CN110601238A - Intelligent micro-grid peak regulation controller of energy storage system - Google Patents
Intelligent micro-grid peak regulation controller of energy storage system Download PDFInfo
- Publication number
- CN110601238A CN110601238A CN201910735033.3A CN201910735033A CN110601238A CN 110601238 A CN110601238 A CN 110601238A CN 201910735033 A CN201910735033 A CN 201910735033A CN 110601238 A CN110601238 A CN 110601238A
- Authority
- CN
- China
- Prior art keywords
- pcs
- data
- module
- controller
- energy storage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004146 energy storage Methods 0.000 title claims abstract description 25
- 238000004891 communication Methods 0.000 claims abstract description 18
- 238000011217 control strategy Methods 0.000 claims abstract description 14
- 230000006870 function Effects 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 4
- 230000010354 integration Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 3
- 230000002093 peripheral effect Effects 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 230000005540 biological transmission Effects 0.000 claims 1
- 238000007599 discharging Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 8
- 230000008901 benefit Effects 0.000 description 3
- 238000000034 method Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000011664 signaling Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
Abstract
The invention provides an intelligent microgrid peak regulation controller of an energy storage system, which comprises a communication management module, a data acquisition module and a control strategy module. The microgrid controller can be operated by a single machine in a microgrid system, and a plurality of devices can be connected in parallel and operated on line. When the single machine runs, the controller combines PCS/BMS data and a set fixed value to realize peak shaving control on the energy storage system; the controllers are interconnected through a ring network switching module during online operation, one of the controllers is a host, the other controllers are slaves, the slaves collect information of the PCS and the BMS and send the information to the host, and the host controls systems of the slaves respectively by combining feedback states of the slaves. The intelligent microgrid controller provided by the invention can directly carry out peak shaving control on the PCS according to the equipment state and the preset value, can receive an AGC command, and has short time delay and high efficiency.
Description
Technical Field
The invention relates to the technical field of power distribution, in particular to an intelligent micro-grid peak regulation controller of an energy storage system.
Background
One of the main functions of the energy storage system is peak shaving, charging in idle time and discharging in peak time are matched with a dispatching center for control, and the energy storage system can perform the functions of peak shaving, valley filling, reactive compensation and the like on a power grid, so that the power quality is improved, and the power supply reliability is improved. A complete energy storage system consists of a battery, a BMS battery management system, a PCS energy storage converter, a protocol converter and an EMS electric energy management system, and the EMS electric energy management system realizes a peak shaving strategy and responds to an AGC dispatching command. The EMS system is generally realized in a computer background, a computer needs to be configured independently, a central control room needs to be built for placing the EMS background in a user energy storage station, the project cost and the project implementation difficulty are increased, and the EMS system runs on a non-real-time operating system and has certain time delay for responding to an AGC command.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides an intelligent microgrid peak regulation controller for an energy storage system, which realizes the function integration of field electrical quantity acquisition, protocol conversion and peak regulation control strategies, can realize two functions of protocol converter and EMS management in the energy storage system, and has great advantages in application occasions with scattered energy storage box transformer substation arrangement or small energy storage capacity.
The invention comprises the following steps: the device comprises a communication management module, a data acquisition module and a control strategy module. The communication management module realizes communication integration of PCS and BMS, monitors the state of the system in real time, receives an AGC command, and completes data interaction between the master and the slave in a ring network mode when a plurality of machines run in parallel; the data acquisition module acquires incoming line, PCS and load voltage and current and calculates power of each path; the control strategy module is the core of the invention, collects the data of other modules, realizes the strategies of peak clipping and valley filling, load tracking, demand control and the like, realizes the control strategies of the host and each slave when a plurality of machines run in parallel, and outputs the control result to the PCS through the communication management module for execution.
The communication management module is specifically as follows:
1. the device is connected with devices such as a PCS, a BMS, an air conditioner, an ammeter and the like through an RS485 interface, a CAN interface and an Ethernet interface, reads the electrical quantity information of the devices and executes setting operation;
2. the method comprises the steps of connecting scheduling through an Ethernet interface, and receiving an AGC scheduling command;
3. when multiple machines run in parallel, the data interaction between the master machine and the slave machine is realized through the ring network;
4. the microgrid system information can be transmitted to a background through communication between the RS485 interface and the background or an Ethernet interface, and a background command is executed.
The data acquisition module specifically comprises the following components:
1. the FPGA controls 2 AD acquisition incoming lines, PCS, load current signals and bus voltage signals and sends the signals to the CPU;
2. and the FPGA is used for acquiring an input signal and controlling the output and the like.
The control strategy module is specifically as follows:
1. operating a peak shaving strategy;
2. and operating the multi-machine parallel control strategy when the multi-machine parallel operation is performed.
The peak regulation strategy has peak clipping and valley filling, demand control and load tracking, and also has a trickle charge-discharge function, a dynamic demand control function and a flat-period charge amount self-learning function;
one of the machines is set as a master machine and the other machines are set as slave machines when the multiple machines run in parallel, data between the master machine and the slave machines are interacted through a ring network of the communication control module, and the master machine performs overall control according to the data of the master machine and the slave machines and distributes the data to the slave machines.
The invention has the beneficial effects that:
a complete energy storage system consists of a battery, a BMS battery management system, a PCS energy storage converter, a protocol converter and an EMS electric energy management system, and the EMS electric energy management system realizes a peak shaving strategy and responds to an AGC dispatching command. The EMS system is generally realized in a computer background, an independent computer needs to be configured, a central control room is also required to be built for placing the EMS background in the user energy storage station, the project cost and the project implementation difficulty are increased, and the response delay of the AGC command is long as the EMS system is operated on a non-real-time operating system. The controller can realize two functions of protocol converter and EMS management in the energy storage system, has great advantages in application occasions with scattered energy storage box transformer substation arrangement or small energy storage capacity, can be installed on a box transformer substation switch cabinet on site, has a perfect charging and discharging control strategy, and can respond to AGC dispatching control commands in real time.
Drawings
Fig. 1 is a schematic diagram of a hardware configuration according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a stand-alone system according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a topology when multiple machines are connected in parallel according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a system for parallel connection of multiple units according to an embodiment of the present invention.
Detailed Description
The invention will be further explained with reference to the drawings.
The invention is further described below with reference to the figures and examples.
The intelligent microgrid controller of the energy storage system comprises a communication management module, a data acquisition module and a control strategy module. Fig. 1 is a schematic diagram of a hardware structure of this embodiment, and the working principle of each module is as follows:
the communication management module mainly comprises a CPU2 and an FPGA 2.
The FPGA2 expands a serial port and a CAN interface, the serial port is used for integrating information of devices such as PCS and air conditioners, and the CAN interface is used for integrating information of BMS. After reading the information, the CPU2 sends the information to the CPU1 through an Ethernet interface for policy control; and the data is forwarded to a cloud terminal through a serial port 4G module for remote monitoring.
The CPU2 has 3 ethernet interfaces, one for data exchange with the CPU1, one for receiving AGC commands, and another for on-line interfacing when multiple machines are connected in parallel.
The CPU2 sends a command to the PCS to execute immediately upon receiving the AGC command, while notifying the CPU1 that it is currently in AGC control mode.
And the data acquisition module consists of an FPGA1 and an AD. The FPGA1 controls AD to perform analog quantity sampling, and data acquisition of bus voltage, incoming line current, load current and PCS current is realized; meanwhile, the FPGA1 realizes the functions of input acquisition, anti-shake processing, output control and the like. The CPU1 can read the collected data periodically through the data bus.
And the control strategy module mainly comprises a CPU1, a peripheral memory device Flash, an external RAM and the like. The CPU1 reads the data collected by the data collecting module through the data bus at regular time, and obtains the incoming line power, the load power and the PCS power through calculation, and controls the tripping operation when necessary. The CPU1 reads PCS and BMS real-time data integrated by the communication management module through the ethernet, and sends a returned execution result to the communication management module for execution after the policy processing.
Fig. 2 is a schematic diagram of a stand-alone system, and the device monitors line incoming power Pm1 at a point M1, charging and discharging power Pm2 at a point M2, and load power Pm3 at a point M3 in real time.
The peak regulation control strategy comprises: peak clipping and valley filling, demand control and load tracking; in addition, the system also has a trickle charge-discharge function, a dynamic demand control function and a flat period charge amount self-learning function.
The dynamic demand control implementation method comprises the following steps: firstly, the incoming line power is calculated according to the voltage and current collected by the data collection module, and the maximum incoming line power in a week is counted to be used as the historical demand value of the day. The dynamic demand control mode has a day mode and a week mode, the week mode selects the historical demand before a week, and the day mode selects the historical demand of the previous day to control the demand, and the specific control mode is as follows:
monitoring incoming line power Pm1 and load power Pm3 in real time, and when the increase of Pm1 exceeds the selected historical demand value Pmax, if the current state is in a charging state, rapidly reducing the charging power Pm2 to control the Pm1 to be below the Pmax; if the current state is in a discharging state, the discharging power Pm2 is rapidly increased, and Pm1 is controlled to be smaller than Pmax.
The above charge power and discharge power Pm2 has a calculation formula of Pm2= Pmax-Pm 3; the charging power is assumed to be positive and the discharging power is assumed to be negative.
The method for realizing the self-learning function of the charging quantity in the flat time period comprises the following steps: and counting the historical discharge quantity delta SOC of the battery in the second discharge period of each day in the last week, namely, the electric quantity SOC1 when the battery enters the discharge period and the electric quantity SOC2 when the battery enters the discharge period, stopping charging when the battery electric quantity required to be charged in the ordinary period reaches the historical discharge quantity, ensuring that the charging quantity in the ordinary period is equal to the discharge quantity in the subsequent discharge period, and realizing the maximization of economic benefit.
The normal period charging amount learning mode has a day mode and a week mode, wherein the week mode takes the discharging amount of the second discharging period before one week, the day mode takes the discharging amount of the second discharging period before one day, and the current normal period charging stop threshold value is calculated.
Fig. 3 is a schematic diagram of a topology structure when multiple controllers are connected in parallel, multiple controllers are connected into a ring network local area network through a ring network board of the device, one of the controllers is set as a master, the other controllers are set as slaves, the master receives respective PCS power and states of the slaves, and calculates load power according to incoming line power.
FIG. 4 is a schematic diagram of a system with multiple parallel machines.
The controller can support at most 33 main and auxiliary machines (1 main and 32 auxiliary machines) to charge and discharge online. When a plurality of energy storage cabinets are in a micro-grid system, in order to prevent the situation that the compensation total power is not matched with the load when each energy storage cabinet operates independently, the information quantity of each slave computer is read by the host computer, and then the charging and discharging power of each slave computer is distributed comprehensively according to the battery capacity proportion set by each slave computer.
In the figure, the power of M2 point can be obtained by additionally installing a current transformer and performing acquisition and calculation by a master computer, and the power of each master computer and each slave computer can be calculated on the spot where the transformer is inconvenient to install, wherein the power of Pm2= Pm21+ Pm22+ … + Pm2 n.
While the invention has been described in terms of its preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention.
Claims (5)
1. The utility model provides an energy storage system intelligence microgrid peak regulation controller which characterized in that: the system comprises a communication management module, a data acquisition module and a control strategy module;
the data acquisition module acquires bus voltage, incoming line current, load current and PCS charge-discharge current, and calculates the incoming line power, the load power and the charge-discharge power;
the control strategy module is connected between the data acquisition module and the communication management module and has a dynamic demand control function and a flat-period charging amount self-learning function;
the communication management module is provided with a plurality of serial ports, a CAN port and an Ethernet port, and realizes the integration of information of devices such as PCS/BMS of the energy storage system and the data transmission of a background.
2. The intelligent microgrid peak shaving controller of claim 1, characterized in that: the controllers are interconnected through a ring network and run in parallel in a local area network, one controller is set as a host, and the other controllers are slaves.
3. The intelligent microgrid peak shaving controller of claim 1, characterized in that: the communication management module mainly comprises a CPU2 and an FPGA 2;
the FPGA2 expands a serial port and a CAN interface, the serial port is used for integrating information of devices such as PCS and air conditioners, and the CAN interface is used for integrating information of BMS;
after reading the information, the CPU2 sends the information to the CPU1 through an Ethernet interface for policy control; the data is forwarded to a cloud end through a serial port connection 4G module for remote monitoring;
the CPU2 has 3 Ethernet interfaces, one is used for data exchange with the CPU1, one is used for receiving AGC commands, and the other is used for an online interface when multiple computers are connected in parallel;
the CPU2 sends a command to the PCS to execute immediately upon receiving the AGC command, while notifying the CPU1 that it is currently in AGC control mode.
4. The intelligent microgrid peak shaving controller of claim 1, characterized in that: the data acquisition module consists of an FPGA1 and an AD; the FPGA1 controls AD to perform analog quantity sampling, and data acquisition of bus voltage, incoming line current, load current and PCS current is realized; meanwhile, the FPGA1 realizes the functions of input acquisition, anti-shake processing, output control and the like; the CPU1 periodically reads the collected data through the data bus.
5. The intelligent microgrid peak shaving controller of claim 1, characterized in that: the control strategy module mainly comprises a CPU1, a peripheral memory device Flash and an external RAM; the CPU1 reads the data collected by the data collecting module through the data bus at regular time, and obtains the incoming line power, the load power and the PCS power through calculation, and controls the tripping operation when necessary; the CPU1 reads PCS and BMS real-time data integrated by the communication management module through the ethernet, and sends a returned execution result to the communication management module for execution after the policy processing.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910735033.3A CN110601238A (en) | 2019-08-09 | 2019-08-09 | Intelligent micro-grid peak regulation controller of energy storage system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910735033.3A CN110601238A (en) | 2019-08-09 | 2019-08-09 | Intelligent micro-grid peak regulation controller of energy storage system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110601238A true CN110601238A (en) | 2019-12-20 |
Family
ID=68853823
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910735033.3A Pending CN110601238A (en) | 2019-08-09 | 2019-08-09 | Intelligent micro-grid peak regulation controller of energy storage system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110601238A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112838619A (en) * | 2020-12-30 | 2021-05-25 | 山东大学 | Energy storage converter parallel operation system and method based on high-speed serial optical fiber |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102010023112A1 (en) * | 2010-06-07 | 2011-12-08 | Siemens Aktiengesellschaft | Energy transfer device |
| CN106356901A (en) * | 2016-10-09 | 2017-01-25 | 江苏现代能源微网系统有限公司 | Micro-grid energy regulation method suitable for single residence |
| CN108110762A (en) * | 2018-01-29 | 2018-06-01 | 阳光电源股份有限公司 | A kind of alternating current-direct current mixing micro-capacitance sensor and its control method |
-
2019
- 2019-08-09 CN CN201910735033.3A patent/CN110601238A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102010023112A1 (en) * | 2010-06-07 | 2011-12-08 | Siemens Aktiengesellschaft | Energy transfer device |
| CN106356901A (en) * | 2016-10-09 | 2017-01-25 | 江苏现代能源微网系统有限公司 | Micro-grid energy regulation method suitable for single residence |
| CN108110762A (en) * | 2018-01-29 | 2018-06-01 | 阳光电源股份有限公司 | A kind of alternating current-direct current mixing micro-capacitance sensor and its control method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112838619A (en) * | 2020-12-30 | 2021-05-25 | 山东大学 | Energy storage converter parallel operation system and method based on high-speed serial optical fiber |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110803051B (en) | Energy storage type charging pile and charging system | |
| CN202435131U (en) | Power distribution automation terminal | |
| CN102055241B (en) | Integrated realtime power and solar-electricity station control system | |
| TWI437791B (en) | Networked dc power system | |
| CN103532158A (en) | Micro-grid new energy hybrid energy storage system | |
| CN108695874A (en) | A kind of composite energy storage type bi-directional power conversion device | |
| CN103501006A (en) | Centralized control method for microgrid | |
| CN108767892B (en) | Charging station system of electric automobile | |
| CN110707743A (en) | Dual-mode distributed photovoltaic power generation micro-grid control system and method based on MAS | |
| CN110855006B (en) | Distributed optical storage and charging regulation and control system based on edge internet of things agent | |
| CN103580052B (en) | A kind of composite energy storage power station for active distribution network and distribution method thereof | |
| CN110165689A (en) | A kind of control system for energy-storage system and corresponding energy-storage system | |
| WO2018036325A1 (en) | Switched-mode power supply parallel operation system | |
| CN110601238A (en) | Intelligent micro-grid peak regulation controller of energy storage system | |
| CN104953613A (en) | Intelligent building micro-grid system and control method | |
| CN111600317A (en) | Energy storage metering system and energy storage unit | |
| CN109361228B (en) | Multi-agent control system and method based on distributed battery energy storage | |
| CN116914859A (en) | New energy stable grid-connected intelligent power grid power allocation system | |
| CN111600389A (en) | Energy storage monitoring system | |
| CN202721498U (en) | Micro grid coordination controller based on PCC platform | |
| CN216530731U (en) | Synthesize green energy efficiency intelligence management and control system | |
| CN105375503A (en) | Energy storage in-situ monitoring system | |
| CN102427139B (en) | Vanadium redox flow battery energy storage monitoring system and control method thereof | |
| CN102969754B (en) | Storage battery pack connection circuit and intelligent storage battery pack | |
| CN203339807U (en) | Lithium iron phosphate battery based substation direct-current power supply integrated monitoring system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191220 |