CN110535178B - Energy Control Strategy of Photovoltaic/Lithium Battery Hybrid System Based on Single Particle Physics Model - Google Patents

Abstract

The invention relates to an energy control strategy for a photovoltaic/lithium battery hybrid system based on a single particle physical model, including: Step 1. Module design of the PV-BES hybrid system, including: photovoltaic panel array, maximum power point tracking controller, lithium battery pack and electronic components; the entire photovoltaic panel array and related electronic components are expressed as a set of differential algebraic equations and integrated with the lithium battery model equations; Step 2. Photovoltaic panel array modeling: build an equivalent of a photovoltaic panel array based on a single diode Circuit model; Step 3. Hardware and algorithm flow design of PV-BES hybrid system; Step 4. Energy control strategy design of PV-BES hybrid system; Control the power flow between photovoltaic panels and battery energy storage system BES. The beneficial effects of the present invention are: the present invention can effectively realize the control algorithm, realize more accurate performance prediction and robust control, and the energy control algorithm proposed by the present invention can satisfy a number of performance indicators, such as zero residual energy, no overcharge phenomenon and maintaining a safe SOC range, etc.

Description

Energy Control Strategy of Photovoltaic/Lithium Battery Hybrid System Based on Single Particle Physics Model

technical field

The invention relates to the field of energy control, in particular to an energy control strategy for a photovoltaic/lithium battery hybrid system based on a single particle physical model. More specifically, it relates to a single-particle model of lithium batteries based on physical properties and an independent photovoltaic/lithium battery energy storage hybrid system based on Mixed Order Finite Difference (Mixed FD) and Maximum Power Point Tracking (MPPT) modes ( PV-BES) energy control strategy.

Background technique

The establishment of solar photovoltaic power plants has become a feasible measure to meet the growing demand for clean energy, and battery-free photovoltaic microgrids with optimal operation strategies can also provide uninterrupted power and reduce total dispatch energy costs. However, the current microgrid still needs fossil fuels as auxiliary energy, which is not good for environmental protection.

The lithium battery models proposed by the researchers are divided into two categories: physical models and equivalent circuit models (ECM). Natsheh et al. propose a PV-BES hybrid system that uses an equivalent circuit to simulate battery performance, and use empirical models to build a new model for photovoltaic cells/microgrids. In this model, the equivalent circuit model ECM is used to predict the overall operating conditions and power values of photovoltaic power plants. However, the equivalent circuit model ECM relies on a resistor-capacitor (RC) network, and the control module under dynamic conditions deviates from the experimental data. The battery model based on physical properties includes coupled partial differential equations, has better reliability and control performance, and maximizes the lifetime and safety of photovoltaic power generation systems.

The control strategy and power allocation of PV-BES hybrid system is another research area worthy of attention, and the optimal power control strategy has been proposed in the literature. Combining a battery energy storage system (BES) with a stand-alone photovoltaic system, a PV-BES hybrid system is designed to meet load demands under all operating conditions. Lithium-ion batteries (LIBs) are widely used in PV-BES hybrid systems due to their excellent energy storage performance and long cycle life. However, in the simulation and control algorithm of PV-BES hybrid system, the battery is regarded as a black box, its internal state is less considered, and the overall energy control strategy is also less studied.

In summary, it is particularly important to propose an energy control strategy for photovoltaic/lithium battery hybrid systems based on a single-particle physical model.

SUMMARY OF THE INVENTION

The purpose of the present invention is to overcome the deficiencies in the prior art and provide a photovoltaic/lithium battery hybrid system energy control strategy based on a single particle physical model.

The energy control strategy of the photovoltaic/lithium battery hybrid system based on the single-particle physics model specifically includes the following steps:

Step 1. Module design of PV-BES hybrid system; the module includes: photovoltaic panel array, maximum power point tracking controller, lithium battery pack and electronic components; the entire photovoltaic panel array and related electronic components are represented as a set of differential algebra equations, and integrated with the lithium battery model equations;

Step 2. Photovoltaic panel array modeling: establish an equivalent circuit model of a photovoltaic panel array based on a single diode;

Step 3. Hardware and algorithm flow design of PV-BES hybrid system;

Step 4. Energy control strategy design of PV-BES hybrid system; control the power flow between photovoltaic panels and battery energy storage system BES.

Preferably, the step 1 specifically includes the following steps:

Step 1.1. Establish a single-particle equivalent model based on physical properties; according to Frick's second law, such as formula (1), the ambient temperature and solar radiation are used as inputs to the photovoltaic model, and the photovoltaic panel voltage and current are used as outputs; the physical properties are based on The initial state formula of the single-particle equivalent model is formula (2), and the boundary condition formula is formula (3):

Q _i =Q _i0 ; when t=0 (2)

In the above formula, t is the time variable, Q _i is the charge of the positive and negative lithium particles, Di is the particle diameter, _ri is the particle radius, _i =n represents the negative electrode, i=p represents the positive electrode, and Q _i0 is the initial charge of the lithium particle. value, R _i is the critical radius value, J _i is the particle energy;

Step 1.2. When PV-BES hybrid system works:

1) If the power generated by the photovoltaic panels exceeds the load demand, the excess power is used to charge the lithium battery; the energy control strategy manages the power flow to avoid overcharging or overdischarging the battery pack;

2) When the state of charge SOC reaches 100%, the control strategy makes the photovoltaic panel jump out of the working mode of the maximum power point, the lithium battery is disconnected from the photovoltaic panel, and the photovoltaic panel only generates electrical energy that meets the load demand;

3) Control strategy According to the load demand, solar radiation and the SOC value of the lithium battery state of charge, the photovoltaic panel selects the normal working mode.

Preferably, the step 2 specifically includes the following steps:

Step 2.1 The volt-ampere characteristic formula of the photovoltaic panel array is as follows:

In the above formula, V(t) is the output voltage, I(t) is the output current, I _pv (t) is the photovoltaic panel current source, _Isat is the saturation current, V _T is the thermal voltage, R _s is the series resistance, R _p is the parallel resistance, α is the ideal constant of the diode;

The important parameters to solve the equation are as follows:

In the above formula, V _T is the thermal voltage, k is the Boltzmann constant, C _s is the series connection capacitance, T is the instantaneous temperature, q is the electron charge, I _pv (t) is the photovoltaic panel current source; I _{pv, n} is the light generation Current value, K _I is the current coefficient, T _n is the rated temperature, G _n is the rated illumination, G(t) is the instantaneous illumination, _Isat is the saturation current, I _oc,n is the rated short-circuit current, V _oc,n is the rated short-circuit voltage, α is the diode constant;

Step 2.2. Establish the maximum power point tracking algorithm formula based on differential algebraic equations, and express the photovoltaic panel array and related electronic components as differential algebraic equations:

In the above formula, P(t) is the output power of the photovoltaic array, I(t) is the output current, both P(t) and I(t) are functions of the output voltage, and d() is the derivation formula; the tracking algorithm formula The final form is:

In the above formula, I( _t ) is the output current, V( _t ) is the output voltage, _Isat is the saturation current, Rs is the series resistance, VT is the thermal voltage, α is the diode ideal constant, and _Rp is the parallel resistance.

Preferably, the step 3 specifically includes the following steps:

Step 3.1: Express the DC bus current of the hardware as:

In the above formula, I _dc,battery (t) is the DC bus current of the lithium battery, P _PV (t) is the output power of the inverter connected to the photovoltaic panel, P _demand (t) is the power required by the overall system, and η is the bidirectional DC/AC inverter conversion efficiency, V _dc is the bidirectional DC/AC inverter voltage;

Step 3.2: Use a PV-BES hybrid system to compensate for the difference between the load and the photovoltaic system power: use a bidirectional DC/AC inverter with conversion efficiency η to convert DC to AC or AC to DC; The electrical energy is supplied to the electrical equipment through the bidirectional DC/AC inverter. If the electrical energy required by the load is less than the total electrical energy generated by the photovoltaic panels, the excess electrical energy will charge the battery energy storage system BES. If the electrical energy demanded by the load is greater than that generated by the photovoltaic panels The total electrical energy of the battery energy storage system BES discharges and provides additional electrical energy.

Preferably, the step 4 specifically includes the following steps:

Step 4.1. Control strategy flow description:

1) Input the annual load, solar radiation energy, PV parameters and battery parameters of the load;

2) Calculate the parameter values I _PV,max (t), V _PV,max (t) and P _PV (t) according to the input data;

3) Determine whether P _PV (t) satisfies P _PV (t)>P _demand (t): if it does not satisfy P _PV (t)> P _demand (t), charge the lithium battery, and use the hybrid order finite difference method and Runge–Kutta algorithm for single particle model to solve the state of charge SOC; if P _PV (t)>P _demand (t) is satisfied, then go to 4);

4) Judging the SOC value of the state of charge: if the SOC=100% is satisfied, the lithium battery stops charging; if the SOC=100% is not satisfied, the lithium battery is charged, and is solved based on the mixed order finite difference method and the Runge–Kutta algorithm Single particle equivalent model based on physical properties;

5) On the basis of 4), judge again whether the SOC=100% is satisfied; if the SOC=100% is satisfied, the lithium battery stops charging, if the SOC=100% is not satisfied, the voltage value is calculated based on the SOC value of the lithium battery state of charge V _battey (t);

6): Calculate the total demand power, the total demand power P _demand includes the lithium battery demand power P _battey and the solar panel demand power P _PV , and the calculation formula satisfies P _demand =P _PV +P _battey ;

Step 4.2. Design of the switching process of the hybrid system adjustment mode:

1) If the SOC of the lithium battery reaches the overcharge state of 100%, the battery performance will be reduced and the battery life will be reduced;

2) Under high solar radiation, no load/light load and high state of charge SOC conditions: the state of charge SOC limit mode is always active; the photovoltaic panel only measures the load demand, and the photovoltaic panel automatically reduces the power required by the load until the lithium battery is charged. The electrical state SOC drops to within 100%;

3) When the load demand increases or the lithium battery is not fully charged, the hybrid system operates in MPPT mode, which ensures that the photovoltaic panels generate maximum power; if the total power cannot meet the load demand, the battery energy storage system BES will discharge to meet the load. power requirements;

4) At any time, only one regulation mode is active, and there is only one control target; the control algorithm switches from one mode to another according to the operating parameters.

The beneficial effects of the present invention are:

The present invention uses a differential algebraic equation system to represent the photovoltaic/lithium battery hybrid system PV-BES, and the equation system can effectively realize a control algorithm. At the same time, a lithium battery single-particle state model based on physical properties is established and applied in the simulation and control process. The model includes a photovoltaic cell model based on a single diode, a lithium battery single particle model based on physical properties, and a maximum power point tracking control algorithm based on differential algebraic equations. Using a single-particle model of lithium batteries based on physical properties to achieve more accurate performance prediction and robust control, and proposed to introduce thermal effects and degradation mechanisms into the control model; the new method can better understand and analyze the degradation of BES in battery energy storage systems According to the mechanism, the remaining service life of the BES of the battery energy storage system is predicted; the simulation results show that the energy control algorithm proposed by the present invention can meet a number of performance indicators, such as zero residual energy, no overcharge phenomenon, and maintaining a safe SOC range.

Description of drawings

Figure 1 is an equivalent circuit model of a photovoltaic cell based on a single diode;

Figure 2 is a flow chart of the PV-BES hardware and algorithm of the photovoltaic/lithium battery hybrid system;

Figure 3 is a flow chart of the PV-BES energy control strategy for the photovoltaic/lithium battery hybrid system;

Figure 4 shows the estimated results of lithium battery voltage value and SOC value based on the annual data of the power plant;

Figure 5 shows the power generated by the photovoltaic panel in the SOC limit mode;

Fig. 6 is the load power diagram under the SOC limit mode;

Figure 7 shows the SOC value of the lithium battery in the SOC limit mode.

Detailed ways

The present invention will be further described below in conjunction with the embodiments. The following examples are illustrative only to aid in the understanding of the present invention. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, the present invention can also be modified several times, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

To overcome the following problems:

1) Microgrid still needs fossil fuels as auxiliary energy, which is not good for environmental protection;

2) The equivalent circuit model ECM relies on the resistance-capacitor (RC) network, and the control module under dynamic conditions will deviate from the experimental data;

3) In the simulation and control algorithm of PV-BES hybrid system, the battery is regarded as a black box, its internal state is less considered, and the overall energy control strategy is also less studied.

The purpose of the present invention is to overcome the deficiencies in the prior art and provide a photovoltaic/lithium battery hybrid system energy control strategy based on a single particle physical model. The entire photovoltaic panel array and associated electronic components are represented as a set of differential algebraic equations (DAEs) and integrated with the lithium battery model equations for simultaneous simulation and efficient control.

The energy control strategy of the photovoltaic/lithium battery hybrid system based on the single-particle physics model specifically includes the following steps:

Step 1. Module design of PV-BES hybrid system; the module includes: photovoltaic panel array, maximum power point tracking controller, lithium battery pack and electronic components; the entire photovoltaic panel array and related electronic components are represented as a set of differential algebra equations, and integrated with the lithium battery model equations;

Step 2. Photovoltaic panel array modeling: establish an equivalent circuit model of a photovoltaic panel array based on a single diode;

Step 3. Hardware and algorithm flow design of PV-BES hybrid system, as shown in Figure 2;

Step 4. Energy control strategy design of PV-BES hybrid system; control the power flow between photovoltaic panels and battery energy storage system BES.

Preferably, the step 1 specifically includes the following steps:

Step 1.1. Establish a single-particle equivalent model based on physical properties; according to Frick's second law, such as formula (1), the ambient temperature and solar radiation are used as inputs to the photovoltaic model, and the photovoltaic panel voltage and current are used as outputs; the physical properties are based on The initial state formula of the single-particle equivalent model is formula (2), and the boundary condition formula is formula (3):

Q _i =Q _i0 ; when t=0 (2)

In the above formula, t is the time variable, Q _i is the charge of the positive and negative lithium particles, Di is the particle diameter, _ri is the particle radius, _i =n represents the negative electrode, i=p represents the positive electrode, and Q _i0 is the initial charge of the lithium particle. value, R _i is the critical radius value, J _i is the particle energy;

Step 1.2. When PV-BES hybrid system works:

1) If the power generated by the photovoltaic panels exceeds the load demand, the excess power is used to charge the lithium battery; the energy control strategy manages the power flow to avoid overcharging or overdischarging the battery pack;

2) When the state of charge SOC reaches 100%, the control strategy makes the photovoltaic panel jump out of the working mode of the maximum power point, the lithium battery is disconnected from the photovoltaic panel, and the photovoltaic panel only generates electrical energy that meets the load demand;

3) Control strategy According to the load demand, solar radiation and the SOC value of the lithium battery state of charge, the photovoltaic panel selects the normal working mode.

Preferably, the step 2 specifically includes the following steps:

Step 2.1 Establish an equivalent circuit model of the photovoltaic panel array based on a single diode; as shown in Figure 1, where V is the output voltage, I is the output current, I _pv is the current source generated by the photovoltaic panel, R _p is the parallel equivalent resistance, R _s is the series equivalent resistance, and a single diode is connected in parallel to the circuit. The volt-ampere characteristic formula of the photovoltaic panel array is as follows:

In the above formula, V(t) is the output voltage, I(t) is the output current, I _pv (t) is the photovoltaic panel current source, _Isat is the saturation current, V _T is the thermal voltage, R _s is the series resistance, R _p is the parallel equivalent resistance, α is the ideal constant of the diode;

The important parameters to solve the equation are as follows:

In the above formula, V _T is the thermal voltage, k is the Boltzmann constant, C _s is the series connection capacitance, T is the instantaneous temperature, q is the electron charge, I _pv (t) is the photovoltaic panel current source; I _{pv, n} is the light generation Current value, K _I is the current coefficient, T _n is the rated temperature, G _n is the rated illumination, G(t) is the instantaneous illumination, _Isat is the saturation current, I _oc,n is the rated short-circuit current, V _oc,n is the rated short-circuit voltage, α is the diode constant;

Step 2.2. Establish the maximum power point tracking algorithm formula based on differential algebraic equations, and express the photovoltaic panel array and related electronic components as differential algebraic equations:

In the above formula, P(t) is the output power of the photovoltaic array, I(t) is the output current, both P(t) and I(t) are functions of the output voltage, and d() is the derivation formula; 5) Substitute into formula (6), the final form of the tracking algorithm formula is:

In the above formula, I( _t ) is the output current, V( _t ) is the output voltage, _Isat is the saturation current, Rs is the series resistance, VT is the thermal voltage, α is the diode ideal constant, and _Rp is the parallel resistance.

Preferably, the step 3 specifically includes the following steps:

Step 3.1: Express the DC bus current of the hardware as:

In the above formula, I _dc,battery (t) is the DC bus current of the lithium battery, P _PV (t) is the output power of the inverter connected to the photovoltaic panel, P _demand (t) is the power required by the overall system, and η is the bidirectional DC/AC inverter conversion efficiency, V _dc is the bidirectional DC/AC inverter voltage;

Step 3.2: Compensate the difference between load and photovoltaic system power with photovoltaic/lithium battery hybrid system PV-BES: convert DC to AC or AC to DC using a bidirectional DC/AC inverter with conversion efficiency η; The electric energy generated by the photovoltaic panels is supplied to the electrical equipment through the bidirectional DC/AC inverter. If the electric energy required by the load is less than the total electric energy generated by the photovoltaic panels, the excess electric energy will charge the battery energy storage system BES. If it is greater than the total electricity generated by the photovoltaic panels, the battery energy storage system BES discharges and provides additional electricity.

Preferably, the step 4 specifically includes the following steps:

Step 4.1. The control flow is shown in Figure 3, and the control strategy flow is described:

1) Input the annual load, solar radiation energy, PV parameters and battery parameters of the load;

2) Calculate the parameter values I _PV,max (t), V _PV,max (t) and P _PV (t) according to the input data;

3) Determine whether P _PV (t) satisfies P _PV (t)>P _demand (t): if it does not satisfy P _PV (t)> P _demand (t), charge the lithium battery, and use the hybrid order finite difference method and Runge–Kutta algorithm for single particle model to solve the state of charge SOC; if P _PV (t)>P _demand (t) is satisfied, then go to 4);

4) Judging the SOC value of the state of charge: if the SOC=100% is satisfied, the lithium battery stops charging; if the SOC=100% is not satisfied, the lithium battery is charged, and is solved based on the mixed order finite difference method and the Runge–Kutta algorithm Single particle equivalent model based on physical properties;

5) On the basis of 4), judge again whether the SOC=100% is satisfied; if the SOC=100% is satisfied, the lithium battery stops charging, if the SOC=100% is not satisfied, the voltage value is calculated based on the SOC value of the lithium battery state of charge V _battey (t);

6): Calculate the total demand power, the total demand power P _demand includes the lithium battery demand power P _battey and the solar panel demand power P _PV , and the calculation formula satisfies P _demand =P _PV +P _battey ;

Step 4.2. Design of the switching process of the hybrid system adjustment mode:

1) 1) Under any solar radiation and load conditions, the adjustment mode can be freely selected; if the SOC of the lithium battery reaches an overcharged state of 100%, the battery performance will be reduced and the battery life will be reduced;

2) Under high solar radiation, no load/light load and high state of charge SOC conditions: the state of charge SOC limit mode is always active; the photovoltaic panel only measures the load demand, and the photovoltaic panel automatically reduces the power required by the load until the lithium battery is charged. The electrical state SOC drops to within 100%;

3) When the load demand increases or the lithium battery is not fully charged, the hybrid system operates in MPPT mode, which ensures that the photovoltaic panels generate maximum power; if the total power cannot meet the load demand, the battery energy storage system BES will discharge to meet the load. power requirements;

4) At any time, only one regulation mode is active, and there is only one control target; the control algorithm switches from one mode to another according to the operating parameters.

Experimental result 1:

The present invention applies a physical-property-based lithium-ion single-particle model and a novel energy control strategy to power plants to obtain more accurate information about BES during stand-alone photovoltaic system operation. Figure 4 shows the estimation results of the voltage value and SOC value of the single lithium battery, using the annual data of the power plant, and assuming that the single lithium battery is balanced in charge and discharge in the battery pack structure. The results show that the estimated value based on the single-particle lithium battery model is in line with the measured data:

(1) On the 180th to 250th day (June to August), the SOC value of the lithium battery is between 90% and 100%. During this time period, the photovoltaic panel power generation and load requirements are low, and the lithium battery maintains a high SOC value to prevent deep discharge.

(2) From the 200th day to the 250th day (July to August), the sunlight is larger in summer, and the power generation of photovoltaic panels is higher.

(3) The larger discharge process of lithium batteries occurs in the 100th-150th day (April and May), which is related to the high cooling load.

(4) From the 250th to the 300th day (September and October), the load consumes more electricity during this period, and the SOC value of the lithium battery decreases rapidly.

Experimental result 2:

Figure 5 shows the power generated by the photovoltaic panel in the lithium battery SOC limit mode, the load power is shown in Figure 6, and the battery SOC value is shown in Figure 7. Three days of atypical experimental data (261-263) are selected. The results show:

(1) When the lithium battery current is positive, the battery energy storage system is charged, and the remaining photovoltaic energy (overflow energy) generated by the excess load demand cannot be used due to the limitation of the size of the storage system. The control strategy prevents any energy spillage when the lithium battery is fully charged.

(2) When the solar radiation is high or the load value is low, the SOC value of the lithium battery exceeds the safety limit, and the control strategy adjusts the SOC value in the SOC limit mode.

(3) When the battery pack is fully charged (SOC=100%), the current of the lithium battery is zero. In the SOC limit mode, the power generated by the photovoltaic panel only meets the load demand, and the overflow energy is zero at this time.

(4) The energy control strategy proposed in this paper ensures the maximum power point operation model of the photovoltaic array, and ensures the safe operation of the battery under different operating conditions.

Claims (4)

1. Photovoltaic/lithium battery hybrid system energy control strategy based on single particle physical model, its characterized in that: the method specifically comprises the following steps:

step 1, designing a PV-BES hybrid system module; the module comprises: the system comprises a photovoltaic panel array, a maximum power point tracking controller, a lithium battery pack and electronic components; the whole photovoltaic panel array and related electronic components are expressed as a group of differential algebraic equations and integrated with a lithium battery model equation; the step 1 specifically comprises the following steps:

step 1.1, establishing a single particle equivalent model based on physical properties; according to Frick's second law, such as formula (1), the ambient temperature and solar radiation are used as the input of the photovoltaic model, and the photovoltaic panel voltage and current are used as the output; the initial state formula of the single particle equivalent model based on the physical properties is a formula (2), and the boundary condition formula is a formula (3):

Q_i＝Q_i0(ii) a When t is 0 (2)

In the above formula, t is a time variable, Q_iIs the positive and negative electrode lithium particle capacity, D_iIs the particle diameter, r_iThe particle radius is represented by i ═ n for the negative electrode, i ═ p for the positive electrode, and Q_i0Is the initial value of the electric quantity of the lithium particles, R_iIs the critical radius value, J_iIs the particle energy;

step 1.2. operation of the PV-BES hybrid system:

1) if the electric energy generated by the photovoltaic panel exceeds the load demand, the redundant electric energy is used for charging the lithium battery; the energy control strategy manages power flow to avoid overcharge or overdischarge of the battery pack;

2) when the SOC reaches 100%, the control strategy enables the photovoltaic panel to jump away from the working mode of the maximum power point, the lithium battery is disconnected with the photovoltaic panel, and the photovoltaic panel only generates electric energy meeting the load requirement;

3) the control strategy is that the photovoltaic panel selects a normal working mode according to the load demand, the solar radiation and the SOC value of the lithium battery;

step 2, modeling the photovoltaic panel array: establishing an equivalent circuit model of the photovoltaic panel array based on the single diode;

step 3, designing hardware and algorithm flow of the PV-BES hybrid system;

step 4, designing an energy control strategy of the PV-BES hybrid system; controlling the power flow between the photovoltaic panel and the battery energy storage system BES.

2. The single-particle physical model-based energy control strategy for a photovoltaic/lithium battery hybrid system according to claim 1, wherein the step 2 specifically comprises the following steps:

step 2.1 volt-ampere characteristic formula of photovoltaic panel array is as follows:

in the above formula, V (t) is the output voltage, I (t) is the output current, I_pv(t) is a current source of the photovoltaic panel, I_satIs a saturation current, V_TIs a thermal voltage, R_sIs a series resistance, R_pIs a parallel resistor, and alpha is an ideal constant of the diode;

the important parameter solving equation is as follows:

in the above formula, V_TIs the thermal voltage, k is the Boltzmann constant, C_sFor connecting the capacitors in series, T is the instantaneous temperature, q is the electronic charge, I_pv(t) is a photovoltaic panel current source; i is_pv,nGenerating a current value for illumination, K_IIs a current coefficient, T_nTo rated temperature, G_nFor nominal illumination, G (t) for instantaneous illumination, I_satIn order to be a saturation current, the current,I_oc,nfor rated short-circuit current, V_oc,nIs the rated short circuit voltage, alpha is the diode constant;

step 2.2, establishing a maximum power point tracking algorithm formula based on a differential algebraic equation, and expressing the photovoltaic panel array and related electronic components as the differential algebraic equation:

in the above formula, p (t) is the output power of the photovoltaic array, i (t) is the output current, p (t) and i (t) are both functions of the output voltage, and d () is the derivation formula; the final form of the tracking algorithm formula is:

in the above formula, I (t) is the output current, V (t) is the output voltage, I_satIs a saturation current, R_sIs a series resistance, V_TIs a thermal voltage, alpha is an ideal constant of the diode, R_pIs a parallel resistor.

3. The single-particle physical model-based energy control strategy for a photovoltaic/lithium battery hybrid system according to claim 1, wherein the step 3 specifically comprises the following steps:

step 3.1: the dc bus current of the hardware is represented as:

in the above formula, I_dc,battery(t) is the DC bus current of the lithium battery, P_PV(t) inverter output power connected to the photovoltaic panel, P_demand(t) power required by the overall system, η is the conversion efficiency of the bi-directional DC/AC inverter, V_dcIs a bi-directional dc/ac inverter voltage;

step 3.2: compensating for differences between load and photovoltaic system electrical energy with a PV-BES hybrid system: converting direct current into alternating current or converting alternating current into direct current by using a bidirectional direct current/alternating current inverter with conversion efficiency eta; the electric energy generated by the photovoltaic panel is provided for the electric equipment through the bidirectional direct current/alternating current inverter, if the electric energy required by the load is less than the total electric energy generated by the photovoltaic panel, the redundant electric energy is used for charging the battery energy storage system BES, and if the electric energy required by the load is more than the total electric energy generated by the photovoltaic panel, the battery energy storage system BES discharges and provides additional electric energy.

4. The single-particle physical model-based energy control strategy for a photovoltaic/lithium battery hybrid system according to claim 1, wherein the step 4 specifically comprises the following steps:

step 4.1, control strategy flow description:

1) inputting the annual load capacity, solar radiation energy, PV parameters and battery parameters of a load;

2) calculating parameter values I from input data_PV,max(t)、V_PV,max(t) and P_PV(t); wherein I_PV,max(t) is the maximum value of the current generated by the photovoltaic panel, V_PV,max(t) is the maximum voltage generated by the photovoltaic panel;

3) judgment of P_PV(t) whether or not P is satisfied_PV(t)＞P_demand(t): if not, P_PV(t)＞P_demand(t), charging a lithium battery, and solving the SOC through a single-particle model based on a mixed order finite difference method and a Runge-Kutta algorithm; if P is satisfied_PV(t)＞P_demand(t), then go to 4);

4) judging the SOC value: if the SOC is 100%, stopping charging the lithium battery; if the SOC is not satisfied, charging the lithium battery, and solving a single particle equivalent model based on physical properties based on a mixed order finite difference method and a Runge-Kutta algorithm;

5) on the basis of 4), judging whether the SOC meets 100 percent again; if the SOC is 100%, the lithium battery stops charging, and if the SOC is not 100%, the lithium battery is based onSOC value of battery, and calculated voltage value V_battey(t)；

6): calculating a total power demand, said total power demand P_demandIncluding the required power P of the lithium battery_batteyAnd the required power P of the solar panel_PVThe calculation formula satisfies P_demand＝P_PV+P_battey；

And 4.2, designing a hybrid system regulation mode switching process:

1) if the SOC of the lithium battery reaches the overcharge state of 100%, the performance of the battery is reduced, and the service life of the battery is reduced;

2) under high solar radiation, no/light load and high state of charge SOC conditions: the state of charge, SOC, limit mode is always active; the photovoltaic panel only measures the load demand, and automatically reduces the power required by the load until the SOC of the lithium battery is reduced to be within 100%;

3) when the load demand increases or the lithium battery is not fully charged, the hybrid system operates in MPPT mode, which ensures that the photovoltaic panel produces maximum power; if the total power can not meet the load requirement, the battery energy storage system BES discharges to meet the load power requirement;

4) at any time, only one regulation mode is in an activated state, and only one control target is available; the control algorithm switches from one mode to another depending on the operating parameters.

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