CN112581309A - Block chain-based distributed energy transaction method and system for power distribution network - Google Patents

Block chain-based distributed energy transaction method and system for power distribution network Download PDF

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CN112581309A
CN112581309A CN202011380456.7A CN202011380456A CN112581309A CN 112581309 A CN112581309 A CN 112581309A CN 202011380456 A CN202011380456 A CN 202011380456A CN 112581309 A CN112581309 A CN 112581309A
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冯迎春
王嘉乐
王蓓蓓
陈浩
高博
蒋宇
丁羽
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Jiangsu Electric Power Trading Center Co ltd
Southeast University
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Abstract

The invention discloses a distributed energy transaction method and system for a power distribution network based on a block chain, wherein the transaction method comprises the following steps: establishing a block chain network, acquiring the quotation report quantity of a power purchasing party and a power selling party, adjusting the quotation of the power purchasing party and the power selling party by considering the network loss and a voltage constraint model, clearing the adjusted declaration result, and uploading the cleared result to a block chain. The transaction system includes: the system comprises a blockchain transaction node, a blockchain network, a distributed processing subsystem, a centralized processing subsystem A and a centralized processing subsystem B. The invention solves the transaction problem of distributed energy under the condition of power grid constraint, and makes the transaction with less influence on the power grid be successful first by adjusting the quotations of both purchasing and selling parties on the premise of reducing the benefit loss of both purchasing and selling parties, thereby ensuring the safe operation of the power grid; the optimal bidding decision is provided with the supply target of the target resource so as to maximize the market benefit of the supply target.

Description

Block chain-based distributed energy transaction method and system for power distribution network
Technical Field
The invention belongs to the technical field of power distribution network power, and particularly relates to a distributed energy trading method and system for a power distribution network based on a block chain.
Background
With the spread of Distributed Renewable Energy (DRE) and Demand Response (DR) technologies, the boundaries between generators and consumers in power distribution networks are becoming increasingly blurred. These power generators are numerous in number, making scheduling even more difficult. The DRE power generation resources have the characteristics of small capacity, large quantity and wide distribution, which means that the centralized scheduling method faces the problems of high operation cost, long time consumption and the like. Therefore, scholars at home and abroad propose a distributed scheduling method with better expandability and reliability, and the method is more suitable for processing the optimal scheduling problem of distributed resources.
In decentralized market trading mode design, the function of realizing market optimization clearing by using an intelligent contract technology through a block chain has been researched. However, the injection of distributed power may result in line overload or voltage violations, and power transactions agreed upon by the market may not be honored due to violations of grid physical constraints, thus requiring processing of transactions that cannot be achieved. In a decentralized trading market based on a block chain, when an agreed trade cannot be redeemed due to blocking, a power grid operator needs to perform security check outside the block chain and give adjustment information of a trading contract.
According to the distributed power trading method, a distribution node electricity price (DLMP) model is introduced into a block chain decentralized market clearing method, and the distributed power trading method considering the line capacity and voltage constraints is established.
Disclosure of Invention
In view of the defects of the prior art, the present invention provides a distributed energy trading method and system for a power distribution network based on a block chain, which provides an optimal quotation decision with a supply object of a target resource, so as to maximize the market profit of the supply object.
The purpose of the invention can be realized by the following technical scheme:
a distributed energy transaction method for a power distribution network based on a block chain comprises the following steps:
s110, establishing a block chain network
S120, obtaining the quotation report quantity of the electricity purchasing party and the electricity selling party
The quotation report amounts submitted by the electricity purchasing party and the electricity selling party are respectively collected through a reporting module and uploaded to the block chain transaction nodes corresponding to the electricity purchasing and selling nodes, and the data are uploaded to the block chain platform through the corresponding block chain transaction nodes;
s130, adjusting the quotation of the electricity buying and selling parties through a model considering network loss and voltage constraint
Aiming at user requirements, a linear OPF method is applied to solve the economic dispatching problem, a DLMP formula similar to LMP is provided, and the DLMP comprises three parts: ECC, LCC and VCC, wherein two components of LCC and VCC reflect the influence of each transaction on the system network loss and voltage offset;
under network constraints, the economic scheduling expression aiming at minimizing the system operation cost is as follows:
Figure BDA0002808325470000021
the above model needs to satisfy active and reactive power balance, output and voltage constraints:
Figure BDA0002808325470000022
Figure BDA0002808325470000023
Pi_Gmin≤Pi_G≤Pi_Gmax i＝1,2,...,NG
Qi_Gmin≤Qi_G≤Qi_Gmax i＝1,2,...,NG
Vmin≤Vi(Sx)≤Vmax i＝1,2,...,NB
constructing a Lagrange function on the basis of the model, and performing derivation on physical node data corresponding to the electricity purchasing i to obtain the following formula:
Figure BDA0002808325470000031
the network loss cost component LCC calculation model of the electricity purchasing node i is expressed as follows:
Figure BDA0002808325470000032
wherein,
Figure BDA0002808325470000033
the voltage offset cost component VCC calculation model for the power purchase node i is represented as:
Figure BDA0002808325470000034
wherein,
Figure BDA0002808325470000035
when no P2P transaction is carried out, the method for calculating the power flow distribution of the power distribution network, namely determining the operation point of the cost component LCC calculation model and the voltage offset cost component VCC comprises the following steps:
when the computing distribution network has no P2P transaction, the output P of each conventional machine set in the distribution network nodei_GAnd the power flow distribution under the state, including the power flow of each line
Figure BDA0002808325470000036
Power injection P at each nodeiVoltage value ViLoss of star and grid PlossAnd an LCC component value and a VCC component value in each node DLMP value;
constructing a network loss sensitivity matrix by using LCC component values and VCC component values in each node DLMP value:
Figure BDA0002808325470000037
and a voltage offset sensitivity matrix:
Figure BDA0002808325470000038
s140, clearing the adjusted declaration result
Sorting the transaction nodes after adjusting quotation through a clearing module, pairing according to the high and low orders, and finishing market clearing according to the matching result of the transaction nodes and the original declaration price of the transaction nodes;
s150, uploading the clear result to a block chain
And uploading the transaction result to the block chain through the clearing module.
Further, the block chain-based power distribution network distributed energy trading system proposed in S110 includes: the system comprises a blockchain transaction node, a blockchain network, a distributed processing subsystem, a centralized processing subsystem A and a centralized processing subsystem B.
Further, the formula in S130
Figure BDA0002808325470000041
The parameters are expressed as: c. Ci_GActive switching for DGs located at node iPrice, di_GReactive bid price, P, for DGs located at node ii_GActive output, Q, for electricity selling nodei_GReactive output, P, for electricity selling nodesPSPAmount of work, Q, purchased to a transmission grid for nodes connected to the gridPSPAmount of reactive power purchased to the grid for nodes connected to the grid, c0Is the corresponding active price, d0Is the reactive price corresponding to the price.
Further, the formula in S130
Figure BDA0002808325470000042
Figure BDA0002808325470000043
Pi_Gmin≤Pi_G≤Pi_Gmax i＝1,2,...,NG
Qi_Gmin≤Qi_G≤Qi_Gmax i＝1,2,...,NG
Vmin≤Vi(Sx)≤Vmax i＝1,2,...,NB
The parameters are expressed as: NG is the number of DGs; NB is the number of system nodes; sxFor controlling variables, including PPSP,QPSP,Pi_G,Qi_G；Pi_DFor the active demand of node i, Qi_DIs the reactive demand of node i.
Further, the formula in S130
Figure BDA0002808325470000044
The parameters are expressed as: lambda [ alpha ]pIn order to be able to do so for the energy price,
Figure BDA0002808325470000045
represents the partial derivative of the active network loss to the i-load of the power purchase node,
Figure BDA0002808325470000051
represents the partial derivative of reactive network loss to the i load of the power purchase node, NB represents the number of branches, muupper_ViAnd mulower_ViA penalty factor representing the node crossing the upper and lower limits, BNA matrix resulting from the branch impedance operation is represented.
Further, B isNSpecifically, the following are shown:
Figure BDA0002808325470000052
B1and B2Expressed as:
Figure BDA0002808325470000053
Figure BDA0002808325470000054
a control device of a distributed energy transaction method of a power distribution network based on a block chain comprises a device main body, wherein a processing unit, a system memory, a bus, an I/O interface and a network adapter are arranged in the device main body, and the system memory comprises an access memory, a cache memory, a storage system, a program module and a program utility tool.
The I/O interface is connected with the display, the external equipment and the processing unit, the processing unit is connected with the access memory, the cache memory and the storage system, and the whole connection mode is electrically connected through a bus;
the device body is in the form of a general purpose computing device, the components of which include, but are not limited to: one or more processors or processing units, a system memory, and a bus connecting various system components including the system memory and the processing units.
The invention has the beneficial effects that:
1. the distributed energy trading method and system for the power distribution network based on the block chain, provided by the invention, solve the trading problem of distributed energy under the condition of power grid constraint, and ensure the safe operation of the power grid by adjusting the quotation of both purchasing and selling parties and making the trade with less influence on the power grid in advance on the premise of reducing the benefit loss of both purchasing and selling parties;
2. the distributed energy trading method and system for the power distribution network based on the block chain, provided by the invention, provide the optimal quotation decision by the supply object of the target resource so as to maximize the market income of the supply object.
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In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of an overall transaction method of an embodiment of the present invention;
FIG. 2 is a block diagram of an overall transaction system of an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a control device according to an embodiment of the present invention;
fig. 4 is a topology diagram of a power distribution network according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Example 1
As shown in fig. 1, a distributed energy trading method for a power distribution network based on a block chain includes the following steps:
s110, establishing a block chain network
As shown in fig. 2, a block chain-based distributed energy transaction system for a power distribution network includes: the system comprises a blockchain transaction node, a blockchain network, a distributed processing subsystem, a centralized processing subsystem A and a centralized processing subsystem B. The block chain transaction node mainly comprises an electricity purchasing side node and an electricity selling side node; the block chain network mainly plays a role of an accounting platform; the distributed processing subsystem forms a declaration module of each transaction node; the centralized processing subsystem A is a verification module of the whole system; the centralized processing subsystem B is a clearing module of the whole system.
The whole system is distributed, a plurality of transaction nodes are connected into a block chain network, and a user under each transaction node can be an electricity purchasing party or an electricity selling party. The system comprises a declaration module, a clearing module and a checking module. The electricity purchasing side and the electricity selling side declare the electric quantity and the electricity price through the declaration module, the clearing module determines the transaction electricity price and the electric quantity, and the verification module verifies each transaction so as to ensure the operation safety of the power grid.
S120, obtaining the quotation report quantity of the electricity purchasing party and the electricity selling party
The reporting module is used for respectively acquiring quoted price reporting amounts submitted by the electricity purchasing party and the electricity selling party, uploading the quoted price reporting amounts to the block chain transaction nodes corresponding to the electricity purchasing and selling nodes, uploading data to the block chain platform through the corresponding block chain transaction nodes, wherein the topology of a power distribution system is shown in figure 4, and the data of both the electricity purchasing party and the electricity selling party is shown in table 1.
Node point Buy/sell Electric quantity Price quote
1 -1 0.01 300
2 1 0.022 295
3 1 0.03 310
4 1 0.023 305
5 -1 0.021 290
6 1 0.031 320
7 -1 0.032 280
8 1 0.028 301
9 -1 0.03 311
10 -1 0.02 307
TABLE 1
S130, adjusting the quotation of the electricity buying and selling parties through a model considering network loss and voltage constraint
Considering that certain network loss and voltage offset are brought when transaction is physically executed, aiming at user requirements, a linear optimal power flow calculation (OPF) method is applied to solve an economic dispatching problem, and a power distribution node price (DLMP) formula similar to a power transmission node price (LMP) is provided. DLMP consists of three parts: an Energy Cost Component (ECC), a Loss Cost Component (LCC), and a voltage component (VCC), where both components reflect the effect of each transaction on system net loss and voltage offset.
Under network constraints, the economic scheduling expression aiming at minimizing the system operation cost is as follows:
Figure BDA0002808325470000081
in the above formula: c. Ci_GActive bid price, d, for DGs located at node ii_GReactive bid price, P, for DGs located at node ii_GTo sellActive output, Q, of an electrical nodei_GReactive output, P, for electricity selling nodesPSPAmount of work, Q, purchased to a transmission grid for nodes connected to the gridPSPAmount of reactive power purchased to the grid for nodes connected to the grid, c0Is the corresponding active price, d0Is the reactive price corresponding to the price.
The above model needs to satisfy active and reactive power balance, output and voltage constraints:
Figure BDA0002808325470000082
Figure BDA0002808325470000083
Pi_Gmin≤Pi_G≤Pi_Gmax i＝1,2,...,NG
Qi_Gmin≤Qi_G≤Qi_Gmax i＝1,2,...,NG
Vmin≤Vi(Sx)≤Vmax i＝1,2,...,NB
in the above formula: NG is the number of DGs; NB is the number of system nodes; sxFor controlling variables, including PPSP,QPSP,Pi_G,Qi_G；Pi_DFor the active demand of node i, Qi_DIs the reactive demand of node i.
Constructing a Lagrange function on the basis of the model, and performing derivation on physical node data corresponding to the electricity purchasing i to obtain the following formula:
Figure BDA0002808325470000091
in the above formula, λpIn order to be able to do so for the energy price,
Figure BDA0002808325470000092
representing active network loss versus power purchaseThe partial derivative of the load at node i,
Figure BDA0002808325470000093
represents the partial derivative of reactive network loss to the i load of the power purchase node, NB represents the number of branches, muupper_ViAnd mulower_ViA penalty factor representing the node crossing the upper and lower limits, BNThe matrix obtained by the branch impedance operation is shown as follows:
Figure BDA0002808325470000094
in the above formula, B1And B2Expressed as:
Figure BDA0002808325470000095
Figure BDA0002808325470000096
the network loss cost component LCC calculation model of the electricity purchasing node i is expressed as follows:
Figure BDA0002808325470000097
wherein,
Figure BDA0002808325470000098
the voltage offset cost component VCC calculation model for the power purchase node i is represented as:
Figure BDA0002808325470000099
wherein,
Figure BDA00028083254700000910
when no P2P transaction is carried out, the method for calculating the power flow distribution of the power distribution network, namely determining the operation point of the cost component LCC calculation model and the voltage offset cost component VCC comprises the following steps:
when the computing distribution network has no P2P transaction, the output P of each conventional machine set in the distribution network nodei_GAnd the power flow distribution under the state, including the power flow of each line
Figure BDA0002808325470000101
Power injection P at each nodeiVoltage value ViLoss of star and grid Ploss, and the LCC component value and VCC component value in each node DLMP value.
Constructing a network loss sensitivity matrix by using LCC component values and VCC component values in each node DLMP value:
Figure BDA0002808325470000102
and a voltage offset sensitivity matrix:
Figure BDA0002808325470000103
the method comprises the following steps: trading node m intention trades electricity sales P through P2PmQuoted price is lambdam_PTrading node n is willing to trade purchase quantity of electricity D through P2PnQuoted price is lambdan_D。
At the moment, the change of the node i relative to the net injected power under the optimal power flow state is delta Pi(-PmOr Dn) The induced network loss variation is:
Figure BDA0002808325470000104
then the total network loss brought by the node i is:
P′loss,i＝ΔPloss,i+Ploss*
introducing a network loss sensitivity factor lambdaloss,iThe ratio of the grid loss to its injected power, which describes the DG contribution:
Figure BDA0002808325470000105
in the above formula: piFor node i power injection value, Pi＝Pi*+ΔPi。
At the moment, the change of the node i relative to the net injected power under the optimal power flow state is delta Pi(-PmOr Dn) The resulting voltage at node j changes as:
Figure BDA0002808325470000106
due to the change of the injection power of the node i, the voltage of each node is changed as follows:
V′j＝Vj+ΔVj
if V'kThe excess voltage upper limit or lower limit is dV'kIntroduction of a voltage sensitivity factor lambdaV,iDescribing the ratio of the total voltage out-of-limit caused by the change of the injection power of the node i to the injection power thereof:
Figure BDA0002808325470000111
and (3) carrying out standardization processing on data:
Figure BDA0002808325470000112
wherein,
Figure BDA0002808325470000113
Figure BDA0002808325470000114
wherein,
Figure BDA0002808325470000115
each user's updated quote is λ'n_D＝λn_D-α*λ′loss,n-β*λ′V,nλ 'is quote for each DG updated'm_P＝λm_P+α*λ′loss,m+β*λ′V,m. Wherein α is an influence coefficient of the network loss sensitivity factor on the price quotation, β is an influence coefficient of the voltage sensitivity factor on the price quotation, the initial values are respectively set to 20, and finally, the updating results of the price quotation of both the electricity purchasing and selling parties are shown in tables 2 and 3.
Node point Buy Electric quantity Price quote
3 1 0.03 337.3125
4 1 0.023 332.1959
6 1 0.031 331.7643
8 1 0.028 295.8634
2 1 0.022 265.3721
TABLE 2
Node point Selling machine Electric quantity Price quote
1 -1 0.01 266.4424
7 -1 0.032 272.6673
5 -1 0.021 277.8578
9 -1 0.03 341.696
10 -1 0.02 360.8447
TABLE 3
S140, clearing the adjusted declaration result
The transaction nodes after adjusting the quotation are sequenced through the clearing module, the pairing is carried out according to the high and low orders, the market clearing is finished according to the matching result of the transaction nodes and the original declaration price of the transaction nodes, and the result is shown in the table 4.
Node point Buy/sell Electric quantity Price quote Node point Buy/sell Electric quantity Price quote
3 1 0.03 337.3125 1 -1 0.01 266.4424
4 1 0.023 332.1959 7 -1 0.032 272.6673
6 1 0.01 331.7643 5 -1 0.021 277.8578
TABLE 4
S150, uploading the clear result to a block chain
And uploading the transaction result to the block chain through the clearing module.
Example 2
As shown in fig. 3, a structure diagram of a control device consistent with the present application is provided, and this embodiment provides services for implementing the distributed energy trading method of the power distribution network according to the above embodiment.
It should be noted that fig. 3 illustrates a block diagram of an exemplary device suitable for use in implementing embodiments of the present invention. The device illustrated in fig. 3 is only an example and should not bring any limitations to the function and scope of use of the embodiments of the present invention.
The control device conforming to the distributed energy transaction method of the power distribution network comprises a device main body 12, wherein a processing unit 16, a system memory (internal memory) 28, a bus 18, an I/O interface 22 and a network adapter 20 are arranged in the device main body 12. The system memory 28 includes access memory (RAM)30, cache memory 32, storage system 34, program modules 42, and program utility 40. The program utility 40 is comprised of program modules 42, it being understood that each program module 42 constitutes a program utility 40.
The I/O interface 22 is coupled to the display 24, the external device 14, and the processing unit 16 is coupled to the access memory 30, the cache memory 32, and the storage system 34. The overall connection is electrically connected by a bus 18.
The device body 12 is in the form of a general purpose computing device. The components of the device body 12 include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
The device body 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by the device body 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 includes computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and cache memory 32. The device body 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, and commonly referred to as a "hard drive"). Not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
Program utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The device body 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with the device body 12, and/or with any devices (e.g., network card, modem, etc.) that enable the device body 12 to communicate with one or more other computing devices. Such communication may be through the I/O interface 22. Also, the device body 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) through the network adapter 20. As shown in fig. 3, the network adapter 20 communicates with the other modules of the device body 12 via the bus 18. It should be understood that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with device body 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, to implement the distributed energy trading method for the power distribution network provided by the embodiment of the present invention.
Through the equipment, the transaction problem of distributed energy under the condition of power grid constraint is solved, and by adjusting the quotations of the electricity purchasing and selling parties, the transaction with less influence on the power grid can be committed first on the premise of reducing the benefit loss of the electricity purchasing and selling parties, so that the safe operation of the power grid is ensured.
Example 3
The present embodiments provide a storage medium containing computer executable instructions which, when executed by a computer processor, perform a method of power distribution grid distributed energy trading, the method comprising: the block chain network consisting of the electricity purchasing side nodes and the electricity selling side nodes is established, the electricity purchasing side and the electricity selling side respectively submit quotation report amounts in the declaration module, the corresponding nodes collect quotation report amount data and upload the quotation report amount data to the block chain, the check module adjusts the quotation of the electricity purchasing and selling side through a transaction model considering network loss and voltage constraint, and the clearing module is responsible for clearing to obtain a transaction result and uploading the transaction result to the block chain.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer 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.
Computer program code for carrying out operations for aspects 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, Smalltalk, C + + or the like and conventional procedural programming languages, such as the C language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.

Claims (8)

1. A distributed energy transaction method for a power distribution network based on a block chain is characterized by comprising the following steps:
s110, establishing a block chain network
S120, obtaining the quotation report quantity of the electricity purchasing party and the electricity selling party
The quotation report amounts submitted by the electricity purchasing party and the electricity selling party are respectively collected through a reporting module and uploaded to the block chain transaction nodes corresponding to the electricity purchasing and selling nodes, and the data are uploaded to the block chain platform through the corresponding block chain transaction nodes;
s130, adjusting the quotation of the electricity buying and selling parties through a model considering network loss and voltage constraint
Aiming at user requirements, a linear OPF method is applied to solve the economic dispatching problem, a DLMP formula similar to LMP is provided, and the DLMP comprises three parts: ECC, LCC and VCC, wherein two components of LCC and VCC reflect the influence of each transaction on the system network loss and voltage offset;
under network constraints, the economic scheduling expression aiming at minimizing the system operation cost is as follows:
Figure FDA0002808325460000011
the above model needs to satisfy active and reactive power balance, output and voltage constraints:
Figure FDA0002808325460000012
Figure FDA0002808325460000013
Pi_Gmin≤Pi_G≤Pi_Gmax i＝1,2,...,NG
Qi_Gmin≤Qi_G≤Qi_Gmax i＝1,2,...,NG
Vmin≤Vi(Sx)≤Vmax i＝1,2,...,NB
constructing a Lagrange function on the basis of the model, and performing derivation on physical node data corresponding to the electricity purchasing i to obtain the following formula:
Figure FDA0002808325460000021
the network loss cost component LCC calculation model of the electricity purchasing node i is expressed as follows:
Figure FDA0002808325460000022
wherein,
Figure FDA0002808325460000023
the voltage offset cost component VCC calculation model for the power purchase node i is represented as:
Figure FDA0002808325460000024
wherein,
Figure FDA0002808325460000025
when no P2P transaction is carried out, the method for calculating the power flow distribution of the power distribution network, namely determining the operation point of the cost component LCC calculation model and the voltage offset cost component VCC comprises the following steps:
when the computing distribution network has no P2P transaction, the output P of each conventional machine set in the distribution network nodei_GAnd the power flow distribution under the state, including the power flow of each line
Figure FDA0002808325460000026
Power injection P at each nodeiVoltage value ViLoss of star and grid PlossAnd an LCC component value and a VCC component value in each node DLMP value;
constructing a network loss sensitivity matrix by using LCC component values and VCC component values in each node DLMP value:
Figure FDA0002808325460000027
and a voltage offset sensitivity matrix:
Figure FDA0002808325460000028
s140, clearing the adjusted declaration result
Sorting the transaction nodes after adjusting quotation through a clearing module, pairing according to the high and low orders, and finishing market clearing according to the matching result of the transaction nodes and the original declaration price of the transaction nodes;
s150, uploading the clear result to a block chain
And uploading the transaction result to the block chain through the clearing module.
2. The block chain based power distribution network distributed energy trading method according to claim 1, wherein the block chain based power distribution network distributed energy trading system proposed in S110 comprises: the system comprises a blockchain transaction node, a blockchain network, a distributed processing subsystem, a centralized processing subsystem A and a centralized processing subsystem B.
3. The block chain-based distributed energy trading method for power distribution network according to claim 1, wherein the formula in S130 is
Figure FDA0002808325460000031
The parameters are expressed as: c. Ci_GActive bid price, d, for DGs located at node ii_GReactive bid price, P, for DGs located at node ii_GActive output, Q, for electricity selling nodei_GReactive output, P, for electricity selling nodesPSPAmount of work, Q, purchased to a transmission grid for nodes connected to the gridPSPAmount of reactive power purchased to the grid for nodes connected to the grid, c0Is the corresponding active price, d0Is the reactive price corresponding to the price.
4. The block chain-based distributed energy trading method for power distribution network according to claim 1, wherein the formula in S130 is
Figure FDA0002808325460000032
Figure FDA0002808325460000033
Pi_Gmin≤Pi_G≤Pi_Gmax i＝1,2,...,NG
Qi_Gmin≤Qi_G≤Qi_Gmax i＝1,2,...,NG
Vmin≤Vi(Sx)≤Vmax i＝1,2,...,NB
The parameters are expressed as: NG is the number of DGs; NB is the number of system nodes; sxFor controlling variables, including PPSP,QPSP,Pi_G,Qi_G；Pi_DFor the active demand of node i, Qi_DIs the reactive demand of node i.
5. The block chain-based distributed energy trading method for power distribution network according to claim 1, wherein the formula in S130 is
Figure FDA0002808325460000041
The parameters are expressed as: lambda [ alpha ]pIn order to be able to do so for the energy price,
Figure FDA0002808325460000042
represents the partial derivative of the active network loss to the i-load of the power purchase node,
Figure FDA0002808325460000043
represents the partial derivative of reactive network loss to the i load of the power purchase node, NB represents the number of branches, muupper_ViAnd mulower_ViA penalty factor representing the node crossing the upper and lower limits, BNA matrix resulting from the branch impedance operation is represented.
6. The distributed energy trading method for the power distribution network based on the block chain as claimed in claim 5, wherein B isNSpecifically, the following are shown:
Figure FDA0002808325460000044
B1and B2Expressed as:
Figure FDA0002808325460000045
Figure FDA0002808325460000046
7. the control device for the block chain based distributed energy trading method of the power distribution network according to any one of claims 1 to 6, comprising a device main body (12), wherein a processing unit (16), a system memory (28), a bus (18), an I/O interface (22) and a network adapter (20) are arranged in the device main body (12), and the system memory (28) comprises an access memory (30), a cache memory (32), a storage system (34), a program module (42) and a program utility (40).
8. The control device of the distributed energy transaction method for the power distribution network based on the blockchain according to claim 7, wherein the I/O interface (22) is connected with the display (24), the external device (14) and the processing unit (16), the processing unit (16) is connected with the access memory (30), the cache memory (32) and the storage system (34), and the whole connection mode is electrically connected through the bus (18);
the device body (12) is in the form of a general purpose computing device, the components of the device body (12) including but not limited to: one or more processors or processing units (16), a system memory (28), and a bus (18) that couples various system components including the system memory (28) and the processing unit (16).
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