Electric power spot market transaction method meeting dominant strategy incentive compatibility

Abstract

The invention discloses an electric power spot market transaction method meeting dominance strategy incentive compatibility, and relates to the field of electric power transaction. The invention aims to solve the problem that the price formed by marginal cost bidding is difficult to completely reflect the system cost paid by flexible resources for absorbing new energy while meeting the incentive compatibility principle under the traditional transaction mechanism of the electric power spot market. According to the method, an upper-layer new energy clearing model is constructed to obtain the optimal market deviation electric quantity; constructing a lower-layer flexibility resource clearing model to obtain the optimal electric energy balance service total cost; calculating the average marginal equilibrium cost caused by the main body by adopting a Shapley value; and calculating unbalanced funds which should be allocated by the balanced service demand subject by using an unbalanced fund allocation method.

Description

Technical Field

[0001] The invention belongs to the field of power trading. Background Art

[0002] In the new power system, renewable energy will become the main source of electricity, and the electricity spot market will usher in a zero-carbon transformation stage. Under the traditional trading mechanism, the price formed by marginal cost bidding is difficult to fully reflect the system cost paid by flexible resources to absorb new energy while satisfying the incentive compatibility principle. Therefore, it is urgent to design a market price mechanism that can adapt to the large-scale access of a high proportion of renewable energy, rely on the corresponding market trading methods and market clearing models to ensure the market benefits of multiple types of energy entities and meet the flexibility needs of the new power system. Summary of the invention

[0003] The present invention aims to solve the problem that in the electricity spot market under the traditional trading mechanism, the price formed by marginal cost bidding is difficult to fully reflect the system cost paid by flexible resources for absorbing new energy while satisfying the incentive compatibility principle. A power spot market trading method that satisfies the incentive compatibility of dominant strategies is now provided.

[0004] The power spot market trading method that meets the incentive compatibility of dominant strategies includes:

[0005] Construct an upper-layer new energy clearing model to obtain the optimal market deviation electricity;

[0006] Construct a lower-level flexibility resource clearing model to obtain the optimal total cost of electricity energy balance service;

[0007] The Shapley value is used to calculate the average marginal equilibrium cost incurred by the entity;

[0008] The imbalance funds allocation method is used to calculate the imbalance funds that should be shared by the entity that needs the balancing service.

[0009] Furthermore, the upper-layer new energy clearing model is constructed to obtain the optimal market deviation electricity, including:

[0010] The expression of the upper-level new energy clearing model is:

[0011]

[0012] Where: is the market deviation electricity, T is the market transaction cycle, is the predicted capacity of new energy source i at time t, is the required capacity of user m at time t, P i,t is the clearing amount of new energy i at time t, I is the total number of new energy types, and M is the total number of users;

[0013] The constraints of the upper-level new energy clearing model include:

[0014] Line flow constraints:

[0015]

[0016] New energy output constraints:

[0017]

[0018] New energy trading capacity constraints:

[0019]

[0020] Where: Φ E is the set of nodes connected to new energy sources / users, P e,t is the clearing capacity of the new energy connected to node e at time t, is the load demand of the users connected to node e at time t, F s,- and F s,+ are the lower and upper limits of the transmission capacity of line s, respectively, se are the elements of the transfer distribution factor matrix, is the actual output of new energy source i at time t, P i RAT is the rated capacity of new energy i.

[0021] Furthermore, the above-mentioned lower-level flexible resource clearing model is constructed to obtain the total cost of the optimal electric energy balance service, including:

[0022] The expression of the lower-level flexibility resource clearing model is:

[0023]

[0024] Where: is the total price of the flexibility resource, X * is the optimal economic dispatch vector of flexible resources, represents the total cost of electric energy balance service under optimal economic dispatch, The service contribution of flexible resource j at time t, D j,t is the unit equilibrium service cost of flexibility resource j at time t, J is the total number of flexibility resource types, and T is the market transaction cycle;

[0025] The constraints of the lower-level flexible resource clearing model include:

[0026] Deviation power balance constraint:

[0027]

[0028] Line flow constraints:

[0029]

[0030] Flexibility resource ramping constraints:

[0031]

[0032] Flexible resource output constraints:

[0033]

[0034] Where: Φ A is the set of nodes connected to the flexibility resource, is the demand deviation of user m at time t, is the actual output deviation of new energy source i at time t, is the line power flow from node a to node b at time t, λ ab,t is the dual multiplier of the deviation power balance constraint, is the maximum transmission capacity of line ab, and are the maximum down-climbing capacity and up-climbing capacity of flexibility resource j, and are the lower and upper limits of the output of flexible resource j at time t respectively.

[0035]

[0036] Where: P i,t is the clearing amount of new energy i at time t, is the demand capacity of user m at time t, I is the total number of new energy types, M is the total number of users, is the actual output of new energy i at time t.

[0037] Furthermore, the above-mentioned average marginal equilibrium cost caused by the Shapley value calculation entity includes:

[0038] Let K be the set of entities that demand balancing services in the spot market, and Y be the subset containing the balancing service demand y.

[0039] The difference in the overall balancing cost of subset Y in the two scenarios with and without subject y participating in the market is taken as the marginal balancing cost contribution m of subject y to subset Y in balancing service demand y (Y);

[0040] Based on the marginal balancing cost contribution m of the balancing service demand subject y to the subset Y y(Y), using Shapley value to calculate the average marginal equilibrium cost ψ caused by balancing the service demand subject y y (G).

[0041] Furthermore, the marginal balancing cost contribution m of the above-mentioned balancing service demand subject y to the subset Y is y The expression of (Y) is:

[0042]

[0043] Where: T is the market transaction cycle, Φ S represents the set of flexible resources that provide balancing services for subset Y, D s,t is the unit balancing service cost of the flexible resource s at time t, Y / y represents the subset consisting of the remaining elements in the subset Y after removing the balancing service demand subject y, is the service output of flexibility resource s at time t when all entities in subset Y participate in the new spot market, To balance the service demand subject y’s service output at time t when the flexible resource s does not participate in the market.

[0044] Furthermore, the Shapley value is used to calculate the average marginal balancing cost ψ caused by balancing the service demand subject y y (G) including:

[0045]

[0046] Furthermore, the above-mentioned method of allocating unbalanced funds is used to calculate the unbalanced funds that the balancing service demand subject should share, including:

[0047] Let K be the set of entities that demand balancing services in the spot market, and Y be the subset containing the balancing service demand y. Then the expression of the unbalanced funds that the subject of balancing service demand should share is:

[0048]

[0049] in, To balance the imbalance of funds that service demand subject y should share, [ψ y (G)]+=max{ψ y (G),0},ψ y (G) is the average marginal balancing cost caused by balancing the service demand entity y, is the total unbalanced funds of the system and has:

[0050]

[0051] is the total fee paid to all flexibility resources based on the VCG mechanism, The total payment to all flexibility resources based on the traditional marginal electricity price mechanism.

[0052] Furthermore, the total fee paid to all flexibility resources based on the VCG mechanism is The sum of fees paid to each flexibility resource based on the VCG mechanism;

[0053] Fees paid to flexibility resource j based on VCG mechanism The expression is:

[0054]

[0055] Where: and They are the economic dispatch results and quotations of the remaining flexible resources after removing flexible resource j; The overall electricity energy balance service cost of the market after removing the flexibility resources j is: is the total cost of the electric energy balance service under the optimal economic dispatch, The total cost of the electric energy balancing service provided to flexibility resource j.

[0056] Furthermore, the total cost paid to all flexibility resources based on the traditional marginal electricity price mechanism is The sum of the fees paid to each flexibility resource based on the traditional marginal electricity price mechanism;

[0057] Payment to flexibility resource j based on traditional marginal electricity price mechanism The expression is:

[0058]

[0059] Where: Φ A is the set of nodes connected to the flexibility resource, is the marginal electricity price of node a at time t, is the service output of flexibility resource j at time t, and T is the market transaction cycle.

[0060] The present invention designs a power spot market trading mechanism that can meet the incentive compatibility of dominant strategies under high proportion of new energy penetration. The present invention proposes an optimized two-tier trading framework and a flexible resource cost recovery scheme based on the VCG mechanism; at the same time, a cost sharing mechanism based on average marginal balancing cost is designed to solve the core problems of market structure, cost recovery, imbalance of revenue and expenditure, and participation of new energy in trading. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is the user load demand curve;

[0062] Figure 2 This is a schematic diagram of new energy transactions in the upper echelons of the market;

[0063] Figure 3 It is the profit ratio curve chart under the strategic bidding behavior of thermal power units;

[0064] Figure 4 This is a comparison chart of thermal power market revenue under the VCG mechanism and the traditional marginal electricity price mechanism;

[0065] Figure 5 This is a diagram showing the allocation of funds for market imbalances. DETAILED DESCRIPTION

[0066] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0067] The power spot market transaction method that satisfies the incentive compatibility of the dominant strategy described in this implementation manner includes:

[0068] 1. Constructing the upper-level new energy clearing model

[0069] The electricity commodities of new energy are cleared in a centralized manner according to a single price mechanism, and the power system operator organizes new energy operators and users to report capacity information to minimize market deviation. For the purpose, the upper-level new energy clearing model of the market is as follows:

[0070]

[0071] Where: is the predicted capacity of new energy source i at time t, is the required capacity of user m at time t, P i,t is the clearing volume of new energy i at time t, I is the total number of new energy types, M is the total number of users, and T is the market transaction cycle.

[0072] The constraints are as follows:

[0073] 1. Line flow constraints:

[0074]

[0075] Where: Φ Eis the set of nodes connected to new energy sources / users, P e,t is the clearing capacity of the new energy connected to node e at time t, is the load demand of the user connected to node e at time t, s is the line number, F s,- and F s,+ are the lower and upper limits of the transmission capacity of line s, respectively, se are the elements of the transfer distribution factor matrix.

[0076] 2. Constraints on new energy output:

[0077]

[0078] Where: is the actual output of new energy source i at time t, P i RAT is the rated capacity of new energy i.

[0079] 3. New energy trading capacity constraints:

[0080]

[0081] 2. Constructing a model for clearing lower-level flexibility resources

[0082] Assume that all the flexibility resources participating in the spot market are in the activated state to minimize the total cost of the electricity energy balancing service of the flexibility resources. As the goal, the market lower-level flexibility resource clearing model is as follows:

[0083]

[0084] Where: is the total bid for the flexibility resource, X is the economic dispatch vector of the flexibility resource, and X * is the optimal economic dispatch vector of flexible resources, is the total cost of the electric energy balance service under the optimal economic dispatch, The service output of the flexible resource j at time t, which may be positive or negative. Its positive or negative value determines whether the flexible resource j provides power generation (or discharge) or charging balancing service in the lower-level market transaction at time t. The sum of the service outputs of all flexible resources in the entire market transaction cycle is the market deviation power. D j,t is the unit equilibrium service cost of flexible resource j at time t; J is the total number of flexible resource types.

[0085] The constraints are as follows:

[0086] 1. Deviation power balance constraint:

[0087]

[0088] Where: Φ A is a set of nodes connected to the flexibility resource; is the demand deviation of user m at time t; is the actual output deviation of new energy source i at time t; is the line power flow from node a to node b at time t; ab,t is the dual multiplier corresponding to the constraint.

[0089] 2. Line flow constraints:

[0090]

[0091] Where: is the maximum transmission capacity of line ab.

[0092] 3. Flexibility resource ramping constraints:

[0093]

[0094] Where: and are the maximum down-climbing capacity and up-climbing capacity of flexibility resource j respectively.

[0095] 4. Flexible resource output constraints:

[0096]

[0097] Where: and are the lower and upper limits of the output of flexible resource j at time t respectively.

[0098] 3. Flexible resource cost recovery mechanism based on VCG mechanism

[0099] Combined with the optimal market deviation electricity, the fee paid to the flexible resource j based on the traditional marginal electricity price mechanism is for:

[0100]

[0101] Where: is the marginal electricity price of node a at time t.

[0102] Combined with the total cost of optimal energy balance service, the fee paid to flexibility resource j based on the VCG mechanism is for:

[0103]

[0104] Where: and They are the economic dispatch results and quotations of the remaining flexible resources after removing flexible resource j; is the overall market balance cost after removing flexibility resource j, when its value is equal to the price of other flexibility resources When , the objective function value of the market bottom-level clearing model; The total cost of providing electric energy balancing service for flexibility resource j, It is the sum of the costs of flexibility resources except flexibility resource j when all flexibility resources participate in the lower-level market transactions.

[0105] 4. Average Marginal Balanced Cost Calculation Based on Shapley Value

[0106] Let K be the set of demand entities with balancing services in the spot market, and Y be the subset containing demand entity y. Balance the marginal balancing cost contribution m of service demand subject y to set Y y (Y) is defined as the difference in the overall equilibrium cost of subset Y in two scenarios with and without subject y participating in the market:

[0107]

[0108] Where: T is the market transaction cycle, Φ S represents the set of flexible resources that provide balancing services for subset Y, D s,t is the unit equilibrium service cost of the flexible resource s at time t, Y / y represents the subset consisting of the remaining elements in the subset Y after removing the subject y, is the service output of flexibility resource s at time t when all entities in subset Y participate in the new spot market, The service output of flexibility resource s at time t when subject y does not participate in the market.

[0109] The Shapley value is used to calculate the average marginal equilibrium cost ψ caused by entity y y (G), expressed as the weighted average of the marginal balancing cost contributions of subject y to all |K|! different combinations of demand subjects, reflecting its average contribution to the overall balancing cost:

[0110]

[0111] The average marginal equilibrium cost ψ calculated based on the Shapley value y (G) has the following properties:

[0112] 1. Total cost invariance. The sum of the marginal balancing costs caused by all balancing demand entities is the total balancing cost of the system, that is:

[0113]

[0114] 2. Fairness of multiple types of energy entities in the market. y The calculation of (G) is not affected by the order in which the subjects of the balance requirement are arranged during the analysis and is fair to all subjects.

[0115] 3. Can be positive or negative. y When (G) is a positive number, it means that subject y has enjoyed the balancing service and increased the balancing cost. When it is a negative number, it means that subject y has relieved the balancing pressure and reduced the balancing cost. For example, users actively reduce electricity load by participating in demand response, and clear excess load in the lower-level transactions of the market when new energy is generated. At this time, subject y can recover its indirect balancing cost when participating in the market.

[0116] 5. Cost Allocation Calculation Based on Average Marginal Balanced Cost

[0117] The calculation formula of the unbalanced capital allocation method based on average marginal equilibrium cost is:

[0118]

[0119] Where: To balance the service demand, the imbalanced funds that entity y should share; [ψ y (G)]+=max{ψ y (G),0}; The total imbalance of funds in the system, is the total fee paid to all flexibility resources based on the VCG mechanism, The total payment to all flexibility resources based on the traditional marginal electricity price mechanism.

[0120] In order to verify the method designed in this implementation, the IEEE 30-node system is selected to verify the effectiveness of the proposed mechanism. The IEEE 30-node system includes: 3 photovoltaic power stations and 2 wind power stations, located at nodes 1, 7, 12, 21 and 30 respectively; 5 thermal power units, located at nodes 2, 13, 22, 23 and 27 respectively; 10 electricity consumers, located at nodes 2, 3, 5, 8, 11, 12, 15, 22, 25 and 28 respectively. The market operation simulation cycle is 24 hours, and the user data is as follows Figure 1 shown.

[0121] In the upper-level market transactions, the clearing of new energy is as follows: Figure 2 As shown. Figure 2It can be seen that from 7:00 to 18:00, all five new energy stations participated in market clearing; from 19:00 to 6:00, due to the lack of sunlight, only wind power was used to provide electricity. The market transaction volume fits well with the user load demand in most time periods, and the market clearing efficiency of new energy is 50% higher. The blank part in the figure is the user's remaining load demand. The actual output of the five new energy stations is lower than the predicted output, and the output deviation fluctuation range is about 30% of the predicted capacity. All 10 users need to further purchase a portion of electricity in the lower-level market transactions to balance their own load deviations.

[0122] In the lower-level market transactions, the incentive compatibility of the cost recovery mechanism under the VCG mechanism is verified by comparing the market revenue ratios of thermal power units under different bidding behaviors, such as Figure 3 As shown in the figure, when the profit ratio is 1, it means that the thermal power unit has the best profit. Figure 3 It can be seen that when the market quotations of the five thermal power units are true costs, their own benefits can be maximized with certainty, which verifies the incentive compatibility of the flexibility resource cost recovery mechanism based on the VCG mechanism. This mechanism can guide the true quotation of flexibility resources, restore individual rationality, and thus maximize market benefits.

[0123] Comparison of the revenue of thermal power units under the VCG mechanism and the traditional marginal electricity price mechanism Figure 4 As shown. Figure 4 It can be seen that the electric energy of thermal power units can be effectively cleared in the market. Under the premise that the market trading volume remains unchanged, the market revenues obtained by the five thermal power units using the VCG mechanism are all higher than the market revenues using the marginal electricity price mechanism. There are obvious differences in the market revenues of the five thermal power units under the two mechanisms. The market revenue under the flexibility resource cost recovery mechanism based on the VCG mechanism is higher, and the revenue difference can reach up to 1,590.4 yuan. The flexibility resources under this mechanism will still have sufficient market competitiveness in the new power system with new energy as the main power supply in the future. The difference in the revenue of thermal power units under the two mechanisms is unbalanced funds, and the total amount of unbalanced funds in the market is 5,927.72 yuan.

[0124] According to the designed cost sharing mechanism, the imbalance funds to be shared by new energy and users are calculated. The allocation of the imbalance funds is as follows: Figure 5 As shown. Figure 5It can be seen that the cost sharing mechanism based on the average marginal balancing cost is effective and provides a reasonable basis for the sharing of unbalanced funds. All 10 users and 5 new energy sources need to pay corresponding unbalanced funds to the market entities providing balancing services on the basis of purchasing electricity at the marginal electricity price. Wind Power 2 with the largest fluctuation needs to pay a further 847.4 yuan. The unbalanced fund sharing optimization model of this sharing mechanism is a mixed integer optimization problem. When it is actually applied in the new power system, classification or clustering methods can be used to reduce the number of members for Shapley value calculation to reduce the difficulty of calculation, and unbalanced funds can be shared by the same rules for similar market entities.

[0125] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the present invention. It should therefore be understood that many modifications may be made to the exemplary embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in a manner different from that described in the original claims. It should also be understood that the features described in conjunction with a single embodiment may be used in other described embodiments.

Claims

1. A power spot market trading method that satisfies the incentive compatibility of dominant strategies, characterized in that: include: Construct an upper-layer new energy clearing model to obtain the optimal market deviation electricity; Construct a lower-level flexibility resource clearing model to obtain the optimal total cost of electricity energy balance service; The Shapley value is used to calculate the average marginal equilibrium cost incurred by the entity; The imbalance funds allocation method is used to calculate the imbalance funds that should be shared by the entity that needs the balancing service.

2. The power spot market transaction method satisfying the incentive compatibility of dominant strategies according to claim 1 is characterized in that: The upper-layer new energy clearing model is constructed to obtain the optimal market deviation electricity, including: The expression of the upper-level new energy clearing model is: Where: is the market deviation electricity, T is the market transaction cycle, is the predicted capacity of new energy source i at time t, is the required capacity of user m at time t, P i,t is the clearing amount of new energy i at time t, I is the total number of new energy types, and M is the total number of users; The constraints of the upper-level new energy clearing model include: Line flow constraints: New energy output constraints: New energy trading capacity constraints: Where: Φ E is the set of nodes connected to new energy sources / users, P e,t is the clearing capacity of the new energy connected to node e at time t, is the load demand of the users connected to node e at time t, F s,- and F s,+ are the lower and upper limits of the transmission capacity of line s, respectively, se are the elements of the transfer distribution factor matrix, is the actual output of new energy source i at time t, P i RAT is the rated capacity of new energy i.

3. The power spot market trading method satisfying the incentive compatibility of dominant strategies according to claim 1 or 2, characterized in that: The construction of the lower-layer flexibility resource clearing model to obtain the optimal total cost of electric energy balance service includes: The expression of the lower-level flexibility resource clearing model is: Where: is the total price of the flexibility resource, X * is the optimal economic dispatch vector of flexible resources, represents the total cost of electric energy balance service under optimal economic dispatch, The service contribution of flexible resource j at time t, D j,t is the unit equilibrium service cost of flexibility resource j at time t, J is the total number of flexibility resource types, and T is the market transaction cycle; The constraints of the lower-level flexible resource clearing model include: Deviation power balance constraint: Line flow constraints: Flexibility resource ramping constraints: Flexible resource output constraints: Where: Φ A is the set of nodes connected to the flexibility resource, is the demand deviation of user m at time t, is the actual output deviation of new energy source i at time t, is the line power flow from node a to node b at time t, λ ab,t is the dual multiplier of the deviation power balance constraint, is the maximum transmission capacity of line ab, and are the maximum down-climbing capacity and up-climbing capacity of flexibility resource j, and are the lower and upper limits of the output of flexible resource j at time t respectively.

4. The power spot market transaction method satisfying the incentive compatibility of dominant strategies according to claim 3 is characterized in that: Where: P i,t is the clearing amount of new energy i at time t, is the demand capacity of user m at time t, I is the total number of new energy types, M is the total number of users, is the actual output of new energy i at time t.

5. The power spot market trading method satisfying the incentive compatibility of dominant strategies according to claim 1, 2 or 4, characterized in that: The Shapley value is used to calculate the average marginal equilibrium cost of the subject, including: Let K be the set of entities that demand balancing services in the spot market, and Y be the subset containing the balancing service demand y. The difference in the overall balancing cost of subset Y in the two scenarios with and without subject y participating in the market is taken as the marginal balancing cost contribution m of subject y to subset Y in balancing service demand y (Y); Based on the marginal balancing cost contribution m of the balancing service demand subject y to the subset Y y (Y), using Shapley value to calculate the average marginal equilibrium cost ψ caused by balancing the service demand subject y y (G).

6. The power spot market transaction method satisfying the incentive compatibility of dominant strategies according to claim 5 is characterized in that: The marginal balancing cost contribution m of the balancing service demand subject y to the subset Y y The expression of (Y) is: Where: T is the market transaction cycle, Φ S represents the set of flexible resources that provide balancing services for subset Y, D s,t is the unit balancing service cost of the flexible resource s at time t, Y / y represents the subset consisting of the remaining elements in the subset Y after removing the balancing service demand subject y, is the service output of flexibility resource s at time t when all entities in subset Y participate in the new spot market, To balance the service demand subject y’s service output at time t when the flexible resource s does not participate in the market.

7. The power spot market transaction method satisfying the incentive compatibility of dominant strategies according to claim 6 is characterized in that: The Shapley value is used to calculate the average marginal equilibrium cost ψ caused by balancing the service demand subject y y (G) including:

8. The power spot market trading method satisfying the incentive compatibility of dominant strategies according to claim 1, 2, 4, 6 or 7, characterized in that: The method of calculating the unbalanced funds to be shared by the balancing service demand subject using the unbalanced funds sharing method includes: Let K be the set of entities that demand balancing services in the spot market, and Y be the subset containing the balancing service demand y. Then the expression of the unbalanced funds that the subject of balancing service demand should share is: in, To balance the imbalance of funds that service demand subject y should share, [ψ y (G)]+=max{ψ y (G),0},ψ y (G) is the average marginal balancing cost caused by balancing the service demand entity y, is the total unbalanced funds of the system and has: is the total fee paid to all flexibility resources based on the VCG mechanism, The total payment to all flexibility resources based on the traditional marginal electricity price mechanism.

9. The power spot market transaction method satisfying the incentive compatibility of dominant strategies according to claim 8 is characterized in that: Total fees paid to all flexibility resources based on the VCG mechanism The sum of fees paid to each flexibility resource based on the VCG mechanism; Fees paid to flexibility resource j based on VCG mechanism The expression is: Where: and They are the economic dispatch results and quotations of the remaining flexible resources after removing flexible resource j; The overall electricity energy balance service cost of the market after removing the flexibility resources j is: is the total cost of the electric energy balance service under the optimal economic dispatch, The total cost of the electric energy balancing service provided to flexibility resource j.

10. The power spot market transaction method satisfying the incentive compatibility of dominant strategies according to claim 9, characterized in that: Total payment to all flexibility resources based on traditional marginal electricity price mechanism The sum of the fees paid to each flexibility resource based on the traditional marginal electricity price mechanism; Payment to flexibility resource j based on traditional marginal electricity price mechanism The expression is: Where: Φ A is the set of nodes connected to the flexibility resource, is the marginal electricity price of node a at time t, is the service output of flexibility resource j at time t, and T is the market transaction cycle.

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