CN-121984039-A - Intelligent regulation and control method for energy storage-PCS device of platform area under cloud edge cooperative framework

CN121984039ACN 121984039 ACN121984039 ACN 121984039ACN-121984039-A

Abstract

The invention provides an intelligent regulation and control method for an energy storage-PCS device of a lower station area of a cloud edge cooperative framework, and belongs to the technical field of power distribution network regulation and control. The method comprises the following steps of firstly, acquiring and implementing multidimensional data, wherein a measurement and control unit of an edge side energy storage-PCS device acquires three-phase voltage, three-phase current, active power, reactive power, frequency and voltage harmonic distortion rate data of an outlet of a transformer in a transformer area and a line terminal. According to the invention, layered coordination and accurate response of the regulation and control of the transformer area are realized through the cloud edge coordination framework, the edge side relies on a high-precision data acquisition and model prediction control algorithm, and active power and reactive power adjustment can be completed within millisecond time, so that the voltage qualification rate at the tail end of the transformer area is obviously improved, the three-phase unbalance is controlled within 5%, the problems of slow response and limited treatment effect of the traditional regulation and control mode are effectively solved, and the power quality and the operation stability of the power distribution network are obviously improved.

Inventors

CHEN LIN
YAO NAN
WANG TINGTING
REN KEYU
MA QIANWEN
ZHANG YI
YU XIANG

Assignees

国网河南省电力公司南阳供电公司

Dates

Publication Date: 20260505
Application Date: 20260206

Claims (10)

1. An intelligent regulation and control method of a platform region energy storage-PCS device under cloud edge cooperative architecture is characterized by comprising the following steps: the method comprises the steps that firstly, multidimensional data acquisition is implemented, wherein a measurement and control unit of an edge side energy storage-PCS device acquires three-phase voltage, three-phase current, active power, reactive power, frequency and voltage harmonic distortion rate data of an outlet of a transformer in a transformer area and a line end; the cloud server receives the collected data uploaded by the edge side, and builds a load prediction model by combining historical load data, date type data and meteorological data; Step three, generating and implementing the district health index, namely calculating voltage deviation rate, three-phase imbalance, total current harmonic distortion rate, transformer load rate and line theoretical line loss rate by an edge side based on collected data, and generating the district health index through a preset algorithm; The cloud server outputs an ultra-short-term load prediction result and a short-term load prediction result through a load prediction model, and generates a charge-discharge reference instruction by combining time-of-use electricity price parameters and energy storage charge-discharge efficiency parameters and transmits the charge-discharge reference instruction to the edge side; And fifthly, executing the power regulation operation, namely receiving a charging and discharging reference instruction at the edge side, outputting an active power regulation quantity and a reactive power regulation quantity through a preset control algorithm in combination with the district health index, and driving the energy storage-PCS device to execute the power regulation operation.
2. The intelligent regulation and control method of the cloud edge collaborative architecture lower station area energy storage-PCS device of claim 1, wherein the frequency of collecting three-phase voltage and three-phase current data at the edge side is once per second, the frequency of collecting active power, reactive power, frequency and voltage harmonic distortion rate data is once per second, and the collection precision of the voltage and current data is 0.2 level.
3. The intelligent regulation and control method of a cloud-edge collaborative architecture lower district energy storage-PCS device of claim 1, wherein the load prediction model is a long-short-term memory network model, the time range corresponding to the ultra-short-term load prediction result is 15 minutes to 4 hours, and the time range corresponding to the short-term load prediction result is 24 hours to 72 hours.
4. The intelligent regulation and control method of a transformer area energy storage-PCS device under a cloud edge collaborative architecture of claim 1, wherein the preset algorithm is a fuzzy logic algorithm, and weights of the voltage deviation rate, the three-phase imbalance, the total current harmonic distortion rate, the transformer load rate and the line theoretical line loss rate are preset by an expert system.
5. The intelligent regulation and control method of the cloud-side collaborative architecture lower district energy storage-PCS device of claim 1, wherein a mixed integer linear programming model is adopted when the cloud server generates a charging and discharging reference command, and constraint conditions of the mixed integer linear programming model comprise an upper limit value of the residual capacity of an energy storage battery, a lower limit value of the residual capacity of the energy storage battery, an upper limit value of power output of the PCS device, a lower limit value of power output of the PCS device and a limit value of capacity of a transformer.
6. The intelligent regulation and control method of a cloud-edge collaborative architecture lower district energy storage-PCS device of claim 1, wherein the preset control algorithm is a model preset control algorithm which is constructed based on a district simplified mathematical model comprising transformer equivalent impedance parameters, line parameters and load characteristic parameters.
7. The method for intelligently regulating and controlling energy storage-PCS devices in a lower station area of cloud edge collaborative architecture according to any one of claims 1-6, wherein when the energy storage-PCS devices are deployed in a plurality of station areas, each edge side exchanges energy storage residual capacity data and adjustable power data through a local communication network, and performs power mutual-aid regulation and control operation based on a consistency algorithm.
8. The intelligent regulation and control method of cloud edge collaborative architecture lower district energy storage-PCS device of any one of claims 1-6, wherein when the edge side executes power regulation operation, the response time of reactive power regulation is less than or equal to 10ms, and the output precision error of active power regulation is not more than +/-2% of rated power.
9. The intelligent regulation and control method of an energy storage-PCS device of a cloud edge collaborative architecture lower area of any one of claims 1-6 is characterized in that a main circuit of the energy storage-PCS device adopts a three-phase full-bridge two-flat voltage source type converter topology, an LCL filter is configured on an output side of the converter, and inductance parameters and capacitance parameters of the LCL filter are calculated and determined based on harmonic suppression requirements.
10. The intelligent regulation and control method of the cloud-edge collaborative architecture lower district energy storage-PCS device according to any one of claims 1-6, wherein the edge side and a cloud server communicate through HPLC or a wireless private network, communication data comprises collected data, district health index, charge and discharge reference instructions and device running state information, and communication delay is less than or equal to 50ms.

Description

Intelligent regulation and control method for energy storage-PCS device of platform area under cloud edge cooperative framework Technical Field The invention belongs to the technical field of power distribution network regulation and control, and particularly relates to an intelligent regulation and control method of an energy storage-PCS device of a lower station area of a cloud edge cooperative framework. Background The power distribution network is used as a key link of a power system for connecting users, and the running quality of the power distribution network directly influences the power supply reliability and the power quality. In rural and urban and rural junction areas, due to the limitation of historical construction conditions, a large number of areas have the problems of overlong power supply radius (part exceeds 5 km), large line impedance and the like, so that the terminal voltage drops obviously, the voltage qualification rate is lower than 90% for a long time, and particularly, the problem of low voltage during summer and winter load peaks is more remarkable. Meanwhile, the space-time distribution of the power grid load is uneven, the peak-valley difference can reach 3-5 times, the light load and heavy load working conditions of the transformer are alternately generated, and the three-phase unbalance degree is generally over 35% due to the single-phase characteristic of civil load, so that the line loss is increased, the insulation aging of equipment is further increased, and the service life of the distribution transformer is shortened. In addition, impact loads of industrial users and commercial facilities in jurisdictions can generate severe current impact in the starting and running processes, so that voltage sag of a power grid is caused, and misoperation or shutdown of peripheral sensitive instruments and automatic equipment is caused, so that normal order of power supply and power utilization is affected. The traditional power distribution network management means rely on the 'rigid' transformation such as transformer capacity increase and crude section wire replacement, and the like, so that the defects of large investment, long period, poor flexibility and the like exist, the existing regulation and control mode lacks global collaborative optimization capability, has low response speed to load fluctuation, is difficult to solve comprehensive power quality problems such as low voltage, high line loss, three-phase imbalance, voltage sag and the like, cannot meet the development requirement of the power distribution network on 'active and intelligent' transformation, and needs a fault positioning device which can integrate multidimensional fault information, has high-efficiency data processing capability and is convenient for field operation. Disclosure of Invention The invention aims to solve the technical problems that the manual line inspection method is low in efficiency, the positioning accuracy of a single sensor is insufficient, the applicability of a fixed monitoring device is poor, and the data processing and fusion capability is weak, and provides an intelligent regulation and control method of an energy storage-PCS device of a cloud-edge collaborative architecture lower stage area aiming at the defects of the prior art. In order to solve the technical problems, the technical scheme adopted by the invention is that the intelligent regulation and control method of the energy storage-PCS device of the lower station area of the cloud edge cooperative framework comprises the following steps: the method comprises the steps that firstly, multidimensional data acquisition is implemented, wherein a measurement and control unit of an edge side energy storage-PCS device acquires three-phase voltage, three-phase current, active power, reactive power, frequency and voltage harmonic distortion rate data of an outlet of a transformer in a transformer area and a line end; the cloud server receives the collected data uploaded by the edge side, and builds a load prediction model by combining historical load data, date type data and meteorological data; Step three, generating and implementing the district health index, namely calculating voltage deviation rate, three-phase imbalance, total current harmonic distortion rate, transformer load rate and line theoretical line loss rate by an edge side based on collected data, and generating the district health index through a preset algorithm; The cloud server outputs an ultra-short-term load prediction result and a short-term load prediction result through a load prediction model, and generates a charge-discharge reference instruction by combining time-of-use electricity price parameters and energy storage charge-discharge efficiency parameters and transmits the charge-discharge reference instruction to the edge side; And fifthly, executing the power regulation operation, namely receiving a charging and discharging reference instruction at the ed