Frequency grading multi-time scale energy management and control method suitable for composite energy supply system

Abstract

The frequency grading multi-time scale energy management and control method suitable for the composite energy supply system has certain universality, is suitable for most energy systems on the one hand, and is suitable for day-ahead control and intra-day control on the other hand. Based on physical characteristics and response rates of different subsystems such as a power supply, an energy storage system and a load, the subsystems are arranged step by step according to high frequency, intermediate frequency and low frequency; the power state of the low-frequency subsystem is controlled through the capacity state of the high-frequency subsystem, so that a time sequence responds step by step from fast to slow under the condition that the output and load of each subsystem are not subjected to frequency domain decomposition; and a control instruction is optimized through methods of hysteresis control, follow-up control and the like. According to the method, theoretical guidance is provided for multi-time scale energy management and control of the'source-network-load-storage 'type composite energy supply system under double-side random, real-time and dynamic complex working conditions.

Description

Technical Field

[0001] The present invention belongs to the field of energy management and control of a "source-grid-load-storage" integrated energy system, and specifically relates to a frequency-graded multi-time-scale energy management and control method suitable for a composite energy supply system. Background Art

[0002] In the new power system dominated by new energy, large-scale grid connection has brought serious impact on the balance and stability of the power system due to the intermittent, volatile and random characteristics of new energy generation. In order to ensure the smooth consumption of new energy and the safety of the power grid, it is necessary to enhance the complementarity between different energy sources and the interactivity of the "source-grid-load-storage" side. Therefore, it is urgent to develop a "source-grid-load-storage" type composite energy supply system. This system has typical "three more" characteristics, namely, multi-energy, multi-scale and multi-variable. Multi-energy is manifested in the diversity of energy forms, energy categories, and subsystems; multi-scale is manifested in the multi-time scale of real-time response and long-term planning and the multi-spatial scale of source, storage, and load across regions; multi-variable is manifested in the differences and complexity of subsystem physical characteristics and parameters, as well as the strong volatility of parameters on the time scale. In order to make the composite energy supply system stable and efficient, energy management and control methods are crucial.

[0003] Most of the existing system energy management methods are based on the power balance strategy proposed by specific subsystems. They can make the system run normally, but there is still a lot of room for optimization from the perspective of efficient energy utilization, and they are only targeted at specific systems, lacking universality at the method level. A few methods perform global output planning for new energy power generation, conventional energy power generation, energy storage, etc. from a system perspective. Although they can make the system energy distribution more reasonable and improve the comprehensive utilization efficiency of system energy, global planning often depends on the accuracy of predictions such as new energy power generation and user load, and is only applicable to day-ahead scheduling. Intraday scheduling still requires methods such as rolling optimization to maintain the real-time power balance of the system, and cannot handle real-time load fluctuations. Summary of the invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art and address the deficiencies of the existing system energy management methods, the purpose of the present invention is to provide a frequency-graded multi-time-scale energy management method suitable for a composite energy supply system based on the physical characteristics and response times of different subsystems, so as to provide theoretical guidance for the multi-time-scale energy management of a "source-grid-load-storage" composite energy supply system under bilateral random, real-time dynamic and complex working conditions.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A frequency-graded multi-time-scale energy management and control method suitable for a composite energy supply system mainly includes the following steps:

[0007] Step 1: Frequency classification. According to the different physical characteristics and response rates of the source, storage, load and other subsystems, the subsystems are arranged in order of high frequency, medium frequency and low frequency. High-frequency subsystems are generally based on electrical energy. They respond quickly and change in real time. The response time is in the order of seconds or less, usually less than 1 second. Typical high-frequency subsystems include user loads, grid fluctuations and unconstrained renewable energy generation. Medium-frequency subsystems involve the conversion of electrical energy and other forms of energy. They are limited by objective physical processes and cannot respond as quickly as electricity. The response time is between the high-frequency response time and the low-frequency response time, usually between 1 second and 1 minute. Typical medium-frequency subsystems include electrochemical energy storage, mechanical energy storage and other electrical energy storage. Low-frequency subsystems are usually based on thermodynamic processes. Due to the large inertia of heat and mass transfer processes, thermodynamic processes usually respond slowly, with a response time of minutes or more, usually greater than 1 minute. Typical low-frequency subsystems include power cycles, fuel cells and thermal mass storage.

[0008] Step 2: Step-by-step control, control the power state of the low-frequency subsystem through the capacity state of the high-frequency subsystem, and control the power state of the low-frequency subsystem through the capacity state of the medium-frequency subsystem. First, although different subsystems have different physical characteristics and characterization parameters, power and capacity are external characteristic parameters that each subsystem has. Secondly, from a dimensional analysis, capacity is the product of power and time. The capacity parameters of the high-frequency subsystem can be quickly calculated within a short time scale, and then the power parameters of the low-frequency subsystem can be controlled on a long time scale. Finally, this control method enables the output and load of each subsystem to respond step by step from fast to slow in time series without frequency domain decomposition.

[0009] Step 3: Command optimization. According to the dynamic operation characteristics of the composite energy supply system, the control commands are optimized through hysteresis control, follow-up control and other methods to achieve stable and efficient operation of the composite energy supply system. If the main goal is to ensure stable operation of the system, it is necessary to reduce the volatility of the power cycle output so that it can be maintained in a steady-state condition. The "hysteresis control" based on fuzzy thinking can effectively filter out the output commands of the power cycle fluctuations; if the main goal is to ensure efficient operation of the system, it is necessary to improve the load following ability of the power cycle. The "follow-up control" can improve the power cycle output command from step regulation to stepless regulation, thereby reducing the energy loss of the system.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] 1. The present invention is applicable to most energy systems. For any integrated energy system, subsystems can be arranged by frequency through different time constants. Low-frequency power parameters are controlled by high-frequency capacity parameters to achieve coordinated operation of subsystems.

[0012] 2. The present invention is applicable to both day-ahead control and intraday control. The fluctuation of user load or new energy can be connected to high-frequency parameters in real time, and the system can perform intraday regulation through high, medium and low frequency step-by-step response.

[0013] 3. The present invention can optimize control instructions using specific methods such as hysteresis control and follow-up control according to different requirements of the composite energy supply system, such as stable output and efficient energy supply.

[0014] In summary, the present invention can realize multi-time-scale energy control of the "source-grid-load-storage" composite energy supply system under bilateral random and real-time dynamic complex working conditions, which helps to absorb a high proportion of new energy and the efficient and stable operation of new power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the frequency classification method of the present invention.

[0016] Figure 2 The diagram is a schematic diagram of the frequency-graded multi-time-scale energy management method of the present invention. The left side shows the frequency-graded result of the present invention, and the right side shows the algorithm flow of the frequency-graded control method of the present invention in a typical composite energy supply system including a photovoltaic power generation subsystem, a supercritical carbon dioxide power cycle power generation subsystem, an all-vanadium liquid flow energy storage subsystem, and a user load subsystem.

[0017] Figure 3 It is a typical operating condition. (a) is the light intensity under sunny conditions, and (b) is the typical industrial load curve after being proportionally reduced according to laboratory conditions.

[0018] Figure 4 Figure 2 shows the output curve of the supercritical carbon dioxide power cycle under typical operating conditions. (a) is the basic frequency-grading control method, and (b) is the frequency-grading control method that optimizes instructions through hysteresis control. DETAILED DESCRIPTION

[0019] In the following, in combination with the accompanying drawings, taking a composite energy supply system including a source-side subsystem, a grid-side subsystem, a load-side subsystem and a storage-side subsystem as an example, the frequency-graded multi-time-scale energy management and control method is described in detail.

[0020] Specifically, the source-side subsystem includes new energy and conventional energy. New energy includes photovoltaic cells, and conventional energy includes supercritical carbon dioxide (S-CO2) power cycle. The grid-side subsystem includes large power grid and micro energy grid; the load-side subsystem includes electric load and cold and hot load, which constitutes the user load. The storage-side subsystem mainly includes vanadium redox battery (VRB).

[0021] like Figure 1 As shown, the universal multi-time scale frequency classification method of the present invention is as follows: according to the different physical characteristics and response rates of the source, storage, load and other subsystems, the subsystems are arranged in sequence of high frequency, medium frequency and low frequency. High-frequency subsystems are generally based on electrical energy. They respond quickly, change in real time, and the time constant is usually less than 1 second. Typical high-frequency subsystems include user loads, grid fluctuations and unconstrained renewable energy generation. Medium-frequency subsystems involve the conversion of electrical energy and other forms of energy. They are limited by objective physical processes and cannot respond as quickly as electricity. The time constant is usually between 1 second and 1 minute. Typical medium-frequency subsystems include electrochemical energy storage, mechanical energy storage and other electrical energy storage. Low-frequency subsystems are usually based on thermodynamic processes. Due to the large inertia of heat and mass transfer processes, thermodynamic processes usually respond slowly, and the time constant is usually greater than 1 minute. Typical low-frequency subsystems include power cycles, fuel cells and thermal mass storage.

[0022] like Figure 2 As shown, taking the composite energy supply system including source side subsystem, storage side subsystem and load side subsystem as an example, the user load and photovoltaic power generation subsystem are high frequency, the all-vanadium liquid flow battery is medium frequency, and the supercritical carbon dioxide power cycle power generation subsystem is low frequency. The detailed control steps are as follows:

[0023] ① High-frequency control: Calculate the difference power through the real-time output of the source-side subsystem and the load-side subsystem. Specifically, input the photovoltaic power generation power and user load data, set the initial supercritical carbon dioxide power cycle load rate to x% = 70%, and calculate the difference power. In appropriate cases, x can be taken between 60 and 80 as appropriate. For the high-frequency subsystem, the time scale is 1 second, and numerically, the power and capacity are equal.

[0024] ② Medium frequency control: Use the real-time output of the source-side subsystem to control the charging and discharging power of the storage-side subsystem. Specifically, the power (low frequency) of the all-vanadium liquid flow battery is controlled by the difference in power (high frequency). When the difference in power is greater than zero, the all-vanadium liquid flow battery is charged, otherwise, the all-vanadium liquid flow battery is discharged.

[0025] ③ Low-frequency control: Using the state of charge (SOC) of the all-vanadium liquid flow battery to control the output command (W / W) of the supercritical carbon dioxide power cycle design). Specifically, the supercritical carbon dioxide power cycle power (low frequency) is controlled by the charge state (high frequency) of the all-vanadium liquid flow battery. The all-vanadium liquid flow battery SOC is calculated, and the control instruction boundary SOC=40% and 60%, that is, when the SOC is less than 40%, the supercritical carbon dioxide power cycle load rate is set to a%, when the SOC is greater than 60%, the supercritical carbon dioxide power cycle load rate is set to c%; when the SOC is between 40% and 60%, the supercritical carbon dioxide power cycle load rate is set to b%. The control equation is expressed by formula (1).

[0026]

[0027] Where W is the actual power of supercritical carbon dioxide power cycle, W design is the rated power of the supercritical carbon dioxide power cycle, 80<a≤100, 60<b≤80, 40≤c≤60, in this embodiment, a=100, b=70, c=40.

[0028] In actual operation, if the SOC of the all-vanadium flow battery fluctuates around 40% or 60%, the supercritical carbon dioxide power cycle subsystem will be in a state of frequent load changes, endangering system safety. The hysteresis control method is used to optimize the control command of the all-vanadium flow battery SOC to the supercritical carbon dioxide power cycle output. The hysteresis position is the control command boundary, and the hysteresis range is ±5%. Specifically, a 10% hysteresis zone is set at the control boundary (SOC = 40% and 60%). Then the secondary control is adjusted to the following strategy: During the charging of the all-vanadium flow battery and the load reduction of the supercritical carbon dioxide power cycle, the decreasing boundaries of the supercritical carbon dioxide power cycle output command are 45% and 65% of the all-vanadium flow battery SOC respectively; on the contrary, during the discharging of the all-vanadium flow battery and the load increase of the supercritical carbon dioxide power cycle, the increasing boundaries of the supercritical carbon dioxide power cycle output command are 55% and 35% of the all-vanadium flow battery SOC respectively. The control equation is expressed by formula (2).

[0029]

[0030] like Figure 3 As shown in the figure, (a) is the light intensity under typical sunny conditions, and (b) is the typical industrial load curve scaled down according to laboratory conditions. It can be seen that the light conditions have strong peak and valley characteristics, and the load curve has large fluctuations.

[0031] like Figure 4 As shown, (a) is Figure 3(a) is the output curve of the supercritical carbon dioxide power cycle when the basic frequency graded control method is applied under typical operating conditions, and (b) is the output curve of the supercritical carbon dioxide power cycle when the frequency graded control method with hysteresis control optimization instructions is applied. It can be seen that hysteresis control can effectively avoid frequent fluctuations in the output of the supercritical carbon dioxide cycle and improve the system operation stability.

[0032] Due to the characteristics of the step control command, the basic frequency-grading control method makes the supercritical carbon dioxide power cycle response lag behind the change of user load. Therefore, without changing the variable load rate of the supercritical carbon dioxide power cycle, improving the control command of the all-vanadium liquid flow battery SOC on the supercritical carbon dioxide power cycle output to follow-up control can effectively improve the load following characteristics of the supercritical carbon dioxide power cycle. This means that the output command of the supercritical carbon dioxide power cycle changes in real time with the SOC of the all-vanadium liquid flow battery, rather than a sudden change after the SOC reaches a certain threshold. The control equations of linear follow-up control and circular follow-up control are expressed by equations (2) and (3), respectively.

[0033]

[0034]

[0035] Table 1 shows the power purchase rate and power abandonment rate of the composite energy supply system under typical operating conditions when the basic frequency classification control method and the frequency classification control method through follow-up control optimization instructions are applied.

[0036] Table 1

[0037] Control Methods Electricity purchase rate Power abandonment rate average Frequency Grading Control Method 0.31％ 0.03％ 0.17％ Frequency Grading + Linear Follow-up 0.21％ 0.03％ 0.12％ Frequency classification + circular follow-up 0.03％ 0.01％ 0.02％

[0038] Combined with Table 1, it can be seen that Figure 3 Under the typical operating conditions shown, after the follow-up control optimization instructions, the power purchase rate and power abandonment rate of the hybrid energy supply system are reduced, indicating that the follow-up control can reduce the energy loss of the system and realize the efficient operation of the hybrid energy supply system.

[0039] Based on the physical characteristics and response time of different subsystems, the present invention proposes a frequency-graded multi-time-scale energy control method suitable for composite energy supply systems. The present invention can realize multi-time-scale energy control of "source-grid-load-storage" composite energy supply systems under random and real-time dynamic complex working conditions on both sides, and help high-proportion new energy consumption and efficient and stable operation of new power systems.

Claims

1. A frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system, wherein the composite energy supply system comprises a source-side subsystem, a grid-side subsystem, a load-side subsystem and a storage-side subsystem; the frequency-graded multi-time-scale energy management and control method comprises the following steps: Step 1: Arrange the subsystems in order of high frequency, medium frequency, and low frequency according to their different response rates; Step 2: Control the power state of the medium-frequency subsystem through the capacity state of the high-frequency subsystem, and control the power state of the low-frequency subsystem through the capacity state of the medium-frequency subsystem, so that the output and load of each subsystem respond step by step from fast to slow without frequency domain decomposition; Step 3: According to the dynamic operation characteristics of the composite energy supply system, optimize the control instructions to achieve efficient and stable operation of the system.

2. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 1 is characterized in that: In the step 1, the frequencies are arranged step by step according to the time series, and the frequency classification range is: the high-frequency response time is seconds or less, the low-frequency response time is minutes or more, and the medium-frequency response time is between the high-frequency response time and the low-frequency response time.

3. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 2 is characterized in that: The high frequency response time is less than 1 second, the medium frequency response time is 1 second to 1 minute, and the low frequency response time is greater than 1 minute.

4. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 1 is characterized in that: The source-side subsystem includes new energy and conventional energy, the new energy includes photovoltaic cells, and the conventional energy includes supercritical carbon dioxide (S-CO2) power cycle; the grid-side subsystem includes a large power grid and a micro-energy grid; the load-side subsystem includes electrical loads and cold and hot loads; the storage-side subsystem includes a vanadium redox battery (VRB); step 2 includes high-frequency control, medium-frequency control and low-frequency control, specifically: ① High-frequency control, calculating the difference power through the real-time output of the source-side subsystem and the load-side subsystem; ② Medium frequency control, using the real-time output of the source-side subsystem to control the charging and discharging power of the storage-side subsystem; when the difference in power is greater than zero, the all-vanadium liquid flow battery is charged, otherwise, the all-vanadium liquid flow battery is discharged; ③ Low-frequency control, using the state of charge (SOC) of the all-vanadium liquid flow battery to control the output command (W / W) of the supercritical carbon dioxide power cycle design ), the control equation is (1), the control command boundary SOC = 40% and 60%, the supercritical carbon dioxide power cycle output command W / W design = a%, b%, and c%; Where W is the actual power of supercritical carbon dioxide power cycle, W design is the rated power of the supercritical carbon dioxide power cycle, 80<a≤100, 60<b≤80, 40≤c≤60.

5. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 4 is characterized in that: The optimization control instruction method of step 3 includes hysteresis control and follow-up control.

6. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 5, characterized in that: The hysteresis control is the hysteresis control of the SOC of the all-vanadium liquid flow battery to the output command of the supercritical carbon dioxide power cycle. The control equation is formula (2). The hysteresis position is the boundary of the control command, and the hysteresis range is ±5%; 7. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 5, characterized in that: The following motion control includes linear following motion and circular following motion.

8. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 7, characterized in that: The linear follow-up control equation is formula (3); 9. The frequency-graded multi-time-scale energy management and control method applicable to a composite energy supply system according to claim 7, characterized in that: The circular follower, the control equation is formula (4);

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