CN110350579B - Multi-energy-storage-battery operation model capable of achieving smooth photovoltaic output - Google Patents
Multi-energy-storage-battery operation model capable of achieving smooth photovoltaic output Download PDFInfo
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- 238000004146 energy storage Methods 0.000 claims abstract description 147
- 238000007599 discharging Methods 0.000 claims abstract description 27
- 239000002699 waste material Substances 0.000 claims abstract description 9
- 238000000034 method Methods 0.000 claims abstract description 5
- 238000010248 power generation Methods 0.000 claims description 12
- 238000009499 grossing Methods 0.000 claims description 4
- 238000005562 fading Methods 0.000 claims description 3
- 230000014759 maintenance of location Effects 0.000 claims description 3
- 230000015556 catabolic process Effects 0.000 claims 1
- 238000006731 degradation reaction Methods 0.000 claims 1
- 230000000452 restraining effect Effects 0.000 claims 1
- 230000007423 decrease Effects 0.000 description 4
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 3
- 229910052744 lithium Inorganic materials 0.000 description 3
- 230000005611 electricity Effects 0.000 description 1
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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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- H02J3/383—
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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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Abstract
The invention discloses a multi-energy-storage-battery dynamic operation model capable of automatically adjusting and realizing smooth photovoltaic output curves, which comprehensively considers the performances of rated capacity, charging and discharging multiplying power, cycle times, charging and discharging efficiency, service life and the like of different types of energy storage batteries, establishes a dynamic operation model of a multi-battery energy storage system for the purposes of realizing the lowest photovoltaic waste rate, the longest service life and smooth output of the energy storage batteries, automatically releases the model and distributes the charging and discharging power to the different types of energy storage batteries in real time, schedules the energy storage batteries for charging and discharging work, and adjusts the smooth photovoltaic output. The photovoltaic output power control method reduces the fluctuation of photovoltaic output, ensures smooth output of a photovoltaic output power curve, avoids manual intervention and adjustment, automatically adjusts, reduces electric quantity waste, improves the service life of the energy storage battery, and realizes optimal economy.
Description
Technical Field
The invention relates to a multi-energy-storage-battery operation model capable of automatically adjusting and achieving smooth photovoltaic output, and belongs to the technical field of solar batteries.
Background
With the great popularization and development of new energy solar power generation, the permeability of photovoltaic power generation in a power grid is continuously increased, the negative influence of the random fluctuation characteristic of photovoltaic power on the scheduling and operation of the power grid is increasingly remarkable, and especially when a large amount of photovoltaic power generation is connected to the power grid, especially in northwest regions, the safety and the stability of the power grid are seriously influenced and damaged. Therefore, it is necessary to take certain technical measures to improve the random fluctuation characteristics of the photovoltaic power generation. In a grid-connected photovoltaic system, the energy storage technology is applied, so that the user demand side management can be effectively realized, the day and night peak-valley difference is eliminated, the load is smoothed, and the power supply cost is reduced; the utilization of renewable energy sources is promoted, the running stability of a power grid system is improved, and the power quality of the power grid is improved.
The photovoltaic and energy storage mode is one of effective measures for solving photovoltaic power fluctuation, eliminating day and night peak-valley difference, smoothing load and reducing power supply cost. However, for the energy storage system equipped in the photovoltaic power station, how to apply the energy storage system to achieve the purpose and simultaneously considering the problems of the service life of the energy storage battery, the photovoltaic power rejection rate and the like is a problem which needs to be solved urgently. The energy storage battery mainly refers to a storage battery used for storing energy in solar power generation equipment, wind power generation equipment and renewable energy sources, and comprises a lithium battery and a liquid battery. The photovoltaic output curve refers to a real-time output power curve generated by a photovoltaic power station and is characterized by presenting larger fluctuation along with the change of weather. Smooth output means that the photovoltaic output curve can be adjusted by the energy storage battery under the condition of being influenced by the outside (weather) so as to avoid fluctuation and realize smooth output.
Most of the existing energy storage systems are provided with the same energy storage battery system, and the scheduling model only needs to consider the average distribution of the rated power value of the PCS of the energy storage system to carry out charging and discharging operations. At present, almost no system for configuring multiple types of energy storage batteries for a photovoltaic power station exists, how to schedule the multiple types of energy storage batteries so as to realize smooth output of photovoltaic power is the lowest photovoltaic waste rate, and the longest service life of the energy storage batteries is the problem which needs to be solved urgently at present.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the scheduling problem of how to automatically adjust various energy storage batteries under a smooth output scene so as to achieve the purposes of smooth photovoltaic output curve, longest service life of the energy storage batteries and lowest photovoltaic abandonment rate.
In order to solve the technical problem, the invention adopts the following technical scheme:
a multi-energy-storage-battery dynamic operation model capable of achieving photovoltaic output curve smoothing is characterized by comprising the following specific steps:
an objective function: the model enables the photovoltaic abandonment rate to be the lowest by optimizing the scheduling of the energy storage battery, namely:
the constraints are as follows:
power balance: the sum of the generated power of the remaining photovoltaic system and the discharged power of the alternating-current energy storage battery at any moment should be equal to the sum of the charged power of the alternating-current energy storage battery, the effective generated energy of the remaining photovoltaic and the discarded amount thereof, namely:
in the formula, I is an alternating current energy storage battery module set; j represents a residual photovoltaic subarray set after removing the photovoltaic subarrays in the direct-current energy storage system; n is a module set of a direct current system; p pv,j (t) represents the photovoltaic subarray power generation amount with the number j; p is i in (t) and P i out (t) charge and discharge power for the ac energy storage battery module numbered i, respectively; eta ac,i The discharging efficiency of the alternating-current energy storage battery module with the number i is shown; lambda [ alpha ] ac,i The charging efficiency of the alternating-current energy storage battery module with the number i is shown; p ac (t) is the amount of power supplied by the hybrid power supply system to the power grid; p pw (t) is the amount of waste of remaining photovoltaic subarrays;
and (4) smooth constraint: for the whole hybrid power supply system, the change rate delta P of the power supply quantity of the alternating current system to the power grid at any time ac (t) not more than 10% of installed capacity/min of the photovoltaic power station, obtaining:
P ac (t+1)＝P ac (t)+ΔP ac (T), T ∈ T formula (3);
-C pv,a ×10％≤ΔP ac (t)≤C pv,a x 10%, and T is T formula (4);
wherein, C pv,a The installed capacity of a photovoltaic power station representing an alternating current system;
energy storage battery subsystem constraints: the residual capacity B of any group of energy storage batteries at the moment t m (t) can be represented by
Wherein M represents a set of all kinds of energy storage batteries, including sets I and N;
the electric quantity of the mth group of energy storage batteries at any moment needs to meet the following requirements:
SOC min,m C a,m ≤B m (t)≤SOC max,m C a,m formula (6);
B m (t)≤C a,m (S m -Q loss,m (t)) formula (7);
in the formula, SOC min,m The minimum charge state of the mth energy storage battery pack; SOC (system on chip) max,m The maximum charge state of the mth energy storage battery pack; c a,m The rated capacity of the mth energy storage battery pack; s m The initial capacity retention rate of the mth energy storage battery pack;
the upper limit and the lower limit of the charge and discharge power of any group of energy storage batteries at any time can meet the following requirements:
in the formula, P m in,min And P m out,min Respectively represents the lower limit of charging and discharging power, P, of the mth energy storage battery pack m nom The rated power of the mth energy storage battery pack;
and (3) energy storage system charge and discharge state constraint: in view of the safety of the batteries, the charging and discharging operations of the same group of batteries are mutually exclusive, and the same group of batteries cannot be charged and discharged simultaneously in the same period of time, namely:
wherein z is m in (t) and z m out (t) are binary variables, respectively;
capacity fade of energy storage batteries: the capacity decline of the lithium battery is influenced by factors such as temperature T, state of charge SOC, delta SOC, depth of discharge d, charge and discharge current, charge termination voltage, discharge termination voltage and charging mode, and no matter the direct current energy storage battery or the alternating current energy storage battery, the capacity decline rate at any moment can be expressed as:
Q tot,m (t)＝Q cal,m (t)+Q cyc,m (t) formula (15);
wherein Q is cal,m (t) the calendar life decay rate of the mth energy storage battery pack in the t period; q cyc,m (t) is the cycle life decay rate of the mth energy storage battery pack in the t period; q tot,m (t) is the total capacity fading rate of the mth energy storage battery pack in the time period t; life cal,m Indicating the total calendar Life, life, of the mth energy storage battery pack cyc,m Representing the total cycle number of the mth energy storage battery pack; c max,m Representing the initial capacity of the mth energy storage battery pack;
because the capacity of the energy storage battery is reduced to 80% of the standard capacity of the energy storage battery and then needs to be replaced, the total capacity reduction rate Q of the mth energy storage battery pack in the period t relative to the whole battery life loss,m (t)：
Q loss,m (t)＝q m *Q total,m (t) Formula (15);
wherein q is m And the capacity ratio of the m-th energy storage battery pack until retirement is declined.
The model is realized in the following mode:
step 1): the method comprises the steps of collecting power generation power of each sub-array in a photovoltaic and energy storage system, the SOC state of an energy storage battery and the attenuation rate of battery capacity input into the photovoltaic and energy storage system in real time, and outputting power to a power grid at the last moment;
step 2): automatically calculating through the established model and distributing the charging and discharging power of different energy storage batteries in real time;
step 3): the energy storage batteries are automatically scheduled to perform charging and discharging work through the charging and discharging power distributed to different energy storage batteries in the last step, and smooth output of a photovoltaic output curve is realized.
The multi-energy-storage-battery dynamic operation model capable of automatically adjusting and achieving the smoothness of the photovoltaic output curve comprehensively considers the performances of rated capacity, charging and discharging multiplying power, cycle times, charging and discharging efficiency, service life and the like of different types of energy storage batteries, aims at achieving the purposes of lowest photovoltaic waste rate, longest service life and smooth output of the energy storage batteries, establishes the dynamic operation model of the multi-battery energy storage system, automatically releases the model, distributes the model to the charging and discharging power of the different types of energy storage batteries in real time, schedules the energy storage batteries to perform charging and discharging work, and adjusts the smoothness of the photovoltaic output.
The photovoltaic output fluctuation is reduced, and smooth output of a photovoltaic output curve is ensured; the minimum photovoltaic waste rate and the maximum service life of the energy storage battery are finally realized by combining the performances of the different types of energy storage batteries, such as rated capacity, charge-discharge multiplying power, cycle times, charge-discharge efficiency, service life and the like, and a dynamic operation strategy of the multi-battery energy storage system is established; the method avoids manual intervention and adjustment and automatic adjustment, reduces the electricity waste, improves the service life of the energy storage battery, and realizes the optimal economy.
Drawings
Fig. 1 is a flow chart of scheduling between photovoltaic and energy storage.
Detailed Description
In order to make the invention more comprehensible, preferred embodiments are described in detail below with reference to the accompanying drawings.
Examples
A multi-energy-storage-battery dynamic operation model capable of achieving photovoltaic output curve smoothing is characterized by comprising the following specific steps:
an objective function: the model enables the photovoltaic abandonment rate to be the lowest by optimizing the scheduling of the energy storage battery, namely:
the constraints are as follows:
power balance: the sum of the generated power of the remaining photovoltaic system and the discharged power of the alternating-current energy storage battery at any moment is equal to the sum of the charged power of the alternating-current energy storage battery, the effective generated energy of the remaining photovoltaic and the discarded amount thereof, namely:
in the formula, I is an alternating current energy storage battery module set; j represents a residual photovoltaic subarray set after removing the photovoltaic subarrays in the direct-current energy storage system; n is a module set of a direct current system; p pv,j (t) represents the photovoltaic subarray power generation amount with the number j; p i in (t) and P i out (t) charge and discharge power for the ac energy storage battery module numbered i, respectively; eta ac,i The discharging efficiency of the alternating-current energy storage battery module with the number i is shown; lambda ac,i The charging efficiency of the alternating-current energy storage battery module with the number i is shown; p ac (t) is the amount of power supplied by the hybrid power supply system to the power grid; p pw (t) is the amount of waste of remaining photovoltaic subarrays;
and (4) smooth constraint: for the whole hybrid power supply system, the change rate delta P of the power supply quantity of the alternating current system to the power grid at any time ac (t) not more than 10% installed capacity/min of the photovoltaic power station, obtaining:
P ac (t+1)＝P ac (t)+ΔP ac (t),t∈T formula (3);
-C pv,a ×10％≤ΔP ac (t)≤C pv,a x 10%, and T is T formula (4);
wherein, C pv,a Representing installed capacity of a photovoltaic power plant of the alternating current system;
energy storage battery subsystem constraints: the residual electric quantity B of any group of energy storage batteries at the moment t m (t) can be represented by
Wherein M represents a set of all kinds of energy storage batteries, including sets I and N;
the electric quantity of the mth group of energy storage batteries at any moment needs to meet the following requirements:
SOC min,m C a,m ≤B m (t)≤SOC max,m C a,m formula (6);
B m (t)≤C a,m (S m -Q loss,m (t)) formula (7);
in the formula, SOC min,m The minimum charge state of the mth energy storage battery pack; SOC (system on chip) max,m The maximum charge state of the mth energy storage battery pack; c a,m The rated capacity of the mth energy storage battery pack; s m The initial capacity retention rate of the mth energy storage battery pack;
the upper limit and the lower limit of the charge and discharge power of any group of energy storage batteries at any time can meet the following requirements:
in the formula, P m in,min And P m out,min Respectively represents the lower limit of charging and discharging power, P, of the mth energy storage battery pack m nom The rated power of the mth energy storage battery pack;
and (3) energy storage system charge and discharge state constraint: in view of the safety of the batteries, the charging and discharging operations of the same group of batteries are mutually exclusive, and the same group of batteries cannot be charged and discharged simultaneously in the same period of time, namely:
wherein z is m in (t) and z m out (t) are binary variables, respectively;
capacity fade of energy storage batteries: the capacity decline of the lithium battery is influenced by factors such as temperature T, state of charge SOC, delta SOC, depth of discharge d, charge and discharge current, charge termination voltage, discharge termination voltage and charging mode, and no matter the direct current energy storage battery or the alternating current energy storage battery, the capacity decline rate at any moment can be expressed as:
Q tot,m (t)＝Q cal,m (t)+Q cyc,m (t) formula (15);
wherein Q is cal,m (t) the calendar life decay rate of the mth energy storage battery pack in the t period; q cyc,m (t) is the cycle life decay rate of the mth energy storage battery pack in the t period; q tot,m (t) is the followingThe total capacity fading rate of the m energy storage battery packs in the t period; life cal,m Indicating the total calendar Life, life, of the mth energy storage battery pack cyc,m Representing the total cycle number of the mth energy storage battery pack; c max,m Representing the initial capacity of the mth energy storage battery pack;
because the capacity of the energy storage battery is reduced to 80% of the standard capacity of the energy storage battery and then needs to be replaced, the total capacity reduction rate Q of the mth energy storage battery pack in the period t relative to the whole battery life loss,m (t)：
Q loss,m (t)＝q m *Q total,m (t) formula (15);
wherein q is m And the capacity ratio of the m-th energy storage battery pack until retirement is declined.
The implementation of the above model is shown in fig. 1:
step 1): the method comprises the steps of collecting power generation power of each sub-array in a photovoltaic and energy storage system, the SOC state of an energy storage battery and the attenuation rate of battery capacity input into the photovoltaic and energy storage system in real time, and outputting power to a power grid at the last moment;
step 2): automatically calculating through the established model and distributing the charging and discharging power of different energy storage batteries in real time;
step 3): the energy storage batteries are automatically scheduled to perform charging and discharging work through the charging and discharging power distributed to different energy storage batteries in the last step, and smooth output of a photovoltaic output curve is realized.
Claims (2)
1. A multi-energy-storage-battery dynamic operation model capable of achieving photovoltaic output curve smoothing is characterized by comprising the following specific steps:
an objective function: the model enables the photovoltaic abandonment rate to be the lowest by optimizing the scheduling of the energy storage battery, namely:
the constraints are as follows:
power balance: the sum of the generated power of the remaining photovoltaic system and the discharged power of the alternating-current energy storage battery at any moment should be equal to the sum of the charged power of the alternating-current energy storage battery, the effective generated energy of the remaining photovoltaic and the discarded amount thereof, namely:
in the formula, I is an alternating current energy storage battery module set; j represents a residual photovoltaic subarray set after removing the photovoltaic subarrays in the direct-current energy storage system; n is a module set of a direct current system; p pv,j (t) represents the photovoltaic subarray power generation amount with the number j; p i in (t) and P i out (t) charge and discharge power for the ac energy storage battery module numbered i, respectively; eta ac,i The discharging efficiency of the alternating-current energy storage battery module with the number i is shown; lambda [ alpha ] ac,i The charging efficiency of the alternating-current energy storage battery module with the number i is shown; p ac (t) is the amount of power supplied by the hybrid power supply system to the power grid; p pw (t) is the amount of waste of remaining photovoltaic subarrays;
and (4) smooth constraint: for the whole hybrid power supply system, the change rate delta P of the power supply quantity of the alternating current system to the power grid at any time ac (t) not more than 10% installed capacity/min of the photovoltaic power station, obtaining:
P ac (t+1)＝P ac (t)+ΔP ac (T), T ∈ T formula (3);
-C pv,a ×10％≤ΔP ac (t)≤C pv,a x 10%, and T is T formula (4);
wherein, C pv,a Representing installed capacity of a photovoltaic power plant of the alternating current system;
energy storage battery subsystem constraints: the residual capacity B of any group of energy storage batteries at the moment t m (t) can be represented by
Wherein M represents a set of all kinds of energy storage batteries, including sets I and N;
the electric quantity of the mth group of energy storage batteries at any moment needs to meet the following requirements:
SOC min,m C a,m ≤B m (t)≤SOC max,m C a,m formula (6);
B m (t)≤C a,m (S m -Q loss,m (t)) formula (7);
in the formula, SOC min,m The minimum charge state of the mth energy storage battery pack; SOC max,m The maximum charge state of the mth energy storage battery pack; c a,m The rated capacity of the mth energy storage battery pack; s. the m The initial capacity retention rate of the mth energy storage battery pack;
the upper limit and the lower limit of the charge and discharge power of any group of energy storage batteries at any time can meet the following requirements:
in the formula, P m in,min And P m out,min Respectively represents the lower limit of charging and discharging power, P, of the mth energy storage battery pack m nom The rated power of the mth energy storage battery pack;
and (3) restraining the charge and discharge states of the energy storage system: in view of the safety of the battery, the charging and discharging operations of the same battery set are mutually exclusive, and the same battery set cannot be charged and discharged at the same time in the same period of time, namely:
wherein z is m in (t) and z m out (t) are binary variables, respectively;
capacity fade of energy storage batteries: whether the direct-current energy storage battery or the alternating-current energy storage battery is adopted, the capacity degradation rate at any moment can be expressed as:
Q tot,m (t)＝Q cal,m (t)+Q cyc,m (t) formula (15);
wherein Q is cal,m (t) the calendar life decay rate of the mth energy storage battery pack in the t period; q cyc,m (t) is the cycle life decay rate of the mth energy storage battery pack in the t period; q tot,m (t) is the total capacity fading rate of the mth energy storage battery pack in the time period t; life cal,m Indicating the total calendar Life, life, of the mth energy storage battery pack cyc,m Representing the total cycle number of the mth energy storage battery pack; c max,m Representing the initial capacity of the mth energy storage battery pack;
because the capacity of the energy storage battery is reduced to 80% of the standard capacity of the energy storage battery and then needs to be replaced, the total capacity reduction rate Q of the mth energy storage battery pack in the period t relative to the whole battery life loss,m (t)：
Q loss,m (t)＝q m *Q total,m (t) formula (15);
wherein q is m And the capacity ratio of the m-th energy storage battery pack until retirement is declined.
2. The model of claim 1, wherein the model is implemented by:
step 1): the method comprises the steps of collecting power generation power of each subarray input into a photovoltaic and energy storage system, SOC (state of charge) of an energy storage battery and attenuation rate of battery capacity in real time, and outputting power to a power grid at the last moment;
step 2): automatically calculating through the established model and distributing the charging and discharging power of different energy storage batteries in real time;
step 3): the energy storage batteries are automatically scheduled to perform charging and discharging work through the charging and discharging power distributed to different energy storage batteries in the last step, and smooth output of a photovoltaic output curve is realized.
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