CN-121984134-A - Power system capacity allocation method and system considering supply and demand unbalance risk under distributed resource seasonal characteristics

CN121984134ACN 121984134 ACN121984134 ACN 121984134ACN-121984134-A

Abstract

The invention relates to the technical field of intelligent power grid operation control, in particular to a power system capacity configuration method and system considering supply-demand unbalance risk under the seasonal characteristic of distributed resources, wherein the method comprises the steps of constructing a multi-dimensional meteorological time sequence based on historical meteorological data, and obtaining four-season typical and extreme meteorological scenes and occurrence probability thereof through clustering; the method comprises the steps of establishing a seasonal characteristic model of distributed energy output and load demands on the basis of the seasonal characteristic model, obtaining supply and demand results under different scenes, establishing an energy storage operation model containing cross-season energy-saving state continuity constraint, realizing seasonal scale energy transfer, further introducing supply and demand unbalance risk constraint in a planning stage, and carrying out cooperative configuration on distributed energy capacity, energy storage capacity and related equipment capacity.

Inventors

WANG CHONG
Yue Bowei
LI ZHENG
JIANG TINGYU
ZHANG CHENG
YANG RUI

Assignees

河海大学

Dates

Publication Date: 20260505
Application Date: 20260409

Claims (10)

1. A power system capacity allocation method considering the risk of unbalance of supply and demand under the seasonal characteristic of distributed resources, the method comprising: The method comprises the steps of generating a multi-dimensional weather time sequence reflecting seasonal variation characteristics based on historical weather data, carrying out cluster analysis on the multi-dimensional weather time sequence to obtain a typical weather scene and an extreme weather scene in four seasons, and determining occurrence probability of each scene; According to the typical meteorological scene, constructing a seasonal characteristic model of the output and load demand of the distributed energy along with the change of the meteorological conditions so as to describe the running characteristics of the distributed resources under different seasonal conditions, thereby obtaining the supply and demand results of the distributed resources under the typical meteorological scene; Constructing an energy storage operation model for coordinating energy demands of different time scales, and introducing cross-season energy-saving state continuity constraint into the energy storage operation model to limit the energy regulation capacity of the energy storage system under different season conditions; under the typical meteorological scene, an electric power system operation and planning model comprising supply and demand unbalance risk constraint is constructed based on the supply and demand result and the energy regulation capability as constraint conditions, and distributed energy capacity, energy storage capacity and related equipment capacity in the electric power system are cooperatively configured based on the electric power system operation and planning model, so that an electric power system capacity configuration scheme considering supply and demand unbalance risk under the seasonal characteristic of distributed resources is obtained.
2. The power system capacity allocation method considering the risk of unbalance between supply and demand under seasonal characteristics of distributed resources according to claim 1, wherein the method comprises generating a multidimensional weather time series reflecting the characteristic of seasonal variation, and performing cluster analysis on the multidimensional weather time series, comprising: Generating annual time series data containing air temperature, dew point temperature and irradiance based on a state transition probability matrix of historical meteorological data by adopting a Markov chain-Monte Carlo simulation method; Performing Z-Score standardization processing on the annual time series data, and dividing according to seasons and Zhou Du; And calculating the comprehensive similarity between time sequences by adopting an improved K-Shape algorithm for fusing dynamic time warping distances and taking a week as a unit, and completing scene clustering according to the comprehensive similarity.
3. The power system capacity allocation method considering the risk of unbalance between supply and demand under seasonal characteristics of distributed resources according to claim 1, wherein the constructing a seasonal characteristic model of the output of distributed energy and the load demand according to the weather conditions includes: establishing a photovoltaic module output power model, wherein the output power of the photovoltaic module output power model is coupled with solar irradiance and module working temperature; Establishing an electric automobile load model, wherein the electric automobile load model at least comprises a probability distribution model of the starting probability of an on-vehicle air conditioner about air temperature and a function model of the running power of the air conditioner about air temperature; and establishing a temperature control load model, wherein the temperature control load model describes the coupling relation between the power of the air conditioning system and the outdoor air temperature and humidity through a temperature and humidity index and a heat balance equation.
4. The power system capacity allocation method considering supply and demand unbalance risks under the seasonal characteristics of distributed resources according to claim 1, wherein the energy storage operation model is a hybrid energy storage model of liquid air energy storage and a storage battery, wherein the liquid air energy storage characterizes long-term energy transfer capacity of the liquid air energy storage through a cross-season energy-saving state continuity constraint, and the storage battery characterizes intra-day regulation capacity of the storage battery through a daily cycle energy balance constraint.
5. The power system capacity allocation method taking into account supply-demand imbalance risk under seasonal characteristics of distributed resources according to claim 1, wherein constructing an energy storage operation model for coordinating energy demands of different time scales and introducing cross-season energy saving state continuity constraints in the energy storage operation model to define energy conditioning capacity of the energy storage system under different seasonal conditions comprises: Establishing a hybrid energy storage architecture consisting of liquid air energy storage and electrochemical energy storage, wherein the liquid air energy storage is used for realizing energy transfer of seasons and longer periods, and the electrochemical energy storage is used for realizing daily cycle charge and discharge regulation; The power-quality coupling operation model of the liquid air energy storage is built, and the power-quality coupling operation model comprises an energy consumption model of a compression liquefaction link, a quality balance model of a liquid air storage link and a power generation power model of an expansion energy release link; Setting cross-period energy state continuity constraint for the liquid air energy storage to correlate energy storage states of different dispatching periods from beginning to end, ensuring long-term dispatching performance of energy, and setting daily energy balance constraint for the electrochemical energy storage.
6. The method according to claim 5, wherein the cross-cycle energy state continuity constraint is implemented by making the liquid air reserve at the initial time of the first scheduling period equal to or related to the reserve at the end time of the last scheduling period in an annual rolling schedule made up of typical weather periods.
7. The power system capacity allocation method taking into account supply and demand imbalance risk under seasonal characteristics of distributed resources according to claim 1, wherein the energy storage operation model further comprises an energy loss characterization of the liquid air energy storage: In the liquid air energy storage scheduling of the inter-week or inter-month, a self-release rate parameter is introduced to describe energy attenuation of the liquid air in the long-term storage process, and the self-release rate is used for correcting the liquid air reserves at the starting moment of the adjacent scheduling period.
8. The power system capacity allocation method considering supply and demand imbalance risk under distributed resource seasonal characteristics according to claim 1, wherein the energy storage operation model further comprises an operation state mutual exclusion constraint of liquid air energy storage in a single scheduling day: The liquid air energy storage can be only in one of an energy storage mode and an energy release mode in the same scheduling day, and the simultaneous charge and discharge operation is forbidden.
9. The power system capacity allocation method considering the risk of unbalance between supply and demand under seasonal characteristics of distributed resources according to claim 1, wherein the constructing the power system operation and planning model including the constraint of unbalance between supply and demand comprises: constructing an upper-level planning model aiming at minimizing the total cost of the system, wherein the total cost comprises the annual value of equipment investment and the expected cost of system operation in a typical meteorological scene; constructing a lower-layer operation simulation model aiming at minimizing the system electric quantity deficiency expectation and the renewable energy power-off expectation, and establishing an iterative optimization or nested solving relationship between the lower-layer operation simulation model and the upper-layer planning model; introducing supply-demand unbalance risk constraint in the power system operation and planning model, wherein the supply-demand unbalance risk constraint is constructed based on conditional risk value and is used for controlling expected supply-demand unbalance loss in an extreme meteorological scene within a preset threshold; And introducing line dynamic transmission capacity constraint into the power system operation and planning model, wherein the line dynamic transmission capacity constraint accounts for the influence of ambient air temperature on the current carrying capacity of the power transmission line.
10. A power system capacity allocation system taking into account supply-demand imbalance risk under seasonal characteristics of distributed resources, the system comprising: The system comprises a weather scene construction unit, a multi-dimensional weather time sequence generation unit, a weather scene generation unit and a weather scene generation unit, wherein the weather scene construction unit is used for generating a multi-dimensional weather time sequence reflecting seasonal change characteristics based on historical weather data; the source load characteristic modeling unit is used for constructing a seasonal characteristic model of the output and load demand of the distributed energy source along with the change of the meteorological conditions according to the typical meteorological scene so as to describe the running characteristics of the distributed resource under different seasonal conditions, thereby obtaining the supply and demand results of the distributed resource under the typical meteorological scene; The hybrid energy storage modeling unit is used for constructing an energy storage operation model for coordinating energy demands of different time scales, and introducing cross-season energy-saving state continuity constraint into the energy storage operation model so as to limit the energy adjustment capability of the energy storage system under different seasonal conditions; And the collaborative optimization configuration unit is used for constructing an electric power system operation and planning model containing unbalance risk constraint of supply and demand based on the supply and demand result and the energy regulation capability as constraint conditions in the typical meteorological scene, and collaborative configuration of distributed energy capacity, energy storage capacity and related equipment capacity in the electric power system based on the electric power system operation and planning model so as to obtain an electric power system capacity configuration scheme considering the unbalance risk of supply and demand under the seasonal characteristic of distributed resources.

Description

Power system capacity allocation method and system considering supply and demand unbalance risk under distributed resource seasonal characteristics Technical Field The invention relates to the technical field of intelligent power grid operation control, in particular to a power system capacity configuration method and system considering supply and demand unbalance risks under the seasonal characteristic of distributed resources. Background The capacity configuration of the power system refers to the process of comprehensively determining the power supply capacity, the energy storage capacity and the scale of related equipment under the given conditions of power supply reliability, economy and operation constraint, and aims to realize supply-demand balance and ensure the safe operation of the system in a planning period, and the power system gradually presents the characteristic that both sides of a source load are obviously influenced by weather conditions along with the continuous improvement of the access proportion of distributed resources, wherein the output level of the distributed renewable energy sources such as distributed photovoltaics changes along with factors such as solar irradiance and air temperature; the distributed load such as the charging load of the electric automobile, the air conditioning load and the like also presents obvious seasonal differences along with meteorological factors such as air temperature, humidity and the like, so that the power supply and demand relationship can be unbalanced in stages under different seasons and extreme meteorological conditions. The existing power system capacity configuration method is generally based on historical load and renewable energy output data, a typical day or typical week curve is selected for planning, power balance constraint and energy storage charge-discharge constraint are introduced into a model to optimize investment cost and operation cost, in a distributed resource scene, partial methods further consider influences of meteorological factors on output or load and deal with uncertainty in a multi-scene or probability weighting mode, however, the method is generally modeled in a relatively independent representative scene, continuous association is not generally established between different seasonal scenes of energy storage states, so that energy transfer relation between abundant energy seasons and withered energy seasons is difficult to accurately describe in a planning stage, and supply and demand unbalance risks under the season scale and extreme meteorological conditions are difficult to effectively constraint on a capacity configuration level. The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art. Disclosure of Invention The invention provides a power system capacity configuration method and system considering the supply and demand unbalance risk under the seasonal characteristic of distributed resources, thereby effectively solving the problems in the background technology. In order to achieve the purpose, the technical scheme adopted by the invention is that the power system capacity allocation method considering the unbalance risk of supply and demand under the seasonal characteristic of distributed resources comprises the following steps: The method comprises the steps of generating a multi-dimensional weather time sequence reflecting seasonal variation characteristics based on historical weather data, carrying out cluster analysis on the multi-dimensional weather time sequence to obtain a typical weather scene and an extreme weather scene in four seasons, and determining occurrence probability of each scene; According to the typical meteorological scene, constructing a seasonal characteristic model of the output and load demand of the distributed energy along with the change of the meteorological conditions so as to describe the running characteristics of the distributed resources under different seasonal conditions, thereby obtaining the supply and demand results of the distributed resources under the typical meteorological scene; Constructing an energy storage operation model for coordinating energy demands of different time scales, and introducing cross-season energy-saving state continuity constraint into the energy storage operation model to limit the energy regulation capacity of the energy storage system under different season conditions; under the typical meteorological scene, an electric power system operation and planning model comprising supply and demand unbalance risk constraint is constructed based on the supply and demand result and the energy regulation capability as constraint conditions, and distributed energy capacity, energy storage capacity and related equipmen