service life of the energy storage device are improved, the energy loss of the energy storage device in the charging process is reduced through equalizing the charging duration and the energy loss by an optimization algorithm, the efficiency of the energy storage system is improved, and the equalization strategy is adaptively adjusted according to the battery type, the system requirement, the performance target and the environmental factors of the energy storage device, so that the optimal management of the energy storage device can be realized under various conditions.
In the embodiment of the application, each module has the following functions:
the energy storage device information collection module is used for collecting real-time data of the energy storage device, including voltage, current, battery type, system demand, performance targets and environmental factors, and transmitting the data to the data processing module;
the data processing module is used for preprocessing, extracting features and analyzing the acquired data and providing data support for the equalization strategy and the energy management strategy;
the equalization strategy module designs an equalization strategy according to the battery type, the system requirement, the performance target and the environmental factors of the energy storage device;
the energy management module is used for establishing an energy loss monitoring model to monitor an energy loss value, and finding out an optimal charging curve and charging multiplying power meeting an optimization target by using a gradient descent optimization model;
the control and execution module is used for controlling the energy storage equipment in real time according to the equalization strategy module and the energy management module, and comprises charging control and discharging control;
the upgrade maintenance module is used for periodically maintaining and upgrading the EMS energy storage energy management system.
The equalization strategy module is used for controlling the battery type, the system requirement, the performance target and the environmental factors of the energy storage device, wherein the battery type comprises a lithium ion battery, a lead-acid battery and a nickel-hydrogen battery;
the system requirement refers to the performance requirement of the energy storage system in a specific application scene, such as the power system needs high power output and quick response, so that more frequent voltage equalization is needed, and the electric automobile needs to prolong the service life of the battery, so that the voltage equalization is more focused on the maximization of the service life of the battery;
performance objectives include maximizing system efficiency, maximizing battery life, and minimizing energy loss, where maximizing system efficiency refers to the proportion of useful energy output given input energy, and where the formula for maximizing system efficiency is expressed as: system efficiency = (useful output energy/input energy) x100%; maximizing battery life is achieved by limiting the battery's charge and discharge rate, reducing the battery's heat loss and chemical stress, thereby extending the battery's life or limiting the battery's deep charge and discharge to reduce the capacity loss in each cycle; minimizing energy loss is related to charge-discharge efficiency of the battery and system loss, and methods for reducing energy loss are as follows: (1) improving the charge and discharge efficiency of the battery: by optimizing the charging and discharging strategy, the energy loss in the battery is reduced; (2) reducing system losses: by selecting efficient electronic components and circuit designs, energy loss in the system is reduced; dynamically adjusting a charging and discharging strategy: the charge and discharge strategy is adjusted to minimize losses based on real-time conditions, including temperature, battery status, and load requirements.
In the embodiment of the application, the energy management module is used for establishing an energy loss monitoring model to monitor the energy loss value, and the monitoring indexes of the energy loss monitoring model comprise the internal resistance of a battery, the temperature of the battery, the charging efficiency, the discharging efficiency, the number of charge and discharge cycles of the battery and the duration of the charging process, and the formula of the energy loss monitoring model is as follows:
；
wherein:for internal resistance of battery->For the battery temperature +.>For charging efficiency, +.>For discharging efficiency>For the number of charge and discharge cycles of the battery, < > for>For the duration of the charging process.
In the embodiment of the application, the specific steps of using the gradient descent optimization model to find the optimal charging curve and the optimal charging multiplying power meeting the optimization target by the energy management module are as follows:
r1, establishing a connection model based on a gradient descent optimization model, and connecting a charging curve and a charging multiplying power with an optimization target, wherein the connection model has the following formula:
；
；
wherein:for optimization purposes, < >>For the total time of the charging process, +.>For the charging curve +.>For charging multiplying power->For the energy loss function at a given charging curve and charging rate +.>As a function of the energy loss rate, the energy loss rate per unit time given a charging curve and a charging rate is expressed,/->Is the time step;
and R2, differentiating the optimized objective function to calculate the gradient relative to the charging curve and the charging multiplying power:
；
；
；
wherein:as a Lagrangian density function, +.>In order to be a lagrange multiplier,for constraint function->For Lagrangian density function relative to +.>Variation of->Is relative to->Variation of derivative of>Is->Derivative with respect to time, < >>Relative to Lagrangian density functionVariation of->Is relative to->Variation of derivative of>Is->Derivative with respect to time;
r3, solving the Lagrangian density function equation to obtain a charging curveAnd charging multiplying power->And (3) solving a differential equation by using a normal differential equation solver to find an optimal charging curve and charging multiplying power.
By using the gradient descent optimization model, the optimal charging curve and the optimal charging multiplying power which meet the optimization target are accurately found, so that the optimization management of the energy storage device is realized, the gradient descent optimization model has stronger robustness, various external interferences and system errors can be dealt with, the stability and the reliability of the energy storage system are maintained, and the dynamic adjustment and the optimization of the energy storage system are realized.
In the embodiment of the application, the energy storage equipment information collection module is connected with the balance strategy module, the balance strategy module is connected with the energy management module, the energy management module is connected with the control and execution module, and the control and execution module is connected with the upgrade maintenance module.
According to the embodiment of the application, an equalization strategy is designed according to the battery type, the system demand, the performance target and the environmental factors of the energy storage device, and the charge duration and the energy loss are equalized by using an optimization algorithm according to an equalization method and a triggering condition, so that the inconsistency of a battery pack can be reduced, the performance and the service life of the energy storage device are improved, the energy loss of the energy storage device in the charge process is reduced, and the efficiency of an energy storage system is improved; an energy loss monitoring model is established through an energy management module to monitor an energy loss value, the energy loss value is monitored, and an optimal charging curve and charging multiplying power meeting an optimization target are found through a gradient descent optimization model, so that energy loss is reduced; the gradient descent optimization model is used for finding out the optimal charging curve and the optimal charging multiplying power which meet the optimization target, and the optimal charging curve and the optimal charging multiplying power which meet the optimization target are accurately found out, so that the optimal management of the energy storage equipment is realized, the service life of the energy storage equipment is prolonged, the energy loss is reduced, the stability of the energy storage system is improved, and the energy storage system is convenient to upgrade and maintain.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (5)
1. The energy storage energy management system of EMS, including energy storage equipment information collection module, balanced tactics module, energy management module, control and execution module and upgrade maintenance module, its characterized in that, balanced tactics module designs balanced tactics according to battery type, system demand, performance target and environmental factor of energy storage equipment, and the concrete step that balanced tactics were formulated is:
step one, setting an equalization target: equalization objectives include maximizing battery life, maximizing system efficiency, and minimizing energy loss;
step two, selecting an equalization method: selecting an equalization method according to an equalization target, wherein the equalization method comprises active equalization, passive equalization and mixed equalization;
setting an equilibrium triggering condition: setting a voltage difference threshold trigger based on the voltage difference, and setting a battery state of charge threshold trigger based on the battery state of charge;
fourth, constructing an equilibrium control algorithm: according to the equalizing method and the triggering condition, equalizing the charge duration and the energy loss by using an optimizing algorithm, wherein the equalizing the charge duration and the energy loss by using the optimizing algorithm comprises the following specific steps:
step Q1, setting an objective function: defining objective function by integrating charging duration and energy lossWherein the objective function->The formula of (2) is:
；
wherein:for equalizing the coefficient of the charge duration, +.>To equalize the coefficients of energy loss, +.>For the charging period +.>Is the energy loss;
step Q2, introducing constraint conditions: constraint conditions of charging duration and energy loss are introduced to ensure that the equalization strategy does not exceed the limit while meeting the performance requirement, and the constraint conditions are as follows:
；
；
wherein:is the maximum allowable value of energy loss, < ->The maximum allowable value of the charging duration is set;
step Q3, equalization optimization: constructing an equalization optimization model by combining the objective function and the constraint condition, wherein the formula of the equalization optimization model is as follows:
；
wherein:a trade-off coefficient between charge duration and energy loss;
step five, strategy adjustment: and adjusting the balancing strategy according to the real-time requirements and the load of the system.
2. The EMS energy storage energy management system of claim 1, wherein the energy storage device information collection module is configured to collect real-time data of the energy storage device, including voltage, current, battery type, system requirements, performance goals, and environmental factors, and to transmit the data to the data processing module;
the data processing module is used for preprocessing, extracting features and analyzing the acquired data and providing data support for the equalization strategy and the energy management strategy;
the equalization strategy module designs an equalization strategy according to the battery type, the system requirement, the performance target and the environmental factors of the energy storage device;
the energy management module is used for establishing an energy loss monitoring model to monitor an energy loss value, and finding out an optimal charging curve and charging multiplying power meeting an optimization target by using a gradient descent optimization model;
the control and execution module is used for controlling the energy storage equipment in real time according to the equalization strategy module and the energy management module, and comprises charging control and discharging control;
the upgrade maintenance module is used for periodically maintaining and upgrading the EMS energy storage energy management system.
3. The EMS energy storage energy management system of claim 1, wherein the energy management module is configured to establish an energy loss monitoring model to monitor an energy loss value, the monitoring indicators of the energy loss monitoring model include a battery internal resistance, a battery temperature, a charging efficiency, a discharging efficiency, a battery charge-discharge cycle number, and a charging process duration, and the formula of the energy loss monitoring model is as follows:
；
wherein:for internal resistance of battery->For the battery temperature +.>For charging efficiency, +.>For discharging efficiency>For the number of charge and discharge cycles of the battery, < > for>For the duration of the charging process.
4. The EMS energy storage energy management system of claim 1, wherein the energy management module finds an optimal charging curve and charging rate that meet the optimization objective using a gradient descent optimization model by:
r1, establishing a connection model based on a gradient descent optimization model, and connecting a charging curve and a charging multiplying power with an optimization target, wherein the connection model has the following formula:
；
；
wherein:for optimization purposes, < >>For the total time of the charging process, +.>For the charging curve +.>In order to achieve the charging rate,for the energy loss function at a given charging curve and charging rate +.>As a function of the energy loss rate, the energy loss rate per unit time given a charging curve and a charging rate is expressed,/->Is the time step;
and R2, differentiating the optimized objective function to calculate the gradient relative to the charging curve and the charging multiplying power:
；
；
；
wherein:as a Lagrangian density function, +.>In order to be a lagrange multiplier,for constraint function->For Lagrangian density function relative to +.>Variation of->Is relative to->Variation of derivative of>Is->Derivative with respect to time, < >>Relative to Lagrangian density functionVariation of->Is relative to->Variation of derivative of>Is->Derivative with respect to time;
r3, solving the Lagrangian density function equation to obtain a charging curveAnd charging multiplying power->And (3) solving a differential equation by using a normal differential equation solver to find an optimal charging curve and charging multiplying power.
5. The EMS energy storage energy management system of claim 1, wherein the energy storage device information collection module is coupled to an equalization policy module, the equalization policy module is coupled to an energy management module, the energy management module is coupled to a control and execution module, and the control and execution module is coupled to an upgrade maintenance module.
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Citations (9)
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