CN111725889B - Energy storage cluster rapid control system and method based on '3S + cloud' architecture - Google Patents
Energy storage cluster rapid control system and method based on '3S + cloud' architecture Download PDFInfo
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Abstract
The invention discloses a rapid control system and a method of an energy storage cluster based on a 3S + cloud architecture, which comprises more than one battery unit, more than one battery management optimization unit, more than one power conversion unit, a 3S integrated control unit, a rapid control management unit and a cloud platform service unit, wherein the battery units are connected on a feeder line, all the battery units of the same power distribution node on the feeder line form a region, each region is provided with one battery management optimization unit and one power conversion unit, the battery units in the same region are connected with the battery management optimization units in the same region, the invention can avoid redundant communication, improve the communication efficiency, the reliability and the regulation speed of the existing energy storage system, meanwhile, the overall controlled capacity of the stored energy is improved, and meanwhile distributed energy storage cooperative control is supported, so that effective response to the dispatching or auxiliary service requirements of a power grid company is realized.
Description
Technical Field
The invention relates to the technical field of energy storage control of smart power grids, in particular to a system and a method for quickly controlling an integrated energy storage cluster based on a 3S + cloud architecture.
Background
With the development of social economy, the urban power grid load is rapidly increased, the peak-valley difference is continuously increased, and the popularization and application of random energy sources such as solar energy, wind energy and the like in the smart power grid further reduces the stability of the power grid and improves the difficulty in adjusting the power grid. The energy storage technology is one of key technologies in the construction of the smart grid as an important means for improving the renewable energy power generation and capacity of the smart grid and a center and a link for realizing the energy bidirectional interaction of the smart grid. The main application scenarios of the energy storage technology mainly comprise:
1) and (3) short time scale real-time control, namely smoothing output fluctuation of intermittent renewable energy power generation, reducing impact on a power grid, improving the permeability of clean energy, and simultaneously realizing real-time adjustment of the operating frequency and voltage of the power grid.
2) And (3) long-time scale optimization management: and the output/load curve is smoothed, the construction requirement of the reserve capacity of the power generation system is reduced, and the equipment utilization rate of the power transmission and distribution system is improved.
The existing energy storage control system architecture is generally shown in fig. 1, in which the dashed lines represent communication interactions. The energy storage control system is generally composed of the following parts:
1) the battery system (including the battery cluster, the high-voltage box, the collection cabinet) and the corresponding Battery Management System (BMS) BMS are generally configured in three levels of the battery cluster, the high-voltage box and the collection cabinet. The BMS mainly collects voltage, current and temperature information of the battery units, calculates the state of charge (SOC), the state of health (SOH) of the battery, and converts voltage, current and temperature sampling values and controls the power supply and the power supply.
2) Power Conversion System (PCS). And receiving a superior EMS control command, charging the battery system in the controlled range or converting the battery electric energy into alternating current electric energy, and transmitting the control command to a subordinate BMS.
3) The energy storage device energy control system (EMS) collects related information such as BMS and PCS, controls the operation of the whole energy storage system according to the functional requirements of the energy storage system, and ensures the safety and stability of the operation of the energy storage system.
The traditional architecture has technical limitations when being applied to current multi-type scenes:
1) and (3) short-time scale real-time control:
the short-time-scale real-time control needs to be applied to scenes with high real-time requirements, such as intermittent renewable energy consumption, rapid load fluctuation stabilization and the like.
BMS processing capacity is limited, and data real-time performance is reduced by simultaneously undertaking collection and calculation work.
And communication channel redundancy reduces the real-time performance of the control process. Taking the energy storage power out-of-limit warning data as an example, the energy storage power out-of-limit is influenced by the rated power and also limited by the SOC value, the SOC value in the energy storage system is calculated by the BMS and then is uploaded to the EMS, the EMS calculates the power limit value according to the SOC value, and the power is controlled through the PCS, so that the purpose of avoiding the energy storage SOC out-of-limit is achieved. This process involves a BMS-EMS-PCS process complexity.
And thirdly, in special scenes of out-of-limit frequency, voltage and the like, the frequency signals collected by the power grid are uploaded to an EMS system, when the frequency deviates, the power regulation value is calculated by the EMS system and then is transmitted to the PCS, and the power regulation is realized through the PCS. This process is severely limited by the processing speed of the EMS server.
The scenes with higher real-time performance all need to seek faster adjustment and calculation speed, and the existing system architecture cannot realize control speed improvement.
2) And (3) long-time scale optimization management:
the long-time scale optimization management is generally applied to load curve peak clipping and valley filling, supply path optimization in an energy range and other scenes. If the existing energy storage is small-scale energy storage, the power is limited, the influence on peak clipping and valley filling of a power grid is limited, and the aim of slowing down the construction of the reserve capacity of a power generation system cannot be achieved. Although the capacity of part of the energy stored on the side of the power grid is large, peak clipping and valley filling can be realized, the energy is concentrated on the same node for grid connection, the energy supply path cannot be optimized and adjusted, regional energy optimization is realized, and a certain contradiction exists between the capacity and the distribution.
In this scenario, a larger energy storage capacity and a wider energy storage distribution are required to be pursued, and the interconnection and interaction cannot be supported between the existing multiple energy storage systems.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a rapid energy storage cluster control system and method based on a 3S + cloud architecture, which are used for controlling an energy storage cluster and improving the whole energy storage on a long-time scale.
The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that:
a rapid energy storage cluster control system based on a 3S + cloud architecture comprises more than one battery unit, more than one battery management optimization unit, more than one power conversion unit, a 3S integrated control unit, a rapid control management unit and a cloud platform service unit, wherein the battery units are connected on a feeder line, all the battery units of the same power distribution node on the feeder line form a region, each region is provided with a battery management optimization unit and a power conversion unit, the battery units in the same region are connected with the battery management optimization units in the same region, the battery management optimization units are in communication connection with the power conversion units in the same region, the power conversion units are in communication connection with the 3S integrated control unit and the rapid control management unit respectively, the 3S integrated control unit and the rapid control management unit are connected with the cloud platform service unit respectively in communication connection, wherein:
the battery management optimization unit is used for acquiring voltage, current and temperature information of the battery unit.
The 3S integrated control unit is used for calculating the SOC, the SOH of the battery, the conversion of voltage, current and temperature sampling values, the power-on and power-off control according to the collected voltage, current and temperature information, collecting relevant information of the battery management optimization unit and the power conversion unit in the area, and controlling the power conversion unit according to the control requirement of the cloud platform service unit.
The rapid control management unit acquires measurement values of power distribution nodes in an area in real time, controls of the 3S integrated control unit on the power conversion unit are cut off according to triggering of the emergency early warning event list and the threshold value, and the power conversion unit is directly controlled according to the operation sensitivity list and the collected information.
And the power conversion unit charges the battery unit in the jurisdiction range or inverts the battery electric energy into alternating current electric energy through the battery management optimization unit according to the control instructions of the quick control management unit and the 3S integrated control unit.
The cloud platform service unit is deployed in a comprehensive application system at the cloud end, so that the management of the 3S integrated control units in a plurality of areas is realized, and an emergency early warning event list, a threshold value and an operation sensitivity list of the rapid control management unit are updated. And issuing a control instruction to the rapid control management unit and the 3S integrated control unit according to the power grid parameters, the emergency early warning event list, the threshold value and the operation sensitivity list.
Preferably: the battery unit comprises a battery cluster, a high-voltage box and a confluence cabinet which are connected in sequence.
Preferably: all battery units of the same power distribution node on the 10kV feeder line form a region.
A rapid control method of an energy storage cluster based on a 3S + cloud architecture comprises the following steps:
step S1: the service types of the battery cells are classified into a long-time scale service type, a short-time scale service type, and an emergency service type. And the service type is adjusted in a cloud platform service unit, and when a new service requirement is accessed, the service type is selected.
Step S2: the emergency service type processing method comprises the following steps:
step S21: the cloud platform service unit collects power grid parameters, generates an emergency early warning event list, a threshold value and an operation sensitivity list by taking a fixed time as a period, and sends the emergency early warning event list, the threshold value and the operation sensitivity list to the rapid control management unit.
Step S22: and the rapid control management unit acquires parameter values of corresponding key nodes in real time according to the parameter names in the emergency early warning event list, a timer t is t +1, t represents the count of control circulation, the key nodes are power distribution nodes on a feeder line, if the acquired key node parameters exceed the threshold value, the step S23 is executed, and if the acquired key node parameters do not exceed the threshold value, the step S25 is executed.
Step S23: and the timer t is 0, and the quick control management unit generates a target regulating value one according to the operation sensitivity list and the acquisition key node parameters.
Step S24: and the rapid control management unit cuts off a control channel of the 3S integrated control unit to the power conversion unit and directly sends the target regulating value to the power conversion unit.
Step S25: the power conversion unit executes the target adjustment value one, and goes to step S22.
Step S26: if the control channel between the 3S integrated control unit and the power conversion unit is currently in the off state and T > T, the control channel is restored, where T is a set dead time range, and step S22 is performed. Otherwise, go directly to step S22.
Step S3: the long-time scale service type processing method comprises the following steps:
step S31: the cloud platform service unit collects power grid parameters and information of the 3S integrated control units in the plurality of areas, generates a second target adjusting value according to service contents by taking a second timing period as a period, and respectively sends the second target adjusting value to the 3S integrated control units.
Step S32: and each 3S integrated control unit decomposes the target regulating value into two parts to corresponding power conversion units.
Step S33: and each power conversion unit executes a target regulating value two.
Step S4: the short timescale service type processing method comprises the following steps:
step S41: the cloud platform service unit collects power grid parameters, generates a short-time-scale service target guide value for a certain area according to service contents in a period of time three, does not issue the value for services which do not need the target guide value, and issues the target guide value to the 3S integrated control unit of the corresponding area.
Step S42: and the 3S integrated control unit generates a third target adjusting value according to the target guide value and forwards the third target adjusting value to the power conversion unit.
Step S43: the power conversion unit executes the target adjustment value three.
Preferably: the long-time scale service type is carried out by taking days or hours as a period, and comprises energy storage cluster optimization calculation, load curve peak clipping and valley filling and supply path optimization in an energy range.
Preferably: the short-time scale service type is carried out by taking minutes or seconds as a period, and comprises intermittent renewable energy real-time consumption and load rapid fluctuation stabilization.
Preferably: the emergency service type is ms-level response service generated aiming at power grid or equipment faults, and comprises power grid frequency out-of-limit and power grid voltage out-of-limit.
Compared with the prior art, the invention has the following beneficial effects:
(1) on a short time scale, BMS pressure is reduced through system architecture optimization, redundant communication is avoided, and communication efficiency, reliability and adjusting speed of the existing energy storage system are improved.
(2) Under special application scenes (such as line overload, voltage out-of-limit and frequency out-of-limit), the local quick control function of 10ms level is completed through the quick control management unit.
(3) On a long time scale, unified management among multiple PCS and multiple EMS is realized through cooperation among '3S + cloud' systems, the overall controlled capacity of energy storage is improved, meanwhile, distributed energy storage cooperative control is supported, and effective response to dispatching or auxiliary service requirements of a power grid company is realized.
Drawings
FIG. 1 illustrates a conventional energy storage control system architecture;
fig. 2 is a schematic diagram of an architecture of an integrated energy storage cluster fast control system based on a "3S + cloud" architecture according to an embodiment of the present invention;
fig. 3 is an application diagram of an integrated energy storage cluster fast control system based on a "3S + cloud" architecture according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of grid-connected depth according to an embodiment of the present invention;
FIG. 5 is a flowchart of an integrated energy storage cluster fast control method based on a 3S + cloud architecture;
in the figure: the system comprises a 1-battery management optimization unit, a 2-3S integrated control hall, a 3-quick control management unit, a 4-cloud platform service unit and a 5-power conversion unit.
Detailed Description
The present invention is further illustrated by the following description in conjunction with the accompanying drawings and the specific embodiments, it is to be understood that these examples are given solely for the purpose of illustration and are not intended as a definition of the limits of the invention, since various equivalent modifications will occur to those skilled in the art upon reading the present invention and fall within the limits of the appended claims.
An energy storage cluster rapid control system based on a '3S + cloud' architecture divides a large number of smart grids connected into a distributed energy storage system into a plurality of regions according to a region division principle and is used for controlling distributed energy storage equipment in the power grids, as shown in figures 2-4, the system comprises more than one battery unit, more than one battery management optimization unit, more than one power conversion unit, a 3S integrated control unit, a rapid control management unit and a cloud platform service unit, wherein the battery units are connected on a feeder line, all the battery units of the same distribution node on the feeder line form a region, each region is provided with a battery management optimization unit BMS2.0 and a power conversion unit PCS, the battery units in the same region are all connected with the battery management optimization units in the same region, and the battery management optimization units are in communication connection with the power conversion units in the same region, the power conversion unit communication respectively with 3S integrated control unit, quick control management unit communication connection, 3S integrated control unit, quick control management unit connect respectively with cloud platform service unit communication connection, the battery unit includes the battery cluster, high-voltage box, the cabinet that converges that connect gradually, wherein:
as shown in fig. 2, according to the principle of region division of the smart grid, all energy storage devices (battery units) of the same power distribution node on a 10kV feeder may form a region, and parameter updating may be performed after region range matching extension and physical grid transformation between regions, so as to achieve a better region control effect. The physical grid transformation mainly refers to topology transformation caused by switching of switch states. The parameter is updated to a power conversion unit (PCS) list controlled by the 3S integrated control unit and the fast control management unit,
each area is provided with the 3S integrated control unit and the quick control management unit, and the quick control management unit can be installed at the installation position of the metering device at the entrance of the area.
The battery management optimizing unit is used for acquiring voltage, current and temperature information of the battery unit, only an acquisition part is reserved for simplifying functions of a traditional battery management system, and a calculation part is not borne by the battery management optimizing unit any more, so that the BMS pressure of the battery management optimizing unit is reduced compared with that of the traditional system, and the real-time performance of data can be improved through faster calculation.
The 3S integrated control unit is based on a high-performance embedded device, bears the calculation function of a traditional battery management optimization system, is used for calculating the SOC (state of charge), the SOH (state of health) of the battery, the conversion of voltage, current and temperature sampling values and the power-on and power-off control according to the collected voltage, current and temperature information, collects the relevant information of the battery management optimization unit and the power conversion unit in the area, and controls the power conversion unit according to the control requirement of the cloud platform service unit.
Here, the functional reconfiguration of the 3S integrated control unit and the battery management optimization unit can bring about communication optimization, taking the energy storage power out-of-limit alarm data as an example, the energy storage power out-of-limit is affected by the rated power and also limited by the SOC value, the SOC value in the conventional energy storage unit is calculated by the BMS, the SOC value is uploaded to the EMS, the EMS calculates the power limit value according to the SOC value, and the power is controlled by the PCS, thereby achieving the purpose of avoiding the energy storage SOC out-of-limit. This process involves a BMS-EMS-PCS process complexity. And the state of charge (SOC) in the unit is directly calculated by the 3S integrated control unit, and when the input/output power of the power conversion unit (PCS) approaches the input/output limit power value, the SOC power limit is directly carried out. The input/output limit power value is calculated as follows:
in the formula, Ssoc(t) represents the SOC value of the energy storage equipment at the time t;
respectively representing output and input limit active power values;
respectively representing rated capacity values of the energy storage units;
representing the SOC limit of the energy storage unit, in general
The setting was made to be 0.2,
set to 0.8; eta, mu is the energy conversion efficiency of the energy storage device in the charging and discharging process, and delta t is the command refreshing interval time.
The SOC limiting value is directly sent to the PCS by the 3S integrated unit to control power, and only two processes of the 3S integrated control unit and the PCS are involved, so that the complexity of the process is greatly reduced, and the redundancy of the communication process is reduced.
The rapid control management unit acquires measurement values of power distribution nodes in an area in real time, controls of the 3S integrated control unit on the power conversion unit are cut off according to triggering of the emergency early warning event list and the threshold value, and the power conversion unit is directly controlled according to the operation sensitivity list and the collected information. And operating the sensitivity list and acquiring information to generate a regional energy storage total target regulation power value, and directly distributing the regional energy storage total target regulation power value to each of the power conversion units according to the proportion by the rapid control management unit. The emergency early warning event list, the threshold value and the operation sensitivity list are generated by a cloud platform unit.
And the power conversion unit charges the battery unit in the jurisdiction range or inverts the battery electric energy into alternating current electric energy through the battery management optimization unit according to the control instructions of the quick control management unit and the 3S integrated control unit.
Taking the voltage out-of-limit as an example, the emergency early warning event list is: event 1: a voltage out-of-limit event. The threshold value (voltage: upper limit 0.95, lower limit 1.05). And when the voltage exceeds the limit, if the voltage reaches 1.06p.u., directly calculating the power value to be regulated of the energy storage in the region to be 400kW according to the voltage deviation value (0.01p.u.) and the operation sensitivity list 0.000025p.u./kW, and proportionally (for example, 1:3:5) generating the target power value of each power conversion unit in the region according to the following energy storage residual adjustable power (the calculation formula is the rated power of each PCS to the current PCS power).
Similar to the line overload, the emergency alert event list is: event 2: a line overload event. The threshold value (current: 154A). And when line overload occurs (for example, the current reaches 174A), calculating the power value which needs to be adjusted for energy storage in the region to be 312.5kW, and generating the target power value of each power conversion unit in the region in proportion according to the residual adjustable power of the subordinate energy storage.
The addition of the rapid control management unit can realize the local rapid control function of the energy storage level of 10ms, the traditional energy storage is influenced by the structure of the traditional energy storage, when the frequency, the voltage and other special scenes are out of limit, a frequency signal collected by a power grid is uploaded to the EMS unit, when the frequency deviates, the power regulation value is calculated by the EMS unit and then is transmitted to the PCS, and the power regulation is realized through the PCS. This process is severely limited by the processing speed of the EMS server. According to the unit architecture, a rapid control management unit is added, an emergency early warning event list (such as a voltage out-of-limit event) and a threshold (voltage: upper limit 0.95 and lower limit 1.05) calculated by a cloud platform service unit are issued to the rapid control management unit, and the list and the threshold can be periodically given according to grid optimization calculation.
The emergency early warning event list is obtained after being classified according to the service requirements supported by the energy storage cluster; the threshold value can be set by a power grid company according to requirements or directly set by national standards; the operational sensitivity list is computed by the cloud platform: taking the operation sensitivity corresponding to the voltage out-of-limit as an example, calculating by using a grid depth index, wherein the grid-connected depth index is the sum of the impedances of the wires from the grid-connected point to the balance node in the area, and the sum is shown as the following formula:
wherein C is the regionA set of wires between the domain grid points to the balance nodes. Taking fig. 3 as an example, C includes wires a-a1, a1-a2, a2-A3, A3-a4, a4-a5, a5-A6, A6-a12, a12-a13, a13-a 15. RiAnd XiRespectively the resistance and reactance of the wire i. The operation sensitivity expresses the influence degree of the energy storage power change in the region on the grid-connected point voltage. If the change amount of the local energy storage power is
(containing both active and reactive components), then
The resulting change in the DG grid-connected point voltage can be estimated by the following equation
Is the voltage vector of the grid-connected point of the region,
is the grid connection point voltage change amount.
When the operation sensitivity is more complicated, the perturbation method can be adopted to calculate the operation sensitivity, namely adding a variable quantity to the power
The change value of the target variable (such as a certain node voltage value, a certain current value and the like) is observed through load flow calculation, so that the operation sensitivity is obtained.
The emergency pre-warning event list; the threshold value and the operation sensitivity list can be updated in a period of 15min or 1h, the validity of the sensitivity is ensured, and particularly, when the switch state is displaced to cause the topology to change, the list is immediately updated.
Therefore, when an emergency fault occurs, the rapid control management unit directly controls the PCS, and the control speed is obviously improved.
In a preferred embodiment, a cloud platform service unit is added and deployed in a cloud comprehensive application unit, so that unified management of a plurality of 3S integrated control units in the area is realized, and the emergency early warning event list, the threshold value and the operation sensitivity list of the rapid control management unit are updated. The centralized state monitoring and analysis of the energy storage units are completed, the functions of centralized energy storage control of the regions and centralized operation and maintenance of the energy storage units are increased, and the comprehensive energy service based on distributed energy storage is supported. The introduction of the platform can realize 'zero accumulation as a whole', the comprehensive control of a multi-region energy storage unit is realized by taking a single region as a unit and through multi-region common control,
the cloud platform calculates the target value by using a long-time-scale 10kV feeder line integral load peak clipping and valley filling operation example, and the calculation equation can be expressed as follows:
in the formula (f)opt(. cndot.) for the purpose of optimizing the expression of the calculation formula,
load i (load) for time ti) A load prediction value calculated by the cloud platform unit,
intermittent renewable energy source j (iter) for time tj) A forecast value, the intermittent renewable energy source forecast value given by cloud platform computing,
for all energy storage units (BESS) in the region k at the time tk) Optimum value of philoadIs the set of all loads under the 10kV feeder line, phiiterIs the set of all intermittent renewable energy sources under the 10kV feeder line, phiBESSAnd the energy storage device is a set of all energy storage devices under the 10kV feeder line.
And the target regulating value of the energy storage unit in the area k at the moment t is obtained. In this way, the energy storage of each region can be added into the load peak clipping and valley filling optimization calculation together. The cloud platform unit sends the target adjustment values to the 3S integrated control units respectively, each 3S integrated control unit decomposes the target adjustment values to the power conversion units (the decomposition mode is consistent with the proportional adjustment in the rapid adjustment), and each power conversion unit executes the target adjustment values.
Taking the short-time power fluctuation stabilization of the 10kV feeder as an example,
firstly, the cloud platform calculates the optimized power value of each region energy storage unit according to an optimization target (such as the integral load peak clipping and valley filling operation of a 10kV feeder), carries out load flow calculation, and obtains the power exchange optimized value of the t 10kV feeder and a superior power grid at the moment
Optimized power value with region k
These two values are the target guideline values. The 3S integrated control unit generates a target adjusting value according to the target guide value, and a control equation of the target adjusting value is expressed as follows:
in the formula, thetafeederThe value of the power exchanged between the 10kV feeder line and the upper-level power grid is measured and obtained by the 3S integrated control unit. Delta thetafeederTo exchange the power control error value, θrgn,kThe actual power value of the area k is measured and obtained by the 3S integrated control unit. Deltaθrgn,kIs the local power control error value. Alpha is alphakBears a proportional value for region k and satisfies
And the 3S integrated control unit generates a target regulation value according to the control equation and forwards the target regulation value to each power conversion unit of the power conversion units to execute the target regulation value.
In conclusion, the cloud platform unit can comprehensively control multi-region energy storage under the condition that the single energy storage control capacity is limited, so that the overall capacity can be improved, peak clipping and valley filling can be realized, the distributed energy storage characteristics can be exerted, and the optimization of the overall operation condition of the feeder line can be realized through regional real-time adjustment.
A rapid control method of an energy storage cluster based on a 3S + cloud architecture comprises the following steps:
step S1: the service types of the battery cells are classified, and the service types may be classified into a long-time-scale service type, a short-time-scale service type, and an emergency service type according to characteristics. And the service type is adjusted in a cloud platform service unit, and when a new service requirement is accessed, the service type is selected. The long-time scale service type is carried out by taking a day or an hour as a period, and includes but is not limited to energy storage cluster optimization calculation, load curve peak clipping and valley filling, and supply path optimization within an energy range. The short-time scale service types are carried out in a period of minutes or seconds, and include but are not limited to functions of intermittent renewable energy real-time consumption, load rapid fluctuation stabilizing and the like. The emergency service type is ms-level response service generated aiming at power grid or equipment faults, and includes but is not limited to functions of power grid frequency out-of-limit, power grid voltage out-of-limit and the like. The emergency service type proceeds to step S2, long timescale service type goes to step S3, and short timescale service type goes to step S4.
Step S2: the emergency service type processing method comprises the following steps:
step S21: the cloud platform service unit collects power grid parameters, generates an emergency early warning event list (such as a voltage out-of-limit event), the threshold value (voltage: upper limit 0.95, lower limit 1.05) and an operation sensitivity list (such as 0.0035V/kW) in a period of 1 hour, and sends the emergency early warning event list, the threshold value and the operation sensitivity list to the rapid control management unit.
Step S22: the rapid control management unit collects parameter values of corresponding key nodes in real time according to parameter names in the emergency early warning event list, calculates deviation values (such as voltage 0.96 and deviation 0.01), a timer t is t +1, t represents the count of control circulation, the key nodes are power distribution nodes on a 10kV feeder line, if the collected key node parameters exceed a threshold value, the step S23 is executed, and if the collected key node parameters do not exceed the threshold value, the step S25 is executed.
Step S23: and the timer t is 0, the quick control management unit generates a first target adjusting value according to the operation sensitivity list and the acquisition key node parameters, and the calculation is performed in a deviation value/sensitivity mode, so that the calculation speed is increased, and the calculation resource loss is reduced.
Step S24: the fast control management unit cuts off a control channel of the 3S integrated control unit to the power conversion unit and directly transmits the target adjustment value to the power conversion unit (PCS).
Step S25: the power conversion unit executes the target adjustment value one, and goes to step S22.
Step S26: if the control channel between the 3S integrated control unit and the power conversion unit is currently in the off state and T > T, the control channel is restored, where T is a set dead time range, and step S22 is performed. Otherwise, the adjustment is not completed, such as the load continuously decreases, and an adjustment value needs to be further generated, or the adjustment is just performed and is still within the dead zone range, so as to avoid the oscillation control, and the step S22 is directly performed.
Step S3: the long-time scale service type processing method comprises the following steps:
step S31: the cloud platform service unit collects power grid parameters and information of the 3S integrated control units in the plurality of areas, generates a second target adjusting value (such as an energy storage peak clipping target value) according to service contents in a period of 1 hour, and respectively sends the second target adjusting value to the 3S integrated control units to play each energy storage role and respectively adjust power.
Step S32: and each 3S integrated control unit decomposes the target regulating value into two parts to corresponding power conversion units.
Step S33: and each power conversion unit executes a target regulating value two.
Step S4: the short timescale service type processing method comprises the following steps:
step S41: the cloud platform service unit collects power grid parameters, a short-time-scale service target guide value (such as a target value for short-time power fluctuation stabilization) for a certain area is generated according to service contents in a period of 1 hour, the value can be not issued for services which do not need the target guide value, if the area is autonomous, power interaction of a superior power grid is reduced as far as possible, the target guide value is issued to the corresponding area, the 3S integrated control unit is used, and each system executes corresponding instructions respectively, so that the energy supply path can be optimized and adjusted.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.
Claims (7)
1. The utility model provides an energy storage cluster quick control system based on "3S + cloud" framework which characterized in that: the system comprises more than one battery unit, more than one battery management optimization unit, more than one power conversion unit, a 3S integrated control unit, a rapid control management unit and a cloud platform service unit, wherein the battery units are connected to a feeder line, all the battery units of the same distribution node on the feeder line form a region, each region is provided with one battery management optimization unit and one power conversion unit, the battery units in the same region are connected with the battery management optimization units in the same region, the battery management optimization units are in communication connection with the power conversion units in the same region, the power conversion units are in communication connection with the 3S integrated control unit and the rapid control management unit respectively, the 3S integrated control unit and the rapid control management unit are connected and are in communication connection with the cloud platform service unit respectively, and the system comprises:
the battery management optimization unit is used for acquiring voltage, current and temperature information of the battery unit;
the 3S integrated control unit is used for calculating the SOC, the SOH of the battery, the voltage, the current and the temperature sampling value conversion and the power-on and power-off control according to the collected voltage, current and temperature information, collecting the relevant information of the battery management optimization unit and the power conversion unit in the area, and controlling the power conversion unit according to the control requirement of the cloud platform service unit;
the rapid control management unit acquires a measurement value of a power distribution node in an area in real time, cuts off the control of the 3S integrated control unit on the power conversion unit according to the triggering of an emergency early warning event list and a threshold value, and directly controls the power conversion unit according to an operation sensitivity list and acquired information;
the power conversion unit charges the battery unit in the jurisdiction range or inverts the battery electric energy into alternating current electric energy through the battery management optimization unit according to the control instructions of the rapid control management unit and the 3S integrated control unit;
the cloud platform service unit is deployed in a comprehensive application system of a cloud end, so that the management of 3S integrated control units in a plurality of areas is realized, and an emergency early warning event list, a threshold value and an operation sensitivity list of the rapid control management unit are updated; and issuing a control instruction to the rapid control management unit and the 3S integrated control unit according to the power grid parameters, the emergency early warning event list, the threshold value and the operation sensitivity list.
2. The energy storage cluster rapid control system based on the 3S + cloud architecture as claimed in claim 1, wherein: the battery unit comprises a battery cluster, a high-voltage box and a confluence cabinet which are connected in sequence.
3. The energy storage cluster rapid control system based on the 3S + cloud architecture as claimed in claim 1, wherein: all battery units of the same power distribution node on the 10kV feeder line form a region.
4. A control method for an energy storage cluster rapid control system based on a 3S + cloud architecture according to any one of claims 1 to 3, comprising the following steps:
step S1: classifying service types of the battery units, wherein the service types are classified into a long-time scale service type, a short-time scale service type and an emergency service type; the service type is adjusted in a cloud platform service unit, and when a new service requirement is accessed, the service type is selected;
step S2: the emergency service type processing method comprises the following steps:
step S21: the cloud platform service unit acquires power grid parameters, generates an emergency early warning event list, a threshold value and an operation sensitivity list by taking a fixed time as a period, and transmits the emergency early warning event list, the threshold value and the operation sensitivity list to the rapid control management unit;
step S22: the rapid control management unit acquires parameter values of corresponding key nodes in real time according to parameter names in the emergency early warning event list, a timer t is t +1, t represents the counting of control circulation, the key nodes are power distribution nodes on a feeder line, if the acquired key node parameters exceed a threshold value, the step S23 is switched, and if the acquired key node parameters do not exceed the threshold value, the step S26 is switched;
step S23: the timer t is 0, and the quick control management unit generates a first target adjusting value according to the operation sensitivity list and the collection key node parameters;
step S24: the rapid control management unit cuts off a control channel of the 3S integrated control unit to the power conversion unit and directly sends the target regulating value to the power conversion unit;
step S25: the power conversion unit executes the target adjustment value one, and goes to step S22;
step S26: if the control channel of the 3S integrated control unit and the power conversion unit is currently in the off state and T > T, recovering the control channel, where T is a set dead time range, and performing step S22; otherwise, go directly to step S22;
step S3: the long-time scale service type processing method comprises the following steps:
step S31: the cloud platform service unit acquires power grid parameters and information of the 3S integrated control units in the plurality of areas, generates a second target adjusting value according to service contents by taking a second timing period as a period, and respectively sends the second target adjusting value to the 3S integrated control units;
step S32: each 3S integrated control unit decomposes the target regulating value into two parts to be corresponding to a power conversion unit;
step S33: each power conversion unit executes a target regulating value II;
step S4: the short timescale service type processing method comprises the following steps:
step S41: the cloud platform service unit acquires power grid parameters, generates a short-time-scale service target guide value for a certain area according to service contents in a period of timing three, does not issue the value for services which do not need the target guide value, and issues the target guide value to the 3S integrated control unit of the corresponding area;
step S42: the 3S integrated control unit generates a third target adjusting value according to the target guide value and forwards the third target adjusting value to the power conversion unit;
step S43: the power conversion unit executes the target adjustment value three.
5. The control method according to claim 4, characterized in that: the long-time scale service type is carried out by taking days or hours as a period, and comprises energy storage cluster optimization calculation, load curve peak clipping and valley filling and supply path optimization in an energy range.
6. The control method according to claim 4, characterized in that: the short-time scale service type is carried out by taking minutes or seconds as a period, and comprises intermittent renewable energy real-time consumption and load rapid fluctuation stabilization.
7. The control method according to claim 4, characterized in that: the emergency service type is ms-level response service generated aiming at power grid or equipment faults, and comprises power grid frequency out-of-limit and power grid voltage out-of-limit.
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