CN114004646A - Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game - Google Patents

Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game Download PDF

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CN114004646A
CN114004646A CN202111279600.2A CN202111279600A CN114004646A CN 114004646 A CN114004646 A CN 114004646A CN 202111279600 A CN202111279600 A CN 202111279600A CN 114004646 A CN114004646 A CN 114004646A
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张梁
徐晶
李娟�
张章
崔荣靖
刘英英
孙阔
王哲
赵金利
田振
冀浩然
李鹏
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State Grid Tianjin Electric Power Co Ltd
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Abstract

The invention discloses a flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game, which comprises the following steps: the method comprises the steps that the lowest electric energy cost and the lowest node voltage deviation of all interconnected power distribution network areas in a flexible interconnected power distribution system are taken as targets, a cost function of a time period t about transaction power is formed through power flow analysis, and active power limit output by an intelligent soft switch port is obtained; distributed market clearing calculation among all interconnected distribution network areas is carried out based on a non-cooperative game, and under the premise of realizing privacy protection, clearing price and transaction active power of lower-layer end-to-end electric energy transaction at each time period are determined; the method comprises the steps that power loss of a converter is considered, and actual transmission power of an intelligent soft switch in each power distribution network area is obtained; and settling accounts between the power distribution network areas according to the transaction power and the clearing price, and settling accounts between each area of the power distribution network and the superior power network according to the actual transmission power and the electric energy price. The trading method can improve the voltage distribution of each region, promote the reduction of the operation cost of each region and consider privacy protection.

Description

Flexible power distribution network end-to-end electric energy transaction method and device based on non-cooperative game
Technical Field
The invention relates to the technical field of urban power grid planning and evaluation, in particular to a flexible power distribution network end-to-end electric energy trading method and device based on non-cooperative game.
Background
A large amount of accesses of new elements such as distributed power sources and electric vehicles provide higher requirements for operation of a power distribution network, and for meeting diversified and customized power utilization requirements of a user side, the traditional power distribution network is gradually developed into a highly flexible and controllable flexible interconnection structure from a traditional radial structure under the support of flexible power distribution equipment such as a multi-end multi-voltage-level intelligent soft Switch (SOP). All distribution network areas interconnected through the multi-terminal intelligent soft switch have multiple energy interaction ways, accurate and controllable power transmission is supported, and a physical foundation is laid for peer-to-peer (P2P) electric energy transaction of a multi-area flexible interconnected distribution network.
In the face of the end-to-end electric energy transaction requirement of a multi-region flexible interconnected power distribution network, how to realize fair and effective electric energy transaction among multi-benefit subjects and consider the influence of system operation constraint on the transaction become problems to be solved.
The key problem of end-to-end electric energy transaction is how to design a transaction mechanism with the characteristics of data privacy protection, information symmetry and fair competition. The distributed market clearing algorithm can be used for realizing end-to-end electric energy transaction of the flexible interconnected power distribution network with privacy protection and information symmetry. And the non-cooperative game competition rules can be used for realizing fair and reasonable profit competition among the areas.
At present, research on multi-region flexible interconnected power distribution networks at home and abroad mainly focuses on the establishment of operation optimization strategies of multi-terminal intelligent soft switches, and how to realize end-to-end electric energy transaction based on the intelligent soft switches needs to be further researched. Therefore, for the electric energy transaction requirement of a multi-region flexible interconnected power distribution network, an end-to-end electric energy transaction method which promotes the reduction of the operation cost of each region and considers privacy protection is needed.
Disclosure of Invention
The invention aims to solve the problems of fairness of transaction rules, protection of data privacy and the like in electric energy transaction of a flexible interconnected power distribution network, and provides a method and a device for flexible power distribution network end-to-end electric energy transaction based on a non-cooperative game.
The invention provides a flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game, which comprises the following steps:
the method comprises the steps that the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network region in a flexible interconnected power distribution system are taken as targets, a cost function of a time period t about transaction power is formed through power flow analysis, and active power limitation output by an intelligent soft switch port is obtained according to power flow constraint and safe operation constraint;
according to the cost function and the trend constraint and the safe operation constraint of each interconnected distribution network region, distributed market clearing calculation among the interconnected distribution network regions is carried out based on a non-cooperative game, and the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval are determined on the premise of realizing privacy protection;
the intelligent energy storage soft switch calculates and obtains the actual transmission power of the intelligent soft switch in each distribution network region according to the obtained lower-layer end-to-end electric energy transaction result and the cost function and by considering the power loss of the converter;
and settling accounts between the power distribution network areas according to the transaction power and the clearing price, and settling accounts between each area of the power distribution network and the superior power network according to the actual transmission power and the electric energy price.
Further, the cost function of the time period t formed by each interconnected distribution network area with respect to the transaction power is as follows:
Figure BDA0003326333370000021
Figure BDA0003326333370000022
in the formula (f)k，tRepresenting a cost function, pi, of the region k over a period ttElectric energy transaction prices among all regions determined in the lower-layer end-to-end electric energy transaction;
Figure BDA0003326333370000023
the electric energy price for electric energy transaction between each distribution network area and the superior power network;
Figure BDA0003326333370000024
respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;
Figure BDA0003326333370000025
respectively buying and selling active power to the upper-level power grid in a region k in a time period t; f. ofU，k，tK voltage offset cost function for time period t region; Δ t is the transaction period duration;
Figure BDA0003326333370000026
load power for node i；ωUAn out-of-load cost reduction factor for voltage overshoot; vi，tIs the square of the voltage at node i;
Figure BDA0003326333370000027
which is the square of the nominal voltage at node i.
Further, the power flow constraint is as follows:
Figure BDA0003326333370000028
Figure BDA0003326333370000029
Figure BDA00033263333700000210
Figure BDA00033263333700000211
Figure BDA00033263333700000212
Vi，t-Vj，t＝2(RijPij，t+XijQij，t) (8)
in the formula (I), the compound is shown in the specification,
Figure BDA0003326333370000031
branch and node sets of the region k respectively;
Figure BDA0003326333370000032
a node set of an intelligent energy storage soft switch access area k is obtained; pji，t、Qji，tRespectively the active power and the reactive power flowing through the branch ji at the time interval t; pik，t、Qik，tRespectively flowing on branch ik at time interval tPower and reactive power; pi，t、Qi，tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;
Figure BDA0003326333370000033
active power output and reactive power output of the distributed power supply are respectively time period t node i;
Figure BDA0003326333370000034
injecting active power into the intelligent energy storage soft switch at an access node;
Figure BDA0003326333370000035
respectively the active load and the reactive load of a node i in a time interval t; rij、XijRespectively the resistance and reactance of branch ij.
Further, the system safe operation constraints are as follows:
Figure BDA0003326333370000036
Figure BDA0003326333370000037
in the formula, omegaTA set of trade periods for a trade day; i isij，tThe current value of the branch ij is squared;
Figure BDA0003326333370000038
the upper limit of the square value of the current of the branch ij;
Figure BDA0003326333370000039
V ithe upper limit and the lower limit of the square value of the voltage of the node i are respectively;
wherein, the active power balance constraint of each region k can be expressed as follows:
Figure BDA00033263333700000310
Figure BDA00033263333700000311
in the end-to-end electric energy trading market, each region only serves as a buyer or a seller to participate in electric energy trading at the same time period, and the corresponding constraint can be expressed as:
Figure BDA00033263333700000312
Figure BDA00033263333700000313
in the formula, betak，tTaking 1 as a binary variable for representing the market identity of the area k in the time period t to represent the area k as a seller; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
Further, the distributed market clearing calculation method for the interconnected distribution network regions based on the non-cooperative game comprises the following steps:
a) setting the iteration number h as 1, and setting the electricity selling price of the initial end-to-end electric energy trading market in each area k
Figure BDA00033263333700000316
b) Each area collects the electricity selling price of other areas, and calculates whether the area is a buyer or a seller according to the highest electricity price, and the optimal electricity purchasing power
Figure BDA00033263333700000314
Or selling electric power
Figure BDA00033263333700000315
The calculation method is as follows:
Figure BDA0003326333370000041
Figure BDA0003326333370000042
in the formula (f)s，tAs a cost function of the seller s, fb，tA cost function for buyer b;
Figure BDA0003326333370000043
selling electricity and purchasing electric power for the seller s and the buyer b respectively;
c) the same auxiliary parameter M is generated and shared among sellers for privacy protectionhGenerating auxiliary variables for each seller s
Figure BDA0003326333370000044
And transmitted to each buyer; each buyer b calculates the electric energy demand amount distributed to each seller s according to the following formula:
Figure BDA0003326333370000045
ΩB∪ΩS＝ΩR (18)
in the formula, omegaBSet of buyer regions, ΩSFor set of vendor areas, ΩRIs a collection of areas of a flexible interconnected power distribution network,
Figure BDA0003326333370000046
distributing the obtained electric energy demand of the buyer b for the seller s;
d) each seller calculates and updates electricity selling price according to the following formula:
Figure BDA0003326333370000047
in the formula, σs，tAdjusting the factor for the seller s's electricity price;
e) judging whether the electricity price of each seller meets an iteration convergence condition, if so, terminating the iteration, if not, setting h to h +1, and repeating the steps b) to d), wherein the convergence condition is as follows:
Figure BDA0003326333370000048
in the formula, epsilon is the iterative convergence error of the selling price of the seller.
A flexible power distribution network end-to-end electric energy transaction device based on a non-cooperative game comprises the following components:
the cost function and power flow constraint and safe operation constraint acquisition module is used for forming a cost function of a time period t about transaction power through power flow analysis by taking the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring active power limit output by an intelligent soft switch port according to the power flow constraint and the safe operation constraint;
the clearing price and transaction active power acquisition module is used for performing distributed market clearing calculation among the interconnected distribution network regions based on a non-cooperative game according to the cost function and the trend constraint and the safe operation constraint of the interconnected distribution network regions, and determining the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for calculating and acquiring the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function of the intelligent energy storage soft switch by considering the power loss of the converter;
and the electric energy settlement module is used for settling among the power distribution network areas according to the transaction power and the clearing price, and settling between each area of the power distribution network and the superior power grid according to the actual transmission power and the electric energy price.
A computing device, comprising:
one or more processing units;
a storage unit for storing one or more programs,
wherein the one or more programs, when executed by the one or more processing units, cause the one or more processing units to perform the non-cooperative game based flexible distribution network end-to-end power trading method as described above.
A computer readable storage medium having non-volatile program code executable by a processor, the computer program when executed by the processor implementing a non-cooperative gambling based flexible power distribution network end-to-end power trading method as described above.
The invention has the advantages and positive effects that:
the invention discloses an end-to-end electric energy transaction method for a flexible interconnected power distribution network, which is based on the realization of electric energy transaction of fair competition among areas in the flexible interconnected power distribution network, takes the power adjustment of an intelligent soft switch as a transaction main body, fully considers the voltage control requirement of each area, constructs a cost function of each area about transaction power with the minimum electric energy cost and voltage deviation as targets, performs end-to-end electric energy transaction based on non-cooperative game according to the cost function with the highest self transaction profit as the target, realizes data privacy protection and market clearing by adopting a distributed algorithm, and further considers the loss of an intelligent soft switch converter to perform transaction power fine adjustment so that a transaction result meets the system operation constraint.
Drawings
FIG. 1 is a flow chart of a flexible power distribution network end-to-end electric energy transaction method based on non-cooperative game of the invention;
FIG. 2 is a schematic diagram of a four-terminal intelligent soft-switch flexible interconnection power distribution network in an exemplary area of Tianjin North Chen;
FIG. 3 is a photovoltaic, fan and load operating curve;
FIG. 4 is a superior grid power price curve;
FIG. 5 is a voltage distribution of each distribution network region under two schemes;
FIG. 6 is a cost reduction for zones in an end-to-end power transaction;
FIG. 7 is an end-to-end electric energy transaction active power of each zone after transaction trimming;
fig. 8 is an end-to-end trade electricity price result.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in the embodiments of the present invention. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are only some, but not all embodiments of the invention. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The invention discloses a flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game, which comprises the following steps as shown in figure 1:
inputting system parameters and network topology connection relations of each power distribution network region according to the selected flexible interconnected power distribution system, inputting access positions and related parameters of the intelligent soft switch, and using the adjusting power of the intelligent soft switch as an electric energy transaction object; inputting load and distributed power supply access positions, capacities and parameters; inputting a load and a daily operation curve of the distributed power supply; setting a system operation voltage level and a branch current limit; selecting a reference voltage and a reference power value; inputting the electric energy transaction price of each distribution network area and the superior power network in each time period t
Figure BDA0003326333370000061
(ii) a Setting the duration delta t of each transaction time interval in one operation day; inputting the unit cost of load loss under the extreme voltage excursion;
for the present embodiment, a distribution network including four-terminal intelligent soft switches in the Tianjin North-Chen demonstration area is shown in fig. 2, and the detailed parameters are shown in tables 1 and 2. The demonstration area takes a joint table 110kV transformer substation and a wind power park 110kV transformer substation as centers to form a double-loop network structure comprising four feeders, four distribution network areas are flexibly interconnected through four-end intelligent soft switches, the voltage grades are all set to be 10.5kV, and the total active power demand and the total reactive power demand of the load are 9.9880MW and 7.3350Mvar respectively.
To account for the access impact of the high permeability distributed power, the distributed power access case is shown in table 3. The distributed power supply power factors are all set to 1.0. The distributed power output and load demand curves are shown in fig. 3. The capacity of the current converter of each port of the four-end intelligent soft switch is set to be 3MVA, and the loss coefficient is set to be 0.01. The system reference power was set to 1 MVA. The safe voltage operation range of the active power distribution network is 0.90p.u. -1.10 p.u.
In one trading day, the duration Δ t of each trading session is set to 1 hour for a total of 24 trading sessions. The electric energy price curve of the superior electric network in each period is shown in fig. 4. Calculating a voltage offset cost coefficient omega according to the load loss costUSet to 0.011.
According to the provided system parameters, network topology, intelligent soft switch access positions, the capacities and daily operating curves of loads and distributed power supplies in each power distribution network region, and the electric energy price and the load loss unit cost parameters of a superior power grid, each interconnected power distribution network region k takes the lowest electric energy cost and the minimum node voltage deviation as targets, and a cost function f related to transaction power in a time period t is formed through load flow analysisk，tCalculating the output active power limit of the intelligent soft switch port according to the power flow constraint, the safe operation constraint and the like;
the cost function of the time period t formed by the interconnected power distribution network areas on the transaction power is as follows:
Figure BDA0003326333370000071
Figure BDA0003326333370000072
in the formula (f)k，tRepresenting a cost function, pi, of the region k over a period ttElectric energy trading price between regions determined in lower layer end-to-end electric energy trading；
Figure BDA0003326333370000073
The electric energy price for electric energy transaction between each distribution network area and the superior power network;
Figure BDA0003326333370000074
respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;
Figure BDA0003326333370000075
respectively buying and selling active power to the upper-level power grid in a region k in a time period t; f. ofU，k，tK voltage offset cost function for time period t region; Δ t is the transaction period duration;
Figure BDA0003326333370000076
is the load power of node i; omegaUAn out-of-load cost reduction factor for voltage overshoot; vi，tIs the square of the voltage at node i;
Figure BDA0003326333370000077
which is the square of the nominal voltage at node i.
The power flow constraint is as follows:
Figure BDA0003326333370000078
Figure BDA0003326333370000079
Figure BDA00033263333700000710
Figure BDA00033263333700000711
Figure BDA00033263333700000712
Vi，t-Vj，t＝2(RijPij，t+XijQij，t) (8)
in the formula (I), the compound is shown in the specification,
Figure BDA0003326333370000081
branch and node sets of the region k respectively;
Figure BDA0003326333370000082
a node set of an intelligent energy storage soft switch access area k is obtained; pji，t、Qji，tRespectively the active power and the reactive power flowing through the branch ji at the time interval t; pik，t、Qik，tRespectively is the active power and the reactive power flowing through the branch ik at the time interval t; pi，t、Qi，tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;
Figure BDA0003326333370000083
active power output and reactive power output of the distributed power supply are respectively time period t node i;
Figure BDA0003326333370000084
injecting active power into the intelligent energy storage soft switch at an access node;
Figure BDA0003326333370000085
respectively the active load and the reactive load of a node i in a time interval t; rij、XijRespectively the resistance and reactance of branch ij.
The system safe operation constraint is as follows:
Figure BDA0003326333370000086
Figure BDA0003326333370000087
in the formula, omegaTA set of trade periods for a trade day; i isij，tThe current value of the branch ij is squared;
Figure BDA0003326333370000088
the upper limit of the square value of the current of the branch ij;
Figure BDA0003326333370000089
V ithe upper limit and the lower limit of the square value of the voltage of the node i are respectively;
wherein, the active power balance constraint of each region k can be expressed as follows:
Figure BDA00033263333700000810
Figure BDA00033263333700000811
in the end-to-end electric energy trading market, each region only serves as a buyer or a seller to participate in electric energy trading at the same time period, and the corresponding constraint can be expressed as:
Figure BDA00033263333700000812
Figure BDA00033263333700000813
in the formula, betak，tTaking 1 as a binary variable for representing the market identity of the area k in the time period t to represent the area k as a seller; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
According to the obtained cost function of each distribution network region, distributed market clearing calculation based on non-cooperative game among the regions is carried out, and the transaction price pi of end-to-end electric energy transaction is determined on the premise of realizing privacy protectiontAnd the bought power of each region k in the time period t
Figure BDA00033263333700000814
Or selling power
Figure BDA00033263333700000815
The distributed market clearing calculation method based on the non-cooperative game can be described as follows:
a) setting the iteration number h as 1, and setting the electricity selling price of the initial end-to-end electric energy trading market in each area k
Figure BDA00033263333700000816
b) Each area collects the electricity selling price of other areas, and calculates whether the area is a buyer or a seller according to the highest electricity price, and the optimal electricity purchasing power
Figure BDA0003326333370000091
Or selling electric power
Figure BDA0003326333370000092
The calculation method is as follows:
Figure BDA0003326333370000093
Figure BDA0003326333370000094
in the formula (f)s，tAs a cost function of the seller s, fb，tA cost function for buyer b;
Figure BDA0003326333370000095
the seller s and the buyer b sell electricity and purchase electric power respectively.
c) The same auxiliary parameter M is generated and shared among sellers for privacy protectionhGenerating auxiliary variables for each seller s
Figure BDA0003326333370000096
And passed to each buyer. Each buyer b calculates the electric energy demand amount distributed to each seller s according to the following formula:
Figure BDA0003326333370000097
ΩB∪ΩS＝ΩR (18)
in the formula, omegaBSet of buyer regions, ΩSFor set of vendor areas, ΩRIs a collection of areas of a flexible interconnected power distribution network,
Figure BDA0003326333370000098
the resulting demand for electricity by buyer b is distributed to seller s.
d) Each seller calculates and updates electricity selling price according to the following formula:
Figure BDA0003326333370000099
in the formula, σs，tThe factor is adjusted for the seller s's electricity price.
e) Judging whether the electricity price of each seller meets an iteration convergence condition, if so, terminating the iteration, and if not, setting h to h +1 and repeating the steps b) -d), wherein the convergence condition is as follows:
Figure BDA00033263333700000910
in the formula, epsilon is the iterative convergence error of the selling price of the seller.
The intelligent soft switch calculates the actual transmission power of the intelligent soft switch in each distribution network region according to the obtained end-to-end electric energy transaction result and by considering the power loss of the converter;
(1) the method for calculating the actual transmission power of the intelligent soft switch can be expressed as follows:
Figure BDA00033263333700000911
Figure BDA00033263333700000912
in the formula (I), the compound is shown in the specification,
Figure BDA00033263333700000913
setting the actual active power of the intelligent soft switch to be determined in the transaction fine adjustment for the t-period region k;
Figure BDA00033263333700000914
active trading power determined in end-to-end electric energy trading for a t period region k;
Figure BDA00033263333700000915
the loss power of the intelligent soft switch at the port of the converter in the area k in the period t; a. theSOPThe loss coefficient of the intelligent soft switching converter is obtained.
And settling accounts among the regions according to the transaction power and the clearing price, and settling accounts between the regions and the superior power grid according to the actual transmission power and the electric energy price.
In order to verify the feasibility and the effectiveness of the transaction method of the present invention, in this embodiment, the following two scenarios are adopted for verification analysis:
scheme I: and each distribution network area does not participate in electric energy transaction, so that the operation level and the cost of the distribution network in the initial state are obtained.
Scheme II: each distribution network area carries out end-to-end electric energy transaction of a multi-area flexible interconnected distribution network through an intelligent soft switch, and active power transaction fine adjustment based on the intelligent soft switch is carried out after the transaction.
The daily operating costs for each zone in scenario I, II are shown in Table 4. In both schemes, the voltage distribution of each grid area is shown in fig. 5. The cost reduction of each area in the end-to-end electric energy transaction result of the scheme II is shown in fig. 6, and the active power transaction result of each area after fine adjustment in the end-to-end electric energy transaction is shown in fig. 7. In scenario II, the end-to-end electric energy trade power rates are shown in fig. 8.
The computer hardware environment for executing solving calculation is Intel (R) core (TM) i5-5200U CPU, the main frequency is 2.20GHz, and the memory is 4 GB; the software environment is a Windows 10 operating system.
Compared with a scheme I which does not participate in market transaction, the flexible interconnection power distribution network end-to-end electric energy transaction based on the non-cooperative game in the scheme II realizes effective reduction of operation cost of each region, improves voltage distribution of each region, and guarantees cost privacy of market participants.
Compared with the two schemes, the end-to-end electric energy transaction method for the multi-region flexible interconnected power distribution network based on the non-cooperative game can effectively improve the operating economy of the system and improve the voltage distribution of the system.
TABLE 1 arithmetic load access position and power for distribution network in Tianjin North Chen demonstration area
Figure BDA0003326333370000101
Figure BDA0003326333370000111
TABLE 2 calculation circuit parameters of distribution network in Tianjin North Chen demonstration area
Figure BDA0003326333370000112
Figure BDA0003326333370000121
TABLE 3 distributed Power Access location and Capacity
Region(s) Photovoltaic Capacity/MVA Fan Capacity/MVA
Wind 33 1.0 -
Lang 17 1.0 2.0
Wedding 64 - 2.0
Wedding 51 - 2.0
TABLE 4 daily operating costs for each distribution network region
Figure BDA0003326333370000122
A flexible power distribution network end-to-end electric energy transaction device based on a non-cooperative game comprises the following components:
the cost function and power flow constraint and safe operation constraint acquisition module is used for forming a cost function of a time period t about transaction power through power flow analysis by taking the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring active power limit output by an intelligent soft switch port according to the power flow constraint and the safe operation constraint;
the clearing price and transaction active power acquisition module is used for performing distributed market clearing calculation among the interconnected distribution network regions based on a non-cooperative game according to the cost function and the trend constraint and the safe operation constraint of the interconnected distribution network regions, and determining the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for calculating and acquiring the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function of the intelligent energy storage soft switch by considering the power loss of the converter;
and the electric energy settlement module is used for settling among the power distribution network areas according to the transaction power and the clearing price, and settling between each area of the power distribution network and the superior power grid according to the actual transmission power and the electric energy price.
A computing device, comprising:
one or more processing units;
a storage unit for storing one or more programs,
when the one or more programs are executed by the one or more processing units, the one or more processing units execute the non-cooperative game-based flexible power distribution network end-to-end electric energy transaction method; it is noted that the computing device may include, but is not limited to, a processing unit, a storage unit; those skilled in the art will appreciate that the computing device including the processing unit, the memory unit do not constitute a limitation of the computing device, may include more components, or combine certain components, or different components, for example, the computing device may also include input output devices, network access devices, buses, etc.
A computer readable storage medium having non-volatile program code executable by a processor, the computer program when executed by the processor implementing the steps of the above-mentioned non-cooperative game based flexible power distribution network end-to-end electric energy transaction method; it should be noted that the readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof; the program embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. For example, program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the C programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, or entirely on a remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).
Finally, it should be pointed out that: the above examples are only for illustrating the technical solutions of the present invention, and are not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (8)

1. A flexible power distribution network end-to-end electric energy transaction method based on a non-cooperative game is characterized by comprising the following steps:
the method comprises the steps that the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network region in a flexible interconnected power distribution system are taken as targets, a cost function of a time period t about transaction power is formed through power flow analysis, and active power limitation output by an intelligent soft switch port is obtained according to power flow constraint and safe operation constraint;
according to the cost function and the trend constraint and the safe operation constraint of each interconnected distribution network region, distributed market clearing calculation among the interconnected distribution network regions is carried out based on a non-cooperative game, and the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval are determined on the premise of realizing privacy protection;
calculating and obtaining the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function by considering the power loss of the converter;
and settling accounts between the power distribution network areas according to the transaction power and the clearing price, and settling accounts between each area of the power distribution network and the superior power network according to the actual transmission power and the electric energy price.
2. The flexible power distribution network end-to-end electric energy transaction method based on the non-cooperative game as claimed in claim 1, wherein a cost function of a time period t formed by each interconnected power distribution network region with respect to transaction power is as follows:
Figure FDA0003326333360000011
Figure FDA0003326333360000012
in the formula (f)k，tRepresenting a cost function, pi, of the region k over a period ttElectric energy transaction prices among all regions determined in the lower-layer end-to-end electric energy transaction;
Figure FDA0003326333360000013
the electric energy price for electric energy transaction between each distribution network area and the superior power network;
Figure FDA0003326333360000014
respectively buying and selling active power in the end-to-end electric energy transaction in a time period t region k;
Figure FDA0003326333360000015
respectively buying and selling active power to the upper-level power grid in a region k in a time period t; f. ofU，k，tK voltage offset cost function for time period t region; Δ t is the transaction period duration;
Figure FDA0003326333360000016
is the load power of node i; omegaUAn out-of-load cost reduction factor for voltage overshoot; vi，tIs the square of the voltage at node i;
Figure FDA0003326333360000017
which is the square of the nominal voltage at node i.
3. The non-cooperative game-based flexible power distribution network end-to-end electric energy transaction method according to claim 2, wherein the trend constraint is as follows:
Figure FDA0003326333360000018
Figure FDA0003326333360000019
Figure FDA0003326333360000021
Figure FDA0003326333360000022
Figure FDA0003326333360000023
Vi，t-Vj，t＝2(RijPij，t+XijQij，t) (8)
in the formula (I), the compound is shown in the specification,
Figure FDA0003326333360000024
branch and node sets of the region k respectively;
Figure FDA0003326333360000025
a node set of an intelligent energy storage soft switch access area k is obtained; pji，t、Qji，tRespectively the active power and the reactive power flowing through the branch ji at the time interval t; pik，t、Qik，tRespectively is the active power and the reactive power flowing through the branch ik at the time interval t; pi，t、Qi，tRespectively injecting active power and reactive power into the net injection of the node i in the time period t;
Figure FDA0003326333360000026
active power output and reactive power output of the distributed power supply are respectively time period t node i;
Figure FDA0003326333360000027
injecting active power into the intelligent energy storage soft switch at an access node;
Figure FDA0003326333360000028
respectively the active load and the reactive load of a node i in a time interval t; rij、XijRespectively the resistance and reactance of branch ij.
4. The flexible power distribution network end-to-end electric energy transaction method based on the non-cooperative game as claimed in claim 3, wherein the system safety operation constraints are as follows:
Figure FDA0003326333360000029
Figure FDA00033263333600000210
in the formula, omegaTA set of trade periods for a trade day; i isij，tThe current value of the branch ij is squared;
Figure FDA00033263333600000211
the upper limit of the square value of the current of the branch ij;
Figure FDA00033263333600000212
V ithe upper limit and the lower limit of the square value of the voltage of the node i are respectively;
wherein, the active power balance constraint of each region k can be expressed as follows:
Figure FDA00033263333600000213
Figure FDA00033263333600000214
in the end-to-end electric energy trading market, each region only serves as a buyer or a seller to participate in electric energy trading at the same time period, and the corresponding constraint can be expressed as:
Figure FDA00033263333600000215
Figure FDA00033263333600000216
in the formula, betak，tTaking 1 as a binary variable for representing the market identity of the area k in the time period t to represent the area k as a seller; sSOPThe capacity of the converter of the intelligent energy storage soft switch is obtained.
5. The electric energy transaction method for the flexible power distribution network facing the intelligent energy storage soft switch as claimed in claim 1, wherein the distributed market clearing calculation method between the areas of the interconnected power distribution networks based on the non-cooperative game comprises the following steps:
a) setting the iteration number h as 1, and setting the electricity selling price of the initial end-to-end electric energy trading market in each area k
Figure FDA0003326333360000031
b) Each area collects the electricity selling price of other areas, and calculates whether the area is a buyer or a seller according to the highest electricity price, and the optimal electricity purchasing power
Figure FDA0003326333360000032
Or selling electric power
Figure FDA0003326333360000033
The calculation method is as follows:
Figure FDA0003326333360000034
Figure FDA0003326333360000035
in the formula (f)s，tAs a cost function of the seller s, fb，tA cost function for buyer b;
Figure FDA0003326333360000036
selling electricity and purchasing electric power for the seller s and the buyer b respectively;
c) the same auxiliary parameter M is generated and shared among sellers for privacy protectionhGenerating auxiliary variables for each seller s
Figure FDA0003326333360000037
And transmitted to each buyer; each buyer b calculates the electric energy demand amount distributed to each seller s according to the following formula:
Figure FDA0003326333360000038
ΩB∪ΩS＝ΩR (18)
in the formula, omegaBSet of buyer regions, ΩSFor set of vendor areas, ΩRIs a collection of areas of a flexible interconnected power distribution network,
Figure FDA0003326333360000039
distributing the obtained electric energy demand of the buyer b for the seller s;
d) each seller calculates and updates electricity selling price according to the following formula:
Figure FDA00033263333600000310
in the formula, σs，tAdjusting the factor for the seller s's electricity price;
e) judging whether the electricity price of each seller meets an iteration convergence condition, if so, terminating the iteration, if not, setting h to h +1, and repeating the steps b) to d), wherein the convergence condition is as follows:
Figure FDA00033263333600000311
in the formula, epsilon is the iterative convergence error of the selling price of the seller.
6. Flexible distribution network end-to-end electric energy transaction device based on non-cooperative game is characterized by comprising the following components:
the cost function and power flow constraint and safe operation constraint acquisition module is used for forming a cost function of a time period t about transaction power through power flow analysis by taking the lowest electric energy cost and the lowest node voltage deviation of each interconnected power distribution network area in the flexible interconnected power distribution system as targets, and acquiring active power limit output by an intelligent soft switch port according to the power flow constraint and the safe operation constraint;
the clearing price and transaction active power acquisition module is used for performing distributed market clearing calculation among the interconnected distribution network regions based on a non-cooperative game according to the cost function and the trend constraint and the safe operation constraint of the interconnected distribution network regions, and determining the clearing price and the transaction active power of the lower-layer end-to-end electric energy transaction at each time interval on the premise of realizing privacy protection;
the intelligent soft switch actual transmission power acquisition module is used for calculating and acquiring the actual transmission power of the intelligent soft switch in each distribution network area according to the obtained lower-layer end-to-end electric energy transaction result and the cost function of the intelligent energy storage soft switch by considering the power loss of the converter;
and the electric energy settlement module is used for settling among the power distribution network areas according to the transaction power and the clearing price, and settling between each area of the power distribution network and the superior power grid according to the actual transmission power and the electric energy price.
7. A computing device, characterized by: the method comprises the following steps:
one or more processing units;
a storage unit for storing one or more programs,
wherein the one or more programs, when executed by the one or more processing units, cause the one or more processing units to perform the method of any of claims 1-5.
8. A computer-readable storage medium with non-volatile program code executable by a processor, characterized in that the computer program realizes the steps of the method according to any one of claims 1 to 5 when executed by the processor.
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