Electrified flexible source load adjustable potential evaluation method considering cold load characteristics

Abstract

The invention discloses an electrified flexible source load adjustable potential evaluation method considering cold load characteristics, and particularly relates to the technical field of electric power system evaluation and control, and the method comprises the steps: S1, obtaining the environment and equipment parameters of a cold load monomer, S2, constructing an electric-thermal coupling refined model considering a comfort level elastic interval, and S3, constructing an electric-thermal coupling refined model considering a comfort level elastic interval; the method comprises the steps of S1, obtaining a plurality of monomers, S3, calculating the adjustable potential of the monomers and generating a constraint envelope line representing the dynamic attenuation characteristics of the monomers, S4, obtaining a regional cluster potential evaluation result through aggregation according to the spatial dimension and the time scale, and S5, uploading the result to a power grid dispatching system for security defense and intelligent dispatching of a power grid of 750 kilovolts and above. According to the method, accurate quantification and dynamic representation of the adjustable potential of the cooling load are realized, the blank of cognition of a large power grid on the distributed cooling load is filled, and the flexible resource utilization level and the operation safety of the power grid are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of power system assessment and control technology, and more specifically, to a method for assessing the adjustable potential of electrified flexible source loads considering cold load characteristics. Background Technology

[0002] Driven by the dual-carbon strategy, the penetration rate of renewable energy sources, represented by wind power and photovoltaics, in the power grid has increased significantly. However, the randomness and volatility of their output pose a severe challenge to the safe and stable operation of large-scale interconnected power grids of 750 kV and above. At the same time, socio-economic development has led to a sharp increase in the proportion of cooling loads such as air conditioning during peak summer electricity consumption periods, which has become a key factor affecting the peak-valley balance of the power grid. Its potential for large-scale regulation is of great significance for ensuring power grid security and promoting the consumption of new energy sources.

[0003] Currently, existing methods for assessing the potential for adjustable cooling load have the following main shortcomings: First, most methods use a simple aggregation model, treating the cooling load as a traditional "on / off" load, completely ignoring its inherent thermal energy storage characteristics, i.e. thermal inertia, which leads to the evaluation model deviating significantly from physical reality. Secondly, when modeling, a single, fixed temperature setpoint is usually used as a constraint, which fails to fully consider and utilize the user's flexible space for temperature perception. This results in evaluation results that are either too conservative and fail to fully tap the potential, or too aggressive and damage user comfort. Finally, and most importantly, the evaluation output of existing methods is mostly a static power value, which cannot reflect the dynamic decay characteristics of the cluster potential over time during the response process. This makes it difficult for the power grid dispatch center to accurately determine how long the potential can last, and therefore it dares not trust and call such resources in critical defense scenarios involving frequency stability and section safety.

[0004] In view of this, the present invention provides a method for evaluating the adjustable potential of electrified flexible source loads that takes into account the characteristics of cold load. Summary of the Invention

[0005] In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a method for evaluating the adjustable potential of electrified flexible source load considering the characteristics of cold load, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for assessing the adjustable potential of electrified flexible source loads considering cooling load characteristics, comprising the following steps: S1. Obtain the environmental parameters and equipment operating parameters corresponding to each cooling load unit in the target area; S2. Based on environmental parameters and equipment operating parameters, construct a refined model of cold load electro-thermal coupling that considers the user comfort elasticity range; S3. Based on the refined electro-thermal coupling model, calculate the adjustable potential of each cooling load unit under the preset comfort constraint, and generate the constraint envelope characterizing the dynamic change of its adjustable potential over time. S4. Aggregate the constraint envelopes of all individual cooling load units within the target area according to the preset spatial dimensions and time scales to obtain the adjustable potential assessment results of the regional cooling load cluster. S5. Upload the assessment results of the adjustable potential of regional cold load clusters to the power grid dispatching system for security defense and intelligent dispatching of 750 kV and above power grids.

[0007] Preferably, in step S2, constructing a refined model of cooling load electro-thermal coupling considering the user comfort elasticity range specifically includes: establishing an equivalent thermal parameter differential equation model with indoor temperature as the state variable. The parameters of the model include at least the building equivalent thermal resistance, the building equivalent heat capacity, and the air conditioning energy efficiency ratio. The user temperature setpoint is extended from a fixed point to an acceptable temperature fluctuation range. The upper and lower limits of the temperature fluctuation range are used as constraints for the equivalent thermal parameter differential equation model when calculating the adjustable potential.

[0008] Preferably, after step S2, the method further includes step S2a: online adaptive identification of model parameters, specifically: using real-time or near-real-time power data and temperature data collected by smart meters, and through the least squares method or Kalman filtering algorithm, dynamically identifying and updating the building equivalent thermal resistance and building equivalent heat capacity in the equivalent thermal parameter differential equation model.

[0009] Preferably, in step S3, the adjustable potential of each cooling load unit under preset comfort constraints is calculated, specifically including: Upward adjustment potential calculation: Under the constraint that the indoor temperature does not exceed the upper limit of the temperature fluctuation range, calculate the power reduction that can be provided within the maximum sustainable shutdown time after the individual cooling unit of the cooling load is shut down; Downward potential calculation: Under the constraint that the indoor temperature is not lower than the lower limit of the temperature fluctuation range, calculate the increase in power that a single refrigeration unit can provide after being turned on from the off state.

[0010] Preferably, the process of generating the constraint envelope in step S3 is as follows: for the up-adjustment potential, the process of simulating the process of some cooling load units exiting the response due to the rise in indoor temperature within the maximum sustainable shutdown duration, causing the total up-adjustment potential of the cluster to decay over time, forms a power-time relationship curve, which is the constraint envelope.

[0011] Preferably, the aggregation according to the preset spatial dimension in step S4 specifically involves: performing hierarchical and partitioned aggregation according to the voltage level and geographical administrative region of the power grid to form a multi-level potential view from the low-voltage user side to the high-voltage transmission network side.

[0012] Preferably, the aggregation according to a preset time scale in step S4 includes: Second-level / minute-level potential aggregation: Selecting and aggregating individual cold loads whose maximum sustainable shutdown duration is greater than the first preset time threshold, and using the evaluation results for primary frequency regulation of the power grid; Hourly potential aggregation: The potential of all individual cold loads is aggregated, and the evaluation results are used for peak shaving and valley filling of the power grid.

[0013] Preferably, the specific form of the adjustable potential assessment result of the regional cold load cluster obtained in step S4 is as follows: a dynamic potential map is generated, and the map displays the total adjustable potential value of different partitions at different time scales and their corresponding constraint envelopes in a visual manner.

[0014] Preferably, step S5 for security defense and intelligent dispatching of 750 kV and above power grids specifically includes: when the power grid dispatching system detects the risk of frequency exceeding the limit or line power exceeding the limit, it calls the adjustable potential assessment results of the regional cold load cluster, and generates a control command for the designated regional cold load cluster based on the potential and duration defined by the constraint envelope, so as to achieve safe and stable control of the power grid.

[0015] The technical effects and advantages of this invention are as follows: This invention establishes an accurate electro-thermal coupling dynamic model by using user comfort elastic range constraints and online adaptive identification technology for model parameters. It also proposes a constraint envelope that characterizes the dynamic change of adjustable potential over time, realizing a fundamental transformation from static rough estimation to dynamic fine evaluation of cooling load adjustable potential, and significantly improving the accuracy and reliability of the evaluation results. This invention integrates the multi-timescale adjustable potential assessment results obtained by hierarchical and partitioned aggregation into the intelligent dispatch system of 750 kV and above power grids in the form of a dynamic potential map. This fills the gap in the understanding of massive distributed cold loads in the large power grid security defense system, provides new control resources for the power grid, and enhances the power grid's proactive defense capability against power fluctuations and fault disturbances. This invention leverages the thermal energy storage characteristics of cold loads to effectively aggregate dispersed cold load resources into a controllable virtual energy storage system while ensuring user comfort. This improves the comprehensive utilization efficiency of distributed flexible resources, provides a new technical means for power grid peak shaving and valley filling and the absorption of renewable energy, and significantly enhances the economy and security of power grid operation. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the overall steps of the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0018] This invention provides a method for assessing the adjustable potential of electrified flexible source loads considering cooling load characteristics. In specific implementation, it includes the following steps: data acquisition, model construction, potential calculation and constraint envelope generation, potential aggregation, and result uploading and application.

[0019] S1. Obtain the environmental parameters and equipment operating parameters corresponding to each cooling load unit in the target area; In the specific implementation of this step, environmental parameters and equipment operating parameters of each cooling load unit (such as the air conditioning system of a home or office building) in the target area are collected by deploying smart meters and temperature sensors on the user side and obtaining public data from the meteorological department. Among them, the environmental parameters include at least the outdoor temperature and solar radiation intensity, and the equipment operating parameters include at least the on / off status of the refrigeration equipment, the real-time operating power, the temperature range set by the user, and the actual indoor temperature.

[0020] S2. Based on environmental parameters and equipment operating parameters, construct a refined model of cold load electro-thermal coupling that considers the user comfort elasticity range; This step is the core foundation for achieving accurate online assessment. Based on the data obtained in step S1, a refined electro-thermal coupling model considering the user comfort flexibility range is constructed for each cooling load unit, as detailed below: First, an equivalent thermal parameter model of the cooling load unit is established, treating the building as a thermodynamic system whose thermal dynamic processes can be described by differential equations:

[0021] Among them, T in Indoor temperature, state variable, T out Where C is the outdoor temperature, R is the building's equivalent heat capacity, and P is the building's equivalent thermal resistance. cool Q represents the air conditioner's cooling capacity, taken from the equipment's operating parameters, and is a positive value. COP is the air conditioner's energy efficiency ratio. other For other thermal disturbances, such as heat generated by personnel or equipment, the values ​​are positive. The core parameters of the model include the building's equivalent thermal resistance R, the building's equivalent heat capacity C, and the air conditioning energy efficiency ratio COP, which can be obtained through subsequent online identification.

[0022] Secondly, a user comfort elastic range is introduced, which expands the user temperature setpoint from a fixed point (such as 26℃) to an acceptable temperature fluctuation range (such as 24℃-28℃). The upper and lower limits of this range will serve as rigid constraints for the equivalent thermal parameter differential equation model when calculating the adjustable potential.

[0023] Optionally and preferably, it also includes step S2a, where model parameters are adaptively identified online; To improve model accuracy, Rr utilizes real-time or near-real-time power and temperature data collected by smart meters. It then uses the least squares method or Kalman filtering algorithm to dynamically identify and update the model parameters R or C. For example, the parameters are re-identified using data from the most recent period (e.g., 1 hour) every certain period (e.g., 15 minutes). This allows the model to adapt to seasonal changes, differences in building characteristics, and changes in user behavior, ensuring the real-time nature and accuracy of the evaluation results. S3. Based on the refined electro-thermal coupling model, calculate the adjustable potential of each cooling load unit under the preset comfort constraint, and generate a constraint envelope characterizing the dynamic change of its adjustable potential over time. This step is based on the accurate model established in step S2 to calculate the adjustable potential of each cooling load unit. Upward adjustment potential calculation: Under the constraint that the indoor temperature does not exceed the upper limit of the temperature fluctuation range, calculate the amount of power reduction that can be provided by the individual cooling unit after the cooling load is turned off within the maximum sustainable shutdown time. For example, if the current indoor temperature is 26℃ and the upper limit of the comfort range is 28℃, simulate the time required for the indoor temperature to rise to 28℃ after the air conditioner is turned off according to the ETP model. The power reduction during the time period when the air conditioner is turned off is the upward adjustment potential. Calculation of reduction potential: Under the constraint that the indoor temperature is not lower than the lower limit of the temperature fluctuation range, calculate the increase in power that a single cooling unit can provide after being turned on from the off state. For example, if the current indoor temperature is within the comfort range, but the air conditioner is off, the increase in power after turning on the air conditioner is the reduction potential. More importantly, this step will also generate a constraint envelope. For the up-up potential, it simulates that within the maximum sustainable shutdown duration, due to the rise in indoor temperature, some cooling load units will stop responding because they reach the temperature limit. Therefore, the total up-up potential of the entire cluster is not a constant value, but a curve that dynamically decays over time. This power-time relationship curve is the constraint envelope, which accurately depicts the key information of how much power can be mobilized at the current moment and how long that power can be sustained. S4. Aggregate the constraint envelopes of all individual cooling load units within the target area according to preset spatial dimensions and time scales to obtain the assessment results of the adjustable potential of the regional cooling load cluster, as follows: Spatial dimension aggregation: Layered and zoned aggregation according to the voltage level of the power grid (such as 220V user side, 10kV distribution side and 110kV transmission network side) and geographical administrative region (such as street, district and city) helps dispatchers to clearly grasp the spatial distribution of potential in the power grid, thereby forming a multi-level potential view from the user side to the main power grid. For example, first aggregate all the cold loads of a certain community, and then aggregate all the communities of a certain street to form a multi-level potential view from the low-voltage user side to the high-voltage transmission network side. Time-scale aggregation specifically includes: Second-level / minute-level potential aggregation: This involves aggregating individual cold loads whose maximum sustainable shutdown duration exceeds a first preset time threshold (e.g., 2 minutes). This potential has a fast response time and can be used for primary frequency regulation in the power grid. Hourly potential aggregation: Aggregates the potential of all individual cold loads, focusing on assessing their total energy, and the assessment results are used for peak shaving and valley filling of the power grid; The final result of the aggregation is presented in the form of a dynamic potential map, which is overlaid on the GIS system and can intuitively show the total adjustable potential of different regions at the current time and at different time scales, as well as their constraint envelopes.

[0024] S5. Upload the assessment results of the adjustable potential of the regional cold load cluster to the power grid dispatching system for the security defense and intelligent dispatching of the 750 kV and above power grid. This step involves uploading and integrating the dynamic potential map and related data generated in step S4 into the intelligent dispatching system and security defense system of the 750 kV and above power grid via standard communication protocols. Specific application scenarios are as follows: When the dispatching system detects the risk of frequency exceeding limits or power exceeding limits of critical sections through the wide-area measurement system, it can immediately call upon the assessment results provided by this method. The dispatcher or automatic control system can accurately issue control commands based on the constraint envelope of the target area. For example, when the frequency drops, it can call upon the second-level up-adjustment potential of a certain area and specify the effective duration of the command, thereby quickly supporting the restoration of the power grid frequency while ensuring user comfort and achieving safe and stable control of the power grid.

[0025] In summary: This invention achieves accurate quantification of the adjustable potential of cold load through refined modeling and dynamic evaluation, filling the gap in the large power grid security defense system in this field and significantly improving the power grid's utilization level and security stability of distributed flexible resources.

[0026] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An evaluation method of the adjustable potential of electrified flexible source and load considering the characteristics of cold load, characterized in that: The method comprises the following steps: S1, obtaining the environmental parameters and equipment operation parameters corresponding to each cold load unit in the target area; S2, based on the environmental parameters and equipment operation parameters, a cold load electric-thermal coupling refined model considering the user comfort flexibility interval is constructed; S3, based on the electric-thermal coupling refined model, the adjustable potential of each cold load unit under the preset comfort constraint is calculated, and a constraint envelope line representing the dynamic change of the adjustable potential over time is generated; S4, the constraint envelope lines of all cold load units in the target area are aggregated according to the preset spatial dimension and time scale, and the adjustable potential evaluation result of the regional cold load cluster is obtained; S5, the adjustable potential evaluation result of the regional cold load cluster is uploaded to the power grid dispatching system for the safety defense and intelligent dispatching of 750kV and above power grids. 2.The method of claim 1, wherein the method further comprises: In step S2, the cold load electric-thermal coupling refined model considering the user comfort flexibility interval specifically includes: establishing an equivalent thermal parameter differential equation model with indoor temperature as a state variable, the parameters of the model at least including building equivalent thermal resistance, building equivalent thermal capacity and air conditioning energy efficiency ratio, and expanding the user temperature set value from a fixed point to an acceptable temperature floating interval, the upper and lower limits of the temperature floating interval being used as the constraint conditions of the equivalent thermal parameter differential equation model when calculating the adjustable potential. 3.The method of claim 2, wherein the method further comprises: determining the adjustable potential of the electrical flexible source and load based on the cold load characteristics. After step S2, step S2a of online adaptive identification of model parameters is further included, specifically: using real-time or quasi-real-time power data and temperature data collected by smart meters, the building equivalent thermal resistance and building equivalent thermal capacity in the equivalent thermal parameter differential equation model are dynamically identified and updated through least squares method or Kalman filtering algorithm. 4.The method of claim 1, wherein the method further comprises: In step S3, the adjustable potential of each cold load unit under the preset comfort constraint is calculated, specifically including: Up-regulation potential calculation: under the constraint that the indoor temperature is not higher than the upper limit of the temperature floating interval, the power reduction amount that the cold load unit can provide within the maximum sustainable shutdown time after the refrigeration equipment is turned off is calculated; Down-regulation potential calculation: under the constraint that the indoor temperature is not lower than the lower limit of the temperature floating interval, the power increase amount that the cold load unit can provide after the refrigeration equipment is turned on from the shutdown state is calculated.

5. The method of claim 4, wherein the method further comprises: In step S3, the constraint envelope line is generated, specifically: for the up-regulation potential, the process of the total up-regulation potential of the cluster decaying over time due to the indoor temperature rising and some cold load units exiting the response because they touch the temperature upper limit within the maximum sustainable shutdown time is simulated, forming a power-time relationship curve, which is the constraint envelope line.

6. The method of claim 1, wherein the method further comprises: In step S4, the aggregation according to the preset spatial dimension is specifically: according to the voltage level and geographical administrative region of the power grid, the aggregation is layered and zoned to form a multi-level potential view from the low-voltage user side to the high-voltage transmission grid side.

7. The method of claim 1, wherein the method further comprises: The aggregation according to the preset time scale in step S4 includes: Second-level / minute-level potential aggregation: the cold load units with maximum sustainable shutdown time greater than a first preset time threshold are selected for aggregation, and the evaluation result is used for power grid primary frequency modulation; Hour-level potential aggregation: the potentials of all cold load units are aggregated, and the evaluation result is used for power grid peak clipping and valley filling. 8.The method of claim 1, wherein the method further comprises: determining the adjustable potential of the electrical flexible source and load based on the cold load characteristics. The specific form of the adjustable potential evaluation result of the regional cold load cluster in step S4 is to generate a dynamic potential map, which visually displays the total adjustable potential values of different partitions at different time scales and the corresponding constraint envelopes. 9.The method of claim 1, wherein the method further comprises: The specific form of the security defense and intelligent dispatch for the 750 kV and above power grid in step S5 includes: when the power grid dispatching system detects the risk of frequency out-of-limit or line power out-of-limit, the adjustable potential evaluation result of the regional cold load cluster is called, the control instruction for the specified regional cold load cluster is generated according to the potential and duration defined by the constraint envelope, so as to realize the safe and stable control of the power grid.

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