High-energy load flexibility potential assessment method

Abstract

The invention relates to the technical field of flexibility resource potential assessment, and particularly discloses a high-energy load flexibility potential assessment method, which comprises the following steps: constructing a high-energy load flexibility supply refinement model; based on an inter-node multi-path resource transmission mechanism, constructing a flexible supply and demand transmission model and a system flexible supply and demand space-time balance condition; establishing a high-energy load response potential evaluation index system; and on the basis of time sequence production operation simulation, taking the system flexibility insufficient index as an optimization variable, and constructing a high-energy load response potential evaluation model considering flexible supply and demand space-time balance. According to the method, the adjustment characteristic of the high-energy load, the supply and demand transmission process of the power grid and the spatial-temporal distribution characteristic are comprehensively considered, so that the support potential of the high-energy load for the flexibility of the power system is accurately evaluated, and the operation scheduling of the power system is optimized.

Description

Technical Field

[0001] The present application relates to the technical field of flexibility resource potential assessment, and more specifically, to a method for assessing the flexibility potential of high-energy-consuming loads. Background Art

[0002] With the continuous increase in the access ratio of new energy sources such as wind power in the power system, its random volatility has increased significantly, posing a huge challenge to the operation and dispatching of the power system, and frequent problems such as wind curtailment and load shedding have emerged. The flexibility supply capacity of traditional flexibility resources (such as conventional generating units) has been difficult to meet the growing flexibility demand of the power grid. Therefore, demand-side flexibility resources have gradually become an important research direction for power grid dispatching operation. Due to its large electricity consumption, high control reliability, and flexible adjustment characteristics of production plans, high-energy-consuming loads have considerable adjustment potential and can play a key role in improving the wind power consumption capacity and alleviating the system operation pressure during peak load periods.

[0003] Currently, for the research on the assessment of the flexibility potential of high-energy-consuming loads, most of them adopt qualitative analysis index scoring methods or data-driven quantitative calculation methods, mainly focusing on their adjustment potential in single services such as peak shaving and reserve. However, these studies fail to fully consider the coupling effect between different service types, which may affect the accuracy of the assessment results. In addition, due to the differences in the spatial distribution of power sources and loads, electrical energy needs to be transmitted to the load end through the power system network. If the transmission process between flexibility supply and demand is ignored during the assessment of flexibility potential, the assessment results may be too optimistic.

[0004] Therefore, a method for assessing the flexibility potential of high-energy-consuming loads is provided. Summary of the Invention

[0005] In order to solve the above technical problems, the present application is proposed.

[0006] Specifically, according to one aspect of the present application, a method for assessing the flexibility potential of high-energy-consuming loads is provided, which includes:

[0007] S1. Construct a refined model for the flexibility supply of high-energy-consuming loads, where the refined model for the flexibility supply of high-energy-consuming loads includes an electrolytic aluminum load flexibility supply model based on power-current-temperature coupling and an electric arc furnace load flexibility supply model based on the production process;

[0008] S2. Construct a quantitative model for the flexibility supply and demand of power grid nodes;

[0009] S3. Based on the multi-path resource transmission mechanism between nodes, construct a flexibility supply-demand transmission model and the spatio-temporal balance condition of system flexibility supply and demand;

[0010] S4. Establish an evaluation index system for the response potential of high-energy-consuming loads;

[0011] S5. Based on the time-series production operation simulation, use the system flexibility deficiency index as the optimization variable to construct an evaluation model for the response potential of high-energy-consuming loads considering the spatio-temporal balance of flexibility supply and demand.

[0012] Optionally, in the above S3, the flexibility supply-demand transmission model is:

[0013]

[0014] In the formula, and are the distribution amounts of node flexibility supply / demand on line k at time t respectively, and are the regularized flexibility supply / demand transmission amounts of line k at time t respectively, and are the flexibility resource / demand transfer distribution factors of the flexibility supply / demand change at node i on line k respectively, and are the upward and downward flexibility supplies of node i at time t respectively, and are the upward and downward flexibility demands of node i at time t respectively.

[0015] Optionally, in the above S3, the spatio-temporal balance condition of system flexibility supply and demand is:

[0016]

[0017] In the formula, is the flexibility regulation capacity of line k at time t, and P k,t-1 are the maximum transmission capacity of line k and the power transmission value at the previous moment respectively.

[0018] Optionally, in the above S4, the response potential evaluation index system includes the following indexes:

[0019] 1) Peak shaving rate

[0020]

[0021] In the formula, P p and P p ' are the system load peaks before and after the response of high-energy-consuming loads respectively;

[0022] 2) Valley filling rate

[0023]

[0024] In the formula, Pv and P v ' are the minimum system loads before and after the high-energy load responds, respectively;

[0025] 3) System upward flexibility deficiency

[0026]

[0027] In the formula, F defc,+ is the system upward flexibility deficiency; is the upward flexibility deficit of line k at time t;

[0028] 4) System downward flexibility deficiency

[0029]

[0030] In the formula, F defc,- is the system downward flexibility deficiency; is the downward flexibility deficit of line k at time t.

[0031] Compared with the prior art, a method for evaluating the flexibility potential of high-energy loads provided by this application constructs an electrolytic aluminum load flexibility supply model based on power-current-temperature coupling and an electric arc furnace load flexibility supply model based on the production process, accurately describing how high-energy loads flexibly respond to the demand changes of the power system; secondly, using the multi-path resource transmission mechanism between grid nodes, considering and analyzing the distribution of flexibility resources and demands in time and space, and establishing a set of response potential evaluation index systems covering peak shaving and flexibility, which can quantitatively measure the contribution of high-energy loads to the flexibility of the power system; finally, taking the flexibility deficiency index as an optimization variable to construct a high-energy load response potential evaluation model considering the spatio-temporal balance of flexibility supply and demand, which evaluates the peak shaving ability of high-energy loads by simulating the operating conditions at different time points, and further analyzes its flexibility supply potential based on the peak shaving ability. Brief Description of the Drawings

[0032] By describing the embodiments of the present application in more detail in combination with the accompanying drawings, the above and other objects, features, and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0033] Figure 1 Illustrates a high-energy load flexibility potential evaluation framework diagram according to an embodiment of the present application.

[0034] Figure 2The flowchart of the high-energy-consuming load flexibility potential assessment method according to an embodiment of the present application is illustrated.

[0035] Figure 3 The schematic diagram of the spatio-temporal balance analysis of flexibility supply and demand according to an embodiment of the present application is illustrated. Detailed implementation manners

[0036] Hereinafter, embodiments according to the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0037] Embodiment:

[0038] Figure 1 It is a framework diagram for assessing the flexibility potential of high-energy-consuming loads. This diagram not only lists all the input data required for the assessment (including conventional load demands, conventional thermal power units, electrolytic aluminum loads, electric arc furnace loads, grid topologies, and new energy outputs), but also details the model solution steps and calculation evaluation indicators involved in the assessment process. This diagram not only provides a clear assessment process for researchers, but also provides important decision-making support information for decision-makers, helping to better understand and utilize the flexibility of high-energy-consuming loads, thereby improving the stability and economy of the power system.

[0039] As Figure 2 shown, the high-energy-consuming load flexibility potential assessment method according to an embodiment of the present application includes: S1. Construct a refined model for the flexibility supply of high-energy-consuming loads, where the refined model for the flexibility supply of high-energy-consuming loads includes an electrolytic aluminum load flexibility supply model based on power-current-temperature coupling and an electric arc furnace load flexibility supply model based on the production process; S2. Construct a quantification model for the flexibility supply and demand of grid nodes; S3. Based on the multi-path resource transmission mechanism between nodes, construct a flexibility supply and demand transmission model and the spatio-temporal balance condition of system flexibility supply and demand; S4. Establish an evaluation index system for the response potential of high-energy-consuming loads; S5. Based on the time-series production operation simulation, use the system flexibility shortage index as an optimization variable to construct a high-energy-consuming load response potential assessment model considering the spatio-temporal balance of flexibility supply and demand.

[0040] In the embodiments of the present application, S1 is to construct a refined model for the flexible supply of high-energy-consuming loads, where the refined model for the flexible supply of high-energy-consuming loads includes an electrolytic aluminum load flexible supply model based on power-current-temperature coupling and an electric arc furnace load flexible supply model based on the production process. It should be understood that in the traditional method, the evaluation of the flexible supply of loads is only carried out through a single model. However, the regulation characteristics and influencing factors of different types of loads may be different, and there may also be a coupling effect between different service types. This single model is too simplistic and difficult to fully consider the spatio-temporal distribution characteristics of flexible supply and demand, which may lead to an overly optimistic evaluation result and be unable to truly reflect the support ability of high-energy-consuming loads for the flexible operation of the system. Therefore, in order to more accurately evaluate the flexibility potential of high-energy-consuming loads in the power system, a refined model including various high-energy-consuming loads is constructed. This model includes an electrolytic aluminum load flexible supply model based on power-current-temperature coupling and an electric arc furnace load flexible supply model based on the production process. Such a construction helps to comprehensively consider various production regulation factors, couples factors such as power, current, temperature, output, and efficiency, and meets production safety constraint indicators such as current and temperature. In this way, the model can more truly reflect the regulation characteristics and potential of high-energy-consuming loads, thereby providing more accurate data support for the optimal dispatching of the power system.

[0041] Specifically, when constructing an electrolytic aluminum load flexible supply model based on power-current-temperature coupling, a series of constraint conditions need to be satisfied to ensure that the model can truly reflect the actual situation in the electrolytic aluminum production process, so as to provide an accurate flexibility evaluation for the power system. Among them, these constraints include:

[0042] 1) Power-current coupling constraint

[0043]

[0044] In the formula, P AL,t is the power of the electrolytic aluminum load at time t, P AL,max and P AL,min are the upper and lower limits of the inherent power of the electrolytic aluminum load at time t respectively, I AL,t is the series current of the electrolytic aluminum load at time t, I AL,max and I AL,min are the upper and lower limits of the inherent current of the electrolytic aluminum load at time t respectively, R m is the equivalent resistance, and E m is the equivalent back electromotive force;

[0045] 2) Power-temperature coupling constraint

[0046]

[0047] In the formula, T AL,tis the production temperature of the electrolytic aluminum load at time t, T AL,min and T AL,max are respectively the upper and lower limits of the inherent temperature of the electrolytic aluminum load at time t, c AL is the specific heat capacity coefficient of the electrolyte, m AL is the mass of the electrolyte;

[0048] 3) Power adjustment time constraint

[0049]

[0050] In the formula, x AL,t is the power adjustment flag bit of the electrolytic aluminum load at time t. When the value is 1, it means the power is adjusted. When the value is 0, it means the power remains unchanged; T is the scheduling period, T on is the minimum time to maintain the constant power of the electrolytic aluminum load, and M is a constant.

[0051] These constraint conditions ensure that the model can reflect the safety and efficiency in the electrolytic aluminum production process, and at the same time meet the scheduling requirements of the power system.

[0052] By comprehensively considering the power-current coupling constraint, power-temperature coupling constraint, and power adjustment time constraint, the actual situation in the electrolytic aluminum production process can be more accurately simulated, and thus the following flexibility supply model of the electrolytic aluminum load can be obtained:

[0053]

[0054] In the formula, and are respectively the upward and downward flexibility supply capabilities of the electrolytic aluminum load at time t.

[0055] Similarly, when constructing the flexibility supply model of the electric arc furnace load based on the production process, a series of constraint conditions also need to be met to ensure that the model can truly reflect the actual situation in the electric arc furnace production process, so as to provide a more accurate basis for the optimal scheduling of the power system. Among them, the specific constraints include:

[0056] 1) Power regulation constraint

[0057]

[0058] In the formula, and are respectively the maximum upward and downward adjustment powers when the nth electric arc furnace is in the production state at time t, and are respectively the upper and lower limits of the inherent power when the nth electric arc furnace is in the production state at time t;

[0059] 2) Production state constraint

[0060]

[0061] Wherein, is the time required for one heat of production in the electric arc furnace;

[0062] 3) Production status constraint

[0063]

[0064] Wherein, is the maximum furnace drying time of the electric arc furnace.

[0065] By comprehensively considering the power regulation constraint, production status constraint, and production status constraint, a more accurate and practical electric arc furnace load flexibility supply model based on the production process can be obtained, providing strong support for the optimal dispatching of the power system and the utilization of flexibility resources. The electric arc furnace load flexibility supply model is expressed as follows:

[0066]

[0067] Wherein, and are respectively the total upward and downward flexibility supply capabilities of the electric arc furnace load at time t, and are respectively the upward and downward ramp rate limits of the nth electric arc furnace at time t, and Δt is the adjacent time interval.

[0068] In the embodiment of the present application, in step S2, a quantization model for the flexibility supply and demand of grid nodes is constructed. Considering that the randomness of wind power and the uncertainty of load are the main factors affecting the stability of the power grid, by quantifying the impact of these random fluctuations on the flexibility demand of the power grid, the flexibility demand of the power grid can be more accurately evaluated, and corresponding countermeasures can be formulated. Based on this, in step S2, the flexibility resources of grid nodes specifically consider thermal power and high-energy-consuming loads, and the flexibility demand of nodes specifically considers the random fluctuations of wind power and load.

[0069] In addition, in order to more accurately evaluate the uncertainty of the net load prediction, the errors between the historical measured net load data and the predicted data are comprehensively analyzed. Specifically, the non-parametric kernel density estimation is used to dynamically calculate the prediction error limit of the net load at each moment, and the range of the node net load at time t can be expressed as: Wherein, P i,t and are respectively the measured value and the predicted value of the net load of node i at time t, and δ i,t is the prediction error limit of the net load of node i at time t. This dynamic calculation method can capture the probability distribution characteristics of the net load prediction error, thereby providing more reliable prediction information for power grid dispatching.

[0070] Specifically, the flexibility demand model of each node in the system is determined based on the prediction error limit of the net load, and the upward and downward flexibility demands are determined by calculating the maximum and minimum values of the net load. The flexibility demand model of each node in the system is as follows:

[0071]

[0072] In the formula, and are the upward and downward flexibility demands of node i at time t respectively, and are the maximum and minimum values of the net load of node i at time t respectively.

[0073] Specifically, the flexibility supply model of each node in the system considers thermal power and high-energy-consuming loads (such as electrolytic aluminum and electric arc furnaces) as flexibility resources, and the flexibility of thermal power units is related to their ramping ability and regulation ability. The flexibility supply model of each node in the system is as follows:

[0074]

[0075] In the formula, P g,m,t , and are the output and upper and lower limits of thermal power unit m at time t respectively, and are the upward and downward ramping abilities of thermal power unit m respectively, K g,m,i , K AL,i and K EAF,i are the power flow distribution coefficients of thermal power units, electrolytic aluminum loads, and electric arc furnace loads respectively.

[0076] In the embodiment of the present application, in step S3, based on the multi-path resource transmission mechanism between nodes, a flexibility supply-demand transmission model and the spatio-temporal balance condition of system flexibility supply and demand are constructed. It should be understood that the flexibility supply and demand in the power system are not only affected by individual nodes but also by the interaction between nodes in the entire network. By allocating the flexibility supply and demand at nodes to each line according to a certain ratio, the spatial propagation effect of the random fluctuations of node source loads in the power grid can be more realistically described, and then the spatial distribution of system flexibility supply and demand can be quantified. Therefore, a flexibility supply-demand transmission model is further constructed based on the multi-path resource transmission mechanism between nodes.

[0077] Specifically, the flexibility supply-demand transmission model is as follows:

[0078]

[0079] In the formula, and are the allocation amounts of node flexibility supply / demand on line k at time t respectively; and are respectively the flexible supply / demand transfer amounts of line k at time t after regularization; and are respectively the flexible resource / demand transfer distribution factors of the change in flexible supply / demand at node i with respect to line k.

[0080] By constructing a flexible supply-demand transfer model, the flexible supply-demand situations on different nodes and lines can be quantified, thereby providing more accurate information for the optimal dispatching of the power system.

[0081] In particular, the operating condition of the power system is dynamically changing. If the flexible supply and demand are not balanced, the system may not be able to adapt to the changes in the power grid, affecting the reliability of the power grid. Therefore, further consider the flexible regulation accommodation capacity of the line and define the spatio-temporal balance condition of the flexible supply and demand of the system.

[0082] Specifically, this Figure 3 demonstrates the spatio-temporal balance concept of flexible supply and demand in the power system in an intuitive way. Among them, the spatio-temporal balance condition of the flexible supply and demand of the system is:

[0083]

[0084] In the formula, is the flexible regulation accommodation capacity of line k at time t, and P k,t-1 are respectively the maximum transmission capacity of line k and the power transmission value at the previous moment.

[0085] Here, the role of the flexible regulation accommodation capacity of the line is: to ensure that at any given moment, as the transmission channel of flexible resources, the carrying capacity of the line and the margin of flexible resources together constitute the limiting conditions, so as to match the flexible supply and demand on the spatial scale and ensure the stable operation of the power system.

[0086] In the embodiment of the present application, S4, establish an evaluation index system for the response potential of high-energy-consuming loads. It should be understood that in order to accurately evaluate the flexible support of high-energy-consuming loads on the demand side for the power system, effectively match the random fluctuation characteristics of flexible resources, new energy, and loads, so as to achieve the safe and stable operation of the power system. Further establish an evaluation index system for the response potential of high-energy-consuming loads. This index system can reflect the flexible state of the power system, and the typical operating scenarios can represent the flexibility of the operating scenarios of the power system throughout the cycle, thereby shortening the flexible evaluation time.

[0087] In particular, the evaluation index system for the response potential of high-energy-consuming loads specifically includes the following indexes:

[0088] 1) Peak shaving rate

[0089]

[0090] In the formula, P p and P p ' are the peak values of the system load before and after the response of the high-energy-consuming load respectively;

[0091] 2) Valley filling rate

[0092]

[0093] In the formula, P v and P v ' are the valley values of the system load before and after the response of the high-energy-consuming load respectively;

[0094] 3) System upward flexibility shortage

[0095]

[0096] In the formula, F defc,+ is the system upward flexibility shortage; is the upward flexibility deficit of line k at time t;

[0097] 4) System downward flexibility shortage

[0098]

[0099] In the formula, F defc,- is the system downward flexibility shortage; is the downward flexibility deficit of line k at time t.

[0100] These indicators can comprehensively reflect the flexibility requirements and supply capabilities of the power system. Among them, the peak shaving rate and the valley filling rate respectively represent the regulation capabilities of the system during peak and valley periods, and the system upward flexibility shortage and the system downward flexibility shortage reflect the flexibility gaps of the system when increasing or decreasing output. These indicators together constitute a comprehensive evaluation system, which helps the power system operator to comprehensively understand the flexibility status of the system.

[0101] In the embodiment of the present application, in S5, based on the time-series production operation simulation, the system flexibility shortage index is used as an optimization variable to construct a high-energy load response potential evaluation model considering the spatio-temporal balance of flexibility supply and demand. It should be understood that the operation mode of the power system has changed from the traditional unidirectional mode of power supply and load to the bidirectional mode of coordinated interaction among power supply, power grid, load and energy storage, which requires the power grid dispatching to utilize various demand-side resources to achieve "flexibility balance" and meet the flexibility ramp-up demand in each period. Therefore, the time-series simulation is used to evaluate the peak-shaving capacity of the high-energy load, and its flexibility supply potential is evaluated on the basis of peak-shaving. That is, based on the time-series production operation simulation, the system flexibility shortage index is used as an optimization variable to construct a high-energy load response potential evaluation model considering the spatio-temporal balance of flexibility supply and demand, and the flexible supply potential of the high-energy load is evaluated on the basis of peak-shaving operation.

[0102] Specifically, the model takes minimizing the total operation cost C as the objective function, including the start-stop and fuel consumption cost C th of thermal power units, the penalty cost C p for wind curtailment and load shedding, and the penalty cost C d for flexibility deficit. The specific formula is: minC = C th + C p + C d .

[0103] Among them, the start-stop and fuel consumption cost C th of thermal power units is expressed as:

[0104]

[0105] In the formula, a m , b m and c m are the fuel consumption coefficients of thermal power units, and are the start-stop costs of thermal power units respectively, and v g,m,t and h g,m,t are the start-stop variables of thermal power units respectively.

[0106] Among them, the penalty cost C p for wind curtailment and load shedding is expressed as:

[0107]

[0108] In the formula, C w , C L are the penalty costs for wind curtailment and load shedding respectively, N L is the number of load nodes, and ΔP w,t and ΔP L,v,t are the wind curtailment power of the system and the load shedding power of the conventional load v at time t respectively.

[0109] Among them, the flexibility deficit penalty cost C d is expressed as:

[0110]

[0111] In the formula, C f is the line flexibility deficit penalty cost at time t.

[0112] In addition, in order to ensure the safe and stable operation of the power system and at the same time encourage the system to improve flexibility, the model also needs to meet the following constraints:

[0113] 1) Power balance constraint

[0114]

[0115] In the formula, P w,t is the wind power output at time t; P L,v,t is the power of the conventional load v at time t.

[0116] 2) Thermal power unit constraints

[0117] The thermal power unit constraints include the following constraints: (a) unit output constraint, (b) unit ramp rate constraint, (c) unit start-stop constraint, (d) unit minimum start-stop time constraint;

[0118] (a)

[0119] (b)

[0120] (c)

[0121] (d)

[0122] In the formula, and are the minimum continuous on / off times of the thermal power unit m respectively.

[0123] 3) Line transmission constraints

[0124] The line transmission constraints based on DC power flow are as follows:

[0125]

[0126] In the formula, and are the power transfer distribution factors of the thermal power unit, wind farm, conventional load, electrolytic aluminum load and electric arc furnace load to line k respectively.

[0127] 4) Flexible regulation constraints for high-energy-consuming loads

[0128] The flexible regulation of the electrolytic aluminum load needs to satisfy the power-current coupling constraint, the power-temperature coupling constraint, and the power adjustment time constraint in step S1. The flexible regulation of the electric arc furnace load needs to satisfy the power regulation constraint, the production status constraint, and the production status constraint in step S1.

[0129] 5) Abandoned wind and load shedding constraints

[0130]

[0131] In the formula, and are the predicted powers of wind power and conventional load respectively.

[0132] 6) Temporal and spatial balance constraints of flexibility supply and demand

[0133]

[0134] In summary, the high-energy-consuming load flexibility potential evaluation method according to the embodiments of the present application is clarified, which includes: constructing a refined model for the flexibility supply of high-energy-consuming loads; constructing a flexibility supply and demand transmission model and the temporal and spatial balance conditions of system flexibility supply and demand based on the multi-path resource transmission mechanism between nodes; establishing an evaluation index system for the response potential of high-energy-consuming loads; and constructing an evaluation model for the response potential of high-energy-consuming loads considering the temporal and spatial balance of flexibility supply and demand by taking the system flexibility deficiency index as an optimization variable based on the time-series production operation simulation. The present application comprehensively considers the regulation characteristics of high-energy-consuming loads, the supply and demand transmission process of the power grid, and the temporal and spatial distribution characteristics, so as to accurately evaluate the support potential of high-energy-consuming loads for the flexibility of the power system and optimize the operation and dispatching of the power system.

[0135] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit of the technical solutions of the present invention.

Claims

1. A method for evaluating the potential of high energy load flexibility, characterized in that: include: S1. Constructing a high-energy load flexibility supply refined model, wherein the high-energy load flexibility supply refined model includes an electrolytic aluminum load flexibility supply model based on power-current-temperature coupling and an arc furnace load flexibility supply model based on the production process; S2. Construct a quantitative model of grid node flexibility supply and demand; S3. Based on the multi-path resource transmission mechanism between nodes, a flexibility supply and demand transmission model and the spatiotemporal balance conditions of system flexibility supply and demand are constructed; S4. Establish a high-energy load response potential assessment indicator system; S5. Based on the simulation of sequential production operation, the system flexibility deficiency index is used as the optimization variable to construct a high-energy load response potential assessment model that considers the spatiotemporal balance of flexible supply and demand; In S3, the flexibility supply and demand transmission model is: In the formula, and are the allocation of node flexibility supply / demand on line k at time t, and are the flexible supply / demand transmission volume of line k at time t after regularization, and are the flexibility resource / demand transfer distribution factors of the flexibility supply / demand change at node i to line k, and are the upward and downward flexibility supply of node i at time t, and are the upward and downward flexibility requirements of node i at time t, respectively; In S3, the spatiotemporal balance condition of system flexibility supply and demand is: In the formula, is the flexibility adjustment capacity of line k at time t, and P k,t-1 are the maximum transmission capacity of line k and the power transmission value at the previous moment respectively.

2. The high energy load flexibility potential assessment method according to claim 1 is characterized in that: In S1, the aluminum electrolytic load flexibility supply model based on power-current-temperature coupling satisfies the following constraints: 1) Power-current coupling constraints Where P AL,t is the power of the electrolytic aluminum load at time t, P AL,max and P AL,min are the upper and lower limits of the inherent power of the electrolytic aluminum load at time t, I AL,t is the series current of the electrolytic aluminum load at time t, I AL,max and I AL,min are the upper and lower limits of the inherent current of the electrolytic aluminum load at time t, R m is the equivalent resistance, E m is the equivalent back electromotive force; 2) Power-Temperature Coupling Constraints Where, T AL,t is the production temperature of electrolytic aluminum load at time t, T AL,min and T AL,max are the upper and lower limits of the inherent temperature of the electrolytic aluminum load at time t, c AL is the specific heat capacity coefficient of the electrolyte, m AL is the mass of the electrolyte; 3) Power adjustment time constraints In the formula, x AL,t is the power adjustment flag of the electrolytic aluminum load at time t. When the value is 1, it means that the power is adjusted, and when the value is 0, it means that the power remains unchanged. T is the scheduling period, T on The minimum time to maintain the electrolytic aluminum load power unchanged, M is a constant.

3. The high energy load flexibility potential assessment method according to claim 2 is characterized in that: In S1, the electrolytic aluminum load flexibility supply model based on power-current-temperature coupling is expressed as follows: In the formula, and They are the upward and downward flexibility supply capabilities of the electrolytic aluminum load at time t respectively.

4. The high energy load flexibility potential assessment method according to claim 3 is characterized in that: In S1, the arc furnace load flexibility supply model based on the production process satisfies the following constraints: 1) Power regulation constraints In the formula, and are the maximum up and down power when the nth arc furnace is in production state at time t, and They are the upper and lower limits of the inherent power when the nth electric arc furnace is in production state at time t; 2) Production status constraints In the formula, The time required to produce one heat in an electric arc furnace; 3) Oven time constraints In the formula, It is the maximum baking time of electric arc furnace.

5. The high energy load flexibility potential assessment method according to claim 4 is characterized in that: In S1, the arc furnace load flexibility supply model based on the production process is: In the formula, and are the total upward and downward flexibility supply capacity of the arc furnace load at time t, and They are the upward and downward climbing rate limits of the nth arc furnace at time t, and Δt is the interval between adjacent moments.

6. The high energy load flexibility potential assessment method according to claim 5 is characterized in that: In S2, the flexibility demand model of each node in the system is: In the formula, and are the upward and downward flexibility requirements of node i at time t, and are the maximum and minimum net load of node i at time t respectively.

7. The high energy load flexibility potential assessment method according to claim 6, characterized in that: In S2, the flexibility supply model of each node in the system is: Where P g,m,t , and are the output and upper and lower limits of thermal power unit m at time t, and are the upward and downward climbing capabilities of thermal power unit m, K g,m,i , K AL,i and K EAF,i They are the power flow distribution coefficients of thermal power units, electrolytic aluminum load and arc furnace load respectively.

8. The high energy load flexibility potential assessment method according to claim 7, characterized in that: In S4, the response potential evaluation index system includes the following indicators: 1) Peak shaving rate Where P p and P' p They are the peak values ​​of system load before and after high energy load response; 2) Valley filling rate Where P v and P' v They are the system load valley values ​​before and after the high energy load response; 3) Insufficient upward flexibility of the system In the formula, F defc,+ The system lacks upward flexibility; is the upward flexibility deficit of line k at time t; 4) Insufficient downward flexibility of the system In the formula, F defc,- The system lacks downward flexibility; is the downward flexibility shortfall of line k at time t.

9. The high energy load flexibility potential assessment method according to claim 8, characterized in that: In S5, the model aims to minimize the total operating cost C, including the start-up and shutdown costs of thermal power units and the fuel consumption cost C th , the penalty cost of wind curtailment and load shedding C p and the flexibility deficiency penalty cost C d .

10. The high energy load flexibility potential assessment method according to claim 9, characterized in that: In S5, the constraints that the model needs to meet include: power balance constraints, thermal power unit constraints, line transmission constraints, high-energy load flexible adjustment constraints, wind abandonment and load shedding constraints, and flexible supply and demand spatiotemporal balance constraints.

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