CN-121984064-A - Dynamic balance system and method for source network load storage of high-proportion new energy power grid

CN121984064ACN 121984064 ACN121984064 ACN 121984064ACN-121984064-A

Abstract

The invention relates to the field of power systems, and particularly discloses a source network load storage dynamic balancing system and method of a high-proportion new energy power grid. The method comprises the following basic principle that a regional collaborative optimization layer performs rolling optimization by utilizing a distributed model predictive control algorithm based on wide area measurement and ultra-short term predictive data to generate a regional collaborative control target in the form of voltage or reactive power demand, each intelligent power converter in a distributed equipment execution layer performs real-time negotiation with adjacent equipment by running a distributed consistency algorithm after receiving the target, autonomously determines each virtual admittance adjustment quantity, and finally rapidly adjusts the equivalent admittance of a grid-connected point by a virtual admittance control technology to output required reactive power. The scheme has the most core technical effect that the second-level real-time dynamic balancing capability and the safe and stable operation level of the power grid under the high-proportion random new energy access environment are improved.

Inventors

Ma sanjiang
ZHANG ZHIPENG
WU YEJUN
JIANG GUOZHEN
ZHAO TIANYU
LI FEI
GONG YINGFEI
TIAN JIA
YAO JUNZHI

Assignees

中能聚创(杭州)能源科技有限公司
国网浙江省电力有限公司杭州供电公司
国网浙江省电力有限公司建德市供电公司

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (10)

1. The source network load storage dynamic balancing system of the high-proportion new energy power grid is characterized by comprising a regional collaborative optimization layer and a distributed equipment execution layer; the regional collaborative optimization layer is used for generating regional-level collaborative control targets through a distributed optimization algorithm based on wide-area measurement data and prediction data of the power grid; the distributed equipment execution layer comprises a plurality of intelligent power converters deployed in a power grid, wherein the intelligent power converters are configured to: Receiving a cooperative control target of the regional level; Based on the cooperative control target and the local measurement data, determining respective adjustment instructions through distributed negotiation of adjacent intelligent power converters in communication connection with the cooperative control target and the local measurement data; and adjusting the equivalent admittance of the grid-connected point according to the adjusting instruction so as to output corresponding reactive power, and cooperatively realizing the cooperative control target of the regional level.
2. The system of claim 1, further comprising a wide area synchronous measurement unit network; the wide area synchronous measurement unit network is composed of a plurality of synchronous phasor measurement units deployed at key nodes of a power grid and is used for collecting and uploading the wide area measurement data containing voltage and current phasors to the regional collaborative optimization layer at a rate higher than the power frequency.
3. The system of claim 2, wherein the zone co-optimization layer comprises at least one zone controller; The distributed optimization algorithm comprises a distributed model predictive control algorithm, and the regional controller is configured to execute the distributed model predictive control algorithm and specifically comprises the following steps: Rolling estimation is carried out on the state of the future period of the power grid based on the wide area measurement data and the ultra-short-term new energy power prediction data; taking the minimum area net load fluctuation as an optimization target, and solving an optimal control sequence in a future limited time window; And converting the optimal control sequence into a cooperative control target of the regional level, wherein the cooperative control target comprises at least a voltage reference value of a key bus or a regional total reactive power demand value.
4. The system of claim 3, wherein the zone controller performs interval estimation on the system state including the new energy output using a kalman filter algorithm in performing the rolling estimation.
5. The system of claim 1, wherein the intelligent power converter comprises a virtual admittance control module and a consistency coordination module; The consistency coordination module is used for executing a distributed consistency algorithm, exchanging local voltage information with an adjacent intelligent power converter and coordinating with the control target, and obtaining a local virtual admittance set value which enables the local voltage to approach to a target value through iterative calculation as the adjustment instruction; The virtual admittance control module is used for adjusting the modulation signal of the inverter bridge of the converter in real time according to the local virtual admittance set value so as to realize the dynamic control of the equivalent admittance of the grid-connected point.
6. The system of claim 5, wherein the distributed consistency algorithm is an average consistency algorithm or a proportional-integral consistency algorithm to achieve proportional allocation of reactive power of each intelligent power converter by capacity or adjustable margin.
7. The system of claim 6, wherein the regional level cooperative control objective is issued to each of the intelligent power converters via a manufacturing message specification service or a generic object-oriented substation event message based on IEC61850 standards.
8. The system of claim 1, wherein the intelligent power converter is any one of a photovoltaic inverter, an energy storage converter, or a wind power converter.
9. A method for dynamically balancing the source network load storage of a high-proportion new energy power grid, which is applied to the system as claimed in any one of claims 1 to 8, and comprises the following steps: s1, generating a regional level cooperative control target by the regional cooperative optimization layer through distributed optimization based on wide area measurement data and prediction data of a power grid; s2, each intelligent power converter in the distributed equipment execution layer receives the cooperative control target; S3, each intelligent power converter autonomously determines respective virtual admittance adjustment quantity through distributed negotiation with adjacent equipment based on the cooperative control target and local measurement data; And S4, the output of each intelligent power converter is adjusted according to the virtual admittance adjustment quantity so as to cooperatively realize the cooperative control target and complete the real-time dynamic balance of the power grid.
10. The method according to claim 9, wherein the step S1 specifically includes performing rolling optimization on the power grid state in a future time window by using a distributed model predictive control algorithm, and mapping the optimization result to a voltage or reactive cooperative target.

Description

Dynamic balance system and method for source network load storage of high-proportion new energy power grid Technical Field The invention relates to the field of electric energy, in particular to a source network load storage dynamic balancing system and method of a high-proportion new energy power grid. Background With the rapid improvement of the permeability of intermittent power sources such as wind power, photovoltaic and the like, the physical characteristics of a power system are radically changed, and the traditional stable pattern taking a synchronous generator as a dominant mode is broken. The strong randomness, fluctuation and weak support of the new energy output enable the difficulty of maintaining the real-time power balance and voltage stability of the power grid to be exponentially increased, and the problem of the high-proportion new energy consumption is changed from simple electric quantity acceptance to a dynamic balance control problem involving millisecond to minute time scales. In order to cope with the challenge, the prior art mainly develops in two directions, namely, the intelligent and quick performance of centralized control is enhanced, such as automatic generation control AGC algorithm improvement, ultra-short-term power prediction introduction and the like, but the essence is still a mode of central calculation and terminal execution, and the inherent bottlenecks of response delay, high calculation complexity, strong communication dependence and the like exist facing to massive and decentralized distributed resources, and the fully distributed local control is developed, such as autonomous frequency modulation and voltage regulation based on sagging characteristics. The two technical paths have the splitting on the control framework, so that the severe requirements on global optimization and rapid cooperation under a high-proportion scene are difficult to meet. Therefore, the outstanding problem in the current technical field is that the existing control system architecture cannot effectively cooperate with the optimal decision capability of the scheduling side and the quick response capability of the mass equipment side, so that the real-time dynamic balancing capability of the power grid for coping with the second-level fluctuation of the high-proportion new energy is insufficient. A new scheme capable of through optimization and execution, and integration of centralized guidance and distributed autonomy is needed to systematically improve the elasticity and toughness of the power grid. Disclosure of Invention The invention aims to provide a real-time dynamic balance solution for a high-proportion new energy power grid, which is self-contained, optimized and executed in a penetrating way, and guided and distributed in a concentrated way. According to a first aspect of the invention, a source network load storage dynamic balancing system of a high-proportion new energy power grid is provided, which comprises a regional collaborative optimization layer and a distributed equipment execution layer; The regional collaborative optimization layer is used for generating a regional-level collaborative control target through a distributed optimization algorithm based on wide-area measurement data and prediction data of the power grid; the distributed equipment execution layer comprises a plurality of intelligent power converters deployed in a power grid, wherein the intelligent power converters are configured to: Receiving a cooperative control target of a regional level; Based on the cooperative control target and the local measurement data, determining respective adjustment instructions through distributed negotiation of adjacent intelligent power converters in communication connection with the cooperative control target and the local measurement data; And adjusting the equivalent admittance of the grid-connected point according to the adjusting instruction so as to output corresponding reactive power and cooperatively realize the cooperative control target of the regional level. According to some embodiments, in the system of the first aspect of the present invention, the region co-optimization layer includes at least one region controller; the distributed optimization algorithm comprises a distributed model predictive control algorithm, and the regional controller is configured to execute the distributed model predictive control algorithm and specifically comprises: rolling estimation is carried out on the state of the future period of the power grid based on the wide-area measurement data and the ultra-short-term new energy power prediction data; taking the minimum area net load fluctuation as an optimization target, and solving an optimal control sequence in a future limited time window; The optimal control sequence is converted into a cooperative control target of a regional level, wherein the cooperative control target comprises at least a voltage reference value of a key bus o