Inter-provincial mutual aid optimization method based on bidirectional TTC calculation constraint

Abstract

The invention relates to the field of electricity markets, and discloses an inter-province mutual aid optimization method based on bidirectional TTC calculation constraint, which comprises the following steps: constructing an in-province clearing transaction model to carry out in-province electricity market pre-clearing; constructing an inter-provincial power transaction model to perform inter-provincial concentrated bidding clearing, obtaining an inter-provincial transaction plan and key section power distribution, inputting a pre-clearing operation mode as an initial operation state into a TTC calculation model, and calculating dynamic power transmission limits of the key section in positive and negative power transmission directions; taking the calculated bidirectional TTC value as a transmission capacity constraint of a power transmission section, feeding back the bidirectional TTC value to the inter-province power transaction model, and performing inter-province clearing and intra-province clearing again to obtain an updated pre-clearing operation mode; iterative calculation is carried out until the error between TTC values obtained through two times of calculation is smaller than a set threshold value, and the inter-provincial transaction plan at the moment serves as a final optimization result to be output. The method has the advantage that the problem of complexity and stability caused by coupling of the extra-high voltage direct current and the strong alternating current looped network can be effectively solved.

Description

Technical Field

[0001] This invention relates to the field of electricity markets, and in particular to an inter-provincial mutual assistance optimization method based on bidirectional TTC calculation constraints. Background Technology

[0002] The energy structure is rapidly transforming towards diversification and cleaner energy sources. Taking the Southwest Power Grid as an example, its power source composition has expanded from traditional hydropower as the main source to a pattern of coordinated development of multiple energy sources, including hydropower, wind power, solar power, and thermal power. In particular, the planning and construction of ultra-high-voltage direct current (UHVDC) projects such as "Xinjiang Electricity to Chongqing" and "Gansu Electricity to Sichuan" have injected large-scale wind and solar renewable energy from the Northwest into the Southwest, further enriching the energy supply system. Many key DC channels adopt grid-commutated converter-type high-voltage direct current transmission (LCC-HVDC) technology, enabling DC transmission and reception, providing efficient channels for power transmission. To accommodate large-scale power transmission, the power grid architecture has also been upgraded simultaneously, with regional power grid voltage levels increasing from 500 kV to UHV, forming a complex new network of large-scale AC / DC hybrid connections. While this evolution enhances the ability to allocate resources across regions, it also makes the operating characteristics and stability of the power grid unprecedentedly complex, posing unprecedented challenges to the system's balancing capabilities.

[0003] Under this new framework, inter-provincial power transfer, which includes DC transmission and reception, has become a core pillar for ensuring grid security and promoting energy consumption. Among these, the transmission and reception of DC power plays a crucial role. On the one hand, inter-provincial power transfer can provide broader consumption space for flexible resources such as wind and solar power, which are highly volatile. Simultaneously, local generating units can supply power to other provinces. When local renewable energy consumption / generator capacity is sufficient but the power supply capacity of other provinces is insufficient, surplus power can be transmitted to neighboring provinces, significantly reducing local wind and solar curtailment rates and providing surplus power support to other provinces. On the other hand, when local power supply capacity is insufficient, DC channels can achieve power reduction or return transmission. Furthermore, power transfer can effectively improve overall supply security. In the event of extreme weather or local power shortages, rapid support can be achieved through robust interconnection lines, collaboratively addressing supply and demand imbalances. However, the increasingly severe pressure on supply security and the extreme uncertainty of renewable energy place higher demands on the flexibility, reliability, and economy of power transfer.

[0004] Currently, traditional inter-provincial power trading and cross-section safety management models are no longer fully adapted to the dynamic characteristics of new power systems. Their core limitation lies in their reliance on fixed-quota transmission limits, calculated offline based on typical or extreme operating conditions. This static model fails to consider the ever-changing actual operating modes of the power grid and ignores the fact that the actual transmission capacity of a cross-section strongly depends on dynamic factors such as real-time generator operation and power flow distribution. Fixed-quota calculations are often overly conservative, limiting channel potential and resulting in resource waste.

[0005] Furthermore, ultra-high voltage direct current (UHVDC), as a highly efficient inter-regional power transmission channel, has not only greatly increased the scale of inter-regional resource allocation but also profoundly changed the operating characteristics of regional power grids. It is no longer merely a single energy transmission or reception channel but has evolved into a key infrastructure capable of enabling flexible bidirectional exchange of large-capacity power across regions. Together with the AC system, it forms a hybrid AC / DC system with powerful bidirectional power regulation capabilities in both time and space. This characteristic greatly enhances the power grid's ability to provide mutual assistance between regions, but it also makes the power distribution and stability characteristics within the system more complex, placing unprecedented demands on the accurate sensing of transmission capacity. Therefore, there is an urgent need for an inter-provincial mutual assistance trading system that balances economic efficiency and security, as well as a computationally feasible and interpretable method for analyzing the bidirectional transmission capacity of inter-provincial mutual assistance channels. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide an inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints.

[0007] The objective of this invention is achieved through the following technical solution: an inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints, the method comprising,

[0008] S1. Based on the power grid topology, unit parameters, load and new energy forecast data, construct a provincial clearing transaction model to conduct pre-clearing of the provincial power market, and obtain information on the provincial unit combination, output plan and surplus or deficit power after provincial balance.

[0009] S2. Based on the surplus or shortage of electricity in each province, construct an inter-provincial electricity trading model. With the goal of maximizing the total system price difference, consider the bids of both buyers and sellers, transmission prices and network losses, and conduct centralized bidding and clearing between provinces to obtain a preliminary inter-provincial trading plan and power distribution of key sections, which serves as the pre-clearing operation mode.

[0010] S3. The pre-clearing operation mode is taken as the initial operation state and input into the TTC calculation model of the bidirectional total transmission capacity of the AC / DC hybrid power grid that takes into account the UHVDC transmission / reception, and the dynamic transmission limit of the key section in the positive and negative power transmission directions is calculated respectively.

[0011] S4. The calculated bidirectional TTC value is used as the transmission capacity constraint of the transmission section and fed back into the inter-provincial power trading model to re-perform inter-provincial clearing and intra-provincial clearing to obtain an updated pre-clearing operation mode.

[0012] S5. Repeat steps S3 and S4 until the error between the two calculated TTC values ​​is less than the set threshold. Output the inter-provincial transaction plan and cross-sectional transmission limit at this time as the final optimization result.

[0013] Specifically, the objective function of the intra-provincial clearing transaction model is:

[0014] ;

[0015] In the formula, and These are the unit start-up and shutdown cost variables and the unit output cost variables, respectively. and These are the unit start-up and shutdown constraint constant matrix and the unit output constraint constant matrix, respectively. The right-hand constraint vector; These are the 0 and 1 variables in the unit combination; These are continuous variables in the unit combination.

[0016] Specifically, the objective function of the inter-provincial power trading model is:

[0017] ;

[0018] In the formula, The objective function is... The total cost of electricity purchase for the electricity purchaser; The total electricity sales revenue of the electricity sales entity; The penalty cost for defaulting on DC nodes; For nodes Electricity purchasing entities exist Trading volume at any given moment; For nodes Electricity purchasing entities exist The declared price at any given time; For nodes On the power generation main body exist Trading volume at any given moment; For nodes Electricity sales entities exist The declared price at any given time; For nodes Upper DC channel in Transmission power at any given time node The contract for the DC channel is stipulated Transmission power at any given moment; The penalty price for breach of contract; This refers to all electricity purchasing entities. For all power generation entities; A collection of power generation entities capable of participating in DC power transmission.

[0019] Specifically, the constraints of the inter-provincial power trading model include:

[0020] Application volume constraints:

[0021] ;

[0022] In the formula, For the buyer's entity Maximum load at any given time; For the seller's entity Maximum output capacity at any given moment; For the seller's entity Pre-emptive clearing capacity at specific times;

[0023] Trading volume constraints:

[0024] ;

[0025] In the formula, For the main body of electricity purchase exist The amount of electricity purchased as declared at any given time; Main generator exist The amount of electricity sold as declared at any given time;

[0026] Unit output constraints:

[0027] ;

[0028] In the formula, For generator sets The upper limit of active power; For generator sets The lower limit of active power; For generator sets The upper limit of reactive power; For generator sets The lower limit of reactive power; For generator sets Active power at time t; For generator sets Reactive power at time t;

[0029] Unit ramp-up constraints:

[0030] ;

[0031] In the formula, For generator sets Maximum power output when climbing a hill; For generator sets Maximum power output when climbing downhill;

[0032] Node power balance constraints:

[0033] ;

[0034] In the formula, The set of all nodes. For nodes Connected, and outgoing nodes The set of channels; For nodes Connected, and flowing into the node The set of channels; For channel exist The power transmission value at any given time; For channel exist The power input value at any given time;

[0035] Upper limit constraints on power transmission lines:

[0036] ;

[0037] In the formula, For the province With Province Transmission capacity of the connecting line section between them; For the province With Province TTC values ​​between;

[0038] Power allocation rules:

[0039] ;

[0040] In the formula, generator set The electricity allocated for sale at time t; For the main body of electricity purchase exist Electricity purchase and allocation at any given time; The number of trade pairs with the same price difference and the same seller entity; This represents the number of trading pairs with the same price difference and the same buyer entity.

[0041] DC output / receiver penalty constraints:

[0042] ;

[0043] In the formula, , The DC transmission fluctuation factor under different operating conditions; The power output specified in the medium- and long-term contract; The received power is the amount specified in the medium- to long-term contract.

[0044] Specifically, the objective function of the TTC calculation model is:

[0045] ;

[0046] In the formula, province With provinces The transmission power of each line contained in the key cross-section;

[0047] Specifically, the constraints of the TTC calculation model include:

[0048] N-1 verification:

[0049] ;

[0050] In the formula, , Components The system's control and state variables when a fault occurs;

[0051] Nodal active power balance constraints:

[0052] ;

[0053] ;

[0054] In the formula, To output active power to the generator; Active load of the node; The active power output of the AC / DC hybrid node generator; Active load at AC / DC hybrid nodes; For nodes Voltage amplitude; For nodes Voltage amplitude; For nodes , The admittance magnitude between; For nodes Voltage phase angle; For nodes Voltage phase angle; For nodes , The admittance phase angle between them; AC / DC hybrid node Voltage amplitude; For nodes , The admittance magnitude between; AC / DC hybrid node Voltage phase angle; For nodes , The admittance phase angle between them; This is the rectifier voltage on the DC side; This is the inverter voltage on the DC side; This refers to the current in a DC line. This refers to the turns ratio of the transformer on the rectifier side. This refers to the turns ratio of the transformer on the inverter side; This refers to the voltage amplitude of the converter. This refers to the commutation angle of the rectifier; The extinction angle of the inverter; The transformer reactance on the rectifier side; The transformer reactance on the inverter side; When the converter station is operating in rectification mode, the DC channel transmits electrical energy outward. When the converter station is operating in inverter mode, the DC channel receives electrical energy from the outside. For regular communication nodes, A special AC node connected to a DC node;

[0055] Nodal reactive power balance constraints:

[0056] ;

[0057] ;

[0058] In the formula, For nodes The generator outputs reactive power; For nodes Power injected by the reactive power compensation device; For nodes Reactive load; For nodes The generator outputs reactive power; For nodes Power injected by the reactive power compensation device; For nodes Reactive load; The power factor angle on the rectifier side; The power factor angle on the inverter side;

[0059] Node voltage constraints:

[0060] ;

[0061] In the formula, The set of all nodes; This refers to the node voltage amplitude. , These are the lower and upper limits of the node voltage amplitude, respectively;

[0062] Generator active power constraints:

[0063] ;

[0064] In the formula, This is the set of all generators; Let be the active power of the generator set at node i; , Let be the lower and upper limits of the active power of the generator set at node i;

[0065] Generator reactive power constraints:

[0066] ;

[0067] In the formula, Let be the reactive power of the generator set at node i; , These are the lower and upper limits of the reactive power of the generator set at node i, respectively;

[0068] Line thermal stability constraints:

[0069] ;

[0070] In the formula, busbar The current; busbar The upper limit of the current amplitude;

[0071] Bus voltage constraint:

[0072] ;

[0073] In the formula, , busbars The lower and upper limits of voltage amplitude.

[0074] Specifically, the particle swarm optimization algorithm is used to jointly solve the model, and the particle update formula is as follows:

[0075] .

[0076] In the formula, No. Individual particles The speed of time; No. Individual particles The speed of time; Inertial weights; For individual learning factors; As a social learning factor; , It is a random number; For the first The best historical position of each particle; This represents the historical best position for all particles. No. Individual particles The position at that moment; No. Individual particles The position at any given moment.

[0077] The present invention has the following advantages:

[0078] 1. This invention uses the cross-sectional transmission capacity, which changes due to the system's operating status, as a feedback constraint for market clearing. Under the premise of ensuring grid security, it can fully tap the potential of transmission channels, guide the combination of generating units and inter-provincial transactions to achieve global optimization, optimize the allocation of power resources within and between provinces, and increase the proportion of clean energy consumption.

[0079] 2. The method proposed in this invention is applicable to large-scale AC / DC hybrid systems and can effectively handle the complex stability problems caused by the coupling of UHVDC and strong AC ring networks, providing dispatchers with a high-quality decision-making solution that is both economical and safe. Attached Figure Description

[0080] Figure 1 This is a schematic diagram of the optimized method flow of the present invention. Detailed Implementation

[0081] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described embodiments are merely some embodiments of the invention, and not all embodiments. The components of the embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0082] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0083] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0084] The present invention will be further described below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following description.

[0085] like Figure 1 As shown, an inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints is proposed. This method includes:

[0086] S1. Based on grid topology, unit parameters, load and renewable energy forecast data, a provincial clearing trading model is constructed to pre-clear the provincial electricity market, obtaining information on provincial unit combinations, output plans, and surplus or deficit power after provincial balance; for both large-scale DC power transmission and reception scenarios, the Big-M method is used to convert the power flow direction of DC lines into binary variables. , This indicates that the line is in the input inverter state. This indicates that the line is in the rectified output state, and this variable is used to switch between different constraint conditions;

[0087] The objective function of the intra-provincial clearing transaction model is:

[0088] ;

[0089] In the formula, and These are the unit start-up and shutdown cost variables and the unit output cost variables, respectively. and These are the unit start-up and shutdown constraint constant matrix and the unit output constraint constant matrix, respectively. The right-hand constraint vector; These are the 0 and 1 variables in the unit combination; These are continuous variables in the unit combination.

[0090] S2. Based on the surplus or shortage of electricity in each province, construct an inter-provincial electricity trading model. With the goal of maximizing the total system price difference, consider the bids of both buyers and sellers, transmission prices and network losses, and conduct centralized bidding and clearing between provinces to obtain a preliminary inter-provincial trading plan and power distribution of key sections, which serves as the pre-clearing operation mode.

[0091] Inter-provincial power trading occurs after pre-clearing within each province. Pre-clearing within a province provides information on the operating status of generating units and the transmission power of transmission lines. Based on this, provinces with surplus power have the capacity to supply power to other provinces, while provinces with power shortages have the capacity to receive power from other provinces, thus enabling inter-provincial power trading. In inter-provincial spot power trading, one province is defined as one trading node. Market participants within a node are not allowed to conduct inter-provincial spot power trading. Spot trading adopts a centralized bidding clearing method. The objective function of the inter-provincial power trading model is to maximize the total system price difference. Buyers submit time-of-use "electricity-price" curves at their respective nodes. After considering the transmission prices and grid losses of all trading paths, the prices are converted to seller nodes one by one. At seller nodes, sellers' bids are sorted from low to high, and buyers' converted prices are sorted from high to low. Clearing proceeds according to the principle of decreasing price differences between buyers and sellers, with the trading pair with the largest price difference being prioritized, until the price difference is less than zero or the available transmission capacity of the trading path between nodes is zero. The objective function of the inter-provincial power trading model is:

[0092] ;

[0093] In the formula, The objective function is... The total cost of electricity purchase for the electricity purchaser; The total electricity sales revenue of the electricity sales entity; The penalty cost for defaulting on DC nodes; For nodes Electricity purchasing entities exist Trading volume at any given moment; For nodes Electricity purchasing entities exist The declared price at any given time; For nodes On the power generation main body exist Trading volume at any given moment; For nodes Electricity sales entities exist The declared price at any given time; For nodes Upper DC channel in Transmission power at any given time node The contract for the DC channel is stipulated Transmission power at any given moment; The penalty price for breach of contract; This refers to all electricity purchasing entities. For all power generation entities; A collection of power generation entities capable of participating in DC power transmission.

[0094] The constraints of the inter-provincial power trading model include:

[0095] The electricity declared by the electricity seller cannot exceed the difference between its actual power generation capacity and the pre-cleared electricity capacity, while the electricity declared by the electricity buyer is capped at its maximum power load.

[0096] ;

[0097] In the formula, For the buyer's entity Maximum load at any given time; For the seller's entity Maximum output capacity at any given moment; For the seller's entity Pre-emptive clearing capacity at specific times;

[0098] The trading volume constraint stipulates that the total trading volume of both buyers and sellers of electricity should be less than their own declared volume.

[0099] ;

[0100] In the formula, For the main body of electricity purchase exist The amount of electricity purchased as declared at any given time; Main generator exist The amount of electricity sold as declared at any given time;

[0101] Generator output constraints: When the generator set is in operation, its output at any given moment must be within the limits of its minimum and maximum output power to ensure stable operation.

[0102] ;

[0103] In the formula, For generator sets The upper limit of active power; For generator sets The lower limit of active power; For generator sets The upper limit of reactive power; For generator sets The lower limit of reactive power; For generator sets Active power at time t; For generator sets Reactive power at time t;

[0104] Unit ramp-up constraints limit the rate of output change of cogeneration units during start-up, shutdown, and operation. Upper / lower ramp-up limits are introduced to control the amplitude of output changes between adjacent time periods, avoiding system fluctuation risks caused by excessively rapid output changes. When the unit's operating conditions remain constant, the output change must not exceed the maximum ramp-up rate.

[0105] ;

[0106] In the formula, For generator sets Maximum power output when climbing a hill; For generator sets Maximum power output when climbing downhill;

[0107] In inter-provincial power trading, there are three types of nodes: power sellers, power buyers, and intermediate nodes. For power sellers, their power sales should be the difference between the channel's output power and its received power. For power buyers, their power purchases should be the difference between the channel's received power and its output power. For intermediate nodes, the channel's received power equals its output power.

[0108] ;

[0109] In the formula, The set of all nodes. For nodes Connected, and outgoing nodes The set of channels; For nodes Connected, and flowing into the node The set of channels; For channel exist The power transmission value at any given time; For channel exist The power input value at any given time;

[0110] The upper limit of power transmission through transmission lines is constrained by the cross-sectional transmission limit. In this invention, the calculated value of the cross-sectional transmission limit is used as the cross-sectional transmission limit to restrict the transmission of cross-sectional power in the system.

[0111] ;

[0112] In the formula, For the province With Province Transmission capacity of the connecting line section between them; For the province With Province TTC values ​​between;

[0113] When multiple trading pairs have the same price difference, the power allocation rules stipulate that the power delivery demand of the seller node and the power receiving demand of the buyer node in the trading pair are allocated according to the proportion of the declared power:

[0114] ;

[0115] In the formula, generator set The electricity allocated for sale at time t. For the main body of electricity purchase exist The power purchase and allocation at any time, for This represents the number of trade pairs with the same price difference and the same seller entity. This represents the number of trading pairs with the same price difference and the same buyer entity.

[0116] DC transmission / reception penalty constraints: Under both DC transmission and reception operating conditions, the transmission and reception power of the DC channel should be consistent with the transmission capacity stipulated in the medium- and long-term contracts between the two parties. If insufficient supply occurs, the transmission capacity is allowed to fluctuate within a small range, and a corresponding penalty will be imposed.

[0117] ;

[0118] In the formula, , The DC transmission fluctuation factor under different operating conditions; The power output specified in the medium- and long-term contract; The received power as stipulated in the medium- and long-term contract;

[0119] S3. The pre-clearance operation mode is used as the initial operating state and input into the TTC calculation model of the bidirectional total transmission capacity of the AC / DC hybrid power grid considering UHVDC transmission / reception. The dynamic transmission limits of key sections in both the forward and reverse power transmission directions are calculated separately. The TTC calculation model aims to solve the key problem of inter-provincial transaction security assessment in AC / DC hybrid power grids containing large-scale UHVDC transmission. The core is to accurately quantify the transmission limits of key transmission channels in the power grid using a TTC calculation method based on strict stability criteria. Different intra-provincial and inter-provincial pre-clearance points will affect the TTC calculation results of key sections of the system. Furthermore, the model considers the impact of different UHVDC operation modes (external transmission / reception) on the stability limits of AC channels, thus enabling the calculation and provision of dynamic limits for transmission sections in both the forward and reverse power transmission directions.

[0120] The objective function of the TTC calculation model is to maximize the total transmission capacity from power transmission area 1 to power reception area 2.

[0121] ;

[0122] In the formula, province With provinces The transmission power of each line contained in the key cross-section;

[0123] Furthermore, the constraints of the TTC calculation model include:

[0124] The N-1 check ensures that the entire power system can maintain safe and stable operation even after any critical component fails and disconnects.

[0125] ;

[0126] In the formula, , Components The system's control and state variables when a fault occurs;

[0127] Nodal active power balance constraints:

[0128] ;

[0129] ;

[0130] In the formula, To output active power to the generator; Active load of the node; The active power output of the AC / DC hybrid node generator; Active load at AC / DC hybrid nodes; For nodes Voltage amplitude; For nodes Voltage amplitude; For nodes , The admittance magnitude between; For nodes Voltage phase angle; For nodes Voltage phase angle; For nodes , The admittance phase angle between them; AC / DC hybrid node Voltage amplitude; For nodes , The admittance magnitude between; AC / DC hybrid node Voltage phase angle; For nodes , The admittance phase angle between them; This is the rectifier voltage on the DC side; This is the inverter voltage on the DC side; This refers to the current in a DC line. This refers to the turns ratio of the transformer on the rectifier side. This refers to the turns ratio of the transformer on the inverter side; This refers to the voltage amplitude of the converter. This refers to the commutation angle of the rectifier; The extinction angle of the inverter; The transformer reactance on the rectifier side; The transformer reactance on the inverter side; When the converter station is operating in rectification mode, the DC channel transmits electrical energy outward. When the converter station is operating in inverter mode, the DC channel receives electrical energy from the outside. For regular communication nodes, A special AC node connected to a DC node;

[0131] Nodal reactive power balance constraints:

[0132] ;

[0133] ;

[0134] In the formula, For nodes The generator outputs reactive power; For nodes Power injected by the reactive power compensation device; For nodes Reactive load; For nodes The generator outputs reactive power; For nodes Power injected by the reactive power compensation device; For nodes Reactive load; The power factor angle on the rectifier side; The power factor angle on the inverter side;

[0135] Node voltage constraints:

[0136] ;

[0137] In the formula, The set of all nodes; This refers to the node voltage amplitude. , These are the lower and upper limits of the node voltage amplitude, respectively;

[0138] Generator active power constraints:

[0139] ;

[0140] In the formula, This is the set of all generators; Let be the active power of the generator set at node i; , Let be the lower and upper limits of the active power of the generator set at node i;

[0141] Generator reactive power constraints:

[0142] ;

[0143] In the formula, Let be the reactive power of the generator set at node i; , These are the lower and upper limits of the reactive power of the generator set at node i, respectively;

[0144] Line thermal stability constraints:

[0145] ;

[0146] In the formula, busbar The current; busbar The upper limit of the current amplitude;

[0147] Bus voltage constraint:

[0148] ;

[0149] In the formula, , busbars The lower and upper limits of voltage amplitude.

[0150] S4. The calculated bidirectional TTC value is used as the transmission capacity constraint of the transmission section and fed back into the inter-provincial power trading model to re-perform inter-provincial clearing and intra-provincial clearing, resulting in an updated pre-clearing operation mode. Meta-heuristic algorithms such as particle swarm optimization are used to jointly solve the model. After each calculation of TTC using the optimal power flow method, the parameters of the particle swarm optimization are updated. The particle update formula is as follows:

[0151] .

[0152] In the formula, No. Individual particles The speed of time; No. Individual particles The speed of time; Inertial weights; For individual learning factors; As a social learning factor; , It is a random number; For the first The best historical position of each particle; This represents the historical best position for all particles. No. Individual particles The position at that moment; No. Individual particles The position at any given moment.

[0153] S5. Repeat steps S3 and S4 until the error between the two calculated TTC values ​​is less than the set threshold. Output the inter-provincial transaction plan and cross-sectional transmission limit at this time as the final optimization result.

[0154] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any person skilled in the art can make many possible variations and modifications to the technical solution of the present invention, or modify it into equivalent embodiments, without departing from the scope of the present invention. Therefore, any modifications, equivalent changes, and alterations made to the above embodiments based on the technology of the present invention without departing from the scope of the present invention are within the protection scope of the present invention.

Claims

1. A method for inter-provincial mutual assistance optimization based on bidirectional TTC computational constraints, characterized in that: The method includes, S1. Based on the power grid topology, unit parameters, load and new energy forecast data, construct a provincial clearing transaction model to conduct pre-clearing of the provincial power market, and obtain information on the provincial unit combination, output plan and surplus or deficit power after provincial balance. S2. Based on the surplus or shortage of electricity in each province, construct an inter-provincial electricity trading model. With the goal of maximizing the total system price difference, consider the bids of both buyers and sellers, transmission prices and network losses, and conduct centralized bidding and clearing between provinces to obtain a preliminary inter-provincial trading plan and power distribution of key sections, which serves as the pre-clearing operation mode. S3. The pre-clearing operation mode is taken as the initial operation state and input into the TTC calculation model of the bidirectional total transmission capacity of the AC / DC hybrid power grid that takes into account the UHVDC transmission / reception, and the dynamic transmission limit of the key section in the positive and negative power transmission directions is calculated respectively. S4. The calculated bidirectional TTC value is used as the transmission capacity constraint of the transmission section and fed back into the inter-provincial power trading model to re-perform inter-provincial clearing and intra-provincial clearing to obtain an updated pre-clearing operation mode. S5. Repeat steps S3 and S4 until the error between the two calculated TTC values ​​is less than the set threshold. Output the inter-provincial transaction plan and cross-sectional transmission limit at this time as the final optimization result.

2. The inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints according to claim 1, characterized in that: The objective function of the intra-provincial clearing transaction model is: ； In the formula, and These are the unit start-up and shutdown cost variables and the unit output cost variables, respectively. and These are the unit start-up and shutdown constraint constant matrix and the unit output constraint constant matrix, respectively. The right-hand constraint vector; These are the 0 and 1 variables in the unit combination; These are continuous variables in the unit combination.

3. The inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints according to claim 1, characterized in that: The objective function of the inter-provincial power trading model is: ； In the formula, The objective function is... The total cost of electricity purchase for the electricity purchaser; The total electricity sales revenue of the power generation entity; The penalty cost for defaulting on DC nodes; For nodes Electricity purchasing entities exist Trading volume at any given moment; For nodes Electricity purchasing entities exist The declared price at any given time; For nodes On the power generation main body exist Trading volume at any given moment; For nodes On the power generation main body exist The declared price at any given time; For nodes Upper DC channel in Transmission power at any given time node The contract for the DC channel is stipulated Transmission power at any given moment; The penalty price for breach of contract; This refers to all electricity purchasing entities. For all power generation entities; A collection of power generation entities capable of participating in DC power transmission.

4. The inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints according to claim 3, characterized in that: The constraints of the inter-provincial power trading model include: Application volume constraints: ； In the formula, For the buyer's entity Maximum load at any given moment; For the seller's entity Maximum output capacity at any given moment; For the seller's entity Pre-emptive clearing capacity at specific times; Trading volume constraints: ； In the formula, For the main body of electricity purchase exist The amount of electricity purchased as declared at any given time; Main generator exist The amount of electricity sold as declared at any given time; Unit output constraints: ； In the formula, For generator sets The upper limit of active power; For generator sets The lower limit of active power; For generator sets The upper limit of reactive power; For generator sets The lower limit of reactive power; For generator sets Active power at time t; For generator sets Reactive power at time t; Unit ramp-up constraints: ； In the formula, For generator sets Maximum power output when climbing a hill; For generator sets Maximum power output when climbing downhill; Node power balance constraints: ； In the formula, The set of all nodes. For nodes Connected, and outgoing nodes The set of channels; For nodes Connected, and flowing into the node The set of channels; For channel exist The power transmission value at any given time; For channel exist The power input value at any given time; Transmission line transmission limit constraints: ； In the formula, For the province With Province Transmission capacity of the connecting line section between them; For the province With Province The TTC value between; Power allocation rules: ； In the formula, generator set The electricity allocated for sale at time t. For the main body of electricity purchase exist The power purchase and allocation at any time, for This represents the number of trade pairs with the same price spread and the same seller entity. The number of trade pairs with the same price difference and the same buyer entity; DC output / receiver penalty constraints: ； In the formula, , The DC transmission fluctuation factor under different operating conditions; The DC power transmission capacity is specified in the medium- and long-term contract. The DC input power specified in the medium- and long-term contract; 5. The inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints according to claim 1, characterized in that: The objective function of the TTC calculation model is: ； In the formula, province With provinces The transmission power of each line contained in the key cross-section.

6. The inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints according to claim 5, characterized in that: The constraints of the TTC calculation model include: N-1 verification: ； In the formula, , Components The system's control and state variables when a fault occurs; Nodal active power balance constraints: ； ； In the formula, For nodes The generator outputs active power; For nodes Active load; AC / DC hybrid node The generator outputs active power; AC / DC hybrid node Active load; For nodes Voltage amplitude; For nodes Voltage amplitude; For nodes , The admittance magnitude between; For nodes Voltage phase angle; For nodes Voltage phase angle; For nodes , The admittance phase angle between them; AC / DC hybrid node Voltage amplitude; For nodes , The admittance magnitude between; AC / DC hybrid node Voltage phase angle; For nodes , The admittance phase angle between them; This is the rectifier voltage on the DC side; This is the inverter voltage on the DC side; This refers to the current in a DC line. This refers to the turns ratio of the transformer on the rectifier side. This refers to the turns ratio of the transformer on the inverter side; This refers to the voltage amplitude of the converter. This refers to the commutation angle of the rectifier; The extinction angle of the inverter; The transformer reactance on the rectifier side; The transformer reactance on the inverter side; When the converter station is operating in rectification mode, the DC channel transmits electrical energy outward. When the converter station is operating in inverter mode, the DC channel receives electrical energy from the outside. , For regular communication nodes, A special AC node connected to a DC node; Nodal reactive power balance constraints: ； ； In the formula, For nodes The generator outputs reactive power; For nodes Power injected by the reactive power compensation device; For nodes Reactive load; For nodes The generator outputs reactive power; For nodes Power injected by the reactive power compensation device; For nodes Reactive load; The power factor angle on the rectifier side; The power factor angle on the inverter side; Node voltage constraints: ； In the formula, The set of all nodes; This refers to the node voltage amplitude. , These are the lower and upper limits of the node voltage amplitude, respectively; Generator active power constraints: ； In the formula, This is the set of all generators; Let be the active power of the generator set at node i; , Let be the lower and upper limits of the active power of the generator set at node i; Generator reactive power constraints: ； In the formula, Let be the reactive power of the generator set at node i; , These are the lower and upper limits of the reactive power of the generator set at node i, respectively; Line thermal stability constraints: ； In the formula, busbar The current; busbar The upper limit of the current amplitude; Bus voltage constraint: ； In the formula, , busbars The lower and upper limits of voltage amplitude.

7. The inter-provincial mutual assistance optimization method based on bidirectional TTC computational constraints according to claim 5, characterized in that: The model is solved jointly using the particle swarm optimization algorithm, and the particle update formula is as follows: ； In the formula, No. Individual particles The speed of time; No. Individual particles The speed of time; Inertial weights; For individual learning factors; As a social learning factor; , It is a random number; For the first The best historical position of each particle; This represents the historical best position for all particles. No. Individual particles The position at that moment; No. Individual particles The location at any given moment.

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