CN113343571A - Distributed photovoltaic electric energy consumption method in rural power distribution network - Google Patents

Distributed photovoltaic electric energy consumption method in rural power distribution network Download PDF

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CN113343571A
CN113343571A CN202110658433.6A CN202110658433A CN113343571A CN 113343571 A CN113343571 A CN 113343571A CN 202110658433 A CN202110658433 A CN 202110658433A CN 113343571 A CN113343571 A CN 113343571A
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杨建华
靳开元
张涛
薛文景
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China Agricultural University
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Abstract

The invention relates to a distributed photovoltaic electric energy consumption method in a rural power distribution network. According to the method, a block chain system and benefit functions of different benefit subjects are established, an internal trading electricity price and a user optimal electricity utilization strategy are determined by using a game theory model, and the agricultural users are promoted to move time-shifting loads to consume photovoltaic electricity through a credit value mechanism, so that the problems that the existing photovoltaic trading mode is poor in applicability in rural power distribution networks and photovoltaic power generation power cannot be consumed on the spot are solved, and the consumption level on the spot is improved.

Description

Distributed photovoltaic electric energy consumption method in rural power distribution network
Technical Field
The invention belongs to the technical field of distributed electric energy consumption, and particularly relates to a distributed photovoltaic electric energy consumption method in a rural power distribution network.
Background
Photovoltaic power generation is a clean renewable energy power generation mode, and can promote the development of local economy 'near zero carbon emission'. However, the rural power distribution network with a relatively weak grid structure is under great pressure due to the large-scale access of photovoltaic power supplies, and the problems of voltage out-of-limit, network loss increase, difficulty in local consumption and the like occur in partial areas. Under the large background that the problem of 'light abandonment' is serious day by day, explore the transaction mode of distributed photovoltaic in rural power distribution network, help to arouse the power consumption potentiality of agricultural load, realize the local or nearby consumption of photovoltaic power generation power, reduce the electric wire netting operating loss, improve the economic income of agriculture, realize the goal of 'killing more than one thing' and 'nearly zero carbon emission' development.
In recent years, the block chain technology gradually goes to reality from technical conception, and has shown strong application potential in the field of energy and power. The block chain technology with the characteristics of decentralization, traceability, transparent transaction, non-falsification and the like can solve the trust problem of electric energy transaction, so that the transaction cost between electric energy supplies and users is reduced. With the development of the internet of things and the 5G technology, edge computing as a distributed computing mode can provide more intelligent real-time service for users; meanwhile, the edge calculation is very fit with the distributed characteristics of the block chain, the edge calculation unit can be used as a node of the block chain, optimization solution is carried out according to corresponding requirements, data safety is guaranteed under the support of the block chain technology, and the possibility is provided for future service type expansion.
At present, distributed photovoltaic consumption of rural power distribution networks is less researched, the existing photovoltaic trading mode has no pertinence, the photovoltaic power generation power cannot be consumed on the spot or nearby, and the phenomenon of light abandonment is serious. Some research documents only research the application of block chain technology in microgrid electric energy transaction, and cannot be applied to the transaction scene of rural power distribution network distributed photovoltaic.
Disclosure of Invention
Aiming at the technical problems, the invention aims to provide a distributed photovoltaic electric energy consumption method in a rural power distribution network, which is used for establishing a block chain system and benefit functions of different benefit subjects, determining internal transaction electricity prices and user optimal electricity utilization strategies by using a game theory model, promoting agricultural users to mobilize time-shifting loads to consume photovoltaic electric quantity by using a credit value mechanism, solving the problems that the existing photovoltaic transaction mode is poor in applicability in the rural power distribution network and photovoltaic power generation power cannot be consumed on the spot, and improving the consumption level on the spot.
In order to achieve the purpose, the invention provides the following technical scheme:
a distributed photovoltaic electric energy consumption method in a rural power distribution network comprises the following steps:
s1, establishing a blockchain system, registering the agricultural user with transaction qualification and the distributed photovoltaic aggregators in the blockchain system, and uploading the position information of the agricultural user, the position information of each distributed photovoltaic access point of the distributed photovoltaic aggregators and the installed capacity to the blockchain system;
the block chain system comprises a plurality of blocks generated by agricultural users and distributed photovoltaic aggregators after completing photovoltaic electric energy transactions; each block comprises a block head and a block body;
the block head comprises a hash value, a time stamp and a Mercker root of a previous block; wherein the time stamp records a generation time of the block; the hash value of the previous block is used as an identification code, so that each block has traceability, and a complete transaction chain is formed; the Mercker root is a root node of a block body;
the block body adopts a structure of a Mercker tree, and a root node is arranged in a block head and comprises a distributed photovoltaic sub-node, an agricultural user sub-node and a photovoltaic absorption information node; the distributed photovoltaic sub-nodes comprise photovoltaic predicted output hash values and photovoltaic actual output hash values; the agricultural user child node comprises an agricultural load prediction hash value and an agricultural load actual hash value; the photovoltaic consumption information node comprises a photovoltaic consumption electric quantity hash value and a large power grid balance electric quantity hash value;
the block chain system allows distributed photovoltaic aggregators and agricultural users to join as nodes, the distributed photovoltaic aggregators comprise one or more distributed photovoltaic sub-nodes, and one agricultural user serves as one agricultural user sub-node; the large power grid is used as a photovoltaic consumption information node and is responsible for transmitting electric energy, supervising photovoltaic electric energy transaction and balancing deviation electric quantity;
s2, at a certain time before trading, the distributed photovoltaic aggregators in the block chain system obtain photovoltaic peak power according to the installed capacity of the distributed photovoltaic aggregators in the step S1, and then obtain the predicted photovoltaic power generation power in the trading period according to the photovoltaic peak power; an agricultural user issues a power purchase request;
s3, respectively establishing benefit functions of agricultural users and benefit functions of distributed photovoltaic aggregators by the blockchain system, and calculating a balanced solution of a master-slave game model through a master-slave game method, namely obtaining an optimal internal trading electricity price psOptimal electricity utilization strategy x for and each agricultural useri*；
S3.1, the benefit function of the agricultural user established by the block chain system is shown as the formula 1:
Figure BDA0003114239740000031
in the formula 1, AiThe unit is element for the benefit of the agricultural user i; k is a radical ofiA benefit parameter for agricultural user i;
Figure BDA0003114239740000032
the electricity consumption of the agricultural user i in a period of time T is represented by kWh; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofsThe price of the power is not lower than the price of the power on the internet and is not higher than the price of the power sold by the power grid; the on-line electricity price is the electricity price for purchasing electricity from the large power grid to the distributed photovoltaic aggregation suppliers, and the electricity selling price is the electricity price for purchasing electricity from the large power grid to farmersSelling the electricity price of the electric energy by the business user;
the benefit function of the distributed photovoltaic aggregator established by the block chain system is shown as formula 2:
Figure BDA0003114239740000033
in the formula 2, AsThe unit is element for the benefit of the distributed photovoltaic aggregator;
Figure BDA0003114239740000034
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure BDA0003114239740000041
the total electricity consumption of the agricultural users in the block chain in the time period T is represented in kWh; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the current voltage level, wherein the unit is element; p is a radical ofgbThe unit of the electricity selling price of the power grid under the current voltage level is element; σ is a constant value set to 0.01;
s3.2, constructing a master-slave game model G, wherein the master-slave game model G is shown as a formula 3:
Figure BDA0003114239740000042
in equation 3, distributed photovoltaic aggregation quotient N within the blockchain systemSAs a leader, a set of agricultural users N within a blockchainBAs a follower;
Figure BDA0003114239740000043
electricity consumption for agricultural user i within time T
Figure BDA0003114239740000044
A selection set of (a); p is the internal trade price P of the blockchainsThe set of policies of (2); a. theiBenefits for agricultural users i; a. thesFor distributed photovoltaic aggregatorsThe benefits;
to achieve nash equilibrium in the master-slave game model G, all participants need to obtain optimal values under the conditions, namely the distributed photovoltaic aggregator has the maximum benefit and the agricultural user group has the maximum benefit, equilibrium solutions of the master-slave game model are obtained through calculation of a formula 4 and a formula 5 respectively, namely the distributed photovoltaic aggregator finds the optimal internal trading electricity price psMake it have the benefit AsMaximally, each agricultural user finds the optimal power utilization strategy xiThereby achieving maximum revenue;
Figure BDA0003114239740000045
Figure BDA0003114239740000046
in the formulas 4 and 5, N is the number of agricultural users in the block chain system; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the voltage level, and the unit is element; k is a radical ofiA benefit parameter for agricultural user i; p is a radical ofsThe price is the optimal internal transaction price, and the unit is element; x is the number ofiAn optimal electricity usage strategy for each agricultural user;
s4, the intelligent contract module in the blockchain system acquires the optimal electricity utilization strategy x of the agricultural user according to the electricity purchase request issued by the agricultural user in the step S1, the predicted photovoltaic power generation power of the distributed photovoltaic aggregators in the step S2 and the optimal electricity utilization strategy x of the agricultural user acquired in the step S3iAutomatically generating a trade contract; the predicted photovoltaic power generation power is a photovoltaic predicted output hash value; the optimal power utilization strategy xiThe hash value is the agricultural load prediction hash value; if the predicted photovoltaic power generation power cannot meet the optimal power utilization strategy xiTime, the predicted additional power delivered by the large power grid is balanced;
s5, according to the trade contract, the distributed photovoltaic aggregators enable the photovoltaic power generation power to be at the internal trade price psSelling to nearby agricultural users in the block chain system, and enabling the agricultural users to follow the optimal electricity utilization strategy xiElectricity usage; in the process, when light is emittedWhen the photovoltaic power generation power is excessive and cannot be absorbed at the current voltage level, the redundant photovoltaic power generation power is the price p of the network electricitygsSelling to a large power grid; when the photovoltaic power generation power cannot meet the power utilization requirement of the agricultural users, namely the load net power is larger than zero, the large power grid transmits the actual extra power to the agricultural users in the block chain system; the load net power is the hash value of the photovoltaic absorption electric quantity and is equal to the difference value of the actual hash value of the agricultural load and the actual hash value of the photovoltaic output; the difference value of the actual extra power transmitted by the large power grid and the predicted extra power transmitted by the large power grid is the hash value of the balance electric quantity of the large power grid; after the transaction contract is fulfilled, the distributed photovoltaic sub-nodes of the distributed photovoltaic aggregators and the agricultural user sub-nodes jointly generate blocks;
s6, after the transaction time period is over, the intelligent metering devices of the agricultural users serve as edge calculation units to feed back actual power utilization conditions to the blockchain system, the intelligent contracts complete transfer of transaction funds, and the blockchain system calculates credit values of the distributed photovoltaic aggregators and local consumption scores of the agricultural users according to the transaction conditions;
in step S6, the reputation value of the distributed photovoltaic aggregator includes two parts: the photovoltaic electric quantity deviation rate and the photovoltaic local or nearby consumption rate are shown as formulas 6 and 7:
Figure BDA0003114239740000051
Figure BDA0003114239740000052
in the formula (I), the compound is shown in the specification,
Figure BDA0003114239740000053
representing the actual total electric quantity sent by the distributed photovoltaic aggregator within the time T, namely the actual photovoltaic output hash value with the unit of kWh;
Figure BDA0003114239740000061
representing distributed photovoltaic aggregationThe predicted total amount of electricity emitted by the quotient over time T, i.e. the photovoltaic predicted output hash value, is given in kWh,
Figure BDA0003114239740000062
Figure BDA0003114239740000063
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure BDA0003114239740000064
represents the power consumption of all agricultural users in kWh within the time T;
Figure BDA0003114239740000065
the photovoltaic transaction electric quantity deviation rate of the distributed photovoltaic aggregators in the transaction time period T is obtained;
Figure BDA0003114239740000066
the local or nearby consumption rate of the photovoltaic in the transaction period T is given to the distributed photovoltaic aggregators;
Figure BDA0003114239740000067
reflects the enthusiasm of agricultural users in power consumption from the side,
Figure BDA0003114239740000068
the smaller the photovoltaic power is, the more energy consumed by a user in the time period is indicated, and the photovoltaic power can be promoted to be consumed locally or nearby when the photovoltaic power is excessive;
the credit value R of the distributed photovoltaic aggregators is shown as a formula 8;
Figure BDA0003114239740000069
wherein n is the number of transaction sessions within a day; alpha is alpha1And beta1The weight of the two indexes respectively represents the importance degree of the photovoltaic electric quantity deviation rate of the node and the photovoltaic grounding or nearby consumption rate, and the method uses alpha1Is set to 0.3, beta1Set to 0.7;
Figure BDA00031142397400000610
the photovoltaic transaction electric quantity deviation rate of the distributed photovoltaic aggregators in the transaction time period T is obtained;
Figure BDA00031142397400000611
the local or nearby consumption rate of the photovoltaic in the transaction period T is given to the distributed photovoltaic aggregators;
in step S6, the node voltage may have an out-of-limit condition along with the power loss in the process of transmitting the photovoltaic energy, the grid company serving as the block chain operation and supervision party expects the photovoltaic power to be consumed by the agricultural load at a short distance, and the agricultural user i consumes the score r on the spotiThe expression of (b) is shown in formula 9;
Figure BDA00031142397400000612
in the formula, LiThe distance between the agricultural load i and the nearest distributed photovoltaic access point is km, and the distance is obtained according to the position information of the agricultural user and the position information of each distributed photovoltaic access point of the distributed photovoltaic aggregator in the step S1; n is the number of transaction periods within a day;
Figure BDA0003114239740000071
actual electricity consumption of an agricultural user i in a period of time T, namely an agricultural load actual hash value, and the unit is kWh; the local consumption score is proportional to the agricultural load electricity consumption, and the closer to the distributed photovoltaic access point, the higher the evaluation is.
The agricultural user sub-node and the distributed photovoltaic sub-node are respectively provided with an intelligent metering device, the intelligent metering devices are used as edge calculation units, have a power bidirectional metering function, and can read power purchasing and power selling data of the nodes; the edge computing unit disperses a traditional server centralized computing task to edge nodes of a block chain system network, each node can collect operation data of distributed photovoltaic and loads in real time, data storage and computation are carried out according to requirements, and results are uploaded to the block chain system.
The architecture of the edge compute unit is divided into three levels: cloud layer, edge layer and end layer; the cloud layer is a cloud computing center and is responsible for issuing computing tasks to the edge layer, and the cloud layer is matched with the edge layer in a coordinated mode; the edge layer is a core part of an edge computing network and consists of an edge unit, an edge computing platform and edge computing software; the end layer is composed of various terminal devices, including distributed photovoltaic and various loads, and is responsible for providing field data for the edge computing unit.
Each node in the block chain system adopts a point-to-point P2P networking mode, transmits information through a network communication protocol and verifies the information.
In step S1, the agricultural user sub-node is compared with the existing rural power distribution network rack topology, and if the agricultural user sub-node is not consistent with the existing rural power distribution network rack topology, the agricultural user sub-node is verified and calibrated.
Preferably, step S2 is performed 60 minutes before the transaction.
The method further comprises:
s7, updating the credit value of the distributed photovoltaic aggregator once a day, and for photovoltaic power which cannot be consumed by the distributed photovoltaic aggregator on site or nearby, charging a certain amount of net charge by the power grid company, wherein the higher the credit value is, the lower the net charge charged by unit electric quantity is; the credit mechanism changes the benefit function of the distributed photovoltaic aggregator that photovoltaic power excess cannot be absorbed at the current voltage level, as shown in equation 10:
Figure BDA0003114239740000081
in the formula 10, AsThe unit is element for the benefit of the distributed photovoltaic aggregator; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the voltage level, and the unit is element;
Figure BDA0003114239740000082
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure BDA0003114239740000083
the total electricity consumption of the agricultural users in the block chain in the time period T is represented in kWh; gamma is a coefficient of the network cost, and the relation between gamma and the credit value R of the distributed photovoltaic aggregator is shown as formula 11:
Figure BDA0003114239740000084
in order to ensure that the photovoltaic output can be consumed to the maximum extent, the power grid company gives additional electricity price subsidies to agricultural users with higher local consumption scores, and the benefit function of the agricultural users changes, as shown in formula 12;
Figure BDA0003114239740000085
in the formula, AiThe unit is element for the benefit of the agricultural user i; k is a radical ofiA benefit parameter for agricultural user i;
Figure BDA0003114239740000086
the electricity consumption of the agricultural user i in a period of time T is represented by kWh; p is a radical ofsThe unit is element for internal transaction electricity price; mu.si TAdditional subsidizing of the electrovalence coefficient, μ, for time period Ti TThe relation with the local consumption score of the agricultural user is shown as a formula 13;
Figure BDA0003114239740000087
in the formula, riScoring an agricultural user i for local consumption;
the setting of the incentive mechanism influences the benefit functions of both game parties, and finally the optimal internal transaction price p is obtainedsSum optimal power policy xiAs shown in formula 14 and formula 15;
Figure BDA0003114239740000091
Figure BDA0003114239740000092
in the formula, pgsRepresenting the photovoltaic on-line electricity price under the current voltage level, wherein the unit is element; k is a radical ofiA benefit parameter for agricultural user i; mu.si TAdditional subsidizing the electricity price coefficient for time period T; n is the number of agricultural users in the block chain system; gamma is the coefficient of the net cost;
Figure BDA0003114239740000093
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh; p is a radical ofsThe price is the optimal internal transaction price, and the unit is element; x is the number ofiOptimal electricity usage strategy for each agricultural user.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a distributed photovoltaic electric energy consumption method in a rural power distribution network, which integrates a block chain technology and edge calculation into a distributed electric energy trading market, reduces credit cost, and ensures the safety and effective supervision of trading; the game theory method is applied to maximize the benefit, the potential agricultural load in a time period with large solar irradiation intensity is excavated, and photovoltaic on-site or nearby consumption is promoted.
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FIG. 1 is a schematic flow diagram of a distributed photovoltaic power consumption method in a rural power distribution network of the present invention;
FIG. 2 is a block content and structure diagram of a blockchain system;
FIG. 3 is a block chain system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of photovoltaic trade internal trade electricity price provided by an embodiment of the invention;
FIG. 5 is a schematic diagram showing a comparison of photovoltaic absorption before and after the method is used;
FIG. 6 is a schematic diagram of agricultural user profits provided by an embodiment of the present invention;
fig. 7 is a schematic diagram of revenue of a distributed photovoltaic aggregator provided by an embodiment of the invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
As shown in fig. 1, a distributed photovoltaic power consumption method in a rural power distribution network includes the following steps:
s1, establishing a blockchain system, registering the agricultural user with transaction qualification and the distributed photovoltaic aggregators in the blockchain system, and uploading the position information of the agricultural user, the position information of each distributed photovoltaic access point of the distributed photovoltaic aggregators and the installed capacity to the blockchain system;
as shown in fig. 2, the blockchain system includes a plurality of blocks generated by agricultural users and distributed photovoltaic aggregators upon completion of a photovoltaic power transaction; each block comprises a block head and a block body;
the block head comprises a hash value, a time stamp and a Mercker root of a previous block; wherein the time stamp records a generation time of the block; the hash value of the previous block is used as an identification code, so that each block has traceability, and a complete transaction chain is formed; the merkel root is a root node of a block body.
The block body adopts a structure of a Mercker tree, and a root node is arranged in a block head and comprises a distributed photovoltaic sub-node, an agricultural user sub-node and a photovoltaic absorption information node; the distributed photovoltaic sub-nodes comprise photovoltaic predicted output hash values and photovoltaic actual output hash values; the agricultural user child node comprises an agricultural load prediction hash value and an agricultural load actual hash value; the photovoltaic consumption information node comprises a photovoltaic consumption electric quantity hash value and a large power grid balance electric quantity hash value.
The chain structure enables the transaction information not to be tampered, the data safety is improved by using the Hash encryption algorithm, and each node can trace any transaction information through the chain structure.
As shown in fig. 3, the blockchain system allows a distributed photovoltaic aggregator and an agricultural user to join as nodes, where the distributed photovoltaic aggregator includes one or more distributed photovoltaic sub-nodes and an agricultural user serves as an agricultural user sub-node; the large power grid (power grid company) is used as a photovoltaic consumption information node and is responsible for transmitting electric energy, supervising photovoltaic electric energy transaction and balancing deviation electric quantity.
The agricultural user sub-node and the distributed photovoltaic sub-node are respectively provided with an intelligent metering device, the intelligent metering devices are used as edge calculation units, have a power bidirectional metering function, and can read power purchasing and power selling data of the nodes. The edge computing unit disperses a traditional server centralized computing task to edge nodes of the block chain system network, each node can collect operation data of distributed photovoltaic and loads in real time, data storage and computation are carried out according to requirements, and results are uploaded to the block chain system.
The architecture of the edge compute unit is divided into three levels: cloud layer, edge layer and end layer; the cloud layer is a cloud computing center and is responsible for issuing computing tasks to the edge layer, and the cloud layer is matched with the edge layer in a coordinated mode; the edge layer is a core part of an edge computing network and consists of an edge unit, an edge computing platform and edge computing software; the end layer is composed of various terminal devices, including distributed photovoltaic and various loads, and is responsible for providing field data for the edge computing unit.
Each node in the blockchain system adopts a peer-to-peer (P2P) networking mode, transmits information through a network communication protocol and verifies the information.
As shown in fig. 3, electric energy as a special commodity has a certain time sequence, electric energy transmission and transactions between nodes belong to two networks, namely power flow and information flow, a blockchain system cannot be independent from unified scheduling of a large power grid, the large power grid cannot directly interfere transactions in the blockchain system, account addresses of all nodes are stored, energy consumption and transaction conditions of each node can be analyzed in real time, electric energy economic scheduling is facilitated, and photovoltaic local consumption is promoted.
Preferably, in step S1, the agricultural user sub-node is compared with the existing rural power distribution network rack topology, and if the agricultural user sub-node is not consistent with the existing rural power distribution network rack topology, the agricultural user sub-node is verified and calibrated.
S2, at a certain time before trading, the distributed photovoltaic aggregators in the block chain system obtain photovoltaic peak power according to the installed capacity of the distributed photovoltaic aggregators in the step S1, and then obtain the predicted photovoltaic power generation power in the trading period according to the photovoltaic peak power; an agricultural user issues a power purchase request;
preferably, step S2 is performed 60 minutes before the transaction, too early to affect the accuracy of the prediction, and too late to leave sufficient preparation time for the transaction.
The existing mature photovoltaic power prediction method is adopted, for example, a neural network is trained according to massive weather data and photovoltaic operation data to perform short-term prediction, and the predicted photovoltaic power generation power in the transaction period is obtained.
S3, respectively establishing benefit functions of agricultural users and benefit functions of distributed photovoltaic aggregators by the blockchain system, and calculating a balanced solution of a master-slave game model through a master-slave game method, namely obtaining an optimal internal trading electricity price psOptimal electricity utilization strategy x for and each agricultural useri*。
S3.1, the benefit function of the agricultural user established by the block chain system is shown as the formula 1:
Figure BDA0003114239740000121
in the formula 1, AiThe unit is element for the benefit of the agricultural user i; k is a radical ofiA benefit parameter for agricultural user i;
Figure BDA0003114239740000122
the electricity consumption of the agricultural user i in a period of time T is represented by kWh; p is a radical ofsThe unit is element for internal transaction electricity price. p is a radical ofsIs not lowThe price of the power on the internet is not higher than that of the power sold by the power grid, otherwise the distributed photovoltaic aggregators and agricultural users tend to trade with the large power grid directly. The online electricity price is the electricity price for electricity purchased by the large power grid to the distributed photovoltaic aggregation suppliers, and the electricity selling price is the electricity price for electricity sold by the large power grid to agricultural users.
The benefit function of the distributed photovoltaic aggregator established by the block chain system is shown as formula 2:
Figure BDA0003114239740000123
in the formula 2, AsThe unit is element for the benefit of the distributed photovoltaic aggregator;
Figure BDA0003114239740000124
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure BDA0003114239740000125
the total electricity consumption of the agricultural users in the block chain in the time period T is represented in kWh; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the current voltage level, wherein the unit is element; p is a radical ofgbThe unit of the electricity selling price of the power grid under the current voltage level is element; σ is a constant value set to 0.01.
S3.2, constructing a master-slave game model G, wherein the master-slave game model G is shown as a formula 3:
Figure BDA0003114239740000131
in equation 3, distributed photovoltaic aggregation quotient N within the blockchain systemSAs a leader, a set of agricultural users N within a blockchainBAs a follower;
Figure BDA0003114239740000132
electricity consumption for agricultural user i within time T
Figure BDA0003114239740000133
A selection set of (a); p is the internal trade price P of the blockchainsThe set of policies of (2); a. theiBenefits for agricultural users i; a. thesIs the benefit of the distributed photovoltaic aggregator.
To achieve nash equilibrium in the master-slave game model G, all participants need to obtain optimal values under the conditions, namely the distributed photovoltaic aggregator has the maximum benefit and the agricultural user group has the maximum benefit, equilibrium solutions of the master-slave game model are obtained through calculation of a formula 4 and a formula 5 respectively, namely the distributed photovoltaic aggregator finds the optimal internal trading electricity price psMake it have the benefit AsMaximally, each agricultural user finds the optimal power utilization strategy xiThereby achieving maximum gain.
Figure BDA0003114239740000134
Figure BDA0003114239740000135
In the formulas 4 and 5, N is the number of agricultural users in the block chain system; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the voltage level, and the unit is element; k is a radical ofiA benefit parameter for agricultural user i; p is a radical ofsThe price is the optimal internal transaction price, and the unit is element; x is the number ofiOptimal electricity usage strategy for each agricultural user.
S4, the intelligent contract module in the blockchain system acquires the optimal electricity utilization strategy x of the agricultural user according to the electricity purchase request issued by the agricultural user in the step S1, the predicted photovoltaic power generation power of the distributed photovoltaic aggregators in the step S2 and the optimal electricity utilization strategy x of the agricultural user acquired in the step S3iAutomatically generating a trade contract; the predicted photovoltaic power generation power is a photovoltaic predicted output hash value; the optimal power utilization strategy xiThe hash value is the agricultural load prediction hash value; if the predicted photovoltaic power generation power cannot meet the optimal power utilization strategy xiTime, the predicted additional power delivered by the large grid is balanced.
S5, according to the trade contract, the distributed photovoltaic aggregators enable the photovoltaic power generation power to be at the internal trade price psSelling to nearby agricultural users in the block chain system, and enabling the agricultural users to follow the optimal electricity utilization strategy xiElectricity usage; in the process, when the photovoltaic power generation power is excessive and cannot be absorbed at the current voltage level, the redundant photovoltaic power generation power is equal to the internet price pgsSelling to a large power grid; when the photovoltaic power generation power cannot meet the power utilization requirement (agricultural load) of an agricultural user, namely the net load power is larger than zero, the large power grid transmits actual extra power to the agricultural user in the block chain system; the load net power is the hash value of the photovoltaic absorption electric quantity and is equal to the difference value of the actual hash value of the agricultural load and the actual hash value of the photovoltaic output; the difference value of the actual extra power transmitted by the large power grid and the predicted extra power transmitted by the large power grid is the hash value of the balance electric quantity of the large power grid; and after the transaction contract is fulfilled, the distributed photovoltaic sub-nodes of the distributed photovoltaic aggregators and the agricultural user sub-nodes jointly generate blocks.
And S6, after the transaction time period is over, the intelligent metering devices of the agricultural users serve as edge calculation units to feed back actual power utilization conditions to the blockchain system, the intelligent contracts complete transfer of transaction funds, and the blockchain system calculates credit values of the distributed photovoltaic aggregators and local consumption scores of the agricultural users according to the transaction conditions.
In step S6, the reputation value of the distributed photovoltaic aggregator includes two parts: the photovoltaic electric quantity deviation rate and the photovoltaic local or nearby consumption rate are shown as formulas 6 and 7:
Figure BDA0003114239740000141
Figure BDA0003114239740000142
in the formula (I), the compound is shown in the specification,
Figure BDA0003114239740000143
represents a scoreThe actual total electric quantity sent by the distributed photovoltaic aggregator within the time T, namely the actual photovoltaic output hash value, is expressed in kWh;
Figure BDA0003114239740000144
the predicted total electric quantity emitted by the distributed photovoltaic aggregator in time T, namely the photovoltaic predicted output hash value, is expressed in kWh,
Figure BDA0003114239740000151
Figure BDA0003114239740000152
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure BDA0003114239740000153
represents the power consumption of all agricultural users in kWh within the time T;
Figure BDA0003114239740000154
the photovoltaic transaction electric quantity deviation rate of the distributed photovoltaic aggregators in the transaction time period T is obtained;
Figure BDA0003114239740000155
and (4) the local or nearby consumption rate of the photovoltaic in the transaction period T is provided for the distributed photovoltaic aggregators.
Figure BDA0003114239740000156
Reflects the enthusiasm of agricultural users in power consumption from the side,
Figure BDA0003114239740000157
smaller indicates that the user consumes more energy during the time period, and can facilitate photovoltaic consumption on-site or nearby when photovoltaic power is excessive.
In summary, the reputation value R of the distributed photovoltaic aggregator is shown in formula 8.
Figure BDA0003114239740000158
Wherein n is the number of transaction sessions within a day; alpha is alpha1And beta1The weight of the two indexes respectively represents the importance degree of the photovoltaic electric quantity deviation rate of the node and the photovoltaic grounding or nearby consumption rate, and the method uses alpha1Is set to 0.3, beta1Set to 0.7.
Figure BDA0003114239740000159
The photovoltaic transaction electric quantity deviation rate of the distributed photovoltaic aggregators in the transaction time period T is obtained;
Figure BDA00031142397400001510
and (4) the local or nearby consumption rate of the photovoltaic in the transaction period T is provided for the distributed photovoltaic aggregators.
In step S6, the node voltage may have an out-of-limit condition along with the power loss in the process of transmitting the photovoltaic energy, the grid company serving as the block chain operation and supervision party expects the photovoltaic power to be consumed by the agricultural load at a short distance, and the agricultural user i consumes the score r on the spotiIs represented by formula 9.
Figure BDA00031142397400001511
In the formula, LiThe distance between the agricultural load i and the nearest distributed photovoltaic access point is km, and the distance is obtained according to the position information of the agricultural user and the position information of each distributed photovoltaic access point of the distributed photovoltaic aggregator in the step S1. n is the number of transaction periods within a day;
Figure BDA00031142397400001512
actual electricity consumption of an agricultural user i in a period of time T, namely an agricultural load actual hash value, and the unit is kWh; the local consumption score is proportional to the agricultural load electricity consumption, and the closer to the distributed photovoltaic access point, the higher the evaluation is.
S7, updating the credit value of the distributed photovoltaic aggregator once a day, and for photovoltaic power which cannot be consumed by the distributed photovoltaic aggregator on site or nearby, charging a certain amount of net charge by the power grid company, wherein the higher the credit value is, the lower the net charge is charged by the unit electric quantity. The credit mechanism changes the benefit function of the distributed photovoltaic aggregator that photovoltaic power excess cannot be absorbed at the current voltage level, as shown in equation 10:
Figure BDA0003114239740000161
in the formula 10, AsThe unit is element for the benefit of the distributed photovoltaic aggregator; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the voltage level, and the unit is element;
Figure BDA0003114239740000162
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure BDA0003114239740000163
the total electricity consumption of the agricultural users in the block chain in the time period T is represented in kWh; gamma is
Figure BDA0003114239740000164
Figure BDA0003114239740000165
In order to ensure that the photovoltaic output can be maximally absorbed, the power grid company will provide additional subsidies of electricity prices for agricultural users with higher local absorption scores, and the benefit function of the agricultural users will change, as shown in formula 12.
Figure BDA0003114239740000166
In the formula, AiThe unit is element for the benefit of the agricultural user i; k is a radical ofiA benefit parameter for agricultural user i;
Figure BDA0003114239740000167
the electricity consumption of the agricultural user i in a period of time T is represented by kWh; p is a radical ofsThe unit is element for internal transaction electricity price; mu.si TAdditional subsidizing of the electrovalence coefficient, μ, for time period Ti TThe relationship with the on-site consumption score of the agricultural user is shown in formula 13. The agricultural user with higher consumption on the spot score is given extra electricity price subsidies, so that the user enthusiasm is improved, and the photovoltaic consumption on the spot is promoted.
Figure BDA0003114239740000171
In the formula, riScoring an agricultural user i for local consumption;
the setting of the incentive mechanism influences the benefit functions of both game parties, and finally the optimal internal transaction price p is obtainedsSum optimal power policy xiAs shown in formula 14 and formula 15.
Figure BDA0003114239740000172
Figure BDA0003114239740000173
In the formula, pgsRepresenting the photovoltaic on-line electricity price under the current voltage level, wherein the unit is element; k is a radical ofiA benefit parameter for agricultural user i; mu.si TAdditional subsidizing the electricity price coefficient for time period T; n is the number of agricultural users in the block chain system; gamma is the coefficient of the net cost;
Figure BDA0003114239740000174
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh; p is a radical ofsThe price is the optimal internal transaction price, and the unit is element; x is the number ofiOptimal electricity usage strategy for each agricultural user.
Taking the IEEE 33 node medium voltage distribution network model as an example, the total load of the region is 3.715+ j0.950mva, and the reference value of the voltage is 12.66 kV. Only the transaction behaviors of the agricultural users and the distributed photovoltaic aggregators in the time period of the photovoltaic power generation power are researched, and the users purchase power according to the power price of the power grid company in other time periods. Taking a typical winter day as an example, the photovoltaic power generation time period is 7:00-17:00 for 10 hours, which is divided according to the peak-valley electricity price of a certain northern city, the power prices of 7:00-10:00 and 15:00-17:00 are flat sections, the power price of 10:00-15:00 is a peak period, the power price of the medium-pressure peak period is 0.9042 yuan/kWh, the power price of the flat section is 0.6005 yuan/kWh, and the power price of the distributed photovoltaic on-grid is 0.45 yuan/kWh.
And in the whole photovoltaic transaction process, the internal transaction electricity price of all the time periods is between the photovoltaic on-grid electricity price and the grid electricity selling price, so that the method accords with the basic benefits of agricultural users and distributed photovoltaic aggregators. It can be seen that, in a period of time when the photovoltaic power generation power is large, the distributed photovoltaic aggregators reduce the internal transaction electricity price, so that agricultural users consume more electric energy, and further increase the income by increasing the electricity selling cost. However, the power consumption of agricultural users is limited, and the overall benefit is reduced by excessively reducing the electricity selling price.
The photovoltaic electric energy consumption method affects the overall photovoltaic consumption situation in the power distribution network, and the photovoltaic consumption situations before and after the consumption method are compared, as shown in fig. 5. Before the method is adopted, the power returned by the medium-voltage distribution network to the upper-level power grid reaches a maximum value 445kW at 14:00, and the total electric quantity is not consumed 2703kWh in 10:00-15:00 time period; after the method is adopted, the power reversing situation is obviously improved, the maximum unconsumed power in one day is reduced to 144kW, the unconsumed photovoltaic electric quantity is reduced to 703kWh, and the local consumption degree is greatly improved.
Fig. 6 and 7 show the profit of both parties of the transaction before and after the method of the present invention is used. Before the adoption of the absorption method, in a period of time when the photovoltaic power generation power is large, the phenomenon of light abandon occurs, and a photovoltaic aggregator loses a part of electricity selling cost; after the consumption method is adopted, the photovoltaic aggregator can independently make a trading power price in the block chain, the profit of photovoltaic electric energy sold in the block chain system is increased, the photovoltaic electric energy sent back to the upper-level power grid is sold according to the photovoltaic on-line power price, and a certain net-passing fee is charged. In a general view, the income of the photovoltaic aggregator is obviously increased after the trading model is adopted.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (7)

1. A distributed photovoltaic electric energy consumption method in a rural power distribution network is characterized by comprising the following steps:
s1, establishing a blockchain system, registering the agricultural user with transaction qualification and the distributed photovoltaic aggregators in the blockchain system, and uploading the position information of the agricultural user, the position information of each distributed photovoltaic access point of the distributed photovoltaic aggregators and the installed capacity to the blockchain system;
the block chain system comprises a plurality of blocks generated by agricultural users and distributed photovoltaic aggregators after completing photovoltaic electric energy transactions; each block comprises a block head and a block body;
the block head comprises a hash value, a time stamp and a Mercker root of a previous block; wherein the time stamp records a generation time of the block; the hash value of the previous block is used as an identification code, so that each block has traceability, and a complete transaction chain is formed; the Mercker root is a root node of a block body;
the block body adopts a structure of a Mercker tree, and a root node is arranged in a block head and comprises a distributed photovoltaic sub-node, an agricultural user sub-node and a photovoltaic absorption information node; the distributed photovoltaic sub-nodes comprise photovoltaic predicted output hash values and photovoltaic actual output hash values; the agricultural user child node comprises an agricultural load prediction hash value and an agricultural load actual hash value; the photovoltaic consumption information node comprises a photovoltaic consumption electric quantity hash value and a large power grid balance electric quantity hash value;
the block chain system allows distributed photovoltaic aggregators and agricultural users to join as nodes, the distributed photovoltaic aggregators comprise one or more distributed photovoltaic sub-nodes, and one agricultural user serves as one agricultural user sub-node; the large power grid is used as a photovoltaic consumption information node and is responsible for transmitting electric energy, supervising photovoltaic electric energy transaction and balancing deviation electric quantity;
s2, at a certain time before trading, the distributed photovoltaic aggregators in the block chain system obtain photovoltaic peak power according to the installed capacity of the distributed photovoltaic aggregators in the step S1, and then obtain the predicted photovoltaic power generation power in the trading period according to the photovoltaic peak power; an agricultural user issues a power purchase request;
s3, respectively establishing benefit functions of agricultural users and benefit functions of distributed photovoltaic aggregators by the blockchain system, and calculating a balanced solution of a master-slave game model through a master-slave game method, namely obtaining an optimal internal trading electricity price psOptimal electricity utilization strategy x for and each agricultural useri*；
S3.1, the benefit function of the agricultural user established by the block chain system is shown as the formula 1:
Figure FDA0003114239730000021
in the formula 1, AiThe unit is element for the benefit of the agricultural user i; k is a radical ofiA benefit parameter for agricultural user i;
Figure FDA0003114239730000022
the electricity consumption of the agricultural user i in a period of time T is represented by kWh; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofsThe price of the power is not lower than the price of the power on the internet and is not higher than the price of the power sold by the power grid; the online electricity price is the electricity price for electricity purchased by the large power grid to the distributed photovoltaic aggregation provider, and the electricity selling price is the electricity price for electricity sold by the large power grid to the agricultural user;
the benefit function of the distributed photovoltaic aggregator established by the block chain system is shown as formula 2:
Figure FDA0003114239730000023
in the formula 2, AsThe unit is element for the benefit of the distributed photovoltaic aggregator;
Figure FDA0003114239730000024
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure FDA0003114239730000025
the total electricity consumption of the agricultural users in the block chain in the time period T is represented in kWh; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the current voltage level, wherein the unit is element; p is a radical ofgbThe unit of the electricity selling price of the power grid under the current voltage level is element; σ is a constant value set to 0.01;
s3.2, constructing a master-slave game model G, wherein the master-slave game model G is shown as a formula 3:
Figure FDA0003114239730000026
in equation 3, distributed photovoltaic aggregation quotient N within the blockchain systemSAs a leader, a set of agricultural users N within a blockchainBAs a follower;
Figure FDA0003114239730000027
electricity consumption for agricultural user i within time T
Figure FDA0003114239730000031
A selection set of (a); p is the internal trade price P of the blockchainsThe set of policies of (2); a. theiBenefits for agricultural users i; a. thesBenefits for distributed photovoltaic aggregators;
to achieve nash equilibrium in the master-slave game model G, all participants need to obtain optimal values under the conditions, namely the distributed photovoltaic aggregator has the maximum benefit and the agricultural user group has the maximum benefit, equilibrium solutions of the master-slave game model are obtained through calculation of a formula 4 and a formula 5 respectively, namely the distributed photovoltaic aggregator finds the optimal internal trading electricity price psMake it have the benefit AsMaximally, each agricultural user finds the optimal power utilization strategy xiThereby achieving maximum revenue;
Figure FDA0003114239730000032
Figure FDA0003114239730000033
in the formulas 4 and 5, N is the number of agricultural users in the block chain system; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the voltage level, and the unit is element; k is a radical ofiA benefit parameter for agricultural user i; p is a radical ofsThe price is the optimal internal transaction price, and the unit is element; x is the number ofiAn optimal electricity usage strategy for each agricultural user;
s4, the intelligent contract module in the blockchain system acquires the optimal electricity utilization strategy x of the agricultural user according to the electricity purchase request issued by the agricultural user in the step S1, the predicted photovoltaic power generation power of the distributed photovoltaic aggregators in the step S2 and the optimal electricity utilization strategy x of the agricultural user acquired in the step S3iAutomatically generating a trade contract; the predicted photovoltaic power generation power is a photovoltaic predicted output hash value; the optimal power utilization strategy xiThe hash value is the agricultural load prediction hash value; if the predicted photovoltaic power generation power cannot meet the optimal power utilization strategy xiTime, the predicted additional power delivered by the large power grid is balanced;
s5, according to the trade contract, the distributed photovoltaic aggregators enable the photovoltaic power generation power to be at the internal trade price psSold to nearby agricultural users within the blockchain system, according to the topOptimal power utilization strategy xiElectricity usage; in the process, when the photovoltaic power generation power is excessive and cannot be absorbed at the current voltage level, the redundant photovoltaic power generation power is equal to the internet price pgsSelling to a large power grid; when the photovoltaic power generation power cannot meet the power utilization requirement of the agricultural users, namely the load net power is larger than zero, the large power grid transmits the actual extra power to the agricultural users in the block chain system; the load net power is the hash value of the photovoltaic absorption electric quantity and is equal to the difference value of the actual hash value of the agricultural load and the actual hash value of the photovoltaic output; the difference value of the actual extra power transmitted by the large power grid and the predicted extra power transmitted by the large power grid is the hash value of the balance electric quantity of the large power grid; after the transaction contract is fulfilled, the distributed photovoltaic sub-nodes of the distributed photovoltaic aggregators and the agricultural user sub-nodes jointly generate blocks;
s6, after the transaction time period is over, the intelligent metering devices of the agricultural users serve as edge calculation units to feed back actual power utilization conditions to the blockchain system, the intelligent contracts complete transfer of transaction funds, and the blockchain system calculates credit values of the distributed photovoltaic aggregators and local consumption scores of the agricultural users according to the transaction conditions;
in step S6, the reputation value of the distributed photovoltaic aggregator includes two parts: the photovoltaic electric quantity deviation rate and the photovoltaic local or nearby consumption rate are shown as formulas 6 and 7:
Figure FDA0003114239730000041
Figure FDA0003114239730000042
in the formula (I), the compound is shown in the specification,
Figure FDA0003114239730000043
representing the actual total electric quantity sent by the distributed photovoltaic aggregator within the time T, namely the actual photovoltaic output hash value with the unit of kWh;
Figure FDA0003114239730000044
the predicted total electric quantity emitted by the distributed photovoltaic aggregator in time T, namely the photovoltaic predicted output hash value, is expressed in kWh,
Figure FDA0003114239730000045
Figure FDA0003114239730000046
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure FDA0003114239730000047
represents the power consumption of all agricultural users in kWh within the time T;
Figure FDA0003114239730000048
the photovoltaic transaction electric quantity deviation rate of the distributed photovoltaic aggregators in the transaction time period T is obtained;
Figure FDA0003114239730000049
the local or nearby consumption rate of the photovoltaic in the transaction period T is given to the distributed photovoltaic aggregators;
Figure FDA00031142397300000410
reflects the enthusiasm of agricultural users in power consumption from the side,
Figure FDA00031142397300000411
the smaller the photovoltaic power is, the more energy consumed by a user in the time period is indicated, and the photovoltaic power can be promoted to be consumed locally or nearby when the photovoltaic power is excessive;
the credit value R of the distributed photovoltaic aggregators is shown as a formula 8;
Figure FDA0003114239730000051
wherein n is within one dayThe number of transaction periods; alpha is alpha1And beta1The weight of the two indexes respectively represents the importance degree of the photovoltaic electric quantity deviation rate of the node and the photovoltaic grounding or nearby consumption rate, and the method uses alpha1Is set to 0.3, beta1Set to 0.7;
Figure FDA0003114239730000052
the photovoltaic transaction electric quantity deviation rate of the distributed photovoltaic aggregators in the transaction time period T is obtained;
Figure FDA0003114239730000053
the local or nearby consumption rate of the photovoltaic in the transaction period T is given to the distributed photovoltaic aggregators;
in step S6, the agricultural user i consumes the score r on the spotiThe expression of (b) is shown in formula 9;
Figure FDA0003114239730000054
in the formula, LiThe distance between the agricultural load i and the nearest distributed photovoltaic access point is km, and the distance is obtained according to the position information of the agricultural user and the position information of each distributed photovoltaic access point of the distributed photovoltaic aggregator in the step S1; n is the number of transaction periods within a day;
Figure FDA0003114239730000055
actual electricity consumption of an agricultural user i in a period of time T, namely an agricultural load actual hash value, and the unit is kWh; the local consumption score is proportional to the agricultural load electricity consumption, and the closer to the distributed photovoltaic access point, the higher the evaluation is.
2. The distributed photovoltaic electric energy consumption method in the rural power distribution network according to claim 1, wherein the agricultural user sub-node and the distributed photovoltaic sub-node are respectively provided with an intelligent metering device, and the intelligent metering devices are used as edge calculation units, have a power bidirectional metering function, and can read the electricity purchasing and electricity selling data of the nodes; the edge computing unit disperses a traditional server centralized computing task to edge nodes of a block chain system network, each node can collect operation data of distributed photovoltaic and loads in real time, data storage and computation are carried out according to requirements, and results are uploaded to the block chain system.
3. The method of claim 1, wherein the architecture of the edge computing unit is divided into three levels: cloud layer, edge layer and end layer; the cloud layer is a cloud computing center and is responsible for issuing computing tasks to the edge layer, and the cloud layer is matched with the edge layer in a coordinated mode; the edge layer is a core part of an edge computing network and consists of an edge unit, an edge computing platform and edge computing software; the end layer is composed of various terminal devices, including distributed photovoltaic and various loads, and is responsible for providing field data for the edge computing unit.
4. The method for consuming distributed photovoltaic power in a rural power distribution network according to claim 1, wherein each node in the blockchain system transmits information and verifies the information through a network communication protocol in a point-to-point P2P networking mode.
5. The method for distributed photovoltaic power consumption in rural power distribution networks according to claim 1, wherein in step S1, the agricultural user sub-nodes are compared with the existing rural power distribution network grid topology, and if the agricultural user sub-nodes are not consistent with the existing rural power distribution network grid topology, the agricultural user sub-nodes are verified and calibrated.
6. The method for distributed photovoltaic power consumption in rural power distribution networks according to claim 1, wherein step S2 is performed 60 minutes before the transaction.
7. The method for distributed photovoltaic power consumption in a rural power distribution network according to any of claims 1-6, wherein the method further comprises:
s7, updating the credit value of the distributed photovoltaic aggregator once a day, and for photovoltaic power which cannot be consumed by the distributed photovoltaic aggregator on site or nearby, charging a certain amount of net charge by the power grid company, wherein the higher the credit value is, the lower the net charge charged by unit electric quantity is; the credit mechanism changes the benefit function of the distributed photovoltaic aggregator that photovoltaic power excess cannot be absorbed at the current voltage level, as shown in equation 10:
Figure FDA0003114239730000071
in the formula 10, AsThe unit is element for the benefit of the distributed photovoltaic aggregator; p is a radical ofsThe unit is element for internal transaction electricity price; p is a radical ofgsRepresenting the photovoltaic on-line electricity price under the voltage level, and the unit is element;
Figure FDA0003114239730000072
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh;
Figure FDA0003114239730000073
the total electricity consumption of the agricultural users in the block chain in the time period T is represented in kWh; gamma is a coefficient of the network cost, and the relation between gamma and the credit value R of the distributed photovoltaic aggregator is shown as formula 11:
Figure FDA0003114239730000074
the benefit function of the agricultural user also changes, as shown in equation 12;
Figure FDA0003114239730000075
in the formula, AiBenefits for agricultural user iThe unit is element; k is a radical ofiA benefit parameter for agricultural user i;
Figure FDA0003114239730000076
the electricity consumption of the agricultural user i in a period of time T is represented by kWh; p is a radical ofsThe unit is element for internal transaction electricity price; mu.si TAdditional subsidizing of the electrovalence coefficient, μ, for time period Ti TThe relation with the local consumption score of the agricultural user is shown as a formula 13;
Figure FDA0003114239730000077
in the formula, riScoring an agricultural user i for local consumption;
the setting of the incentive mechanism influences the benefit functions of both game parties, and finally the optimal internal transaction price p is obtainedsSum optimal power policy xiAs shown in formula 14 and formula 15;
Figure FDA0003114239730000078
Figure FDA0003114239730000081
in the formula, pgsRepresenting the photovoltaic on-line electricity price under the current voltage level, wherein the unit is element; k is a radical ofiA benefit parameter for agricultural user i; mu.si TAdditional subsidizing the electricity price coefficient for time period T; n is the number of agricultural users in the block chain system; gamma is the coefficient of the net cost;
Figure FDA0003114239730000082
representing the total power generation of a photovoltaic aggregation quotient in a block chain in a time interval T, wherein the unit is kWh; p is a radical ofsThe price is the optimal internal transaction price, and the unit is element; x is the number ofiOptimal electricity usage strategy for each agricultural user.
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