CN116231706A - Energy storage unit power distribution method and system - Google Patents
Energy storage unit power distribution method and system Download PDFInfo
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- CN116231706A CN116231706A CN202310036694.3A CN202310036694A CN116231706A CN 116231706 A CN116231706 A CN 116231706A CN 202310036694 A CN202310036694 A CN 202310036694A CN 116231706 A CN116231706 A CN 116231706A
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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
- 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
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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Abstract
The invention discloses a method and a system for distributing power of an energy storage unit, comprising the following steps: sequentially acquiring battery characteristics corresponding to energy storage units of an energy storage power station; calculating the charging capacity and discharging capacity of each energy storage unit according to the battery characteristics; judging the state of each energy storage unit according to the total power, if the state of each energy storage unit is a charging state, calculating the charging capacity of each energy storage unit, and establishing a charging power loss optimization model; iteratively solving the charging power loss optimization model until the charging power distribution factors of the energy storage units meet the respective corresponding charging power constraint conditions and total charging power distribution weight constraint conditions, stopping iteration, and outputting the first charging power distribution factors of the energy storage units; and according to the first charging power distribution factor, sequentially updating the first charge state of each energy storage unit, and distributing charging power for each energy storage unit. The invention can reduce the power loss of the energy storage system, prolong the service life of the energy storage battery and improve the performance of the energy storage unit.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a power distribution method of an energy storage unit.
Background
Although the new energy is connected into the power grid, the energy supply is increased, the energy structure is improved to a certain extent, and the environmental pollution problem is relieved to a certain extent. However, in actual operation, the grid itself needs to meet the real-time balance of power generation and load power at all times during operation. The output of the new energy is mainly determined by external weather conditions, the generated power shows strong fluctuation, the fluctuation of the output of the new energy generating equipment can also cause sudden voltage rise/drop or voltage flicker at the grid-connected point, adverse effects are generated on the power quality of the power grid, and the running reliability of the power grid is reduced.
Through quick energy storage and release of electric energy, the energy storage power station not only can participate in peak clipping and valley filling of a system and stabilize new energy power generation fluctuation, but also plays an important role in improving new energy power generation income, delaying power grid construction and upgrading and the like. The gradually improved energy storage power station has become a novel, complex-function and operable and independent economic entity in the modern new energy power generation system, and the business model also shows a gradually clear development prospect.
The energy storage power station has different technical requirements and different economic benefits when being applied to different scenes, the control strategy of the energy storage system is used as a core link of energy storage planning, factors such as an application scene, an application mode, environment, economy and the like need to be comprehensively considered, and the indexes of the control strategy relate to two aspects of application scene/energy storage ontology technology, such as diversity and irreducibility, and the mixing of original information and a large number of subjective factors. As a commodity, several energy storage technologies with higher development maturity are presented with short plate bureaus, and economic cost is high, and the development of the maturity of the energy storage technology to 'high safety, low cost and long service life' is still not carried out, so that the energy storage technology enters a commercial popularization stage. Under the development background, the energy storage control strategy has gradually become a factor to be considered in the power station construction process, and analysis and research on the control strategies under different application scenes and control targets are needed.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a power distribution method of an energy storage unit, which aims to reduce power loss during charging of the energy storage unit, improve the charging capacity of each energy storage unit and prolong the service life of an energy storage battery.
In a first aspect, the present invention provides a method for distributing power of an energy storage unit, the method comprising:
sequentially acquiring battery characteristics corresponding to energy storage units of an energy storage power station; the battery characteristics comprise a first charge state of charging of each energy storage unit, a second charge state of discharging of each energy storage unit, rated power of each energy storage unit and total electric power of superior scheduling;
calculating the charging capacity and discharging capacity of each energy storage unit according to the battery characteristics;
judging the state of each energy storage unit according to the total power, if the state of each energy storage unit is a charging state, calculating the charging capacity of each energy storage unit, and establishing a charging power loss optimization model;
iteratively solving the charging power loss optimization model to obtain the charging power distribution factor of each energy storage unit until the charging power distribution factor of each energy storage unit meets the respective corresponding charging power constraint condition and total charging power distribution weight constraint condition, stopping iteration, and outputting the first charging power distribution factor of each energy storage unit; updating parameters of the charging power loss optimization model during each iteration;
Sequentially updating the first charge states of the energy storage units according to the first charge power distribution factors;
and distributing charging power for each energy storage unit by using the first charging power distribution factor.
According to the invention, the influence of the battery characteristics of the energy storage units on the distribution of the charging power is comprehensively considered in the charging state of each energy storage unit, a model which aims at minimum charging power loss is built for the energy storage units in the charging state, and the feasible solution that the charging power distribution factor meets the charging power constraint and the total charging power distribution weight constraint is solved, so that the power loss of each energy storage unit in the charging state can be reduced, the energy storage charging capacity of each energy storage unit is improved, the charging performance of an energy storage system is improved, and the service life of an energy storage battery is prolonged.
Further, the determining the state of each energy storage unit according to the total power further includes:
judging the state of each energy storage unit according to the total power, and if the state of each energy storage unit is a discharge state, establishing a discharge power loss optimization model according to the discharge capacity of each energy storage unit;
iteratively solving the discharge power loss optimization model to obtain a discharge power distribution factor of each energy storage unit until the discharge power distribution factor of each energy storage unit meets a respective corresponding discharge power constraint condition and a total discharge power distribution weight constraint condition, stopping iteration, and outputting a first discharge power distribution factor of each energy storage unit; wherein, during each iteration, the parameters of the discharge power loss optimization model are updated;
Sequentially updating the first charge states of the energy storage units according to the first discharge power distribution factors;
and carrying out discharge power distribution by taking the first discharge power distribution factor as each energy storage unit.
In the invention, the influence of the battery characteristics of the energy storage units on the discharge power distribution is comprehensively considered in the discharge state, a model which aims at the minimum discharge power loss is built for the energy storage units in the discharge state, and the feasible solution that the discharge power distribution factor meets the discharge power constraint and the total discharge power distribution weight constraint is solved, so that the power loss of each energy storage unit in the discharge state can be reduced, the energy storage and discharge capacity of each energy storage unit is improved, the discharge performance of the energy storage system is improved, and the service life of the energy storage battery is prolonged.
Further, the determining the state of each energy storage unit according to the total power includes:
if the total power is greater than a charge-discharge threshold, determining that the states of the energy storage units are all charge states; otherwise, determining that the states of the energy storage units are all discharge states.
Still further, the calculating the charging capability and discharging capability of each energy storage unit according to the battery characteristics specifically includes:
And according to the battery characteristics, respectively calculating the charging factors of the energy storage units, and taking the minimum value of the rated power and the charging factors of the energy storage units as the charging capacity of the energy storage units.
The invention takes the minimum value of the charging capacity of each energy storage unit as the charging capacity, and the charging capacity of each energy storage unit does not exceed the power range of each energy storage unit, so that the situation that the charging capacity of each energy storage unit is calculated to be larger than the allowable power range of each energy storage unit can be prevented.
Further, the energy storage unit power distribution method further comprises the following steps:
and according to the battery characteristics, respectively calculating the discharge factors of the energy storage units, and taking the opposite number of the rated power of each energy storage unit and the maximum value of the discharge factors as the discharge capacity of each energy storage unit.
The invention takes the maximum value of the discharge capacity of each energy storage unit as the discharge capacity and the respective power and the discharge factor of each energy storage unit as the discharge capacity, the discharge capacity of each energy storage unit does not exceed the power range of each energy storage unit, and the invention can prevent the situation that the discharge factor of each energy storage unit is smaller than the allowable power range of each energy storage unit after the discharge factor of each energy storage unit is directly calculated.
Still further, the specific steps until the charging power distribution factor of each energy storage unit meets the respective corresponding charging power constraint condition and total charging power distribution weight constraint condition are as follows:
according to the respective charging power distribution factors and the total power of the energy storage units, calculating to obtain a charging power distribution result of each energy storage unit;
when the charging power distribution result of each energy storage unit is smaller than or equal to the charging capacity of each energy storage unit and is larger than or equal to 0, determining that the respective corresponding charging power constraint conditions are met;
and when the sum of the charging power distribution factors of all the energy storage units is 1, determining that the total charging power distribution weight constraint is met.
According to the invention, the charging power distribution factors which are solved are adopted to carry out the restriction of the charging power distribution weight and the restriction of the total charging power distribution weight, only the charging power distribution factors which simultaneously meet the restriction of the charging power and the restriction of the total charging power distribution weight are the final solving result, and the accurate feasible solution can be obtained after solving for many times, so that the charging power loss is reduced, and the charging capacity of the energy storage system is improved.
Still further, the specific steps until the discharge power distribution factor of each energy storage unit meets the respective corresponding discharge power constraint condition and total discharge power distribution weight constraint condition are as follows:
According to the respective discharge power distribution factors and the total power of the energy storage units, calculating to obtain a discharge power distribution result of each energy storage unit;
when the discharge power distribution result of each energy storage unit is smaller than or equal to 0 and is larger than or equal to the discharge capacity of each energy storage unit, determining that the corresponding discharge power constraint conditions are met;
and when the sum of the discharge power distribution factors of all the energy storage units is 1, determining that the total discharge power distribution weight constraint is met.
According to the invention, the solved discharge power distribution factors are subjected to discharge power constraint and total discharge power distribution weight constraint limitation, only the discharge power distribution factors which simultaneously meet the discharge power constraint and the total discharge power distribution weight constraint are the final solving result, and after multiple solving, the accurate feasible solution can be obtained, the discharge power loss is reduced, and thus the overall discharge capacity of the energy storage system is improved.
Still further, according to the charging capability of each energy storage unit, a charging power loss optimization model is established, and the calculation formula of the charging power loss optimization model is as follows:
wherein N is the number of the energy storage units, 
For the charging efficiency of the ith energy storage cell, < >>
For the charging power distribution factor of the ith energy storage unit, P (t) is the total electric power of the upper schedule, delta t is the sampling time interval, +.>
Is the charging capacity of the ith energy storage unit.
Then, according to the discharging capability of each energy storage unit, a discharging power loss optimization model is established, and the calculating formula of the discharging power loss optimization model is as follows:
wherein N is the number of the energy storage units,
for the discharge efficiency of the ith energy storage cell, < >>
For the discharge power distribution factor of the ith energy storage unit, P (t) is the total electric power of the upper schedule, deltat is the sampling time interval, +.>
Is the discharge capacity of the ith energy storage cell.
In a second aspect, the present invention also provides an energy storage unit power distribution system, including:
the battery characteristic acquisition module is used for sequentially acquiring battery characteristics corresponding to each energy storage unit of the energy storage power station; the battery characteristics comprise a first charge state of charging of each energy storage unit, a second charge state of discharging of each energy storage unit, rated power of each energy storage unit and total electric power of superior scheduling;
the charge and discharge capacity calculation module is used for calculating the charge capacity and discharge capacity of each energy storage unit according to the battery characteristics;
The charging power loss optimization model construction module is used for judging the state of each energy storage unit according to the total power, if the state of each energy storage unit is a charging state, calculating the charging capacity of each energy storage unit, and building a charging power loss optimization model;
the charging power calculation module is used for iteratively solving the charging power loss optimization model to obtain the charging power distribution factor of each energy storage unit until the charging power distribution factor of each energy storage unit meets the respective corresponding charging power constraint condition and total charging power distribution weight constraint condition, stopping iteration, and outputting the first charging power distribution factor of each energy storage unit; updating parameters of the charging power loss optimization model during each iteration;
the first charge state updating module is used for sequentially updating the first charge states of the energy storage units according to the first charge power distribution factors;
and the charging power distribution module is used for distributing charging power for each energy storage unit by using the first charging power distribution factor.
According to the invention, the influence of the battery characteristics of the energy storage units on the charging power distribution is comprehensively considered by the energy storage unit power distribution system in the charging state, a model which aims at minimum charging power loss is built for the energy storage units in the charging state, and the feasible solution that the charging power distribution factor meets the charging power constraint and the total charging power distribution weight constraint is solved, so that the power loss of each energy storage unit in the charging state can be reduced, the energy storage charging capacity of each energy storage unit is improved, and the charging performance of the energy storage system is improved.
Further, the energy storage unit power distribution system further includes:
the discharging power loss optimization model construction module is used for judging the state of each energy storage unit according to the total power, and if the state of each energy storage unit is a discharging state, a discharging power loss optimization model is built according to the discharging capacity of each energy storage unit;
the discharge power calculation module is used for iteratively solving the discharge power loss optimization model to obtain the discharge power distribution factor of each energy storage unit until the discharge power distribution factor of each energy storage unit meets the respective corresponding discharge power constraint condition and total discharge power distribution weight constraint condition, stopping iteration, and outputting the first discharge power distribution factor of each energy storage unit; wherein, during each iteration, the parameters of the discharge power loss optimization model are updated;
the second charge state updating module is used for sequentially updating the first charge states of the energy storage units according to the first discharge power distribution factors;
and the discharge power distribution module is used for distributing the discharge power by taking the first discharge power distribution factor as each energy storage unit.
The invention also considers not only the charging state, but also the influence of the battery characteristics of the integrated energy storage units on the discharge power distribution of each energy storage unit in the discharging state, establishes a model with the minimum discharge power loss as a target, solves the feasible solution that the discharge power distribution factor meets the discharge power constraint and the total discharge power distribution weight constraint, can reduce the power loss of each energy storage unit in the discharging state, and improves the energy storage and discharge capacity of each energy storage unit, thereby improving the discharge performance of the energy storage system.
Drawings
Fig. 1 is a schematic flow chart of power distribution of an energy storage unit according to an embodiment of the present invention
Fig. 2 is a schematic structural diagram of a power distribution system of an energy storage unit according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flow chart of charging power distribution of an energy storage unit according to an embodiment of the present invention includes steps S100 to S114, specifically:
step S100, sequentially acquiring battery characteristics corresponding to energy storage units of an energy storage power station; the battery characteristics comprise a first charge state of charging of each energy storage unit, a second charge state of discharging of each energy storage unit, rated power of each energy storage unit and total electric power of superior scheduling.
Notably, the rechargeable battery characteristics include a first state of charge of each energy storage unit, a second state of charge of each energy storage unit, and a total electric power of a superordinate schedule, and further include: charge efficiency, discharge efficiency, health status, capacity.
Specifically, the judging the state of each energy storage unit according to the total power includes: if the total power is greater than a charge-discharge threshold, determining that the states of the energy storage units are all charge states; otherwise, determining that the states of the energy storage units are all discharge states.
Step S101, calculating the charging capacity and the discharging capacity of each energy storage unit according to the battery characteristics.
It should be noted that, since the states of charge of the energy storage units at different moments are different, the energy storage units have different charge and discharge characteristics, and the charge capacity of each energy storage unit is related to the rated power, the charge efficiency, the health status, the capacity, etc. of each energy storage unit, and the discharge capacity of each energy storage unit is related to the rated power, the discharge efficiency, the health status, the capacity, etc. of each energy storage unit.
Specifically, the calculation of the charging capability is: and according to the battery characteristics, respectively calculating the charging factors of the energy storage units, and taking the minimum value of the rated power and the charging factors of the energy storage units as the charging capacity of the energy storage units.
Preferably, the charging factor of each energy storage unit may be expressed as:
wherein, the subscript i is the ith energy storage unit, SOH i For the State of health (SOH) of the ith energy storage unit,
for the capacity of the ith energy storage cell, +.>
And SOC (System on chip) i (t) the ith energy storage units respectivelyUpper limit of State of charge (SOC) of charge at time t and State of charge at time t +.>
The charging efficiency of the ith energy storage unit.
Preferably, the charging capability of each energy storage unit may be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
and->
The rated power and the charging factor of the ith energy storage unit respectively.
The discharge capacity was calculated as: and according to the battery characteristics, respectively calculating the discharge factors of the energy storage units, and taking the opposite number of the rated power of each energy storage unit and the maximum value of the discharge factors as the discharge capacity of each energy storage unit.
Preferably, the discharge factor of each energy storage unit may be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
SOH for the capacity of the ith energy storage cell i For the health status of the ith energy storage unit, < >>
And
respectively the lower limit of the discharging state and the discharging efficiency of the ith energy storage unit, and SOC i And (t) is the charge state of the ith energy storage unit at the moment t.
Preferably, the charging capability of each energy storage unit may be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
and->
The rated power and the discharge factor of the ith energy storage unit respectively.
Step S102, judging the state of each energy storage unit according to the total power, judging the state of each energy storage unit to be a charging state, if the state of each energy storage unit is the charging state, proceeding to step S103, otherwise proceeding to step S109.
Specifically, the determining the state of each energy storage unit according to the total power includes: if the total power is greater than a charge-discharge threshold, determining that the states of the energy storage units are all charge states; otherwise, determining that the states of the energy storage units are all discharge states.
It is noted that the charge and discharge states of the energy storage units are determined by the grid-connected power and the new energy power generation power together, if the total power is larger than the charge and discharge threshold value, the discharge capacity of the energy storage units is mainly considered, namely the new energy power generation power is smaller than the grid-connected power, and at the moment, each energy storage unit is required to be used as a power supply to discharge to meet the grid-connected power; otherwise, when the total power is smaller than the charge-discharge threshold, the charging of the energy storage unit is indicated, and the charging capacity is mainly considered, namely the new energy power generation power is smaller than the grid-connected power, and the new energy power generation power is larger than the grid-connected power, so that the energy storage unit is required to be used as a load for charging to reduce resource waste.
Preferably, the charge-discharge threshold value is 0.
And step S103, according to the charging capacity of each energy storage unit, establishing a charging power loss optimization model.
Preferably, the calculation formula of the charging power loss optimization model is as follows:
wherein N is the number of the energy storage units,
for the charging efficiency of the ith energy storage cell, < >>
For the charging power distribution factor of the ith energy storage unit, P (t) is the total electric power of the upper schedule, delta t is the sampling time interval, +.>
Is the charging capacity of the ith energy storage unit.
Step S104, solving the charging power loss optimization model to obtain the charging power distribution factor of each energy storage unit
The charging power loss optimization model is solved iteratively, the charging power distribution factor of each energy storage unit is obtained until the charging power distribution factor of each energy storage unit meets the corresponding charging power constraint condition and the total charging power distribution weight constraint condition, iteration is stopped, and the first charging power distribution factor of each energy storage unit is output; and updating parameters of the charging power loss optimization model during each iteration.
Preferably, the charging power distribution factor of each energy storage unit is solved according to a particle swarm algorithm, and in each iteration process, parameters of the charging power loss optimization model are updated.
Step 105, judging that the charging power distribution factors of the energy storage units meet the respective corresponding charging power constraint conditions.
Specifically, if the charging power distribution factor of each energy storage unit meets the respective corresponding charging power constraint condition, the step S106 is entered, otherwise, the step S103 is entered, and the charging power distribution factor is recalculated according to the charging power loss optimization model.
The charging power constraint condition specifically comprises: according to the respective charging power distribution factors and the total power of the energy storage units, calculating to obtain a charging power distribution result of each energy storage unit; and when the charging power distribution result of each energy storage unit is smaller than or equal to the charging capacity of each energy storage unit and is larger than or equal to 0, determining that the respective corresponding charging power constraint conditions are met.
The charging power distribution result of each energy storage unit can be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
and P (t) is the charging power distribution factor of the ith energy storage unit and the total electric power of the upper level schedule respectively.
The charging power constraint can be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
is the charging power allocation result of the ith energy storage unit,/->
The charging capacity of the ith energy storage unit at the time t.
And S106, judging that the charging power distribution factors of the energy storage units meet the constraint condition of total charging power distribution weight.
Specifically, if the charge power distribution factor of each energy storage unit meets the constraint condition of the total charge power distribution weight, the step S107 is entered, otherwise, the step S103 is entered, and the charge power distribution factor is recalculated according to the charge power loss optimization model.
Wherein when the sum of the charge power distribution factors of all the energy storage units is 1, it is determined that the total charge electric power distribution weight constraint is satisfied, the total charge electric power distribution weight constraint may be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
and N is the charge power distribution factor of the ith energy storage unit and the total number of the energy storage units respectively.
Step S107, according to the first charge power distribution factor, sequentially updating the first charge states of the energy storage units.
It should be noted that, step S107 may also be performed after step S104 and between steps S105, mainly by updating the first state of charge of each energy storage unit according to the charge power distribution factor of each energy storage unit that satisfies the respective corresponding charge power constraint condition and the total charge power distribution weight constraint condition, which is not limited herein.
Preferably, in order to reduce the amount of calculation, the updating of the first state of charge of each energy storage unit is put after an iterative calculation of the charge power distribution factor of each energy storage unit.
Preferably, the updating of the first state of charge of each energy storage unit may be expressed as:
wherein SOC is i (t) and
respectively, the charge state and the charging power distribution result of the ith energy storage unit at the moment t, delta t and delta #>
Sampling time interval and charging efficiency, Q i And SOH i The capacity and health of the ith energy storage unit, respectively.
And S108, distributing charging power for each energy storage unit by using the first charging power distribution factor.
It is noted that each energy storage unit obtains a corresponding charging power distribution result according to the first charging power distribution factor and the total electric power of the upper schedule, and performs power distribution according to the charging power distribution result.
According to the invention, the influence of the battery characteristics of the energy storage units on the distribution of the charging power is comprehensively considered in the charging state of each energy storage unit, a model which aims at the minimum charging power loss is built for the energy storage units in the charging state, and the feasible solution that the charging power distribution factor meets the charging power constraint and the total charging power distribution weight constraint is solved, so that the power loss of each energy storage unit in the charging state can be reduced, the energy storage charging capacity of each energy storage unit is improved, and the charging performance of the energy storage system is improved.
Preferably, the discharge power loss optimization model is calculated as:
wherein N is the number of the energy storage units,
for the discharge efficiency of the ith energy storage cell, < >>
For the discharge power distribution factor of the ith energy storage unit, P (t) is the total electric power of the upper schedule, deltat is the sampling time interval, +.>
Is the discharge capacity of the ith energy storage cell.
And step S110, solving the discharge power loss optimization model to obtain the discharge power distribution factor of each energy storage unit.
The method comprises the steps of solving a discharge power loss optimization model in an iterative mode to obtain a discharge power distribution factor of each energy storage unit until the discharge power distribution factor of each energy storage unit meets a respective corresponding discharge power constraint condition and a total discharge power distribution weight constraint condition, stopping iteration, and outputting a first discharge power distribution factor of each energy storage unit; and updating parameters of the discharge power loss optimization model during each iteration.
Preferably, the discharge power distribution factor of each energy storage unit is solved according to a particle swarm algorithm, and in each iteration process, parameters of the discharge power loss optimization model are updated.
Step 111, the discharge power distribution factor of each energy storage unit meets the respective corresponding discharge power constraint condition.
Specifically, if the discharge power distribution factor of each energy storage unit meets the respective corresponding discharge power constraint condition, the step S112 is entered, otherwise, the step S109 is entered, and the discharge power distribution factor is recalculated according to the discharge power loss optimization model.
The discharge power constraint condition specifically comprises: according to the respective discharge power distribution factors and the total power of the energy storage units, calculating to obtain a discharge power distribution result of each energy storage unit; and when the discharge power distribution result of each energy storage unit is smaller than or equal to 0 and is larger than or equal to the discharge capacity of each energy storage unit, determining that the respective corresponding discharge power constraint conditions are met.
The discharge power distribution result of each energy storage unit can be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
and P (r) is the discharge power distribution factor of the ith energy storage unit and the total electric power of the upper level schedule, respectively.
The discharge power constraint can be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
is the discharge power distribution result of the ith energy storage unit.
And 112, judging that the discharge power distribution factors of the energy storage units meet the constraint condition of total discharge power distribution weight.
Specifically, if the discharge power distribution factor of each energy storage unit meets the total discharge power distribution weight constraint condition, the step S113 is entered, otherwise, the step S109 is entered, and the discharge power distribution factor is recalculated according to the discharge power loss optimization model.
Wherein when the sum of the discharge power distribution factors of all the energy storage units is 1, it is determined that the total discharge electric power distribution weight constraint is satisfied, the total discharge electric power distribution weight constraint may be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
and N is the discharge power distribution factor and the total number of the energy storage units of the ith energy storage unit respectively.
Step S113, updating the second charge states of the energy storage units in turn according to the first discharge power distribution factor.
It should be noted that, step S113 may also be performed after step S110 and between steps S11, mainly by updating the second state of charge of each energy storage unit according to the discharge power distribution factor of each energy storage unit that satisfies the respective corresponding discharge power constraint condition and the total discharge power distribution weight constraint condition, which is not limited herein.
Preferably, in order to reduce the calculation effort, the updating of the second state of charge of the respective energy storage unit is put after an iterative calculation of the discharge power distribution factor of the respective energy storage unit.
Preferably, the updating of the second state of charge of each energy storage unit may be expressed as:
wherein SOC is i (t) and
respectively, the charge state and the discharge power distribution result of the ith energy storage unit at the moment t, delta t and delta +.>
Sampling time interval and discharge efficiency, Q i And SOH i The capacity and health of the ith energy storage unit, respectively.
And step S114, carrying out discharge power distribution by taking the first discharge power distribution factor as each energy storage unit.
It is noted that each energy storage unit obtains a corresponding discharge power distribution result according to the first discharge power distribution factor and the total electric power of the upper scheduling, and performs power distribution according to the discharge power distribution result.
In the invention, the influence of the battery characteristics of the energy storage units on the discharge power distribution is comprehensively considered in the discharge state, a model which aims at the minimum discharge power loss is built for the energy storage units in the discharge state, and the feasible solution that the discharge power distribution factor meets the discharge power constraint and the total discharge power distribution weight constraint is solved, so that the power loss of each energy storage unit in the discharge state can be reduced, the energy storage and discharge capacity of each energy storage unit is improved, the discharge performance of the energy storage system is improved, and the service life of the energy storage unit is further prolonged.
The invention also provides a schematic structural diagram of an energy storage unit power distribution system, referring to fig. 2, which is a schematic structural diagram of an energy storage unit power distribution system according to an embodiment of the invention, including: the battery characteristic acquisition module 21, the charge and discharge capacity calculation module 22, the charge power loss optimization model construction module 23, the charge power calculation module 24, the first state of charge update module 25, the charge power distribution module 26, the charge power loss optimization model construction module 27, the discharge power calculation module 28, the second state of charge update module 29, and the discharge power distribution module 30.
A battery characteristic obtaining module 21, configured to sequentially obtain battery characteristics corresponding to each energy storage unit of the energy storage power station; the battery characteristics comprise a first charge state of charging of each energy storage unit, a second charge state of discharging of each energy storage unit, rated power of each energy storage unit and total electric power of superior scheduling.
A charge/discharge capacity calculation module 22 for calculating the charge capacity and discharge capacity of each energy storage unit based on the battery characteristics.
The charging power loss optimization model construction module 23 is configured to determine a state of each energy storage unit according to the total power, calculate a charging capacity of each energy storage unit if the state of each energy storage unit is a charging state, and establish a charging power loss optimization model.
The charging power calculation module 24 is configured to iteratively solve the charging power loss optimization model to obtain a charging power distribution factor of each energy storage unit, until the charging power distribution factor of each energy storage unit meets a charging power constraint condition and a total charging power distribution weight constraint condition corresponding to each energy storage unit, stop iteration, and output a first charging power distribution factor of each energy storage unit; and updating parameters of the charging power loss optimization model during each iteration.
The first charge state updating module 25 is configured to sequentially update the first charge states of the energy storage units according to the first charge power distribution factor.
The charging power distribution module 26 is configured to distribute charging power to each energy storage unit according to the first charging power distribution factor.
And the discharge power loss optimization model construction module 27 is configured to determine the state of each energy storage unit according to the total power, and if the state of each energy storage unit is a discharge state, establish a discharge power loss optimization model according to the discharge capacity of each energy storage unit.
A discharge power calculation module 28, configured to iteratively solve the discharge power loss optimization model, obtain a discharge power distribution factor of each energy storage unit until the discharge power distribution factor of each energy storage unit meets a respective corresponding discharge power constraint condition and a total discharge power distribution weight constraint condition, stop iteration, and output a first discharge power distribution factor of each energy storage unit; and updating parameters of the discharge power loss optimization model during each iteration.
The second charge state updating module 29 is configured to sequentially update the first charge states of the energy storage units according to the first discharge power distribution factor.
The discharge power distribution module 30 distributes the discharge power for each energy storage unit by using the first discharge power distribution factor.
The invention also establishes a model targeting the minimum charge and discharge power loss by judging the charge and discharge states of the energy storage battery and considering the charge power distribution and the discharge power distribution respectively in the charge state and the discharge state and integrating the influence of the battery characteristics of the energy storage units on the charge and discharge power distribution of each energy storage unit, solves the feasible solution that the charge and discharge power distribution factors meet the charge and discharge power constraint and the total charge and total discharge power distribution weight constraint, can reduce the power loss of each energy storage unit in the charge state and the discharge state, and simultaneously improves the energy storage charging capacity and the discharge capacity of each energy storage unit, thereby improving the charge performance and the discharge performance of the energy storage system and further prolonging the service life of the energy storage battery.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (11)
1. A method of energy storage unit power distribution, the method comprising:
sequentially acquiring battery characteristics corresponding to energy storage units of an energy storage power station; the battery characteristics comprise a first charge state of charging of each energy storage unit, a second charge state of discharging of each energy storage unit, rated power of each energy storage unit and total electric power of superior scheduling;
calculating the charging capacity and discharging capacity of each energy storage unit according to the battery characteristics;
Judging the state of each energy storage unit according to the total power, if the state of each energy storage unit is a charging state, calculating the charging capacity of each energy storage unit, and establishing a charging power loss optimization model;
iteratively solving the charging power loss optimization model to obtain the charging power distribution factor of each energy storage unit until the charging power distribution factor of each energy storage unit meets the respective corresponding charging power constraint condition and total charging power distribution weight constraint condition, stopping iteration, and outputting the first charging power distribution factor of each energy storage unit; updating parameters of the charging power loss optimization model during each iteration;
sequentially updating the first charge states of the energy storage units according to the first charge power distribution factors;
and distributing charging power for each energy storage unit by using the first charging power distribution factor.
2. The method for distributing power to energy storage units according to claim 1, wherein said determining the state of each energy storage unit according to the total power further comprises:
judging the state of each energy storage unit according to the total power, and if the state of each energy storage unit is a discharge state, establishing a discharge power loss optimization model according to the discharge capacity of each energy storage unit;
Iteratively solving the discharge power loss optimization model to obtain a discharge power distribution factor of each energy storage unit until the discharge power distribution factor of each energy storage unit meets a respective corresponding discharge power constraint condition and a total discharge power distribution weight constraint condition, stopping iteration, and outputting a first discharge power distribution factor of each energy storage unit; wherein, during each iteration, the parameters of the discharge power loss optimization model are updated;
sequentially updating the first charge states of the energy storage units according to the first discharge power distribution factors;
and carrying out discharge power distribution by taking the first discharge power distribution factor as each energy storage unit.
3. The method for distributing power to energy storage units according to claim 1, wherein said determining the state of each energy storage unit according to the total power comprises:
if the total power is greater than a charge-discharge threshold, determining that the states of the energy storage units are all charge states; otherwise, determining that the states of the energy storage units are all discharge states.
4. The method for distributing power to energy storage units according to claim 1, wherein the calculating of the charging capacity and discharging capacity of each energy storage unit according to the battery characteristics is specifically:
And according to the battery characteristics, respectively calculating the charging factors of the energy storage units, and taking the minimum value of the rated power and the charging factors of the energy storage units as the charging capacity of the energy storage units.
5. The method of claim 4, further comprising calculating a discharge capacity, specifically:
and according to the battery characteristics, respectively calculating the discharge factors of the energy storage units, and taking the opposite number of the rated power of each energy storage unit and the maximum value of the discharge factors as the discharge capacity of each energy storage unit.
6. The method for distributing power to energy storage units according to claim 1, wherein the charging power distribution factor up to each energy storage unit satisfies a respective corresponding charging power constraint condition and a total charging power distribution weight constraint condition is specifically:
according to the respective charging power distribution factors and the total power of the energy storage units, calculating to obtain a charging power distribution result of each energy storage unit;
when the charging power distribution result of each energy storage unit is smaller than or equal to the charging capacity of each energy storage unit and is larger than or equal to 0, determining that the respective corresponding charging power constraint conditions are met;
And when the sum of the charging power distribution factors of all the energy storage units is 1, determining that the total charging power distribution weight constraint is met.
7. The method for distributing power to energy storage units according to claim 2, wherein the specific steps of the discharging power distribution factor of each energy storage unit until the discharging power distribution factor of each energy storage unit meets the respective corresponding discharging power constraint condition and total discharging power distribution weight constraint condition are as follows:
according to the respective discharge power distribution factors and the total power of the energy storage units, calculating to obtain a discharge power distribution result of each energy storage unit;
when the discharge power distribution result of each energy storage unit is smaller than or equal to 0 and is larger than or equal to the discharge capacity of each energy storage unit, determining that the corresponding discharge power constraint conditions are met;
and when the sum of the discharge power distribution factors of all the energy storage units is 1, determining that the total discharge power distribution weight constraint is met.
8. The method for distributing power to energy storage units according to claim 1, wherein the calculation formula of the charge power loss optimization model is as follows:
Wherein N is the number of the energy storage units,
for the charging efficiency of the ith energy storage cell, < >>
For the charging power distribution factor of the ith energy storage unit, P (t) is the total electric power of the upper schedule, delta t is the sampling time interval, +.>
Is the charging capacity of the ith energy storage unit.
9. The method for distributing power to energy storage units according to claim 2, wherein a discharge power loss optimization model is established according to the discharge capacity of each energy storage unit, and the calculation formula of the discharge power loss optimization model is as follows:
wherein N is the number of the energy storage units,
for the discharge efficiency of the ith energy storage cell, < >>
For the discharge power distribution factor of the ith energy storage unit, P (t) is the total electric power of the upper schedule, deltat is the sampling time interval, +.>
Is the discharge capacity of the ith energy storage cell.
10. An energy storage unit power distribution system, comprising:
the battery characteristic acquisition module is used for sequentially acquiring battery characteristics corresponding to each energy storage unit of the energy storage power station; the battery characteristics comprise a first charge state of charging of each energy storage unit, a second charge state of discharging of each energy storage unit, rated power of each energy storage unit and total electric power of superior scheduling;
The charge and discharge capacity calculation module is used for calculating the charge capacity and discharge capacity of each energy storage unit according to the battery characteristics;
the charging power loss optimization model construction module is used for judging the state of each energy storage unit according to the total power, if the state of each energy storage unit is a charging state, calculating the charging capacity of each energy storage unit, and building a charging power loss optimization model;
the charging power calculation module is used for iteratively solving the charging power loss optimization model to obtain the charging power distribution factor of each energy storage unit until the charging power distribution factor of each energy storage unit meets the respective corresponding charging power constraint condition and total charging power distribution weight constraint condition, stopping iteration, and outputting the first charging power distribution factor of each energy storage unit; updating parameters of the charging power loss optimization model during each iteration;
the first charge state updating module is used for sequentially updating the first charge states of the energy storage units according to the first charge power distribution factors;
and the charging power distribution module is used for distributing charging power for each energy storage unit by using the first charging power distribution factor.
11. The energy storage unit power distribution system of claim 10, further comprising:
the discharging power loss optimization model construction module is used for judging the state of each energy storage unit according to the total power, and if the state of each energy storage unit is a discharging state, a discharging power loss optimization model is built according to the discharging capacity of each energy storage unit;
the discharge power calculation module is used for iteratively solving the discharge power loss optimization model to obtain the discharge power distribution factor of each energy storage unit until the discharge power distribution factor of each energy storage unit meets the respective corresponding discharge power constraint condition and total discharge power distribution weight constraint condition, stopping iteration, and outputting the first discharge power distribution factor of each energy storage unit; wherein, during each iteration, the parameters of the discharge power loss optimization model are updated;
the second charge state updating module is used for sequentially updating the first charge states of the energy storage units according to the first discharge power distribution factors;
and the discharge power distribution module is used for distributing the discharge power by taking the first discharge power distribution factor as each energy storage unit.
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