Method for optimizing inter-provincial and inter-regional power output and related device

Abstract

The application belongs to the field of electric power automation, and discloses a cross-provincial and cross-regional electric energy optimization clearing method and related devices, which comprises the following steps: obtaining a cross-provincial and cross-regional power transmission channel available capacity calculation rule description set based on infix expression and analyzing the same to obtain cross-provincial and cross-regional power transmission channel available capacity rule variables; constructing cross-provincial and cross-regional power transmission channel dynamic constraints according to the cross-provincial and cross-regional power transmission channel available capacity rule variables; performing cross-provincial and cross-regional electric energy optimization clearing according to the cross-provincial and cross-regional power transmission channel dynamic constraints, combining cross-provincial and cross-regional power transmission channel static operation constraints, declared power constraints, transaction path association constraints, transaction combination price difference sequences and cross-provincial and cross-regional electric energy optimization clearing objective functions to obtain cross-provincial and cross-regional electric energy optimization clearing results. Based on the construction of the cross-provincial and cross-regional power transmission channel dynamic constraints, the power transmission right allocation is integrated into unified optimization, the clearing considering the dynamic change of the cross-provincial and cross-regional power transmission channel dynamic available capacity is realized, and the optimality and the executability of the clearing results are ensured.

Description

Technical Field

[0001] This invention belongs to the field of power automation and relates to a cross-provincial power energy optimization and clearing method and related devices. Background Technology

[0002] As power sector reform progresses, in order to accelerate the construction of an effectively competitive power market, it is necessary to establish a cross-provincial spot power trading mechanism through market-based means, further break down inter-provincial barriers, give full play to the role of the widely interconnected power grid as the main platform for the optimal allocation of energy resources, and promote the large-scale allocation of surplus and shortage resources across provinces and regions.

[0003] Currently, the inter-provincial spot market employs a clearing technique that considers inter-provincial transmission prices, grid losses, and available capacity. Before clearing calculations, the available capacity of inter-provincial transmission channels is calculated based on the current grid operation mode, inter-provincial channel limits, and pre-planning, forming the boundary conditions for clearing calculations. However, with the innovative mechanisms in the inter-provincial spot market, such as flexible switching between power purchase and sale roles and inter-provincial two-way transactions, the sending and receiving ends and power flow directions in the inter-provincial spot market are uncertain. The trading volume of inter-provincial and inter-regional transmission channels has further expanded, and the direction of transactions is uncertain, posing significant challenges to market optimization and clearing.

[0004] Existing optimization clearing methods struggle to accurately guarantee the optimality of clearing results under complex computational constraints. Furthermore, the clearing results may alter the pre-determined grid operation mode, thereby changing channel coupling relationships and causing the clearing results to fail to meet grid operation constraints, making effective implementation difficult. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a cross-provincial power energy optimization and clearing method and related apparatus.

[0006] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, this invention provides a method for optimizing and clearing cross-provincial power consumption, comprising: acquiring and parsing a set of rules for calculating the available capacity of cross-provincial transmission channels based on infix expressions to obtain rule variables for the available capacity of cross-provincial transmission channels; constructing dynamic constraints for cross-provincial transmission channels based on the rule variables for the available capacity of cross-provincial transmission channels; and performing cross-provincial power consumption optimization and clearing based on the dynamic constraints of cross-provincial transmission channels, combined with static operation constraints, declared power constraints, transaction path association constraints, transaction combination price difference sequences, and the objective function for optimizing and clearing cross-provincial power consumption, to obtain the result of optimizing and clearing cross-provincial power consumption.

[0007] Optionally, the step of obtaining and parsing the set of rules for calculating the available capacity of inter-provincial transmission channels based on infix expressions includes: obtaining the set of rules for calculating the available capacity of inter-provincial transmission channels based on infix expressions through a human-machine interface; using the set of rules for calculating the available capacity of inter-provincial transmission channels based on infix expressions as logical expressions and parsing them in the following manner: obtaining the type and number of each parameter in the logical expression, and obtaining the initial value of each parameter for each time period; decoupling logical expressions whose initial values ​​change in adjacent time periods based on the fluctuation of the initial values ​​of each parameter for each time period, and merging logical expressions with the same initial value; In this process, when a logical expression has a multi-layered logical structure, the symbol "()" in the logical expression is searched to determine the logical layer, and the layered logical expression is preprocessed: when the first symbol of the layered logical expression is "+" or "-", 0 is added before the symbol "+" or "-", and the decision node branches of the layered logical expression are analyzed layer by layer using the hierarchical analysis method; based on the reverse Polish notation, the infix expression form of the logical expression is converted into the postfix expression form to form a rule set of available capacity for inter-provincial transmission channels, and the rule variables of available capacity for inter-provincial transmission channels are constructed according to the rule set of available capacity for inter-provincial transmission channels using the following formula: Does not meet the requirements of Article 1 i One rule Conforms to the i One rule in, express t Inter-provincial power transmission channels d Available capacity rule variables.

[0008] Optionally, constructing dynamic constraints for inter-provincial power transmission channels based on available capacity rule variables includes: constructing dynamic constraints for inter-provincial power transmission channels based on available capacity rule variables.

[0009]

[0010]

[0011] in, express t Inter-provincial power transmission channels d Maximum transmission power, express t Inter-provincial power transmission channels d Minimum transmission power, and They represent t Inter-provincial power transmission channels d In thei The available capacity rules define forward and reverse transaction limits. For inter-provincial power transmission channels d The total number of available capacity rules.

[0012] Optionally, the trading portfolio spread sequence is obtained by: acquiring all trading portfolios within each trading period; converting the buyer's bid price in each trading portfolio to the seller's bid price and subtracting it from the seller's bid price to obtain the spread of each trading portfolio; sorting the spreads of each trading portfolio from largest to smallest, and removing trading portfolios with spreads less than 0 to obtain the trading portfolio spread sequence.

[0013] Optionally, the objective function for cross-provincial / regional energy optimization and clearing is:

[0014] in, To clear out the overall economic situation across provincial regions, for t Time period n The price difference of each trading combination, for t Time period n The transaction power of each trading combination T For the number of time periods, For time period t The number of transaction combinations.

[0015] Optionally, the static operating constraints of the inter-provincial power transmission channel include: Maximum available capacity constraints for inter-provincial power transmission channels:

[0016] in, express t Inter-provincial power transmission channels d Maximum transmission power, express t Inter-provincial power transmission channels d Minimum transmission power, for t Inter-provincial power transmission channels d The initial planned transmission power value; for t Inter-provincial power transmission channels d Electricity transactions; Maximum ramping power constraint for inter-provincial power transmission channels:

[0017] And the minimum ramp power constraint for inter-provincial power transmission channels:

[0018] in, for t Inter-provincial power transmission channels d Minimum climbing power, for t Inter-provincial power transmission channels d Maximum climbing power.

[0019] Optionally, the declared power constraints include: power constraints for electricity sales in the trading portfolio:

[0020]

[0021]

[0022] in, for t Time-based trading combinations n Electricity transactions, This is a correlation matrix between trading combinations and electricity sales price segments. for t Time period seller quote segment i With trading portfolio n The correlation coefficient, for t Time-based trading combinations n The corresponding seller's quotation segment number, Trading session t The number of transaction combinations, for t Time period seller quote segment i The declared electricity; And the power purchase constraints of the trading portfolio:

[0023]

[0024]

[0025] in, This is a correlation matrix between transaction portfolios and electricity purchase price ranges. for t Buyer's quote range j With trading portfolio n The correlation coefficient, for t Time-based trading combinations n The corresponding buyer's quotation segment number, for t Time-based trading combinations nNetwork loss rate corresponding to the transaction path, for t Time period seller quote segment j The declared electricity; The transaction path association constraints include: transaction combination and transaction path association constraints.

[0026]

[0027]

[0028] in, for t Trading Path p Electricity transactions; for t Correlation matrix between time-of-day trading combinations and trading paths; for t Trading Paths and Combinations by Time Period n The correlation coefficient; for t Time-based trading combinations n The corresponding transaction path number; And the constraints related to the transaction path and inter-provincial power transmission channels:

[0029]

[0030]

[0031] in, E The power flow transfer factor matrix for transaction paths and inter-provincial transmission channels; For transaction path h Transmission channels between provinces and regions d The power transfer factor; For transaction path h The first in k Inter-provincial power transmission channels d Network loss; For inter-provincial power transmission channels d In the transaction path h The serial number in; for t Trading Path p Electricity transactions; for t Inter-provincial power transmission channels d Electricity transactions.

[0032] In a second aspect, the present invention provides a cross-provincial power energy optimization and clearing system, comprising: a rule acquisition module, used to acquire and parse a set of cross-provincial transmission channel available capacity calculation rule descriptions based on infix expressions to obtain cross-provincial transmission channel available capacity rule variables; a dynamic constraint construction module, used to construct cross-provincial transmission channel dynamic constraints based on cross-provincial transmission channel available capacity rule variables; and an optimization and clearing module, used to perform cross-provincial power energy optimization and clearing based on the cross-provincial transmission channel dynamic constraints, combined with cross-provincial transmission channel static operation constraints, declared power constraints, transaction path association constraints, transaction combination price difference sequence, and cross-provincial power energy optimization and clearing objective function, to obtain cross-provincial power energy optimization and clearing results.

[0033] In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described cross-provincial power optimization and clearing method.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described cross-provincial power energy optimization and clearing method.

[0035] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method for optimizing and clearing inter-provincial power energy. It obtains and parses a set of rules describing the available capacity calculation of inter-provincial transmission channels based on infix expressions, thus generating rule variables for the available capacity of these channels. Then, it constructs dynamic constraints for the inter-provincial transmission channels based on these rule variables. By employing an infix-based method for describing the available capacity calculation rules, it facilitates intuitive operations for planners, such as adding, modifying, and querying scheduling rules. The constraints for clearing calculations can be adjusted by modifying the descriptions of the available capacity calculation rules, and the rules are converted into clearing constraints, avoiding frequent modifications to the clearing calculation program due to rule changes. Furthermore, based on the dynamic constraints of inter-provincial transmission channels, the static operation constraints of inter-provincial transmission channels, the power application constraints, the transaction path correlation constraints, and the transaction portfolio price difference sequence, the optimization clearing is carried out in conjunction with the objective function of inter-provincial power energy optimization clearing. Based on the construction of the dynamic constraints of inter-provincial transmission channels, the allocation of transmission rights is incorporated into the unified optimization, so as to realize the optimization clearing of inter-provincial power energy considering the dynamic changes of the dynamic available capacity of inter-provincial transmission channels, thereby ensuring the optimality of the clearing result and the executability of the clearing result. Attached Figure Description

[0036] Figure 1This is a flowchart of the cross-provincial power energy optimization and clearing method according to an embodiment of the present invention.

[0037] Figure 2 This is a flowchart illustrating the analysis of the rules for calculating the available capacity of inter-provincial power transmission channels based on infix expressions, according to an embodiment of the present invention.

[0038] Figure 3 This is a structural block diagram of the cross-provincial power energy optimization and clearing system according to an embodiment of the present invention. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0041] First, let's introduce the relevant terminology used in the embodiments of this invention: Electricity spot market: The general term for electricity trading activities conducted on a trading platform within a short period of time, up to the next day or within the same day. The underlying asset of cross-provincial electricity spot market is electrical energy.

[0042] Power transmission channels: Branch lines of electrical equipment such as lines and transformers that connect regions.

[0043] Available transmission capacity (ATC): The remaining transmission capacity in the actual physical transmission network that is available for commercial use, based on existing transmission contracts.

[0044] Power transmission network loss: Power loss in the form of heat during the transmission of electrical energy, which is the active power consumed by resistance and conduction.

[0045] Transmission price: The price paid for transmitting electrical energy through transmission channels.

[0046] Transaction clearing: Based on the "electricity-price" curves declared by both buyers and sellers, a centralized clearing process is carried out with the goal of maximizing social welfare, providing the quantity and price of the transactions reached between buyers and sellers.

[0047] Dynamic constraints: In the clearing calculation, the transmission capacity constraints of inter-provincial transmission channels change according to certain logical relationships based on the cleared power of inter-provincial transmission channels.

[0048] Infix expressions: Infix expressions are a general method of representing arithmetic or logical formulas, where operators are placed in infix form between operands. Infix expressions are a commonly used method of arithmetic representation. They support logic such as equal to, if, greater than or equal to (>=), and less than or equal to (<=). Each part consists of several functions, and each function has two parameters, which can be constants, variables, or functions. The parameters support logic such as addition, subtraction, multiplication, taking the larger (max), taking the smaller (min), greater than or equal to (>=), less than or equal to (<=), equal to (==), AND (&), and OR (||).

[0049] As described in the background section, the current electricity spot market clearing method involves ordering buyer bids from highest to lowest and seller bids from lowest to highest. The highest bidder and the lowest bidder are given priority for transaction, and clearing proceeds sequentially according to the principle of decreasing price difference, until all electricity bids are executed or the buyer's bid is lower than the seller's bid, at which point the transaction ends.

[0050] The above scheme has the following main drawbacks: First, it is difficult to guarantee the maximization of overall social welfare from the market clearing outcome. While the transmission rights allocation method based on price difference order can maximize social welfare at each clearing step, it sometimes fails to guarantee the maximization of overall social welfare when inter-provincial and cross-regional transmission channel congestion is frequent. Second, static constraints on the available capacity of transmission channels may limit the completion of transactions. The operation constraints of UHV AC / DC power grids are complex, and there are coupling relationships between transmission channels. Increased trading volume and changes in trading direction will alter the original power grid operation mode, thereby changing the coupling relationships between transmission channels. The available capacity of transmission channels determined before the clearing calculation may not be able to guarantee the maximization of trading volume.

[0051] As power system reform progresses, it is necessary to conduct cross-provincial and regional spot power transactions through market-based means, adapt to the pricing mechanism of cross-provincial and regional transmission channels, and meet the increasingly complex operating characteristics of long-distance, chain-relay transmission channels, so as to promote the large-scale allocation of surplus and shortage resources across provinces and regions.

[0052] The present invention will now be described in further detail with reference to the accompanying drawings: See Figure 1 In one embodiment of the present invention, a cross-provincial power energy optimization clearing method is provided. Specifically, it is a cross-provincial power energy optimization clearing method that considers the dynamic constraints of cross-provincial transmission channels. By incorporating the allocation of transmission rights into the unified optimization in the clearing calculation, the dynamic construction of the available capacity constraints of cross-provincial transmission channels is realized, thereby realizing an optimization clearing method that considers the dynamic available capacity of cross-provincial transmission channels.

[0053] Specifically, the cross-provincial / regional power energy optimization and clearing method of the present invention includes the following steps: S1: Obtain and parse the set of rules for calculating the available capacity of inter-provincial transmission channels based on infix expressions to obtain the rule variables for the available capacity of inter-provincial transmission channels.

[0054] S2: Construct dynamic constraints for inter-provincial power transmission channels based on the available capacity rule variables of the inter-provincial power transmission channels.

[0055] S3: Based on the dynamic constraints of inter-provincial power transmission channels, combined with the static operation constraints of inter-provincial power transmission channels, the declared power constraints, the transaction path correlation constraints, the transaction combination price difference sequence, and the objective function for the optimization and clearing of inter-provincial power, the optimization and clearing results of inter-provincial power are obtained.

[0056] This invention provides a method for optimizing and clearing inter-provincial power energy. It obtains and parses a set of rules describing the available capacity calculation of inter-provincial transmission channels based on infix expressions, thus generating rule variables for the available capacity of these channels. Then, it constructs dynamic constraints for the inter-provincial transmission channels based on these rule variables. By employing an infix-based method for describing the available capacity calculation rules, it facilitates intuitive operations for planners, such as adding, modifying, and querying scheduling rules. The constraints for clearing calculations can be adjusted by modifying the descriptions of the available capacity calculation rules, and the rules are converted into clearing constraints, avoiding frequent modifications to the clearing calculation program due to rule changes. Furthermore, based on the dynamic constraints of inter-provincial transmission channels, the static operation constraints of inter-provincial transmission channels, the power application constraints, the transaction path correlation constraints, and the transaction portfolio price difference sequence, the optimization clearing is carried out in conjunction with the objective function of inter-provincial power energy optimization clearing. Based on the construction of the dynamic constraints of inter-provincial transmission channels, the allocation of transmission rights is incorporated into the unified optimization, so as to realize the optimization clearing of inter-provincial power energy considering the dynamic changes of the dynamic available capacity of inter-provincial transmission channels, thereby ensuring the optimality of the clearing result and the executability of the clearing result.

[0057] In one possible implementation, the step of obtaining and parsing the set of rules for calculating the available capacity of inter-provincial transmission channels based on infix expressions includes: obtaining the set of rules for calculating the available capacity of inter-provincial transmission channels based on infix expressions through a human-machine interface; using the calculation rule descriptions of the available capacity of inter-provincial transmission channels based on infix expressions in the set of calculation rule descriptions as logical expressions and parsing them in the following manner: obtaining the type and number of each parameter in the logical expression, and obtaining the initial value of each parameter for each time period; based on the fluctuation of the initial value of each parameter for each time period, decoupling logical expressions whose initial values ​​change in adjacent time periods, and merging logical tables with the same initial value. The expression is described in the following formula: When the logical expression is a multi-level logical structure, the symbol "()" in the logical expression is searched to determine the logical layer and the logical expression is preprocessed after layering: when the first symbol of the layered logical expression is "+" or "-", 0 is added before the symbol "+" or "-", and the decision node branches of the logical expression layer by layer are analyzed by using the hierarchical analysis method; based on the reverse Polish notation, the infix expression form of the logical expression is converted into the postfix expression form to form a set of rules for the available capacity of inter-provincial transmission channels, and the rule variables for the available capacity of inter-provincial transmission channels are constructed according to the rule set of rules for the available capacity of inter-provincial transmission channels using the following formula: Does not meet the requirements of Article 1 i One rule Conforms to the i One rule in, express t Inter-provincial power transmission channels d Available capacity rule variables.

[0058] Specifically, a rule description for calculating the available capacity of inter-provincial transmission channels is established. Infix expressions are used to describe the logical relationships of business models such as inter-provincial transmission channels, dispatching equipment (generators, power plants, converters), and trading components, and this is displayed through a human-machine interface. Then, the rule description of the available capacity of inter-provincial transmission channels is parsed and modeled. The rule description is used as a logical expression, the type of the logical expression is identified, the attribute state quantities of the parameters are retrieved and obtained, the infix expression form is converted to postfix form, and constraints in the optimized clearing model are generated. See also... Figure 2The parsing process in this implementation is as follows: 1. Read in the logical expression, obtain and compile the basic information of the rule. 2. Parse the type and number of each parameter in the logical expression, call the attribute state quantity acquisition function, and obtain the initial values ​​of the 96 parameters. 3. Determine whether the logical expression is a multi-level logical structure. If it is, use the hierarchical analysis method to parse the decision node branches of the logical expression layer by layer. 4. Based on the fluctuation of the initial values ​​of the 96 parameters, decouple the logical expressions whose initial values ​​change in adjacent time periods, merge logical expressions with the same initial values, and compress the number of logical expressions to be calculated. 5. Since the calculation variables and parameters are all integer types, the special symbols in the logical expression can be logically negated to meet the requirements of the optimization model. 6. Based on the reverse Polish notation, convert the infix form of the logical expression into the postfix form, and store it in the rule base along with the basic information to construct the optimization model.

[0059] Specifically, based on the parsing method described in the above-mentioned inter-provincial transmission channel available capacity calculation rules, the type of logical expression can be automatically identified, the attribute status quantities of the parameters can be retrieved and obtained, and the logical expression in infix form can be converted into postfix form, thereby transforming the semi-natural language form of the inter-provincial transmission channel available capacity calculation rules description into a description form that is easy for the program to process.

[0060] In one possible implementation, constructing dynamic constraints for inter-provincial power transmission channels based on available capacity rule variables includes: constructing dynamic constraints for inter-provincial power transmission channels based on available capacity rule variables.

[0061]

[0062]

[0063] in, express t Inter-provincial power transmission channels d Maximum transmission power, express t Inter-provincial power transmission channels d Minimum transmission power, and They represent t Inter-provincial power transmission channels d In the i The available capacity rules define forward and reverse transaction limits. For inter-provincial power transmission channels d The total number of available capacity rules.

[0064] Specifically, based on the parsed set of rules for calculating the available capacity of inter-provincial transmission channels, state variables corresponding to the rules are set and incorporated into the optimization and clearing model. The values ​​of the state parameters are automatically identified, and the dynamic available capacity of the inter-provincial transmission channels is calculated through the dynamic constraint equations of the inter-provincial transmission channels to support the clearing calculation.

[0065] In one possible implementation, the trading portfolio spread sequence is obtained by: acquiring all trading portfolios within each trading period; converting the buyer's bid price in each trading portfolio to the seller's bid price and subtracting it from the seller's bid price to obtain the spread of each trading portfolio; sorting the spreads of each trading portfolio from largest to smallest, and removing trading portfolios with spreads less than 0 to obtain the trading portfolio spread sequence.

[0066] Specifically, obtaining the spread sequence of a trading portfolio can be broken down into the following steps: 1. Prepare application data: Obtain application data information from market participants through the electricity spot trading system, such as market participant name, time-of-use electricity application, time-of-use electricity price, and number of time-of-use electricity price segments.

[0067] 2. Construction of Transaction Portfolio Sets. Within the same trading session, a transaction portfolio is formed by any segment of bids from the buyer, any segment of bids from the seller, and feasible trading paths between the buyer and seller. Each transaction portfolio includes the buyer's bid electricity, the buyer's bid electricity price, the seller's bid electricity, the seller's bid electricity price, the trading path, the buyer's executed electricity, and the seller's executed electricity. The set of all transaction portfolios within the same trading session is called the transaction portfolio set. Transaction portfolio sets are constructed separately for each trading session according to the trading session to which the bid data belongs.

[0068] 3. Calculation of the price spread for the trading combination. Based on the transmission price and transmission loss rate of the transmission channels along the trading path, the buyer's declared electricity and price are converted to the seller's price. The difference between the buyer's declared price and the seller's declared price is the price spread for this trading combination. The specific calculation formula is as follows:

[0069]

[0070]

[0071] in, This represents the network loss rate for the trading path corresponding to the trading portfolio. For the first in the transaction path h The network loss rate of inter-provincial power transmission channels, H This represents the total number of inter-provincial power transmission channels in the transaction path. h This refers to the sequence number of the inter-provincial power transmission channel within this transaction path. The transmission price of the trading path corresponding to the trading combination. For the first in the transaction path h The transmission price of inter-provincial power transmission channels. Declare electricity for the buyer, The electricity declared by the buyer is converted to the electricity declared by the seller based on the network loss.

[0072] 4. Generate a trading portfolio spread sequence. Sort all trading portfolios in descending order of spread to form a trading portfolio spread sequence, and remove trading portfolios with a spread less than 0.

[0073] In one possible implementation, the cross-provincial energy optimization clearing objective function is:

[0074] in, To clear out the overall economic situation across provincial regions, for t Time period n The price difference of each trading combination, for t Time period n The transaction power of each trading combination T For the number of time periods, For time period t The number of transaction combinations.

[0075] Specifically, an objective function for optimizing the clearing of inter-provincial electricity is established. Electricity clearing is based on buyer and seller bids, considering the available capacity of inter-provincial transmission channels, transmission prices of inter-provincial transmission channels, regional power grids, and seller's power grids, as well as network losses. The clearing objective aims to maximize the overall economic efficiency, i.e., social welfare, of the inter-provincial clearing process. Social welfare is the sum of the social welfare of each trading combination, and the social welfare of each trading combination is the product of its economic efficiency and the amount of electricity traded. This optimization objective is based on the bid prices and bid amounts from both buyers and sellers, using the traded electricity of each trading combination in each time period as the decision variable, thereby obtaining the traded electricity of the trading combination under the objective of maximizing social benefit.

[0076] In one possible implementation, the static operation constraints of the inter-provincial power transmission channel include: the maximum available capacity constraint of the inter-provincial power transmission channel, the maximum ramp power constraint of the inter-provincial power transmission channel, and the minimum ramp power constraint of the inter-provincial power transmission channel. These constraints are established based on the pre-planned, maximum and minimum transmission power limits, power ramp-up limits, and power ramp-down limits of the inter-provincial power transmission channel.

[0077] Among them, the maximum available capacity constraint for inter-provincial power transmission channels is:

[0078] in, express t Inter-provincial power transmission channels d Maximum transmission power, express t Inter-provincial power transmission channels d Minimum transmission power, for t Inter-provincial power transmission channels d The initial planned transmission power value; for t Inter-provincial power transmission channels d Electricity transactions.

[0079] Maximum ramping power constraint for inter-provincial power transmission channels:

[0080] Minimum ramp power constraint for inter-provincial power transmission channels:

[0081] in, for t Inter-provincial power transmission channels d Minimum climbing power, for t Inter-provincial power transmission channels d Maximum climbing power.

[0082] In one possible implementation, the declared power constraints include power selling constraints and power buying constraints for the trading portfolio. By obtaining the declared power and electricity price of each market participant, the trading portfolio corresponding to the quoted price segment is matched, requiring that the power selling of the trading portfolio should be less than the declared power selling, and that the power buying of the trading portfolio should be less than the declared power buying, thereby establishing the trading portfolio.

[0083] Among them, the electricity sales constraints of the trading portfolio are:

[0084]

[0085]

[0086] in, for t Time-based trading combinations n Electricity transactions, This is a correlation matrix between trading combinations and electricity sales price segments. for t Time period seller quote segment i With trading portfolio n The correlation coefficient, fort Time-based trading combinations n The corresponding seller's quotation segment number, Trading session t The number of transaction combinations, for t Time period seller quote segment i The declared electricity.

[0087] Electricity purchase constraints for the trading portfolio:

[0088]

[0089]

[0090] in, This is a correlation matrix between transaction portfolios and electricity purchase price ranges. for t Buyer's quote range j With trading portfolio n The correlation coefficient, for t Time-based trading combinations n The corresponding buyer's quotation segment number, for t Time-based trading combinations n Network loss rate corresponding to the transaction path, for t Time period seller quote segment j The declared electricity.

[0091] In one possible implementation, the transaction path association constraints include the association constraints between transaction combinations and transaction paths, as well as the association constraints between transaction paths and inter-provincial power transmission channels. By obtaining the electricity and electricity prices declared by each market participant, transaction combinations corresponding to the quoted price segment are matched, requiring that the electricity sold in the transaction combination should be less than the declared electricity sold, and the electricity purchased in the transaction combination should be less than the declared electricity purchased, thereby establishing the transaction path.

[0092] Among them, the constraints related to the trading portfolio and trading path are as follows:

[0093]

[0094]

[0095] in, for t Trading Path p Electricity transactions; for tCorrelation matrix between time-of-day trading combinations and trading paths; for t Trading Paths and Combinations by Time Period n The correlation coefficient; for t Time-based trading combinations n The corresponding transaction path number.

[0096] Constraints related to the transaction path and inter-provincial power transmission channels:

[0097]

[0098]

[0099] in, E The power flow transfer factor matrix for transaction paths and inter-provincial transmission channels; For transaction path h Transmission channels between provinces and regions d The power transfer factor; For transaction path h The first in k Inter-provincial power transmission channels d Network loss; For inter-provincial power transmission channels d In the transaction path h The serial number in; for t Trading Path p Electricity transactions; for t Inter-provincial power transmission channels d Electricity transactions.

[0100] In one possible implementation, the data preparation for cross-provincial power energy optimization clearing includes: acquiring and preparing a cross-provincial spot trading network model through the power spot trading system, such as basic data like trading nodes, trading channels, regional information, market member information, tie-line information, and trading path information.

[0101] When conducting cross-provincial power energy optimization and clearing, the branch-and-bound method is used for calculation, and the clearing results are output to the power spot trading system after the clearing calculation is completed to guide the power system dispatching process.

[0102] By establishing an objective function based on the price difference of trading portfolios, the transmission price and network loss of inter-provincial transmission channels can be accurately considered, ensuring the optimality of the clearing result. Simultaneously, static and dynamic constraint equations for electricity purchase and sale declarations, trading path correlations, and inter-provincial transmission channels are established to ensure the executability of the clearing result.

[0103] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0104] See Figure 3 In another embodiment of the present invention, a cross-provincial power energy optimization and clearing system is provided, which can be used to implement the above-mentioned cross-provincial power energy optimization and clearing method. Specifically, the cross-provincial power energy optimization and clearing system includes a rule acquisition module, a dynamic constraint construction module, and an optimization and clearing module.

[0105] The system comprises three modules: a rule acquisition module, a dynamic constraint construction module, and an optimization clearing module. The former is used to acquire and parse the rule description set for calculating the available capacity of inter-provincial transmission channels based on infix expressions, thereby obtaining the rule variables for the available capacity of inter-provincial transmission channels. The latter is used to construct dynamic constraints for inter-provincial transmission channels based on the rule variables for the available capacity of inter-provincial transmission channels. The latter is used to perform optimization clearing of inter-provincial power based on the dynamic constraints of inter-provincial transmission channels, combined with static operation constraints, declared power constraints, transaction path association constraints, transaction combination price difference sequence, and the objective function for optimization clearing of inter-provincial power, thereby obtaining the optimization clearing result of inter-provincial power.

[0106] All relevant content of each step involved in the aforementioned embodiments of the cross-provincial and regional power optimization and clearing method can be referenced to the functional description of the corresponding functional module of the cross-provincial and regional power optimization and clearing system in the embodiments of the present invention, and will not be repeated here.

[0107] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0108] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can be used for the operation of a cross-provincial / regional power energy optimization and clearing method.

[0109] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the cross-provincial power energy optimization and clearing method in the above embodiments.

[0110] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0111] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0112] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0113] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing and clearing electrical energy across provinces and regions, characterized in that, include: Obtain and parse the rule description set for calculating the available capacity of inter-provincial transmission channels based on infix expressions to obtain the rule variables for the available capacity of inter-provincial transmission channels; Based on the available capacity rule variables of inter-provincial power transmission channels, dynamic constraints for inter-provincial power transmission channels are constructed; Based on the dynamic constraints of inter-provincial power transmission channels, combined with the static operation constraints of inter-provincial power transmission channels, the declared power constraints, the transaction path correlation constraints, the transaction combination price difference sequence, and the objective function for inter-provincial power energy optimization and clearing, the inter-provincial power energy optimization and clearing is carried out to obtain the inter-provincial power energy optimization and clearing results.

2. The cross-provincial / regional energy optimization and clearing method according to claim 1, characterized in that, The process of obtaining and parsing the rule description set for calculating the available capacity of inter-provincial power transmission channels based on infix expressions includes: The human-machine interface is used to obtain a set of rules for calculating the available capacity of inter-provincial power transmission channels based on infix expressions; The calculation rule descriptions for the available capacity calculation of inter-provincial transmission channels based on infix expressions in the aforementioned calculation rule description set are used as logical expressions and parsed in the following manner: Obtain the type and number of each parameter in the logical expression, and obtain the initial value of each parameter for each time period; Based on the fluctuation of the initial values ​​of each parameter in each time period, decouple logical expressions whose initial values ​​change in adjacent time periods and merge logical expressions with the same initial value; among them, when the logical expression is a multi-level logical structure, search for the symbol "(" in the logical expression to determine the logical layer and preprocess the logical expression after layering: when the first symbol of the layered logical expression is "+" or "-", add 0 before the symbol "+" or "-", and use the hierarchical analysis method to parse the decision node branches of the logical expression layer by layer; Based on the Reverse Polish Notation (RPN) method, the infix form of the logical expression is transformed into the postfix form, forming a rule set for the available capacity of inter-provincial transmission channels. Then, based on this rule set, the rule variables for the available capacity of inter-provincial transmission channels are constructed using the following formula: Does not meet the requirements of Article 1 i One rule Conforms to the i One rule in, express t Inter-provincial power transmission channels d Available capacity rule variables.

3. The cross-provincial / regional energy optimization and clearing method according to claim 2, characterized in that, The construction of dynamic constraints for inter-provincial power transmission channels based on available capacity rule variables includes: Based on the available capacity rule variables of inter-provincial power transmission channels, dynamic constraints for inter-provincial power transmission channels are constructed: in, express t Inter-provincial power transmission channels d Maximum transmission power, express t Inter-provincial power transmission channels d Minimum transmission power, and They represent t Inter-provincial power transmission channels d In the i The available capacity rules define forward and reverse transaction limits. For inter-provincial power transmission channels d The total number of available capacity rules.

4. The cross-provincial / regional energy optimization and clearing method according to claim 1, characterized in that, The price spread sequence of the trading portfolio is obtained in the following manner: Get all trading combinations within each trading session; The price difference between the buyer's bid price and the seller's bid price in each trading combination is obtained by converting the buyer's bid price to the seller's bid price. Sort the price differences of each trading combination from largest to smallest, and remove the trading combinations with price differences less than 0 to obtain the trading combination price difference sequence.

5. The cross-provincial / regional power energy optimization and clearing method according to claim 1, characterized in that, The objective function for cross-provincial / regional energy optimization and clearing is: in, To clear out the overall economic situation across provincial regions, for t Time period n The price difference of each trading combination, for t Time period n The transaction power of each trading combination T For the number of time periods, For time period t The number of transaction combinations.

6. The cross-provincial / regional energy optimization and clearing method according to claim 1, characterized in that, The static operation constraints of the inter-provincial power transmission channels include: Maximum available capacity constraints for inter-provincial power transmission channels: in, express t Inter-provincial power transmission channels d Maximum transmission power, express t Inter-provincial power transmission channels d Minimum transmission power, for t Inter-provincial power transmission channels d The initial planned transmission power value; for t Inter-provincial power transmission channels d Electricity transactions; Maximum ramping power constraint for inter-provincial power transmission channels: And the minimum ramp power constraint for inter-provincial power transmission channels: in, for t Inter-provincial power transmission channels d Minimum climbing power, for t Inter-provincial power transmission channels d Maximum climbing power.

7. The cross-provincial / regional energy optimization and clearing method according to claim 1, characterized in that, The declared power constraints include: Electricity sales constraints of the trading portfolio: in, for t Time-based trading combinations n Electricity transactions, This is a correlation matrix between trading combinations and electricity sales price segments. for t Time period seller quote segment i With trading portfolio n The correlation coefficient, for t Time-based trading combinations n The corresponding seller's quotation segment number, Trading session t The number of transaction combinations, for t Time period seller quote segment i The declared electricity; And the power purchase constraints of the trading portfolio: in, This is a correlation matrix between transaction portfolios and electricity purchase price ranges. for t Buyer's quote range j With trading portfolio n The correlation coefficient, for t Time-based trading combinations n The corresponding buyer's quotation segment number, for t Time-based trading combinations n Network loss rate corresponding to the transaction path, for t Time period seller quote segment j The declared electricity; The transaction path association constraints include: Constraints on the association between trading portfolio and trading path: in, for t Trading Path p Electricity transactions; for t Correlation matrix between time-of-day trading combinations and trading paths; for t Trading Paths and Combinations by Time Period n The correlation coefficient; for t Time-based trading combinations n The corresponding transaction path number; And the constraints related to the transaction path and inter-provincial power transmission channels: in, E The power flow transfer factor matrix for transaction paths and inter-provincial transmission channels; For transaction path h Transmission channels between provinces and regions d The power transfer factor; For transaction path h The first in k Inter-provincial power transmission channels d Network loss; For inter-provincial power transmission channels d In the transaction path h The serial number in; for t Trading Path p Electricity transactions; for t Inter-provincial power transmission channels d Electricity transactions.

8. A cross-provincial / regional power energy optimization and clearing system, characterized in that, include: The rule acquisition module is used to acquire and parse the rule description set for calculating the available capacity of inter-provincial transmission channels based on infix expressions, and obtain the rule variables for the available capacity of inter-provincial transmission channels. The dynamic constraint construction module is used to construct dynamic constraints for inter-provincial power transmission channels based on the available capacity rule variables of the inter-provincial power transmission channels. The optimization clearing module is used to optimize the clearing of inter-provincial power energy based on the dynamic constraints of inter-provincial power transmission channels, combined with the static operation constraints of inter-provincial power transmission channels, declared power constraints, transaction path association constraints, transaction combination price difference sequence, and the objective function of inter-provincial power energy optimization clearing, and to obtain the inter-provincial power energy optimization clearing result.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the cross-provincial power energy optimization and clearing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the cross-provincial power optimization clearing method as described in any one of claims 1 to 7.

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