Method, device and equipment for collaborative optimization of power demand response based on flexibility sharing and medium

Abstract

The application discloses a power demand response collaborative optimization method and device based on flexibility sharing, equipment and medium, relates to the technical field of power system demand response, and comprises the following steps: acquiring the load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response collaborative operation; the load flexibility demand is the power vector difference between the actual load curve of each target user after independently adjusting the load and the standard load curve; the load flexibility demand and load flexibility supply cost information are input into a preset power demand response collaborative optimization model, so that the corresponding power demand response collaborative scheme is determined through the preset power demand response collaborative optimization model; and the power demand response collaborative scheme is executed to perform flexibility settlement and flexibility transaction surplus distribution according to the target user execution situation. The execution of the demand response collaborative scheme based on flexibility sharing is realized, and the economy and reliability of load adjustment are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system demand response, in particular to a power demand response collaborative optimization method and device based on flexibility sharing, equipment and medium. BACKGROUND

[0002] Power demand response (DR) can tap the potential of demand-side flexible load adjustment and relieve the burden of grid regulation. Price type and incentive type are included. Price type has the problems of difficult reflection of system dynamic demand and easy rebound; incentive type has heavy baseline calculation burden in large-scale scenarios, and lacks historical data in normal scenarios and is controversial to develop. DR based on load quasi-line takes ideal load curve as the guiding target, has the characteristics of large-scale promotion and normal implementation, and can support the construction of new power system, but existing researches mostly focus on user independent participation in response. In addition, some existing inventions such as collaborative optimization method for load flexibility control, P2P market mechanism considering demand response and multi-blockchain node energy sharing alliance flexibility transaction method have deficiencies in flexibility transaction, participant restriction and calculation complexity.

[0003] In summary, the current user independent participation in DR faces the bottlenecks of high response cost, low economy, large uncertainty of response result, low reliability, insufficient flexibility mining of users and low adequacy. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a power demand response collaborative optimization method and device based on flexibility sharing, which can give the supply and demand definition and quantification method of user flexibility in DR, and realize user collaborative participation in DR. The specific scheme is as follows:

[0005] In the first aspect, the present application discloses a power demand response collaborative optimization method based on flexibility sharing, applied to a power demand response organizer, comprising:

[0006] Obtaining the load flexibility demand and load flexibility supply cost information reported by each target user participating in the power demand response collaborative operation; the load flexibility demand is the power vector difference between the actual load curve and the standard load curve of each target user after independent adjustment of the load;

[0007] Inputting the load flexibility demand and load flexibility supply cost information into a preset power demand response collaborative optimization model, so as to determine the corresponding power demand response collaborative scheme through the preset power demand response collaborative optimization model;

[0008] Executing the power demand response collaborative scheme to perform flexibility settlement and flexibility transaction surplus distribution according to the execution of the target user.

[0009] The preset power demand response coordination optimization model is a coordination optimization model constructed based on an objective function of minimizing total cost of load supply, load supply-demand balance constraints, first energy conservation constraints, single target user load supply-demand direction constraints, and single target user load supply-demand feasible region constraints.

[0010] Optionally, the load flexibility demand and load flexibility supply cost information reported by each target user participating in the power demand response coordination operation are obtained, and the obtaining includes:

[0011] The standard load curve and load flexibility price limit information are issued to each target user participating in the power demand response coordination operation, so that each target user determines whether there is a load flexibility demand according to the standard load curve, the load flexibility price limit information, independent regulation load cost information, and an actual load curve.

[0012] If the load flexibility demand exists, the load flexibility demand and load flexibility supply cost information are reported by the target user to the power demand response organization.

[0013] Optionally, the determination of whether there is a load flexibility demand according to the standard load curve, the load flexibility price limit information, independent regulation load cost information, and an actual load curve includes:

[0014] A load flexibility demand prediction model including a minimization cost function, a power constraint following a standard load curve, second energy conservation constraints, load demand constraints, and user individual operation feasible region constraints is constructed; the minimization cost function is a minimization function including a utility loss caused by power regulation of an actual load curve according to the standard load curve and a cost function of expected payment of a target user for load demand.

[0015] The standard load curve, the load flexibility price limit information, independent regulation load cost information, and an actual load curve of each target user are input into the load flexibility demand prediction model, so that the load flexibility demand prediction model predicts whether there is a load flexibility demand of each target user.

[0016] Optionally, the load supply-demand balance constraint is that the total load flexibility demand of the coupled target users is equal to the total load supply vector of all target users; the first energy conservation constraint is that the total energy adjustment amount of each target user is zero; the single target user load supply-demand direction constraint is that the sign of the load supply vector of a single target user and the total load demand vector in any same time period is opposite; and the single target user load supply-demand feasible region constraint includes a power boundary constraint and a ramp rate constraint, the power boundary constraint is that the load supply amount of a single target user does not exceed the upper and lower limits of the physical adjustment capability, and the ramp rate constraint is that the load supply adjustment amount between adjacent time periods satisfies the maximum ramp limit.

[0017] Optionally, the corresponding power demand response coordination scheme is determined by the preset power demand response coordination optimization model, including:

[0018] The power demand response coordination scheme including a load flexibility sharing price and a load supply bid amount is determined by the preset power demand response coordination optimization model.

[0019] Optionally, the target load supply side and the target load demand side are determined from each of the target users, and the target load supply side and the target load demand side are informed to execute the power demand response coordination scheme, including:

[0020] The target load supply side and the target load demand side are determined from each of the target users according to the power demand response coordination scheme;

[0021] The target load supply side is informed to charge the target load demand side with a corresponding target coordination fee based on the load supply bid amount and the load flexibility sharing price, so as to complete the flexibility settlement.

[0022] Optionally, the flexibility transaction surplus is allocated according to the execution of the target user, including:

[0023] If the directions of the load flexibility demands reported by each target user are opposite, the difference between the absolute values of the load flexibility demands is taken as a load demand complement amount;

[0024] The flexibility transaction surplus corresponding to the load demand complement amount is allocated according to the contribution proportion of the target load demand side to the load demand complement amount.

[0025] In a second aspect, the application discloses a power demand response coordination optimization device based on flexibility sharing, applied to a power demand response organizer, including:

[0026] An information acquisition module is configured to acquire load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response collaborative operation, wherein the load flexibility demand is a power vector difference between an actual load curve of each target user after independently adjusting the load and a standard load curve.

[0027] A response collaboration module is configured to input the load flexibility demand and the load flexibility supply cost information into a preset power demand response collaborative optimization model, so as to determine a corresponding power demand response collaborative scheme by the preset power demand response collaborative optimization model.

[0028] A scheme execution module is configured to execute the power demand response collaborative scheme, so as to perform flexibility settlement and flexibility transaction surplus distribution according to execution of the target user.

[0029] The preset power demand response collaborative optimization model is a collaborative optimization model constructed based on a target function of minimizing total load supply cost, load supply and demand balance constraint, first energy conservation constraint, single target user load supply and demand direction constraint, and single target user load supply and demand feasible region constraint.

[0030] In a third aspect, the present application discloses an electronic device, comprising:

[0031] A memory is configured to save a computer program.

[0032] A processor is configured to execute the computer program to implement steps of the power demand response collaborative optimization method based on flexibility sharing disclosed in the foregoing.

[0033] In a fourth aspect, the present application discloses a computer readable storage medium configured to store a computer program, wherein the computer program is executed by a processor to implement steps of the power demand response collaborative optimization method based on flexibility sharing disclosed in the foregoing.

[0034] It can be seen that the application discloses a power demand response cooperative optimization method based on flexibility sharing, which is applied to a power demand response organizer and comprises the following steps: acquiring load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response cooperation; the load flexibility demand is a power vector difference between an actual load curve of each target user after independently adjusting the load and a standard load curve; the load flexibility demand and the load flexibility supply cost information are input into a preset power demand response cooperative optimization model, so as to determine a corresponding power demand response cooperation scheme through the preset power demand response cooperative optimization model; and the power demand response cooperation scheme is executed, and flexibility settlement and flexibility transaction surplus distribution are performed according to execution conditions of the target users; wherein the preset power demand response cooperative optimization model is a cooperative optimization model constructed based on a target function of minimizing total load supply cost, load supply and demand balance constraints, first energy conservation constraints, single target user load supply and demand direction constraints and single target user load supply and demand feasible region constraints. It can be seen that, by acquiring the load flexibility demand and the flexibility supply cost information reported by the users, the users can independently decide and report the flexibility demand, the optimization model is constructed with the target of minimizing the total load supply cost, the users with low adjustment cost can be preferentially selected as the supply side, and the overall transaction cost is reduced. The demand side can purchase the flexibility which is relatively cheaper than the adjustment cost to track the target curve, participate in the flexibility sharing, the users can reduce the cost paid for tracking the target curve of the power demand response, and a win-win situation is realized. Moreover, the preset power demand response cooperative optimization model comprises the load supply and demand balance constraints, the energy conservation constraints and the supply and demand direction constraints, so that the actual load curves of all the users can strictly track the standard load curve, all the users can realize complete tracking of the target load curve by participating in the power demand response cooperation through sharing, the uncertainty of the response results of the users is reduced or even eliminated, the implementation effect of the power demand response is ensured, the power demand response can provide reliable adjustment service for the power grid, and the uncertainty of the response cooperation results is eliminated. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only belong to the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on the provided drawings.

[0036] Figure 1 A flow chart of a power demand response cooperative optimization method based on flexibility sharing disclosed by the present application;

[0037] Figure 2A user flexibility demand indication diagram disclosed by the present application;

[0038] Figure 3 A user flexibility demand decision indication diagram disclosed by the present application;

[0039] Figure 4 A user flexibility supply indication diagram disclosed by the present application;

[0040] Figure 5 A flexibility sharing transaction architecture indication diagram disclosed by the present application;

[0041] Figure 6 A user original power purchase curve (without DR) disclosed by the present application;

[0042] Figure 7 A user flexibility demand indication diagram disclosed by the present application;

[0043] Figure 8 A flexibility supply indication diagram disclosed by the present application;

[0044] Figure 9 A flexibility sharing clearing price and user flexibility supply marginal price diagram disclosed by the present application;

[0045] Figure 10 A user flexibility demand complementary quantity average marginal contribution diagram disclosed by the present application;

[0046] Figure 11 A surplus distribution result diagram disclosed by the present application;

[0047] Figure 12 A power demand response collaborative optimization device structure indication diagram based on flexibility sharing disclosed by the present application;

[0048] Figure 13 An electronic device structure diagram disclosed by the present application. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0050] Demand response (DR) can tap the potential of demand side flexible load regulation and relieve the burden of power grid regulation. Price-based DR has the problems of difficulty in reflecting system dynamic demand and rebound. Incentive-based DR has the problems of heavy baseline calculation burden in large-scale scenarios and lack of historical data in normal scenarios. DR based on load directrix takes the ideal load curve as the guiding target, has the characteristics of large-scale promotion and normal implementation, and can support the construction of new power system. However, existing researches mostly focus on user independent participation in response. In addition, some existing inventions such as the collaborative optimization method for load flexibility control, the P2P market mechanism considering demand response and the multi-blockchain node energy sharing alliance flexibility transaction method have the problems of insufficient flexibility, limited participants and high computational complexity.

[0051] In summary, the current user independent participation in DR has the problems of high response cost, low economy, large uncertainty of response result, low reliability, insufficient flexibility and low adequacy.

[0052] Therefore, the present application provides a power demand response collaborative optimization scheme, which can define and quantify the supply and demand of user flexibility in DR, and realize user collaborative participation in DR.

[0053] Referring to Figure 1 The embodiment of the present application discloses a power demand response collaborative optimization method based on flexibility sharing, applied to a power demand response organizer, comprising:

[0054] Step S11: obtaining the load flexibility demand and load flexibility supply cost information reported by each target user participating in the power demand response collaborative operation; the load flexibility demand is the power vector difference between the actual load curve and the standard load curve of each target user after independent load adjustment.

[0055] In the embodiment, the standard load curve and the load flexibility price limit information are issued to each target user participating in the power demand response collaborative operation, so that each target user determines whether there is a load flexibility demand according to the standard load curve, the load flexibility price limit information, the independent load adjustment cost information and the actual load curve; if there is the load flexibility demand, the target user reports the load flexibility demand and the load flexibility supply cost information to the power demand response organizer. It can be understood that the target user participating in DR receives the standard load curve, i.e. the load directrix (CDL) and the flexibility sharing price limit (load flexibility price limit information) issued by the power demand response organizer, and the target user decides the flexibility demand (load flexibility demand) of the target user independently. The user flexibility demand schematic diagram is shown in Figure 2 According to the load directrix (CDL) and the flexibility sharing price limit (load flexibility price limit information)Figure 2 It can be seen that the target user considers the self-regulation ability, the independent regulation load cost information to obtain the actual load curve, and then determines the difference power vector between the actual load curve and the CDL as the load flexibility demand. Record the target user The original load curve (not participating in DR) is The standard load curve (ideal target curve) shape issued by the power demand response organization is The power vector autonomously regulated by the target user is The actual load curve after the user autonomously regulates is The flexibility demand is The mathematical expression is:

[0056] ;

[0057] The flexibility demand is autonomously and independently determined by the target user according to the regulation cost evaluation, the risk bearing capacity of the price cap and the individual constraint. The design has the following advantages:

[0058] (1) Enhance decision autonomy: users react to the uncertainty of the flexibility sharing clearing price according to their risk preferences. Respecting user decisions helps to promote their continuous participation in flexibility sharing and maintain enthusiasm.

[0059] (2) Reduce the calculation burden of the organization: the complexity of the decision model is caused by the difference between the flexibility resources of the users and the individual demand. Allowing users to independently determine the flexibility demand not only protects their privacy, but also significantly reduces the calculation burden of the power demand response organization.

[0060] (3) Improve user flexibility: under the guidance of the target CDL and the price cap, users can accurately evaluate their flexibility and identify relevant influencing factors, so as to make targeted adjustments and improve individual flexibility.

[0061] In this embodiment, a load flexibility demand prediction model is constructed, which includes a minimum cost function, a power constraint for tracking the standard load curve, a second energy conservation constraint, a load demand constraint, and a user individual operation feasible region constraint. The minimum cost function is a minimum function including the utility loss caused by power regulation of the actual load curve according to the standard load curve, and the cost function of the expected payment of the target user for purchasing load demand. The standard load curve of each target user, the load flexibility price limit information, the independent regulation load cost information and the actual load curve are input into the load flexibility demand prediction model, so that the load flexibility demand prediction model predicts whether each target user has a load flexibility demand. It can be understood that, as Figure 3 ​The load flexibility demand prediction model for user autonomous decision flexibility demand is shown in the schematic diagram for subsequent analysis and illustration. In practice, users can modify the load flexibility demand prediction model according to their own, risk preference degree, and specific constraint conditions. Among them, the target user The minimum cost function of autonomous decision flexibility demand is:

[0062] ;

[0063] Among them, represents the target user Compared with the original load curve Power adjustment Causes the loss of utility or cost, assuming that the utility loss caused by the same power up and down is the same, without loss of generality, the absolute value of the power adjustment amount is used. The quadratic function form represents the utility loss; , is the corresponding utility loss coefficient. is the cost function of the expected payment of the user Purchase flexibility; is the flexibility demand vector of the user ; Among them, represents the power vector at Time, represents the 1-norm of the vector ; is the highest limit price given by the power demand response organization.

[0064] The constraint conditions include the power constraint of tracking the ideal target curve CDL (tracking the straight line constraint), the second energy adjustment constraint (energy adjustment constraint), and the load demand constraint (flexibility demand constraint). Considering that the target user reshapes the power curve by transferring energy in the time dimension under the condition of constant total energy, the user should self-regulate energy and purchase flexibility demand, which should meet the constraint of constant total energy. Among them, the power constraint of tracking the ideal target curve CDL is:

[0065] ;

[0066] The second energy adjustment constraint is as follows:

[0067] ;

[0068] The load demand constraint is as follows:

[0069] ;

[0070] In addition, the user energy adjustment should be carried out within its individual operation feasible region, and the user individual operation feasible region constraint is as follows:

[0071] ;

[0072] wherein, represents the target user The individual operation feasible region includes the constraints of the purchased power not less than 0, the upper and lower limits of the regulation power, and the regulation power ramping, etc. , respectively represent the minimum and maximum adjustable power of the user ; , respectively represent the maximum downward and upward ramping of the regulation power of the user ; .

[0073] Let represent the optimal solution of the objective function which minimizes the cost function and combines the above constraints. If , the user does not generate the purchase demand of flexibility; if , it indicates that the user generates the purchase demand of flexibility, which is defined as the target load demand side (the purchase side) of flexibility sharing in the present application, and the set of the target load demand side is denoted as , and the corresponding cardinality is .

[0074] Therefore, the total demand of flexibility sharing is: .

[0075] After the power demand response organization side collects the flexibility demand information, the target user needs to report the cost curve of providing flexibility (load flexibility supply cost information). The flexibility supply of each user is determined by the power demand response organization side. The flexibility supply of the target user is defined as the power vector which is further adjusted by the user on the basis of the self-power adjustment of the user to completely track the ideal target curve CDL. The schematic diagram is shown in Figure 4 . The set of the flexibility supply side user is denoted as , and the cardinality is ; the final actual load curve of the user after further adjustment is denoted as , and the flexibility supply of the user winning the bid is mathematically expressed as:

[0076] ;

[0077] The flexibility supply side will be divided into two categories as follows:

[0078] Users without flexibility demand, i.e. users : These users can independently track the ideal target curve through their own energy regulation due to their high flexibility or low regulation cost. Therefore, these users can act as flexibility suppliers, selling excess flexibility to help users with low flexibility.

[0079] Users with flexibility demand, i.e. users : These users can also participate in the bidding of flexibility supply to ensure the fairness of flexibility sharing. When a user both generates flexibility demand and successfully bids for supply of flexibility in the same period, it indicates that the user has low regulation cost and thus wins the bid. In addition, allowing demand-side users to participate in bidding, although they generate flexibility demand in some periods, but can provide effective and cost-effective flexibility in other periods, is conducive to improving flexibility utilization. It is particularly suitable for users with significant time-varying flexibility, such as the aluminum electrolysis industry and data centers.

[0080] Step S12: inputting the load flexibility demand and the load flexibility supply cost information into a preset power demand response collaborative optimization model to determine a corresponding power demand response collaborative scheme through the preset power demand response collaborative optimization model; wherein the preset power demand response collaborative optimization model is a collaborative optimization model constructed based on an objective function of minimizing total load supply cost, load supply and demand balance constraints, first energy conservation constraints, single target user load supply and demand direction constraints, and single target user load supply and demand feasible region constraints.

[0081] In this embodiment, the power demand response organizer performs flexibility sharing clearing according to the flexibility supply cost curve reported by the user. The objective function of the preset power demand response collaborative optimization model is to minimize the total cost of flexibility supply:

[0082] ;

[0083] wherein, is the flexibility supply vector of the user ; and is the regulation cost coefficient of the user in the period, which is reported by the user independently; represents the regulation cost generated by the user to further adjust the power vector to provide flexibility compared to the self-regulated power vector . It should be noted that since the reference power benchmark for power regulation is different when determining flexibility demand and supply, the cost coefficient in the preset power demand response collaborative optimization model and the cost coefficient in the flexibility demand decision model are different.

[0084] like Figure 5 As shown, a flexible shared transaction architecture is disclosed, wherein the constraints of the pre-set power demand response collaborative optimization model are as follows: the load supply and demand balance constraint is that the total load flexibility demand of each coupled target user is equal to the total load supply vector of all target users; the first energy conservation constraint is that the total energy adjustment of each target user is zero; the single target user load supply and demand direction constraint is that the load supply vector of a single target user and the total load demand vector have opposite signs in any equal time period; the single target user load supply and demand feasible region constraint includes a power boundary constraint and a ramp rate constraint, wherein the power boundary constraint is that the load supply of a single target user does not exceed the upper and lower limits of the physical regulation capacity, and the ramp rate constraint is that the load supply adjustment between adjacent time periods meets the maximum ramp limit. It can be understood that the load supply and demand balance constraint couples the flexible supply vectors of multiple users; the first energy conservation constraint ensures that the total energy of each flexible supply user remains unchanged; the single target user load supply and demand direction constraint requires that the flexible supply of a single user and the total flexibility demand have opposite directions in each time period, wherein... This constraint indicates that the user... Flexible supply There will be no further increase in flexibility requirements for any given period of time: ,user To satisfy The demand for time slots contributed to this. ,user To satisfy Demand during a given time period does not contribute; the feasible domain of supply and demand for a single target user load is constrained, including power purchase constraints, flexibility supply constraints, and ramp rate constraints. , users respectively The maximum downward and upward ramp values ​​of the regulated power are compared with the user's original load curve without DR. Autonomous adjustment of power vector Relatedly, the load supply and demand balance constraint is:

[0085] ;

[0086] The first energy conservation constraint is: ;

[0087] The load supply and demand direction constraints for a single target user are: ;

[0088] The feasible region constraint for the supply and demand of a single target user load is:

[0089] ;

[0090] By It can be derived that With Expression , in which , The actual maximum downward and upward ramping of the purchased power of the user .

[0091] The preset power demand response collaborative optimization model of the flexibility sharing transaction is constructed based on the objective function of minimizing the total cost of load supply, the load supply and demand balance constraint, the first energy conservation constraint, the single target user load supply and demand direction constraint, and the single target user load supply and demand feasible region constraint. The preset power demand response collaborative optimization model is a minimum optimization problem with absolute values of optimization variables. Considering that the signs before the optimization variables in the objective function are all positive and the constraint conditions are all linear constraints, the constructed model can be equivalently converted into a quadratic convex optimization problem for accurate solution. In addition, due to the particularity of the constructed model, the preset power demand response collaborative optimization model can also be transformed by the following method. Let the sign vector of be , as shown below,

[0092] ;

[0093] The optimization variable can be represented as , Substituting the formula into the above preset power demand response collaborative optimization model can convert the optimization problem with absolute values into a quadratic convex optimization problem.

[0094] In this embodiment, the power demand response collaborative scheme including the load flexibility sharing price and the load supply winning quantity is determined by the preset power demand response collaborative optimization model. It can be understood that, according to the marginal cost pricing method, the flexibility sharing price (load flexibility sharing price) is defined as the highest marginal cost of the winning flexibility supply :

[0095] ;

[0096] Among them, is the clearing flexibility supply vector. The flexibility sharing price is a T×1-dimensional vector, reflecting the value of the unit flexibility supply amount at the time period. Since the flexibility supply users have different costs of flexibility supply at different time periods, the flexibility sharing price may be different at different time periods.

[0097] flexibility suppliers (target load suppliers) the revenues and demands of the flexibility suppliers (target load suppliers) the expenditures of the flexibility demands and the revenues of the flexibility suppliers are respectively shown as follows:

[0098] ;

[0099] .

[0100] Step S13: performing the power demand response coordination scheme to make flexibility settlement and flexibility transaction surplus distribution according to the execution of the target users.

[0101] In this embodiment, the target load suppliers and the target load suppliers are determined according to the power demand response coordination scheme; the target load suppliers are informed to charge the target load suppliers with corresponding target coordination fees based on the load supply bid quantities and the load flexibility sharing price to the target load suppliers, so as to complete the flexibility settlement. If the directions of the load flexibility demands reported by each target user are opposite, the difference between the absolute values of the load flexibility demands is taken as the load demand complementary amount; the flexibility transaction surplus corresponding to the load demand complementary amount is distributed according to the contribution proportion of the target load suppliers to the load demand complementary amount. It can be understood that the proposed flexibility transaction surplus is non-negative, so that no additional imbalance fee is needed to maintain the development of flexibility sharing. The flexibility transaction surplus is as follows:

[0102] ;

[0103] The proof process of the above-mentioned flexibility transaction surplus is as follows:

[0104] ;

[0105] After superimposing each flexibility demand, the total demand is less than the algebraic sum of their absolute values. The reduction of the total demand after superimposing individual demands is defined as the flexibility demand complementary amount. Obviously, the flexibility transaction surplus comes from the complementary flexibility demand, because the directions of each flexibility supply vector are consistent, and the total flexibility supply is equal to the total flexibility demand. Since the power demand response organizer is a non-profit platform aiming to promote the transaction of flexibility sharing, the flexibility transaction surplus should be fairly distributed to the participating members.

[0106] According to the cost causality principle, the demand side initiates the flexibility demand complementary amount, which in turn leads to the transaction surplus, and should bear the corresponding surplus. Therefore, the surplus is fairly distributed to the demand side according to the degree of contribution of the demand side to the flexibility demand complementary amount. The Shapley value in cooperative game theory can be used to describe the average marginal contribution of each member in the system to a certain index of the coalition set in which the member is located. The Shapley value of each member in the system is calculated as follows: to the set The contribution of the flexibility demand complementarity of a user to the total flexibility demand complementarity can be expressed as , and the contribution is expressed as

[0107] ;

[0108] where the first bracket represents the flexibility demand complementarity of the set , and the second bracket represents the flexibility demand complementarity of the new set obtained by removing the member from the set . Further, considering the contribution of a user in different subsets, the average marginal contribution of a user to the total flexibility demand complementarity is calculated by

[0109] ;

[0110] It is noted that the average marginal contribution here represents the average incremental effect of a flexibility demand user when joining different user combinations (i.e. different subsets of the demand set) on the flexibility demand complementarity.

[0111] Obviously, , represents the number of elements of the set . By the properties of the Shapley value, the sum of the average marginal contributions of all users to the flexibility demand complementarity is equal to the flexibility demand complementarity, as shown in the following equation:

[0112] ;

[0113] Therefore, the flexibility transaction surplus can be distributed to the corresponding users in a fair manner according to the average marginal contribution of the users to the complementary flexibility demand, as shown in the following equation:

[0114] ;

[0115] Based on the above flexible sharing transaction architecture, the flexible sharing transaction process is as follows:

[0116] 1. The DR organization side publishes the ideal target curve and the highest limit price of flexible sharing;

[0117] 2. Users make autonomous decisions and report flexibility demand;

[0118] 3. Users report flexibility supply cost curves;

[0119] 4. The organization party clears based on the constructed flexible sharing clearing model, and publishes the flexible sharing clearing price and the flexible supply winning amount to the users;

[0120] 5. The users adjust the load based on the clearing result;

[0121] 6. The DR organization party settles the flexible sharing according to the response result of the users, including paying the flexible supply fee, collecting the flexible demand fee, and distributing the flexible transaction surplus.

[0122] Therefore, through the demand side flexible sharing transaction method of the present application, the users cooperatively participate in the DR, and the implementation effect of the DR is significantly improved. The specific advantages are as follows:

[0123] (1) Improving the economy of the DR. Through the flexible sharing, the flexible supply party brings the income by selling the surplus flexibility after tracking the target curve, and the flexible demand party purchases the flexibility which is relatively cheaper than the adjustment cost to track the target curve. Through the participation in the flexible sharing, the users can reduce the cost paid for tracking the target curve of the DR, and realize the win-win of all parties.

[0124] (2) Improving the reliability of the DR. Through the cooperative participation in the DR by the flexible sharing, all the users realize the complete tracking of the target load curve, reduce or even eliminate the uncertainty of the response result of the users, guarantee the implementation effect of the DR, and make the DR provide reliable adjustment service for the power grid.

[0125] (3) Improving the adequacy of the DR. Based on the method, the high-flexibility users sell the flexibility after tracking the target curve by self-adjusting the load, help the low-flexibility users participate in the DR, realize the excavation and release of the demand side flexibility, and can improve the utilization rate of the demand side flexibility of the DR. In addition, the method does not limit the types and categories of the users participating in the sharing, has more extensive participation, and can introduce more massive users to participate in the sharing transaction.

[0126] It can be seen that the application discloses a power demand response cooperative optimization method based on flexibility sharing, which is applied to a power demand response organizer and includes the following steps: obtaining load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response cooperation; the load flexibility demand is a power vector difference between an actual load curve of each target user after independently adjusting the load and a standard load curve; inputting the load flexibility demand and the load flexibility supply cost information into a preset power demand response cooperative optimization model, so as to determine a corresponding power demand response cooperation scheme through the preset power demand response cooperative optimization model; and executing the power demand response cooperation scheme to perform flexibility settlement and flexibility transaction surplus distribution according to execution conditions of the target users; wherein the preset power demand response cooperative optimization model is a cooperative optimization model constructed based on a target function of minimizing total load supply cost, load supply and demand balance constraints, first energy conservation constraints, single target user load supply and demand direction constraints and single target user load supply and demand feasible region constraints. It can be seen that, by obtaining the load flexibility demand and supply cost information reported by the users, the users can independently decide and report the flexibility demand, the optimization model is constructed with the target of minimizing total load supply cost, the users with low adjustment cost can be preferentially selected as the supply side, and the overall transaction cost is reduced. The demand side can purchase the flexibility which is relatively cheaper than the adjustment cost to track the target curve, participate in the flexibility sharing, the users can reduce the cost paid for tracking the target curve of the power demand response, and multiple parties can win. Moreover, the preset power demand response cooperative optimization model includes the load supply and demand balance constraints, the energy conservation constraints and the supply and demand direction constraints, the actual load curves of all the users can strictly track the standard load curve, all the users can realize complete tracking of the target load curve by participating in the power demand response cooperation through the sharing, the uncertainty of the response results of the users is reduced or even eliminated, the implementation effect of the power demand response is ensured, the power demand response can provide reliable adjustment service for the power grid, and the uncertainty of the response cooperation results is eliminated.

[0127] The application uses a system including four DR users to analyze the effectiveness of the proposed flexibility sharing method. The purchase curves of the four users under the condition of no DR are as shown in Figure 6 Figure 6 The different color broken lines (pink, dark blue, light blue and orange) correspond to the purchase curves of the user 1 to the user 4, and the flexibility supply cost coefficients of the corresponding four users are shown in Table 1 and Table 2. The single time period load adjustment amount constraint of each user is that the user 1 cannot exceed the original power consumption; the user 2 and the user 3 are limited within ±10% of the average load; and the user 4 is limited within ±50% of the average load. The highest limit price of the flexibility sharing mechanism is set to 15 yuan / kWh. ​

[0128] Table 1. Quadratic cost coefficients for flexible supply ( )

[0129]

[0130] Table 2. Primary Cost Coefficients of Flexible Supply ( )

[0131]

[0132] Based on the aforementioned scheme, the user's flexibility requirements can be calculated, such as... Figure 7 As shown. User 1's self-adjusted load curve perfectly tracks the load baseline because, compared to paying a higher cost for flexibility, such as... Figure 7 As shown in (a), User 1 can follow the guideline with a low adjustment cost, therefore its flexibility requirement is 0, and no further flexibility purchase is needed. Figure 7 As shown in (b) and (c), the self-adjusted curves of users 2 and 3 did not completely track the baseline, requiring the purchase of flexibility: User 2's load was below the baseline from 1 to 7 hours, resulting in a positive flexibility requirement, while its load was above the baseline from 8 to 19 hours, resulting in a negative flexibility requirement; conversely, User 3's self-adjusted load was still below the baseline from 11 to 16 hours, resulting in a positive flexibility requirement. Figure 7 As shown in (d), user 4 has a positive flexibility requirement from 7 to 16 hours, a negative flexibility requirement with a large amplitude from 18 to 20 hours, and can fully track the guideline by adjusting itself from 21 to 24 hours due to the high flexibility and low adjustment cost, without the need to purchase flexibility.

[0133] Based on the aforementioned scheme, the user's flexibility supply can be calculated, such as... Figure 8 As shown. Figure 8 As shown in (a), User 1 won a higher bid for flexible supply due to its greater availability of cheaper flexible options, and the trend of the supply magnitude across different time periods was consistent with the trend of the aggregate demand magnitude. During the 22-23 time period, since the demand for flexibility was zero, no flexibility was required. User 4 did not win the bid at 21h because its marginal price was lower when the flexible supply was smaller, thus giving it priority in the bid. Figure 8 As shown in (b), User 2 has a flexibility supply of approximately magnitude 2 at 5h and 18h. This is because its primary adjustment cost coefficients of 7.7 yuan / kWh and 6.6 yuan / kWh at 5h and 18h ​​respectively are lower than User 1's primary coefficient of 8 yuan / kWh. When the flexibility supply is small, the marginal price corresponding to the former is lower than that of the latter, therefore the former prioritizes winning a smaller portion of the flexibility supply. Figure 8 As shown in (c), User 3, due to having the highest adjustment cost, also has the highest bid, resulting in a zero flexibility supply obtained from clearing.Figure 8 As shown in (d), user 4, due to lower adjustment costs, preferentially won the flexibility supply of sizes 1 and 2 at 21h and 24h, respectively. Furthermore, if the four users clear their flexibility supply in the same period, their directions are consistent, indicating that they all contribute to meeting flexibility demand, thus satisfying the flexibility supply and demand direction constraint.

[0134] Based on the aforementioned scheme, the flexibility-sharing clearing price can be calculated, such as... Figure 9 As shown in the results, users 1 and 2 won the bid for time 5 hours, but the latter had a higher marginal price. According to the marginal clearing principle, the clearing price was user 2's marginal price. Users 1 and 4 won the bids for times 9, 12, 17, 18, and 24 hours. User 4 had a higher marginal price in the first four time periods, which became the clearing price. In the fifth time period, user 1's marginal price became the clearing price. At times 18 and 20 hours, three users won the bids, with user 4 having the highest marginal price, which became the clearing price. For the remaining time periods, only the user with the lowest cost won the bid, and their marginal price became the clearing price. In the 22-23 hour period, because there was no flexibility sharing, the clearing price was 0.

[0135] Based on the aforementioned scheme, the surplus allocation result can be calculated, where the average marginal contribution of users to the complementary amount of flexibility demand is as follows: Figure 10 As shown, the surplus allocation results based on average marginal contribution are as follows: Figure 11 As shown, the sum of the average marginal contributions is 60.53 kW. User 1, having generated no flexibility demand, does not participate in surplus allocation, meaning its surplus is 0. Users 2 and 4 receive relatively higher surpluses, while user 3 receives a lower surplus. Users 2 and 4 generate high flexibility demand from 8 to 16 hours, and in opposite directions, indicating a high contribution to the complementary amount of flexibility demand. Although user 3's flexibility demand from 13 to 16 hours can also offset user 1's, its demand magnitude is smaller, therefore user 3's contribution to the complementary amount of flexibility demand is relatively low.

[0136] Based on the above scheme, the flexibility sharing benefits for each user can be calculated, as shown in Table 3.

[0137] Table 3. Comparison of cost-effectiveness for DR users with and without flexible sharing (Unit: Yuan)

[0138]

[0139] Wherein, each definition in Table 3 is as follows: flexibility sharing net cost = adjustment cost + flexibility sharing expenditure - flexibility sharing benefit - surplus return; the adjustment cost refers to utility loss of the user compared with the load curve without DR, and the cost includes loss generated by the user providing flexibility supply; flexibility sharing benefit = adjustment cost without flexibility sharing - flexibility sharing net cost; the adjustment cost without flexibility sharing refers to utility loss of the user compared with the load curve without DR for tracking the quota line completely.

[0140] From the results in Table 3, it can be seen that participating in flexibility sharing brings considerable benefits to all users. Specifically, compared with the adjustment cost of the user for tracking the node load quota line without flexibility sharing, the net cost of the user for tracking the load quota line after participating in flexibility sharing is significantly reduced. After participating in flexibility sharing, the cost of the four users for tracking the quota line is reduced by 18.7%, 52.5%, 44.5% and 56.2% respectively, and the total cost of all users is reduced by 47.9%. Respectively, user 1, as the main supplier of flexibility, provides flexibility for other users, and compared with the case of not participating in sharing, it pays more adjustment cost (3115.45-1355.43=1760.02 yuan). However, by providing relatively cheap flexibility, user 1 obtains a benefit of 2013.35 yuan, and the net cost of tracking the quota line is reduced by 253.33 yuan, that is, it brings a benefit of 253.33 yuan by participating in flexibility sharing. User 3 reduces the adjustment cost from 1603.77 yuan without participating in sharing to 315.07 yuan, and as a buyer, it only pays 575.6 yuan (639.81-64.21) to purchase the flexibility required by other users to track the quota line, so the actual net cost is 890.67 yuan, and thus it saves the cost of 713.1 yuan by participating in flexibility sharing. Users 2 and 4 have dual identities as buyers and sellers, but mainly as buyers to purchase flexibility with lower adjustment cost than their own to track the quota line, and the benefits of participating in flexibility sharing are 1435.95 yuan and 2188 yuan respectively.

[0141] Therefore, based on the proposed flexibility sharing scheme, flexible energy adjustment transactions are realized among users. Users with low adjustment cost help users with high adjustment cost to reduce the cost of tracking the quota line, achieving a win-win situation for all parties. This shows that the proposed mechanism can effectively stimulate the motivation of users to participate in flexibility sharing, and is conducive to more users participating in flexibility sharing, thereby supporting the large-scale and normal development of DR, and providing reliable and economic adjustment services for the power grid.

[0142] Referring to Figure 12 The application also discloses a power demand response cooperative optimization device based on flexibility sharing, which is applied to a power demand response organizer and comprises:

[0143] An information acquisition module 11 is configured to acquire load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response cooperation; the load flexibility demand is a power vector difference between an actual load curve of each target user after independently adjusting the load and a standard load curve;

[0144] A response cooperation module 12 is configured to input the load flexibility demand and the load flexibility supply cost information into a preset power demand response cooperation optimization model, so as to determine a corresponding power demand response cooperation scheme by the preset power demand response cooperation optimization model;

[0145] A scheme execution module 13 is configured to execute the power demand response cooperation scheme, and perform flexibility settlement and flexibility transaction surplus distribution according to an execution situation of the target user.

[0146] The preset power demand response cooperation optimization model is a cooperation optimization model constructed based on a target function of minimizing total load supply cost, load supply and demand balance constraints, first energy conservation constraints, single target user load supply and demand direction constraints, and single target user load supply and demand feasible region constraints.

[0147] It can be seen that the application discloses obtaining load flexibility demand and load flexibility supply cost information reported by each target user participating in power demand response cooperative operation; the load flexibility demand is a power vector difference between an actual load curve of each target user after independently adjusting a load and a standard load curve; the load flexibility demand and the load flexibility supply cost information are input into a preset power demand response cooperative optimization model, so as to determine a corresponding power demand response cooperative scheme through the preset power demand response cooperative optimization model; the power demand response cooperative scheme is executed, and flexibility settlement and flexibility transaction surplus distribution are performed according to an execution situation of the target user; wherein the preset power demand response cooperative optimization model is a cooperative optimization model constructed based on a target function of minimizing total load supply cost, load supply and demand balance constraints, first energy conservation constraints, single target user load supply and demand direction constraints, and single target user load supply and demand feasible region constraints. It can be seen that by obtaining the load flexibility demand and supply cost information reported by the user, the user can independently decide and report the flexibility demand, an optimization model is constructed with the target of minimizing total load supply cost, the user with low adjustment cost can be preferentially selected as a supply side, and the overall transaction cost is reduced. The demand side can purchase relatively cheaper flexibility to track the target curve, participate in flexibility sharing, the user can reduce the cost paid for tracking the target curve of the power demand response, and multiple parties can win. Moreover, the preset power demand response cooperative optimization model includes load supply and demand balance constraints, energy conservation constraints and supply and demand direction constraints, so as to ensure that the actual load curve of all users strictly tracks the standard load curve, all users can realize complete tracking of the target load curve by participating in power demand response cooperation, the uncertainty of the response result of the user is reduced or even eliminated, the implementation effect of the power demand response is ensured, the power demand response can provide reliable adjustment service for the power grid, and the uncertainty of the response cooperative result is eliminated.

[0148] Further, the embodiment of the application further discloses an electronic device, Figure 13 The electronic device 20 is shown in accordance with an exemplary embodiment, and the contents in the figure cannot be considered as any limitation on the use range of the application.

[0149] Figure 13A structural schematic diagram of an electronic device 20 is provided in the embodiments of the present application. The electronic device 20 can specifically include at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25 and a communication bus 26. The memory 22 is configured to store a computer program, and the processor 21 is configured to load and execute the computer program to implement the related steps in the flexible sharing-based power demand response collaborative optimization method disclosed in any of the foregoing embodiments. In addition, the electronic device 20 in the embodiments of the present application can be specifically an electronic computer.

[0150] In the embodiments of the present application, the power supply 23 is configured to provide working voltage for each hardware device on the electronic device 20; the communication interface 24 is capable of creating a data transmission channel between the electronic device 20 and external devices, and the communication protocol followed by the communication interface 24 can be any communication protocol applicable to the technical solutions of the present application, which is not specifically limited herein; the input / output interface 25 is configured to obtain external input data or output data to the outside world, and the specific interface type can be selected according to the specific application needs, which is not specifically limited herein.

[0151] The processor 21 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array) and a PLA (Programmable Logic Array). The processor 21 can also include a main processor and a coprocessor. The main processor is a processor for processing data in a wake-up state, also known as a CPU (Central Processing Unit). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 21 can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 can further include an AI (Artificial Intelligence) processor for processing machine learning-related computing operations.

[0152] In addition, the memory 22 as a carrier for resource storage can be a read-only memory, a random access memory, a magnetic disk or an optical disk, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage mode can be temporary storage or permanent storage.

[0153] The operating system 221 is used to manage and control each hardware device on the electronic device 20 and the computer program 222, so as to realize the operation and processing of the processor 21 on the mass data 223 in the memory 22, which can be Windows Server, Netware, Unix, Linux, etc. In addition to the computer program capable of completing the flexible sharing-based power demand response collaborative optimization method disclosed by the electronic device 20, the computer program 222 can further include a computer program capable of completing other specific work. In addition to the data transmitted by the external device, the data 223 can also include the data collected by the self input and output interface 25, etc.

[0154] Further, the application also discloses a computer readable storage medium for storing a computer program; wherein the computer program is executed by the processor to realize the flexible sharing-based power demand response collaborative optimization method disclosed above. For the specific steps of the method, please refer to the corresponding content disclosed in the foregoing embodiments, which will not be repeated here.

[0155] Each embodiment in the specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. For the same or similar parts between each embodiment, please refer to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant part is described in the method part.

[0156] Those skilled in the art will further appreciate that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or any combination thereof. To clearly illustrate the interchangeability of hardware and software, various components have been described above generally in terms of their functionality, without limitation. The handwiring and software implementations of the examples described herein could be accomplished using any number of microprocessors, microcontrollers, programmable consumption logic devices, application-specific integrated circuits, or general-purpose computers with interconnecting circuits that either run software programs or use opencircuit or other hardware components that are designed to perform the functions described herein. The embodiments described herein can be implemented along with software modules, and the software modules can be stored on any of a variety of non-transitory machine-readable media. A non-transitory machine-readable medium includes any medium that participates in providing instructions to a processor for execution. Such a medium can take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks and other persistent memory. Volatile media includes dynamic memories, and physical registers. Transmission media includes coaxial cables, copper wires and fiber optic cables, including wires that comprise bus conductors. Transmission media also can also take the form of acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, solid-state drive, magnetic tape, or any other magnetic data storage medium, a Compact Disc - Read Only Memory (CD-ROM), any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a programmable ROM (PROM), an erasable PROM (EPROM), a FLASH-EPROM, any other memory chip or cartridge, a carrier wave, a

[0157] Finally, it should also be noted that, in the present text, relational terms such as first and second and the like can only be used to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between such entities or operations. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by an occurrence of the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0158] The above has carried on the detailed introduction to the scheme provided by the present application, the principle and implementation mode of the present application are described by applying the specific examples in the present text, the above example explanation is only for helping the understanding of the method and core idea of the present application; simultaneously, for the general technical personnel of the field, according to the idea of the present application, there will be the change in the specific implementation mode and application range, the above-mentioned content of the description should not be understood as the limitation of the present application.

Claims

1. A collaborative optimization method for power demand response based on flexibility sharing, characterized in that, Applied to electricity demand response organizations, including: Obtain the load flexibility demand and load flexibility supply cost information reported by each target user participating in the power demand response collaborative operation; the load flexibility demand is the power vector difference between the actual load curve and the standard load curve of each target user after independent load adjustment; The load flexibility demand and the load flexibility supply cost information are input into a preset power demand response collaborative optimization model so as to determine the corresponding power demand response collaborative scheme through the preset power demand response collaborative optimization model. The power demand response coordination scheme is implemented to perform flexibility settlement and flexibility transaction surplus allocation based on the performance of the target users; The preset power demand response collaborative optimization model is a collaborative optimization model constructed based on the objective function of minimizing the total cost of load supply, load supply and demand balance constraints, the first energy conservation constraint, the load supply and demand direction constraints of a single target user, and the load supply and demand feasible region constraints of a single target user. The acquisition of load flexibility demand and load flexibility supply cost information reported by each target user participating in the power demand response collaborative operation includes: Standard load curves and load flexibility pricing information are distributed to each target user participating in the electricity demand response coordinated operation, so that each target user can determine whether it has load flexibility needs based on the standard load curves, the load flexibility pricing information, the independent adjustment load cost information, and the actual load curves. If the load flexibility requirement exists, the target user shall report the load flexibility requirement and load flexibility supply cost information to the power demand response organization. The step of determining whether each target user has a load flexibility requirement based on the standard load curve, the load flexibility price limit information, the independent load adjustment cost information, and the actual load curve includes: A load flexibility demand forecasting model is constructed, which includes minimizing the cost function, power constraints on the curve based on the standard load, a second energy conservation constraint, load demand constraints, and user individual operational feasibility domain constraints. The cost function is a function that minimizes the utility loss caused by power adjustment of the actual load curve based on the standard load and the cost function expected to be paid by the target user for purchasing load demand. The standard load curve, load flexibility price limit information, independent load adjustment cost information, and actual load curve of each target user are input into the load flexibility demand prediction model so that the load flexibility demand prediction model can predict whether each target user has load flexibility demand.

2. The collaborative optimization method for power demand response based on flexibility sharing according to claim 1, characterized in that, The load supply and demand balance constraint is that the total load flexibility demand of all coupled target users is equal to the total load supply vector of all target users; the first energy conservation constraint is that the total energy adjustment of each target user is zero; the load supply and demand direction constraint of a single target user is that the load supply vector of a single target user and the total load demand vector have opposite signs in any equal time period; the load supply and demand feasible region constraint of a single target user includes power boundary constraints and ramp rate constraints, the power boundary constraint is that the load supply of a single target user does not exceed the upper and lower limits of the physical regulation capacity, and the ramp rate constraint is that the load supply adjustment between adjacent time periods meets the maximum ramp limit.

3. The collaborative optimization method for power demand response based on flexibility sharing according to claim 1, characterized in that, The step of determining the corresponding power demand response coordination scheme through the preset power demand response coordination optimization model includes: The pre-defined power demand response collaborative optimization model determines a power demand response collaborative scheme that includes load flexibility sharing price and load supply bid volume.

4. The collaborative optimization method for power demand response based on flexibility sharing according to claim 3, characterized in that, The execution of the power demand response coordination scheme to perform flexible settlement based on the execution status of the target users includes: Based on the aforementioned power demand response coordination scheme, target load suppliers and target load demanders are determined from each of the target users. The target load supplier is notified to collect the corresponding target coordination fee from the target load demander based on the winning bid amount of the load supply and the load flexibility sharing price, in order to complete the flexibility settlement.

5. The collaborative optimization method for power demand response based on flexibility sharing according to claim 1, characterized in that, The allocation of flexible transaction surpluses based on the performance of the target users includes: If the load flexibility requirements reported by each target user are in opposite directions, the difference in the absolute values ​​of the load flexibility requirements shall be taken as the load requirement complement. The flexibility trading surplus corresponding to the load demand complementarity is allocated according to the contribution ratio of the target load demander to the load demand complementarity.

6. A power demand response collaborative optimization device based on flexibility sharing, characterized in that, Applied to electricity demand response organizations, including: The information acquisition module is used to acquire the load flexibility demand and load flexibility supply cost information reported by each target user participating in the power demand response collaborative operation; the load flexibility demand is the power vector difference between the actual load curve and the standard load curve of each target user after independent load adjustment. The response coordination module is used to input the load flexibility demand and the load flexibility supply cost information into a preset power demand response coordination optimization model, so as to determine the corresponding power demand response coordination scheme through the preset power demand response coordination optimization model. The scheme execution module is used to execute the power demand response coordination scheme to perform flexible settlement and flexible transaction surplus allocation based on the execution status of the target users; The preset power demand response collaborative optimization model is a collaborative optimization model constructed based on the objective function of minimizing the total cost of load supply, load supply and demand balance constraints, the first energy conservation constraint, the load supply and demand direction constraints of a single target user, and the load supply and demand feasible region constraints of a single target user. The information acquisition module is specifically used to send standard load curves and load flexibility price limits to each target user participating in the power demand response collaborative operation, so that each target user can determine whether it has a load flexibility demand based on the standard load curve, the load flexibility price limit, the independent load adjustment cost information, and the actual load curve; if the load flexibility demand exists, the target user reports the load flexibility demand and load flexibility supply cost information to the power demand response organization. The apparatus is further configured to construct a load flexibility demand prediction model that includes a minimization cost function, a power constraint tracking the standard load curve, a second energy conservation constraint, a load demand constraint, and a user individual operational feasibility domain constraint; wherein, the minimization cost function is a function that minimizes the utility loss caused by power adjustment of the actual load curve according to the standard load curve and the cost function expected to be paid by the target user for purchasing load demand; the standard load curve, the load flexibility price limit information, the independent load adjustment cost information, and the actual load curve of each target user are input into the load flexibility demand prediction model so that the load flexibility demand prediction model predicts whether each target user has load flexibility demand.

7. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the steps of the power demand response collaborative optimization method based on flexibility sharing as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, Used to store a computer program; wherein, when the computer program is executed by a processor, it implements the steps of the power demand response collaborative optimization method based on flexibility sharing as described in any one of claims 1 to 5.

Images