CN111798046B - Method, device and storage medium for clearing medium- and long-term inter-provincial transactions taking into account ATC - Google Patents

Abstract

The present invention discloses a modeling method, device and storage medium for clearing medium- and long-term transactions between provinces taking into account ATC, including simplification of AC/DC hybrid power grid and calculation of sensitivity factors in clearing of concentrated transactions between provinces; organization of concentrated bidding transactions between provinces and release of information to market members; transaction declaration by market members; aggregation of declaration curves in each price zone; adoption of a partition optimization clearing model based on sensitivity factors; partition clearing taking into account transmission charges and network losses to form the winning power and electricity price of each market member; release of transaction results as a basis for settlement; aggregation declaration for purchase and sale price zones, realization of purchase and sale price zone clearing and partition pricing, thus improving the executability of medium- and long-term transactions between provinces, mining price signals for medium- and long-term transactions between provinces, contributing to the development of medium- and long-term transactions between provinces, and promoting the consumption of clean energy in my country.

Description

Method, device and storage medium for clearing medium- and long-term inter-provincial transactions taking into account ATC

Technical Field

The present invention belongs to the technical field of electric power automation, and in particular relates to a method, device and storage medium for modeling medium- and long-term inter-provincial transactions clearing taking into account ATC.

Background technique

Due to its vast territory and the differences in resource endowments in various regions, my country has long relied on UHV lines to achieve large-scale resource optimization through medium- and long-term transactions between provinces. my country currently has 11 UHV DC lines in operation and 10 UHV AC lines in operation. With the approval and reconstruction of the UHV power grid, the transmission channels between the 27 provinces within the business scope of State Grid Corporation will become more and more complicated. How to optimize and clear medium- and long-term transactions between provinces based on the AC/DC hybrid power grid and take into account ATC (available transmission capacity) and improve the feasibility of medium- and long-term transactions between provinces is a problem that needs to be studied and solved. Due to the differences in resource endowments in various regions, my country has long relied on UHV lines to achieve large-scale resource optimization through medium- and long-term transactions between provinces. With the deepening of power market reform, the actual demand for overall coordinated and optimized allocation of power resources has highlighted the importance and urgency of building a unified national power market.

Summary of the invention

The present invention provides a modeling method, device and storage medium for clearing medium- and long-term inter-provincial transactions taking into account ATC, so as to solve the above-mentioned problems existing in the prior art. The modeling method for optimizing clearing medium- and long-term inter-provincial transactions taking into account ATC is based on a simplified equivalent network structure, takes into account the physical operation characteristics of AC transmission lines and DC transmission lines, takes into account the ATC parameters of the available transmission capacity of the lines, takes into account the existing charging methods of inter-provincial transmission channels in my country and line network losses, establishes a partition optimization model based on sensitivity factors, and realizes the optimization modeling of medium- and long-term inter-provincial transactions taking into account ATC and the clearing of partition electricity prices in an AC/DC hybrid power grid.

The present invention proposes a modeling method for clearing medium- and long-term inter-provincial transactions taking into account ATC, comprising: obtaining the available transmission capacity ATC and simplified topological relationship of each transmission channel in the power trading network, calculating the sensitivity factors of key nodes and key sections; and obtaining the declared data of each market member in the power trading market, forming an aggregation curve with the declared data, performing partition optimization clearing based on the aggregation curve combined with the sensitivity factor, and establishing a maximum optimization objective function for optimizing the transmission price and the network loss rate; the maximum optimization objective function has constraints; solving the maximum optimization objective function, and using the solution result to guide the purchase and sale price zone clearing and partition pricing.

Preferably, before calculating the sensitivity factor, it further includes: first simplifying the AC/DC hybrid power grid to retain key sections and key nodes for inter-provincial transactions.

Preferably, in any one of the above embodiments, the key interface includes all inter-provincial DC and AC transmission sections, as well as key sections within the province that are prone to congestion; the key nodes include the endpoints of the DC interconnection lines, the generator set nodes that directly participate in inter-provincial transactions, and the virtual aggregation nodes that are represented by provincial companies to participate in inter-provincial transactions.

Preferably, in any of the above embodiments, when the declared data are formed into an aggregate curve, the declared data of market members in each price zone are aggregated, and the electricity declared at the same price is merged to obtain the electricity purchase demand curve and electricity sales curve summarized in each price zone.

In any of the above embodiments, preferably, the following objective function is used to optimize the transmission price:

Where o is an element in the electricity price zone set O, d is an element in the electricity purchase price zone set D, p _o is the declared electricity price in the electricity price zone o, and p _d is the declared electricity purchase price in the electricity purchase price zone d. DX _d (t) is the proportion of electricity winning bids in the electricity purchase price zone d in period t; SX _o (t) is the proportion of electricity winning bids in the electricity price zone o in period t;

The following objective function is used to optimize the network loss rate:

b _l (t) = p _o (t) * u _l / (1-u _l ) + m _l

Wherein, b _l (t) is the transmission price ml on transmission channel l at time t in period _plus network loss discount, and _ul is the network loss rate of transmission channel l.

In any of the above embodiments, preferably, the constraint conditions of the maximum optimization objective function are set; including

1) Power balance constraints in each price zone

Among them, Start _a,l represents the transmission channel with the a price zone as the starting point, and End _a,l represents the transmission channel with the a price zone as the end point. It means that the transmission channel l transmits power in the positive direction during the period t,/> represents the reverse transmission power of transmission channel l in time period t, SX _a (t) represents the winning proportion of the electricity sales demand reported in price zone a, and DX _a (t) represents the winning proportion of the electricity purchase demand reported in price zone a;

2) Power Constraints for Winning Bids

The winning bid power in each price zone does not exceed the declared demand, and the winning bid ratio is between 0 and 1;

0≤DX _d (t)≤1

0≤SX _o (t)≤1

3) Requirements for the rate of change of power flow in DC transmission channels

Wherein, _fl (t-1) represents the power flow on the transmission channel l at time t-1; RampUp is the maximum power increase value allowed by the transmission channel; RampDn is the maximum power decrease value allowed by the transmission channel;

4) Constraints on the number of power flow changes per day on the DC transmission channel

y _ij (t)＝1if _fl (t)＞f _l (t-1) t, t-1∈the same day

z _ij (t) = 1 if _fl (t) < _fl (t-1) t and t-1∈ the same day

y _ij (t)+z _ij (t)≤N _ij

y _ij (t) = 1 means that the power at time t on the transmission channel (i, j) changes upward;

z _ij (t) = 1 means that the power at time t on the transmission channel (i, j) changes downward;

N _ij is the maximum number of changes in the transmission channel (i, j) in one day;

5) Transmission channel power calculation based on sensitivity factor

For transmission channel l, the power flow calculation of the transmission channel is performed based on the sensitivity factor from the node to the key section. Sens(o,l,t) represents the sensitivity factor of the electricity sales price zone o to the transmission channel l in the t period, and Sens(d,l,t) represents the sensitivity factor of the electricity purchase price zone d to the transmission channel l in the t period. AC represents the set of AC sections;

6) Transmission channel capacity constraints

ATC _l (t) is the remaining available transmission capacity of transmission channel l at time t. The calculation needs to take into account the maintenance, outage and completed transactions of transmission equipment;

is the power transmitted in the forward and reverse directions on the transmission channel l;

7) Transmission channel set constraints

If there are multiple transmission channels that provide a total available transmission capacity, a transmission channel cluster is established and constraints are imposed on the cluster: if multiple transmission channels l share a total transmission capacity parameter ATC _T (t), these transmission channels are added to the T cluster;

8) Partition pricing constraints

The shadow price is calculated according to the power balance constraint of the partition to obtain the partition node electricity price price(a,t), and the recovery of transmission fee is ensured by the following constraints;

price(a,t)-price(a',t)≥m _l (t)

m _l (t) represents the transmission fee of transmission channel l in time period t, price(a,t) represents the price of price zone a at the beginning of transmission channel; price(a',t) represents the price of price zone a' at the end of transmission channel l.

Preferably, in any of the above embodiments, when the optimization algorithm is used to optimize the objective function, a mixed integer programming algorithm is used, and the COMPLEX optimization engine is used to solve the problem, so as to obtain the winning power ratio of the power purchase price zone in the time period and the winning power ratio of the power sales price zone in the time period, and obtain the power of each transmission channel in each time period; according to the obtained winning purchase and sales power ratio, the purchase and sale price zone clearing and zone pricing are adjusted; according to the power of each transmission channel in each time period, the clearing order is adjusted; after the transaction is concluded in the clearing order, the winning power and electricity price of each market member are formed, and the transaction results are published as the basis for settlement.

Preferably, in any of the above embodiments, when the zoning optimization clearing with sensitivity factors is adopted, the transmission price and network loss rate corresponding to each UHV transmission channel are determined by using the maximum optimization objective function, and the determined transmission price and network loss rate are used to guide the zoning pricing of the area to which the UHV transmission channel belongs.

The present invention also proposes a medium- and long-term inter-provincial transaction clearing device taking ATC into account, comprising:

The data acquisition module is used to obtain the available transmission capacity ATC and simplified topological relationship of each transmission channel in the power trading network, calculate the sensitivity factors of key nodes and key sections; and obtain the declared data of each market member in the power trading market, and form an aggregate curve with the declared data;

An objective function establishment module is used to perform partition optimization clearing based on the aggregation curve combined with the sensitivity factor, and establish a maximum optimization objective function for optimizing the transmission price and the network loss rate; the maximum optimization objective function has constraints;

A solution module is used to solve the maximum optimization objective function and use the solution results to guide the purchase and sale price zone clearance and zone pricing.

The present invention further provides a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned modeling method are implemented.

The method, device and storage medium for clearing inter-provincial medium- and long-term transactions taking into account ATC of the present invention propose a modeling method for clearing inter-provincial medium- and long-term transactions taking into account ATC in view of the current situation of my country's AC/DC hybrid power grid. Considering the available transmission capacity (ATC) of the line, the transmission fee and network loss of the ultra-high voltage transmission channel, and the different operating characteristics of the AC and DC transmission channels, the purchase and sale price zones are aggregated and declared, and the purchase and sale price zone clearing and zone pricing are realized, which improves the executability of inter-provincial medium- and long-term transactions, excavates the price signals of inter-provincial medium- and long-term transactions, helps to promote the development of inter-provincial medium- and long-term transactions, and is conducive to promoting the consumption of clean energy in my country.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

FIG1 is a flow chart of a method for clearing inter-provincial medium- and long-term transactions taking ATC into account proposed by the present invention.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present invention belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

As shown in FIG1 , the present invention provides a modeling method for clearing medium- and long-term inter-provincial transactions taking into account ATC, comprising the following steps:

S1. Obtain the available transmission capacity ATC and simplified topological relationship of each transmission channel in the power trading network, and obtain the sensitivity factors of key nodes and key sections by power flow calculation;

S2. Obtain the declared data of each market member in the power trading market and form an aggregate curve with the declared data;

S3, based on the aggregation curve combined with the sensitivity factor, the partition optimization clearing is carried out to establish the maximum optimization objective function for optimizing the transmission price and network loss rate;

S4, setting the constraints of the maximum optimization objective function;

S5. Use optimization algorithms to solve the objective function and use the solution results to guide the clearing of purchase and sale price zones and zone pricing.

Among them, the execution order of step S1 and step S2 is not in particular order, and they can be executed simultaneously. In S1, various types of transaction information released by the Beijing Power Exchange Center are obtained from the exchange center, including organizing inter-provincial centralized bidding transactions, publishing transaction cycles, market access members, transaction declaration windows, available transmission capacity (ATC) on each transmission channel, etc., as well as simplified network topology information; before calculating the sensitivity factor, the AC/DC hybrid power grid is simplified, the key sections and key nodes of inter-provincial transactions are retained, and an equivalent simplified network suitable for the organization of inter-provincial medium- and long-term transactions is constructed. The key interface includes all inter-provincial DC and AC transmission sections, as well as key sections that are easily blocked within the province; the key nodes include the endpoints of the DC tie line, the nodes of the generator sets that directly participate in inter-provincial transactions, and the virtual aggregation nodes that are represented by the provincial company to participate in inter-provincial transactions.

In S2, when obtaining the declared data of each market member in the power trading market, since the market members in each price zone of the Beijing Power Trading Center can choose to directly participate in the inter-provincial centralized bidding transaction, or choose to participate in the inter-provincial centralized bidding transaction through the provincial company as an agent, each market member is allowed to declare different power and electricity prices in different time periods; therefore, the declared data of market members in each price zone are collected, and the declared power at the same price is merged to obtain the power purchase demand curve and power sales curve after the summary of each price zone.

Based on the aggregation curve reported in the price zone, the social welfare maximum optimization objective considering transmission costs and network losses was established:

Where o is an element in the electricity price zone set O, d is an element in the electricity purchase price zone set D, p _o is the declared electricity price in the electricity price zone o, and p _d is the declared electricity purchase price in the electricity purchase price zone d. DX _d (t) is the proportion of electricity winning bids in the electricity purchase price zone d during period t; SX _o (t) is the proportion of electricity winning bids in the electricity price zone o during period t.

The following objective function is used to optimize the network loss rate:

b _l (t) = p _o (t) * u _l / (1-u _l ) + m _l

Wherein, b _l (t) is the transmission price ml on transmission channel l at time t in period _plus network loss discount, and _ul is the network loss rate of transmission channel l.

In S4, when setting the constraints of the maximum optimization objective function; including

1) Power balance constraints in each price zone

Among them, Start _a,l represents the transmission channel with price zone a as the starting point, and End _a,l represents the transmission channel with price zone a as the end point. It means that the transmission channel l transmits power in the positive direction during the period t,/> represents the reverse transmission power of transmission channel l in time period t, SX _a (t) represents the winning proportion of the electricity sales demand reported in price zone a, and DX _a (t) represents the winning proportion of the electricity purchase demand reported in price zone a;

2) Power Constraints for Winning Bids

The winning bid power in each price zone does not exceed the declared demand, and the winning bid ratio is between 0 and 1;

0≤DX _d (t)≤1

0≤SX _o (t)≤1

3) Requirements for the rate of change of power flow in DC transmission channels

f _l (t-1) represents the power flow on the transmission channel l at time t-1; RampUp is the maximum power increase value allowed by the transmission channel; RampDn is the maximum power decrease value allowed by the transmission channel;

4) Constraints on the number of power flow changes per day on the DC transmission channel

y _ij (t)＝1if _fl (t)＞f _l (t-1) t, t-1∈the same day

z _ij (t) = 1 if _fl (t) < _fl (t-1) t and t-1∈ the same day

y _ij (t)+z _ij (t)≤N _ij

y _ij (t) = 1 means that the power at time t on the transmission channel (i, j) changes upward;

z _ij (t) = 1 means that the power at time t on the transmission channel (i, j) changes downward;

N _ij is the maximum number of changes in the transmission channel (i, j) in one day;

5) Transmission channel power calculation based on sensitivity factor

For transmission channel l, the power flow calculation of the transmission channel is performed based on the sensitivity factor from the node to the key section. Sens(o,l,t) represents the sensitivity factor of the electricity sales price zone o to the transmission channel l in the t period, and Sens(d,l,t) represents the sensitivity factor of the electricity purchase price zone d to the transmission channel l in the t period. AC represents the set of AC sections;

6) Transmission channel capacity constraints

ATC _l (t) is the remaining available transmission capacity of transmission channel l at time t. The calculation needs to take into account the maintenance, outage and completed transactions of transmission equipment;

_fl ⁺ (t) _-fl- ⁽ t)＝ _fl (t)

_fl ⁺ (t) and _fl ^- (t) are the forward and reverse powers transmitted on the transmission channel l;

7) Transmission channel set constraints

If there are multiple transmission channels that provide a total available transmission capacity, a transmission channel cluster is established and constraints are imposed on the cluster: if multiple transmission channels l share a total transmission capacity parameter ATC _T (t), these transmission channels are added to the T cluster;

8) Partition pricing constraints

The shadow price is calculated according to the power balance constraint of the partition to obtain the partition node electricity price price(a,t), and the recovery of transmission fee is ensured by the following constraints;

price(a,t)-price(a',t)≥m _l (t)

m _l (t) represents the transmission fee of transmission channel l in time period t, price(a,t) represents the price of price zone a at the beginning of transmission channel; price(a',t) represents the price of price zone a' at the end of transmission channel l.

In S5, when the optimization algorithm is used to optimize the objective function, a mixed integer programming algorithm is used, and the COMPLEX optimization engine is used to solve the winning power ratio DX _d (t) of the purchase price zone d in the period t and the winning power ratio SX _o (t) of the sales price zone o in the period t, and the power _fl (t) of each transmission channel in each period is obtained. The solution result is used to guide the adjustment of the purchase and sale price zone clearing and zone pricing; the purchase and sale price zone clearing and zone pricing are adjusted according to the obtained winning purchase and sale power ratio; the clearing order is adjusted according to the power in each period, and the winning power and electricity price of each market member are formed after the transaction is completed, and the transaction results are released as the basis for settlement.

In S3, in combination with the current situation of UHV operation in my country, in order to adjust the zoning pricing more accurately, in one embodiment of the present invention, an objective function is established for each UHV transmission channel, and a transmission price and network loss rate are determined for each UHV transmission channel using the function, and the determined transmission price and network loss rate are used to guide the zoning pricing of the area to which the UHV transmission channel belongs. It should be noted that when guiding zoning pricing, the result of solving the maximum optimization objective function should be the first priority, and the transmission price and network loss rate determined for the UHV transmission channel should be adjusted as the second priority reference.

This method first merges the declared demands of the purchase and sale price zones according to the price, and then constructs the maximum optimization target of social welfare considering transmission fees and network losses, establishes the power balance constraint, winning power constraint, flow change rate requirement of the DC transmission channel, daily flow change number constraint on the DC transmission channel, transmission channel power calculation based on sensitivity factor, transmission channel capacity constraint, transmission channel collection constraint and zone pricing constraint for each price zone, realizes the clearing of medium- and long-term transactions between provinces and the mining of zone electricity price signals; aggregate declaration is carried out for the purchase and sale price zones, the clearing of purchase and sale price zones and zone pricing are realized, the feasibility of medium- and long-term transactions between provinces is improved, the price signals of medium- and long-term transactions between provinces are mined, which is helpful to promote the development of medium- and long-term transactions between provinces and is conducive to promoting the consumption of clean energy in my country.

The present invention also proposes a modeling device for clearing inter-provincial medium- and long-term transactions taking into account ATC, and a data acquisition module for obtaining the available transmission capacity ATC and simplified topological relationships of each transmission channel in the power trading network, calculating the sensitivity factors of key nodes and key sections; and obtaining the declared data of each market member in the power trading market, and forming an aggregate curve with the declared data;

An objective function establishment module is used to perform partition optimization clearing based on the aggregation curve combined with the sensitivity factor, and establish a maximum optimization objective function for optimizing the transmission price and the network loss rate; the maximum optimization objective function has constraints;

A solution module is used to solve the maximum optimization objective function and use the solution results to guide the purchase and sale price zone clearance and zone pricing.

The present invention also proposes a computer storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned modeling method are implemented, namely, a modeling method for optimizing the clearing of inter-provincial medium- and long-term transactions based on sensitivity factors, transmission charges, network losses, and ATC.

Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

The present invention is described with reference to the flowchart and/or block diagram of the method, device (system), and computer program product according to the embodiment of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of the process and/or box in the flowchart and/or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

Claims (8)

1. A method for clearing transaction between provinces in medium and long term taking account of ATC is characterized in that: comprising the following steps:

the method comprises the steps of obtaining available transmission capacity ATC and simplified topological relation of each transmission channel in a power transaction network, and calculating sensitivity factors of key nodes and key sections; acquiring declaration data of each market member in the electric power trade market, and forming a polymerization curve from the declaration data;

Carrying out partition optimization clearing based on an aggregation curve and combining sensitivity factors, and establishing a social benefit maximum optimization objective function considering power transmission price and network loss rate; the maximum optimization objective function has constraint conditions;

Solving the maximum optimization objective function, and guiding the clearing of the purchase price region and the pricing of the region by utilizing the solving result;

The following objective function is adopted to optimize the power transmission price:

Wherein O is an element in the electricity selling price area set O, D is an element in the electricity purchasing price area set D, p _o is the electricity selling price declared by the electricity selling price area O in the t period, and p _d is the electricity purchasing price declared by the electricity purchasing price area D in the t period; DX _d (t) is the proportion of the bid-winning electric power in the t period of the electricity purchase price region d; SX _o (t) is the proportion of the bid-up power in the t period in the electricity price selling area o;

Optimizing the network loss rate by adopting the following objective function:

b_l(t)＝p_o(t)*u_l/(1-u_l)+m_l

wherein b _l (t) is the transmission price m _l of the transmission channel l at the time of the period t plus the grid loss discount price, and u _l is the grid loss rate of the transmission channel l;

Constraints of the maximum optimization objective function include,

1) Power balance constraint per price zone:

Wherein, start _a,l represents a power transmission channel taking a price area as a starting point, end _a,l represents a power transmission channel taking the price area as an End point, f _l ⁺ (t) represents forward power transmission of power transmission channel l in t period, f _l ^- (t) represents reverse power transmission of power transmission channel l in t period, SX _a (t) represents a bid-in-bid ratio of electricity-selling requirements declared in the price area, DX _a (t) represents a bid-in-bid ratio of electricity-purchasing requirements declared in the price area;

2) Winning power constraint:

The winning power of each price zone does not exceed the declaration requirement, and the winning proportion is between 0 and 1;

0≤DX_d(t)≤1

0≤SX_o(t)≤1

3) The power flow change rate requirement of the direct current transmission channel is as follows:

wherein f _l (t-1) represents the power flow at time t-1 on the transmission channel l; rampUp is the allowable maximum power up-regulation value of the transmission channel; rampDn the transmission channel allows the maximum power to be adjusted down;

4) The daily tide change times constraint on the direct current transmission channel:

y _ij(t)＝1 if f_l(t)＞f_l (t-1) t, t-1 ε same day

Z _ij(t)＝1 if f_l(t)＜f_l (t-1) t, t-1 ε same day

y_ij(t)+z_ij(t)≤N_ij

Y _ij (t) =1 indicates that there is a change in power at time t on the transmission channel (i, j) upward;

z _ij (t) =1 indicates that there is a downward change in power at time t on the transmission channel (i, j);

N _ij represents the maximum number of changes over a day of the transmission path (i, j);

5) Sensitivity factor-based power transmission channel power calculation:

aiming at the power transmission channel l, carrying out power flow calculation of the power transmission channel based on sensitivity factors from the nodes to the key sections; sens (o, l, t) represents the sensitivity factor of the selling price area o to the power transmission channel l over the t period, and Sens (d, l, t) the purchasing price area d to the power transmission channel l over the t period; AC represents a collection of alternating current sections;

6) Power transmission channel capacity constraints:

ATC _l (t) is the remaining available transmission capacity of transmission channel l at t, and the conditions of overhauling, stopping operation and transaction of transmission equipment are considered during calculation;

f_l ⁺(t)-f_l ^-(t)＝f_l(t)

7) Power transmission channel set constraint:

If there are multiple power transmission channels providing an aggregate available power transmission capacity, a cluster of power transmission channels is established, and constraints are placed on this cluster: adding a plurality of power transmission channels to a T cluster if the plurality of power transmission channels share an aggregate power transmission capacity parameter ATC _T (T);

8) Partition pricing constraints:

Calculating shadow prices according to the partition power balance constraint to obtain partition node power price (a, t), and ensuring recovery of power transmission fees through the following constraint;

price(a,t)-price(a',t)≥m_l(t)

m _l (t) represents the power transmission fee of the power transmission channel l in the period t, and price (a, t) represents the price of the head end price zone a of the power transmission channel; price (a ', t) represents the price of the terminal price zone a' of transmission channel l.

2. The method of claim 1, further comprising, prior to the sensitivity factor calculation: and simplifying the AC/DC series-parallel power grid, and reserving key sections and key nodes of inter-provincial transaction.

3. The method according to claim 2, characterized in that: the key sections comprise all inter-provincial direct current and alternating current power transmission sections and key sections which are easy to block in the provincial; the key nodes comprise end points at two ends of the direct current tie line, a generator set node directly participating in the inter-provincial transaction, and a virtual aggregation node which is participated in the inter-provincial transaction by the agency of the provincial company.

4. The method according to claim 1, characterized in that: when reporting data form an aggregation curve, collecting reporting data of market members in each price area, and combining reporting power of the same price to obtain a power purchasing demand curve and a power selling curve after the reporting data are collected in each price area.

5. The method according to claim 1, characterized in that: the solving the maximum optimization objective function comprises the following steps:

Adopting a mixed integer programming algorithm, and solving by using a COMPLEX optimization engine to obtain the proportion of the bid-in power of the electricity purchase price region in the t period and the proportion of the bid-in power of the electricity selling price region in the t period, so as to obtain the power of each power transmission channel in each period;

According to the obtained winning bid purchase and sale power proportion, adjusting the clearing of the purchase and sale price area and the pricing of the subarea; according to the power of each transmission channel in each period, the clearing sequence is adjusted;

After the trade is achieved according to the clearing order, the winning bid power and the electricity price of each market member are formed, and the trade result is issued as a settlement basis.

6. The method according to claim 1, characterized in that: when the sensitivity factor is adopted for partition optimization, the maximum optimization objective function is utilized to check the corresponding power transmission price and the network loss rate of each extra-high voltage power transmission channel, and the checked power transmission price and the checked network loss rate are used for guiding the partition pricing of the region to which each extra-high voltage power transmission channel belongs.

7. An inter-provincial medium-long term transaction clearing device considering ATC, which is characterized in that: for performing the method of claim 1, comprising

The data acquisition module is used for acquiring the available transmission capacity ATC of each transmission channel in the power transaction network and simplifying the topological relation, and calculating the sensitivity factors of the key nodes and the key sections; acquiring declaration data of each market member in the electric power trade market, and forming a polymerization curve from the declaration data;

the objective function establishing module is used for carrying out partition optimization clearing based on the combination of the aggregation curve and the sensitivity factor, and establishing a maximum optimization objective function for optimizing the power transmission price and the network loss rate; the maximum optimization objective function has constraint conditions;

and the solving module is used for solving the maximum optimization objective function and guiding the purchase price region to be clear and the region pricing by utilizing the solving result.

8. A computer storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, implements the steps of a method of clearing as claimed in any one of claims 1 to 6.