Distributed wind, light and hydrogen storage integrated power supply system

Abstract

The invention discloses an energy management control strategy for a wind-light-hydrogen storage off-grid type comprehensive power supply system, and belongs to the technical field of clean energy power generation equipment. The system is composed of a wind generating set, a photovoltaic generating set, a lithium battery pack, a PEM fuel cell stack, a water electrolysis hydrogen production device and the like, clean energy such as wind power, light energy and hydrogen energy is used for power generation to meet the power utilization load, and the lithium battery pack and the water electrolysis hydrogen production device-fuel cell'energy storage closed loop 'is used for absorbing or supplementing electric energy with excessive power supply or shortage. According to the invention, modeling is carried out on system energy management, a system power supply state is divided into three typical power supply states based on system power supply characteristics, and a multi-state transition energy management algorithm based on fuzzy control is provided.

Description

Technical Field Clean energy power generation equipment technology Background Technology

[0001] The integrated wind-solar-hydrogen-storage power supply system comprises wind turbine generators, photovoltaic generators, PEM fuel cell stacks, lithium battery packs, and water electrolysis hydrogen production units. The challenge in designing the system's energy management algorithm stems from the complexity of the system composition and the interconnectedness of the operating states of each unit, making independent analysis and control impossible to guarantee the availability, stability, and reliability of power supply. If we consider the integrated wind-solar-hydrogen-storage power supply system as a "black box," the wind and solar energy inputs and the matching electrical load at the output end determine the system's specific operating state. The system can be divided into three states: wind-solar complementary power supply, wind-solar-storage power supply, and wind-solar-storage-fuel cell (fuel cell) power supply. These three operating states transition between each other due to external and internal factors. External factors include wind energy, solar energy, and electrical load, while the internal factor primarily involves the "memory capacity" (SOC) of the lithium battery packs within the system's components. The combined external and internal factors determine the operating state of each unit in the system. The system controller needs to collect the current operating state information of each unit, and may also be affected by uncertainties such as environment and economics. For example, PEM fuel cell stacks have high start-up and shutdown costs and are not suitable for frequent switching operations. In fact, the process of the system controller controlling the various units of the system can be summarized as a typical highly nonlinear control process, and the nonlinearity of the control also brings some challenges. Considering the issues that need to be considered in the above system energy management algorithms, this paper designs a fuzzy control algorithm based on multi-state transition for energy management. The fuzzy controller addresses the nonlinear control difficulties in the system by formulating a rule base based on the multi-state transition of the system, thereby managing the system's energy flow in a reasonable and efficient manner. Summary of the Invention

[0002] To address the complex and highly nonlinear characteristics of integrated wind-solar-hydrogen-storage power supply systems, a multi-state transition energy management algorithm based on fuzzy control was designed. The system's operating states are divided into three categories: wind-solar hybrid power supply, wind-solar-storage power supply, and wind-solar-storage-gas power supply. External factors such as system input and power load, along with internal factors such as lithium battery SOC, influence the system's operating states, causing it to transition between these three power supply states. A rule table for the fuzzy algorithm is formulated based on the state transition principle. Attached Figure Description

[0003] The system block diagram of the present invention is as follows: Figure 1 As shown.

[0004] Energy management algorithm process as follows Figure 2 As shown.

[0005] The operation status switching of a wind-solar-storage-gas multi-energy complementary system is as follows: Figure 3 As shown.

[0006] In fuzzy control, the error and rate of change functions are as follows: Figure 4 As shown.

[0007] The control membership functions of lithium batteries, PEM fuel cells, and water electrolysis hydrogen production devices are as follows: Figure 5 As shown. Detailed Implementation

[0008] The system controller needs to adjust the various units of the system based on the system inputs of wind power generation, photovoltaic power generation, lithium battery SOC, and electrical load. This mainly involves controlling the operating status of three controlled objects: the lithium battery pack, the PEM fuel cell, and the water electrolysis hydrogen production unit, to replenish or absorb electrical energy in the system's energy bus. However, the mutual influence of the operating states of the controlled objects increases the difficulty of controller regulation. For example, when the lithium battery SOC is below 20%, it should not continue discharging; at this time, only the PEM fuel cell can output power. The controlled objects are difficult to represent using linear mathematical models. Fortunately, the operating states of the controlled objects are relatively intuitive and easily represented by several linguistic variables, making fuzzy control suitable. Based on the electrical characteristic analysis in Section 2.3, the normal operating state of charge of the lithium battery is suitable to be maintained in the range [0.20, 0.80]. To maintain lithium battery performance, 0.35 is set as the lower limit threshold for battery discharge, and 0.65 is set as the upper limit threshold for battery charging. During the discharge protection range, the lithium battery can only charge, and during the charging protection range, the battery can only discharge. The lithium battery SOC can be divided into Equation 1:

[0009]

[0010] In this paper, to improve the real-time performance of the fuzzy controller, three fuzzy rules are set for the three intervals of the lithium battery SOC. Therefore, the fuzzy controller uses the difference between the system output power and the electrical load as the control error (see Equation 2), denoted as e(t) and its rate of change. These are the two inputs to the fuzzy controller.

[0011] e(t) = P wind (t)+P pv (t)+P bat (t)+P fc (t)+P ele (t)-P load (t)…(2)

[0012] A two-input, three-output MIMO controller is constructed using three outputs: a lithium battery, a PEM fuel cell, and a water electrolysis hydrogen production device. The control principle of the fuzzy controller is described in [link to fuzzy controller documentation]. Figure 2 :

[0013] According to e(t), The three input variables—including the lithium battery pack's SOC—are used to match the control rules of the fuzzy controller. The inference engine uses a rule base to infer and output the control variables that match the rules for the current variables. The most important rule base is designed based on the system definition of the transition processes between three power supply states: wind-solar hybrid power supply, wind-solar-storage power supply, and wind-solar-hydrogen-storage-fuel power supply. This allows for the control of the three internal controlled objects—the PEM fuel cell, the water electrolysis hydrogen production unit, and the lithium battery—based on the characteristics of different power supply state transitions. The specific quantization parameters of the control signals are determined by the fuzzy controller. The system's three power supply state definitions and transition processes are described in [link to documentation]. Figure 3 :

[0014] System multi-power supply state transition process:

[0015] 1) Wind-Solar Hybrid Power Supply Mode: When the output power of the wind-solar hybrid power supply exceeds the electrical load, the system is in wind-solar hybrid operation mode. At this time, the electrical load is completely met by wind-solar hybrid power generation, and the excess electrical energy is stored in the form of hydrogen production through water electrolysis. When the wind-solar hybrid power supply is lower than the electrical load, and the SOC of the lithium-ion battery pack is higher than its SOC protection lower limit of 0.35, this mode switches to wind-solar-storage power supply mode; when the wind-solar hybrid power supply is lower than the electrical load, but the SOC of the lithium-ion battery pack is lower than its SOC protection lower limit of 0.35, this mode switches to wind-solar-storage-fuel power supply mode.

[0016] 2) Wind-Solar-Storage Power Supply Status: When the output power of the wind-solar hybrid power supply does not exceed the electrical load, but the SOC of the lithium-ion battery pack is higher than its SOC protection lower limit of 0.35%, the system is in the wind-solar-storage power supply status. When the wind-solar hybrid power supply power is higher than the electrical load, this status transitions to the wind-solar hybrid power supply status; when the wind-solar hybrid power supply power is lower than the electrical load, and the SOC of the lithium-ion battery pack is lower than its SOC protection lower limit of 0.35%, this status transitions to the wind-solar-storage-gasoline power supply status.

[0017] 3) Wind-Solar-Storage-Gas Power Supply Status: When the power supply of the wind-solar hybrid system does not exceed the electrical load, but the SOC of the lithium-ion battery pack is within its normal operating range between its upper limit of 0.65 and lower limit of 0.35, the system is in the wind-solar-storage-gas power supply status. When the power supply of the wind-solar hybrid system is higher than the electrical load, and the SOC of the lithium-ion battery pack is higher than its upper limit of 0.65, this status transitions to the wind-solar hybrid power supply status; when the difference between the power supply of the wind-solar hybrid system and the electrical load is higher than the fuel cell terminal voltage, and the SOC of the lithium-ion battery pack is higher than its upper limit of 0.65, this status transitions to the wind-solar-storage-gas power supply status.

[0018] Flow of a multi-state transition algorithm based on fuzzy control

[0019] 1) Determine the control performance indicators of the control system: This system is designed only for small-scale power demand, so the output power control adjustment range is [0, 10kw]; the dynamic performance requirement of the system is that the total output power of the system should not be less than the power load in a timely manner, and the real-time performance of the system control should be good.

[0020] 2) Determine the fuzzy control scheme: Based on the three different intervals of SOC in the input variable [0.2, 0.35], [0.35, 0.65], and [0.65, 0.8], this system adopts three different sets of rule tables to improve the real-time performance of control; the difference between the system output power and the electrical load e(t) and its rate of change are selected. The input variables are the rules base, and the output variables are the control quantities of lithium battery packs, PEM fuel cells, and water electrolysis hydrogen production devices.

[0021] 3) Universe of discourse selection: MIMO format was adopted, with the universe of discourse for all variables designed to be [-6, 6]. Normalization was performed based on the actual range of variable values ​​in the experiment. The most commonly used triangular membership function was employed, and the output variables were obtained through defuzzification using a weighted average method. The membership functions of the controller input and output variables are shown below. Figure 4 , Figure 5 As shown:

[0022] 4) Control Rule Table: The rule table needs to meet several important conditions: rule completeness, meaning there should be no uncontrolled situations. (Rule table reference) Figure 3 , Figure 4 The design is based on the migration principle between three power supply states: wind-solar hybrid power supply, wind-solar-storage power supply, and wind-solar-storage-fuel power supply. Under three different SOC ranges [0.2, 0.35], [0.35, 0.65], and [0.65, 0.8], the control rules for lithium batteries are shown in Tables 1, 2, and 3; the control rules for PEM fuel cells are shown in Tables 4, 5, and 6; and the control rules for water electrolysis hydrogen production devices are shown in Tables 7, 8, and 9.

[0023] Table 1. Control rules for lithium battery packs with SOC between [0.35% and 0.65%].

[0024]

[0025] Table 2 shows the control rules for lithium battery packs when SOC is [0.20, 0.35].

[0026]

[0027] Table 3. Control rules for lithium battery packs when SOC is [0.65, 0.80].

[0028]

[0029]

[0030] Table 4 shows the control rules for PEM fuel cells when SOC is [0.35, 0.65].

[0031]

[0032] Table 5 shows the control rules for PEM fuel cells when SOC is [0.20, 0.35].

[0033]

[0034] Table 6 shows the control rules for PEM fuel cells when SOC is [0.65, 0.80].

[0035]

[0036] Table 7 Control Rules for Water Electrolysis Hydrogen Production Units with SOC [0.35, 0.65]

[0037]

[0038]

[0039] Table 8. Control Rules for Water Electrolysis Hydrogen Production Units with SOC [0.20, 0.35]

[0040]

[0041] Table 9. Control Rules for Water Electrolysis Hydrogen Production Units with SOC [0.65, 0.80]

[0042]

[0043] 5) Analyze the control results of the fuzzy controller, adjust the control rules until the control effect is good and meets the real-time requirements of the system control.

Claims

1. A distributed wind-solar-hydrogen-storage integrated power supply system, characterized in that, The system includes a wind turbine generator set, a photovoltaic generator set, a PEM fuel cell stack, a lithium battery pack, a water electrolysis hydrogen production unit, and a system controller, all connected via an energy bus. The system controller executes a fuzzy control algorithm based on multi-state transitions, with the wind power generation P as the input. wind (t), Photovoltaic power generation P pv (t), State of charge (SOC) of lithium battery pack and electrical load P load (t) is the input, which controls the working status of the lithium battery pack, PEM fuel cell stack, and water electrolysis hydrogen production device to achieve dynamic balance of electrical energy in the energy bus.

2. The system according to claim 1, characterized in that, The system's operating states are divided into: wind-solar hybrid power supply state, when P... wind (t)+P pv (t)>P load When (t), the electricity load is met by wind and solar power generation, and excess electricity is stored by hydrogen production through water electrolysis; in the wind-solar-storage power supply state, when P wind (t)+P pv (t)≤P load (t) and when SOC > 0.35, the lithium battery pack discharges to replenish the energy gap; in wind, solar, and gas storage power supply mode, when P wind (t)+P pv (t)≤P load (t) When SOC≤0.35, the PEM fuel cell stack starts to supply power.

3. The system according to claim 2, characterized in that, The state transition conditions include: the wind-solar hybrid power supply state is in P wind (t)+P pv (t)≤P load (t) and when SOC>0.35, it migrates to the wind-solar-storage power supply state, at P wind (t)+P pv (t)≤P load (t) and when SOC≤0.35, the system migrates to wind-solar-storage-gas power supply mode; the wind-solar-storage power supply mode is in P wind (t)+P pv (t)≤P load When (t) and SOC≤0.35, the system will migrate to the wind-solar-storage-gas power supply state.

4. The system according to claim 1, characterized in that, The fuzzy control algorithm adopts a two-input, three-output architecture, with the input being the control error e(t) = P. wind (t)+P pv (t)+P bat (t)+P f (t)+P ele (t)-P load (t) and its rate of change The lithium battery pack's SOC (State of Charge) outputs the lithium battery pack's charging and discharging power P. bat (t), PEM fuel cell stack output power P f (t), Power P of the water electrolysis hydrogen production unit ele (t); Three sets of control rule tables are formulated based on the SOC intervals of [0.20,0.35], [0.35,0.65], and [0.65,0.80]. Each set of rule tables contains control logic for the lithium battery pack, PEM fuel cell stack, and water electrolysis hydrogen production device.

5. The system according to claim 4, characterized in that, The input variables of the fuzzy controller have a universe of discourse of [-6,6] after normalization. The control variables are generated by defuzzification using a triangular membership function and a weighted average method.

6. The system according to claim 1, characterized in that, The SOC protection mechanism of lithium battery packs is as follows: when SOC ≤ 0.35, it is the discharge protection range, and charging is allowed only; when SOC ≥ 0.65, it is the charging protection range, and discharging is allowed only; when 0.35 < SOC < 0.65, it is the normal operating range, and charging and discharging are allowed.

7. An energy management method based on the system according to any one of claims 1-6, characterized in that, This includes real-time data collection of wind power generation, photovoltaic power generation, lithium battery state of charge (SOC), and electricity load; calling the corresponding fuzzy rule table based on the SOC interval; and calculating the control error e(t) and its rate of change. The output power of each device is determined by fuzzy reasoning; the system operating state is dynamically switched based on the power difference and the SOC threshold.

8. The method according to claim 7, characterized in that, P under wind-solar hybrid power supply status wind (t)+P pv (t)>P load When (t), excess electrical energy is preferentially stored through a water electrolysis hydrogen production device until the SOC reaches 0.

65. The method according to claim 7, characterized in that, Under wind, solar, and gas storage power supply conditions, the PEM fuel cell stack maintains continuous operation only when SOC > 0.35 and P wind (t)+P pv (t)>P load Power supply is stopped at (t).

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