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CN108282008B - Hybrid energy storage control method based on low-pass charge-discharge coefficient constraint - Google Patents

Hybrid energy storage control method based on low-pass charge-discharge coefficient constraint Download PDF

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CN108282008B
CN108282008B CN201810149753.7A CN201810149753A CN108282008B CN 108282008 B CN108282008 B CN 108282008B CN 201810149753 A CN201810149753 A CN 201810149753A CN 108282008 B CN108282008 B CN 108282008B
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卢泉
邓海华
胡立坤
卢子广
韦雪菲
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Guangxi University
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    • H02J7/0003—
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
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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
    • H02J7/34—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering
    • H02J7/345—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering using capacitors as storage or buffering devices
    • 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
    • H02J7/34—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering
    • H02J7/35—Parallel operation in networks using both storage and other DC sources, e.g. providing buffering with light sensitive cells
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    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
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    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
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Abstract

本发明公开了一种基于低通充放电系数约束的混合储能控制方法，使用于包括超级电容器和蓄电池组成的混合储能系统，分别设置可根据蓄电池剩余电量SOC变化的充电低通时间系数λ和放电低通时间系数τ，对蓄电池剩余电量SOC的变化进行曲线拟合，根据所拟合的SOC曲线分别转换得到充电低通时间系数λ和放电低通时间系数τ的变化曲线和变化范围，根据充电低通时间系数λ和放电低通时间系数τ对蓄电池的充放电功率进行平滑。与现有技术相比，本发明的低通系数方法更能兼顾蓄电池不同剩余电量SOC时的电气性能变化，在达到平滑蓄电池功率波动，延长蓄电池寿命的前提下，更好发挥蓄电池的电气特性，有利于维护直流母线电压稳定。

Figure 201810149753

The invention discloses a hybrid energy storage control method based on a low-pass charge-discharge coefficient constraint, which is used in a hybrid energy-storage system including a supercapacitor and a battery, and a charging low-pass time coefficient λ that can be changed according to the remaining battery power SOC is respectively set and the discharge low-pass time coefficient τ, the curve fitting is performed on the change of the SOC of the remaining battery power, and the change curve and range of the charging low-pass time coefficient λ and the discharge low-pass time coefficient τ are respectively converted according to the fitted SOC curve, The charging and discharging power of the battery is smoothed according to the charging low-pass time coefficient λ and the discharging low-pass time coefficient τ. Compared with the prior art, the low-pass coefficient method of the present invention can better take into account the electrical performance changes of the battery with different remaining power SOCs, and under the premise of smoothing the battery power fluctuation and prolonging the battery life, the electrical characteristics of the battery can be better utilized. Conducive to maintaining the DC bus voltage stability.

Figure 201810149753

Description

Hybrid energy storage control method based on low-pass charge-discharge coefficient constraint
Technical Field
The invention relates to the technical field of electric power, in particular to a hybrid energy storage control method based on low-pass charge-discharge coefficient constraint.
Background
Photovoltaic power generation is one of important components for realizing energy and electric power and sustainable development strategy in China. However, photovoltaic power generation has very strong volatility and randomness, so that great interference is caused to the stability of a new energy system, in order to more efficiently utilize renewable energy, the photovoltaic system is often used in cooperation with an energy storage device, and a light storage complementary system can improve the continuity, stability and reliability of the direct-current bus voltage of the system, so that the photovoltaic effect is maximized.
However, the common storage battery is often low in energy density and high power density, frequent charging and discharging of the storage battery are caused by frequent fluctuation of a direct current bus in a photovoltaic system, even the service life of the storage battery is seriously influenced by quick charging and quick discharging, and the system cost is increased; however, the super capacitor has small energy density and large power density, especially the super capacitor is developed rapidly at present, the number of times of the super capacitor can be charged and discharged circularly far exceeds that of the storage battery, and the super capacitor and the storage battery can form very good complementation, so that in the hybrid energy storage system, the super capacitor bears high-frequency power fluctuation, the storage battery bears low-frequency power fluctuation, the service life of the storage battery can be greatly prolonged, and the stability of the direct current bus is increased. For this reason, in the hybrid energy storage system, a hybrid energy storage control method is required.
Disclosure of Invention
The invention aims to provide a hybrid energy storage control method based on low-pass charge-discharge coefficient constraint, which can smooth the power fluctuation of a storage battery when the storage battery has different electric quantities, prolong the service life of the storage battery, better exert the electrical characteristics of the storage battery and be beneficial to maintaining the voltage stability of a direct-current bus.
A hybrid energy storage control method based on low-pass charge-discharge coefficient constraint is used for a hybrid energy storage system consisting of a super capacitor and a storage battery, a charge low-pass time coefficient lambda and a discharge low-pass time coefficient tau which can change according to the residual capacity SOC of the storage battery are respectively set, curve fitting is carried out on the change of the residual capacity SOC of the storage battery, the change curve and the change range of the charge low-pass time coefficient lambda and the discharge low-pass time coefficient tau are respectively obtained through conversion according to the fitted SOC curves, the charge-discharge power of the storage battery is smoothed according to the charge low-pass time coefficient lambda and the discharge low-pass time coefficient tau, and the power distribution of the storage battery and the super capacitor is shown as the following formula:
Figure BDA0001579607760000011
or
Figure BDA0001579607760000012
psc_ref＝pdc-pbat_ref
Wherein p isdcIs the total power of the DC bus, pbat_refIs the reference power of the battery, psc_refS represents the laplacian operator for the reference power of the super capacitor.
The curve fitting of the residual battery SOC comprises primary fitting and multiple fitting, and the primary fitting curve is as follows:
Figure BDA0001579607760000021
the multi-fit curve is:
Figure BDA0001579607760000022
wherein, Vcur、Vmax、VminRespectively representing the current voltage, the maximum voltage and the minimum voltage of the storage battery; SOCcur、SOCmaxRespectively representing the current residual electric quantity and the maximum capacity of the storage battery; SOCn-1、SOCnDividing the current residual capacity SOC value of the storage battery into a previous moment and a current moment, wherein n is more than or equal to 1;
according to the primary fitting curve and the multiple fitting curves, respectively converting the variation curves of the charging low-pass time coefficient lambda and the discharging low-pass time coefficient tau according to the following formula:
Figure BDA0001579607760000023
Figure BDA0001579607760000024
wherein, taucur，τmax，τminRespectively representing a current discharge low-pass time coefficient, a maximum discharge low-pass time coefficient and a minimum discharge low-pass time coefficient; lambda [ alpha ]cur，λmax，λminRespectively the current charging low-pass time coefficient and the maximumA charge low-pass time coefficient and a minimum charge low-pass time coefficient.
The maximum discharge low-pass time coefficient taumaxAnd minimum discharge low-pass time coefficient tauminThe calculation method comprises the following steps:
Iout_max＝k×SOCmax
when the battery is fully charged, there are:
Figure BDA0001579607760000031
SOC when the battery is lowshortageIn time, there are:
Figure BDA0001579607760000032
therein, SOCmaxFor the maximum capacity of the battery, k is a user-defined discharge multiple of the battery, typically taken as: k is more than 0 and less than or equal to 3, Iout_maxThe maximum current of the storage battery; SOCshortageFor a set quantity of electricity, V, during the power shortage of the accumulatorbat_shortageCorresponding SOC for the storage batteryshortageVoltage value of pdc_max、pbat_max、Vbat_maxThe maximum output power of the system, the maximum output power of the battery and the maximum voltage of the battery are respectively, C is the maximum value of SOC calibrated when the storage battery leaves a factory, and S represents a Laplace operator.
The maximum discharge low-pass time coefficient lambdamaxAnd a minimum discharge low-pass time coefficient lambdaminThe calculation method of (2) is as follows:
SOC when the battery is lowshortageAt first, there is a maximum charging current Iin_maxAnd a minimum charge low-pass time coefficient lambdamin：
Iin_max＝k×SOCmax/10
Figure BDA0001579607760000033
When storing electricityWhen the battery capacity is sufficient, there is a minimum charging current Iin_minAnd maximum discharge low-pass time coefficient lambdamax：
Iin_min＝k×SOCmax/200
Figure BDA0001579607760000034
Therein, SOCshortageFor setting the quantity of electricity, SOC, during the power shortage of the accumulatorenoughThe set electric quantity when the storage battery is fully charged generally means that more than 80% of the electric quantity is fully charged and less than 20% of the electric quantity is insufficient, namely 0 < SOCshortage＜0.2SOCmax＜SOCenough＜0.8SOCmax；Vbat_shortage、VenoughThe voltages are corresponding to the short-circuit and full-electricity of the storage battery respectively; i isin_max、Iin_minMaximum and minimum charging currents, p, of the accumulatordc_maxIs the system maximum output power.
Compared with the prior art, the method of the invention can better take into account the electrical property change of the storage battery when the electric quantity allowance is different, can more smooth the power fluctuation of the storage battery in the hybrid energy storage system, and prolong the service life of the storage battery; the low-pass coefficient of the invention is more beneficial to maintaining the voltage stability of the direct current bus.
Drawings
FIG. 1 is a system block diagram of a hybrid energy storage system of the method of the present invention.
FIG. 2 is a primary V-SOC curve of the method of the present invention.
FIG. 3 is a multiple V-SOC curve of the method of the present invention.
FIG. 4 is a first fit V-time coefficient curve of the method of the present invention.
FIG. 5 is a multiple fit V-time coefficient curve of the method of the present invention.
Detailed Description
According to the hybrid energy storage control method, the charging low-pass time coefficient and the discharging low-pass time coefficient are designed, so that the electric performance of the storage battery in different capacities of SOC is fully utilized while the power of the storage battery is fully smoothed. As shown in fig. 1, the microgrid system of the method of the present invention includes a distributed power supply and a hybrid energy storage system, where the hybrid energy storage system includes a storage battery and a super capacitor; the distributed power source refers to photovoltaic power generation.
In the control method, the low-pass processing is carried out on the power of the direct current bus to be used as a power reference value of the storage battery, the difference value of the power of the direct current bus and the power of the storage battery is used as a power reference value of the super capacitor, namely:
Figure BDA0001579607760000041
psc_ref＝pdc-pbat_ref (2)
in the formulae (1) and (2), pdc、pbat_ref、psc_refThe total power of the direct current bus, the reference power of the storage battery and the reference power of the super capacitor are respectively; tau and lambda are respectively a discharging low-pass time coefficient and a charging low-pass time coefficient; s represents the laplacian operator.
The discharge current of the storage battery is related to the capacity, the maximum discharge current of the storage battery can reach 4-5C according to experience, the safe discharge current of the storage battery is within 2C, and C refers to the nominal capacity of the storage battery. Maximum discharge current I of accumulatorout_maxThe calculation method of (2) is as follows:
Iout_max＝k×SOCmax (3)
where k is the discharge rate of the battery, in order to protect the battery, it is usually: k is more than 0 and less than or equal to 3.
When the storage battery is fully charged, the discharge capacity is strongest, the discharge low-pass time coefficient is minimum, and the minimum discharge low-pass time coefficient tau is obtained at the momentminCalculated as follows (4):
Figure BDA0001579607760000051
in the formulae (3) and (4), pdc_max，pbat_max，Vbat_maxRespectively, the maximum output power of the system and the maximum output power of the batteryOutput power and battery maximum voltage, k is the user defined maximum discharge multiple, SOCmaxC is the maximum SOC value calibrated at the time of shipment of the storage battery, but the SOC is usually the maximum SOC value due to the aging of the storage batterymax≤C。
When the remaining battery capacity is insufficient, the discharge capacity is the weakest and the resistance is worse, so that the discharge low-pass time coefficient is the largest. Defining the SOC of the accumulator in a certain residual capacityshortageThe maximum charging low-pass time coefficient is belowmaxCalculated as follows (5):
Figure BDA0001579607760000052
v in formula (5)bat_shortageAfter the primary or multiple fitting is carried out on the storage battery, the storage battery corresponds to the SOCshortageVoltage value of (1), usually 0 < SOCshortage≤0.2SOCmax. Equation (5) illustrates the SOC when the remaining battery capacity ratio is setshortage＝0.2SOCmaxAt a lower time, τmaxThe maximum value is kept constant.
When the electric quantity of the storage battery is insufficient, the storage battery can bear the maximum charging current and has the minimum charging low-pass time coefficient, so that the maximum charging current Iin_maxAnd a minimum charge low-pass time coefficient lambdaminCalculated according to the following equations (6) and (7), respectively:
Iin_max＝k×SOCmax/10 (6)
Figure BDA0001579607760000053
the battery has minimal resistance to charging current when fully charged, and therefore the charging current should be minimal and smooth, with a maximum discharge low-pass time factor λmaxLet the current at this time:
Iin_min＝k×SOCmax/200 (8)
at this time, the resistance of the storage battery to the charging current is the weakest, and the storage battery has the maximum discharging low-pass timeCoefficient lambdamax：
Figure BDA0001579607760000061
In the above equation (9), the remaining capacity SOC of the battery is definedenoughMaximum charging low-pass time coefficient lambda of above timemaxIs kept constant at maximum, Vbat_enoughIs fitted to the storage battery for the first time or multiple times and then corresponds to the SOCenoughVoltage value of (2), wherein 0.8SOCmax≤SOCenough≤SOCmax。
The primary fitting curve of the residual capacity SOC of the storage battery is calculated according to the formula (10):
Figure BDA0001579607760000062
wherein, Vcur，Vmax，VminRespectively representing the current voltage, the maximum voltage and the minimum voltage of the storage battery; SOCcur，SOCmaxRespectively the current capacity and the maximum capacity of the storage battery; the fitted curve of SOC obtained according to equation (10) is shown in FIG. 2, which provides a fast and simple SOC estimation method for unknown batteries, and the SOC is uniformly distributed according to the voltage.
Calculating a multi-fitting curve of the residual capacity SOC of the storage battery according to the formula (11):
Figure BDA0001579607760000063
wherein the SOCn、SOCn-1Respectively representing the battery residual quantity at the current moment and the battery residual quantity at the previous moment, wherein n is more than or equal to 1. As shown in fig. 3, which is the SOC fitting curve obtained according to equation (11), it can be seen that the curve is nonlinear, and the fitting method will approach the true SOC value more and more as the number of charging and discharging increases.
Respectively calculating the current discharging low-pass time coefficient tau according to the SOC curve of the storage battery obtained by the formula (11)curAnd a current charging low-pass time coefficient lambdacur：
Figure BDA0001579607760000071
Figure BDA0001579607760000072
τcur，τmax，τminRespectively representing a current discharge low-pass time coefficient, a maximum discharge low-pass time coefficient and a minimum discharge low-pass time coefficient; lambda [ alpha ]cur，λmax，λminRespectively a current charging low-pass time coefficient, a maximum charging low-pass time coefficient and a minimum charging low-pass time coefficient.
As shown in fig. 4, the values of the time constants according to equations (12) and (13) are changed with the change of the SOC, and the value of the low-pass time constant for time charging and discharging can be quickly determined according to the curve as long as the SOC is determined. FIG. 4 shows a time constant-V curve which is fitted for the first time, the time constant is linearly and uniformly distributed according to the voltage, different voltages correspond to different time constants, the time constant can be rapidly determined when an unknown storage battery is contacted for the first time, and a low-pass control strategy is determined. FIG. 5 shows a time constant-V curve which is fit for many times, the time constant is distributed in a curve, and low-pass coefficients can be reasonably used according to data recorded by the curve, so that the performance of the storage battery can be better exerted on the basis of smoothing the power of the storage battery.

Claims (3)

1.一种基于低通充放电系数约束的混合储能控制方法，使用于包括超级电容器和蓄电池组成的混合储能系统，其特征在于：分别设置可根据蓄电池剩余电量SOC变化的充电低通时间系数λ和放电低通时间系数τ，对蓄电池剩余电量SOC的变化进行曲线拟合，根据所拟合的SOC曲线分别转换得到充电低通时间系数λ和放电低通时间系数τ的变化曲线和变化范围，根据充电低通时间系数λ和放电低通时间系数τ对蓄电池的充放电功率进行平滑，蓄电池和超级电容的功率分配如下式所示：1. A hybrid energy storage control method based on a low-pass charge-discharge coefficient constraint, used in a hybrid energy storage system comprising a supercapacitor and a battery, characterized in that: the charging low-pass time that can be changed according to the remaining battery SOC of the battery is respectively set The coefficient λ and the discharge low-pass time coefficient τ are used to perform curve fitting on the change of the SOC of the remaining battery power. According to the fitted SOC curve, the change curves and changes of the charging low-pass time coefficient λ and the discharge low-pass time coefficient τ are obtained respectively. The charging and discharging power of the battery is smoothed according to the charging low-pass time coefficient λ and the discharging low-pass time coefficient τ. The power distribution of the battery and the super capacitor is as follows:
Figure FDA0002932660630000011
或
Figure FDA0002932660630000012
Figure FDA0002932660630000011
or
Figure FDA0002932660630000012
 psc_ref＝pdc-pbat_ref p sc_ref = p dc -p bat_ref 其中，pdc为直流母线的总功率，pbat_ref为蓄电池的参考功率，psc_ref为超级电容的参考功率，s表示拉普拉斯算子；Among them, p dc is the total power of the DC bus, p bat_ref is the reference power of the battery, p sc_ref is the reference power of the super capacitor, and s is the Laplace operator; 所述对蓄电池剩余电量SOC的变化进行曲线拟合包括初次拟合和多次拟合，初次拟合曲线为：The curve fitting on the change of the remaining battery power SOC includes initial fitting and multiple fittings, and the initial fitting curve is:
Figure FDA0002932660630000013
Figure FDA0002932660630000013
 多次拟合曲线为：The multiple fitting curve is:
Figure FDA0002932660630000014
Figure FDA0002932660630000014
 其中，Vcur、Vmax、Vmin分别为蓄电池当前电压、最大电压和最小电压；SOCcur、SOCmax分别为蓄电池当前剩余电量和最大容量；SOCn、SOCn-1分为前一时刻和当前时刻的蓄电池当前剩余电量SOC值，n≥1；V为随时间t变化的蓄电池电压、i(t)为随时间t变化的蓄电池充放电电流，t为时间；Among them, V cur , V max , and V min are the current voltage, maximum voltage and minimum voltage of the battery, respectively; SOC cur , SOC max are the current remaining power and maximum capacity of the battery, respectively; SOC n , SOC n-1 are divided into the previous moment and The SOC value of the current remaining battery power at the current moment, n≥1; V is the battery voltage that changes with time t, i(t) is the battery charging and discharging current that changes with time t, and t is time; 根据初次拟合曲线和多次拟合曲线，按照下式分别转换得到充电低通时间系数λ和放电低通时间系数τ的变化曲线为：According to the initial fitting curve and the multiple fitting curves, the change curves of the charging low-pass time coefficient λ and the discharging low-pass time coefficient τ are respectively converted according to the following formulas:
Figure FDA0002932660630000015
Figure FDA0002932660630000015
Figure FDA0002932660630000021
Figure FDA0002932660630000021
 其中，τcur，τmax，τmin分别为当前放电低通时间系数、最大放电低通时间系数和最小放电低通时间系数；λcur，λmax，λmin分别为当前充电低通时间系数、最大充电低通时间系数和最小充电低通时间系数。Among them, τ cur , τ max , τ min are the current discharge low-pass time coefficient, the maximum discharge low-pass time coefficient and the minimum discharge low-pass time coefficient, respectively; λ cur , λ max , λ min are the current charging low-pass time coefficient, Maximum charge low-pass time factor and minimum charge low-pass time factor. 2.根据权利要求1所述的一种基于低通充放电系数约束的混合储能控制方法，其特征在于，所述最大放电低通时间系数τmax和最小放电低通时间系数τmin的计算方法为：2. A hybrid energy storage control method based on low-pass charge-discharge coefficient constraints according to claim 1, wherein the calculation of the maximum discharge low-pass time coefficient τ max and the minimum discharge low-pass time coefficient τ min The method is: Iout_max＝k×SOCmax I out_max =k×SOC max 当蓄电池满电时，有：When the battery is fully charged, there are:
Figure FDA0002932660630000022
Figure FDA0002932660630000022
 当蓄电池电量不足SOCshortage时，有：When the battery is low in SOC shortage , there are:
Figure FDA0002932660630000023
Figure FDA0002932660630000023
 其中，SOCmax为蓄电池最大容量，k是用户定义蓄电池的放电倍数，取：0＜k≤3，Iout_max为蓄电池最大电流；SOCshortage为设定的蓄电池缺电时的电量，Vbat_shortage为蓄电池缺电时对应的电压，pdc_max、pbat_max、Vmax分别是系统最大输出功率、蓄电池最大输出功率和蓄电池最大电压，C为蓄电池出厂时标定的SOC最大值，s表示拉普拉斯算子。Among them, SOC max is the maximum capacity of the battery, k is the discharge multiple of the battery defined by the user, take: 0<k≤3, I out_max is the maximum current of the battery; SOC shortage is the set power when the battery is out of power, and V bat_shortage is the battery Corresponding voltage in case of power failure, p dc_max , p bat_max , V max are the maximum output power of the system, the maximum output power of the battery and the maximum voltage of the battery, C is the maximum SOC calibrated when the battery leaves the factory, and s is the Laplacian operator . 3.根据权利要求1所述的一种基于低通充放电系数约束的混合储能控制方法，其特征在于，所述最大充电低通时间系数λmax和最小充电低通时间系数λmin的计算方法如下：3. A hybrid energy storage control method based on a low-pass charge-discharge coefficient constraint according to claim 1, wherein the calculation of the maximum charging low-pass time coefficient λ max and the minimum charging low-pass time coefficient λ min Methods as below: 当蓄电池电量不足SOCshortage时，有最大充电电流Iin_max以及最小充电低通时间系数λmin：When the battery is low in SOC shortage , there is a maximum charging current I in_max and a minimum charging low-pass time coefficient λ min : Iin_max＝k×SOCmax/10I in_max =k×SOC max /10
Figure FDA0002932660630000024
Figure FDA0002932660630000024
 当蓄电池电量充足时，有最小充电电流Iin_min和最大充电低通时间系数λmax：When the battery is fully charged, there are the minimum charging current I in_min and the maximum charging low-pass time coefficient λ max : Iin_min＝k×SOCmax/200I in_min =k×SOC max /200
Figure FDA0002932660630000031
Figure FDA0002932660630000031
 其中，SOCshortage为设定的蓄电池缺电时的电量，SOCenough为设定的蓄电池足电时的电量,指80％以上电量为足电，20％以下电量为不足电量，即0＜SOCshortage＜0.2SOCmax＜SOCenough＜0.8SOCmax；Vbat_shortage、Vbat_enough分别为蓄电池缺电和足电时对应的电压；Iin_max、Iin_min分别为蓄电池最大、最小充电电流，pdc_max是系统最大输出功率。Among them, SOC shortage is the set power when the battery is short of power, SOC enough is the set power when the battery is fully charged, which means that more than 80% of the power is full power, and less than 20% of the power is insufficient power, that is, 0 < SOC shortage ＜0.2SOC max ＜SOC enough ＜0.8SOC max ; V bat_shortage and V bat_enough are the corresponding voltages when the battery is short of power and full power, respectively; I in_max and I in_min are the maximum and minimum charging currents of the battery, respectively, and p dc_max is the maximum output of the system power.
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