CN107645172B - Control method and device for DC/DC converter of energy storage device of distributed power generation system - Google Patents
Control method and device for DC/DC converter of energy storage device of distributed power generation system Download PDFInfo
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Abstract
The invention discloses a control method and a device for a DC/DC converter of an energy storage device in a distributed power generation system, wherein the control method comprises the following steps: detecting and obtaining at least two types of parameters of the energy storage device, the parameters of the power generation device in the distributed power generation system and the parameters of the load; and generating a control strategy by using a genetic method according to the parameters to control the DC/DC converter. The control device comprises a single chip microcomputer, an RS232 communication interface circuit, a power circuit and a display circuit. The control method and the control device of the DC/DC converter can generate an optimized control strategy according to the actual power generation condition of the distributed power generation system, so that the charging and discharging control of the DC/DC converter is matched with the power generation device and the load in the distributed power generation system to operate, and the optimal control of the distributed power generation system is realized.
Description
Technical Field
The invention relates to the field of distributed power generation, in particular to a control method and a control device for a DC/DC converter of an energy storage device in a distributed power generation system.
Background
Renewable energy has received increasing attention and is considered as a powerful supplement to relieve the pressure of traditional energy sources. Distributed power generation based on photovoltaic power generation, wind power generation, geothermal heat and the like is a hot point of current research.
Active power output by distributed power generation systems such as photovoltaic power generation and wind power generation is greatly influenced by environments, such as wind speed, wind direction, temperature, illumination intensity and the like. When one or more of the environmental factors change, the output power of the distributed power generation system fluctuates greatly. When the distributed power generation system is operated in a grid-connected mode, voltage and frequency of a grid-connected port are fluctuated due to large grid-connected power fluctuation; when the distributed power generation system operates in an isolated island mode and is directly loaded, the reliability of power supply is affected by large output power fluctuation. Therefore, in the distributed power generation system, a corresponding energy storage device is generally configured to stabilize the fluctuation of the output power of the distributed power generation system.
The energy storage device consists of a storage battery and a DC/DC converter, wherein the storage battery is a storage device of energy, and the DC/DC converter is a key device for controlling the charging and discharging of the storage battery. According to different combination modes of the energy storage device and the distributed power generation system, the control of the traditional DC/DC converter is mainly divided into the following two types:
(1) the distributed power generation system, the energy storage device and the load operate in a cascading mode. When resources such as wind energy, illumination and the like are sufficient, the distributed power generation system firstly charges the energy storage device, and the DC/DC converter is controlled as a charger in the charging process; when the load needs to use electricity, the storage battery is discharged through the DC/DC converter, and the DC/DC converter is controlled to be a discharged boost converter.
(2) The distributed power generation system and the energy storage device run in parallel. The output power of the distributed power generation system is connected with the output port of the energy storage device in parallel, and under the condition that the output power of the distributed power generation system fluctuates, the output power of the energy storage device is complementary with the output power of the energy storage device, so that the output power of the parallel system is a stable value, and at the moment, the DC/DC converter of the energy storage device is mainly used as a discharging boost converter. When the load does not need to be supplied with power, the DC/DC converter is controlled as a charger to charge the battery.
As described above, in the conventional DC/DC control, the logic selection judgment for the charge control or the discharge control of the DC/DC converter is simple, and such a logic judgment program is generally provided in the control circuit of the DC/DC converter. The control of the DC/DC converter realizes the charge and discharge control of the storage battery, and does not consider the problem of the optimal operation mode of the whole system, for example, the problems of the charge/discharge times and the discharge depth of the storage battery are not considered when the storage battery is charged and discharged, however, the charge/discharge times and the discharge depth of the storage battery are important factors influencing the service life of the storage battery; in a conventional control strategy of the DC/DC converter, when the storage battery is charged and discharged, the power generation state, the load operation state, and the electric quantity state of the storage battery of various distributed power generation systems are not considered at the same time, which results in a reduction in the power generation utilization rate of the distributed power generation systems.
Disclosure of Invention
The invention aims to provide a control method and a control device for a DC/DC converter of an energy storage device in a distributed power generation system, which simultaneously consider one or more factors of the power generation state, the load running state, the electric quantity state of a storage battery, the charging/discharging times of the storage battery and the discharging depth of the storage battery of various distributed power generation systems to generate an optimized control strategy, thereby prolonging the service life of the storage battery in the energy storage device and improving the power generation utilization rate of the power generation system.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method of controlling a DC/DC converter for an energy storage device in a distributed power generation system, comprising the steps of:
detecting and obtaining at least two types of parameters of the energy storage device, the parameters of the power generation device in the distributed power generation system and the parameters of the load; the parameters of the energy storage device comprise at least one of first output voltage/current, a charge state, charging times, discharging times and discharging depth, the parameters of the power generation device in the distributed power generation system comprise second output voltage/current, and the parameters of the load comprise load current;
and generating a control strategy by using a genetic method according to the parameters to control the DC/DC converter.
Further, in the above method, the generating a control strategy by a genetic method based on the parameter to control the DC/DC converter includes:
the historical parameters of the previous period are used as parameters in a genetic algorithm, and a historical control strategy comprising historical discharge times and historical discharge depth is calculated by using the genetic algorithm;
and taking the parameters obtained by real-time detection, the historical discharge times and the historical discharge depth as parameters in a genetic algorithm, and calculating a real-time control strategy by using the genetic algorithm, wherein the real-time control strategy comprises the steps of controlling the discharge operation and the charge operation of a storage battery, the grid-connected operation of a distributed power generation device and the off-grid operation of the distributed power generation device, and controlling the DC/DC converter by using the real-time control strategy.
Further, in the above method, the historical parameters of the above one period are used as parameters in a genetic algorithm, and a historical control strategy is calculated by using the genetic algorithm, including the steps of:
constructing an objective function based on the minimum operation cost principle;
establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in the objective function, and the variables comprise the discharge times and the generated energy of the power generation device, and the generated energy of the power generation device is obtained by calculating the second output voltage/current and time;
determining constraint conditions including a discharge depth range and power balance;
and performing intersection, variation population calculation and excellent population screening, and generating a historical control strategy after a set genetic algebra is reached to obtain historical discharge times and historical discharge depth data.
Further, in the above method, the calculating a real-time control strategy by using the genetic algorithm with the parameters obtained by real-time detection, the historical discharge times and the historical discharge depth as parameters in the genetic algorithm includes:
constructing an objective function based on the minimum operation cost principle;
establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in an objective function, and the variables comprise historical discharge times, historical discharge depth, power generation power of a power generation device, load current and charge state;
determining constraint conditions including a discharge depth range and power balance;
and performing crossing, variation population calculation and excellent population screening, and generating a real-time control strategy after a set genetic algebra is reached, wherein the real-time control strategy comprises the steps of controlling the discharging operation and the charging operation of a storage battery, the grid-connected operation of a distributed power generation device and the off-grid operation of the distributed power generation device.
Meanwhile, the embodiment of the invention also provides a control device of the DC/DC converter of the energy storage device in the distributed power generation system, which comprises a singlechip, an RS232 communication interface circuit, a power circuit and a display circuit, wherein,
the singlechip processes and operates the data based on a genetic method and generates a control strategy; the data is at least two types of parameters of the energy storage device, parameters of a power generation device in the distributed power generation system and parameters of a load obtained through detection;
the RS232 communication interface circuit is used for realizing communication with the energy storage device, the power generation device and the load so as to obtain corresponding parameters;
the power supply circuit is used for providing required electric energy for the control device;
and the display circuit is used for displaying the operation state of the distributed power generation system.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a control method and a device for a DC/DC converter of an energy storage device in a distributed power generation system, wherein the control device simultaneously detects the power generation state of each distributed power generation device, the power utilization state of a load and the power state information of a storage battery, and generates an optimization control strategy based on a genetic algorithm according to the detection data and considering the discharge depth and the charge and discharge times of the storage battery, namely, the charge and discharge of the DC/DC converter of the energy storage device are optimally controlled, so that the service life of the storage battery in the energy storage device and the power generation utilization rate of the distributed power generation system are improved.
Drawings
Fig. 1 is a block diagram of a control device of a DC/DC converter of an energy storage device in a distributed power generation system according to the present invention;
FIG. 2 is a flow chart of a control method of the DC/DC converter;
FIG. 3 is a flow chart of a calculation of a genetic algorithm.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, a control apparatus for a DC/DC converter of an energy storage device in a distributed power generation system according to an embodiment of the present invention includes: based on STM32 singlechip, RS232 communication interface circuit, power supply circuit, display circuit.
Based on STM32 singlechip includes: an I/O circuit for reading/outputting data; the Flash memory is used for storing data and programs; and the CPU is used for calculating the data and generating a corresponding control strategy.
The RS232 communication interface circuit is used for communicating with a power generation device, an energy storage device (comprising a storage battery and a DC/DC converter) and a load in the distributed power generation system so as to obtain corresponding parameters, namely obtaining the operating condition information of the power generation device, the load and the storage battery, such as the parameters of the energy storage device, including at least one of first output voltage/current, charge state, charging times, discharging times and discharging depth; parameters of the power generation device, including the second output voltage/current; parameters of the load, including load current.
In this embodiment, the single chip microcomputer processes the data based on a genetic algorithm to obtain a corresponding control strategy. When the intelligent controller operates, as shown in fig. 2, the single chip microcomputer starts self-checking, wherein the self-checking includes temperature protection, voltage protection and current protection, and after the self-checking is normal, the single chip microcomputer calls a genetic algorithm program to process data of operating conditions of the power generation device, the load and the storage battery in the distributed mode, so that an optimized control strategy is generated and output through an RS232 communication port, so that charging and discharging operations of the DC/DC converter are controlled, and meanwhile, the power generation device and the energy storage device are controlled to operate in a matched mode.
The process of generating the optimized control strategy is divided into two parts, wherein the first part is an optimized result obtained by adopting historical data of the distributed power generation system in a certain period after the distributed power generation system operates for the certain period, and the optimized result comprises the historical discharge depth and the historical discharge times of the storage battery; and the second part is that an algorithm generates a real-time control strategy according to real-time operation data of the distributed power generation system and the historical discharge depth and the historical discharge times of the first part, so that the discharge and charge operation of the storage battery is controlled. Namely, the historical parameters of the previous period are used as parameters in a genetic algorithm, and a historical control strategy comprising historical discharge times and historical discharge depth is calculated by using the genetic algorithm; and taking the parameters obtained by real-time detection, the historical discharge times and the historical discharge depth as parameters in a genetic algorithm, and calculating a real-time control strategy by using the genetic algorithm, wherein the real-time control strategy comprises the steps of controlling the discharge operation and the charge operation of a storage battery, the grid-connected operation of a distributed power generation device and the off-grid operation of the distributed power generation device, and controlling the DC/DC converter by using the real-time control strategy. Meanwhile, the real-time control strategy also comprises real-time discharge times and real-time discharge depth data which are used as data sources for calculating historical discharge times and historical discharge depth in one period.
In order to ensure the stable operation of the distributed power generation system, after each time of generation of the optimal control strategy, the distributed power generation system keeps stable operation for a period of timet p And then, the genetic algorithm continues to operate to obtain the latest optimization control algorithm.
The ultimate goal of using genetic algorithms is to minimize the operating cost of the distributed power generation system. In the operation of the distributed power generation system, factors increasing the operation cost of the system are the maintenance cost of the distributed power generation device and the maintenance cost of the storage battery, wherein the maintenance cost of the distributed power generation device is related to the power generation amount of the distributed power generation device, and the larger the power generation amount is, the higher the maintenance cost is; the maintenance cost of the storage battery is related to the discharge depth and the discharge frequency of the storage battery, and the deeper the discharge depth of the storage battery is, the more the discharge frequency is, the lower the service life of the storage battery is, and the higher the corresponding maintenance cost is. The factors for reducing the system operation cost are the benefit of the power generation amount of the distributed power generation device and the benefit of the storage battery discharge, and the two benefits are respectively related to the power generation amount of the distributed power generation device and the discharge depth and the discharge frequency of the storage battery, namely, the greater the power generation amount of the distributed power generation device is, the greater the discharge amount of the storage battery is (the greater the discharge frequency is and the greater the discharge depth is), the greater the benefit is.
Therefore, the operation cost of the distributed power generation system has a nonlinear relationship with the power generation amount of the distributed power generation device and the discharge depth and the discharge frequency of the storage battery, the control method and the control device adopt a genetic algorithm to optimize and calculate the variables, and finally generate an optimized control strategy, and the lowest operation cost of the distributed power generation system is realized by intelligent charging and discharging control of the DC/DC converter.
The calculation flow of the genetic algorithm is shown in fig. 3. Therefore, in this embodiment, the historical parameters of the above one period are used as parameters in a genetic algorithm, and the historical control strategy is calculated by using the genetic algorithm, including the steps of:
constructing an objective function based on the minimum operation cost principle;
establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in the objective function, and the variables comprise the discharge times and the generated energy of the power generation device, and the generated energy of the power generation device is obtained by calculating the second output voltage/current and time;
determining constraint conditions including a discharge depth range and power balance;
and performing intersection, variation population calculation and excellent population screening, and generating a historical control strategy after a set genetic algebra is reached to obtain historical discharge times and historical discharge depth data.
The real-time control strategy is calculated by using the parameters obtained by real-time detection, the historical discharge times and the historical discharge depth as the parameters in the genetic algorithm and utilizing the genetic algorithm, and the method comprises the following steps:
constructing an objective function based on the minimum operation cost principle;
establishing an initial population, wherein parameters of the initial population are variables influencing the operation cost in an objective function, and the variables comprise historical discharge times, historical discharge depth, power generation power of a power generation device (determined by instantaneous output voltage/current of the power generation device), load current and charge state;
determining constraint conditions including a discharge depth range and power balance;
and performing crossing, variation population calculation and excellent population screening, and generating a real-time control strategy after a set genetic algebra is reached, wherein the real-time control strategy comprises the steps of controlling the discharging operation and the charging operation of a storage battery, the grid-connected operation of a distributed power generation device and the off-grid operation of the distributed power generation device.
Since the genetic algorithm is an existing algorithm, in the present embodiment, processes of constructing an objective function, creating an initial population, performing intersection, mutation, calculating a variant population, selecting an excellent population, and performing genetic iteration in the genetic algorithm are not described in detail, and a person skilled in the art can unambiguously learn a corresponding specific process according to the description.
The invention adopts a single chip microcomputer based on STM32 to build a control platform, and is also provided with an RS232 communication interface circuit, a power supply circuit and a display circuit. And the genetic algorithm is implanted into a single chip program, an optimization control strategy is generated under the condition of considering both the running condition of each distributed power generation device and the running condition of the storage battery, and the utilization rate of distributed energy resources is improved, the service life of the storage battery is prolonged and the optimal running of the distributed power generation system is achieved by controlling the charging and discharging of the DC/DC converter of the energy storage device.
Claims (5)
1. A control method for a distributed power generation system energy storage device DC/DC converter, comprising the steps of:
detecting and obtaining at least two types of parameters of the energy storage device, the parameters of the power generation device in the distributed power generation system and the parameters of the load; the parameters of the energy storage device comprise at least one of first output voltage and first output current, a charge state, charging times, discharging times and discharging depth, the parameters of the power generation device in the distributed power generation system comprise second output voltage and second output current, and the parameters of the load comprise load current;
generating a control strategy by using a genetic method according to the parameters to control the DC/DC converter, and comprising the following steps of: the historical parameters of the previous period are used as parameters in a genetic algorithm, and a historical control strategy comprising historical discharge times and historical discharge depth is calculated by using the genetic algorithm; taking parameters obtained by real-time detection, the historical discharge times and the historical discharge depth as parameters in a genetic algorithm, and calculating a real-time control strategy by using the genetic algorithm, wherein the real-time control strategy comprises control of storage battery discharge operation, charging operation, distributed power generation device grid-connected operation and off-grid of the distributed power generation device, and the DC/DC converter is controlled by the real-time control strategy;
wherein, the historical parameters of the above one period are used as parameters in a genetic algorithm, and the historical control strategy is calculated by utilizing the genetic algorithm, which comprises the following steps: constructing an objective function based on the minimum operation cost principle; establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in an objective function, and the parameters comprise the discharge times and the generated energy of a power generation device; determining constraints including depth of discharge range and power balance; and performing intersection, variation population calculation and excellent population screening, and generating a historical control strategy after a set genetic algebra is reached to obtain historical discharge times and historical discharge depth data.
2. The method according to claim 1, wherein the real-time control strategy is calculated by using a genetic algorithm according to the parameters obtained by real-time detection and the historical discharge times and the historical discharge depth as parameters in the genetic algorithm, and the method comprises the following steps:
constructing an objective function based on the minimum operation cost principle;
establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in an objective function, and the variables comprise historical discharge times, historical discharge depth, power generation power of a power generation device, load current and charge state;
determining constraints including depth of discharge range and power balance;
and performing crossing, variation population calculation and excellent population screening, and generating a real-time control strategy after a set genetic algebra is reached, wherein the real-time control strategy comprises the control of the discharge operation and the charge operation of a storage battery, the grid-connected operation of a distributed power generation device and the off-grid of the distributed power generation device.
3. A control device for a DC/DC converter of an energy storage device of a distributed power generation system is characterized by comprising a singlechip, an RS232 communication interface circuit, a power supply circuit and a display circuit, wherein,
the historical parameters of the singlechip in the previous period are used as parameters in a genetic algorithm, a historical control strategy is calculated by using the genetic algorithm, the historical control strategy comprises historical discharge times and historical discharge depth, the parameters obtained by real-time detection and the historical discharge times and the historical discharge depth are used as parameters in the genetic algorithm, a real-time control strategy is calculated by using the genetic algorithm, the real-time control strategy comprises control over discharge operation and charge operation of a storage battery, grid-connected operation of a distributed power generation device and off-grid of the distributed power generation device, and the DC/DC converter is controlled by using the real-time control strategy; the data is at least two types of parameters of the energy storage device, the parameters of the power generation device in the distributed power generation system and the parameters of the load obtained through detection;
the historical parameters of the previous period are used as parameters in a genetic algorithm, and a historical control strategy is calculated by using the genetic algorithm, and the method comprises the following steps: constructing an objective function based on the minimum operation cost principle; establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in an objective function, and the parameters comprise the discharge times and the generated energy of a power generation device; determining constraints including depth of discharge range and power balance; performing crossing, mutation, variant population calculation and excellent population screening, and generating a historical control strategy after a set genetic algebra is reached to obtain historical discharge times and historical discharge depth data;
the RS232 communication interface circuit is used for realizing communication with the energy storage device, the power generation device and the load so as to obtain corresponding parameters;
the power supply circuit is used for providing required electric energy for the control device;
and the display circuit is used for displaying the operation state of the distributed power generation system.
4. The apparatus of claim 3, wherein the single chip microcomputer is an STM32 single chip microcomputer.
5. The apparatus of claim 3, wherein the real-time control strategy is calculated by using a genetic algorithm with the parameters obtained by real-time detection and the historical discharge times and the historical discharge depth as parameters in the genetic algorithm, and the method comprises the following steps:
constructing an objective function based on the minimum operation cost principle;
establishing an initial population, wherein the parameters of the initial population are variables influencing the operation cost in an objective function, and the variables comprise historical discharge times, historical discharge depth, power generation power of a power generation device, load current and charge state;
determining constraints including depth of discharge range and power balance;
and performing crossing, variation population calculation and excellent population screening, and generating a real-time control strategy after a set genetic algebra is reached, wherein the real-time control strategy comprises the control of the discharge operation and the charge operation of a storage battery, the grid-connected operation of a distributed power generation device and the off-grid of the distributed power generation device.
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| CN104242335A (en) * | 2014-06-30 | 2014-12-24 | 江苏华大天益电力科技有限公司 | Wind and light storage generating unit capacity optimal configuration method based on rated capacity |
| CN104485727A (en) * | 2014-12-26 | 2015-04-01 | 广州市香港科大霍英东研究院 | Off-grid photovoltaic power generation energy storage system and energy dispatching method thereof |
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| CN104242335A (en) * | 2014-06-30 | 2014-12-24 | 江苏华大天益电力科技有限公司 | Wind and light storage generating unit capacity optimal configuration method based on rated capacity |
| CN104485727A (en) * | 2014-12-26 | 2015-04-01 | 广州市香港科大霍英东研究院 | Off-grid photovoltaic power generation energy storage system and energy dispatching method thereof |
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