CN108306339B - Energy management hierarchical control method for light-storage-combustion direct current power supply system - Google Patents
Energy management hierarchical control method for light-storage-combustion direct current power supply system Download PDFInfo
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H02J3/385—
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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
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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
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- 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
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Abstract
The invention relates to an energy management hierarchical control method of a light-storage-combustion direct current power supply system, which comprises the following steps: 1) and (3) carrying out upper-layer control design of energy management: defining the energy E in the DC bus capacitor of the systemBusFor smoothing the output variable, the DC bus voltage vBusFor state variables, total load current reference trace pHPSorefDesigning a nonlinear differential smoothing controller and a feedback control law for controlling variables, so as to realize the stable control of the DC bus voltage and obtain a total load current reference track required by lower-layer control; 2) and (3) carrying out lower-layer control design of energy management: according to a simplified dynamic system formed by a super capacitor, a storage battery and a fuel cell converter, a prediction control model is constructed to realize reasonable distribution of power among all power supplies. Compared with the prior art, the invention has the advantages of layered control, stability, margin, large degree of freedom, simple structure and the like.
Description
Technical Field
The invention relates to the field of energy management control, in particular to an energy management hierarchical control method of a light-storage-combustion direct-current power supply system.
Background
Photovoltaic power generation has intermittent, random deficiencies, and it is difficult for fuel cells to respond quickly to photovoltaic power generation and power load transients due to slow internal electrochemical and thermodynamic reactions. In order to further improve the power supply quality, a light-storage-combustion direct current power supply system formed by combining a super capacitor and a storage battery can smooth the fluctuation of the photovoltaic output power and improve the power supply reliability. Aiming at a light-storage-combustion direct-current power supply system consisting of photovoltaic cells, fuel cells, storage batteries and super capacitors, the key point for further popularization and application of the hybrid direct-current power supply system is to realize coordination control and energy optimal distribution among power supplies.
When the existing energy management method is applied to a light-storage-combustion direct-current power supply system with the characteristic of multiple power supplies, the quick dynamic response, high stability and robustness are difficult to realize at the same time. The model prediction control method utilizes the system model to predict future control input and object response, can solve the optimal control law in a rolling mode according to given performance requirements, has flexible multi-input multi-output processing capacity, and is simple in structure and excellent in dynamic response performance. The reasonable distribution of the power among multiple power supplies of the hybrid direct-current power supply system can be realized by utilizing model predictive control. In current research work, a linear PI controller is usually combined to realize voltage stabilization of a direct current bus and system coordination control. The traditional PI controller is generally designed to be linearly controlled based on a specific working point, and when photovoltaic output fluctuates rapidly or system parameters are disturbed, the problem that the performance of a control system is difficult to guarantee can occur. Different from the traditional PI control method, the nonlinear differential smooth control method completely describes the state quantity and the control quantity of the system through an expected smooth output track, avoids approximate processing, directly compensates nonlinear components, has a simple structure, can inhibit the high-frequency unmodeled part and internal and external disturbance of the system, has wide stable domain and strong robustness, and makes great progress in the aspect of converter stable control in recent years. However, the existing nonlinear smooth microminiature method is difficult to complete the task of optimal power distribution among multiple power supplies under the limitation of the charge-discharge rate of the energy storage unit while realizing the stable control of the fuel cell and the energy storage unit. Therefore, it is necessary to provide a simple and efficient control architecture and method, which can realize stable operation of multiple power supplies of the light-storage-combustion dc power supply system, and realize optimal energy distribution and management among the multiple power supplies in consideration of the requirement of limiting current charging and discharging rate in actual operation of the storage battery and the fuel cell.
Disclosure of Invention
The present invention aims to overcome the defects of the prior art and provide a hierarchical energy management control method for a light-storage-combustion dc power supply system.
The purpose of the invention can be realized by the following technical scheme:
a light-storage-combustion DC power supply system energy management hierarchical control method, the DC power supply system is composed of photovoltaic cell, storage battery, super capacitor, fuel cell, three-phase interleaved bidirectional converter and DC load, the storage battery and super capacitor are connected in parallel to DC bus through three-phase interleaved bidirectional converter, DC load is connected directly to DC bus, the method includes following steps:
1) and (3) carrying out upper-layer control design of energy management:
defining the energy E in the DC bus capacitor of the systemBusFor smoothing the output variable, the DC bus voltage vBusFor state variables, the total system load reference power pHPSorefDesigning a nonlinear differential smoothing controller and a feedback control law for controlling variables, so as to realize the stable control of the DC bus voltage and obtain a total load current reference track required by lower-layer control;
2) and (3) carrying out lower-layer control design of energy management:
according to a simplified dynamic system formed by a super capacitor, a storage battery and a fuel cell converter, a prediction control model and a performance index function are constructed, multi-stage optimization is carried out on the performance index function by adopting dynamic programming, and meanwhile, the current value of each power supply is quickly tracked with a reference current value by adopting hysteresis control, so that reasonable distribution of power among the power supplies is realized.
In step 1), the expression of the nonlinear differential smoothing controller is:
pHPSo＝pfco+psco+pbato
wherein the output variable y ═ EBusControl variable u ═ pHPSoref，EBusFor the system DC bus capacitive energy, pHPSorefFor the total load reference power, pfco、psco、pbatoPower output to the DC bus, p, from the fuel cell, the battery and the supercapacitor, respectivelypvoPower, v, output to the dc bus for the photovoltaic cellBus、iloadRespectively, the system DC bus voltage and the system DC load current, CBusFor the system DC bus output capacitance rHPSThe parallel static loss of the fuel cell converter, the storage battery converter and the super capacitor converter.
In the step 1), the feedback control law of the nonlinear differential smoothing controller is as follows:
wherein, K1、K2In order to be a parameter of the controller,
is the energy derivative of the direct current bus capacitance,
is a DC bus capacitance energy derivative reference value, yrefAnd the energy reference value of the direct current bus capacitor is shown, tau is a time integral variable, and t is a time integral upper limit.
In the step 2), the prediction control model of the lower layer control is as follows:
wherein:
wherein the state vector x ═ vfc vbat vsc ilastfcref ilastbatref ilastscref]TAnd control vector u ═ ifcref ibatref iscref]TThe output vector is y ═ vfc vbat vsc iHPSo difc dibat disc]T，ifcref、ibatref、iscrefReference currents, i, for fuel cells, batteries and supercapacitors, respectivelylastfcref、ilastbatref ilastscrefCurrent sample values di of the fuel cell, the battery and the supercapacitor at the previous momentfc、dibat、discFirst order differential of current, i, for fuel cell, battery and supercapacitor respectivelyHPSoFor the total load reference current, v, obtained by upper layer controlBusrefIs a reference value of the DC bus voltage of the system, Cfc、Cbat、CscThe capacitance values, t, of the fuel cell, the battery and the supercapacitor, respectivelysThe system sample time.
In step 2), the performance index function J (k, x) of the lower layer control is:
wherein:
wherein Q is a non-negative definite symmetric weight matrix, R is a positive definite symmetric weight matrix,
is constant, k is the current time, Rifc、Ribat、RiscWeight values, Q, corresponding to the control vectors u, respectivelyvfc、Qvbat、Qvsc、Qiload、Qdifc、Qdibat、QdiscRespectively, the weight values corresponding to the output vector y.
In the step 2), multi-stage optimization from k to k + N is carried out on the performance index function J (k, x) by adopting dynamic programming to obtain an optimal N-stage control function uopt(k) Comprises the following steps:
K＝(2R+2DTQD+2BTPk+1B)-1(-2DTQC-2BTPk+1A)
M＝(2R+2DTQD+2BTPk+1B)-1(-2DTQ-BTZk+1)
where N is the prediction step size and K, M is the coefficient matrix.
Compared with the prior art, the invention has the following advantages:
the invention designs an energy management hierarchical control method, and from the stability perspective, the problems of narrow stability margin and small degree of freedom generated by a traditional control method based on a small signal model are effectively solved, the static/dynamic control performance is excellent, the anti-interference capability on an application object with wide power change range and large load disturbance is strong, and the problems of difficult design and complex structure caused by multi-parameter characteristics of the energy management control method in the existing hybrid power system are solved.
Drawings
Fig. 1 shows a distributed light-storage-combustion dc power supply system.
Fig. 2 shows a hierarchical control method for a light-storage-combustion dc power supply system.
Fig. 3 is a dynamic behavior model of super capacitor \ battery \ fuel cell.
Fig. 4 is a diagram of a dc load power waveform.
Fig. 5 is a waveform diagram of the output power of the photovoltaic cell.
FIG. 6 is a diagram of a super capacitor power waveform.
Fig. 7 is a waveform diagram of the charging and discharging power of the storage battery.
Fig. 8 is a waveform diagram of the output power of the fuel cell.
Fig. 9 is a dc bus voltage waveform diagram.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Example (b):
the invention provides an energy management layered control method of a light-storage-combustion direct-current power supply system, which is composed of a photovoltaic cell, a storage battery, a super capacitor, a fuel cell, an interleaved parallel converter and a direct-current load, and is shown in figure 1. System DC bus capacitor stored energy EbusExpressed as:
DC bus capacitance energy EBusThe derivative of (d) can be expressed as:
wherein:
photovoltaic cell output power ppvoAnd MPPT control is adopted to realize the maximum power output of the photovoltaic power generation power.
To realize the energy E in the DC bus capacitorBusAnd the output is smooth, the voltage of the direct current bus is ensured to be stable, and a total load current expected track is obtained. StatorMean smooth output variable y ═ EBusControl variable u ═ pHPSorefThe state variable x ═ vBusThen, as can be seen from equation (1), the state variable x can be expressed as:
as can be seen from equations (1) - (3), the control input variable u can be expressed as:
equations (3) to (4) are inverse dynamic equations, and the obtained total system load reference power pHPSorefDivided by the dc bus voltage vBusThat is to obtain the total load current expected track i processed in a non-approximate wayHPS。
In order to stabilize the DC bus voltage of the light-storage-combustion DC power supply system, a feedback control law is designed:
in the formula: k1、K2Are controller parameters.
The upper layer control method is shown in FIG. 2, and will obtain the total load current expected track i processed in a non-approximate wayHPSoAnd transmitting the data to a lower controller to realize stable coordination control of the system.
To achieve coordinated control of power between the light-storage-combustion systems in the lower layer, a model predictive controller is designed according to a simplified dynamic system shown in fig. 3. Will ilastfcref、ilastbatref、ilastscrefAs a state variable, smoothing with a current reference value; v is to befc、vbatAnd vscThe state of charge of the power supply is simply estimated and used as a state variable, the voltage of the power supply is kept unchanged, and the continuous and stable work of the system is ensured. To realize the power coordinated distribution of the super capacitor, the storage battery and the fuel cell, i is selectedfcref、ibatref、iscreAs a control variable. The set state vector, output vector, and control vector are as shown in equations (6) - (7):
x＝[vfc vbat vsc ilastfcref ilastbatref ilastscref]T (6)
u＝[ifcref ibatref iscref]T (7)
y＝[vfc vbat vsc ihps difc dibat disc]T (8)
the discrete control model is established as follows:
in order to make the output predicted value of the controlled object under the action of the controller at the future N moments as close as possible to a given expected value, and simultaneously restrain the drastic change of the control action. According to the system performance requirement, the following performance indexes are established by combining a state prediction model:
performing k-to-k + N multi-stage optimization on the performance index function J (k, x) by using dynamic programming, wherein k is the current moment, N is the predicted step length, and obtaining an N-step optimal control function uopt：
In the formula: and the coefficient matrixes K and M are obtained by updating and recursion through a Berman dynamic programming method.
Aiming at a storage battery, a super capacitor and a fuel cell converter, hysteresis loop control is adopted to enable the current value i of each power supply to be equalfc、ibat、iscFast tracking reference current value ifcref、ibatref、iscrefThe lower layer control method is shown in fig. 2.
In order to verify the feasibility and the effectiveness of a control method aiming at the design of an optical-storage-combustion direct-current power supply system, when the output power of a photovoltaic cell changes due to the fact that the load power changes in a simulation mode under an MATLAB/Simulink environment and illumination is suddenly changed under the influence of cloud layers, the conditions of smooth photovoltaic output power, stable direct-current bus voltage and coordinated distribution of the output power of each power supply are analyzed. The controller parameters, system parameter settings are shown in tables 1-2, respectively.
TABLE 1 controller parameters
TABLE 2 System Circuit parameters
Fig. 4-8 are waveforms of load power, photovoltaic output power, super capacitor charge-discharge power, energy storage battery charge-discharge power, and fuel cell output power, respectively. Fig. 9 is a dc bus voltage dynamic response waveform. As can be seen from fig. 4 to 8, in the initial state when t is 0s to 1s, the photovoltaic output power is 0, the discharge power of the super capacitor and the storage battery is 0W, and 326W required for the load power is supplied from the fuel cell.
1) When t is 1s, a sudden increase of the photovoltaic output power from 0W to 326W occurs, while the load demand power is increased from 163W to 326W, when the photovoltaic output power is equal to the load demand power, as shown in fig. 4-5. To quickly respond to power changes, power distribution among the power sources is coordinated. And when t is 1 s-5 s, the super capacitor is switched into a charging mode to bear the high-frequency part of system response and absorb the sudden power larger than the part of the power required by the load. The impact on the storage battery and the fuel cell caused by sudden load change is reduced, and the dynamic response of the system is improved. In order to maintain the energy of the super capacitor and ensure the stable operation of the system, the super capacitor gradually releases the power absorbed this time, as shown in fig. 6. Since the storage battery bears the low-frequency part of the system response, after the super capacitor completes the transient response, the part of the super capacitor greater than the load power demand is absorbed by the storage battery, and the maximum charging power is reached when t is 2s, as shown in fig. 7. Since the photovoltaic output power is equal to the load power and the fuel cell physically reacts slower than the battery, the fuel cell output power gradually decreases and decreases to zero after t is 4s, and the system enters into steady-state operation as shown in fig. 8.
2) When t is 5s, the photovoltaic output power is suddenly reduced from 326W to 163W, the load power is suddenly reduced from 326W to 0W, the photovoltaic output power is greater than the load demand power, and the fuel cell output power, the storage battery charge-discharge power and the super capacitor charge-discharge power are all zero, as shown in fig. 4-5. And when t is 5 s-8 s, the super capacitor is switched into a charging mode to absorb the sudden power of the part which is larger than the power required by the load. After the super capacitor completes transient response, the part of the super capacitor larger than the power required by the load is absorbed by the storage battery, and the maximum charging power is reached when t is 6 s. Since the photovoltaic output power is greater than required by the load power during this time, the fuel cell output power remains zero. The photovoltaic output power continuously charges the storage battery, photovoltaic energy storage is realized, and the system enters steady-state operation.
Simulation results fig. 9 shows: when the system generates illumination and load sudden change, the upper layer controls to quickly respond to power change, and coordinates power distribution among all power supplies through the lower layer control, so that the direct-current bus voltage is quickly recovered to be stable and always kept at 70V, and the correctness and feasibility based on a differential smooth control method are verified; simulation results fig. 4-8 show that: the required load demand is obtained through the upper layer control, current reference values of different charging and discharging rates of each power supply are given through the lower layer control according to the charging and discharging characteristics of each power supply, and coordinated distribution control of power among the power supplies under the condition that step change occurs in photovoltaic output power and load demand power is realized; simulation results fig. 7 shows: under the charge-discharge rate constraint condition, the storage battery has quick response and is effectively matched with the super capacitor and the fuel cell, so that the impact of repeated charge-discharge on the battery is avoided, and the service life is prolonged.
Claims (5)
1. The energy management hierarchical control method of a light-storage-combustion direct current power supply system is characterized by comprising the following steps of:
1) and (3) carrying out upper-layer control design of energy management:
defining the energy E in the DC bus capacitor of the systemBusFor smoothing the output variable, the DC bus voltage vBusFor state variables, the total system load reference power pHPSorefDesigning a nonlinear differential smoothing controller and a feedback control law for controlling variables, wherein the nonlinear differential smoothing controller and the feedback control law are used for realizing the stable control of the direct-current bus voltage and simultaneously acquiring a total load current reference track required by lower-layer control, and the expression of the nonlinear differential smoothing controller is as follows:
pHPSo＝pfco+psco+pbato
wherein the output variable y ═ EBusControl variable u ═ pHPSoref，EBusFor the system DC bus capacitive energy, pHPSorefFor the total load reference power, pfco、psco、pbatoPower output to the DC bus, p, from the fuel cell, the battery and the supercapacitor, respectivelypvoPower, v, output to the dc bus for the photovoltaic cellBus、iloadRespectively, the system DC bus voltage and the system DC load current, CBusFor the system DC bus output capacitance rHPSThe parallel static loss of the fuel cell converter, the storage battery converter and the super capacitor converter is obtained;
2) and (3) carrying out lower-layer control design of energy management:
according to a simplified dynamic system formed by a super capacitor, a storage battery and a fuel cell converter, a prediction control model and a performance index function are constructed, multi-stage optimization is carried out on the performance index function by adopting dynamic programming, and meanwhile, the current value of each power supply is quickly tracked with a reference current value by adopting hysteresis control, so that reasonable distribution of power among the power supplies is realized.
2. The energy management hierarchical control method of the light-storage-combustion direct current power supply system according to claim 1, wherein in the step 1), the feedback control law of the nonlinear differential smoothing controller is as follows:
wherein, K1、K2In order to be a parameter of the controller,
is the energy derivative of the direct current bus capacitance,
is a DC bus capacitance energy derivative reference value, yrefAnd the energy reference value of the direct current bus capacitor is shown, tau is a time integral variable, and t is a time integral upper limit.
3. The method as claimed in claim 1, wherein in the step 2), the predictive control model for the lower layer control is:
wherein:
wherein the state vector x ═ vfc vbat vsc ilastfcref ilastbatref ilastscref]TAnd control vector u ═ ifcrefibatref iscref]TThe output vector is y ═ vfc vbat vsc iHPSo difc dibat disc]T，ifcref、ibatref、iscrefReference currents, i, for fuel cells, batteries and supercapacitors, respectivelylastfcref、ilastbatref ilastscrefCurrent sample values di of the fuel cell, the battery and the supercapacitor at the previous momentfc、dibat、discFirst order differential of current, i, for fuel cell, battery and supercapacitor respectivelyHPSoFor the total load reference current, v, obtained by upper layer controlBusrefIs a reference value of the DC bus voltage of the system, Cfc、Cbat、CscThe capacitance values, t, of the fuel cell, the battery and the supercapacitor, respectivelysThe system sample time.
4. The method according to claim 3, wherein in the step 2), the performance index function J (k, x) of the lower layer control is:
wherein:
wherein Q is a non-negative definite symmetric weight matrix, R is a positive definite symmetric weight matrix,
is constant, k is the current time, Rifc、Ribat、RiscWeight values, Q, corresponding to the control vectors u, respectivelyvfc、Qvbat、Qvsc、Qiload、Qdifc、Qdibat、QdiscRespectively, the weight values corresponding to the output vector y.
5. The energy management hierarchical control method of the light-storage-combustion DC power supply system according to claim 4, characterized in that in the step 2), a multi-stage optimization from k to k + N is performed on the performance index function J (k, x) by using dynamic programming to obtain an optimal N-stage control function uopt(k) Comprises the following steps:
K＝(2R+2DTQD+2BTPk+1B)-1(-2DTQC-2BTPk+1A)
M＝(2R+2DTQD+2BTPk+1B)-1(-2DTQ-BTZk+1)
where N is the prediction step size and K, M is the coefficient matrix.
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| CN109149742B (en) * | 2018-10-17 | 2020-11-10 | 奇瑞汽车股份有限公司 | Composite power supply energy distribution method and device for fuel cell vehicle |
| CN109739107B (en) * | 2018-12-18 | 2022-03-18 | 西北工业大学 | Power buffer design method based on model predictive control |
| CN110048442B (en) * | 2019-04-29 | 2020-12-22 | 上海电力学院 | Differential smooth nonlinear control method and device for modular multilevel converter |
| CN110212514B (en) * | 2019-06-27 | 2023-04-28 | 上海电力学院 | Nonlinear control method of direct-current power spring based on differential smoothing theory |
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| JP2015164015A (en) * | 2014-02-28 | 2015-09-10 | 株式会社Ｎｔｔファシリティーズ | Direct-current feeding system, direct-current power supply device, and feeding control method |
| CN105305480A (en) * | 2015-07-13 | 2016-02-03 | 陕西省地方电力（集团）有限公司 | Hybrid energy-storage DC micro grid hierarchical control method |
| CN105305430A (en) * | 2015-11-06 | 2016-02-03 | 重庆大学 | Power quality promotion method of light storage power generation system based on hierarchical control |
| CN105656022A (en) * | 2016-03-14 | 2016-06-08 | 上海电力学院 | Nonlinear differential flatness control method for distributed type light storage direct-current power supply system |
| CN106208113A (en) * | 2016-07-12 | 2016-12-07 | 上海电力学院 | A kind of hybrid energy-storing hierarchical coordinative control method based on state-of-charge |
| CN107294122A (en) * | 2017-04-17 | 2017-10-24 | 国网浙江省电力公司电力科学研究院 | A kind of mixed energy storage system is layered dynamic control method |
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