CN111276960B - Energy storage module predictive control method in light-storage direct-current micro-grid system - Google Patents
Energy storage module predictive control method in light-storage direct-current micro-grid system Download PDFInfo
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Classifications
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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
- H02J1/00—Circuit arrangements for dc mains or dc distribution networks
- H02J1/14—Balancing the load in a network
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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
- H02J3/36—Arrangements for transfer of electric power between ac networks via a high-tension dc link
-
- 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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- 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
-
- 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
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/60—Arrangements for transfer of electric power between AC networks or generators via a high voltage DC link [HVCD]
Abstract
The invention discloses a predictive control method for an energy storage module in a light-storage direct-current micro-grid system, which belongs to the field of light-storage direct-current micro-grids. The lithium iron phosphate battery is used as an energy storage module of the direct-current micro-grid, and plays important roles in peak clipping, valley filling and bus voltage stabilization in the micro-grid. And determining the optimal working interval of the lithium iron phosphate battery through analysis of experimental characteristics such as open circuit voltage, polarization voltage, battery internal resistance and the like of the lithium iron phosphate battery. And predicting the state of charge of the lithium iron phosphate battery in a variable step length mode, and performing prediction control through prediction data, current data and an optimal working interval of the lithium iron phosphate battery, wherein a corresponding control strategy is formulated by comprehensively considering the stable operation of the light-storage direct current micro-grid and three-stage variable direct current load switching-in/switching-out. The invention ensures that the battery works in the optimal state of charge interval, prolongs the service life of the lithium iron phosphate battery, ensures the stability of the direct current micro-grid and reduces the maintenance cost of the system.
Description
Technical Field
The invention belongs to the field of light-storage direct current micro-grid systems, and particularly relates to a prediction control method for an energy storage module in a light-storage direct current micro-grid system.
Background
With the development of human society, energy has increased in importance as a basis for survival and development of human society. After industrial revolution, the development and utilization amount of non-renewable energy sources such as traditional primary energy sources, namely coal, petroleum, natural gas and the like are rapidly increased, and the environmental pollution problem is gradually serious, so that fossil energy sources available for exploitation are gradually exhausted. The electric energy is used as the most common and cleanest energy form at present and becomes a pulse for national economy development, but the current electric energy production mode is seriously dependent on traditional fossil fuel, so that a huge electric energy gap in the future world is caused. The method improves the energy utilization efficiency, develops new energy and strengthens the utilization of renewable energy, and is a necessary choice for solving the increasingly prominent energy demand increase and energy shortage in the economic and social development process of various countries and the contradiction between energy utilization and environmental protection. In order to solve the double crisis of energy exhaustion and environmental deterioration, the world is in the field of new energy. Aiming at the characteristics of intermittence and randomness of different renewable energy sources, the micro-grid technology solves the problem well, so the micro-grid technology is developed rapidly. In the micro-grid technology, a photovoltaic power generation system is used as a micro-grid with the most extensive application, the proportion of generated energy in all kinds of distributed micro-grids is larger, the patent provides a light-storage direct-current micro-grid prediction control technology, firstly, the stable operation of the light-storage direct-current micro-grid is guaranteed, secondly, the deep charging/deep discharging of a battery is avoided, the service life of the battery is prolonged, and finally, the operation and maintenance cost of the whole system is reduced through the stable operation of the light-storage direct-current micro-grid and the guarantee that the battery operates in an optimal state of charge.
For the control of the light-storage direct-current micro-grid system, literature (Miyang, wu Yanwei, fu Yang, et. Independent light-storage direct-current micro-grid hierarchical coordination control [ J ]. Electric power system protection and control, 2017 (8)) adopts a mode of hierarchical coordination self-adaptive control of the direct-current micro-grid to automatically distribute load power. The academic paper ([ 1] Zhang Kaitao ] the autonomous droop and model prediction control strategy research of the optical storage DC micro-grid converter [ D ] Shaanxi university of Western An technology, 2018.) introduces the model prediction control of the limited control set of the energy storage converter, and introduces a voltage compensation link and a feedback correction link to form closed-loop model prediction control. The literature (Zhang Xiaodong, wang Yu, litz, etc. the optical storage joint operation direct current micro grid control strategy [ J ]. The Guangdong power, 2018, 31 (2)) proposes a direct current micro grid operation control strategy for optical storage joint operation for stabilizing bus voltage. The patent literature (Bi Dajiang, fan Zhufeng, eastern light solution, etc. the island light storage direct current micro-grid autonomous control strategy [ J ]. Grid technology, 2015 (4)) designs a control strategy based on voltage amplitude aiming at the island light storage direct current micro-grid system. And setting the control strategy into different modes by taking the amplitude of the direct current bus voltage as a judging reference. Literature (Zhu Chengzhi, gongsheng, zhou Kaihe, etc.) provides a hierarchical distributed coordination control strategy applicable to photovoltaic-containing and energy-storing direct-current micro-grids for independent operation based on a hierarchical coordination control strategy [ J ] of an independent direct-current micro-grid of a consistency algorithm and an automated chemical report of the power system, 2018, 30 (1): 144-150 ]. In summary, the present optical storage dc micro-grid adopts hierarchical adaptive coordination control or droop control, and on one hand, the main purpose is to maintain the balance of the power of the system and the stability of the bus voltage of the system. The system operation cost and the maintenance cost are not considered simply from the safety operation of the whole system. On the other hand, the prediction method adopted for the charge state of the battery is not simple and feasible, and in engineering practice, the reaction speed of the power system to the system is generally required to be good, so that the method is simple, convenient, rapid and effective and is a main purpose of system control.
Disclosure of Invention
The invention aims to solve the technical problems that the running mode of the system is determined according to the change of the load energy consumption, the photovoltaic power generation amount and the energy storage module in the system according to the whole light-storage direct-current micro-grid aiming at the defects in the prior art, the stability of the system is maintained, the battery is ensured to run in an optimal working area, the service life is prolonged, and the maintenance cost of the whole system is reduced.
In order to achieve the above object, the present invention adopts the following technical scheme:
the predictive control method for the energy storage module in the light-storage direct-current micro-grid system specifically comprises the following steps:
step 1, collecting relevant data of each module of the whole light-storage direct current micro-grid system through a detection module;
step 2, acquiring data of a battery pack in the energy storage module, and judging states of each battery including a charging state, a discharging state and a cutting-out state;
step 3, dividing the battery into working state and static state according to the state of the battery, and carrying out [0, T ] on the battery pack in the working state L ]Battery state of charge during the time period;
step 4, fitting the battery state of charge data based on a least square method according to the collected battery history data of each battery after a period of operation, and predicting the battery state of charge at the next time point by adopting a variable step length prediction method; the battery history record data comprises the state of charge (SOC), voltage (U) and current (I) of the storage battery;
and 5, according to the relation among the generated energy of the photovoltaic array, the energy consumption of the load and the electric energy reserve of the energy storage module, combining the three-stage variable load and the predicted value of the state of charge of the battery, and formulating a corresponding direct-current micro-grid control method and an energy storage module control method.
As a further preferable scheme of the method for predicting and controlling the energy storage module in the light-storage direct-current micro-grid system, in step 1, the relevant data specifically include: (1) Power, voltage and current data generated by each photovoltaic array through the monitoring module; (2) The three-stage variable load side power consumption, voltage and current data, (3) the energy storage module consists of a group of mutually independent lithium iron phosphate batteries, each lithium iron phosphate battery has different numbers, and the working state, charging/discharging voltage and current of each battery and the state of charge of each battery are obtained, (4) bus voltage and current data.
In step 2, the collected data of each lithium iron phosphate battery in the energy storage module is classified according to the working states of the batteries into three types of charging states, discharging states and standby states, wherein the batteries in the charging states and the discharging states are called battery working states.
As a further preferable scheme of the prediction control method of the energy storage module in the light-storage direct-current micro-grid system, in the step 3, the intercepting time length of the lithium iron phosphate battery in the working state in the energy storage module is T L Battery state of charge data for a time period of [0, tl]。
As a further preferable scheme of the energy storage module prediction control method in the light-storage direct current micro-grid system, in step 4, the state of charge of the battery in the next step is predicted based on the least square method, and the method specifically comprises the following steps:
step 4.1, collecting [0, T ] L ]Data as a base data set S 1 At the same time set the error standard value delta rmse 、δ mad 、δ mape ；
Step 4.2, setting the initial predicted time step size T1 and the fluctuation amount T D (T D < 0.1T), the actual step size of the nth prediction is defined as T n ＝T 1 +x n-1 *T D ＝T n-1 ±T D ，(x n-1 ＝x z x j ，n-1＝z+j，x z Number of times of increase in fluctuation amount, x j Number of times of decrease in fluctuation amount) such that y=t n The time range of the first prediction is [ T ] L ，T L +T 1 ]Length of time of mth prediction [ T ] m-1 ，T m-1 ±T D ]；
Step 4.3, obtaining and storing the predicted data and the actual data of the nth period;
step 4.4, based on the predicted data and the actual data of the nth periodCalculating the error delta between the two rmsex 、δ madx 、δ mapex And compares the three error values with delta rmse 、δ mad 、δ mape If at least one of the relationships is greater than the error criterion value, return y=t n+1 ＝T n -T D If the three-phase errors are all smaller than the error standard value, return y=t n+1 ＝T n +T D Specifying that the predicted step size needs to be maintained atWithin the range, the prediction precision can be improved by changing the prediction step length, the prediction efficiency can also be improved, the predicted data volume can be reduced by reducing the step length prediction step length, and the prediction precision can be improved.
In step 5, according to the relation among the generated energy of the data photovoltaic system, the consumed load electric quantity and the electric energy reserve of the energy storage module, which are obtained by the monitoring module, the three-level variable load is combined to comprise a switchable direct current load, an adjustable direct current load, an important direct current load and a predicted value of the state of charge of a battery, and a corresponding direct current micro-grid control method and an energy storage module control method are formulated by referring to the rated capacity of the energy storage module;
wherein, in the light-storage direct current micro-grid, the specific steps are as follows:
the method comprises the following steps: when the generated energy of the photovoltaic system is larger than the consumed electric quantity of the load, namely the load cannot completely consume the electric energy generated by the photovoltaic, the electric energy which is not consumed is conveyed to the energy storage module, and when the energy storage module reaches the maximum rated capacity, the electric energy which cannot be consumed is discarded;
the second method is as follows: when the sum of the generated energy of the photovoltaic system and the electric quantity of the energy storage module is smaller than the consumption electric quantity of the direct current load and is larger than the important consumption of the direct current load and the controllable consumption of the direct current load, the switchable load is cut out to ensure the stability of the system, and meanwhile, the service life of the battery is prolonged to avoid deep charging and deep discharging of the battery; the working state of the battery is obtained through the monitoring module, and one-step predictive control and current state control are carried out on the storage battery according to the actual state of charge of the battery and the predicted state of charge of the battery;
wherein, the one-step predictive control is specifically as follows:
the method comprises the steps of firstly, collecting the charge state of a battery at the moment and the prediction state of the next step;
secondly, if D is more than 0, the battery is in a discharging state, if D is less than 0, the battery is in a charging state, and the next step of judgment is carried out according to the comparison of D and 0;
third, if D > 0, the lower bound SOC of the optimal control interval with the state of charge min Comparing, if D < 0, the upper bound SOC of the optimal control interval with the state of charge max Comparing, and determining the state of the battery in the next step;
fourth, if D > 0, SOC fore (k+1)＜SOC min When the battery is cut out and the rechargeable standby battery is cut in, if D is more than 0, SOC fore When (k+1) is more than SOCmin, the storage battery keeps a discharge state, makes up the deficiency of photovoltaic power generation capacity, provides power for a load, and stabilizes bus voltage; if D is less than 0, SOC fore (k+1)＞SOC max When the battery is cut out and discharged, the standby battery is cut in, if D is less than 0, SOC fore (k+1)＜SOC max When the battery is in a charged state, the generated energy of the photovoltaic battery which is not consumed by the load is consumed, the bus voltage is stabilized, and the charged state of the battery at the current moment is compared with the predicted charged state as a safeguard measure, and by judging whether the charged state of the battery at the current moment is in the optimal working state of the battery, the SOC (k) epsilon (SOC) min ，SOC max )，SOC min ＝20％，SOC max If the state of charge of the storage battery is in the optimal working state, the original charge and discharge state is maintained, the balance of the system is maintained, if the state of charge of the storage battery exceeds the optimal working state of the storage battery, the storage battery is cut out, compared with predictive control, the current time control has hysteresis, the performance of the storage battery can be influenced, but the deep charge/deep discharge of the storage battery caused by the occurrence of errors of predictive control in the predictive control can be effectively avoided;
and a third method: when the sum of the generated energy of the photovoltaic system and the electric quantity of the energy storage module is smaller than the load consumption electric quantity and larger than the important load consumption, the switchable load and the controllable load are cut out to ensure the stability of the system, so that the light-storage direct current micro-grid operates in the most basic operation state.
Compared with the prior art, the technical scheme provided by the invention has the following technical effects:
the predictive control technology of the light-storage direct-current micro-grid is used for determining a system operation control strategy by combining detection data of generated electricity quantity and electricity consumption quantity in the system with three-level variable loads and battery charge states. Three operating states are divided into scenario one: when the generated energy of the photovoltaic system is larger than the consumed electric quantity of the load, namely P PV ＞P Load When in use; scene II: when the sum of the generated energy of the photovoltaic system and the electric quantity of the energy storage module is smaller than the electric quantity consumed by the direct current load and is larger than the important direct current load consumption and the controllable direct current load consumption, namely P SLoad +P TLoad ＜P PV +P ESS ＜P Load When in use; scene III: when the sum of the generated energy of the photovoltaic system and the electric quantity of the energy storage module is smaller than the load consumption electric quantity and is larger than the important load consumption amount, namely P SLoad ＜P pV +P ESS ＜P Load When in use; combining three-stage variable load (switchable DC load, controllable DC load and important DC load) and optimal battery running state SOC (k) E (SOC) min ，SOC max ) Determining an operation mode of the system, the system can maintain stable, safe and economical operation of the whole light-storage direct current micro-grid according to a control strategy, the energy storage module can ensure the stability of the bus voltage of the system, and the electric quantity generated by the photovoltaic module can be consumed to the maximum extent through the combination of the three-stage variable direct current load and the energy storage module, so that the photovoltaic module can stably work in a maximum output state; the prediction control of the energy storage module predicts the charge state of the battery in advance, avoids the deep charge/deep discharge of the battery, ensures the battery to run in an optimal working area through the cut-in/cut-out between the backup batteries, prolongs the service life of the battery and reduces the maintenance cost of the whole light-storage direct current micro-grid system; the stable operation of the light-storage direct-current micro-grid system can reduce the consumption of traditional primary fossil energy, is energy-saving and environment-friendly, and can slowAnd the difficulty of inconvenient electricity utilization in remote areas is solved, and the investment cost of large power grid construction is reduced.
Drawings
Fig. 1 is a block diagram of the overall structure of an optical-storage direct-current micro-grid according to the present invention:
fig. 2 is a block diagram of a photovoltaic power generation structure of the present invention:
FIG. 3 is a simulation diagram of an optical storage DC micro-grid of the invention;
FIG. 4 is a simulation model of a photovoltaic cell of the present invention;
FIG. 5 is a Boost circuit topology of the present invention;
FIG. 6 is a control flow diagram of the fixed-step scrambling method of the present invention;
FIG. 7 is an MPPT simulation model of the disturbance observation method of the present invention;
fig. 8 is a Boost circuit of a photovoltaic cell in the MPPT control mode of the present invention;
FIG. 9 (a) is a photovoltaic array output current of the present invention;
fig. 9 (b) is a graph of the photovoltaic array output voltage of the present invention:
fig. 9 (c) is the photovoltaic array output power of the present invention;
fig. 10 is a schematic diagram of the operation of a lithium ion battery of the present invention;
fig. 11 is an equivalent circuit diagram of a lithium battery of the present invention:
FIG. 12 is a block-Boost bi-directional DC/DC converter architecture of the present invention;
FIG. 13 is a Boost mode equivalent circuit of the present invention;
fig. 14 is a Buck mode equivalent circuit of the present invention;
FIG. 15 is a simulation model of the Buck-Boost bi-directional DC/DC converter of the present invention:
FIG. 16 is a flow chart of the battery state of charge prediction of the present invention;
fig. 17 is a predicted curve and an actual curve based on the least square method of the present invention:
fig. 18 is a flowchart of the operation control of the optical-storage dc micro-grid according to the present invention:
fig. 19 (a) is a state of charge change diagram of the working battery SOC critical 20%, cut-out control, and battery backup cut-in control according to the present invention:
fig. 19 (b) is a state of charge change diagram of the working battery SOC critical 80%, cut-out control, and battery backup cut-in control according to the present invention;
Detailed Description
The technical solutions of the present invention will be further described in detail with reference to the accompanying drawings, in which examples of the embodiments are shown, wherein it will be understood by those skilled in the art that all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs unless otherwise defined. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The following describes a predictive control technology for an optical-storage DC micro-grid implemented by the invention with reference to the accompanying drawings.
As shown in fig. 1, the overall structure block diagram of the light-storage direct-current micro-grid is shown, and the overall structure block diagram of the light-storage direct-current micro-grid comprises 3 photovoltaic power generation systems, an energy storage module, a direct-current bus, three-stage variable direct-current loads (switchable direct-current loads, controllable direct-current loads and important direct-current loads) and a direct-current micro-grid control center.
As shown in fig. 2, the solar photovoltaic power generation system is a photovoltaic power generation structure block diagram, and is composed of a photovoltaic whole row, a Boost circuit, an inverter and a transformer.
The equivalent circuit of the photovoltaic cell is as follows:
wherein: i ph Is a photovoltaic array current; i o Is reverse saturation current; q is electron charge (1.6 x 10 -19 C) The method comprises the steps of carrying out a first treatment on the surface of the n is a diode factor; k is Boltzmann constant (1.38×10 -23 J/K); rs is a series resistance; r is R sh Is a parallel resistor;
in actual engineering practice, the mark is marked according to the manufacturerIn a quasi-state (irradiance S) B ＝1kW/m 2 Test parameters I for photovoltaic cell at cell temperature tb=25℃ sc ，V oc ，I m ，V m Modeling, two approximations are made on the basis of equation (1).
(1) Due to R sh Is very large, so (V+R) is ignored s I)/R sh An item;
(2) Rs is much smaller than the diode forward on-resistance, so suppose I sc ＝I ph 。
Based on the above assumptions, the photovoltaic cell I-V equation reduces to:
at the maximum power point
Resolvable C 1 ，C 2 Obtaining:
when there is a change in both the irradiation intensity and the cell temperature, I is recalculated sc_new ，V oc_new ，I m_new Then find C 1_new ，C 2-new The new I-V characteristic curve can be obtained:
ΔT＝T-T B (7)
V oc_new ＝V oc (1-cΔT)(1+bΔS) (8)
V m_new ＝V m (1-cΔT)(1+bΔS) (11)
where coefficients a, c take typical values: a=0.0025/°c; c= 0.00288/°c. The coefficient b adopts the optimized parameter value: b= -0.1949+7.056×10 -4 *S
According to the mathematical model formula, a photovoltaic cell simulation model is built on a MATLAB/simulink simulation platform, as shown in FIG. 4, wherein the input is illumination, temperature and working voltage respectively, and the output is current and power.
As shown in fig. 5, the photovoltaic array is in a Boost circuit topological structure, and a Boost chopper circuit is generally selected in an actual system, so that the photovoltaic array can be ensured to always work in a state with continuous input current, and the voltage can be boosted to ensure that the inverter works normally.
The boost chopper circuit operating principle assumes that the values of L and C are large. When V is in on state, the power supply E charges the inductor L, and the current is constant I 1 Capacitor C supplies power to load R and outputs voltage U o Constant. When V is in the off state, the power source E and the inductor L charge the capacitor C at the same time and supply energy to the load.
Basic quantitative relationship
When the circuit is operating in steady state, the energy accumulated by the inductor L in one period T is equal to the released energy, i.e
EI 1 t on ＝(U 0 -E)I 1 t off (12)
Simplifying and obtaining
T/T in the above off And (3) the duty ratio is equal to or greater than 1, and D is the duty ratio.
As shown in fig. 6, a control flow chart of the fixed-step scrambling method is shown; with respect to maximum power point tracking (maximum power point tacking, MPPT) control, the main objective is to guarantee that the photovoltaic array operates in a maximum power output state according to the volt-ampere characteristics of the photovoltaic array by using some control strategies so as to utilize solar energy to the maximum extent. The patent uses a disturbance observation based on a fixed step to track the maximum power of the photovoltaic cell. The principle of the fixed-step disturbance observation (Perturbation Observation) is to periodically apply a fixed-step disturbance DeltaU to the output voltage of the PV cell, and if the power becomes larger at the next moment, the original-direction disturbance is kept, otherwise, the negative disturbance is kept until the MPP is tracked. A workflow diagram of the fixed-step disturbance observation is shown in fig. 6. Wherein D is the duty ratio of the MOS tube of the driving Boost circuit, and Deltad is the fixed step size.
And constructing an MPPT simulation model shown in fig. 7 in MATLAB/simulink. Determining a disturbance step length, adding a hysteresis loop to realize disturbance of the algorithm, simulating a photovoltaic system model through step length value change, and finally obtaining that the step length is optimal in taking 0.0001 simulation effect.
As shown in fig. 8, the voltage Boost circuit of the photovoltaic cell in the MPPT control mode is shown; and changing the DC-DC conversion circuit, namely changing the duty ratio of PWM of a control device in the Boost circuit, so as to obtain optimal impedance matching, and finally realizing MPPT control. The photovoltaic cell is a current source model, and a controlled source is connected to the Iout port of the photovoltaic cell for realizing the butt joint with the electronic element. And a supporting capacitor of 330uf, an output capacitor of 1000uf and an inductance L of 3.2mH are connected in parallel at two ends of the photovoltaic cell. The delay link and the zero-order retainer of the MPPT sub-module are set to have sampling time of 0.0001s, the initial value of the duty ratio D is set to be 0.5, and the frequency of the triangular carrier wave in the PWM module is 5kHz and the amplitude is 1.
Setting the initial value of illumination intensity and temperature to be 1000W/m respectively 2 At 25℃with an illumination intensity of-300W/m at 0.6s and 1.4s, respectively 2 And a disturbance at +30 ℃, and finally simulating to obtain the photovoltaic array output current shown in fig. 9 (a); the photovoltaic array output voltage as shown in fig. 9 (b); the photovoltaic array outputs power as shown in fig. 9 (c).
As shown in fig. 10, a schematic diagram of the operation of the lithium ion battery is shown; lithium ion batteries are one type of useThe lithium ion intercalation and deintercalation performance between the positive and negative electrode materials realizes the secondary battery of charge and discharge. Lithium compound Li is adopted as positive electrode of lithium ion battery x CoO 2 ，LiFePO 4 ，Li x NiO 2 Or Li (lithium) x Mn 2 O 4 The negative electrode adopts a lithium-carbon interlayer compound Li x C 6 ,. The electrolyte is dissolved with Li x PF 6 ，Li x AsF 6 And the like. Among different types of lithium batteries, lithium iron phosphate batteries have received much attention due to the advantages of wide material sources, low cost, no pollution, and the like. Compared with other types of lithium batteries, the lithium iron phosphate has the advantages of good stability at high temperature, strong overcharge resistance, high safety in the use process, moderate working voltage, good voltage platform characteristic, very stable performance, good compatibility with most electrolyte systems, good energy storage, no memory effect, capability of charging with large current and the like. Accordingly, lithium iron phosphate batteries are selected herein as energy storage devices.
Charging and discharging chemical process of lithium iron phosphate battery
And (3) charging:
LiFePO 4 -xLi + -xe - →xFePO 4 +(1-x)LiFePO 4 (14)
the discharging process comprises the following steps:
FePO 4 +xLi + +xe - →xLiFePO 4 +(1-x)LiFePO 4 (15)
due to FePO 4 And LiFePO 4 Has a similar structure, and the olivine crystal structure is kept stable after repeated charge and discharge. Therefore, the lithium iron phosphate battery has excellent cyclic charge and discharge performance. The lithium ion battery takes metal lithium compound as a positive electrode material and graphite as a negative electrode material. During charging, li + The electrons are separated from the positive electrode, pass through the electrolyte and then are embedded into the negative electrode, and then reach the negative electrode from an external circuit, so that current is formed. During discharge, li + The electrons are separated from the negative electrode, pass through the electrolyte and then are embedded into the positive electrode, and the electrons reach the positive electrode from an external circuit to form current.
As shown in fig. 11, an equivalent circuit diagram of the lithium battery; according to the charge and discharge characteristics of the lithium iron phosphate battery, abstracting a general mathematical model of the lithium battery
Lithium battery discharge formula (i) * ＞0)
Lithium battery discharge formula (i) * ＜0)
Wherein:
E 0 : pressing, unit: v (V)
K: resistance, unit: omega shape
i * : area current, unit: a is that
i: cell current, unit: a is that
i t : capacity, unit: ah
Q: pool maximum capacity, unit: ah
A: exponential voltage, unit: v (V)
B: exponential capacity, unit: ah -1
The lithium iron phosphate battery has the advantages of high safety, long cycle life, high-current rapid charge and discharge, good high-temperature performance, high capacity, no memory effect and the like. There are many factors affecting the performance of lithium iron phosphate batteries, wherein the state of charge (SOC) of the battery is one of the main factors affecting the performance of the battery, and if the battery is often operated at an unreasonable SOC level, the service performance of the battery may be seriously affected, and the service life may be reduced. For example, the battery is overcharged and overdischarged, the battery aging is accelerated if the battery is light, the battery power is reduced, and the battery is gassing, failure and even fire if the battery is heavy. Experiments show that when the battery is overcharged in normal temperature environment, li in the battery + Can be largely removed to lead the generated FeP0 4 Increases, and the polarization resistance and polarization potential of the battery are sharply increased, so that the positive electrode material is irreversibly decomposed, and a large amount of heat and oxygen are released to accumulate in the battery, thereby causingThe battery bulges and deforms, so that the possibility of ignition and explosion of the battery is increased; when the battery is over-discharged, the performance of the battery cathode is damaged, an electrolyte interface film on the surface of the cathode is decomposed, a current collector copper foil is subjected to serious oxidation corrosion, the impedance of the cathode is increased, the polarization phenomenon is enhanced, and finally the battery is damaged or fails. The open circuit voltage, the polarization voltage and the internal resistance of the lithium iron phosphate battery are comprehensively researched, and the optimal charge state of the battery operation is finally determined to be 20% -80%.
As shown in fig. 12, the Buck-Boost bidirectional DC/DC converter structure; the bidirectional DC/DC converter can be divided into a bidirectional DC/DC converter with isolation and a bidirectional DC/DC converter without isolation according to whether input and output are isolated, and common structures are a Buck-Boost converter, a Cuk converter, a SEPIC converter and a Zeta converter. The bidirectional Dc/Dc converter with isolation uses transformer isolation, which increases cost, volume and weight, and the converter with isolation generates serious electromagnetic interference. The Buck-Boost converter has the characteristics of simple structure, wide voltage conversion coefficient variation range, mature technology, wide application and the like, so that the circuit structure is selected and changed in the patent. The Buck/Boost converter consists of an inductor L and a filter capacitor C 1 、C 2 Switching devices T1, T 2 And flywheel diode D 1 、D 2 Constitution, V 1 、V 2 The voltage of the low-voltage end and the voltage of the high-voltage end of the Buck/Boost converter are respectively. Fig. 13 is a Boost mode equivalent circuit; fig. 14 is a Buck mode equivalent circuit; FIG. 15 is a simulation model of a Buck-Boost bi-directional DC/DC converter.
FIG. 16 is a battery state of charge prediction flow chart; predicting the charge state of the battery at the next step based on a least square method, and collecting [0, T L ]Data as a base data set s 1 At the same time set the error standard value delta rmse 、δ mad 、δ mape The method comprises the steps of carrying out a first treatment on the surface of the Setting the size T of the initial predicted time step 1 Fluctuation amount T D (T D ＜0.1T 1 ) The actual step size of the nth prediction is defined as tn=t 1 +x n-1 *T D ＝T n-1 ±T D ，(x n-1 ＝x z -x j ，n-1＝z+j，x z Number of times of increase in fluctuation amount, x j Number of times of decrease in fluctuation amount), let y=t n Then the time frame of the first prediction is [ T ] L ，T L +T 1 ]The length of time for the mth prediction is [ T ] m-1 ，T m-1 ±T D ]The method comprises the steps of carrying out a first treatment on the surface of the Thirdly, obtaining and storing predicted data and actual data of an nth period; fourth step of predicting data SOC according to the nth period fore And actual data SOC real Calculating the error delta between the two rmsex 、δ madx 、δ mapex And compares the three error values with delta rmse 、8 mad 、δ mape If at least one of the relationships is greater than the error criterion value, return y=t n+1 ＝T n -T D If the three-phase errors are all smaller than the error standard value, return y=t n+1 ＝T n +T D Specifying that the predicted step size needs to be maintained atWithin the range. By changing the prediction step length, not only the prediction precision can be improved, but also the prediction efficiency can be improved, and by reducing the step length prediction step length, the predicted data volume can be reduced, and the prediction precision can be improved.
In the field of prediction of time-series data, the prediction effect is generally evaluated by three error indexes, namely, a root mean square error index, a mean absolute percentage error index, and a standard root mean square error index, which correspond to delta in the above formula rmsex 、δ madx 、δ mapex Three values.
Mathematical form of root mean square error index:
in the formula (1), the components are as follows,represents the true value of data, O p (n) represents a data prediction value, a represents data for performing predictionThe sequence start point, b, represents the end point of the data sequence at which prediction is performed.
Mathematical form of mean absolute error indicator:
mathematical form of mean absolute percentage error indicator:
as shown in fig. 17, a comparison of the predicted curve and the actual curve based on the least square method is shown.
As shown in fig. 18, a flowchart of the operation control of the light-storage dc micro-grid is shown; generating capacity P of data photovoltaic system obtained according to monitoring module PV Load consumption P Load And energy storage module electric energy reserve P ESS The relation between the two is combined with three-stage variable load (switchable DC load P RLoad Adjustable DC load P TLoad And an important DC load P SLoad ) And battery state of charge prediction value SOC fore Reference to the rated capacity P of the energy storage module RTESS And (5) formulating a corresponding direct-current micro-grid control strategy and an energy storage module control strategy. In an optical-storage direct current microgrid, strategy one: when the generated energy of the photovoltaic system is larger than the consumed electric quantity of the load, namely P PV ＞P Load When the load cannot completely consume the electric energy generated by the photovoltaic, the electric energy which is not consumed is transmitted to the energy storage module, and when the energy storage module reaches the maximum rated capacity, the electric energy which cannot be consumed is discarded; strategy II: when the sum of the generated energy of the photovoltaic system and the electric quantity of the energy storage module is smaller than the electric quantity consumed by the direct current load and is larger than the important direct current load consumption and the controllable direct current load consumption, namely P SLoad +P TLoad ＜P PV +P Ess ＜P Load In order to ensure the stability of the system, the cut-out load is cut out, and meanwhile, in order to avoid deep charging and deep discharging of the battery, the service life of the battery is prolonged. The working state of the battery is obtained through the monitoring module, and the battery is according to the actual state of charge of the battery and the batteryThe predicted state of charge of the battery is subjected to one-step predictive control and current state control. One-step predictive control: first step, collecting the state of charge SOC of the battery at the moment real (k) And the predicted state of the next SOC fore (k+1), second step, let d=soc real (k)-SOC fore (k+1), if D > 0, the battery will be in a discharging state, if D < 0, the battery will be in a charging state, and the next step of judgment is performed according to the comparison of D and 0; third, if D > 0, SOC is determined fore Lower bound SOC for (k+1) and state-of-charge optimal control interval min Comparing, if D < 0, SOC fore Upper bound SOC for (k+1) and state-of-charge optimal control interval max Comparing, determining the next battery state, and if D is greater than 0, SOC fore (k+1)＜SOC min When the battery is cut out and the rechargeable standby battery is cut in, if D is more than 0, SOC fore (k+1)＞SOC min When the photovoltaic power generation device is used, the storage battery is kept in a discharging state, the defect of photovoltaic power generation capacity is overcome, electric quantity is provided for a load, and bus voltage is stabilized; if D is less than 0, SOC fore (k+1)＞SOC max When the battery is cut out and discharged, the standby battery is cut in, if D is less than 0, SOC fore (k+1)＜SOC max And when the load is in a charged state, the generated energy of the photovoltaic battery which cannot be consumed by the load is absorbed, and the bus voltage is stabilized. As a safeguard measure, the state of charge of the battery at the present time is compared with the predicted state of charge, and by determining whether the state of charge of the battery at the present time is in the optimum operating state of the battery, SOC (k) ∈ (SOC min ，SOC max )，SOC min ＝20％，SOC max If the state of charge of the storage battery is in the optimal working state, the original charge and discharge state is maintained, the balance of the system is maintained, if the state of charge of the storage battery exceeds the optimal working state of the storage battery, the storage battery is cut out, and compared with predictive control, the current time control has hysteresis, so that the performance of the storage battery can be influenced, but the deep charge and deep discharge of the storage battery caused by the occurrence of errors of predictive control in the predictive control can be effectively avoided. Strategy III: when the sum of the generated energy of the photovoltaic system and the electric quantity of the energy storage module is smaller than the load consumption electric quantity and is larger than the important load consumption amount, namely P SLoad ＜P PV +P ESS ＜P Load In order to ensure the stability of the system, the switchable load and the controllable load are switched off, so that the light-storage direct current micro-grid operates in the most basic operating state.
Fig. 19 (a) is a working battery soc critical 20%, cut-out control, standby battery cut-in control state of charge change diagram: fig. 19 (b) is a working battery soc critical 80%, cut-out control, and each battery cut-in control state of charge change diagram: as can be seen from fig. 18, according to the battery state-of-charge control rule, fig. 19 (a) shows that when the battery is in a discharged state, the state of charge of the battery is critical to the minimum value SOC set for the battery optimum operation interval min The battery is cut out according to the battery charge-discharge control strategy by the predictive control, each battery is connected to provide electric quantity for stable bus voltage, the front graph of fig. 19 (a) shows that the state of charge of the battery is not changed after the state of charge of the battery is reduced to the minimum value of the optimal working interval, the normal cut-out system of the battery is illustrated, and the rear graph of fig. 19 (a) shows that each battery is connected to the system at the same time to provide electric energy for the system. As can be seen from fig. 19 (b), when the battery is in the charged state, the charged state of the battery is critical to the maximum value soc set for the optimum operation interval of the battery max The battery is cut out according to the battery charge-discharge control strategy by the predictive control, the standby battery is connected to the electric quantity which cannot be consumed by the storage load, the front graph of fig. 19 (b) shows that the state of charge of the battery is not changed after the state of charge of the battery rises to the maximum value of the optimal working interval, the normal cut-out system of the battery is illustrated, the rear graph of fig. 19 (b) shows that the standby battery is connected to the system at the same time, and the electric energy is consumed by the system.
A simulation diagram for achieving verification is shown in fig. 3.
The foregoing is only a partial embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (5)
1. The predictive control method for the energy storage module in the light-storage direct-current micro-grid system is characterized by comprising the following steps of:
step 1, collecting relevant data of each module of the whole light-storage direct current micro-grid system through a detection module;
step 2, acquiring data of a battery pack in the energy storage module, and judging states of each battery including a charging state, a discharging state and a cutting-out state;
step 3, dividing the state of the battery into a working state and a standing state, and collecting battery history record data in a time period of the battery pack [0, TL ] in the working state;
step 4, fitting the battery state of charge data based on a least square method according to the collected battery history data of each battery after a period of operation, and predicting the battery state of charge at the next time point by adopting a variable step length prediction method; the historical record data comprises the state of charge (SOC), voltage (U) and current (I) of the battery;
step 5, according to the relation among the generated energy of the photovoltaic array, the energy consumption of the load and the electric energy reserve of the energy storage module, combining the three-level variable load and the predicted value of the state of charge of the battery, and formulating a corresponding direct-current micro-grid control method and an energy storage module control method;
in step 5, the generated energy P of the photovoltaic system is obtained according to the monitoring module PV Load consumption P Load And energy storage module electric energy reserve P ESS The relation between the consumption P and the DC load RLoad Consumption P of adjustable DC load TLoad Consumption P of important DC load SLoad Internal three-stage variable load and battery state of charge prediction value SOC fore Reference to the rated capacity P of the energy storage module RTESS Formulating a corresponding direct current micro-grid control method and an energy storage module control method;
wherein, in the light-storage direct current micro-grid, the specific steps are as follows:
the method comprises the following steps: when the generated energy of the photovoltaic system is larger than the consumed electric quantity of the load, namely P PV ＞P Load When the load cannot completely consume the electric energy generated by the photovoltaic, the electric energy is not consumedThe electric energy is transmitted to the energy storage module, and when the energy storage module reaches the maximum rated capacity, the electric energy which cannot be consumed is discarded;
the second method is as follows: when the sum of the generated energy of the photovoltaic system and the electric energy reserve of the energy storage module is smaller than the consumed electric quantity of the load and is larger than the sum of the consumed electric quantity of the important direct current load and the consumed electric quantity of the adjustable direct current load, namely P SLoad +P TLoad ＜P PV +P ESS ＜P Load In order to ensure the stability of the system, a cut-off DC load is cut out, and meanwhile, in order to avoid deep charging/deep discharging of the battery, the service life of the battery is prolonged; the working state of the battery is obtained through the monitoring module, and one-step predictive control and current state control are carried out on the storage battery according to the actual state of charge of the battery and the predicted state of charge of the battery;
wherein, the one-step predictive control is specifically as follows:
first, collecting the state of charge (SOC) of the battery real (k) And the predicted state of the next SOC fore (k+1)；
Second, let d=soc real (k)-SOC fore (k+1) if D>0, the battery will be in a discharge state, if D<0, the battery is in a charging state, and the next step of judgment is carried out according to the comparison of D and 0;
third step, if D>0, SOC is then fore Lower bound SOC for (k+1) and state-of-charge optimal control interval min Comparison, if D<0, SOC is then fore Upper bound SOC for (k+1) and state-of-charge optimal control interval max Comparing, and determining the state of the battery in the next step;
fourth step, if D>0，SOC fore (k+1)<SOC min When the battery is cut out and charged, the standby battery is cut in, if D>0，SOC fore (k+1)>SOC min When the photovoltaic power generation device is used, the storage battery is kept in a discharging state, the defect of photovoltaic power generation capacity is overcome, electric quantity is provided for a load, and bus voltage is stabilized; if D<0，SOC fore (k+1)>SOC max When the battery is cut out and discharged, the standby battery is cut in, if D<0，SOC fore (k+1)<SOC max When the battery is in a charged state, the generated energy of the photovoltaic battery which cannot be consumed by the load is absorbedStabilizing the bus voltage as a safeguard measure, and comparing the state of charge of the battery at the current moment with the predicted state of charge, and judging whether the state of charge of the battery at the current moment is in the optimal working state of the battery or not to obtain the SOC real (k)∈(SOC min ,SOC max )，SOC min ＝20％,SOC max If the state of charge of the storage battery is in the optimal working state, the original charge and discharge state is maintained, the balance of the system is maintained, if the state of charge of the storage battery exceeds the optimal working state of the storage battery, the storage battery is cut out, compared with predictive control, the current state control has hysteresis, the performance of the storage battery can be influenced, but the deep charge/deep discharge of the storage battery caused by error of the predictive control can be effectively avoided;
and a third method: when the sum of the generated energy of the photovoltaic system and the electric energy reserve of the energy storage module is smaller than the consumed electric quantity of the load and is larger than the consumed electric quantity of the important direct current load, namely P SLoad ＜P PV +P ESS ＜P Load In order to ensure the stability of the system, the switchable DC load and the adjustable DC load are cut off, so that the light-storage DC micro-grid operates in the most basic operation state.
2. The method for predictive control of an energy storage module in an optical-dc micro grid system according to claim 1, wherein in step 1, the relevant data are specifically: (1) The power, voltage and current data of each photovoltaic array power generation are collected by the monitoring module; (2) The three-stage variable direct current load side electric energy consumption, voltage and current data, (3) the energy storage module is composed of a group of mutually independent lithium iron phosphate batteries, each lithium iron phosphate battery is provided with different numbers, and the working state, charging/discharging voltage and current of each battery and the state of charge of each battery are obtained, (4) bus voltage and current data.
3. The method for predictive control of energy storage modules in an optical-dc micro-grid system according to claim 1, wherein in step 2, the working states of the batteries are classified into two categories by collected data of each lithium iron phosphate battery in the energy storage modules: a charged state and a discharged state.
4. The method for predictive control of an energy storage module in an optical-dc micro grid system according to claim 1, wherein in step 3, a time length of intercepting a lithium iron phosphate battery in an operating state in the energy storage module is T L Is set to be [0, T L ]。
5. The method for predicting and controlling an energy storage module in an optical-storage direct current micro grid system according to claim 1, wherein in step 4, the state of charge of a battery in a next step is predicted based on a least square method, specifically as follows:
step 4.1, collecting [0, T ] L ]Data is used as a basic data set S1, and an error standard value delta is set at the same time rmse 、δ mad 、δ mape ；
Step 4.2, setting the initial predicted time step size T1 and the fluctuation amount T D ，T D <0.1T 1 The actual step length of the nth prediction is defined as T n ＝T 1 +x n-1 *T D ＝T n-1 ±T D ，x n-1 ＝x z -x j ，n-1＝x z +x j ，x z Indicating the number of times of increasing the fluctuation amount, x j Let y=t denote the number of times the fluctuation amount decreases n The first predicted time range is [ T ] L ,T L +T 1 ]The length of time for the mth prediction is [ T ] m-1 ,T m-1 ±T D ]；
Step 4.3, obtaining and storing the predicted data and the actual data of the nth period;
step 4.4, according to the predicted data SOC of the nth period fore And actual data SOC real Calculating the error delta between the two rmsex 、δ madx 、δ mapex And compares the three error values with delta rmse 、δ mad 、δ mape If at least one of the relationships is greater than the error criterion value, then return Y =T n+1 ＝T n -T D If the three-phase errors are all smaller than the error standard value, return y=t n+1 ＝T n +T D It is specified that each predicted step size needs to be kept within range.
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