Inter-provincial spot transaction clearing optimization method and system considering key section condition limit

Abstract

The invention discloses an inter-provincial spot transaction clearing optimization method and system considering a key section condition limit. The method comprises the following steps: establishing a general inter-provincial spot transaction clearing model; constructing a conditional section limit model; constructing an in-province key section power flow model; taking social welfare maximization as an optimization objective function, considering general inter-provincial spot transaction clearing model constraints, conditional section limit model constraints and intra-provincial key section power flow model constraints to construct an inter-provincial spot transaction clearing model considering key section conditional limits, and performing optimization solution to obtain bid-winning power and clearing prices of market subjects; the system comprises an inter-province spot clearing module, a conditional section quota module, a key section power flow module and an optimization module. According to the method, the matching degree of the inter-province power transaction and the complex safe operation mode of the power grid is further improved, the performability of the clearing transaction plan of the inter-province market is enhanced, and a technical basis is provided for inter-province and intra-province power grid safety overall planning in the unified power market.

Description

Technical Field

[0001] The present invention relates to the field of electric power automation technology, and in particular to an inter-provincial spot transaction clearing optimization method and system taking into account key section condition limits. Background Art

[0002] Inter-provincial transactions mainly rely on UHV lines to achieve nationwide resource optimization. Considering the stability characteristics of large AC / DC hybrid power grids, the trading power flows formed through different trading paths will profoundly affect the actual operation mode of the power grid, and the change in operation mode will lead to the generation of new key transmission sections or section limits. In particular, for key AC sections of inter-provincial or provincial power grids, their limits may be strongly correlated with the trading volume carried by cross-regional DC in the electrical area where they are located, thus forming conditional section limits. At present, fixed limit constraints are mostly used for key AC sections in inter-provincial spot clearing optimization models. Not only fixed limits are used for intra-provincial sections, but safety constraints are usually constructed in the form of transaction volume ratios. It is difficult to consider the actual impact of the spatial distribution of power at the transaction node gateway in the province on key sections. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide an inter-provincial spot transaction clearing optimization method and system taking into account key section condition limits.

[0004] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0005] In a first aspect, the present invention provides an inter-provincial spot transaction clearing optimization method considering key section condition limits, comprising:

[0006] Obtain boundary data and build a general inter-provincial spot clearing model;

[0007] Obtain the conditions for the effectiveness of section limits and construct a conditional section limit model;

[0008] Obtain basic data for flow calculation of key sections in the province and construct flow models for key sections in the province;

[0009] Taking social welfare maximization as the optimization objective function, considering the constraints of the general inter-provincial spot clearing model, the conditional section limit model and the key section flow model constraints within the province, an inter-provincial spot transaction clearing model considering the key section conditional limit is constructed, and the clearing model is optimized and solved to obtain the winning electricity and clearing price of market entities.

[0010] Furthermore, the general inter-provincial spot clearing model includes a social welfare maximization optimization objective function, a transaction flow balance constraint, a transmission channel capacity constraint, and a transaction node transaction volume constraint;

[0011] The mathematical expression of the social welfare maximization objective function is as follows:

[0012]

[0013] Among them, ΔP b (m, A) and ΔP s (m, A) respectively represent the winning bids of power purchase transaction node b and power sales transaction node s in the declaration segment m of transaction path A, BTR and OTR respectively represent the mapping relationship matrices between power purchase nodes, power sales nodes and the transaction paths they participate in, OTR(s, A) = 1 means that power sales node s participates in transaction path A, OTR(s, A) = 0 means that power sales node s does not participate in transaction path A, similarly BTR(b, A) = 1 means that power purchase node b participates in transaction path A, BTR(s, A) = 0 means that power purchase node b does not participate in transaction path A, λ m，A (b) and λ m，A (s) represents the declared price of the power purchasing node b and the power selling node s in the declared period m;

[0014] The mathematical expression of the transaction flow balance constraint is as follows:

[0015]

[0016] Among them, P s (A) represents the transaction power of the power selling node s in the transaction path A, P b (A) represents the transaction power of the power purchasing node b in the transaction path;

[0017] The mathematical expression of the transmission channel capacity constraint is as follows:

[0018]

[0019] Wherein, TR(A, l) represents the mapping relationship matrix between transaction path and transmission channel. When TR(A, l) = 1, it means that the transaction path A contains the transmission channel l. When TR(A, l) = 0, it means that the transaction path A does not contain the transmission channel l. L (l) represents the base flow value of transmission channel l before inter-provincial spot clearing, represents the fixed upper limit of the power flow of transmission channel l, T L (l) represents the fixed power flow lower limit of transmission channel l;

[0020] The mathematical expression of the transaction node volume constraint is as follows:

[0021]

[0022] in, and They represent the maximum values ​​of the tradable quantities of the power selling node s and the power purchasing node b respectively.

[0023] Furthermore, the conditional section limit model includes the setting of auxiliary decision variables for conditional section limit, calculation of effective limit values, and corresponding conditional variable constraints when the limit values ​​take effect;

[0024] The setting of auxiliary decision variables for conditional section limit includes: setting multiple groups of auxiliary decision variables with values ​​of 0 or 1 based on the effective conditions of section limit, and the auxiliary decision variables satisfy the state constraint that the sum of each group of variables is always equal to 1. The mathematical model of the state constraint is as follows:

[0025]

[0026] in, Indicates the mth group of conditional section limit n Auxiliary decision variables for the effective conditions;

[0027] The calculation of the effective limit value based on the auxiliary decision variables includes: the effective limit value belongs to the optional limit set, the number of optional limits is equal to the product of the number of segmented value spaces of the limit effective condition and the number of condition groups, and the effective limit value of each condition section is unique, and its value is equal to the product of all optional limits and all associated auxiliary decision variables of the corresponding effective condition. The mathematical model is as follows:

[0028]

[0029] in, Indicates the effective limit of the conditional section. It indicates the cross-sectional limit that takes effect under the combined effect of the m1th effective condition of the 1st group, the m2th effective condition of the 2nd group, and the nth effective conditions of the nth group;

[0030] The mathematical model for constructing conditional variable constraints corresponding to the effective limit based on auxiliary decision variables is as follows:

[0031]

[0032] Among them, p n The condition variable representing the nth set of effective conditions, and The mth group of n n The lower and upper bounds of the value space corresponding to the effective conditions.

[0033] Furthermore, the provincial key section power flow model includes: key section power flow increment calculation and key section power flow limit constraint;

[0034] The flow increment is calculated by the sum of the pre-planned increment of all key node units and the pre-planned increment of the tie line gateway multiplied by the sensitivity of the node; the key section flow value is calculated by adding the incremental flow and the initial flow, and must meet the key section flow limit constraints within the province;

[0035] The sum of the pre-planned increments of the key node units in each province satisfies the sum of the pre-planned increments of the tie line gateways, that is, the constraint that it is equal to the inter-provincial spot transaction volume. The mathematical expression of the constraint is as follows:

[0036]

[0037] in, Indicates unit U i The output plan increment based on the pre-planned basis, Indicates the tie line T i Planned increments based on pre-planned Indicates unit U i The node is about the contact line T i sensitivity, S(U) represents the set of all units in province S, S(T) represents the set of all tie lines in province S, and R(U) represents the set of all units in region R;

[0038] The tidal current value of the key section in the province should be less than the upper limit of the section and greater than the lower limit of the section. The mathematical expression of the tidal current limit constraint of the key section is as follows:

[0039]

[0040] in, Indicates unit U i The node is about the key section E i The sensitivity of Indicates section E i The initial flow is the flow value calculated according to the pre-plan. Indicates section E i The upper limit of the trend, Indicates section E i The lower limit of the tide.

[0041] Furthermore, the electricity won by the market entities includes the winning quantity of the market entities at the power purchasing node and the winning quantity of the market entities at the power selling node. The winning quantity of the market entities at the power purchasing node is the declared demand matched in order from high to low by the total winning quantity of the power purchasing node according to the declared prices of the market entities at the power purchasing node, and the winning quantity of the market entities at the power selling node is the declared demand matched in order from low to high by the total winning quantity of the power selling node according to the declared prices of the market entities at the power selling node;

[0042] The market entity clearing price includes a segmented curve quoted by the power purchase transaction node or the power sales transaction point according to the declared quantity, which is matched in sequence from high to low according to the declared price, and the arithmetic average of the declared segment price of the power purchase transaction node and the declared segment price of the power sales transaction node that are finally matched.

[0043] In a second aspect, the present invention provides an inter-provincial spot transaction clearing optimization system taking into account key section condition limits, comprising:

[0044] Inter-provincial spot clearing module, used to obtain boundary data and establish a general inter-provincial spot clearing model;

[0045] The conditional section limit module is used to obtain the section limit effective conditions and build a conditional section limit model;

[0046] The key section flow module is used to obtain the basic data of the key section flow calculation in the province and build the key section flow model in the province;

[0047] The optimization module is used to take social welfare maximization as the optimization objective function, consider the constraints of the general inter-provincial spot clearing model, the conditional section limit model constraints, and the provincial key section flow model constraints to construct an inter-provincial spot transaction clearing model considering the key section conditional limits, and optimize and solve the clearing model to obtain the winning electricity and clearing price of market entities.

[0048] Furthermore, the inter-provincial spot clearing module is used to obtain boundary data and establish a general inter-provincial spot clearing model;

[0049] The general inter-provincial spot clearing model includes a social welfare maximization optimization objective function, a transaction flow balance constraint, a transmission channel capacity constraint, and a transaction node transaction volume constraint;

[0050] The mathematical expression of the social welfare maximization objective function is as follows:

[0051]

[0052] Among them, ΔP b (m, A) and ΔP s (m, A) respectively represent the winning bids of power purchase transaction node b and power sales transaction node s in the declaration segment m of transaction path A, BTR and OTR respectively represent the mapping relationship matrices between power purchase nodes, power sales nodes and the transaction paths they participate in, OTR(s, A) = 1 means that power sales node s participates in transaction path A, OTR(s, A) = 0 means that power sales node s does not participate in transaction path A, similarly BTR(b, A) = 1 means that power purchase node b participates in transaction path A, BTR(s, A) = 0 means that power purchase node b does not participate in transaction path A, λ m，A (b) and λ m，A(s) represents the declared price of the power purchasing node b and the power selling node s in the declared period m;

[0053] The mathematical expression of the transaction flow balance constraint is as follows:

[0054]

[0055] Among them, P s (A) represents the transaction power of the power selling node s in the transaction path A, P b (A) represents the transaction power of the power purchasing node b in the transaction path;

[0056] The mathematical expression of the transmission channel capacity constraint is as follows:

[0057]

[0058] Wherein, TR(A, l) represents the mapping relationship matrix between transaction path and transmission channel. When TR(A, l) = 1, it means that the transaction path A contains the transmission channel l. When TR(A, l) = 0, it means that the transaction path A does not contain the transmission channel l. L (l) represents the base flow value of transmission channel l before inter-provincial spot clearing, represents the fixed upper limit of the power flow of transmission channel l, T L (l) represents the fixed power flow lower limit of transmission channel l;

[0059] The mathematical expression of the transaction node volume constraint is as follows:

[0060]

[0061] in, and They represent the maximum values ​​of the tradable quantities of the power selling node s and the power purchasing node b respectively.

[0062] Furthermore, the conditional section limit module is used to obtain the section limit effective conditions and construct the conditional section limit model;

[0063] The conditional section limit model includes the setting of auxiliary decision variables for conditional section limit, calculation of effective limit value and corresponding conditional variable constraints when the limit value takes effect;

[0064] The setting of auxiliary decision variables for conditional section limit includes: setting multiple groups of auxiliary decision variables with values ​​of 0 or 1 based on the effective conditions of section limit, and the auxiliary decision variables satisfy the state constraint that the sum of each group of variables is always equal to 1. The mathematical model of the state constraint is as follows:

[0065]

[0066] in, Indicates the mth group of conditional section limit n Auxiliary decision variables for the effective conditions;

[0067] The calculation of the effective limit value based on the auxiliary decision variables includes: the effective limit value belongs to the optional limit set, the number of optional limits is equal to the product of the number of segmented value spaces of the limit effective condition and the number of condition groups, and the effective limit value of each condition section is unique, and its value is equal to the product of all optional limits and all associated auxiliary decision variables of the corresponding effective condition. The mathematical model is as follows:

[0068]

[0069] in, Indicates the effective limit of the conditional section. It means that the m1th effective condition in the first group, the m2th effective condition in the second group, and so on until the mth effective condition in the nth group. n The cross-sectional limit that takes effect under the combined effect of the three effective conditions;

[0070] The mathematical model for constructing conditional variable constraints corresponding to the effective limit based on auxiliary decision variables is as follows:

[0071]

[0072] Among them, p n The condition variable representing the nth set of effective conditions, and The mth group of n n The lower and upper bounds of the value space corresponding to the effective conditions.

[0073] Furthermore, the key section flow module is used to obtain the basic data of the key section flow calculation in the province and construct the key section flow model in the province; the key section flow model in the province includes: key section flow increment calculation and key section flow limit constraint;

[0074] The flow increment is calculated by the sum of the pre-planned increment of all key node units and the pre-planned increment of the tie line gateway multiplied by the sensitivity of the node; the key section flow value is calculated by adding the incremental flow and the initial flow, and must meet the key section flow limit constraints within the province;

[0075] The sum of the pre-planned increments of the key node units in each province satisfies the sum of the pre-planned increments of the tie line gateways, that is, the constraint that it is equal to the inter-provincial spot transaction volume. The mathematical expression of the constraint is as follows:

[0076]

[0077] in, Indicates unit U i The output plan increment based on the pre-planned basis, Indicates the tie line T i Planned increments based on pre-planned Indicates unit U i The node is about the contact line T i sensitivity, S(U) represents the set of all units in province S, S(T) represents the set of all tie lines in province S, and R(U) represents the set of all units in region R;

[0078] The tidal current value of the key section in the province should be less than the upper limit of the section and greater than the lower limit of the section. The mathematical expression of the tidal current limit constraint of the key section is as follows:

[0079]

[0080] in, Indicates unit U i The node is about the key section E i The sensitivity of Indicates section E i The initial flow is the flow value calculated according to the pre-plan. Indicates section E i The upper limit of the trend, Indicates section E i The lower limit of the tide.

[0081] Furthermore, the optimization module is used to take social welfare maximization as the optimization objective function, consider the constraints of the general inter-provincial spot clearing model, the constraints of the conditional section limit model, and the constraints of the provincial key section power flow model to construct an inter-provincial spot transaction clearing model considering the key section conditional limit, and optimize and solve the clearing model to obtain the winning power and clearing price of the market entity;

[0082] The power won by the market entities includes the winning bids of the market entities at the power purchasing node and the winning bids of the market entities at the power selling node. The winning bids of the market entities at the power purchasing node are the declared demand matched in order from high to low according to the declared prices of the market entities at the power purchasing node; the winning bids of the market entities at the power selling node are the declared demand matched in order from low to high according to the declared prices of the market entities at the power selling node;

[0083] The market entity clearing price includes a segmented curve quoted by the power purchase transaction node or the power sales transaction point according to the declared quantity, which is matched in sequence from high to low according to the declared price, and the arithmetic average of the declared segment price of the power purchase transaction node and the declared segment price of the power sales transaction node that are finally matched.

[0084] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, which, when executing the program, implements the steps of the inter-provincial spot transaction clearing optimization method taking into account key section condition limits.

[0085] In a fourth aspect, the present invention provides a computer-readable storage medium, hereinafter referred to as the storage medium, in which a computer program is stored, which is designed to implement the steps of the inter-provincial spot transaction clearing optimization method considering the key section condition limit when running.

[0086] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: the present invention helps to further improve the compatibility between inter-provincial power transactions and the complex and safe operation mode of the power grid, enhances the feasibility of inter-provincial market clearing transaction plans, and provides a technical basis for the overall consideration of inter-provincial and intra-provincial power grid security under the national unified power market. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0088] The technical solution of the present invention is further described below in conjunction with the accompanying drawings. It will be understood by those skilled in the art that the purposes and advantages that can be achieved by the present invention are not limited to the specific description of the above beneficial effects, and the above and other purposes that can be achieved by the present invention will be more clearly understood based on the following detailed description.

[0089] It should be understood by those skilled in the art that the exemplary components, systems and methods described in conjunction with the embodiments disclosed in the present invention can be implemented in hardware, software or a combination of the two. Whether it is implemented in hardware or software depends on the specific application and design of the technical solution. Professional and technical personnel can use different methods to implement the functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0090] Reference to "embodiments" in the present invention means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0091] Embodiment 1

[0092] The present invention provides an optimization method for clearing inter-provincial spot transactions taking into account the critical section condition limit, such as Figure 1As shown in the figure, it is divided into obtaining boundary data and establishing a general inter-provincial spot clearing model; obtaining the conditions for the effectiveness of section limits and building a conditional section limit model; obtaining the basic data for calculating the flow of key sections in the province and building a flow model of key sections in the province; taking social welfare maximization as the optimization objective function, considering the constraints of the general inter-provincial spot clearing model, the constraints of the conditional section limit model and the constraints of the flow model of key sections in the province, building an inter-provincial spot transaction clearing model considering the conditional limits of key sections, and optimizing and solving the clearing model to obtain the four parts of the market entity's winning power and clearing price, which specifically includes the following steps:

[0093] S1. Obtain boundary data such as the volume and price curve declared by the trading nodes, the available trading paths between the trading nodes, and the transmission capacity of the transmission channels;

[0094] S2, obtaining the effective conditions of the section limit and constructing a conditional section limit model;

[0095] S3, obtain the unit adjustable range, sensitivity and other boundary data of the provincial section flow increment calculation;

[0096] S4. Construct a general inter-provincial spot clearing model;

[0097] S5. Construct a tidal flow constraint model for key sections within the province;

[0098] S6. Taking social welfare maximization as the optimization objective function, considering the constraints of the general inter-provincial spot clearing model, the conditional section flow limit constraints and the unconditional section flow limit constraints, a provincial spot transaction clearing model considering the key section conditional limit is constructed;

[0099] S7. Optimize and solve the inter-provincial spot transaction clearing model, and obtain the winning power and price of market entities.

[0100] Among them, the execution order of steps S1, S2 and S3 is not in particular order and can be executed in parallel. In step S1, the quantity and price curves reported by market entities in each province participating in inter-provincial spot transactions are obtained from the trading platform, and the simple topological connection relationship, transaction path search results, fixed transmission capacity, reference flow value and reference flow direction of each inter-provincial tie line, inter-provincial transmission section, and DC transmission channel are obtained, and the association relationship data between the market entity and the transaction node is obtained. The transaction node includes a power selling node that proposes a demand for selling electricity and a power purchasing node that proposes a demand for buying electricity. The transaction path refers to the set of all transmission channels that the transaction flow passes through to reach the power purchasing node starting from the power selling node.

[0101] In step S2, the section limit effectiveness conditions obtained include the segmented value spaces of continuous variables such as cross-regional DC power, associated section currents, regional external transmission / incoming power, and discrete variable value spaces such as the number of units in operation, which are usually expressed as a mapping relationship between multiple sets of segmented value spaces and effective limits. The setting of the effectiveness conditions must ensure that each set of segmented value spaces can take effect on a limit, and that there are no omissions in the segmented value spaces; construct a conditional section limit model, which includes the setting of conditional section limit auxiliary decision variables, the calculation of effective limits, and the corresponding conditional variable constraints when the limit takes effect;

[0102] For the effective conditions of the section limit, multiple groups of auxiliary decision variables with values ​​of 0 or 1 need to be set. The auxiliary decision variables need to satisfy the state constraint that the sum of each group of variables is always equal to 1. The mathematical model of the state constraint is as follows:

[0103]

[0104] in, It represents the auxiliary decision variable of the nth effective condition of the conditional section limit.

[0105] The effective section limit needs to be calculated based on the auxiliary decision variables. The effective limit belongs to the optional limit set. The number of optional limits should be equal to the product of the number of segmented value spaces of the limit effective condition and the number of condition groups. Each condition section effective limit is unique, and its value is equal to the product of all optional limits and all associated auxiliary decision variables of the corresponding effective condition. The specific mathematical model is as follows:

[0106]

[0107] in, Indicates the effective limit of the conditional section. It means that the m1th effective condition in the first group, the m2th effective condition in the second group, and so on until the mth effective condition in the nth group. n The section limit that takes effect under the combined effect of three effective conditions.

[0108] The effective condition variable must satisfy the condition variable constraint corresponding to the effective limit constructed based on the auxiliary decision variable. The condition variable constraint is the value space corresponding to the effective condition. The mathematical model of the value space in the optimization problem is as follows:

[0109]

[0110] Among them, p n The condition variable representing the nth set of effective conditions, and The mth group of n nThe lower and upper bounds of the value space corresponding to the effective conditions.

[0111] In step S3, the basic data for the calculation of the power flow of key sections in the province include the pre-clearance results of the spot in the province, the tie line gateway nodes, the initial power flow values ​​of key sections in the province, the sensitivity of key nodes, and the adjustable range of key node units. The key nodes refer to the associated nodes selected under the condition that the absolute value of the section power flow sensitivity is greater than a certain threshold.

[0112] Steps S4 and S5 are executed in any order and can be executed in parallel. In step S4, the mathematical expression of the social welfare maximization objective function of the general inter-provincial spot clearing optimization model is as follows:

[0113]

[0114] Among them, ΔP b (m, A) and ΔP s (m, A) respectively represent the winning bids of power purchasing transaction node b and power selling transaction node s in the declaration segment m of transaction path A, BTR and OTR respectively represent the mapping relationship matrices between power purchasing nodes, power selling nodes and the transaction paths in which they participate, OTR(s, A)=1 means that power selling node s participates in transaction path A, OTR(s, A)=0 means that power selling node s does not participate in transaction path A, similarly BTR(b, A)=1 means that power purchasing node b participates in transaction path A, BTR(s, A)=0 means that power purchasing node b does not participate in transaction path A.

[0115] The mathematical expression of the transaction flow balance constraint of the general inter-provincial spot clearing optimization model is as follows:

[0116]

[0117] Among them, P s (A) represents the transaction power of the power selling node s in the transaction path A, P b (A) represents the transaction power of the power purchasing node b in the transaction path.

[0118] The mathematical expression of the transmission channel capacity constraint of the general inter-provincial spot clearing optimization model is as follows:

[0119]

[0120] Wherein, TR(A, l) represents the mapping relationship matrix between transaction path and transmission channel. When TR(A, l) = 1, it means that the transaction path A contains the transmission channel l. When TR(A, l) = 0, it means that the transaction path A does not contain the transmission channel l. L (l) represents the base flow value of transmission channel l before inter-provincial spot clearing, represents the fixed upper limit of the power flow of transmission channel l, T L (l) represents the fixed lower limit of power flow in transmission channel l.

[0121] The mathematical expression of the transaction volume constraint of the general inter-provincial spot clearing optimization model is as follows:

[0122]

[0123] in, and They represent the maximum values ​​of the tradable quantities of the power selling node s and the power purchasing node b respectively.

[0124] In step S5, the provincial key section flow constraint model includes key section flow increment calculation and key section flow limit constraint, wherein the flow increment is calculated by the sum of the pre-planned increment of all key node units and the pre-planned increment of the tie line gateway and the product of the node sensitivity. The provincial key section flow value is calculated by adding the incremental flow and the initial flow, and must meet the provincial key section flow limit constraint.

[0125] The sum of the pre-planned increments of key node units in each province must meet the constraint that it is equal to the sum of the pre-planned increments of its tie line gateways. The mathematical expression is as follows:

[0126]

[0127] in, Indicates unit U i The output plan increment based on the pre-planned basis, Indicates the tie line T i Planned increments based on pre-planned Indicates unit U i The node is about the contact line T i sensitivity, S(U) represents the set of all units in province S, S(T) represents the set of all tie lines in province S, and R(U) represents the set of all units in region R.

[0128] The tidal flow value of the key section in the province should be less than the upper limit of the section and greater than the lower limit of the section. The mathematical expression of the constraint is as follows:

[0129]

[0130] in, Indicates unit U i The node is about the key section E i The sensitivity of Indicates section E i The initial flow is the flow value calculated according to the pre-plan. Indicates section Ei The upper limit of the trend, Indicates section E i The lower limit of the tide.

[0131] In step S6, the optimization objective function of the inter-provincial spot transaction clearing model considering the conditional limits of key sections adopts the social welfare maximization objective function of the general inter-provincial spot clearing optimization model; the model constraints include the transaction flow balance constraints, transmission channel capacity constraints, conditional section limit constraints, unconditional section limit constraints and transaction node transaction volume constraints in the general inter-provincial spot clearing model constraints; among them, the conditional section flow limit constraints include replacing the conditional section-related fixed flow limits with the transmission channel capacity constraints of the conditional section effective limits and the provincial key section flow constraints and auxiliary decision variable constraints, and the unconditional section flow limit constraints are manifested as the remaining fixed limit transmission channel capacity constraints and provincial key section flow constraints.

[0132] In step S7, the inter-provincial spot transaction clearing model considering the critical section condition limit is optimized and solved to obtain the market subject's bid quantity and clearing price. The power purchase transaction node or the power sales transaction point is matched in sequence from high to low according to the declared price according to the segmented curve of the declared quantity and price, and the arithmetic average of the declared segment price of the power purchase transaction node and the declared segment price of the power sales transaction node that are finally matched is the clearing price of all market subjects under the transaction node; the market subject's bid quantity includes the bid quantity of the power purchase node market subject and the bid quantity of the power sales node market subject. The bid quantity of the power purchase node market subject is the declared demand that the total bid quantity of the power purchase node is matched in sequence from high to low according to the declared price of the power purchase node market subject, and the bid quantity of the power sales node market subject is the declared demand that the total bid quantity of the power sales node is matched in sequence from low to high according to the declared price of the power sales node market subject.

[0133] Embodiment 2

[0134] In addition, based on the same inventive concept, an embodiment of the present invention also provides an inter-provincial spot transaction clearing optimization system considering key section condition limits, including:

[0135] Inter-provincial spot clearing module, used to obtain boundary data and establish a general inter-provincial spot clearing model;

[0136] The conditional section limit module is used to obtain the section limit effective conditions and build a conditional section limit model;

[0137] The key section flow module is used to obtain the basic data of the key section flow calculation in the province and build the key section flow model in the province;

[0138] The optimization module is used to take social welfare maximization as the optimization objective function, consider the constraints of the general inter-provincial spot clearing model, the conditional section limit model constraints, and the provincial key section flow model constraints to construct an inter-provincial spot transaction clearing model considering the key section conditional limits, and optimize and solve the clearing model to obtain the winning electricity and clearing price of market entities.

[0139] The inter-provincial spot clearing module is used to obtain boundary data and establish a general inter-provincial spot clearing model;

[0140] The general inter-provincial spot clearing model includes a social welfare maximization optimization objective function, a transaction flow balance constraint, a transmission channel capacity constraint, and a transaction node transaction volume constraint;

[0141] The mathematical expression of the social welfare maximization objective function is as follows:

[0142]

[0143] Among them, ΔP b (m, A) and ΔP s (m, A) respectively represent the winning bids of power purchase transaction node b and power sales transaction node s in the declaration segment m of transaction path A, BTR and OTR respectively represent the mapping relationship matrices between power purchase nodes, power sales nodes and the transaction paths they participate in, OTR(s, A) = 1 means that power sales node s participates in transaction path A, OTR(s, A) = 0 means that power sales node s does not participate in transaction path A, similarly BTR(b, A) = 1 means that power purchase node b participates in transaction path A, BTR(s, A) = 0 means that power purchase node b does not participate in transaction path A, λ m，A (b) and λ m，A (s) represents the declared price of the power purchasing node b and the power selling node s in the declared period m;

[0144] The mathematical expression of the transaction flow balance constraint is as follows:

[0145]

[0146] Among them, P s (A) represents the transaction power of the power selling node s in the transaction path A, P b (A) represents the transaction power of the power purchasing node b in the transaction path;

[0147] The mathematical expression of the transmission channel capacity constraint is as follows:

[0148]

[0149] Wherein, TR(A, l) represents the mapping relationship matrix between transaction path and transmission channel. When TR(A, l) = 1, it means that the transaction path A contains the transmission channel l. When TR(A, l) = 0, it means that the transaction path A does not contain the transmission channel l. L (l) represents the base flow value of transmission channel l before inter-provincial spot clearing, represents the fixed upper limit of the power flow of transmission channel l, T L (l) represents the fixed power flow lower limit of transmission channel l;

[0150] The mathematical expression of the transaction node volume constraint is as follows:

[0151]

[0152] in, and They represent the maximum values ​​of the tradable quantities of the power selling node s and the power purchasing node b respectively.

[0153] The conditional section limit module is used to obtain the section limit effective conditions and build a conditional section limit model;

[0154] The conditional section limit model includes the setting of auxiliary decision variables for conditional section limit, calculation of effective limit value and corresponding conditional variable constraints when the limit value takes effect;

[0155] The setting of auxiliary decision variables for conditional section limit includes: setting multiple groups of auxiliary decision variables with values ​​of 0 or 1 based on the effective conditions of section limit, and the auxiliary decision variables satisfy the state constraint that the sum of each group of variables is always equal to 1. The mathematical model of the state constraint is as follows:

[0156]

[0157] in, The auxiliary decision variable representing the nth effective condition of the conditional section limit;

[0158] The calculation of the effective limit value based on the auxiliary decision variables includes: the effective limit value belongs to the optional limit set, the number of optional limits is equal to the product of the number of segmented value spaces of the limit effective condition and the number of condition groups, and the effective limit value of each condition section is unique, and its value is equal to the product of all optional limits and all associated auxiliary decision variables of the corresponding effective condition. The mathematical model is as follows:

[0159]

[0160] in, Indicates the effective limit of the conditional section. It means that the m1th effective condition in the first group, the m2th effective condition in the second group, and so on until the mth effective condition in the nth group. nThe cross-sectional limit that takes effect under the combined effect of the three effective conditions;

[0161] The mathematical model for constructing conditional variable constraints corresponding to the effective limit based on auxiliary decision variables is as follows:

[0162]

[0163] Among them, p n The condition variable representing the nth set of effective conditions, and The mth group of n n The lower and upper bounds of the value space corresponding to the effective conditions.

[0164] The key section flow module is used to obtain the basic data of the key section flow calculation in the province and construct the key section flow model in the province; the key section flow model in the province includes: key section flow increment calculation and key section flow limit constraint;

[0165] The flow increment is calculated by the sum of the pre-planned increment of all key node units and the pre-planned increment of the tie line gateway multiplied by the sensitivity of the node; the key section flow value is calculated by adding the incremental flow and the initial flow, and must meet the key section flow limit constraints within the province;

[0166] The sum of the pre-planned increments of the key node units in each province satisfies the sum of the pre-planned increments of the tie line gateways, that is, the constraint that it is equal to the inter-provincial spot transaction volume. The mathematical expression of the constraint is as follows:

[0167]

[0168] in, Indicates unit U i The output plan increment based on the pre-planned basis, Indicates the tie line T i Planned increments based on pre-planned Indicates unit U i The node is about the contact line T i sensitivity, S(U) represents the set of all units in province S, S(T) represents the set of all tie lines in province S, and R(U) represents the set of all units in region R;

[0169] The tidal current value of the key section in the province should be less than the upper limit of the section and greater than the lower limit of the section. The mathematical expression of the tidal current limit constraint of the key section is as follows:

[0170]

[0171] in, Indicates unit U i The node is about the key section Ei The sensitivity of Indicates section E i The initial flow is the flow value calculated according to the pre-plan. Indicates section E i The upper limit of the trend, Indicates section E i The lower limit of the tide.

[0172] The optimization module is used to take social welfare maximization as the optimization objective function, consider the constraints of the general inter-provincial spot clearing model, the constraints of the conditional section limit model, and the constraints of the provincial key section power flow model to construct an inter-provincial spot transaction clearing model considering the key section conditional limit, and optimize and solve the clearing model to obtain the winning power and clearing price of the market entity;

[0173] The power won by the market entities includes the winning bids of the market entities at the power purchasing node and the winning bids of the market entities at the power selling node. The winning bids of the market entities at the power purchasing node are the declared demand matched in order from high to low according to the declared prices of the market entities at the power purchasing node; the winning bids of the market entities at the power selling node are the declared demand matched in order from low to high according to the declared prices of the market entities at the power selling node;

[0174] The market entity clearing price includes a segmented curve quoted by the power purchase transaction node or the power sales transaction point according to the declared quantity, which is matched in sequence from high to low according to the declared price, and the arithmetic average of the declared segment price of the power purchase transaction node and the declared segment price of the power sales transaction node that are finally matched.

[0175] Embodiment 3

[0176] In addition, based on the same inventive concept, an embodiment of the present invention also provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the inter-provincial spot transaction clearing optimization method considering key section condition limits are implemented.

[0177] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0178] Embodiment 4

[0179] In addition, based on the same inventive concept, an embodiment of the present invention also provides a storage medium storing a computer program, wherein the computer program is designed to implement the steps of the inter-provincial spot transaction clearing optimization method considering key section condition limits when running.

[0180] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0181] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0182] The computer-readable storage medium mentioned above may be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the technical field.

[0183] The specific description above further illustrates the purpose, technical solutions and beneficial effects of the invention in detail. It should be understood that the above is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An optimization method for clearing inter-provincial spot transactions considering key cross-section condition limits, characterized in that: include: Obtain boundary data and build a general inter-provincial spot clearing model; Obtain the conditions for the effectiveness of section limits and construct a conditional section limit model; Obtain basic data for flow calculation of key sections in the province and construct flow models for key sections in the province; Taking social welfare maximization as the optimization objective function, considering the constraints of the general inter-provincial spot clearing model, the conditional section limit model and the key section flow model constraints within the province, an inter-provincial spot transaction clearing model considering the key section conditional limit is constructed, and the clearing model is optimized and solved to obtain the winning electricity and clearing price of market entities.

2. The inter-provincial spot transaction clearing optimization method considering key section condition limits according to claim 1 is characterized in that: The general inter-provincial spot clearing model includes a social welfare maximization optimization objective function, a transaction flow balance constraint, a transmission channel capacity constraint, and a transaction node transaction volume constraint; The mathematical expression of the social welfare maximization objective function is as follows: Where ΔP b (m, A) and ΔP s (m, A) respectively represent the winning bids of power purchase transaction node b and power sales transaction node s in the declaration segment m of transaction path A, BTR and OTR respectively represent the mapping relationship matrices between power purchase nodes, power sales nodes and the transaction paths they participate in, OTR(s, A) = 1 means that power sales node s participates in transaction path A, OTR(s, A) = 0 means that power sales node s does not participate in transaction path A, similarly BTR(b, A) = 1 means that power purchase node b participates in transaction path A, BTR(s, A) = 0 means that power purchase node b does not participate in transaction path A, λ m，A (b) and λ m，A (s) represents the declared price of the power purchasing node b and the power selling node s in the declared period m; The mathematical expression of the transaction flow balance constraint is as follows: Among them, P s (A) represents the transaction power of the power selling node s in the transaction path A, P b (A) represents the transaction power of the power purchasing node b in the transaction path; The mathematical expression of the transmission channel capacity constraint is as follows: Wherein, TR(A, l) represents the mapping relationship matrix between transaction path and transmission channel. When TR(A, l) = 1, it means that the transaction path A contains the transmission channel l. When TR(A, l) = 0, it means that the transaction path A does not contain the transmission channel l. L (l) represents the base flow value of transmission channel l before inter-provincial spot clearing, represents the fixed upper limit of the power flow of transmission channel l, T L (l) represents the fixed power flow lower limit of transmission channel l; The mathematical expression of the transaction node volume constraint is as follows: in, and They represent the maximum values ​​of the tradable quantities of the power selling node s and the power purchasing node b respectively.

3. The inter-provincial spot transaction clearing optimization method considering key section condition limits according to claim 1 is characterized in that: The conditional section limit model includes the setting of auxiliary decision variables for conditional section limit, calculation of effective limit value and corresponding conditional variable constraints when the limit value takes effect; The setting of auxiliary decision variables for conditional section limit includes: setting multiple groups of auxiliary decision variables with values ​​of 0 or 1 based on the effective conditions of section limit, and the auxiliary decision variables satisfy the state constraint that the sum of each group of variables is always equal to 1. The mathematical model of the state constraint is as follows: in, Indicates the mth group of conditional section limit n Auxiliary decision variables for the effective conditions; The calculation of the effective limit value based on the auxiliary decision variables includes: the effective limit value belongs to the optional limit set, the number of optional limits is equal to the product of the number of segmented value spaces of the limit effective condition and the number of condition groups, and the effective limit value of each condition section is unique, and its value is equal to the product of all optional limits and all associated auxiliary decision variables of the corresponding effective condition. The mathematical model is as follows: in, Indicates the effective limit of the conditional section. It means that the m1th effective condition in the first group, the m2th effective condition in the second group, and so on until the mth effective condition in the nth group. n The cross-sectional limit that takes effect under the combined effect of the three effective conditions; The mathematical model for constructing conditional variable constraints corresponding to the effective limit based on auxiliary decision variables is as follows: Among them, p n The condition variable representing the nth set of effective conditions, and The mth group of n n The lower and upper bounds of the value space corresponding to the effective conditions.

4. The inter-provincial spot transaction clearing optimization method considering key section condition limits according to claim 1 is characterized in that: The provincial key section flow model includes: key section flow increment calculation and key section flow limit constraint; The flow increment is calculated by the sum of the pre-planned increment of all key node units and the pre-planned increment of the tie line gateway multiplied by the sensitivity of the node; the key section flow value is calculated by adding the incremental flow and the initial flow, and must meet the key section flow limit constraints within the province; The sum of the pre-planned increments of the key node units in each province satisfies the sum of the pre-planned increments of the tie line gateways, that is, the constraint that it is equal to the inter-provincial spot transaction volume. The mathematical expression of the constraint is as follows: in, Indicates unit U i The output plan increment based on the pre-planned basis, Indicates the tie line T i Planned increments based on pre-planned Indicates unit U i The node is about the contact line T i sensitivity, S(U) represents the set of all units in province S, S(T) represents the set of all tie lines in province S, and R(U) represents the set of all units in region R; The tidal current value of the key section in the province should be less than the upper limit of the section and greater than the lower limit of the section. The mathematical expression of the tidal current limit constraint of the key section is as follows: in, Indicates unit U i The node is about the key section E i The sensitivity of Indicates section E i The initial flow is the flow value calculated according to the pre-plan. Indicates section E i The upper limit of the trend, Indicates section E i The lower limit of the tide.

5. The inter-provincial spot transaction clearing optimization method considering key section condition limits according to claim 1 is characterized in that: The power won by the market entities includes the winning bids of the market entities at the power purchasing node and the winning bids of the market entities at the power selling node. The winning bids of the market entities at the power purchasing node are the declared demand matched in order from high to low according to the declared prices of the market entities at the power purchasing node; the winning bids of the market entities at the power selling node are the declared demand matched in order from low to high according to the declared prices of the market entities at the power selling node; The market entity clearing price includes a segmented curve quoted by the power purchase transaction node or the power sales transaction point according to the declared quantity, which is matched in sequence from high to low according to the declared price, and the arithmetic average of the declared segment price of the power purchase transaction node and the declared segment price of the power sales transaction node that are finally matched.

6. An inter-provincial spot transaction clearing optimization system considering key section condition limits, characterized in that: include: Inter-provincial spot clearing module, used to obtain boundary data and establish a general inter-provincial spot clearing model; The conditional section limit module is used to obtain the section limit effective conditions and build a conditional section limit model; The key section flow module is used to obtain the basic data of the key section flow calculation in the province and build the key section flow model in the province; The optimization module is used to take social welfare maximization as the optimization objective function, consider the constraints of the general inter-provincial spot clearing model, the conditional section limit model constraints, and the provincial key section flow model constraints to construct an inter-provincial spot transaction clearing model considering the key section conditional limits, and optimize and solve the clearing model to obtain the winning electricity and clearing price of market entities.

7. The inter-provincial spot transaction clearing optimization system considering key section condition limits according to claim 6 is characterized in that: The inter-provincial spot clearing module is used to obtain boundary data and establish a general inter-provincial spot clearing model; The general inter-provincial spot clearing model includes a social welfare maximization optimization objective function, a transaction flow balance constraint, a transmission channel capacity constraint, and a transaction node transaction volume constraint; The mathematical expression of the social welfare maximization objective function is as follows: Where ΔP b (m, A) and ΔP s (m, A) respectively represent the winning bids of power purchase transaction node b and power sales transaction node s in the declaration segment m of transaction path A, BTR and OTR respectively represent the mapping relationship matrices between power purchase nodes, power sales nodes and the transaction paths they participate in, OTR(s, A) = 1 means that power sales node s participates in transaction path A, OTR(s, A) = 0 means that power sales node s does not participate in transaction path A, similarly BTR(b, A) = 1 means that power purchase node b participates in transaction path A, BTR(s, A) = 0 means that power purchase node b does not participate in transaction path A, λ m，A (b) and λ m，A (s) represents the declared price of the power purchasing node b and the power selling node s in the declared period m; The mathematical expression of the transaction flow balance constraint is as follows: Among them, P s (A) represents the transaction power of the power selling node s in the transaction path A, P b (A) represents the transaction power of the power purchasing node b in the transaction path; The mathematical expression of the transmission channel capacity constraint is as follows: Wherein, TR(A, l) represents the mapping relationship matrix between transaction path and transmission channel. When TR(A, l) = 1, it means that the transaction path A contains the transmission channel l. When TR(A, l) = 0, it means that the transaction path A does not contain the transmission channel l. L (l) represents the base flow value of transmission channel l before inter-provincial spot clearing, represents the fixed upper limit of the power flow of transmission channel l, T L (l) represents the fixed power flow lower limit of transmission channel l; The mathematical expression of the transaction node volume constraint is as follows: in, and They represent the maximum values ​​of the tradable quantities of the power selling node s and the power purchasing node b respectively.

8. The inter-provincial spot transaction clearing optimization system considering key section condition limits according to claim 6 is characterized in that: The conditional section limit module is used to obtain the section limit effective conditions and build a conditional section limit model; The conditional section limit model includes the setting of auxiliary decision variables for conditional section limit, calculation of effective limit value and corresponding conditional variable constraints when the limit value takes effect; The setting of auxiliary decision variables for conditional section limit includes: setting multiple groups of auxiliary decision variables with values ​​of 0 or 1 based on the effective conditions of section limit, and the auxiliary decision variables satisfy the state constraint that the sum of each group of variables is always equal to 1. The mathematical model of the state constraint is as follows: in, Indicates the mth group of conditional section limit n Auxiliary decision variables for the effective conditions; The calculation of the effective limit value based on the auxiliary decision variables includes: the effective limit value belongs to the optional limit set, the number of optional limits is equal to the product of the number of segmented value spaces of the limit effective condition and the number of condition groups, and the effective limit value of each condition section is unique, and its value is equal to the product of all optional limits and all associated auxiliary decision variables of the corresponding effective condition. The mathematical model is as follows: in, Indicates the effective limit of the conditional section. It means that the m1th effective condition in the first group, the m2th effective condition in the second group, and so on until the mth effective condition in the nth group. n The cross-sectional limit that takes effect under the combined effect of the three effective conditions; The mathematical model for constructing conditional variable constraints corresponding to the effective limit based on auxiliary decision variables is as follows: Among them, p n The condition variable representing the nth set of effective conditions, and The mth group of n n The lower and upper bounds of the value space corresponding to the effective conditions.

9. The inter-provincial spot transaction clearing optimization system considering key section condition limits according to claim 6 is characterized in that: The key section flow module is used to obtain the basic data of the key section flow calculation in the province and construct the key section flow model in the province; the key section flow model in the province includes: key section flow increment calculation and key section flow limit constraint; The flow increment is calculated by the sum of the pre-planned increment of all key node units and the pre-planned increment of the tie line gateway multiplied by the sensitivity of the node; the key section flow value is calculated by adding the incremental flow and the initial flow, and must meet the key section flow limit constraints within the province; The sum of the pre-planned increments of the key node units in each province satisfies the sum of the pre-planned increments of the tie line gateways, that is, the constraint that it is equal to the inter-provincial spot transaction volume. The mathematical expression of the constraint is as follows: in, Indicates unit U i The output plan increment based on the pre-planned basis, Indicates the tie line T i Planned increments based on pre-planned Indicates unit U i The node is about the contact line T i sensitivity, S(U) represents the set of all units in province S, S(T) represents the set of all tie lines in province S, and R(U) represents the set of all units in region R; The tidal current value of the key section in the province should be less than the upper limit of the section and greater than the lower limit of the section. The mathematical expression of the tidal current limit constraint of the key section is as follows: in, Indicates unit U i The node is about the key section E i The sensitivity of Indicates section E i The initial flow is the flow value calculated according to the pre-plan. Indicates section E i The upper limit of the trend, Indicates section E i The lower limit of the tide.

10. The inter-provincial spot transaction clearing optimization system considering key section condition limits according to claim 6 is characterized in that: The optimization module is used to take social welfare maximization as the optimization objective function, consider the constraints of the general inter-provincial spot clearing model, the constraints of the conditional section limit model, and the constraints of the provincial key section power flow model to construct an inter-provincial spot transaction clearing model considering the key section conditional limit, and optimize and solve the clearing model to obtain the winning power and clearing price of the market entity; The power won by the market entities includes the winning bids of the market entities at the power purchasing node and the winning bids of the market entities at the power selling node. The winning bids of the market entities at the power purchasing node are the declared demand matched in order from high to low according to the declared prices of the market entities at the power purchasing node; the winning bids of the market entities at the power selling node are the declared demand matched in order from low to high according to the declared prices of the market entities at the power selling node; The market entity clearing price includes a segmented curve quoted by the power purchase transaction node or the power sales transaction point according to the declared quantity, which is matched in sequence from high to low according to the declared price, and the arithmetic average of the declared segment price of the power purchase transaction node and the declared segment price of the power sales transaction node that are finally matched.

11. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the inter-provincial spot transaction clearing optimization method considering key section condition limits according to any one of claims 1-5.

12. A storage medium storing a computer program, characterized in that: The computer program is designed to implement, when running, the inter-provincial spot transaction clearing optimization method taking into account key section condition limits as described in any one of claims 1 to 5.

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