CN116031864A - Power allocation strategy for energy storage system based on improved SOC balance - Google Patents

Abstract

The invention discloses an energy storage system power distribution strategy based on improved SOC balance, which mainly comprises a consistency control module, an improved SOC balance module, a virtual voltage drop balance module, a voltage compensation module and a voltage and current double-loop control module. Through the consistency control module, each energy storage unit only needs to exchange information with adjacent communication nodes, the average value of the SOC, the virtual voltage drop and the like of the energy storage system can be obtained without a central controller, the local information of the SOC, the virtual voltage drop and the like is respectively combined with the average value of the SOC and the virtual voltage drop of the energy storage system through the SOC equalizer and the virtual voltage drop equalizer, the SOC equalization and the current accurate distribution of the energy storage units with different capacities in the direct current micro-grid are realized, and the voltage compensation module is introduced in the improved droop control, so that the output voltage of the energy storage system is maintained within the rated voltage range, and the stability of the system is ensured.

Description

Power allocation strategy of energy storage system based on improved SOC balance

Technical Field

The present invention relates to the field of power distribution of a DC microgrid distributed energy storage system, and in particular to a power distribution strategy of an energy storage system based on improved SOC balance.

Background Art

In recent years, DC microgrids have attracted widespread attention due to their reliability, scalability and high efficiency. Compared with AC microgrids, DC microgrids have many advantages. They can effectively access distributed power sources such as photovoltaics, energy storage and fuel cells that are essentially DC-based, and do not need to consider issues such as phase, frequency and reactive power. The control is relatively simple and has broad application prospects. In order to meet the electricity demand in remote areas such as islands and mountainous areas, a variety of energy sources can be used to form independent DC microgrids. Independent DC microgrids need to be equipped with energy storage units of a certain capacity to absorb excess energy from renewable energy or to compensate for insufficient output of renewable energy. In order to meet the power level requirements of the microgrid, multiple energy storage units are often required to be configured in parallel to form a distributed energy storage system, in which the capacity of each energy storage unit may be inconsistent. In a distributed energy storage system, the energy storage unit is connected to the DC bus through a bidirectional DC-DC converter, and its charging and discharging process is controlled by a bidirectional DC-DC converter. In order to avoid the imbalance of the state of charge (SOC) of each energy storage unit, which may lead to overcharging or over-discharging and thus affect the life of the energy storage unit and the stability of the microgrid, it is necessary to coordinate the output current and SOC of the energy storage unit to ensure that the output current of each energy storage unit is accurately distributed according to the capacity ratio and the SOC is balanced.

To achieve the above purpose, the technical solution provided by the present invention is:

1) In the consistency control module, the state of charge SOC _i and the virtual voltage drop V _i of each energy storage unit in the energy storage system are detected, and the average state of charge SOC _avg and the average virtual voltage drop V _avg of the energy storage system are obtained after the consistency algorithm. The expression of the consistency algorithm is:

In the formula, each energy storage unit is regarded as a node, _Xi (k) = [ _SOCavgi (k), _Vavgi (k)], _Xi (k+1) = { _SOCavgi (k+1), _Vavgi (k+1)] are the estimated values of the average value of the whole network data of node i at the kth and k+1th iterations, respectively, _Xj (k) = [ _SOCavgj (k), _Vavgj (k)] is the estimated value of the average value of the whole network data of node j at the kth iteration, _Dij (k) and _Dij (k+1) are the cumulative difference between the estimated values of node i and node j at the kth and k+1th iterations, respectively, _Ni is the set of nodes connected to node i, ε represents a constant weight related to the communication topology, _aij represents the connection status between the i-th node and the j-th node, aij = 1 means that adjacent nodes are connected to each other, and _aij = 1 means that adjacent nodes are connected to each other _. =0 means that the node is not connected. Under the action of the dynamic consistency algorithm, the state of charge iteration value SOC _avgi and the virtual voltage drop iteration value V _avgi of each energy storage unit will converge to the state of charge average value SOC _avg and the virtual voltage drop average value V _avg of the energy storage system respectively; the initial difference accumulation _Dij (0) = [0, 0, 0] between the estimated values of node i and node j, and the value range of the constant weight ε is 0 < ε ≤ 0.5.

2) In the improved SOC balancing module, the average state of charge SOC _avg of the energy storage system is divided by the state of charge SOC _i of the energy storage unit, and then the coefficient 1 is subtracted to obtain the control coefficient α _i . The control coefficient α _i is taken as the inverse power of the balancing adjustment coefficient n, and then the coefficient 1 is added. The result is multiplied by the initial value of the droop coefficient R _oi of the local energy storage unit to obtain the adjusted droop coefficient R _i of the local energy storage unit. That is, the expression of the adjusted droop coefficient R _i is:

其中C_i为第i台储能单元的额定容量。The value range of the balance adjustment coefficient n is 5≤n≤49 and n is an odd number. The value requirement of the initial value of the droop coefficient R _oi is,

Where _Ci is the rated capacity of the i-th energy storage unit.

3) In the virtual voltage drop balancing module, the adjusted droop coefficient _Ri is multiplied by the output current _Ii of the local energy storage unit to obtain the virtual voltage drop _Vi of the local energy storage unit. The virtual voltage drop average value _Vavg of the energy storage system and the virtual voltage drop _Vi of the local energy storage unit are subtracted to obtain the virtual voltage drop error _ΔVi . After the virtual voltage drop error _ΔVi is adjusted by the PI controller _GPI1 (s) of the virtual voltage drop balancing link, the output current distribution accuracy compensation amount Δu _Ii is obtained.

4) In the voltage compensation module, the difference between the bus voltage reference value V _ref and the output bus voltage V _bus of the energy storage system is adjusted by the voltage compensation link PI controller G _PI2 (s) to generate a voltage compensation value Δu _Vi to compensate for the bus voltage drop. The bus voltage reference value V _ref is subtracted from the virtual voltage drop _Vi of the local energy storage unit, and the current distribution accuracy compensation value Δu _Ii and the voltage compensation value Δu _Vi are added to obtain the output capacitor voltage reference value V _refi after the virtual impedance is introduced.

5) In the voltage-current dual-loop control module, the output capacitor voltage reference value V _refi after the introduction of virtual impedance is subtracted from the output capacitor voltage V _ci of the local energy storage unit and then passed through the voltage loop PI controller G _PI3 (s) to obtain the reference current I _refi , which is subtracted from the output inductor current I _Li of the local energy storage unit and then passed through the current loop PI controller G _PI4 (s) to obtain the driving voltage _{u si ,} which is then compared with the triangular carrier to obtain the modulation signal.

Compared with the prior art, the principles and advantages of this solution are as follows:

The present invention discloses a power distribution strategy for an energy storage system based on improved SOC balancing, which mainly includes a consistency control module, an improved SOC balancing module, a virtual voltage drop balancing module, a voltage compensation module and a voltage-current dual-loop control module. Through the consistency control module, each energy storage unit only needs to exchange information with adjacent communication nodes, and the average values of the SOC, virtual voltage drop and the like of the energy storage system can be obtained without a central controller. Through the SOC equalizer and the virtual voltage drop equalizer, the local SOC, virtual voltage drop and other information are respectively combined with the SOC and virtual voltage drop average values of the energy storage system, thereby realizing SOC balancing and current precise distribution of energy storage units with different capacities in a DC microgrid, and introducing a voltage compensation module in the improved droop control, so that the output voltage of the energy storage system is maintained within the rated voltage range, thereby ensuring the stability of the system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a main circuit diagram of a power allocation strategy for an energy storage system based on improved SOC balancing according to an embodiment of the present invention;

FIG2 is a control block diagram of a power allocation strategy for an energy storage system based on improved SOC balancing in an embodiment of the present invention;

FIG3 is a SOC waveform diagram of a conventional control strategy in an embodiment of the present invention;

FIG4 is a SOC waveform diagram of an improved control strategy according to an embodiment of the present invention;

FIG5 is an output current waveform diagram of a conventional control strategy according to an embodiment of the present invention;

FIG6 is an output current waveform diagram of an improved control strategy according to an embodiment of the present invention;

FIG7 is a bus voltage waveform diagram of a conventional control strategy in an embodiment of the present invention;

FIG. 8 is a bus voltage waveform diagram of the improved control strategy in an embodiment of the present invention.

DETAILED DESCRIPTION

The present invention will be further described below in conjunction with specific embodiments:

FIG1 shows the main circuit diagram of the power allocation strategy of the energy storage system based on improved SOC balancing. The energy storage system is composed of j energy storage units connected in parallel through a DC-DC converter, where i=1, 2, …, j, DESU _i is any energy storage unit, V _ci is the output capacitor voltage, I _i is the output current, R _linei is the corresponding line impedance, and R _load is the load resistance.

FIG2 shows a control block diagram of a power allocation strategy for an energy storage system based on improved SOC balancing, which includes the following steps:

In the consistency control module, the state of charge SOC _i and the virtual voltage drop V _i of each energy storage unit in the energy storage system are detected, and the average state of charge SOC _avg and the average virtual voltage drop V _avg of the energy storage system are obtained after the consistency algorithm. The expression of the consistency algorithm is:

In the formula, each energy storage unit is regarded as a node, _Xi (k) = [ _SOCavgi (k), _Vavgi (k)], _Xi (k+1) = [ _SOCavgi (k+1), _Vavgi (k+1)] are the estimated values of the average value of the whole network data of node i at the kth and k+1th iterations, respectively, _Xj (k) = [ _SOCavgj (k), _Vavgj (k)] is the estimated value of the average value of the whole network data of node j at the kth iteration, _Dij (k) and _Dij (k+1) are the cumulative difference between the estimated values of node i and node j at the kth and k+1th iterations, respectively, _Ni is the set of nodes connected to node i, ε represents a constant weight related to the communication topology, _aij represents the connection status between the i-th node and the j-th node, _aij = 1 means that adjacent nodes are connected to each other, and _aij = 2 means that adjacent nodes are connected to each other. =0 means that the node is not connected. Under the action of the dynamic consistency algorithm, the state of charge iteration value SOC _avgi and the virtual voltage drop iteration value V _avgi of each energy storage unit will converge to the state of charge average value SOC _avg and the virtual voltage drop average value V _avg of the energy storage system respectively; the initial difference accumulation _Dij (0) = [0, 0, 0] between the estimated values of node i and node j, and the value range of the constant weight ε is 0 < ε ≤ 0.5.

In the improved SOC balancing module, the average state of charge SOC _avg of the energy storage system is divided by the state of charge SOC _i of the energy storage unit, and then the coefficient 1 is subtracted to obtain the control coefficient α _{i . The control coefficient α i is} taken as the inverse power of the balancing adjustment coefficient n, and then the coefficient 1 is added. The result is multiplied by the initial value of the droop coefficient R _oi of the local energy storage unit to obtain the adjusted droop coefficient R _i of the local energy storage unit. That is, the expression of the adjusted droop coefficient R _i is:

其中C_i为第i台储能单元的额定容量。The value range of the balance adjustment coefficient n is 5≤n≤49 and n is an odd number. The value requirement of the initial value of the droop coefficient R _oi is,

Where _Ci is the rated capacity of the i-th energy storage unit.

In the virtual voltage drop balancing module, the adjusted droop coefficient _Ri is multiplied by the output current _Ii of the local energy storage unit to obtain the virtual voltage drop _Vi of the local energy storage unit. The virtual voltage drop average value _Vavg of the energy storage system and the virtual voltage drop _Vi of the local energy storage unit are subtracted to obtain the virtual voltage drop error _ΔVi . After the virtual voltage drop error _ΔVi is adjusted by the PI controller _GPI1 (s) of the virtual voltage drop balancing link, the output current distribution accuracy compensation amount Δu _Ii is obtained.

In the voltage compensation module, the difference between the bus voltage reference value V _ref and the output bus voltage V _bus of the energy storage system is adjusted by the voltage compensation link PI controller G _PI2 (s) to generate a voltage compensation amount Δu _Vi to compensate for the bus voltage drop. The bus voltage reference value V _ref is subtracted from the virtual voltage drop _Vi of the local energy storage unit, and the current distribution accuracy compensation amount Δu _Ii and the voltage compensation amount Δu _Vi are added to obtain the output capacitor voltage reference value V _refi after the virtual impedance is introduced.

In the voltage-current dual-loop control module, the output capacitor voltage reference value V _refi after the introduction of virtual impedance is subtracted from the output capacitor voltage V _ci of the local energy storage unit and then passed through the voltage loop PI controller G _PI3 (s) to obtain the reference current I _refi , which is subtracted from the output inductor current I _Li of the local energy storage unit and then passed through the current loop PI controller G _PI4 (s) to obtain the driving voltage u _si , which is _then compared with the triangular carrier to obtain the modulation signal.

Figures 3 and 4 are the SOC waveforms of the traditional control strategy and the improved control strategy, respectively. The energy storage system consists of four energy storage units with different capacities, and the capacity ratio is C ₁ ∶ _{C 2} ∶ _{C 3} ∶ _{C 4} ＝1.5∶1.5∶1∶1. The initial values of the droop coefficients of the four energy storage units are set in proportion to the inverse of the capacity. Therefore, the initial droop coefficients of each energy storage unit R _oi satisfy R _o1 ∶ _{R o2} ∶ _{R o3} ∶ R _o4 ＝1∶1∶1.5∶1.5, and the actual values are 1/3, 1/3, 0.5, and 0.5, respectively. The initial SOCs are 90%, 85%, 83%, and 87%, respectively. The line impedances of the four energy storage units are 0.50Ω, 0.60Ω, 0.54Ω, and 0.40Ω, respectively. The bus voltage reference value V _ref ＝400V, and the balancing adjustment coefficient n＝7. Under the traditional control strategy, among the four energy storage units, the energy storage units with the same capacity and the same initial droop coefficient have always remained parallel, the SOC difference has always remained unchanged, and the SOC values of the four energy storage units have not reached consistency at the end of the simulation. Under the improved control strategy, for energy storage units with larger SOC initial values, the faster they discharge, the faster their SOC decreases. For energy storage units with smaller SOC initial values, the slower they discharge, the slower their SOC decreases. When the simulation time reaches 2.82 seconds, the SOCs of the four energy storage units are equal, and have been decreasing at the same rate since then, reaching a dynamic balance.

Figures 5 and 6 are the output current waveforms of the traditional control strategy and the improved control strategy, respectively. Under the traditional control strategy, the output currents of the four energy storage units are 8.67A, 7.77A, 6.95A, and 8.05A, respectively. During the simulation, the difference in output current remains unchanged, and the current cannot be distributed in proportion to the capacity of the energy storage unit. Under the improved droop control strategy, the larger the capacity of the energy storage unit, the larger its output current. As the discharge time increases, the output current of the energy storage unit with the same capacity and the same initial droop coefficient slowly approaches and reaches equilibrium at 3.06 seconds. At this time, the output currents of the four energy storage units are 9.6A, 9.6A, 6.4A, and 6.4A, respectively, satisfying 1.5:1.5:1:1. As the simulation progresses, each energy storage unit maintains an output current at equilibrium.

Figures 7 and 8 are the output bus voltage waveforms of the traditional control strategy and the improved control strategy, respectively. Under the traditional droop control, the bus voltage is only 393V, which is due to the introduction of virtual impedance, so the bus voltage has a 7V drop compared to the reference voltage. Under the improved droop control strategy, the bus voltage is 400V, which is due to the introduction of the voltage compensation module, which eliminates the drop of the bus voltage.

The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, all changes made according to the shape and principle of the present invention should be included in the protection scope of the present invention.

Claims (3)

1. A power allocation strategy for an energy storage system based on improved SOC balance, characterized in that it comprises the following steps: 1) In the consistency control module, the state of charge SOC _i and the virtual voltage drop V _i of each energy storage unit in the energy storage system are detected, and the average state of charge SOC _avg and the average virtual voltage drop V _avg of the energy storage system are obtained after the consistency algorithm. The expression of the consistency algorithm is:

In the formula, each energy storage unit is regarded as a node, _Xi (k) = [ _SOCavgi (k), _Vavgi (k)], _Xi (k+1) = [ _SOCavgi (k+1), _Vavgi (k+1)] are the estimated values of the average value of the whole network data of node i at the kth and k+1th iterations, respectively, _Xj (k) = [ _SOCavgj (k), _Vavgj (k)] is the estimated value of the average value of the whole network data of node j at the kth iteration, _Dij (k) and _Dij (k+1) are the cumulative difference between the estimated values of node i and node j at the kth and k+1th iterations, respectively, _Ni is the set of nodes connected to node i, ε represents a constant weight related to the communication topology, _aij represents the connection status between the i-th node and the j-th node, _aij = 1 means that adjacent nodes are connected to each other, and _aij = 2 means that adjacent nodes are connected to each other. =0 means the node is not connected. Under the action of the dynamic consistency algorithm, the state of charge iteration value SOC _avgi and the virtual voltage drop iteration value V _avgi of each energy storage unit will converge to the state of charge average value SOC _avg and the virtual voltage drop average value V _avg of the energy storage system respectively; 2) In the improved SOC balancing module, the average state of charge SOC _avg of the energy storage system is divided by the state of charge SOC _i of the energy storage unit, and then the coefficient 1 is subtracted to obtain the control coefficient α _i . The control coefficient α _i is taken as the inverse power of the balancing adjustment coefficient n, and then the coefficient 1 is added. The result is multiplied by the initial value of the droop coefficient R _oi of the local energy storage unit to obtain the adjusted droop coefficient R _i of the local energy storage unit. That is, the expression of the adjusted droop coefficient R _i is:

3) In the virtual voltage drop balancing module, the adjusted droop coefficient _Ri is multiplied by the output current _Ii of the local energy storage unit to obtain the virtual voltage drop _Vi of the local energy storage unit. The virtual voltage drop average value _Vavg of the energy storage system and the virtual voltage drop _Vi of the local energy storage unit are subtracted to obtain the virtual voltage drop error _ΔVi . After the virtual voltage drop error _ΔVi is adjusted by the virtual voltage drop balancing link PI controller _GPI1 (s), the output current distribution accuracy compensation amount Δu _Ii is obtained; 4) In the voltage compensation module, the difference between the bus voltage reference value V _ref and the energy storage system output bus voltage V _bus is adjusted by the voltage compensation link PI controller G _PI2 (s) to generate the voltage compensation value

To compensate for the bus voltage drop, the bus voltage reference value V _ref is subtracted from the virtual voltage drop _Vi of the local energy storage unit, and then the current distribution accuracy compensation Δu _Ii and the voltage compensation are added.

Obtaining an output capacitor voltage reference value V _refi after introducing virtual impedance; 5) In the voltage-current dual-loop control module, the output capacitor voltage reference value V _refi after the introduction of virtual impedance is subtracted from the output capacitor voltage V _ci of the local energy storage unit and then passed through the voltage loop PI controller G _PI3 (s) to obtain the reference current I _refi , which is subtracted from the output inductor current I _Li of the local energy storage unit and then passed through the current loop PI controller G _PI4 (s) to obtain the driving voltage _{u si} , which is then compared with the triangular carrier to obtain the modulation signal. 2. The power allocation strategy of the energy storage system based on improved SOC balance according to claim 1 is characterized in that, in step 1), the initial difference accumulation amount _Dij (0) of the estimated values of node i and node j is [0, 0, 0], and the value range of the constant weight ε is 0＜ε≤0.5. 3. The power allocation strategy of the energy storage system based on improved SOC balance according to claim 1 is characterized in that, in step 2), the value range of the balance adjustment coefficient n is 5≤n≤49 and n is an odd number, and the value requirement of the initial value of the droop coefficient R _oi is,

Where _Ci is the rated capacity of the i-th energy storage unit.

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