CN116071159A

CN116071159A - System and method for service green power transaction

Info

Publication number: CN116071159A
Application number: CN202211543438.5A
Authority: CN
Inventors: 时智勇; 董晓亮; 张显; 李琼慧; 王彩霞; 乔宁; 张超; 田宏杰; 陈宁; 叶小宁; 吴思; 刘勇; 谭雯娟; 蒋磊
Original assignee: State Grid Energy Research Institute Co Ltd; State Grid Hunan Electric Power Co Ltd; State Grid Ningxia Electric Power Co Ltd
Current assignee: State Grid Energy Research Institute Co Ltd; State Grid Hunan Electric Power Co Ltd; State Grid Ningxia Electric Power Co Ltd
Priority date: 2022-12-02
Filing date: 2022-12-02
Publication date: 2023-05-05

Abstract

The embodiment of the specification provides a system and a method for servicing green power transactions, wherein the system comprises: the electric power transaction platform is used for providing an optimal power supply line after the electricity utilization side purchases electricity according to the selected transaction strategy; the block chain subsystem is used for completing block chain consensus after data uplink; storing privacy data and basic data generated by electric power transaction, and carrying out fine granularity protection on transaction data on a chain by adopting a hierarchical encryption technology; the user transaction subsystem generates transaction according to the provided optimal power supply line, performs blocking judgment on the optimal power supply line, performs examination and consensus, and then uploads transaction data to a database in the electric power transaction platform; the CA certificate subsystem is used for issuing a digital certificate for the user; and the wind-electricity photovoltaic prediction subsystem is used for searching the optimal model parameters through an LSTM method improved by a hybrid algorithm and generating an optimal transaction strategy. To solve the centralization problem of the electric power market.

Description

System and method for service green power transaction

Technical Field

The present document relates to the field of power transaction technologies, and in particular, to a system and a method for servicing green power transactions.

Background

The power energy transformation requires that the power system can consume green energy more timely, the power market is more open, and green power energy transaction should be developed towards the direction of center removal and intellectualization.

The existing green electric power trading center can solve the problem of direct purchase of large electric quantity in a cross region, but the application range is smaller, the effect is not ideal, and the following three problems exist according to the specific gravity between the market trading electric quantity and the whole social electric quantity and the problems found in the actual market trading operation process. Firstly, the green electric power trading center is controlled by a power supply enterprise, cannot independently and independently operate well, and the market regulation function of the electric power trading center is not fully exerted yet. And secondly, the green power transaction is mainly medium-and-long-term transaction, but the transaction electric quantity, time and price of the medium-and-long-term transaction are in a relatively long period in the future, have certain hysteresis, cannot follow the change of the future power energy market, and have unsatisfactory effect of responding to the latest demand of the market and poor market competitiveness. Thirdly, the problem that the two parties of the electric power energy transaction are behind the negotiation mechanism is solved. Market exchange of buyers and sellers led by the green electric power exchange center is mainly carried out in a field bilateral negotiation mode, because of limited participants, the number of alternative electric power energy producers is small, and in addition, the information is asymmetric and a pricing mechanism is opaque, so that the negotiation process time is long and inflexible, and the achieved transaction result does not necessarily meet the safe scheduling condition of system operation. Under the decentralized regional power energy transaction scene, the security risks of information leakage and external attack exist, and the privacy protection and transaction mutual trust of users are also problems to be solved.

The blockchain technology can get rid of the control of a centralization mechanism on big data information to a certain extent, and ensures the transmission of personal privacy data through an encryption means, but at present, many exchanges and wallets are still centralized operation modes, the personal data of users can be inevitably stored, once the users are attacked, a hacker can possibly acquire a large amount of user data, sell the data through a hidden network and the like, and obtain violence. In addition, the privacy information of the user can be easily obtained from the public transparent record through the existing big data analysis and cluster analysis and a certain network attack means. The electric power energy is different from other commodities, is a necessity for modern people, and can have serious consequences if the transaction is not properly operated, so that people are required to monitor the electric power market transaction, the line capacity and the line loss are considered, and the electric power network company is required to adjust, so that the system cannot be completely decentralised.

Disclosure of Invention

The invention provides a system and a method for servicing green power transaction, which adopt a blockchain technology to respectively put users and supervision departments on a blockchain side chain and a main chain, thereby improving the throughput of the transaction; recording transaction data of the electric power transaction system by adopting a blockchain technology, wherein a plurality of nodes in the system can be synchronized in real time, so that the inquiry and traceability of the transaction data of the electric power transaction system are realized; hierarchical encryption is adopted to carry out hierarchical encryption on the public information and the non-public information, so that on one hand, the data disclosure is ensured, and more users are attracted to join the system; on the other hand, the personal privacy data transmission can be prevented, and once the personal privacy data transmission is attacked, a hacker can acquire a large amount of user data and sell the data in a manner of a darknet and the like to obtain violence.

The invention provides a system for servicing green power transactions, comprising: the system comprises an electric power transaction platform, a block chain subsystem, a user transaction subsystem, a CA certificate subsystem and a wind power photovoltaic prediction subsystem;

the power transaction platform is in interactive connection with the block chain subsystem, the user transaction subsystem, the CA certificate subsystem and the wind power photovoltaic prediction subsystem and is used for providing a registration and login platform for users of green power transaction, and the users comprise power generators and power utilization sides; issuing electricity selling information for the electricity generator; the optimal transaction strategy provided by the wind power photovoltaic prediction subsystem is received for the electricity utilization side, and an optimal power supply line is provided for the electricity utilization side after purchasing electricity according to the selected transaction strategy according to the optimal transaction strategy; generating an order according to the power supply line selected by the power utilization side for storing transaction data in a database;

the system comprises a blockchain subsystem, wherein the blockchain subsystem is designed in a blockchain form and comprises a main chain and side chains, wherein members of the side chains comprise a generator and a power utilization side, the members of the main chain comprise a power trading center and a trading supervision department, and the blockchain subsystem is used for completing power and electricity price conversion of the power trading center; the block chain consensus is used for completing the data uplink; the system is used for storing privacy data and basic data generated by electric power transaction, carrying out information interaction between a main chain and a side chain through the side chain, carrying out safe sharing on data of each transaction party, and carrying out fine granularity protection on the transaction data on the chain by adopting a hierarchical encryption technology; the transaction data is used for applying for accessing transaction data stored in the electric power transaction platform;

The user transaction subsystem is used for generating transaction according to the provided optimal power supply line, performing blocking judgment on the optimal power supply line, performing examination and consensus, and uploading transaction data to the database in the power transaction platform;

the CA certificate subsystem is used for issuing a digital certificate after node verification and network access verification are carried out on a user through an intelligent contract;

and the wind-electricity photovoltaic prediction subsystem is used for searching the optimal model parameters through an LSTM method improved by a hybrid algorithm and generating an optimal transaction strategy.

The invention provides a method for servicing green power transactions, comprising the following steps:

s1, a user registers on an electric power transaction platform, an intelligent contract examines, the user can log in after the examination passes, an electricity producer can upload electricity selling information on the electric power transaction platform, and an electricity using side can select according to the electricity selling information uploaded by the electricity producer;

s2, purchasing electricity according to the electricity utilization side, initiating an order after successful payment, judging whether the balance of the electricity utilization side meets the order requirement, and generating the order if the balance of the electricity utilization side meets the order requirement;

s3, the generated order passes through the blocking management module and judges whether the safety condition is met or not, and intelligent contract examination is carried out after the safety condition is met;

S4, after the intelligent contract examination is completed, block chain consensus is conducted, and transaction data are uploaded to a database.

According to the invention, transaction data of the electric power transaction system is recorded through a blockchain technology, and a plurality of nodes in the system can be synchronized in real time, so that the inquiry and traceability of the transaction data of the electric power transaction system are realized; hierarchical encryption is adopted to carry out hierarchical encryption on the public information and the non-public information, so that on one hand, the data disclosure is ensured, and more users are attracted to join the system; on the other hand, the personal privacy data transmission can be prevented, and once the personal privacy data transmission is attacked, a hacker can acquire a large amount of user data and sell the data in a manner of a darknet and the like to obtain violence.

Drawings

For a clearer description of one or more embodiments of the present description or of the solutions of the prior art, the drawings that are necessary for the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description that follow are only some of the embodiments described in the description, from which, for a person skilled in the art, other drawings can be obtained without inventive faculty.

FIG. 1 is a block diagram of a system for servicing green power transactions according to an embodiment of the present invention;

FIG. 2 is a flow chart of a method of servicing a green power transaction according to an embodiment of the present invention;

FIG. 3 is a system frame diagram of a blockchain subsystem in accordance with an embodiment of the present invention;

FIG. 4 is a schematic diagram of a double-stranded structure according to an embodiment of the present invention;

fig. 5 is a hierarchical encryption flow chart of an embodiment of the present invention.

Detailed Description

In order to enable a person skilled in the art to better understand the technical solutions in one or more embodiments of the present specification, the technical solutions in one or more embodiments of the present specification will be clearly and completely described below with reference to the drawings in one or more embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one or more embodiments of the present disclosure without inventive faculty, are intended to be within the scope of the present disclosure.

System embodiment

An embodiment of the present invention provides a system for servicing a green power transaction, and fig. 1 is a schematic diagram of a system for servicing a green power transaction according to an embodiment of the present invention, where, according to the system for servicing a green power transaction shown in fig. 1, the system for servicing a green power transaction according to an embodiment of the present invention includes: the system comprises an electric power transaction platform, a block chain subsystem, a user transaction subsystem, a CA certificate subsystem and a wind power photovoltaic prediction subsystem;

The power transaction platform is in interactive connection with the block chain subsystem, the user transaction subsystem, the CA certificate subsystem and the wind power photovoltaic prediction subsystem and is used for providing a registration and login platform for users of green power transaction, and the users comprise power generators and power utilization sides; issuing electricity selling information for the electricity generator; the optimal transaction strategy provided by the wind power photovoltaic prediction subsystem is received for the electricity utilization side, and an optimal power supply line is provided after electricity purchase is performed for the electricity utilization side according to the selected transaction strategy according to the optimal transaction strategy; the system comprises a power supply line generation module, a transaction data storage module and a data storage module, wherein the power supply line generation module is used for generating orders according to power supply lines selected by a power utilization side and storing transaction data into a database;

the blockchain subsystem is designed in a blockchain form and comprises a main chain and a side chain, and fig. 3 is a system frame diagram of the blockchain subsystem in an embodiment of the invention, wherein members of the side chain comprise a generator and a power utilization side, members of the main chain comprise a power transaction center and a transaction supervision department, and the blockchain subsystem is used for completing power and electricity price conversion of the power transaction center; completing block chain consensus after data uplink; storing privacy data and basic data generated by electric power transaction, carrying out information interaction between the main chain and the side chain through the side chain, carrying out safe sharing on data of each transaction party, and carrying out fine granularity protection on the transaction data on the chain by adopting a hierarchical encryption technology; applying for accessing transaction data stored in the power transaction platform; the blockchain system specifically includes: the electricity price conversion module is used for sending the current market clearing boundary conditions, the current market clearing boundary conditions and the current market pricing to the electric power transaction center, and the electric power transaction center is used for publishing the electricity selling information of the highest electricity price and the lowest electricity price which meet the current time period electricity price specification and are sent by each electricity generator; the consensus module is used for completing consensus of the alliance chain by adopting a dBFT mechanism; the hierarchical encryption and decryption module specifically comprises: and carrying out hierarchical encryption on the private data stored in the main chain and the basic data stored in the side chain by adopting a hierarchical encryption technology.

The user transaction subsystem is used for generating transaction according to the provided optimal power supply line, performing blocking judgment on the optimal power supply line, performing examination and consensus, and uploading transaction data to a database in the electric power transaction platform; the user transaction subsystem specifically comprises: the transaction module is used for generating transaction data according to the order submitted by the user; the blocking management module is used for judging whether to perform blocking management according to the line constraint condition and regenerating a transaction strategy for the line needing blocking management; the security checking module is used for carrying out security checking and checking consensus on the transaction and is used for acquiring transaction data which is subjected to intelligent contract checking through the CA certificate subsystem and is consensus through the blockchain subsystem; and the data uploading module is used for uploading the transaction data in the censoring consensus module to the database.

and the wind-electricity photovoltaic prediction subsystem is used for searching the optimal model parameters through an LSTM method improved by a hybrid algorithm and generating an optimal transaction strategy. Wherein the stroke photovoltaic prediction subsystem comprises: the system comprises M groups of wind power generating units, photovoltaic generating units, thermal power generating units, N edge computing servers, cloud computing servers, wind power data collectors and load data collectors; the wind power data collector is used for collecting capacity information of the generated output electric quantity of the wind generating set; the collected capacity information is sent to an edge computing server; each edge server obtains the energy production information of a plurality of wind generating sets from the wind power data collector, obtains the power consumption of user power consumption equipment from the load data collector, calculates the power and the load power of the wind generating sets at the next moment, and sends the power and the load power to the cloud computing server, and the cloud computing server regulates the wind generating sets through the energy storage battery pack and the thermal power generating set; and the cloud computing server receives the change rate of the electric quantity required by the user terminal at the next moment predicted by each edge server. The wind-electricity photovoltaic prediction subsystem is used for medium-and-long term transaction prediction: the medium-long term prediction is performed once in months, quarters or half a year, and the optimal transaction strategy is obtained.

The mid-long term prediction in the application is to predict once in months, quarters or half a year, and the method for acquiring the mid-long term optimal transaction strategy in the application specifically comprises the following steps: market information and user information are acquired; carrying out transaction price prediction based on market information and user information to obtain day-ahead price prediction data; based on the day-ahead price prediction data, solving with the goal of maximizing the medium-long term and day-ahead settlement yields to obtain a spot transaction strategy, which specifically comprises the following steps:

(1) First, obtaining the information of the demand clients, including: obtaining a client database; performing attribute classification on the client data set to obtain a client classification set; based on the client classification set, respectively carrying out demand parameter analysis on various clients, and determining a client demand parameter list, wherein the client demand parameter list comprises client categories, demand parameters and corresponding relations with demand electric quantity; and obtaining the demand customer information according to the customer demand parameter list. Specifically, the demand customer information is information of the electricity customers, including customer names, attributes, electricity objects, electricity consumption amounts, and the like. In the process of determining and selecting a customer group, the customer group is selected according to the analysis requirement, optionally, a city, a region and the like construct a customer database through the requirement customer information of a selection range, the data in the customer database are subjected to classification analysis, the types of customers are divided according to different attributes of different customers, such as manufacturing and processing industry, living department stores, residential areas and the like, different customer attributes correspond to different requirement influence parameters, such as the manufacturing and processing industry is influenced by the type of working days, production and maintenance plans, sales periodicity and the like, fluctuation and regularity are provided, and fluctuation and change exist in the influence of electricity and seasons and weather factors of the residential areas. The demand parameter analysis is to analyze corresponding demand quantity influence parameters for different types of clients, the client demand parameter list is a parameter set for carrying out attribute and characteristic analysis for each type of client, the determined parameter set for influencing the demand comprises the corresponding relation between the client type and the demand parameter, and meanwhile, the corresponding relation between the demand parameter and the demand electric quantity integrates information content in a client database by utilizing the format of the list, so that the demand quantity of the demand client is conveniently divided and counted.

Therefore, the demand customer information is based on the customer demand parameter list, the demand customer parameter list can be utilized to count and extract the demand quantity of the demand customer, and convenience is provided for reliable analysis of the market demand quantity.

(2) Inputting the demand customer information into a demand prediction model to obtain demand prediction information, wherein the demand prediction information comprises a plurality of demand prediction values in a first period, inputting the demand customer information into the demand prediction model to obtain the demand prediction information, wherein the demand prediction information comprises a plurality of demand prediction values in the first period, and the method comprises the following steps: obtaining a client category, a demand parameter and a demand electric quantity according to the demand client information; inputting a client type, a demand parameter and a demand electric quantity into a demand prediction model, wherein the demand prediction model is a neural network model obtained by training and converging a plurality of sets of training data, and each set of data in the plurality of sets of training data comprises the client type, the demand parameter, the demand electric quantity and identification information for identifying demand prediction information; obtaining various demand prediction results output by a demand prediction model; and accumulating all types of demand prediction results to obtain demand prediction information.

(3) The acquisition of the power supply information is specifically a power supply state of a market for research analysis including power yield, power company information, supply range, equipment maintenance schedule, and the like.

(4) And inputting the electric power supply information into a supply prediction model to obtain supply prediction information, wherein the supply prediction information and the demand prediction information have a corresponding relation of periodic time points. Further, the power supply information includes: the method comprises the steps of inputting power supply information into a supply prediction model to obtain supply prediction information, wherein the supply prediction information and demand prediction information have a corresponding relation of a periodic time point, and the method comprises the following steps: inputting power supply influence information and power supply capacity into the supply prediction model; obtaining a power supply prediction amount output by the supply prediction model; and summarizing all the power supply prediction amounts to obtain the supply prediction information.

Specifically, the power supply information is input into a supply prediction model to perform a prediction analysis of the supply amount, and a change prediction result of the power supply amount is obtained. The supply prediction model is also a computer prediction model through machine learning, and can be a decision tree, a BP neural network, a support vector machine and the like. Aiming at different model architectures, the historical data of power supply is used as training data, the training data is learned, and the identification result in the historical data is corrected and optimized, so that the supply prediction model is trained and converged. The supply prediction model can output supply prediction information after operation processing is carried out on the input power supply information, and the supply prediction information is a change result of the supply quantity.

(5) Constructing a prediction data matrix according to the demand prediction information and the supply prediction information, and constructing the prediction data matrix according to the demand prediction information and the supply prediction information, wherein the method comprises the following steps: obtaining demand time information and a demand predicted value according to the demand predicted information; obtaining supply time information and a supply predicted value according to the supply predicted information; determining a time corresponding relation based on the demand time information and the supply time information; and constructing a predicted data matrix according to the demand predicted value and the supply predicted value based on the time corresponding relation. The demand prediction information includes a prediction result required by a period of time, the setting length of the time is set according to the transaction demand, and is usually a period of one year, the embodiment of the application is preset to a period of one year, the current customer demand information can be used for reporting the electric quantity demand and the current power supply plan, the prediction of one period is performed, the demand prediction information is a predicted value of one year, training data can be used as a group of training data in model training, the change characteristics of the data in the period are analyzed, and the output result is the predicted result in the period. The method can also be dot data training, when dot data training is performed, the predicted output result is a predicted result of one node, then the predicted result of the node is added into the currently determined demand value as input data to be predicted, and then the predicted result is added into the predicted result of the next node after the current data continues, and the node predictions are connected in series to obtain the predicted result. The demand prediction information is thus one period of continuous prediction information. The same supply prediction information is also a continuous prediction result in one cycle.

And aiming at the time nodes in the demand forecast information and the supply forecast information, corresponding the demand forecast result and the supply forecast result, constructing a matrix, wherein transverse data in the forecast data matrix are the demand forecast result and the supply forecast result in sequence, and longitudinal data are the demand forecast result and the supply forecast result of the time nodes.

(6) And carrying out transverse data analysis and longitudinal data analysis on the predicted data matrix to obtain transverse comparison data and longitudinal comparison data, specifically, carrying out transverse data analysis on the data in the predicted data matrix to obtain the numerical value change condition of demand and supply, constructing a demand change curve and a supply change curve, analyzing the longitudinal data in the predicted data matrix, namely, analyzing the demand and the supply quantity of the same time node to obtain a supply-demand relationship, and constructing a supply-demand relationship curve according to the difference value between the supply and the demand, wherein the supply-demand relationship change of the market can be possibly mastered.

(7) And obtaining electric power price information, determining transaction node information according to the electric power price information based on the transverse comparison data and the longitudinal comparison data, and generating a medium-term and long-term transaction strategy according to the transaction node information.

When a user node requests to enter a blockchain network, node check and network access check are firstly required to be carried out on the user units in the CA network, any check is not passed, a user cannot issue transaction information through the intelligent contract, the intelligent contract is utilized to solidify standards in a software program, the function condition, the carbon emission, the safety requirement, the environmental protection standard and the like of the user information units participating in the transaction are checked, and therefore the user meeting the related standards is ensured to participate in the transaction, and a digital certificate is issued to the user after meeting the conditions.

After the user submits the order, the electricity data is sent to the blocking management module, the power transaction meets the trend constraint, so that before the final determination of the transaction, the security check is needed, after the calculation is completed, if the security condition is met, the intelligent contract is entered for examination, the blockchain main chain carries out consensus, after the consensus is completed, the transaction data is uploaded to the database, and the user can check the public transaction data through the private key.

The block management module of the user transaction subsystem is specifically configured to: numbering all unit nodes of an n-node power grid system, wherein the power grid unit nodes are 1,2, … and n-1, the node n is a node connected with a power distribution network, and the node n is regarded as a balance node. At this time, the admittance matrix is defined as Y, which is reduced to a matrix B that only retains the imaginary part of Y if a dc model is used. The flow equation can be expressed as:

Bθ＝P _G -P _D

Wherein B represents a (n-1) x (n-1) matrix without balance nodes;

P _G represents an n-1-dimensional node power generation vector, P _G ＝[P _g1 ，P _g2 ，…P _g(n-1) ] ^T ；

P _D Representing an n-1-dimensional node equivalent load vector, P _D ＝[P _L1 ，P _L2 ，…P _L(n-1) ] ^T 。

θ can be expressed as: θ=b ^-1 (P _G -P _D )

Definition of impedance array z=b ^-1 Definition of

And is also provided with

An augmented equation can be obtained:

obviously for the power of any branch connecting nodes i and j in the distribution network

Can be expressed as:

defining the association matrix of the branch nodes as A (defining the left node as positive and the right node as negative), the above can be written as a matrix form:

substituting the augmentation equation into the above equation:

defining a power transfer factor:

wherein: PTDF (pulse-duration factor) _k-i Representing the power transfer factor of node i to leg k.

The tidal current value of each line can be obtained correspondingly from the power transmission factor, and the result is compared with the capacity of the corresponding line to check whether the tidal current limit is exceeded.

in the formula T_k The maximum transmission power of the line k is represented, and the smaller of the thermal stability and dynamic stability constraint values is taken.

The security verification process in a transaction cycle can be roughly divided into the following three steps:

the first step is to determine the line power flow, and according to the line structure parameters, a power transmission matrix PTDF can be obtained, and the power transmission matrix is unchanged under the condition that the system topology is not changed. After the matching transaction, the distribution network can determine the flow of each line (i lines and m nodes) in the distribution system according to the transaction electric quantity and the declared electric quantity (selling and purchasing).

in the formula P_l Representing the power transmission to which the line l is subjected under the current trade scheme;

PTDF represents the power transmission matrix;

the representation unit m declares the generated energy under the current transaction scheme;

the presentation unit m declares the amount of electricity used under the current transaction scheme.

The second step is to judge out of limit of the power flow, after the power distribution network obtains the power flow of each line, the power flow of each line is compared with the maximum transmission power flow of the line, and whether the problem of out of limit of the power flow exists is judged;

|P _l |≤T _l

and thirdly, carrying out power flow out limit processing, and broadcasting the power flow out-of-limit lines to each unit if the power flow out-of-limit problem exists in the lines l. By power transmission factor PTDF _l-i Determination ofWhether the micro network unit i has an influence on the blocked line i.

in the formula P_l-i Representing the power contribution of the micro-grid element i to the line i.

Definition: if P _l And P _l-i When the numbers are the same, i.e. the power flows are the same, the micro-grid unit i makes a positive contribution to the line l, otherwise it makes a negative contribution.

If the micro-grid unit i makes negative contribution to the line l, the power flow contribution degree beta _l-i 0, and the sum of the negative contributing powers is:

ΔP _l ＝|sum(P _l-i )|

in the formula ΔP_l Representing the sum of the negative contributing powers.

If the micro-grid unit i makes positive contribution to the line l, the power flow contribution degree is as follows:

in distributed blocking management, each unit determines a power flow contribution coefficient to a power flow blocking line, and then determines a blocking management power price:

Δc _i+1 ＝Δc _i +Kβ _l-i |T _k ||P _l-i -T _k |

At the initial time, the congestion management electricity price of the unit i is zero, and the declared price of the congestion management electricity price correction is used:

in the formula

The kth quotation for element i;

is a unitBlocking electricity prices for the kth iteration of i.

And after correcting the quotation by using the blocking electricity price, re-matching the transaction according to the market transaction strategy until the line blocking is eliminated and the safety verification is passed.

The power transaction can generate a line blocking problem, after a user submits an order, power consumption data are sent to a blocking management module, the blocking management module analyzes transaction data, the transaction can be performed after the line safety is met, the power transaction also has a line loss problem, and a method for converting power and electricity price is provided; after transaction data are generated, the members passing through the back blockchain main chain are subjected to intelligent contract checking, the transaction data are uploaded to a database after the checking is finished, all the transaction data in the database are divided into public data and non-public data, the database is encrypted in a grading mode by an HDES, all the data can be seen by the members of the main chain, and only the public data can be seen by the member application of the side chain.

After the auditing of the intelligent contract is satisfied, the new energy power station declares the output curve and the market pricing, and sends the output curve and the market pricing to the electric power transaction center MChain_cen, and the electric power transaction center audits the electricity price and the electric quantity sent by each generator, so that the electricity price in the current time period is satisfied at the specified highest electricity price P _max，t And the lowest electricity price P _min,t Then, the information is published on the blockchain, and after some constraint conditions of buyers and sellers are met, the electricity utilization side can purchase according to the satisfied requirements. The blockchain audit mechanism is constructed on the blockchain and can audit all data operation behaviors on the chain. The mechanism records any read-write operation and updated data of the main chain MChain and the side chain SChain, and enhances the operation compliance of each side of MChain, SChain.

The method for converting the electricity and the electricity price is to convert the electricity and the price declared by the buyer market body at the buyer node into the seller node according to the following formula according to all available transaction paths

price _s,j,t ＝price _b,j,t ×coe ₁ -price

P _min，t ≤price _b,j,t ≤P _max,t

Wherein: power device _b,j,t Reporting power for the buyer market subject j in the t period;

power _s,j,t reporting power conversion to the power of the seller node for the buyer market subject j during the period t;

price _b,j,t electricity price of the buyer market subject j in the t period;

price _s,j,t the electricity price of the price to the seller node is calculated for the buyer market subject j in the period t;

coe ₁ is a conversion parameter;

price _coe is an intermediate conversion variable;

m is a cross-zone channel in the transaction path, and a provincial interconnecting line or a serial number of a regional shared power grid;

ρ _m the transmission network loss rate of the inter-provincial tie lines or regional shared power network is the mth-section trans-regional channel from the seller node to the buyer node in the transaction path;

Pt _m The method comprises the steps that a transmission price of a power grid is shared by inter-provincial tie lines or areas for an mth-section trans-regional channel from a seller node to a buyer node in a transaction path;

n is the total number of cross-zone channels in the transaction path, inter-provincial interconnecting lines or regional shared power grids.

P _max，t The highest electricity price, P, specified for the current time period _min,t The lowest electricity price specified for the current time period.

Line constraint conditions:

in the formula ：F_max Representing maximum capacity, f _i Representing all user capacity;

when (when)

Exceeding F _max When this line is blocked, it is necessary to manage it so that these users can regenerate the transaction policy.

The consensus module of the block chain subsystem after the data is uplink is used for: and adopting a dBFT mechanism to complete the consensus process of the alliance chain. After the data is uplink, the data is recorded in the block after being commonly recognized by each node on the alliance chain. The MChain_cen is used as a main node in the system, and the node only plays a role in initiating and guiding a consensus process, so that the uplink requests can be ordered. Other nodes except the main node on the MChain are set as proxy nodes, and the nodes on the SChain are common nodes. The proxy node has the right to account, and the common node can see the consensus process and synchronize account information, but does not participate in accounting. The specific consensus process is as follows

1) After the data of each transaction party is generated, the data is transmitted to the power transaction center node psi _i After the abstract is extracted through pretreatment, the abstract value record is respectively broadcast to a main chain and a side chain in a block chain network, wherein D _C1 ，D _C2 Transaction data of the encrypted generator and the electricity consumption side are as follows:

2) After receiving enough transaction data, the master node sorts and uploads the data to the new block, signs the new block and hashes the new block with Hash value (D _Ci ) Broadcast into the backbone network. After receiving the block, other proxy nodes on the mchash add the transaction data of each party in the block to the account book of the user, and then perform Hash operation on the transaction data of each party in the block, and the Hash value Hash (D _Ci ') comparing, if the two Hash values are the same, the proxy node considers the block to be correct, andthe acknowledgement information is broadcast onto the blockchain network.

ψ _i →ψ _n :Ver[Sig _{key_cen} (D _C ,Hash(D _C ))]

if:

Hash(D _Ci )＝Hash(D _Ci ')

else:

Hash(D _Ci )≠Hash(D _Ci ')

Timestamp

3) The proxy node needs to collect the confirmation information broadcast by other proxy nodes besides verifying the data integrity of the transaction information sent by the main node. If the proxy node receives more than 2n+1 Commit's acknowledgement, the node considers this block valid and synchronizes it to the local ledger. The common node can synchronize the blocks newly generated by the proxy node. If the proxy node receives the negative acknowledgement information of not more than n Deny, the main node signs the new block again and broadcasts the Hash value to the main network for re-verification. And if the authentication still fails, synchronizing the confirmation information results of other proxy nodes to the local ledger. The master node and the MChain_cen audit and trace the information of the block, and conduct responsibility pursuit on malicious attack behaviors for modifying the information of the block. n is the number of transmission error nodes which can be tolerated by the blockchain, and the system can tolerate the number of the nodes which does not exceed the whole network according to the entrusted Bayesian fault-tolerant mechanism

Is a node error of (a).

The hierarchical encryption and decryption module of the blockchain subsystem is specifically used for: in order to avoid that lawbreakers take all transaction data, transaction data management is carried out in a hierarchical encryption mode of HDES, all the transaction data are stored in a blockchain, the main chain can see all the transaction data, and the side chain can only see public information and transaction information related to the side chain. The MChain cen grants authority between the main chains of government regulatory authorities and transaction management authorities, performs public-private key pair distribution on the authorities on the MChain, and grants blockchain audit authorities authority by the MChain cen. Public and private key pair distribution is also carried out on the SCHain, the data security of users in each party can be ensured through hierarchical encryption, and the institutions or individuals on the MChain and the SCHain obtain keys corresponding to different levels through the authorization of the electric power transaction center to decrypt the data. And performing blockchain audit on all transaction information operations by a blockchain audit method to derive a privacy data visitor record. The MChain_cen can read the record of the data visitor, so that the mastering of the data flow direction is enhanced, and meanwhile, if the data is leaked, the MChain_cen can trace the data leakage behavior, so as to carry out responsibility pursuit and punishment on criminals stealing personal information. The extent of data that can be seen is different due to the different rights of the various institutions MChain, SChain. That is, the institution on the MChain can see all the transaction data, and in order to prevent the data leakage of the transaction parties, the institution on the MChain can only see the public transaction information and the transaction data related to the institution. As shown in fig. 4, the main chain node can view private data and basic data, while the side chain node can only view basic data.

All transaction data are divided into public data and non-public data, wherein the public data are transaction electricity price and electric quantity; the non-public data is transaction address, basic information of both transaction parties, transaction time and transaction order number.

The encryption all transaction data algorithm selects the AES-256 algorithm and the encryption public transaction data selects the CRT-RSA-OAEP algorithm. A, B is assumed to be the backbone-based mechanism MChain _A 、MChain _B C is the mechanism SCHain on the side chain _C . And mchain_cen has been authorized and assigned to MChain _A And MChain _B Private Key Key __ MP _A 、Key_MP _B And public Key Key_MS _A 、Key_MS _B And assigned to SChain _C Private key Key_SP _C And public Key Key_SS _C . Fig. 5 is a hierarchical encryption flow chart of an embodiment of the present invention.

First-stage encryption:

step 1 with MChain _A As an example. First, a key_MS is randomly generated as a main chain node public Key by using a smart contract _A ＝(n ₁ ,e ₁ ) The private Key is Key_MP _A ＝(n ₁ ,d ₁)； wherein ,n₁ Is the product of two random large prime numbers,

and is also provided with

Step 2K generated using Smart contracts _RE1 For all transaction DATA information DATA _A Performing one-by-one symmetric encryption to form ciphertext

At this time with the public transaction DATA information DATA _B Is in plaintext state->

Deriving similar information 1: />

Will be->

And (3) winding;

step 3MChain _A Key_MS using MChain_cen grant assignment _A For K _RE1 Asymmetric encryption, K _RE1 -C _A To use Key_MP _A Encryption K _RE1 Is the ciphertext of (a);

step 4 derives a method similar to MChain _A ∶K _RE1 -C _A And written to the blockchain.

Second-stage encryption:

step 1 with MChain _A And SChain _A As an example. First, side-chain node public key K is randomly generated using smart contractsey_SS _C ＝(n ₂ ,e ₂ ) And private Key Key_SP _C ＝(n ₂ ,d ₂) wherein ,n₂ Is the product of two random large prime numbers,

and is also provided with

Step 2 Using K _RE2 For a pair of

and />

Encryption one by one is carried out, and the encryption is carried out>

Representing the second-stage encrypted ciphertext, at which time DATA _A Is in a secondary encryption state, DATA _B Is in a primary encryption state;

step 3MChain _A And SChain _C . Key assigned using MChain authorization _A And Key_SS _C . For K _RE2 Asymmetric encryption is performed one by one, where K _RE2 -C _C . To use Key_SS _C Encryption K _RE2 Is the ciphertext of (a);

step 4 derives a method similar to SChain _C ∶K _RE2 -C _C Is written into the block chain;

step 5 deriving a similar information 1:

and written to the blockchain.

The flow of decrypting transaction data on the main and side chains is as follows, and MChain is now _A Decrypting the data on the block chain, wherein the specific flow is as follows:

first level decryption:

step 1MChain _A Data acquisition request is sent to the data system, and the current time stamp is sent and encrypted in the following format of request ₁ _C _A ＝(DATA _B ||DATA _S ) The data system then verifies the MChain _A MChain when the identity of (a) _A A verification time stamp is regenerated and encrypted in the following format: verify _A _C ₂ ＝(DATA _B ||DATA _S If the data system verifies the identity successfully, the encrypted data is encrypted

Return to MChain _A . Auditing by a blockchain auditing mechanism;

step 2MChain _A Key_MP read from blockchain using smart contracts _A :K _RE2 -C _A Key value pair, MChain _A Private Key Key_MP distributed using MChain_cen authorization _A For K _RE2 -C _A Decryption is performed. Auditing by a blockchain auditing mechanism to generate a data operation record;

step 3MChain _A Using K _RE2 For a pair of

Decryption is carried out, and audit is carried out by a blockchain audit mechanism. Due to K _RE2 DATA that can only be decrypted _B DATA at this time _A Still is ciphertext state->

Step 4 will

And->

Separating (S) the parts>

For second layer decryption.

Second level decryption:

step 1MChain _A Reading K from blockchain data system using smart contracts _RE1 -C _A ，MChain _A Key_MP distributed using MChain_cen grant _A For K _RE1 Decrypting and auditing by a block chain auditing mechanism to generate a data operation record;

step 2 to obtain K _RE1 After that, MChain _A Acquiring data in a blockchain data system using smart contracts

Key value pairs of (2);

step 3MChain _A Using K _RE1 For a pair of

Decryption is carried out to obtain +. >

And audited by a blockchain audit mechanism.

The individual or institution on the side chain only needs to perform the first level decryption to obtain the basic DATA DATA _B 。

When a node on the main chain or the side chain exits from the blockchain, or the MChain_cen forcible blocks the node, the authority of the node needs to be revoked. But because the blockchain is non-tamper-evident, the similar MChain: K cannot be deleted directly from the blockchain ledger _RE1 -C key-value pair to revoke rights, the system needs to revoke rights to the node to view information by adding revocation information to the blockchain ledger. The new revocation information is added to the blockchain ledger, and the blocks on the blockchain are connected together in time sequence, so that when the access strategy is checked, the latest added access control information is checked first, and once the access control strategy of the node is searched, the search is stopped immediately. The node can check the revocation of the personal information authority.

Method embodiment

An embodiment of the present invention provides a method for servicing a green power transaction, and fig. 2 is a flowchart of a method for servicing a green power transaction according to an embodiment of the present invention, where, according to the method for servicing a green power transaction shown in fig. 2, the method for servicing a green power transaction according to an embodiment of the present invention includes:

S1, a user registers on an electric power transaction platform, an intelligent contract examines and logs in after the examination passes, a generator uploads electricity selling information on the electric power transaction platform, and an electricity using side selects according to the electricity selling information uploaded by the generator;

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the 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 scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims

1. A system for servicing green power transactions, comprising: the system comprises an electric power transaction platform, a block chain subsystem, a user transaction subsystem, a CA certificate subsystem and a wind power photovoltaic prediction subsystem;

the power transaction platform is in interactive connection with the block chain subsystem, the user transaction subsystem, the CA certificate subsystem and the wind power photovoltaic prediction subsystem;

the power transaction platform is used for providing a registration and login platform for users of green power transaction, and the users comprise power generators and power utilization sides; release for power producer Electricity selling information; receiving an optimal transaction strategy provided by the wind power photovoltaic prediction subsystem, and providing an optimal power supply line for the power utilization side after purchasing power according to the selected transaction strategy according to the optimal transaction strategy; generating an order according to the power supply line selected by the power utilization side for storing transaction data in a database;

the blockchain subsystem is designed in a blockchain mode and comprises a main chain and a side chain, wherein members of the side chain comprise a generator and a power utilization side, members of the main chain comprise a power transaction center and a transaction supervision department, and the blockchain subsystem is used for completing power and electricity price conversion of the power transaction center; completing block chain consensus after data uplink; storing privacy data and basic data generated by electric power transaction, carrying out information interaction between the main chain and the side chain through the side chain, carrying out safe sharing on data of each transaction party, and carrying out fine granularity protection on the transaction data on the chain by adopting a hierarchical encryption technology; applying for accessing transaction data stored in the power transaction platform;

the CA certificate subsystem is used for issuing a digital certificate after node verification and network access verification are carried out on the user through an intelligent contract;

2. The system of claim 1, wherein the user transaction subsystem specifically comprises:

the transaction module is used for generating transaction data according to the order submitted by the user;

the blocking management module is used for judging whether to perform blocking management according to the line constraint condition and regenerating a transaction strategy for the line needing blocking management;

a security check module for performing security check on the transaction

The examination consensus module is used for acquiring transaction data which is subjected to intelligent contract examination through the CA certificate subsystem and is consensus through the blockchain subsystem;

and the data uploading module is used for uploading the transaction data in the examination consensus module to a database.

3. The system according to claim 2, wherein the blocking module is specifically configured to:

each unit node of the power grid system participating in green transaction is numbered and is recorded as 1,2, … and n-1, wherein the node n is a node connected with a power distribution network, the node is regarded as a balance node, an admittance matrix is defined as Y, by adopting a direct current model, Y is simplified into a matrix B only retaining an imaginary part of Y through a formula 1, and a power flow equation can be expressed as:

Bθ＝P _G -P _D equation 1;

wherein B represents an (n-1) x (n-1) matrix without balance nodes; p (P) _G Represents an n-1-dimensional node power generation vector, P _G ＝[P _g1 ，P _g2 ，…P _g() ] ^T ；P _D Representing an n-1-dimensional node equivalent load vector, P _D ＝[P _L1 ，P _L2 ，…P _L(n-1) ] ^T The method comprises the steps of carrying out a first treatment on the surface of the θ is expressed as: θ=b ^-1 (P _G -P _D )；

Definition of impedance array z=b ^-1 Definition of

And->

The augmented equation is obtained by equation 2:

obtaining the power of the branch connecting nodes i and j by equation 3

Defining the association matrix of the branch nodes as A, and carrying out

Expressed in matrix form by equation 4:

substituting the augmentation equation into equation 4:

defining a power transfer factor:

wherein PTDF is _k-i Representing the power transmission factor of node i to branch k;

obtaining a tide value of each line according to the power transmission factor obtained in the formula 6, and comparing the tide value with the capacity of the corresponding line to check whether the tide is out of limit;

wherein ,T_k The maximum transmission power of the line k is represented, and the smaller of the thermal stability and dynamic stability constraint values is taken.

4. The system according to claim 2, wherein the security check module is specifically configured to:

acquiring a power transmission matrix PTDF according to a formula 8;

wherein ,P_l Representing the power transmission to which the line l is subjected under the current trade scheme; PTDF represents the power transmission matrix;

the representation unit m declares the generated energy under the current transaction scheme; />

Comparing the power flow of each line with the maximum transmission power flow of the line through a formula 9, and judging whether the problem of power flow out-of-limit exists or not;

|P _l |≤T _l equation 9;

if the line l has the problem of power flow out-of-limit, the line with the power flow out-of-limit is broadcasted to each unit, and the power transmission factor PTDF is used for transmitting the power _l-i Determining whether the micro-grid unit i has an influence on the blocking line l; obtaining the power contribution of the micro network unit i to the line l according to equation 10:

if P _l And P _l-i The same number, namely the same power flow direction, the micro-grid unit i makes positive contribution to the line l, otherwise, makes negative contribution; if the micro-grid unit i makes negative contribution to the line l, the power flow contribution degree beta _l-i Is 0 and the sum of the negative contribution powers is DeltaP _l ：

ΔP _l ＝|sum(P _l-i ) Equation 11;

if the micro-grid unit i makes a positive contribution to the line l, the power flow contribution is obtained by the formula 12:

in the distributed blocking management, each unit determines a power flow contribution coefficient to a power flow blocking line, and then determines a blocking management power price through formula 13:

Δc _i+1 ＝Δc _i +Kβ _l-i |T _k ||P _l-i -T _k equation 13;

at the initial time, the congestion management electricity rate of the unit i is zero, and the declared price corrected using the congestion management electricity rate is obtained by the formula 14:

wherein ,

the kth quotation for element i; />

Blocking electricity price for the kth iteration of unit i.

5. The system according to claim 1, wherein the blockchain system specifically comprises:

the electricity price conversion module is used for sending the current market clearing boundary conditions, the current market clearing boundary conditions and the current market pricing to the electric power transaction center, and the electric power transaction center is used for publishing the electricity selling information of the highest electricity price and the lowest electricity price which meet the current time period electricity price specification and are sent by each electricity generator;

the consensus module is used for completing consensus of the alliance chain by adopting a dBFT mechanism;

The hierarchical encryption and decryption module specifically comprises: and carrying out hierarchical encryption on the private data stored in the main chain and the basic data stored in the side chain by adopting a hierarchical encryption technology.

6. The system of claim 5, wherein the electricity price conversion module is specifically configured to:

the new energy power station declaration output curve and market pricing are sent to the electric power transaction center, the electric power transaction center checks the electricity price and the electric quantity sent by each generator, and the current time period electricity price is satisfied at the specified highest electricity price P _max，t And the lowest electricity price P _min,t Then, it is published on the blockchain; the power transaction center audits electricity prices and electricity quantities sent by all power generators specifically comprises the following steps: the electricity and price declared by the buyer market subject at the buyer node are judged according to all available transaction paths according to the formulas 15 to 19 whether the electricity price in the current time period is at the prescribed highest electricity price P _max，t And the lowest electricity price P _min,t Inner:

price _s,j,t ＝price _b,j,t ×coe ₁ -price formula 16;

P _min，t ≤price _b,j,t ≤P _max,t equation 19;

wherein the power _b,j,t Reporting power for the buyer market subject j in the t period; power device _s,j,t Reporting power conversion to seller node for buyer market subject j during period tElectric power; price _b,j,t Electricity price of the buyer market subject j in the t period; price _s,j,t The electricity price of the price to the seller node is calculated for the buyer market subject j in the period t; coe ₁ Is a conversion parameter; price _coe Is an intermediate conversion variable; m is a cross-zone channel in the transaction path, and a provincial interconnecting line or a serial number of a regional shared power grid; ρ _m The transmission network loss rate of the inter-provincial tie lines or regional shared power network is the mth-section trans-regional channel from the seller node to the buyer node in the transaction path; pt (Pt) _m The method comprises the steps that a transmission price of a power grid is shared by inter-provincial tie lines or areas for an mth-section trans-regional channel from a seller node to a buyer node in a transaction path; n is the total number of cross-region channels in the transaction path, inter-provincial interconnecting lines or regional shared power grids; p (P) _max，t The highest electricity price, P, specified for the current time period _min,t The lowest electricity price specified for the current time period.

7. The system according to claim 1, wherein the CA certificate system specifically comprises:

the intelligent contract checking module is used for checking node check and network access check of the user nodes required to enter the blockchain subsystem through the intelligent contracts, then issuing transaction information through the intelligent contracts, and checking the function conditions, the carbon emission, the safety requirements, the environmental protection standards and the like of the user information units participating in the transaction by utilizing the intelligent contracts so as to ensure that the users meeting the related standards participate in the transaction;

And the issuing certificate module is used for issuing the digital certificate to the user subjected to contract examination.

8. The system of claim 1, wherein the wind-to-photovoltaic prediction subsystem is specifically configured for medium-to-long term transaction prediction:

the medium-long term prediction is performed once in months, quarters or half a year, and an optimal transaction strategy is obtained.

9. The system of claim 5, wherein the hierarchical encryption and decryption module is specifically configured to:

the method adopts an HDES hierarchical encryption mode to conduct transaction data management and encryption, all transaction data algorithms are selected from an AES-256 algorithm, and the encrypted and disclosed transaction data are selected from a CRT-RSA-OAEP algorithm.

10. A method of servicing a green power transaction, characterized in that it is based on any of claims 1-9, comprising: