Cross-regional power market clearing method, device and equipment for flexible direct current transmission system containing new energy

Abstract

This application relates to the field of data processing technology for power systems, and provides a method, apparatus, and equipment for clearing inter-regional power markets including new energy transmission via flexible DC transmission systems. The method includes acquiring the number of regions in the new energy DC transmission system, reactive power data for reserve requirements in each region, real-time electrical data, and day-ahead planned electrical data; constructing a day-ahead clearing optimization model based on the day-ahead planned electrical data and all reactive power demand data; determining whether to perform rolling corrections on the day-ahead clearing optimization model based on real-time electrical data and day-ahead planned electrical data, and constructing a rolling model based on real-time electrical data; correcting the day-ahead clearing optimization model using the rolling model to obtain settlement electrical data; and obtaining highly accurate inter-regional electricity settlement data based on the settlement electrical data, thus realizing a DC participation market mechanism chain that integrates electricity trading with ancillary services such as frequency regulation and reserve, with real-time physical execution and clear settlement responsibilities.

Description

Technical Field

[0001] This application relates to the field of data processing technology for power systems, and in particular to a method, apparatus and equipment for clearing inter-regional power markets including new energy sources transmitted via flexible DC transmission systems. Background Technology

[0002] With the increasing demand for the development of new energy bases and the optimization of resource allocation, large-scale new energy transmission to the receiving-end power grid via high-voltage direct current or flexible direct current has become an important operating mode of regional power systems.

[0003] Regarding the inclusion of DC tie lines in the regional spot market of the power system, existing technologies consider constraints such as the upper and lower limits of DC tie line power, AC / DC tie line ramping constraints, DC tie line network loss constraints, and DC frequency control regulation capability constraints in the regional spot clearing model. Further, there are also solutions that consider DC tie lines providing upward / downward capacity, embedding multi-terminal DC tie line power optimization, and tie line power planning parameters across two-tier regional markets. Existing regional spot market technologies that consider DC regulation capabilities primarily address resource optimization, i.e., incorporating the power boundaries and some regulation capabilities of DC tie lines into the optimized regional spot clearing model during the spot clearing phase, but their focus remains on the day-ahead market or clearing. However, the day-ahead trading results of regional spot clearing models are biased towards economic or financial markets, failing to fully consider the physical feasibility of DC in the real-time phase, constrained by ramp rate, direction switching, minimum duration, non-reverse regulation, and end-network security constraints.

[0004] Regarding the deviation correction and real-time physical execution of electrical energy and ancillary services, existing technologies, targeting the frequency regulation ancillary service market of the power system, optimize the frequency regulation ancillary services, electrical energy, and reserve ancillary services using an ancillary service compensation mechanism based on frequency regulation information, frequency regulation capacity demand, and frequency regulation mileage demand to obtain the day-ahead frequency regulation plan. Then, based on rolling updates, a rolling frequency regulation plan and a real-time frequency regulation plan are obtained, and finally, frequency regulation revenue is settled based on the real-time frequency regulation plan. Existing power system frequency regulation ancillary service markets consider reserve capacity constraints for joint clearing of electrical energy and frequency regulation ancillary services. Other technologies focus on the impact of market clearing results on the physical operation of the power grid, and the feedback from the physical operation of the power grid to the market. However, existing ancillary service compensation mechanisms mainly target conventional generating units and energy storage devices. While inter-regional DC interconnections, as flexible resources, can provide inter-provincial reserve support capacity and participate in the frequency regulation market, there is currently a lack of a mechanism to connect DC regulation capacity with reserve and frequency regulation ancillary service markets. Furthermore, there is a lack of quantitative methods for the opportunity costs, dynamic constraint costs, and deviation risk costs incurred when providing frequency regulation and reserve services to high-voltage DC lines.

[0005] Regarding the settlement of discrepancies between the day-ahead and real-time power markets in the power system, some technologies are geared towards inter-regional power trading settlement, calculating the contract portion first and then the discrepancy portion, with the discrepancy price obtained by weighting existing contract prices according to planned power volume. Other solutions utilize reference marginal costs under peak, flat, and valley load levels to replace real-time market prices, establishing a near-real-time pricing mechanism for discrepancy power. While existing discrepancy settlement technologies can handle the difference between planned and actual power volume, they focus primarily on the formation of discrepancy prices and the settlement of discrepancy charges. However, several issues remain: when high-voltage direct current (HVDC) lines are forced to deviate from the day-ahead planned curve due to unified power system dispatch, for which entity's safety, frequency support, or power balance is this discrepancy generated, and which beneficiary regions or entities should share the corresponding redistribution costs? Furthermore, in the context of renewable energy being transmitted via large-capacity HVDC lines, when the actual output of renewable energy at the sending end deviates, does this discrepancy translate into increased receiving-end balancing and reserve costs? Summary of the Invention

[0006] This application provides a method, apparatus, and equipment for clearing inter-regional electricity markets including new energy transmitted via flexible DC transmission systems, which addresses the technical problem of low accuracy in existing methods for clearing, correcting deviations, and settling inter-regional electricity transmitted via large-capacity DC transmission systems and their flexibility.

[0007] To achieve the above objectives, this application provides the following technical solution:

[0008] On the one hand, a method for clearing the inter-regional electricity market, including new energy sources transmitted via flexible DC transmission systems, is provided, comprising the following steps:

[0009] Obtain the number of regions with new energy DC transmission systems, reactive power data for the reserve demand of each region, real-time electrical data, and day-ahead planned electrical data;

[0010] Based on the day-ahead planned electrical data and all the day-ahead reactive power data, a model is constructed to obtain the day-ahead clearing optimization model of the cross-regional DC joint of the new energy DC transmission system.

[0011] Based on the real-time electrical data and the day-ahead planned electrical data, determine whether the trigger result for real-time rolling correction of the day-ahead clearing optimization model is met; if the trigger result is that the day-ahead clearing optimization model is met, then the model is constructed based on the real-time electrical data to obtain a deviation correction rolling model.

[0012] The rolling model is used to correct the day-ahead clearing optimization model to obtain settlement electrical data; based on the settlement electrical data, the cross-regional electricity settlement data of the new energy through the flexible DC transmission system is determined, and the cross-regional electricity settlement data includes day-ahead electricity settlement, day-ahead DC flexibility reservation settlement, and real-time adjustment settlement.

[0013] Optionally, the real-time electrical data includes rescheduling costs, wind and solar curtailment costs, default costs, real-time DC execution power, DC operating direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow, and real-time frequency deviation for each time period; a rolling model for deviation correction is constructed based on the real-time electrical data, including:

[0014] Based on the real-time DC execution power and the day-ahead reference power for each time period, determine the power deviation for the corresponding time period;

[0015] The DC constraint conditions are constructed based on the real-time DC execution power, the DC operating direction status data, the direction switching data, the real-time direction identification data, the real-time cross-sectional power flow, and the real-time frequency deviation.

[0016] Based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods, a function is constructed to obtain the real-time optimization objective function;

[0017] A model is constructed based on the real-time optimization objective function and the DC constraint conditions to obtain a rolling model for deviation correction.

[0018] Optionally, the day-ahead clearing optimization model includes clearing constraints. The rolling model is used to modify the day-ahead clearing optimization model to obtain settlement electrical data, including:

[0019] Using the day-ahead reference power output by the day-ahead clearing optimization model as a reference trajectory, the rolling optimization method is used to optimize and solve the rolling model to obtain the actual DC power and actual deviation for each time period.

[0020] Based on the actual DC power output and the actual deviation for each time period, determine the day-ahead reference power correction for the corresponding time period;

[0021] The day-ahead reference power supply correction power for each time period is used as the day-ahead reference power supply power for the corresponding time period. The day-ahead clearing optimization model output day-ahead clearing results are corrected according to the day-ahead reference power supply correction power for each time period and the clearing constraints, so as to obtain the day-ahead cross-regional transaction correction energy, the DC tie line upward correction capacity reserve and downward correction capacity reserve for the corresponding time period.

[0022] The settlement electrical data includes the actual deviation for each time period, the corrected electrical energy for cross-regional transactions before the day, and the reserved capacity for upward and downward adjustments of DC tie lines.

[0023] Optionally, the settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, and the upward and downward correction capacity reserves for DC interconnection lines; based on the settlement electrical data, the cross-regional electricity settlement data for the new energy transmitted through the flexible DC transmission system includes:

[0024] Obtain the day-ahead inter-regional electricity transaction price, the upward capacity reserve price, the downward capacity reserve price, and the real-time adjustment price for each time period;

[0025] The day-ahead electricity settlement is calculated based on the day-ahead inter-regional electricity transaction prices and the day-ahead inter-regional transaction adjusted electricity prices for all time periods.

[0026] The day-ahead DC flexibility reservation settlement is calculated based on the upward capacity reservation price, the downward capacity reservation price, the upward adjusted capacity reservation, and the downward adjusted capacity reservation for all time periods.

[0027] The real-time adjustment settlement is calculated based on the real-time adjusted price and the actual deviation for all time periods.

[0028] Optionally, the inter-regional power market clearing method that includes renewable energy transmitted via flexible DC transmission systems may also include:

[0029] Obtain the cost of new energy output deviation, the cost of unified system scheduling deviation, the attribution coefficient of new energy deviation for each new energy power station, the allocation coefficient for each region, and the responsible area and the responsible new energy power station of the responsible entity;

[0030] The new energy deviation cost of the corresponding new energy power station is calculated based on the new energy output deviation cost and the new energy deviation attribution coefficient of each new energy power station.

[0031] The system scheduling deviation cost for the corresponding region is calculated based on the unified system scheduling deviation cost and the allocation coefficient for each region.

[0032] Based on the calculation of all the new energy deviation costs corresponding to the responsible new energy power stations, as well as all the real-time adjustment settlements and system scheduling deviation allocation costs corresponding to the responsible regions, the total real-time settlement corresponding to the responsible entity is obtained, thereby realizing the attribution of responsibility and cost allocation for the actual adjustment and deviation of the cross-regional power settlement of new energy through the flexible DC transmission system.

[0033] On the other hand, a cross-regional power market clearing device with a new energy transmission system via flexible DC transmission is provided, including: a data acquisition module, a first model construction module, a second model construction module, and a correction settlement module;

[0034] The data acquisition module is used to acquire the number of regions of the new energy DC transmission system, the reactive power data of the reserve demand undertaken by each region, real-time electrical data, and day-ahead planned electrical data;

[0035] The first model building module is used to build a model based on the day-ahead planned electrical data and all the demand reactive power data to obtain the day-ahead clearing optimization model of the cross-regional DC joint of the new energy DC transmission system;

[0036] The second model building module is used to determine whether the trigger result for real-time rolling correction of the day-ahead clearing optimization model is met based on the real-time electrical data and the day-ahead planned electrical data; if the trigger result is that the day-ahead clearing optimization model is met for real-time rolling correction, then the model is built based on the real-time electrical data to obtain a deviation correction rolling model;

[0037] The correction settlement module is used to correct the day-ahead clearing optimization model using the rolling model to obtain settlement electrical data; based on the settlement electrical data, it determines the cross-regional electricity settlement data of the new energy through the flexible DC transmission system, the cross-regional electricity settlement data including day-ahead electricity settlement, day-ahead DC flexibility reservation settlement, and real-time adjustment settlement.

[0038] Optionally, the real-time electrical data includes rescheduling costs, wind and solar curtailment costs, default costs, real-time DC execution power, DC operation direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow, and real-time frequency deviation for each time period; the second model building module includes a deviation calculation submodule, a constraint construction submodule, a function construction submodule, and a model building submodule;

[0039] The deviation calculation submodule is used to determine the power deviation for each time period based on the real-time DC execution power and the day-ahead reference power.

[0040] The constraint construction submodule is used to construct constraint conditions based on the real-time DC execution power, the DC operating direction status data, the direction switching data, the real-time direction identification data, the real-time cross-sectional power flow and the real-time frequency deviation, so as to obtain DC constraint conditions.

[0041] The function construction submodule is used to construct a function based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods, so as to obtain a real-time optimization objective function.

[0042] The model building submodule is used to build a model based on the real-time optimization objective function and the DC constraint conditions to obtain a rolling model for deviation correction.

[0043] Optionally, the day-ahead clearing optimization model includes clearing constraints, and the correction settlement module includes a first calculation submodule. The first calculation submodule is used to optimize and solve the rolling model using the day-ahead benchmark power output by the day-ahead clearing optimization model as a reference trajectory, to obtain the actual DC execution power and actual deviation for each time period; to determine the day-ahead benchmark power correction for the corresponding time period based on the actual DC execution power and actual deviation for each time period; to use the day-ahead benchmark power correction for each time period as the day-ahead benchmark power for the corresponding time period, and to correct the day-ahead clearing result output by the day-ahead clearing optimization model based on the day-ahead benchmark power correction for the time period and the clearing constraints, to obtain the day-ahead cross-regional transaction correction energy, the upward correction capacity reservation and the downward correction capacity reservation for DC tie lines for the corresponding time period; wherein, the settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, and the upward correction capacity reservation and the downward correction capacity reservation for DC tie lines.

[0044] Optionally, the settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, and the upward and downward correction capacity reservations for DC tie lines; the correction settlement module includes a second calculation submodule; the second calculation submodule is used to obtain the day-ahead cross-regional transaction price, the upward capacity reservation price, the downward capacity reservation price, and the real-time adjustment price for each time period; calculate the day-ahead energy settlement based on the day-ahead cross-regional transaction price and the day-ahead cross-regional transaction correction energy for all time periods; calculate the day-ahead DC flexibility reservation settlement based on the upward capacity reservation price, the downward capacity reservation price, the upward correction capacity reservation, and the downward correction capacity reservation for all time periods; and calculate the real-time adjustment settlement based on the real-time adjustment price and the actual deviation for all time periods.

[0045] On the other hand, a terminal device is provided, including a processor and a memory;

[0046] The memory is used to store program code and transmit the program code to the processor;

[0047] The processor is used to execute the aforementioned method for clearing the inter-regional power market, which includes new energy sources transmitted via flexible DC transmission systems, according to the instructions in the program code.

[0048] This invention discloses a method, apparatus, and equipment for clearing the inter-regional power market involving renewable energy transmission via flexible DC transmission systems. The method includes: acquiring the number of regions involved in the renewable energy DC transmission system, reactive power data for reserve demand in each region, real-time electrical data, and day-ahead planned electrical data; constructing a model based on the day-ahead planned electrical data and all reactive power demand data to obtain a day-ahead clearing optimization model for inter-regional DC joint transmission of renewable energy; determining, based on the real-time electrical data and the day-ahead planned electrical data, whether a trigger result for real-time rolling correction of the day-ahead clearing optimization model is met; if the trigger result is met, constructing a model based on the real-time electrical data to obtain a deviation correction rolling model; correcting the day-ahead clearing optimization model using the rolling model to obtain settlement electrical data; and determining the inter-regional electricity settlement data for renewable energy transmission via flexible DC transmission systems based on the settlement electrical data. The inter-regional electricity settlement data includes day-ahead electricity settlement, day-ahead DC flexibility reserve settlement, and real-time adjustment settlement.

[0049] As can be seen from the above technical solutions, this application has the following advantages: The inter-regional power market clearing method involving new energy transmission via flexible DC transmission systems constructs a day-ahead clearing optimization model and a rolling model by using the number of regions of the new energy DC transmission system, reactive power data of the reserve demand undertaken by each region, real-time electrical data, and day-ahead planned electrical data. The rolling model is used to correct the day-ahead clearing optimization model to obtain settlement electrical data, and high-accuracy inter-regional power settlement data is calculated based on it. This realizes a DC participation market mechanism chain that connects power trading with frequency regulation, reserve and other ancillary services, real-time physical execution and clear settlement responsibilities, and solves the technical problem of low accuracy in existing inter-regional power energy and flexible coordinated clearing, deviation correction and settlement methods of new energy transmission via large-capacity DC.

[0050] This inter-regional electricity market clearing device, which includes a new energy DC transmission system, acquires the number of regions of the new energy DC transmission system, reactive power data of the reserve demand undertaken by each region, real-time electrical data, and day-ahead planned electrical data through a data acquisition module, a first model construction module, a second model construction module, and a correction and settlement module. It constructs a day-ahead clearing optimization model and a rolling model, and uses the rolling model to correct the day-ahead clearing optimization model to obtain settlement electrical data. Based on this, it calculates highly accurate inter-regional electricity settlement data, thereby realizing a DC participation market mechanism chain that connects electricity trading with frequency regulation, reserve and other ancillary services, real-time physical execution, and clear settlement responsibilities. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating the steps of the inter-regional power market clearing method involving new energy sources via a flexible DC transmission system, as described in an embodiment of this application.

[0053] Figure 2 This is a schematic diagram of the framework of an inter-regional power market clearing device containing a new energy transmission system via a flexible DC transmission system, as described in another embodiment of this application.

[0054] Figure 3 This is a schematic diagram of the terminal device described in an embodiment of this application. Detailed Implementation

[0055] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0056] In the description of the embodiments of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0057] In the embodiments of this application, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of this application according to the specific circumstances.

[0058] Patent terminology used in this application:

[0059] The core of the rolling optimization approach lies in "continuous updates and gradual convergence." Specifically, it involves using a time window as the scale for action, optimizing the objective and constraints within the window; at each action node, re-inputting the latest actual data, prediction results, and external information into the model to recalculate the optimal or near-optimal execution plan; and then using the execution result of the current window as the starting point for the next rolling iteration, gradually forming a stable optimization cycle. The rolling optimization approach can be represented by a rolling window algorithm.

[0060] This application provides a method, apparatus, and equipment for clearing inter-regional electricity markets including new energy transmitted via flexible DC transmission systems, which solves the technical problem of low accuracy in existing methods for clearing, correcting deviations, and settling inter-regional electricity transmitted via large-capacity DC transmission systems in conjunction with flexibility.

[0061] Example 1:

[0062] Figure 1 This is a flowchart illustrating the steps of the inter-regional power market clearing method involving new energy sources transmitted via a flexible DC transmission system, as described in an embodiment of this application.

[0063] like Figure 1 As shown in the figure, this application provides a method for clearing the inter-regional electricity market, including new energy sources transmitted via a flexible DC transmission system, comprising the following steps:

[0064] S1. Obtain the number of regions for new energy DC transmission systems, reactive power data for the reserve demand of each region, real-time electrical data, and day-ahead planned electrical data.

[0065] It should be noted that in the process of clearing out the inter-regional power market involving renewable energy transmitted through flexible DC transmission systems, step S1 can obtain regional data across regions and reactive power data of reserve demand undertaken by each region at each time period t based on the renewable energy DC transmission system. Real-time electrical data and day-ahead planned electrical data provide data for subsequent steps, including the clearing of inter-regional electricity markets involving renewable energy transmission via flexible DC transmission systems. In this embodiment, day-ahead planned electrical data includes the shortest duration of reserve call. And the benefits of cross-regional transactions at different time periods (t). Generator set power generation cost DC interconnection line capacity adjustment reserved DC interconnection line downlink capacity reserved The planned daily power transmission volume of new energy sources The output of generator set g Upper bound of new energy forecast range Lower bound of new energy forecast range Forward frequency modulation capability Negative and positive frequency modulation capability Increase standby capacity Reduce reserve capacity DC allows for the maximum up-modulation capacity within the frequency modulation timescale. Down-modulation capacity DC can be used to continuously increase the equivalent sustainable regulation capability. and down-adjustment of equivalent sustainable adjustment capacity Real-time electrical data includes rescheduling costs for each time period. The cost of abandoning wind and solar power Cost of breach of contract Real-time DC execution power DC operating direction status data Direction switching data Real-time direction identification data Real-time cross-sectional power flow and real-time frequency deviation wait.

[0066] In this embodiment of the application, the data obtained in step S1 can be obtained from the database of the power data acquisition system or the new energy DC transmission system.

[0067] S2. Based on the day-ahead planned electrical data and all demand reactive power data, a model is constructed to obtain the day-ahead clearing optimization model for cross-regional DC joint renewable energy DC transmission system.

[0068] It should be noted that the objective of step S2 is, in the day-ahead phase, to collaboratively determine the inter-regional power trading results and DC flexibility reservation results based on the day-ahead planned electrical data, which includes renewable energy forecasting information, load forecasting information, demand reactive power data, conventional unit bidding information, and DC equipment boundary information, and to construct a day-ahead clearing optimization model for the inter-regional DC joint renewable energy transmission system. This model aims to clear the current benchmark transmission power and upward / downward capacity reservations of the renewable energy DC transmission system. These upward / downward capacity reservations can then be integrated with frequency regulation and backup ancillary services. In this embodiment, the day-ahead clearing optimization model constructed in step S2 provides a computational model for the subsequent realization of inter-regional power and flexibility coordinated clearing, deviation correction, and settlement of the renewable energy DC transmission system.

[0069] In this embodiment of the application, during the process of obtaining the day-ahead clearing optimization model by using preset rules based on the day-ahead planned electrical data and all demand reactive power data, the constructed day-ahead clearing optimization model needs to consider maximizing the cross-regional transaction benefits, DC opportunity cost and reserve procurement cost to obtain the clearing objective function and clearing constraints of the day-ahead clearing optimization model.

[0070] It should be noted that the clearing constraints include: total transmission capacity constraints, DC power ramp-up constraints, new energy planned transmission constraints, receiving end reserve share constraints, and frequency regulation available capacity constraints.

[0071] In this embodiment of the application, the expression for the clearing objective function is:

[0072] ;

[0073] In the formula, The cross-regional transaction benefit for time period t can be calculated by the market operator based on the electricity purchase price of the purchasing region, the electricity sales price of the sending region, the cross-regional transaction volume, and the transaction rules. It is used to characterize the economic benefits brought by cross-regional electricity trading. The unit power generation cost of the generator set for time period t can be obtained by using segmented pricing or a quadratic function cost curve of the unit. The opportunity cost of DC power trading is incurred by the DC tie line during time period t in order to reserve upward and downward adjustment capabilities by giving up part of the electricity trading. The cost of purchasing backup resources due to the uncertainty of new energy sources during time period t.

[0074] In this embodiment, the capacity of the DC interconnection line is reserved according to the time period. Reserved capacity for DC-DC interconnection lines The DC opportunity cost for the corresponding time period can be calculated. .

[0075] It should be noted that the capacity reserve on the DC interconnection line is based on the time period. Reserved capacity for DC-DC interconnection lines The DC opportunity cost for the corresponding time period is calculated using the DC opportunity cost formula. The formula for the opportunity cost of DC is:

[0076] ;

[0077] In the formula, Let t be the opportunity cost of the flow. and These are the marginal opportunity cost coefficients for the reserved upward adjustment capacity and the reserved downward adjustment capacity, respectively, for time period t. Reserved capacity for DC interconnection line adjustment during time period t. This is to reserve capacity for the DC interconnection line downlink during time period t. According to the DC opportunity cost formula, the more capacity reserved, the less space the DC interconnection line of the new energy DC transmission system can be used for electricity trading, thus resulting in potential losses in trading revenue.

[0078] In this embodiment, the standby procurement cost for the corresponding time period is calculated using a preset formula or preset rules based on the standby reactive power data undertaken by each region in time period t. .

[0079] It should be noted that the standby procurement cost for each time period is calculated using a preset formula or preset rule (such as a procurement cost formula) based on the standby reactive power demand data of each region during time period t. The procurement cost formula is:

[0080] ;

[0081] In the formula, The price of spare capacity in region r during time period t. Let R be the reactive power reserve demand data for region r during time period t, where R is the number of regions served by the renewable energy DC transmission system. Based on the procurement cost formula, the reactive power reserve demand data between regions can be converted into a quantifiable economic quantity.

[0082] In this embodiment, both the DC reference power and its reserved regulation capacity must be constrained by the total transmission capacity, thus obtaining the total transmission capacity constraint. The total transmission capacity constraint is:

[0083] ;

[0084] ;

[0085] In the formula, The day-ahead reference power supply of the DC tie line for time period t. The total power limit for DC tie lines. The lower total power limit for DC tie lines.

[0086] In this embodiment of the application, the DC power ramp-up constraint is:

[0087] ;

[0088] In the formula, This represents the acceptable DC downhill climbing capability for the current stage. This represents the acceptable DC ramp-up capability for the current stage. This represents the day-ahead baseline power transmission power corresponding to the previous time period t-1. The day-ahead clearing optimization model reflects the requirements of the renewable energy DC transmission system on the smoothness of DC power curve changes during the day-ahead phase through DC power ramping constraints, avoiding the formation of drastic jump plans that are difficult to execute.

[0089] In this embodiment of the application, the constraints on the transmission of new energy plans are as follows:

[0090] ;

[0091] ;

[0092] In the formula, This refers to the planned daily transmission volume of renewable energy at the sending end of the renewable energy DC transmission system during time period t. This represents the predicted availability of renewable energy at the sending end of a renewable DC transmission system during time period t. The day-ahead cross-regional transaction volume of electrical energy in time period t. Let g be the output of generator unit g in time period t. The first equation of the renewable energy plan's power transmission constraint ensures that the planned daily power transmission of renewable energy does not exceed the available forecast value. The second equation of the renewable energy plan's power transmission constraint indicates that, in addition to renewable energy, conventional power sources can also participate in balancing and supplementing power transmission for the daily cross-regional power transactions.

[0093] In this embodiment of the application, the constraint on the backup share of the receiving end is as follows:

[0094] ;

[0095] ;

[0096] In the formula, The additional flexibility required due to fluctuations in the new energy forecast interval during time period t can be represented by the width of the new energy forecast interval (or the deviation envelope at a given confidence level). and Let these be the upper and lower bounds of the new energy forecast interval for time period t. This is the conversion factor.

[0097] It should be noted that the meaning of the constraint on the share of reserve capacity at the receiving end is that the wider the forecast range of new energy at the sending end of the new energy DC transmission system, the greater its uncertainty, and the higher the requirements for the flexibility of the new energy DC transmission system. Therefore, it is necessary for each region to share the corresponding reserve demand reactive power data.

[0098] In this embodiment of the application, in order to further reserve the DC interconnection line up-up capacity for time period t Reserved capacity for DC-DC interconnection lines The system is decomposed into frequency regulation available capacity and standby available capacity, and the same capacity cannot be calculated repeatedly between frequency regulation products and standby products. Therefore, the clearing constraint conditions of the day-ahead clearing optimization model are set with frequency regulation available capacity constraints. The frequency regulation available capacity constraints include standby frequency regulation constraints and required frequency regulation available capacity constraints. The standby frequency regulation constraints are as follows:

[0099] ;

[0100] ;

[0101] The required available capacity for frequency modulation is constrained as follows:

[0102] ;

[0103] ;

[0104] In the formula, For the positive frequency modulation capability of time period t, The positive and negative frequency modulation capabilities for time period t. The reserve capacity is increased for time period t. The reserve capacity is reduced for time period t. The up-modulation capacity for time period t. The down-modulation capacity for time period t. and It is the proportional coefficient that can be allocated from the current operating power of time period t to frequency modulation products.

[0105] In this embodiment of the application, the clearing constraint of the day-ahead clearing optimization model also includes the requirement that the reserve capacity must be able to maintain a predetermined time constraint after being called. The predetermined time constraint is as follows:

[0106] ;

[0107] ;

[0108] In the formula, For the shortest duration of the backup call, The upward adjustment of time period t is equivalent to the sustainable adjustment capacity. This represents the equivalent sustainable adjustment capacity for the downward adjustment of time period t.

[0109] In this embodiment, the clearing objective function and clearing constraints based on the day-ahead clearing optimization model are solved using mixed integer programming, linear programming, or quadratic programming methods to obtain the day-ahead clearing result. The day-ahead clearing result includes the day-ahead cross-regional transaction electrical energy for time period t. Day-ahead reference power of DC tie line DC interconnection line capacity adjustment reserved DC interconnection line downlink capacity reserved Reactive power data for backup demand undertaken by region r .

[0110] S3. Based on real-time electrical data and day-ahead planned electrical data, determine whether the trigger result for real-time rolling correction of the day-ahead clearing optimization model is met; if the trigger result is that the day-ahead clearing optimization model is met, then build the model based on the real-time electrical data to obtain the deviation correction rolling model.

[0111] It should be noted that step S3 can be understood as performing physically executable rolling corrections to the DC power plan during the real-time operation of the renewable energy DC transmission system. The triggering conditions for real-time rolling corrections to the day-ahead clearing optimization model include: the actual renewable energy output during time period t. With available predicted values Real-time rolling correction is triggered when the deviation exceeds the preset threshold, the safety verification of the key section at the receiving end is not met, the system frequency deviation exceeds the control range, or the dispatching agency issues adjustment instructions based on requirements such as cross-regional power supply guarantee and unified safety optimization. When the triggering conditions for real-time rolling correction of the day-ahead clearing optimization model are met, the model is constructed according to the preset formula or preset rules based on real-time electrical data to obtain the rolling model for deviation correction. This provides a correction model for the subsequent realization of cross-regional power energy and flexibility coordinated clearing, deviation correction and settlement of the new energy DC transmission system.

[0112] In the embodiments of this application, step S can be understood as follows: when the actual output of new energy deviates from the day-ahead forecast, the safety limit of the receiving end section is exceeded, the frequency deviation is exceeded, or unified scheduling is triggered, the DC power curve is rolled over under the condition of DC physical feasibility, so as to construct a rolling model with the minimization of rescheduling cost, wind and solar curtailment and safety default cost.

[0113] S4. The day-ahead clearing optimization model is modified using a rolling model to obtain settlement electrical data; based on the settlement electrical data, the cross-regional electricity settlement data of new energy transmitted through the flexible DC transmission system is determined. The cross-regional electricity settlement data includes day-ahead electricity settlement, day-ahead DC flexibility reservation settlement, and real-time adjustment settlement.

[0114] It should be noted that step S4 first uses a rolling model to calculate the day-ahead reference power output obtained in step S1. Using the reference trajectory, a rolling optimization method is employed to solve the real-time optimization objective function of the rolling model constructed in step S3 and the DC constraint conditions of the real-time physical constraints, thereby obtaining the actual DC execution power for time period t. and actual deviation Among them, the day-ahead benchmark power transmission capacity Based on the current clearing results, real-time modifications are made to the rolling model built in step S3; actual DC power output. The actual deviation of the DC power curve used for scheduling execution. Used for real-time adjustment settlement and deviation responsibility allocation in step S4, resulting in day-ahead electrical energy settlement. DC flexibility reserve settlement and real-time adjustment settlement The data on cross-regional power settlement of new energy through the flexible DC transmission system. In this embodiment, step S4 can be understood as day-ahead settlement payment of cross-regional power contracts and flexibility reservations, real-time settlement payment of actual adjustment amounts and actual deviation amounts, and further identification of beneficiaries and allocation of reschedule costs according to the cause of deviation triggering.

[0115] In this embodiment of the application, the purpose of step S4 is to economically close the loop between the results of steps S2 and S3, that is, to settle the cross-regional transactions and flexibility reservations achieved in step S2, and to assign responsibility and share costs for the adjustments and deviations that actually occurred in step S3.

[0116] It should be noted that step S2 provides step S4 with the day-ahead inter-regional electricity transaction price, the upward capacity reservation price, the downward capacity reservation price, and the real-time adjustment price; step S3 provides step S4 with the actual deviation and rescheduling cost. Step S4 ultimately outputs settlement electrical data, inter-regional electricity settlement data, deviation liability costs, and system dispatching allocation costs, etc.

[0117] In the embodiments of this application, under the operational scenario of large-scale renewable energy transmission via DC, the cross-regional power market clearing method including renewable energy transmission via flexible DC system can not only collaboratively determine cross-regional power trading, DC benchmark planning curve, DC up-and-down capacity reservation and receiving-end reserve share in the day-ahead stage (such as step S2), but also perform physically executable deviation correction of DC power according to renewable energy output deviation and system security requirements in the real-time stage (such as step S3), and distinguish renewable energy deviation responsibility and system dispatch benefit responsibility in the settlement stage (such as step S4), thereby realizing a DC participation market mechanism chain with connection between power trading and auxiliary services such as frequency regulation and reserve, real-time physical execution and clear settlement responsibility.

[0118] It should be noted that the inter-regional power market clearing method involving new energy transmission via flexible DC transmission system, through step S2, can transform large-scale DC transmission from a simple power transmission channel into a market object with both power transmission and flexible supply attributes, enabling new energy transmission via flexible DC transmission system to meet the needs of frequency regulation and backup ancillary services. Through step S3, this method integrates real-time power boundary constraints, real-time ramp rate constraints, direction switching constraints, minimum duration constraints, real-time adjustment non-reverse regulation constraints, key section power flow constraints, and frequency control response logic constraints into a unified rolling model that generates a physically executable deviation correction trajectory, ensuring the deviation correction results are physically executable. Through step S4, this method distinguishes between planned deviations caused by new energy output deviations and passive deviations caused by unified system dispatch, and identifies the beneficiary region or beneficiary entity for the latter, satisfying the settlement principle of "whoever benefits, shares the cost; whoever causes the deviation, bears the responsibility."

[0119] This application provides a method for clearing the inter-regional electricity market involving new energy transmission via flexible DC transmission systems. The method includes acquiring the number of regions involved in the new energy DC transmission system, reactive power data for reserve demand in each region, real-time electrical data, and day-ahead planned electrical data. Based on the day-ahead planned electrical data and all reactive power demand data, a model is constructed to obtain a day-ahead clearing optimization model for inter-regional DC joint transmission of new energy. Based on the real-time electrical data and the day-ahead planned electrical data, it is determined whether the trigger result for real-time rolling correction of the day-ahead clearing optimization model is met. If the trigger result is met, a model is constructed based on the real-time electrical data to obtain a deviation correction rolling model. The rolling model is used to correct the day-ahead clearing optimization model to obtain settlement electrical data. Based on the settlement electrical data, inter-regional electricity settlement data for new energy transmission via flexible DC transmission systems is determined. The inter-regional electricity settlement data includes day-ahead electricity settlement, day-ahead DC flexibility reserve settlement, and real-time adjustment settlement. This cross-regional electricity market clearing method, which includes renewable energy transmission via flexible DC transmission systems, constructs a day-ahead clearing optimization model and a rolling model based on the number of regions of renewable energy DC transmission systems, reactive power data of reserve demand in each region, real-time electrical data, and day-ahead planned electrical data. The rolling model is used to correct the day-ahead clearing optimization model to obtain settlement electrical data, and high-accuracy cross-regional electricity settlement data is calculated based on it. This realizes a DC participation market mechanism chain that connects electricity trading with ancillary services such as frequency regulation and reserve, with real-time physical execution and clear settlement responsibilities. It solves the technical problem of low accuracy in existing cross-regional electricity clearing, deviation correction, and settlement methods for renewable energy transmitted via large-capacity DC and flexible coordination.

[0120] In one embodiment of this application, the rolling model for deviation correction is obtained by model building based on real-time electrical data, including:

[0121] The power deviation for each time period is determined based on the real-time DC execution power and the day-ahead reference power.

[0122] Constraints are constructed based on real-time DC execution power, DC operating direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow, and real-time frequency deviation to obtain DC constraint conditions;

[0123] The function is constructed based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods to obtain the real-time optimization objective function;

[0124] A rolling model for deviation correction is obtained by constructing a model based on the real-time optimization objective function and DC constraints.

[0125] It should be noted that the DC constraints include real-time power boundary constraints, real-time ramp rate constraints, direction switching constraints, minimum duration constraints, real-time adjustment without reverse adjustment constraints, critical section power flow constraints, and frequency control response logic constraints. The power deviation for each time period is determined using a preset formula or preset rule based on the real-time DC execution power and the day-ahead reference power.

[0126] In this embodiment, the power deviation for each time period is determined using a preset formula or rule (such as a power deviation formula) based on the real-time DC execution power and the day-ahead reference power. The power deviation formula is as follows:

[0127] ;

[0128] In the formula, Let be the power deviation over time period t. The real-time DC execution power for time period t. The day-ahead reference power transmission capacity is t.

[0129] In this embodiment of the application, a function is constructed using preset rules based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods to obtain a real-time optimization objective function.

[0130] It should be noted that the objective function for real-time optimization is:

[0131] ;

[0132] In the formula, The total number of time periods. Let be the rescheduling cost for time period t. The cost of wind and solar power curtailment during time period t. Let t be the cost of default. These are weighting coefficients with different values. Among them, the rescheduling cost can be calculated based on real-time rescheduling instructions and adjustment quotations; the cost of wind and solar curtailment can be calculated based on the amount of renewable energy curtailed and the curtailment penalty price; the default cost refers to the cost of default caused by not meeting the safety boundary, which can be calculated based on the safety constraint slack and the safety default penalty coefficient. The weighting coefficients for each term can be set according to actual operational requirements. The first term of the real-time optimization objective function... This can reduce deviations from the day-ahead planning curve and maintain the stability of day-ahead market results; it can be achieved through the second item. The third item The fourth item When necessary, priority should be given to ensuring the consumption of new energy sources and system safety.

[0133] To ensure the feasibility of real-time DC adjustment results, in this embodiment of the application, the real-time power boundary constraint of the DC constraint condition in the rolling model is as follows:

[0134] ;

[0135] In the formula, This represents the lower limit of the actual operating power of the DC power supply. This represents the lower limit of the actual operating power of the DC system. In the rolling model, real-time power boundary constraints ensure that the actual operating power of the DC system always remains within the allowable power range.

[0136] In this embodiment of the application, in the rolling model, the real-time ramp rate constraint of the DC constraint is:

[0137] ;

[0138] In the formula, For real-time acceptable DC downhill ramp capability, For real-time acceptable DC ramp capability.

[0139] In this embodiment of the application, the direction switching constraint of the DC constraint condition in the rolling model is:

[0140] ;

[0141] ;

[0142] In the formula, This is the DC operating direction status data during time period t. This provides the DC operating direction status data for time period t-1. Data for direction switching.

[0143] It should be noted that when the DC power is running in the direction from the sending end to the receiving end, u t =1; when DC is in reverse operation, u t =0. If u t with u t-1 If they are not equal, then z t =1 indicates a direction change has occurred; otherwise, z t =0. The direction switching constraint of the DC constraint is used to identify whether a switch from one direction to another has occurred during a certain period of time.

[0144] In this embodiment of the application, in the rolling model, the minimum duration constraint of the DC constraint condition must be satisfied after the direction switch. The minimum duration constraint of the DC constraint condition is as follows:

[0145] ;

[0146] ;

[0147] In the formula, This represents the DC operating direction state data for time period τ. The minimum duration constraint of the DC constraint condition indicates that after operating in a certain direction, it must last at least T. min Switching is only allowed during specific time periods to avoid impacting power equipment and systems from repeated short-term switching.

[0148] In this embodiment of the application, in the rolling model, the real-time adjustment non-reverse constraint of the DC constraint condition is:

[0149] ;

[0150] In the formula, s t For time period t, the current expected adjustment of the real-time direction indicator data is taken. When the new energy source needs to increase the power transmission through the DC tie line via the flexible DC transmission system, s is taken. t =1; When the new energy transmission system requires a DC tie line to reduce the transmission power, take s. t =-1; when there is no clear positive or negative adjustment need in the time period t, take s. t =0. The real-time adjustment non-reverse adjustment constraint of DC constraint is used to avoid behaviors that counteract the scheduling target, such as the need to increase the DC power output of new energy sources via the flexible DC transmission system while the DC power output is adjusted downward.

[0151] Considering the security constraints of the receiving-end power grid, in the rolling model of this application, the key section power flow constraints of the DC constraint conditions are as follows:

[0152] ;

[0153] ;

[0154] In the formula, Let be the real-time tidal power of the l-th tidal cross section during time period t. Let l be the cross-sectional tidal current limits for tidal current sections. A collection of tidal current sections. Let be the DC injection power of node i during time period t.

[0155] It should be noted that the key section power flow constraint of the DC constraint condition indicates that the change of DC injection power at each node will affect the power flow at the receiving end section through the PTDF power flow distribution factor.

[0156] In this embodiment of the application, in the rolling model, the frequency control response logic constraint of the DC constraint condition is as follows:

[0157] ;

[0158] In the formula, Let Δf be the real-time frequency deviation for time period t. th For frequency deviation threshold, This represents the minimum adjustment power required to meet frequency support requirements during time period t. The DC-constrained frequency control response logic constraint states that at the moment a frequency response is required, the DC power adjustment cannot fall below the minimum power level required to meet frequency support, thus enabling the rolling model to connect with frequency regulation ancillary services.

[0159] In one embodiment of this application, the day-ahead clearing optimization model includes clearing constraints. A rolling model is used to modify the day-ahead clearing optimization model to obtain settlement electrical data, including:

[0160] Using the day-ahead baseline power output from the day-ahead clearing optimization model as a reference trajectory, the rolling optimization method is used to optimize and solve the rolling model to obtain the actual DC power and actual deviation for each time period.

[0161] Based on the actual DC power output and actual deviation for each time period, determine the day-ahead reference power correction for the corresponding time period.

[0162] The day-ahead base power transmission correction power for each time period is used as the day-ahead base power transmission power for the corresponding time period. The day-ahead clearing optimization model output day-ahead clearing results are corrected according to the day-ahead base power transmission correction power and clearing constraints for the time period, so as to obtain the day-ahead cross-regional transaction correction energy, DC tie line upward correction capacity reserve and downward correction capacity reserve for the corresponding time period.

[0163] The settlement electrical data includes the actual deviation for each time period, the corrected electrical energy for cross-regional transactions before the day, and the upward and downward correction capacity reserves for DC interconnection lines.

[0164] It should be noted that the day-ahead reference power correction for each time period is calculated using the power deviation formula based on the actual DC power output and actual deviation for each time period. The day-ahead reference power supply for each time period is adjusted. As the day-ahead benchmark power transmission power for the corresponding time period, the day-ahead clearing results output by the day-ahead clearing optimization model are corrected based on the day-ahead benchmark power transmission correction power for the time period, to obtain the day-ahead cross-regional transaction correction power energy for the time period that meets the clearing constraints. DC interconnection line upward adjustment capacity reserved and reduce the reserved capacity .

[0165] In one embodiment of this application, the settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, the upward adjustment correction capacity reserve and the downward adjustment correction capacity reserve for DC interconnection lines; based on the settlement electrical data, the cross-regional electricity settlement data for new energy transmitted through the flexible DC transmission system includes:

[0166] Obtain the day-ahead inter-regional electricity transaction price, the upward capacity reserve price, the downward capacity reserve price, and the real-time adjustment price for each time period;

[0167] The day-ahead electricity settlement is calculated based on the day-ahead inter-regional electricity transaction prices and the day-ahead inter-regional transaction adjusted electricity prices for all time periods.

[0168] The day-ahead DC flexibility reservation settlement is calculated based on the upward capacity reservation price, downward capacity reservation price, upward adjusted capacity reservation, and downward adjusted capacity reservation for all time periods.

[0169] Real-time adjustment settlement is calculated based on the real-time adjusted prices and actual deviations for all time periods.

[0170] It should be noted that the day-ahead electricity settlement is calculated using the day-ahead electricity settlement formula, based on the day-ahead inter-regional electricity transaction prices and the day-ahead inter-regional transaction correction electricity prices for all time periods. The day-ahead DC flexibility reserve settlement is calculated using the reservation settlement formula, based on the upward capacity reserve price, downward capacity reserve price, upward correction capacity reserve, and downward correction capacity reserve for all time periods. The real-time adjustment settlement is calculated using the adjustment settlement formula, based on the real-time adjustment price and actual deviation for all time periods.

[0171] In this embodiment of the application, the day-ahead electricity calculation formula is:

[0172] ;

[0173] The formula for pre-settlement is:

[0174] ;

[0175] The adjustment and settlement formula is as follows:

[0176] ;

[0177] In the formula, The price of inter-regional electricity transactions during time period t. To adjust the electrical energy for cross-regional transactions before the day of time t. and These represent the upward and downward adjustment of capacity reservation prices for time period t, respectively. This represents the actual deviation over time period t. To adjust the settlement in real time, To adjust prices in real time during time period t, and These represent the upward and downward adjustment capacity reserves for time period t, respectively. Settlement is reserved for day-ahead DC flexibility. This is for the settlement of electricity consumption before the day.

[0178] It should be noted that the adjustment settlement formula represents the adjustment services actually provided by the DC tie line or related entities during the real-time phase.

[0179] In this embodiment of the application, the inter-regional power market clearing method including new energy transmission via flexible DC transmission system further includes calculating the day-ahead total settlement by adding the day-ahead electricity settlement and the day-ahead DC flexibility reservation settlement. ,Right now This reflects that DC not only sells electrical energy during the day-ahead phase, but also sells flexibility reserve capacity, therefore the two should be priced separately.

[0180] In one embodiment of this application, the inter-regional power market clearing method including new energy sources transmitted via flexible DC transmission systems further includes:

[0181] Obtain the cost of new energy output deviation, the cost of unified system scheduling deviation, the attribution coefficient of new energy deviation for each new energy power station, the allocation coefficient for each region, and the responsible area and the responsible new energy power station of the responsible entity;

[0182] The new energy deviation cost of the corresponding new energy power station is calculated based on the new energy output deviation cost and the new energy deviation attribution coefficient of each new energy power station.

[0183] The system scheduling deviation cost for the corresponding region is calculated based on the unified system scheduling deviation cost and the allocation coefficient for each region.

[0184] Based on the calculation of all new energy deviation costs corresponding to the responsible new energy power stations and all real-time adjustment settlement and system scheduling deviation allocation costs corresponding to the responsible areas, the total real-time settlement of the corresponding responsible entities is obtained, realizing the responsibility attribution and cost allocation for the actual adjustment and deviation of the cross-regional power settlement of new energy through the flexible DC transmission system.

[0185] It should be noted that, for deviation settlement, this inter-regional electricity market clearing method, which includes new energy transmission via flexible DC transmission systems, divides real-time deviation costs into new energy output deviation costs. Cost of unified system scheduling deviation If the deviation is triggered by a discrepancy between the actual output of renewable energy and the day-ahead forecast, the corresponding cost will be included in the renewable energy output deviation cost. If the deviation is triggered by end-user security constraints, frequency support, or unified scheduling instructions, the corresponding cost will be included in the system unified scheduling deviation cost. Cost of deviation in new energy output Cost of unified system scheduling deviation It can be decomposed based on scheduling instruction records and real-time rescheduling costs.

[0186] In this embodiment, the new energy deviation cost of the corresponding new energy power station is calculated using the new energy deviation responsibility allocation formula based on the new energy output deviation cost and the new energy deviation attribution coefficient of each new energy power station. The new energy deviation responsibility allocation formula is as follows:

[0187] ;

[0188] In the formula, Let be the attribution coefficient for the new energy deviation of the i-th new energy power station. Let be the new energy deviation cost of the i-th new energy power station.

[0189] It should be noted that the attribution coefficient for new energy deviations can be determined based on the proportion of deviation contribution of new energy power stations and the corresponding division of responsibility among new energy power stations, reflecting the principle of "whoever causes the fluctuations bears the cost".

[0190] For system scheduling deviation responsibility, the beneficiary area is first identified based on the cause of the deviation. If the deviation is used to mitigate receiving-end section overruns, insufficient receiving-end reserves, or receiving-end supply risks, the beneficiary is the corresponding receiving-end area; if the deviation is used for frequency support, the beneficiary is the control area receiving balancing services; if the deviation is used for higher-level unified optimization, the beneficiary is the area that actually receives additional power supply guarantees or system security improvements. In this embodiment, the system scheduling deviation responsibility formula is used to calculate the system scheduling deviation allocation cost for the corresponding area based on the unified system scheduling deviation cost and the allocation coefficient for each area. The system scheduling deviation responsibility formula is:

[0191] ;

[0192] In the formula, The cost of system scheduling deviation to be allocated to region j. It is determined based on the amount of safety constraint relaxation, the amount of cross-sectional over-limit mitigation, and the rescheduling cost. It is determined based on the frequency support call volume and the frequency modulation service price. It is determined based on the additional rescheduling costs caused by cross-regional supply guarantee or unified optimized scheduling instructions; These represent the allocation coefficients of region j in the corresponding benefit component, obtained by normalization based on the benefit amount or scheduling records. The system scheduling deviation responsibility formula embodies the principle of "whoever benefits, shares the burden".

[0193] In this embodiment, the total real-time settlement for the corresponding responsible entity is calculated using the total real-time settlement result formula, based on all new energy deviation costs corresponding to the responsible new energy power stations and all real-time adjustment settlement and system scheduling deviation allocation costs corresponding to the responsible areas. The total real-time settlement result formula is as follows:

[0194] ;

[0195] In the formula, The new energy deviation liability cost is calculated by summing the new energy deviation costs of all responsible new energy power stations in the responsible entity k. The system scheduling deviation allocation cost is calculated by summing the system scheduling deviation allocation costs of all responsible regions in the responsible entity k. The real-time settlement net amount is calculated by summing the real-time adjustment settlements of all responsible areas in the responsible entity k. The total real-time settlement for the responsible entity k.

[0196] It should be noted that the formula for the overall real-time settlement result can remind the party that provides regulation and flexibility, allowing them to obtain regulation benefits; however, if they constitute a responsible party for new energy deviations or are required to bear system dispatch costs, corresponding deductions will also be applied. This allows the inter-regional power market clearing method involving new energy transmission via flexible DC systems to further decompose deviations caused by unified system dispatch into three categories: receiving-end security improvement, frequency support, and inter-regional supply guarantee. Furthermore, it identifies the beneficiary regions or responsible parties and allocates re-dispatch costs accordingly.

[0197] Example 2:

[0198] Figure 2 This is a schematic diagram of the framework of the inter-regional power market clearing device containing a new energy transmission system via flexible DC transmission, as described in the embodiments of this application.

[0199] like Figure 2 As shown, this application embodiment provides an inter-regional power market clearing device containing new energy transmitted via a flexible DC transmission system, including: a data acquisition module 100, a first model construction module 200, a second model construction module 300, and a correction settlement module 400;

[0200] The data acquisition module 100 is used to acquire the number of regions of the new energy DC transmission system, the reactive power data of the reserve demand undertaken by each region, real-time electrical data, and day-ahead planned electrical data;

[0201] The first model building module 200 is used to build a model based on the day-ahead planned electrical data and all demand reactive power data to obtain the day-ahead clearing optimization model of cross-regional DC joint new energy DC transmission system.

[0202] The second model building module 300 is used to determine whether the trigger result for real-time rolling correction of the day-ahead clearing optimization model is met based on real-time electrical data and day-ahead planned electrical data; if the trigger result is that the day-ahead clearing optimization model is met, then the model is built based on the real-time electrical data to obtain the deviation correction rolling model.

[0203] The modified settlement module 400 is used to modify the day-ahead clearing optimization model using a rolling model to obtain settlement electrical data; based on the settlement electrical data, the cross-regional electricity settlement data of new energy through the flexible DC transmission system is determined. The cross-regional electricity settlement data includes day-ahead electricity settlement, day-ahead DC flexibility reservation settlement, and real-time adjustment settlement.

[0204] It should be noted that the content of each module in the device of Embodiment 2 corresponds to the content of each step in the method of Embodiment 1. In this embodiment, the content of each module of the inter-regional power market clearing device containing new energy through flexible DC transmission system will not be described again. The inter-regional power market clearing device containing new energy through flexible DC transmission system obtains the number of regions of new energy DC transmission system, reactive power data of reserve demand undertaken by each region, real-time electrical data and day-ahead planned electrical data through data acquisition module, first model construction module, second model construction module and correction settlement module to construct day-ahead clearing optimization model and rolling model. The rolling model is used to correct the day-ahead clearing optimization model to obtain settlement electrical data and calculate high-accuracy inter-regional power settlement data based on it, thereby realizing the DC participation market mechanism chain of power energy trading and frequency regulation, reserve and other ancillary services, real-time physical execution and clear settlement responsibility.

[0205] In this embodiment, the real-time electrical data includes rescheduling costs, wind and solar curtailment costs, default costs, real-time DC execution power, DC operation direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow, and real-time frequency deviation for each time period; the second model building module 300 includes a deviation calculation submodule, a constraint construction submodule, a function construction submodule, and a model building submodule.

[0206] The deviation calculation submodule is used to determine the power deviation for each time period based on the real-time DC execution power and the day-ahead reference power.

[0207] The constraint construction submodule is used to construct constraint conditions based on real-time DC execution power, DC operating direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow and real-time frequency deviation, and obtain DC constraint conditions.

[0208] The function construction submodule is used to construct functions based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods, so as to obtain the real-time optimization objective function;

[0209] The model building submodule is used to build a model based on the real-time optimization objective function and DC constraints, and obtain a rolling model with deviation correction.

[0210] In this embodiment, the day-ahead clearing optimization model includes clearing constraints, and the correction settlement module 400 includes a first calculation submodule. The first calculation submodule is used to optimize and solve the rolling model using the day-ahead benchmark power output by the day-ahead clearing optimization model as a reference trajectory, and obtain the actual DC execution power and actual deviation for each time period. Based on the actual DC execution power and actual deviation for each time period, the day-ahead benchmark power correction power for the corresponding time period is determined. The day-ahead benchmark power correction power for each time period is used as the day-ahead benchmark power for the corresponding time period, and the day-ahead clearing result output by the day-ahead clearing optimization model is corrected according to the day-ahead benchmark power correction power and clearing constraints for the time period, to obtain the day-ahead cross-regional transaction correction energy, the upward correction capacity reservation and the downward correction capacity reservation for the DC tie line for the corresponding time period. The settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, and the upward correction capacity reservation and the downward correction capacity reservation for the DC tie line.

[0211] In this embodiment, the settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, and the upward and downward correction capacity reservations for DC tie lines. The correction settlement module 400 includes a second calculation submodule. The second calculation submodule is used to obtain the day-ahead cross-regional transaction price, the upward capacity reservation price, the downward capacity reservation price, and the real-time adjustment price for each time period. Based on the day-ahead cross-regional transaction price and the day-ahead cross-regional transaction correction energy for all time periods, the day-ahead energy settlement is obtained. Based on the upward capacity reservation price, the downward capacity reservation price, the upward correction capacity reservation, and the downward correction capacity reservation for all time periods, the day-ahead DC flexibility reservation settlement is obtained. Based on the real-time adjustment price and the actual deviation for all time periods, the real-time adjustment settlement is obtained.

[0212] Example 3:

[0213] Figure 3 This is a schematic diagram of the terminal device described in an embodiment of this application.

[0214] like Figure 3 As shown, this application provides a terminal device, including a processor and a memory;

[0215] Memory is used to store program code and transfer the program code to the processor;

[0216] The processor is used to execute the aforementioned method for clearing the inter-regional power market, which includes new energy sources transmitted via flexible DC transmission systems, according to instructions in the program code.

[0217] It should be noted that the processor is used to execute the steps in the above-described embodiment of a method for clearing the inter-regional power market involving new energy sources via a flexible DC transmission system, according to the instructions in the program code. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-described system / device embodiments.

[0218] For example, a computer program can be divided into one or more modules / units, one or more of which are stored in memory and executed by a processor to complete this application. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0219] Terminal devices can be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. Terminal devices may include, but are not limited to, processors and memory. Those skilled in the art will understand that this does not constitute a limitation on the terminal device, which may include more or fewer components than illustrated, or combinations of certain components, or different components. For example, a terminal device may also include input / output devices, network access devices, buses, etc.

[0220] The processor can 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. A general-purpose processor can be a microprocessor or any conventional processor.

[0221] Memory can be an internal storage unit of a terminal device, such as a hard drive or RAM. Memory can also be an external storage device, such as a plug-in hard drive, SmartMedia Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, memory can include both internal and external storage units. Memory is used to store computer programs and other programs and data required by the terminal device. Memory can also be used to temporarily store data that has been output or will be output.

[0222] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0223] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0224] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0225] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0226] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0227] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for clearing out inter-regional power markets including renewable energy transmitted via flexible DC transmission systems, characterized in that, Includes the following steps: Obtain the number of regions with new energy DC transmission systems, reactive power data for the reserve demand of each region, real-time electrical data, and day-ahead planned electrical data; Based on the day-ahead planned electrical data and all the day-ahead reactive power data, a model is constructed to obtain the day-ahead clearing optimization model of the cross-regional DC joint of the new energy DC transmission system. Based on the real-time electrical data and the day-ahead planned electrical data, determine whether the triggering result for real-time rolling correction of the day-ahead clearing optimization model is met; If the triggering result satisfies the requirement for real-time rolling correction of the day-ahead clearing optimization model, then the model is constructed based on the real-time electrical data to obtain a deviation-corrected rolling model. The rolling model is used to correct the day-ahead clearing optimization model to obtain settlement electrical data; based on the settlement electrical data, the cross-regional electricity settlement data of the new energy through the flexible DC transmission system is determined, and the cross-regional electricity settlement data includes day-ahead electricity settlement, day-ahead DC flexibility reservation settlement, and real-time adjustment settlement.

2. The method for clearing the inter-regional power market including new energy sources via flexible DC transmission systems according to claim 1, characterized in that, The real-time electrical data includes rescheduling costs, wind and solar curtailment costs, default costs, real-time DC execution power, DC operating direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow, and real-time frequency deviation for each time period. Based on the real-time electrical data, a model is constructed to obtain a rolling model for deviation correction, including: Based on the real-time DC execution power and the day-ahead reference power for each time period, determine the power deviation for the corresponding time period; The DC constraint conditions are constructed based on the real-time DC execution power, the DC operating direction status data, the direction switching data, the real-time direction identification data, the real-time cross-sectional power flow, and the real-time frequency deviation. Based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods, a function is constructed to obtain the real-time optimization objective function; A model is constructed based on the real-time optimization objective function and the DC constraint conditions to obtain a rolling model for deviation correction.

3. The method for clearing the inter-regional power market including new energy sources via flexible DC transmission systems according to claim 1, characterized in that, The day-ahead clearing optimization model includes clearing constraints. The rolling model is used to modify the day-ahead clearing optimization model to obtain the settlement electrical data, which includes: Using the day-ahead reference power output by the day-ahead clearing optimization model as a reference trajectory, the rolling optimization method is used to optimize and solve the rolling model to obtain the actual DC power and actual deviation for each time period. Based on the actual DC power output and the actual deviation for each time period, determine the day-ahead reference power correction for the corresponding time period; The day-ahead reference power supply correction power for each time period is used as the day-ahead reference power supply power for the corresponding time period. The day-ahead clearing optimization model output day-ahead clearing results are corrected according to the day-ahead reference power supply correction power for each time period and the clearing constraints, so as to obtain the day-ahead cross-regional transaction correction energy, the DC tie line upward correction capacity reserve and downward correction capacity reserve for the corresponding time period. The settlement electrical data includes the actual deviation for each time period, the corrected electrical energy for cross-regional transactions before the day, and the reserved capacity for upward and downward adjustments of DC tie lines.

4. The method for clearing the inter-regional power market including new energy sources via a flexible DC transmission system according to claim 1, characterized in that, The settlement electrical data includes the actual deviation for each time period, the corrected electrical energy for cross-regional transactions before the day, and the upward and downward correction capacity reserves for DC interconnection lines. Based on the settlement electrical data, the cross-regional power settlement data for the new energy transmitted via the flexible DC transmission system includes: Obtain the day-ahead inter-regional electricity transaction price, the upward capacity reserve price, the downward capacity reserve price, and the real-time adjustment price for each time period; The day-ahead electricity settlement is calculated based on the day-ahead inter-regional electricity transaction price and the day-ahead inter-regional transaction adjusted electricity price for all time periods. The day-ahead DC flexibility reservation settlement is calculated based on the upward capacity reservation price, the downward capacity reservation price, the upward adjusted capacity reservation, and the downward adjusted capacity reservation for all time periods. The real-time adjustment settlement is calculated based on the real-time adjusted price and the actual deviation for all time periods.

5. The method for clearing the inter-regional power market including new energy sources via flexible DC transmission systems according to any one of claims 1-4, characterized in that, Also includes: Obtain the cost of new energy output deviation, the cost of unified system scheduling deviation, the attribution coefficient of new energy deviation for each new energy power station, the allocation coefficient for each region, and the responsible area and the responsible new energy power station of the responsible entity; The new energy deviation cost of the corresponding new energy power station is calculated based on the new energy output deviation cost and the new energy deviation attribution coefficient of each new energy power station. The system scheduling deviation cost for the corresponding region is calculated based on the unified system scheduling deviation cost and the allocation coefficient for each region. Based on the calculation of all the new energy deviation costs corresponding to the responsible new energy power stations, as well as all the real-time adjustment settlements and system scheduling deviation allocation costs corresponding to the responsible regions, the total real-time settlement corresponding to the responsible entity is obtained, thereby realizing the attribution of responsibility and cost allocation for the actual adjustment and deviation of the cross-regional power settlement of new energy through the flexible DC transmission system.

6. A cross-regional power market clearing device incorporating a new energy transmission system via flexible DC transmission, characterized in that, include: The module comprises a data acquisition module, a first model construction module, a second model construction module, and a correction and settlement module. The data acquisition module is used to acquire the number of regions of the new energy DC transmission system, the reactive power data of the reserve demand undertaken by each region, real-time electrical data, and day-ahead planned electrical data; The first model building module is used to build a model based on the day-ahead planned electrical data and all the demand reactive power data to obtain the day-ahead clearing optimization model of the cross-regional DC joint of the new energy DC transmission system; The second model building module is used to determine, based on the real-time electrical data and the day-ahead planned electrical data, whether the triggering result for real-time rolling correction of the day-ahead clearing optimization model is met; If the triggering result satisfies the requirement for real-time rolling correction of the day-ahead clearing optimization model, then the model is constructed based on the real-time electrical data to obtain a deviation-corrected rolling model. The correction settlement module is used to correct the day-ahead clearing optimization model using the rolling model to obtain settlement electrical data; based on the settlement electrical data, it determines the cross-regional electricity settlement data of the new energy through the flexible DC transmission system, the cross-regional electricity settlement data including day-ahead electricity settlement, day-ahead DC flexibility reservation settlement, and real-time adjustment settlement.

7. The inter-regional power market clearing device including a new energy transmission system via flexible DC transmission as described in claim 6, characterized in that, The real-time electrical data includes rescheduling costs, wind and solar curtailment costs, default costs, real-time DC execution power, DC operating direction status data, direction switching data, real-time direction identification data, real-time cross-sectional power flow, and real-time frequency deviation for each time period. The second model building module includes a deviation calculation submodule, a constraint construction submodule, a function construction submodule, and a model building submodule; The deviation calculation submodule is used to determine the power deviation for each time period based on the real-time DC execution power and the day-ahead reference power. The constraint construction submodule is used to construct constraint conditions based on the real-time DC execution power, the DC operating direction status data, the direction switching data, the real-time direction identification data, the real-time cross-sectional power flow and the real-time frequency deviation, so as to obtain DC constraint conditions. The function construction submodule is used to construct a function based on the power deviation, rescheduling cost, wind and solar curtailment cost, and default cost for all time periods, so as to obtain a real-time optimization objective function. The model building submodule is used to build a model based on the real-time optimization objective function and the DC constraint conditions to obtain a rolling model for deviation correction.

8. The inter-regional power market clearing device including a new energy transmission system via flexible DC transmission as described in claim 6, characterized in that, The day-ahead clearing optimization model includes clearing constraints, and the correction settlement module includes a first calculation submodule. The first calculation submodule is used to optimize and solve the rolling model using the day-ahead reference power output by the day-ahead clearing optimization model as a reference trajectory, and obtain the actual DC power and actual deviation for each time period. Based on the actual DC power and actual deviation for each time period, the day-ahead reference power correction power for the corresponding time period is determined. The day-ahead reference power transmission correction power for each time period is used as the day-ahead reference power transmission power for the corresponding time period. The day-ahead clearing optimization model output day-ahead clearing results are corrected according to the day-ahead reference power transmission correction power for each time period and the clearing constraints, to obtain the day-ahead cross-regional transaction correction energy, the upward correction capacity reserve and the downward correction capacity reserve of the DC tie line for the corresponding time period. The settlement electrical data includes the actual deviation amount for each time period, the day-ahead cross-regional transaction correction energy, and the upward correction capacity reserve and the downward correction capacity reserve of the DC tie line.

9. The inter-regional power market clearing device including a new energy transmission system via flexible DC transmission as described in claim 6, characterized in that, The settlement electrical data includes the actual deviation for each time period, the day-ahead cross-regional transaction correction energy, and the upward and downward correction capacity reservations for DC tie lines. The correction settlement module includes a second calculation submodule. The second calculation submodule is used to obtain the day-ahead cross-regional transaction price, the upward capacity reservation price, the downward capacity reservation price, and the real-time adjustment price for each time period. Based on the day-ahead cross-regional transaction price and the day-ahead cross-regional transaction correction energy for all time periods, the day-ahead energy settlement is obtained. Based on the upward capacity reservation price, the downward capacity reservation price, the upward correction capacity reservation, and the downward correction capacity reservation for all time periods, the day-ahead DC flexibility reservation settlement is obtained. Based on the real-time adjustment price and the actual deviation for all time periods, the real-time adjustment settlement is obtained.

10. A terminal device, characterized in that, Including the processor and memory; The memory is used to store program code and transmit the program code to the processor; The processor is configured to execute, according to the instructions in the program code, the method for clearing the inter-regional power market including new energy sources via a flexible DC transmission system as described in any one of claims 1-5.

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