A credit evaluation-based incentive method for industrial load demand response

Abstract

The present invention discloses an industrial load demand response incentive method based on credit evaluation, including: combining the time reliability index of each industrial load regulation with the industrial load subscription performance index to construct the credit evaluation index of each industrial load; dividing all industrial load demand responses into day-ahead demand response, intraday demand response and real-time demand response according to the operation time; establishing a day-ahead demand response incentive decision model according to the day-ahead demand response, and determining the optimal day-ahead demand response capacity and compensation amount corresponding to the industrial load through optimization solution; establishing an intraday demand response incentive decision model according to the intraday demand response, and determining the optimal intraday demand response capacity and compensation amount corresponding to the industrial load through optimization solution; establishing a real-time response incentive decision model for the real-time demand response, and determining the compensation amount under the corresponding industrial load. The present invention dynamically adjusts the credit score and incentive measures, which can better tap the demand response potential of industrial loads.

Description

Technical Field

[0001] The present invention belongs to the technical field of power demand response, and in particular, relates to an industrial load demand response incentive method based on credit evaluation. Background Art

[0002] Promoting the grid connection and consumption of a high proportion of renewable energy has become a top priority for my country to build a new power system. However, the randomness and uncertainty of new energy output bring challenges to the operation and control of the power system. Therefore, it is urgent to tap adjustable resources from the demand side to improve the flexibility of the power system. At present, there have been a lot of research on demand response (DR) for residential loads and commercial loads. As a high-power consumption industry, industry has great potential for demand response. However, common DR incentive mechanisms such as real-time pricing RTP, time-varying electricity price TOU and reward-based incentive schemes often lead to insufficient participation of industrial users due to complex electricity price signals or operational complexity. In addition, these incentives are difficult to effectively control users' default behavior, increasing the risk of system operation. Summary of the invention

[0003] In response to the problems existing in the prior art, the present invention provides an industrial load demand response incentive method based on credit evaluation. By continuously monitoring and evaluating users' demand response behaviors and dynamically adjusting credit scores and incentives, the demand response potential of industrial loads can be better tapped, thereby improving the supply and demand balancing ability of the power grid, alleviating peak load pressure, and promoting the stable operation and reliability of the power system.

[0004] To achieve the above technical objectives, the present invention adopts the following technical solution: an industrial load demand response incentive method based on credit evaluation, specifically comprising the following steps:

[0005] Step 1: Combine the reliability index of each industrial load control time with the industrial load subscription performance index to construct the credit evaluation index of each industrial load;

[0006] Step 2: All industrial load demand responses are divided into day-ahead demand response, intraday demand response and real-time demand response according to the operation time;

[0007] Step 3: Based on the day-ahead demand response, establish a day-ahead demand response incentive decision model with the upper layer maximizing the benefits of both supply and demand parties and the lower layer maximizing the overall response credit of industrial loads. Determine the optimal day-ahead demand response capacity and compensation amount corresponding to the industrial load through optimization solution;

[0008] Step 4: Based on the intraday demand response, establish an intraday demand response incentive decision model with the upper layer aiming at minimizing the grid regulation cost and the lower layer aiming at maximizing the overall response credit of the industrial load, and determine the optimal intraday demand response capacity and compensation amount corresponding to the industrial load through optimization solution;

[0009] Step 5: Establish a real-time demand response incentive decision model with the goal of minimizing the economic cost of interrupted loads, and determine the compensation amount under the corresponding industrial load.

[0010] Furthermore, step 1 includes the following sub-steps:

[0011] Step 1.1, determine the target industrial load response capacity of each industrial load within the evaluation period, and calculate the average industrial load response capacity according to the actual industrial load response capacity of each industrial load within the evaluation period. When the average industrial load response capacity is less than the target industrial load response capacity, the ratio of the average industrial load response capacity to the target industrial load response capacity is used as the load subscription performance indicator; otherwise, the ratio of the target industrial load response capacity to the average industrial load response capacity is used as the load subscription performance indicator;

[0012] Step 1.2, the ratio of the time period during which the deviation between the actual industrial load response capacity and the target industrial load response capacity of each industrial load within the evaluation period is controlled within 20% to the evaluation period is used as the control time reliability index;

[0013] Step 1.3: The product of the industrial load subscription performance index and the regulation time reliability index of each industrial load in the evaluation period is used as the corresponding industrial load credit evaluation base value, combined with the corresponding industrial load credit evaluation value of the previous evaluation period, to obtain the corresponding industrial load credit evaluation index in the current evaluation period.

[0014] Furthermore, the process of obtaining the corresponding industrial load credit evaluation index in the current evaluation cycle in step 1.3 is specifically as follows:

[0015]

[0016] in, represents the credit evaluation index value of industrial load i in the nth evaluation cycle, represents the credit evaluation base value of industrial load i in the nth evaluation period, θ1 represents The weight coefficient of .

[0017] Furthermore, step 3 includes the following sub-steps:

[0018] Step 3.1: Incorporate the corresponding industrial load incentives and demand response costs into the day-ahead control operation cost objective function established by the upper layer according to the day-ahead demand response. Determine the industrial load demand response capacity and unit incentive price under the conditions of maximum benefits for both supply and demand parties through active power balance constraints, upper and lower limits of thermal power unit output constraints, thermal power unit ramp constraints, thermal power unit minimum start-up and shutdown time constraints, day-ahead demand response resource constraints, cement enterprise storage constraints, electrolytic aluminum enterprise heat balance constraints, and wind, solar, and load abandonment constraints.

[0019] Step 3.2, combine the industrial load demand response capacity with the corresponding industrial load credit evaluation index to establish the lower-level industrial load overall response credit objective function, set the industrial load demand response monotonic change constraint, the optimal industrial load demand response quantity constraint, the total industrial load demand response quantity constraint and the total compensation amount constraint, substitute the industrial load demand response capacity and unit incentive price in step 3.1 into the total industrial load demand response quantity constraint and the total compensation amount constraint, update the industrial load demand response capacity and unit incentive price, and determine the industrial load demand response capacity and unit incentive price under the condition of the highest industrial load overall response credit;

[0020] Step 3.3: Calculate the total incentive price based on the industrial load demand response capacity and unit incentive price under the highest overall industrial load response credit condition, and update the total incentive price through the reward and punishment coefficient. The sum of the updated total incentive price and the demand response cost of the industrial load on the day before is used as the compensation cost of the industrial load on the day before.

[0021] Furthermore, the day-ahead control operation cost objective function established in the upper layer in step 3.1 is:

[0022]

[0023] in, is the sum of the operating costs of all scenarios of day-ahead control, N s is the number of scenes, s is N s The index of N GN is the total amount of thermal power units, g is N GN The index of N T is the number of control periods, t is N T The index of ; π s is the probability of the sth scenario occurring, is the power generation cost of thermal power units, is the output power of the g-th thermal power plant in the s-th scenario during the t-th period; U g,t , D g,t are the start-up and shutdown costs of the g-th thermal power plant in period t, N AN is the number of cement enterprises, a is N AN The index of is the unit incentive price of the a-th cement load in period t, is the labor cost of the a-th cement load in period t; N BN is the number of electrolytic aluminum enterprises, b is N BN The index of is the unit incentive price of the bth electrolytic aluminum load in period t, is the labor cost of the bth electrolytic aluminum load in period t; d t is the electricity price in period t; The power of a single crusher of the cement company participating in the demand response is The number of crushers increased and decreased by the a-th cement enterprise in period t respectively; are the power increase and decrease of the b-th electrolytic aluminum enterprise in period t, respectively, Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are wind power abandonment, solar power abandonment and load loss power under scenario s in period t respectively;

[0024] The overall response credit objective function of the lower-level industrial load in step 3.2 is:

[0025]

[0026] in, The overall response credit of industrial load for day-ahead demand, They are the credit evaluation indicators of the ath cement load and the bth electrolytic aluminum load respectively; is the number of crushers to be increased or decreased for the a-th cement load in period t after the lower-level scheduling. It is the demand response of the bth electrolytic aluminum load in period t after lower-level scheduling.

[0027] Furthermore, the process of updating the total incentive price through the reward and punishment coefficient in step 3.3 is:

[0028] i. The power company determines the power shortage or surplus based on the short-term peak load predicted on the day before, classifies the day-ahead demand response of industrial loads according to the proportion of the power shortage or surplus to the total power generation capacity, and determines the reward and punishment coefficients for different levels;

[0029] ii. Determine whether the credit evaluation index of the corresponding industrial load is less than 0.8. If so, the subsidy amount is 0; otherwise, update the total incentive price according to the credit evaluation index and reward and punishment coefficient of the corresponding industrial load:

[0030]

[0031] Among them, M is the updated total incentive price, μ is the reward and punishment coefficient, and M′ is the total incentive price. is the unit incentive price of the a-th cement load in period t after lower-level scheduling, It is the unit incentive price of the bth electrolytic aluminum load in time period t after lower-level scheduling.

[0032] Furthermore, step 4 includes the following sub-steps:

[0033] Step 4.1: The industrial load corresponding to the daily demand response determines the maximum limit of the daily demand response capacity and the market bidding price according to its own situation, and the power grid company determines the compensation unit price of the daily demand response according to the market bidding results;

[0034] Step 4.2: Combine market bidding to establish the objective function of the daily demand response regulation and control operation cost. Set the energy storage load constraint and the captive power plant load constraint according to the maximum limit of the daily demand response capacity, and set the power balance constraint, wind curtailment, solar and load loss constraints to determine the daily demand response capacity with the minimum grid regulation and control operation cost.

[0035] Step 4.3, combine the intraday demand response capacity with the corresponding industrial load credit evaluation index to establish the lower-level industrial load overall response credit objective function, set the intraday total demand response quantity constraint, substitute the intraday demand response capacity in step 4.2 into the intraday total demand response quantity constraint, and solve the optimal intraday demand response capacity under the highest industrial load overall response credit;

[0036] Step 4.4: Calculate the compensation price of the intraday demand response capacity based on the optimal intraday demand response capacity and the market bidding.

[0037] Furthermore, the intraday demand response regulation operation cost objective function established in step 4.2 is:

[0038]

[0039] in, is the sum of the daily demand response regulation and operation costs, V price is the market price of the day, N ess is the amount of energy storage on the user side, i is N ess The index of are the load increase and decrease responses of the energy storage load at the i-th user side, N cpp is the number of self-provided power plant loads, c is N cpp The index of are the load increase and load decrease responses of the cth self-provided power plant respectively; λ Wcut , PVcut and λ Lcutare the penalty prices for wind curtailment, solar curtailment and load loss, They are wind power abandonment, solar power abandonment and load loss power under scenario s in period t respectively;

[0040] The overall response credit objective function of industrial load in step 4.3 is:

[0041]

[0042] in, is the overall response credit objective function of industrial load, is the credit evaluation index of the energy storage load at the i-th user side, They are respectively the load increase response and load reduction response of the i-th user-side energy storage load in the lower-level scheduling; is the credit evaluation index of the load of the i-th self-provided power plant, They are respectively the load increase response and load reduction response of the cth captive power plant in the lower-level dispatching.

[0043] Furthermore, the real-time response incentive decision model is:

[0044]

[0045] in, is the economic cost of real-time demand response in the current period, Nall is the sum of all industrial users that can participate in real-time demand response, is the power interruption action of the i-th industrial load, represents the power supply status of the i-th industrial load, The cost incurred when the power supply to the i-th industrial load is interrupted, is the cost incurred during the power outage of the i-th industrial load, λ Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are respectively the wind power abandoned, solar power abandoned and load loss power under scenario s in period t.

[0046] Furthermore, the calculation process of the compensation amount corresponding to the industrial load in step 5 is:

[0047]

[0048] Among them, N T is the number of control periods, t is N T The index of is the unit incentive price for real-time demand response, is the maximum unit incentive price for day-ahead demand response, is the highest unit incentive price for demand response within the day, is the power of the i-th industrial load under normal power supply conditions in period t.

[0049] Compared with the prior art, the present invention has the following beneficial effects: the industrial load demand response incentive method based on credit evaluation of the present invention dynamically adjusts the credit evaluation indicators and incentive measures by continuously monitoring and evaluating the demand response behavior of industrial loads. This method can not only effectively improve the participation of industrial loads and reduce default behaviors, but also ensure the fairness and effectiveness of demand response incentives. Through this credit evaluation-based incentive method, the demand response potential of industrial loads can be better tapped, thereby improving the supply and demand balancing ability of the power grid, alleviating peak load pressure, and promoting the stable operation and reliability of the power system. This not only provides new impetus and direction for industrial load demand response, but also provides a reference for the modern management of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flow chart of the industrial load demand response incentive method based on credit evaluation of the present invention;

[0051] Figure 2 is a schematic diagram of the day-ahead demand response incentive decision model;

[0052] Figure 3 It is a schematic diagram of the intraday demand response incentive decision model;

[0053] Figure 4 is a schematic diagram of a real-time demand response incentive decision model;

[0054] Figure 5 It is a schematic diagram of the improved IEEE-30 node system;

[0055] Figure 6 is a schematic diagram of the demand response volume and unit incentive price of electrolytic aluminum enterprises, where: Figure 6 (a) is a schematic diagram of the demand response of electrolytic aluminum enterprises. Figure 6 (b) is a schematic diagram of the unit incentive price of electrolytic aluminum enterprises;

[0056] Figure 7 This is a schematic diagram of the electrolytic aluminum enterprise 1’s own benefits under different default rates. DETAILED DESCRIPTION

[0057] The technical solution of the present invention is further explained below in conjunction with the accompanying drawings.

[0058] like Figure 1 The flowchart of the industrial load demand response incentive method based on credit evaluation of the present invention is as follows:

[0059] Step 1: Combining the time reliability index of each industrial load with the industrial load subscription performance index to construct the credit evaluation index of each industrial load can more comprehensively reflect the credit status of the industrial load; specifically, the following sub-steps are included:

[0060] Step 1.1, industrial loads are adjusted accordingly according to the demand response instructions issued by the power grid company. By comparing the real-time data collected by smart meters with the baseline load, the actual demand response of users can be accurately calculated. The completion rate of demand response includes two dimensions: capacity and time to evaluate the user's response credit. Among them, the capacity dimension is measured by the improved subscription performance index, and the time dimension is described by the reliability index of the regulation time. The traditional subscription performance index is the ratio of the average response of industrial loads during the evaluation period to the target response. This index directly reflects the relationship between the actual response and the target response, and can effectively evaluate the response behavior of different types of users. The higher the value of this index, the better the response effect of industrial loads, but it may also cause additional burden on the power system due to excessive response. Therefore, the present invention determines the target industrial load response capacity of each industrial load within the evaluation period, and obtains the average industrial load response capacity according to the industrial actual load response capacity of each industrial load within the evaluation period. When the average industrial load response capacity is less than the target industrial load response capacity, the ratio of the average industrial load response capacity to the target industrial load response capacity is used as the industrial load subscription performance index; otherwise, the ratio of the target industrial load response capacity to the average industrial load response capacity is used as the industrial load subscription performance index:

[0061]

[0062] Among them, λ i SPI is the improved performance index of industrial load i, P i avg is the average response of industrial load i during the evaluation period, P i sub is the target response of industrial load i within the evaluation, is the response of industrial load i in period t, which can be either load increase or load reduction. The value of the improved subscription performance index is limited to [0,1].

[0063] Step 1.2: The time period in which the deviation between the actual industrial load response capacity and the target industrial load response capacity of each industrial load within the evaluation period is controlled within 20% is considered qualified. The more qualified response time periods there are, the better the response effect of the industrial load is, and the higher the credibility of the industrial load is. Therefore, the ratio of the qualified time period to the evaluation period is used as the control time reliability index:

[0064]

[0065] in, is the reliability index of the regulation time of industrial load i, is the specified response of industrial load i in period t. The value range of the control time reliability index is also between [0,1]. When the value is 1, it means that the industrial load meets the requirements in all periods of the evaluation period. When the value is 0, it means that the industrial load fails to meet the requirements in all periods of the control period.

[0066] Step 1.3: The product of the industrial load subscription performance index and the regulation time reliability index of each industrial load in the evaluation period is used as the basic value of the corresponding industrial load credit evaluation. Combined with the corresponding industrial load credit evaluation value of the previous evaluation period, the corresponding industrial load credit evaluation index in the current evaluation period is obtained to fully demonstrate the consistency and standardization of the industrial load response.

[0067] The corresponding industrial load credit evaluation index in the current evaluation cycle in the present invention is:

[0068]

[0069] in, represents the credit evaluation index value of industrial load i in the nth evaluation cycle, represents the credit evaluation base value of industrial load i in the nth evaluation period, θ1 represents The weight coefficient is set and the evaluation period of all industrial loads is set to one day.

[0070] Step 2: Divide all industrial load demand responses into day-ahead demand response, intraday demand response, and real-time demand response according to the operating time. The industrial load types participating in the day-ahead demand response are transferable loads, including cement enterprises and electrolytic aluminum enterprises. Such loads can transfer electricity consumption from one time period to another, and the total electricity consumption remains unchanged during the regulation cycle, with little impact on overall production; those participating in intraday demand response are mainly enterprises with energy storage facilities or self-provided power generation capabilities, including energy storage loads and self-provided power plant loads; those participating in real-time demand response are mainly industrial loads with low economic cost of interruption.

[0071] Step 3. Based on the day-ahead demand response, establish a day-ahead demand response incentive decision model with the upper layer maximizing the interests of both supply and demand parties and the lower layer maximizing the overall response credit of industrial loads as the goal. Determine the optimal day-ahead demand response capacity and compensation amount corresponding to the industrial load through optimization and solution. By establishing a decision model that maximizes the interests of both supply and demand parties, it can ensure that the interests of power supply companies and power users are reasonably protected. With the highest overall response credit of industrial loads as the goal, power users can be encouraged to actively participate in demand response and improve the actual implementation effect of demand response. By optimizing and solving the day-ahead demand response incentive decision model, power supply companies can be helped to manage industrial loads more effectively, avoid contradictions between supply and demand when power supply is tight, and improve the stability and security of power grid operation. Figure 2 , specifically including the following sub-steps:

[0072] Step 3.1: Incorporate the corresponding industrial load incentives and demand response costs into the day-ahead control operation cost objective function established by the upper layer according to the day-ahead demand response. Determine the industrial load demand response capacity and unit incentive price under the conditions of maximum benefits for both supply and demand parties through active power balance constraints, upper and lower limits of thermal power unit output constraints, thermal power unit ramp constraints, thermal power unit minimum start-up and shutdown time constraints, day-ahead demand response resource constraints, cement enterprise storage constraints, electrolytic aluminum enterprise heat balance constraints, and wind, solar, and load abandonment constraints.

[0073] The day-ahead control operation cost objective function established by the upper layer is:

[0074]

[0075] in, is the sum of the operating costs of all scenarios of day-ahead control, N s is the number of scenes, s is N s The index of N GN is the total amount of thermal power units, g is N GN The index of N T is the number of control periods, t is N T The index of ; π s is the probability of the sth scenario occurring, is the power generation cost of the thermal power unit, is the output power of the g-th thermal power plant in the s-th scenario during the t-th period; U g,t , D g,t are the start-up and shutdown costs of the g-th thermal power plant in period t, N AN is the number of cement enterprises, a is N AN The index of is the unit incentive price of the a-th cement load in period t, is the labor cost of the a-th cement load in period t; N BNis the number of electrolytic aluminum enterprises, b is N BN The index of is the unit incentive price of the bth electrolytic aluminum load in period t, is the labor cost of the bth electrolytic aluminum load in period t; d t is the electricity price in period t; The power of a single crusher of the cement company participating in the demand response is The number of crushers increased and decreased by the a-th cement enterprise in period t respectively; are the power increase and decrease of the b-th electrolytic aluminum enterprise in period t, respectively, Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are wind power abandonment, solar power abandonment and load loss power under scenario s in period t respectively;

[0076] Constraints:

[0077] (1) Active power balance constraint:

[0078]

[0079] In the formula, is the value of “new energy output-load” in period t under the sth scenario.

[0080] (2) Constraints on upper and lower limits of thermal power unit output:

[0081]

[0082] In the formula, They represent the maximum and minimum output of the g-th thermal power unit, Indicates the on / off status of the g-th thermal power unit in period t, 1 means on and 0 means off.

[0083] (3) Climbing constraints of thermal power units:

[0084]

[0085] In the formula, and They respectively represent the upper and lower limits of the climbing rate of the g-th thermal power unit.

[0086] (4) Minimum start-up and shutdown time constraints for thermal power units:

[0087] Thermal power units cannot be started and stopped frequently during operation and need to be kept for a certain period of time:

[0088]

[0089] In the formula, and are the minimum startup and shutdown time of the g-th thermal power unit respectively.

[0090] (5) Day-ahead demand response resource constraints:

[0091]

[0092] In the formula, and The maximum number of crushers that can be increased or decreased by the a-th cement company in response to demand is: and are the maximum power increased and decreased by the bth aluminum smelter participating in demand response.

[0093] (6) Storage constraints of cement enterprises:

[0094] Since the storage capacity of raw material particles of each cement manufacturer is limited, it is necessary to constrain the storage of cement. The raw material storage capacity of a cement enterprise can be equivalent to MW·h, so the constraint for each time period can be expressed as:

[0095]

[0096] In the formula, represents the raw material storage capacity of the a-th cement company in period t; in addition, in order to reduce the impact of demand response on the production of cement companies, the total capacity of raw material particle storage increase and decrease should be equal during the entire day-ahead regulation cycle. The specific constraints are as follows:

[0097]

[0098] (7) Thermal balance constraints of electrolytic aluminum enterprises:

[0099] Since the electrolytic cell needs to maintain thermal balance during the production process to ensure production quality, the capacity increase and decrease of the electrolytic cell are set equal during the system control cycle. The specific expression is as follows:

[0100]

[0101] (8) Wind power curtailment, solar power curtailment and load loss constraints:

[0102]

[0103] Where P t Wforecast , P t Pforecast and P t Lforecast are the day-ahead forecast values ​​of wind, solar output and load power in period t respectively.

[0104] Step 3.2, combine the industrial load demand response capacity with the corresponding industrial load credit evaluation index to establish the lower-level industrial load overall response credit objective function, set the industrial load demand response monotonic change constraint, the optimal industrial load demand response quantity constraint, the total industrial load demand response quantity constraint and the total compensation amount constraint, substitute the industrial load demand response capacity and unit incentive price in step 3.1 into the total industrial load demand response quantity constraint and the total compensation amount constraint, update the industrial load demand response capacity and unit incentive price, and determine the industrial load demand response capacity and unit incentive price under the condition of the highest industrial load overall response credit;

[0105] The overall response credit objective function of the lower industrial load is:

[0106]

[0107] in, The overall response credit of industrial load for day-ahead demand, They are the credit evaluation indicators of the ath cement load and the bth electrolytic aluminum load respectively; is the number of crushers to be increased or decreased for the a-th cement load in period t after the lower-level scheduling. It is the demand response of the bth electrolytic aluminum load in period t after lower-level scheduling.

[0108] In order to ensure that only load increase or load reduction response is performed in each period during the dispatch process, the load increase and decrease flag is introduced into the constraint conditions of the demand response resource. The specific expression is as follows:

[0109]

[0110]

[0111] In the formula, Respectively represent the signs of the increase of the a-th cement load and the b-th electrolytic aluminum load in the t period. When the value is 1, it means the load is increased, and when the value is 0, it means no load is increased; They respectively represent the signs of load reduction of the a-th cement load and the b-th electrolytic aluminum load in time period t. When the value is 1, it means load reduction is carried out, and when the value is 0, it means no load reduction is carried out.

[0112] The constraints of the optimal response are:

[0113]

[0114] In the formula, They represent the absolute value expressions of the optimal responses of cement and electrolytic aluminum loads in time period t respectively.

[0115] In order to make the total demand response of each type of load in each period equal to the upper-level optimization and ensure the source-load balance of the system, it is also necessary to add a total response constraint, which is specifically expressed as follows:

[0116]

[0117] In order to make the total compensation amount of each type of load in the scheduling optimization cycle equal to the upper-level optimization and ensure the economy of system scheduling, it is necessary to add a total compensation amount constraint, which is specifically expressed as follows:

[0118]

[0119] C AC =C AC′

[0120]

[0121] C BC =C BC′

[0122] In the formula, C AC , C AC′ are the total compensation amount of cement load after upper and lower layer optimization, C BC , C BC′ The total compensation amount for electrolytic aluminum load after upper and lower layer optimization respectively.

[0123] Finally, after optimizing the lower-level model, the demand response variables and incentive prices of cement load are obtained. Demand response variables and incentive prices for aluminum smelting loads

[0124] Step 3.3: Calculate the total incentive price based on the industrial load demand response capacity and unit incentive price under the condition of the highest overall industrial load response credit, and update the total incentive price through the reward and penalty coefficient. The sum of the updated total incentive price and the demand response cost of the industrial load on the day before is used as the compensation cost of the industrial load on the day before. Specifically,

[0125] i. The power company determines the power shortage or surplus based on the short-term peak load predicted on the day before, divides the day-ahead demand response of industrial load into different levels according to the proportion of the power shortage or surplus to the total power generation capacity, and determines the reward and punishment coefficients under different levels, as shown in Table 1;

[0126] Table 1: Relationship between response level and reward and punishment coefficient

[0127] Response Level Power generation deficit / surplus Reward and punishment coefficient μ A 10% or more 1.5 B 5% to 10% 1.2 C Less than 5% 1

[0128] ii. Determine whether the credit evaluation index of the corresponding industrial load is less than 0.8. If so, the subsidy amount is 0; otherwise, update the total incentive price according to the credit evaluation index and reward and punishment coefficient of the corresponding industrial load:

[0129]

[0130] Among them, M is the updated total incentive price, μ is the reward and punishment coefficient, and M′ is the total incentive price. is the unit incentive price of the a-th cement load in period t after lower-level scheduling, It is the unit incentive price of the bth electrolytic aluminum load in time period t after lower-level scheduling.

[0131] The demand response cost of industrial load on the day before includes: the change of electricity cost caused by the difference of time-of-use electricity price and the change of labor cost caused by the difference of labor cost in different time periods. Therefore, the demand response cost of industrial load on the day before is as follows:

[0132]

[0133] In the formula, is the demand response cost of the ith load shift, d t is the electricity price in period t, l i,t is the equivalent labor cost of the i-th transfer load in different periods, in RMB / MWh, that is, the labor cost required for the enterprise to increase 1MWh. and They are load increase and load reduction in demand response respectively.

[0134] Step 4. Based on the intraday demand response, establish an intraday demand response incentive decision model with the upper layer aiming at minimizing the grid regulation cost and the lower layer aiming at maximizing the overall response credit of industrial loads. Through optimization and solution, determine the optimal intraday demand response capacity and compensation amount corresponding to the industrial load. With the goal of minimizing the grid regulation cost, the grid regulation cost in the demand response process can be effectively reduced. With the goal of maximizing the overall response credit of industrial loads, it can ensure that the companies participating in the demand response have a good credit record and execution ability, thereby improving the actual execution effect of the demand response and ensuring the accuracy and reliability of grid regulation. The intraday demand response incentive decision model focuses on short-term load regulation and can quickly respond to changes in the power market and grid load, improving the flexibility and adaptability of grid regulation. Figure 3 , specifically including the following sub-steps:

[0135] Step 4.1. Users can register on the power trading platform and apply to become the emergency demand response resource of the power grid. The power grid company will evaluate the users who apply and install automatic control devices on the emergency response resources of these users after confirming that they have emergency response capabilities. In this way, the power grid company can directly and quickly regulate these emergency demand response resources in an emergency. One day before the regulation, the power grid company will publish the emergency response demand for the next day on the power trading platform. The industrial load corresponding to the daily demand response will determine the maximum limit of the daily demand response capacity and the market bidding according to its own situation. The power grid company will determine the compensation unit price of the daily demand response according to the market bidding results; in addition, the power grid company must also calculate the cost of emergency demand response and require users to quote higher than the minimum cost to prevent some users from disrupting the market order by malicious price cuts.

[0136] Step 4.2: Combine market bidding to establish the objective function of the daily demand response regulation and control operation cost. Set the energy storage load constraint and the captive power plant load constraint according to the maximum limit of the daily demand response capacity, and set the power balance constraint, wind curtailment, solar and load loss constraints to determine the daily demand response capacity with the minimum grid regulation and control operation cost.

[0137] The intraday demand response regulation operation cost objective function established in the present invention is:

[0138]

[0139] in, is the sum of the daily demand response regulation and operation costs, V price is the market price of the day, N ess is the amount of energy storage on the user side, i is N ess The index of are the load increase and decrease responses of the energy storage load at the i-th user side, N cpp is the number of self-provided power plant loads, c is N cpp The index of are the load increase and load decrease responses of the cth self-provided power plant respectively; λ Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are wind power abandonment, solar power abandonment and load loss power under scenario s in period t respectively;

[0140] The constraints are:

[0141] The specific expression of the power balance constraint is as follows:

[0142]

[0143] In the formula, ΔP t′ is the system power deviation after day-ahead demand response.

[0144] The wind curtailment, solar power and load loss constraints are the same as those in the day-ahead demand response incentive decision model.

[0145] The constraints on energy storage load are:

[0146]

[0147] In the formula, are the charging and discharging states of the i-th energy storage load in period t, P i essDR+,max , P i essDR-,max are the maximum values ​​of load increase and load reduction allowed by the i-th energy storage load, is the storage capacity of the i-th energy storage load that has been regulated by the power grid before time period t, are the charging and discharging coefficients of the i-th energy storage load, are the maximum and minimum energy storage capacities allowed for the grid by the i-th energy storage load.

[0148] The load constraints of the captive power plant are:

[0149]

[0150] In the formula, are the maximum and minimum values ​​of the demand response of the cth self-provided power plant load in time period t. Since the self-provided power plant cannot increase or decrease the power generation capacity without limit, it is necessary to constrain the cumulative response of the self-provided power plant. They are respectively the maximum and minimum values ​​of the cumulative response of the cth captive power plant load.

[0151] Step 4.3, combine the intraday demand response capacity with the corresponding industrial load credit evaluation index to establish the lower-level industrial load overall response credit objective function, set the intraday total demand response quantity constraint, substitute the intraday demand response capacity in step 4.2 into the intraday total demand response quantity constraint, and solve the optimal intraday demand response capacity under the highest industrial load overall response credit;

[0152] The overall response credit objective function of industrial load is:

[0153]

[0154] in, is the overall response credit objective function of industrial load, is the credit evaluation index of the energy storage load at the i-th user side, They are respectively the load increase response and load reduction response of the i-th user-side energy storage load in the lower-level scheduling; is the credit evaluation index of the load of the i-th self-provided power plant, They are respectively the load increase response and load reduction response of the cth captive power plant in the lower-level dispatching.

[0155] In order to ensure that the total demand response amount of the upper and lower layers of the daily demand response optimization in different periods is equal, the total demand response amount constraint is introduced, which is specifically expressed as follows:

[0156]

[0157] After the upper and lower optimization of the daily demand response, the demand response of the energy storage load is finally obtained as follows: The load constraint of the captive power plant is

[0158] Step 4.4: Calculate the compensation price of the intraday demand response capacity based on the optimal intraday demand response capacity and the market bidding.

[0159] Step 5: Figure 4 , establish a real-time response incentive decision model with the goal of minimizing the economic cost of interrupted loads for real-time demand response, and determine the compensation amount under the corresponding industrial load.

[0160] The real-time response incentive decision model is:

[0161]

[0162] in, is the economic cost of real-time demand response in the current period, N all is the sum of all industrial users that can participate in real-time demand response, is the power interruption action of the i-th industrial load, represents the power supply status of the i-th industrial load, The cost incurred when the power supply to the i-th industrial load is interrupted, is the cost incurred during the power outage of the i-th industrial load, λ Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are respectively the wind power abandoned, solar power abandoned and load loss power under scenario s in period t.

[0163] The constraints are:

[0164] The wind curtailment, solar power and load loss constraints are the same as those in the day-ahead demand response incentive decision model.

[0165] Real-time demand response needs to fill the power supply gap caused by system failure as soon as possible, so its constraints are:

[0166]

[0167] In the formula, is the power of the ith industrial user under normal power supply conditions in the current period, ΔP t ″ is the system power deficit caused by system failure and still existing after day-ahead and intraday demand response.

[0168] In addition, the load shedding action needs to be constrained, and its specific expression is as follows:

[0169]

[0170] In the formula, It is a sign that power is restored.

[0171] The calculation process of the compensation amount corresponding to industrial load is:

[0172]

[0173] Among them, N T is the number of control periods, t is N T The index of is the unit incentive price for real-time demand response, is the maximum unit incentive price for day-ahead demand response, is the highest unit incentive price for demand response within the day, is the power of the i-th industrial load under normal power supply conditions in period t.

[0174] Example

[0175] This embodiment uses an improved IEEE-30 node system for simulation analysis. Figure 5 Nodes 1, 2, and 5 are wind farms, and nodes 8 and 11 are photovoltaic power stations. The installed capacity of each new energy power station is set to be approximately 300MW, the cost of wind and light abandonment is 16,000 yuan / MWh, and the cost of load loss is 20,000 yuan / MWh; node 13 is a thermal power plant, which has two thermal power units with installed capacities of 800MW and 500MW respectively. The specific parameters are shown in Table 2; the maximum power of the load in the system is 1600MW, and the demand response (DR) resource parameters are shown in Table 3-4.

[0176] Table 2 Thermal power unit parameters

[0177]

[0178]

[0179] Table 3 Cement enterprise parameters

[0180] parameter 5 companies’ values Maximum storage capacity / (MW·h) 40、60、60、50、40 Initial capacity / (MW·h) 20、20、30、20、20 Maximum reduction in the number of crushers / unit 4、5、5、5、4 Maximum number of additional crushers / unit 2、3、3、3、2 Power of each crusher / MW 2、2、2、2、2 <![CDATA[Compensation price / [Yuan·(MW·h) -1 > 600、600、600、600、600

[0181] Table 4 Parameters of electrolytic aluminum enterprises

[0182] Aluminum smelting enterprises Adjustment range / MW <![CDATA[Compensation price / [yuan·(MW·h) -1 > 1 -8～8 600 2 -9～9 600 3 -9～9 600 4 -8～8 600 5 -10～10 600

[0183] Set the load parameters of each type of industrial load to be the same except for the credit rating value; the parameters of the day-ahead demand response load are shown in Table 3-4, the parameters of the intraday demand response load are shown in Table 5-6, and the parameters of the real-time demand response load are shown in Appendix Table 7.

[0184] Table 5 User-side energy storage load parameters

[0185] parameter 4 load values Maximum load increase / MW 2、2、2、2 Maximum load reduction / MW -2、-2、-2、-2 Maximum amount of energy storage allowed to be used by the grid / MWh 2.5、2.5、2.5、2.5 Minimum energy storage capacity allowed for grid use / MWh 0.5、0.5、0.5、0.5 Initial storage capacity / MWh 1.5、1.5、1.5、1.5 User credit evaluation 0.93、0.97、0.92、0.94

[0186] Table 6 Load parameters of self-provided power plant

[0187] parameter 3 load values Maximum load increase / MW 3、3、3 Maximum load reduction / MW -3、-3、-3 Maximum cumulative response value / MWh 4、4、4 Cumulative minimum response value / MWh -4、-4、-4 User credit evaluation 0.98、0.95、0.90

[0188] Table 7 Real-time demand response load parameters

[0189]

[0190] Based on the parameters of industrial load, the Gurobi solver is used in the python environment to solve the industrial load demand response incentive method of the present invention, and the equilibrium solution of the master-slave game between the power grid company and the demand response user can be obtained. Taking the electrolytic aluminum enterprise 1 as an example, the relationship between the demand response amount and the unit incentive price arranged by the power grid company for the electrolytic aluminum enterprise 1 is as follows: Figure 6 As shown, Figure 6 (a) is the demand response of electrolytic aluminum enterprise 1 in each period, Figure 6 (b) is the unit response incentive price of electrolytic aluminum enterprise 1 in each period. The results show that the higher the unit incentive price set by the power grid company, the greater the enterprise's demand response. When the user's demand response is 0MW, the incentive price is also 0 yuan, that is, the user's demand response is positively correlated with the incentive price, which is in line with the general economic law. Compared with the fixed incentive price, the incentive price set by the method in this paper has a stronger guiding effect on user behavior.

[0191] Figure 7is the revenue of electrolytic aluminum enterprise 1 under different default rates, and it is assumed that the default rate in each period is the same. The revenue of users in different periods under the default rates of 0%, 5%, 10%, 15% and 20% are given; the results show that the smaller the user response default rate, the higher its own revenue, and as the demand response volume increases, the revenue gap caused by high default rate and low default rate is also larger; this is mainly due to the consideration of the interests of both supply and demand, so for the user side, following the demand response instruction is the best choice for its pursuit of maximum revenue; and in order to reduce the loss of user default to the power grid, this paper deducts part of its incentive price according to the user default situation, thus further widening the revenue of users with high default rate and low default rate.

[0192] When all users do not default in their demand response on the day and there is no system failure, the operating cost of the system is shown in Table 8. It can be seen that in this case, the operating cost of thermal power units is the highest, followed by day-ahead demand response, with a small amount of intraday demand response cost, no real-time demand response cost, and no abandonment of wind, solar and load loss.

[0193] Table 8 System operation cost without default and failure

[0194] Cost Type Cost value when power supply is insufficient / 10,000 yuan Day-ahead demand response costs 156.71 Intraday demand response costs 6.86 Real-time demand response costs 0 Thermal power unit operating costs 662.44 Cost of curtailing wind and solar power 0 Lost load cost 0 Total operating cost 826.01

[0195] When some industrial loads default in demand response, the industrial load default situation is shown in Table 11, but when there is no system failure, the system operating cost is shown in Table 9. It can be seen that due to the default of some day-ahead demand response users, the intraday demand response load needs to increase the response amount to prevent the phenomenon of wind, light and load abandonment, thereby increasing the intraday demand response cost; but since the present invention will deduct part of the response incentive price for the defaulting industrial load, the cost of the day-ahead demand response is reduced, the total operating cost does not change much compared with the case without default.

[0196] Table 9 System operation cost with default and no failure

[0197] Cost Type Cost value when power supply is insufficient / 10,000 yuan Day-ahead demand response costs 154.72 Intraday demand response costs 9.62 Real-time demand response costs 0 Thermal power unit operating costs 662.44 Cost of curtailing wind and solar power 0 Lost load cost 0 Total operating cost 826.78

[0198] Assuming that a system failure occurs during the 18th and 19th periods, and a power shortage of 50MW occurs on the power supply side, when some industrial loads default on demand response and there are system failures, the operating cost of the system is as shown in Table 12. When a system failure occurs, after optimization calculation, it is found that the cost of emergency interruption of load 3 in the real-time demand response resource is the smallest, so the power supply to load 3 is interrupted. The cost of cutting off load 3 is 58,000 yuan, and the total incentive price is 224,000 yuan. Therefore, the price compensated to the industrial load is 282,000 yuan. Through real-time demand response, the normal power supply needs of other industrial loads in the system are guaranteed, and the power grid avoids the high cost of load shedding.

[0199] Table 10 System operation costs with default and failure

[0200] Cost Type Cost value when power supply is insufficient / 10,000 yuan Day-ahead demand response costs 154.72 Intraday demand response costs 9.62 Real-time demand response costs 28.2 Thermal power unit operating costs 662.44 Cost of curtailing wind and solar power 0 Lost load cost 0 Total operating cost 854.98

[0201] Table 11 Industrial load demand response defaults

[0202]

[0203]

[0204] The industrial load demand response incentive method based on credit evaluation of the present invention dynamically adjusts credit evaluation indicators and incentives by continuously monitoring and evaluating the demand response behavior of industrial loads. This method can not only effectively improve the participation of industrial loads and reduce default behaviors, but also ensure the fairness and effectiveness of demand response incentives. Through this incentive method based on credit evaluation, the demand response potential of industrial loads can be better tapped, thereby improving the supply and demand balancing ability of the power grid, alleviating peak load pressure, and promoting the stable operation and reliability of the power system. This not only provides new impetus and direction for industrial load demand response, but also provides a reference for the modern management of the power system.

[0205] In a technical solution of the present invention, a computer-readable storage medium is also provided, storing a computer program, wherein the computer program enables a computer to execute the industrial load demand response incentive method based on credit evaluation.

[0206] In a technical solution of the present invention, an electronic device is also provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the industrial load demand response incentive method based on credit evaluation is implemented.

[0207] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0208] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0209] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. An industrial load demand response incentive method based on credit evaluation, characterized in that: The specific steps include: Step 1: Combine the reliability index of each industrial load control time with the industrial load subscription performance index to construct the credit evaluation index of each industrial load; Step 2: All industrial load demand responses are divided into day-ahead demand response, intraday demand response and real-time demand response according to the operation time; Step 3: Based on the day-ahead demand response, establish a day-ahead demand response incentive decision model with the upper layer maximizing the benefits of both supply and demand parties and the lower layer maximizing the overall response credit of industrial loads. Determine the optimal day-ahead demand response capacity and compensation amount corresponding to the industrial load through optimization solution; Step 4: Based on the intraday demand response, establish an intraday demand response incentive decision model with the upper layer aiming at minimizing the grid regulation cost and the lower layer aiming at maximizing the overall response credit of the industrial load, and determine the optimal intraday demand response capacity and compensation amount corresponding to the industrial load through optimization solution; Step 5: Establish a real-time demand response incentive decision model with the goal of minimizing the economic cost of interrupted loads, and determine the compensation amount under the corresponding industrial load.

2. The industrial load demand response incentive method based on credit evaluation according to claim 1 is characterized in that: Step 1 includes the following sub-steps: Step 1.1, determine the target industrial load response capacity of each industrial load within the evaluation period, and calculate the average industrial load response capacity according to the actual industrial load response capacity of each industrial load within the evaluation period. When the average industrial load response capacity is less than the target industrial load response capacity, the ratio of the average industrial load response capacity to the target industrial load response capacity is used as the industrial load subscription performance indicator; otherwise, the ratio of the target industrial load response capacity to the average industrial load response capacity is used as the industrial load subscription performance indicator; Step 1.2, the ratio of the time period during which the deviation between the actual industrial load response capacity and the target industrial load response capacity of each industrial load within the evaluation period is controlled within 20% to the evaluation period is used as the control time reliability index; Step 1.3: The product of the industrial load subscription performance index and the regulation time reliability index of each industrial load in the evaluation period is used as the corresponding industrial load credit evaluation base value, combined with the corresponding industrial load credit evaluation value of the previous evaluation period, to obtain the corresponding industrial load credit evaluation index in the current evaluation period.

3. The industrial load demand response incentive method based on credit evaluation according to claim 2 is characterized in that: The specific process of obtaining the corresponding industrial load credit evaluation index in the current evaluation cycle in step 1.3 is as follows: in, represents the credit evaluation index value of industrial load i in the nth evaluation cycle, represents the credit evaluation base value of industrial load i in the nth evaluation period, θ1 represents The weight coefficient of .

4. The industrial load demand response incentive method based on credit evaluation according to claim 3 is characterized in that: Step 3 includes the following sub-steps: Step 3.1: Incorporate the corresponding industrial load incentives and demand response costs into the day-ahead control operation cost objective function established by the upper layer according to the day-ahead demand response. Determine the industrial load demand response capacity and unit incentive price under the conditions of maximum benefits for both supply and demand parties through active power balance constraints, upper and lower limits of thermal power unit output constraints, thermal power unit ramp constraints, thermal power unit minimum start-up and shutdown time constraints, day-ahead demand response resource constraints, cement enterprise storage constraints, electrolytic aluminum enterprise heat balance constraints, and wind, solar, and load abandonment constraints. Step 3.2, combine the industrial load demand response capacity with the corresponding industrial load credit evaluation index to establish the lower-level industrial load overall response credit objective function, set the industrial load demand response monotonic change constraint, the optimal industrial load demand response quantity constraint, the total industrial load demand response quantity constraint and the total compensation amount constraint, substitute the industrial load demand response capacity and unit incentive price in step 3.1 into the total industrial load demand response quantity constraint and the total compensation amount constraint, update the industrial load demand response capacity and unit incentive price, and determine the industrial load demand response capacity and unit incentive price under the condition of the highest industrial load overall response credit; Step 3.3: Calculate the total incentive price based on the industrial load demand response capacity and unit incentive price under the highest overall industrial load response credit condition, and update the total incentive price through the reward and punishment coefficient. The sum of the updated total incentive price and the demand response cost of the industrial load on the day before is used as the compensation cost of the industrial load on the day before.

5. The industrial load demand response incentive method based on credit evaluation according to claim 4 is characterized in that: The day-ahead control operation cost objective function established at the upper level in step 3.1 is: in, is the sum of the operating costs of all scenarios of day-ahead control, N s is the number of scenes, s is N s The index of N GN is the total amount of thermal power units, g is N GN The index of N T is the number of control periods, t is N T The index of ; π s is the probability of the sth scenario occurring, is the power generation cost of thermal power units, is the output power of the g-th thermal power plant in the s-th scenario during period t; U g,t , D g,t are the start-up and shutdown costs of the g-th thermal power plant in period t, N AN is the number of cement enterprises, a is N AN The index of is the unit incentive price of the a-th cement load in period t, is the labor cost of the a-th cement load in period t; N BN is the number of electrolytic aluminum enterprises, b is N BN The index of is the unit incentive price of the bth electrolytic aluminum load in period t, is the labor cost of the bth electrolytic aluminum load in period t; d t is the electricity price in period t; The power of a single crusher of the cement company participating in the demand response is The number of crushers increased and decreased by the a-th cement enterprise in period t respectively; are the power increase and decrease of the b-th electrolytic aluminum enterprise in period t, respectively, Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are wind power abandonment, solar power abandonment and load loss power under scenario s in period t respectively; The overall response credit objective function of the lower-level industrial load in step 3.2 is: in, The overall response credit of industrial load for day-ahead demand, are the credit evaluation indicators of the ath cement load and the bth electrolytic aluminum load respectively; is the number of crushers to be increased or decreased for the a-th cement load in period t after the lower-level scheduling. It is the demand response of the bth electrolytic aluminum load in time period t after lower-level scheduling.

6. The industrial load demand response incentive method based on credit evaluation according to claim 5 is characterized in that: The process of updating the total incentive price through the reward and punishment coefficient in step 3.3 is: i. The power company determines the power shortage or surplus based on the short-term peak load predicted on the day before, classifies the day-ahead demand response of industrial loads according to the proportion of the power shortage or surplus to the total power generation capacity, and determines the reward and punishment coefficients for different levels; ii. Determine whether the credit evaluation index of the corresponding industrial load is less than 0.

8. If so, the subsidy amount is 0; otherwise, update the total incentive price according to the credit evaluation index and reward and punishment coefficient of the corresponding industrial load: Among them, M is the updated total incentive price, μ is the reward and punishment coefficient, and M′ is the total incentive price. is the unit incentive price of the a-th cement load in period t after lower-level scheduling, It is the unit incentive price of the bth electrolytic aluminum load in time period t after lower-level scheduling.

7. The industrial load demand response incentive method based on credit evaluation according to claim 3 is characterized in that: Step 4 includes the following sub-steps: Step 4.1: The industrial load corresponding to the daily demand response determines the maximum limit of the daily demand response capacity and the market bidding price according to its own situation, and the power grid company determines the compensation unit price of the daily demand response according to the market bidding results; Step 4.2: Combine market bidding to establish the objective function of the daily demand response regulation and control operation cost. Set the energy storage load constraint and the captive power plant load constraint according to the maximum limit of the daily demand response capacity, and set the power balance constraint, wind curtailment, solar and load loss constraints to determine the daily demand response capacity with the minimum grid regulation and control operation cost. Step 4.3, combine the intraday demand response capacity with the corresponding industrial load credit evaluation index to establish the lower-level industrial load overall response credit objective function, set the intraday total demand response quantity constraint, substitute the intraday demand response capacity in step 4.2 into the intraday total demand response quantity constraint, and solve the optimal intraday demand response capacity under the highest industrial load overall response credit; Step 4.4: Calculate the compensation price of the intraday demand response capacity based on the optimal intraday demand response capacity and the market bidding.

8. The industrial load demand response incentive method based on credit evaluation according to claim 7 is characterized in that: The intraday demand response regulation operation cost objective function established in step 4.2 is: in, is the sum of the daily demand response regulation and operation costs, V price is the market price of the day, N ess is the amount of energy storage on the user side, i is N ess The index of are the load increase and decrease responses of the energy storage load at the i-th user side, N cpp is the number of self-provided power plant loads, c is N cpp The index of are the load increase and load decrease responses of the cth self-provided power plant respectively; Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are wind power abandonment, solar power abandonment and load loss power under scenario s in period t respectively; The overall response credit objective function of industrial load in step 4.3 is: in, is the overall response credit objective function of industrial load, is the credit evaluation index of the energy storage load at the i-th user side, They are respectively the load increase response and load reduction response of the i-th user-side energy storage load in the lower-level scheduling; is the credit evaluation index of the load of the i-th self-provided power plant, They are respectively the load increase response and load reduction response of the cth captive power plant in the lower-level dispatching.

9. The industrial load demand response incentive method based on credit evaluation according to claim 3 is characterized in that: The real-time response incentive decision model is: in, is the economic cost of real-time demand response in the current period, N all is the sum of all industrial users that can participate in real-time demand response, is the power interruption action of the i-th industrial load, represents the power supply status of the i-th industrial load, The cost incurred when the power supply to the i-th industrial load is interrupted, is the cost incurred during the power outage of the i-th industrial load, λ Wcut , PVcut and λ Lcut are the penalty prices for wind curtailment, solar curtailment and load loss, They are respectively the wind power abandoned, solar power abandoned and load loss power under scenario s in period t.

10. The industrial load demand response incentive method based on credit evaluation according to claim 9 is characterized in that: The calculation process of the compensation amount corresponding to industrial load in step 5 is: Among them, N T is the number of control periods, t is N T The index of is the unit incentive price for real-time demand response, is the maximum unit incentive price for day-ahead demand response, is the highest unit incentive price for demand response within the day, is the power of the i-th industrial load under normal power supply conditions in period t.

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