1. A source network load storage interaction promotion clean energy consumption method based on a car pooling algorithm is characterized by comprising the following steps: the method comprises the following steps:

1) constructing a source network load storage transaction management framework based on a point-to-point mode;

2) constructing a source network load storage transaction management mode based on a point-to-point mode;

3) forming a source network load storage market trading architecture based on a car pooling algorithm;

4) and constructing a car-sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism.

2. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 1, wherein: the specific method of the step 1) comprises the following steps: a source network load storage transaction and management framework based on point-to-point transaction is constructed, and the source network load storage transaction and management framework mainly comprises three main factors, namely: distributed energy nodes, source network storage aggregators and smart meters.

3. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 2, wherein: the distributed energy nodes comprise photovoltaic power stations, gas turbines, electric vehicles, energy storage systems and flexible load distributed energy which are aggregated through advanced information technology and software systems, each distributed energy and load have the characteristic of decentralized autonomy and can be regarded as energy nodes which are divided into 3 types, namely energy purchasing nodes, energy selling nodes and idle nodes, wherein the idle nodes refer to nodes which do not participate in energy transaction in the current transaction period.

4. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 2, wherein: the source network charge storage aggregator, namely a control center of a source network charge storage operator, can provide information consultation, transaction management and wireless communication service for each distributed energy node in source network charge storage, and comprises three main parts, namely a transaction processing center, an account storage center and a transaction record storage center.

5. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 2, wherein: the intelligent electric meter aims at realizing information transmission between the distributed energy nodes and the source network charge storage aggregator, the intelligent electric meters are required to be installed on all the distributed energy nodes, the functions of calculating and recording electric power transaction amount in real time are achieved, and meanwhile the distributed energy nodes can pay and collect encrypted digital currency according to the transaction records of the intelligent electric meters.

6. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 1, wherein: the specific method of the step 2) comprises the following steps: the source network charge storage trading and management mode based on point-to-point trading is characterized in that the consensus process is completed by all distributed energy nodes in the source network charge storage, and the consensus process can be divided into 5 steps which are respectively as follows: energy node authentication, energy optimization scheduling, energy transaction matching, energy transaction settlement and data block generation.

7. The method for facilitating clean energy consumption based on source network charge storage interaction of car pooling according to any one of claims 2 to 6, wherein: the energy node authentication step is that the distributed energy nodes need to be registered at a source network charge storage aggregator before being added into the source network charge storage, the real identity ID, the energy type, the tradable amount and the actual address information of the distributed energy nodes are reported, and the source network charge storage aggregator issues corresponding public and private key pairs and digital wallet addresses to each distributed energy node through an asymmetric encryption technology after auditing and stores the public and private key pairs and the digital wallet addresses in an account storage center.

8. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 6, wherein: and the energy optimization scheduling step is that after the energy trading role is determined, the source network load storage aggregator performs optimization scheduling by taking the maximum accumulated profit as a target according to the energy information of each distributed energy node to obtain the day-ahead planned output of each distributed energy node, and sends the day-ahead planned output to each distributed energy node.

9. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 6, wherein: the energy transaction matching step is that after the day-ahead optimization scheduling is finished, in order to promote the local consumption of the distributed energy, a point-to-point transaction technology is further adopted in the source network load storage to realize transaction matching between the distributed power supply and the fixed load; after the matching of the transaction is completed, the source network load storage sells the residual electricity to the electricity market, and before the matching of the transaction, the energy purchasing node/energy selling node sends the demand information to the transaction processing center of the source network load storage aggregator, wherein the demand information comprises expected transaction electricity quantity, expected transaction time and expected price information; the source network charge storage aggregator adopts a continuous bidirectional auction mechanism to carry out transaction matching between the energy purchasing node and the energy selling node; after the transaction matching is completed, the energy purchasing node and the energy selling node perform power transmission.

10. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 6, wherein: and the energy transaction settlement step is that after the transaction matching between the distributed energy nodes is completed, the energy purchasing node transfers the energy currency from a digital wallet thereof to a wallet address provided by the energy selling node, and adopts a private key for signature, the energy selling node downloads a public key corresponding to the energy purchasing node from an account storage center of the source network charge storage aggregator, and decrypts the received energy payment information so as to verify that the payment information comes from the corresponding energy purchasing node.

11. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 6, wherein: the data block generation step is that the distributed energy source node which obtains the accounting right broadcasts block information to other nodes of the system, the other nodes continue to broadcast the data block to the other nodes after auditing and signing, each node compares the audit result with the results of the other nodes and replies to the accounting node, if the other nodes reach the same result about the block, the accounting node sends the currently audited data block to all other nodes for storage, and after the work is completed, the block is added into the energy point-to-point transaction according to the time sequence.

12. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 1, wherein: the specific method of the step 3) comprises the following steps: the method is similar to an objective function for maximizing the total platform income in a car pooling algorithm, and forms an objective function and a constraint for optimizing the profit of the source network load storage aggregator.

13. The method for facilitating clean energy consumption based on source network charge storage interaction of car pooling of claim 12, wherein: the source network load storage aggregator trading income and running cost in the market through the source network load storage target function with optimal profitThe source network load is stored in the market, and the trading income is the market trading volume G_p,s,tAnd electricity price lambda_p,tMultiplying the start-stop cost of the gas turbine unit by the start-stop variableAnd start-stop base cost S^GTMultiplication composition, scene probability including photovoltaic output scene probability pi(s) and electricity price sceneThe probability pi (p) T is the total time period number in one day; ns and np are respectively the number of photovoltaic scenes and the number of electricity price scenes:

the operating cost of a gas turbine can be expressed as a piecewise linear function:

wherein a is fixed production cost;is an operating variable of the gas turbine; k is a radical of_jGenerating cost slope for the j section of the gas turbine;is the output of the gas turbine during the period t.

14. The method for facilitating clean energy consumption based on source network charge storage interaction of car pooling of claim 12, wherein: the source network load storage aggregator profit function constraints include gas turbine constraints, energy storage system constraints, electricity market trading volume constraints and power balance constraints:

the gas turbine constraints are:

wherein, g^GT,max、g^GT,minMaximum and minimum output power of the gas turbine, respectively; r is^U、r^DThe upward and downward ramp rates of the gas turbine;the upper limit of the output of the j section of the gas turbine is; t is t^su、t^sdMinimum on-off time of the gas turbine; t is t^{su ,0}、t^sd，0Initial startup and shutdown times of the gas turbine are respectively;

the energy storage system constraints are:

wherein the content of the first and second substances,is the charge capacity of the ESS; eta_c、η_dRespectively the charge-discharge efficiency of the ESS;respectively the charge and discharge capacity of the ESS; s^es,min、S^es,maxRespectively the upper limit and the lower limit of the electric capacity of the ESS; g^esc,max、g^esd,maxThe maximum charge and discharge power of the ESS respectively;

the electric power market trading volume constraint is as follows:

wherein the content of the first and second substances,maximum power purchase and sale stored in DAM for source networkAn amount;

the power balance constraint is:

wherein the content of the first and second substances,output for renewable energy;the load demand in the source network load store.

15. The method for promoting the consumption of clean energy by the interaction of the source network and the storage based on the car sharing algorithm as claimed in claim 1, wherein: the specific method of the step 4) comprises the following steps: in the matching process, after the two transaction parties submit the quotes, the quotes of the buyers are arranged from high to low, and the optimal buying price is the highest quote of the buyers; arranging the offers of the seller from low to high, wherein the optimal selling price is the lowest offer of the seller; and when the optimal buying price is greater than or equal to the optimal selling price, the buyer and the seller reach transaction matching, the actual transaction price is the average value of the quoted prices of the buyer and the seller, and if the transaction matching cannot be completed in the current transaction period, the buyer and the seller need to update the quoted prices according to the optimal buying price/the optimal selling price until the electricity is sold out or the transaction time is cut off.

Background

Renewable energy is considered as an important energy source for replacing traditional energy sources in the future due to good environmental and social benefits and sustainability. The development of renewable energy is one of the important energy strategy choices in all countries of the world. However, the general use cost of renewable energy is high, the scale development of renewable energy is already restricted by the high cost, and a corresponding development policy needs to be made for the sustainable and healthy development of renewable energy. Therefore, the development of renewable energy requires not only resource endowments but also governments to adopt corresponding energy policies to increase the market demand of renewable energy while improving production concentration and production technology level.

Clean energy grid-connected consumption is a systematic project and relates to each link of power production, transmission, consumption and the like and each element of source, grid, load, storage and the like. The clean energy consumption capacity of Jiangsu is comprehensively improved, and matched market transaction mechanism software needs to be continuously optimized and improved while hardware such as a strong smart grid and a ubiquitous power Internet of things of Jiangsu are continuously constructed and perfected. Currently, in the aspects of policy and market mechanism, a marketable mechanism capable of realizing friendly and economic interaction between each element of source, load and storage and a power grid through marketable means is lacked. Innovative research on a marketization mechanism is urgently needed to promote safe, high-quality and economic consumption of clean energy.

Disclosure of Invention

The invention aims to provide a method for promoting the consumption of clean energy by the interaction of source network and storage based on a car-pooling algorithm.

In order to achieve the purpose, the invention provides the following technical scheme: a source network load storage interaction promotion clean energy consumption method based on a car sharing algorithm comprises the following steps:

constructing a source network load storage transaction management framework based on a point-to-point mode;

constructing a source network load storage transaction management mode based on a point-to-point mode;

forming a source network load storage market trading architecture based on a car pooling algorithm;

and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism.

The specific method of the step 1 comprises the following steps: a source network load storage transaction and management framework based on point-to-point transaction is constructed, and the source network load storage transaction and management framework mainly comprises three main factors, namely: the system comprises distributed energy nodes, a source network charge storage aggregator and an intelligent electric meter;

the distributed energy nodes comprise photovoltaic power stations, gas turbines, electric vehicles, energy storage systems and flexible load distributed energy which are aggregated through advanced information technology and software systems, each distributed energy and load have the characteristic of dispersion autonomy and can be regarded as energy nodes which are divided into 3 types, namely energy purchasing nodes, energy selling nodes and idle nodes. The idle node refers to a node which does not participate in energy trading in the current trading period.

The source network charge storage aggregator, namely a control center of a source network charge storage operator, can provide information consultation, transaction management and wireless communication service for each distributed energy node in source network charge storage, and comprises three main parts, namely a transaction processing center, an account storage center and a transaction record storage center.

The intelligent electric meter aims at realizing information transmission between the distributed energy nodes and the source network charge storage aggregator, and each distributed energy node needs to be provided with the intelligent electric meter and has the functions of calculating and recording electric power transaction amount in real time. Meanwhile, the distributed energy nodes can also pay and collect encrypted digital currency according to the transaction records of the intelligent electric meter.

The specific method of the step 2 comprises the following steps: the source network charge storage trading and management mode based on point-to-point trading is characterized in that the consensus process is completed by all distributed energy nodes in the source network charge storage, and the consensus process can be divided into 5 steps which are respectively as follows: energy node authentication, energy optimization scheduling, energy transaction matching, energy transaction settlement and data block generation.

The energy node authentication step is that the distributed energy nodes need to be registered in a source network load storage aggregator before being added into the source network load storage, and information such as real identity ID, energy type, tradable amount, actual address and the like of the distributed energy nodes is reported. And after the source network load storage aggregator is audited, corresponding public and private key pairs and digital wallet addresses are issued to all distributed energy nodes through an asymmetric encryption technology and are stored in an account storage center.

And the energy optimization scheduling step is that after the energy trading role is determined, the source network load storage aggregator performs optimization scheduling by taking the maximum accumulated profit as a target according to the energy information of each distributed energy node to obtain the day-ahead planned output of each distributed energy node, and sends the day-ahead planned output to each distributed energy node.

And the energy transaction matching step is that after the day-ahead optimization scheduling is finished, in order to promote the local consumption of the distributed energy, the transaction matching between the distributed power supply and the fixed load is further realized by adopting a point-to-point transaction technology in the source network load storage. After the trade match is completed, the source grid load stores the remaining electricity for sale to the electricity market. Before the transactions are matched, the energy purchasing node/the energy selling node sends the demand information to a transaction processing center of the source network charge storage aggregator, wherein the demand information comprises information such as expected transaction electric quantity, expected transaction time and expected price quotation. The source network storage aggregator uses a continuous bidirectional auction mechanism to carry out transaction matching between the energy purchasing node and the energy selling node. After the transaction matching is completed, the energy purchasing node and the energy selling node perform power transmission.

And the energy transaction settlement step is that after the transaction matching between the distributed energy nodes is completed, the energy purchasing node transfers the energy currency from the digital wallet to a wallet address provided by the energy selling node and adopts a private key for signature. And the energy selling node downloads the public key corresponding to the energy purchasing node from the account storage center of the source network charge storage aggregator, and decrypts the received energy payment information so as to verify that the payment information comes from the corresponding energy purchasing node.

And the data block generation step comprises the steps that the distributed energy source node which obtains the accounting right broadcasts block information to other nodes of the system, and the other nodes continue to broadcast the data block to other nodes after auditing and signing the data block. Each node compares the audit result with the results of other nodes and replies to the accounting node. If the other nodes agree on the block, the accounting node sends the currently audited data block to all other nodes for storage. After the work is completed, the block is added to the energy point-to-point transaction in time sequence.

The specific method of the step 3 comprises the following steps: the method is similar to an objective function for maximizing the total platform income in a car pooling algorithm, and forms an objective function and a constraint for optimizing the profit of the source network load storage aggregator.

The source network load storage aggregator trading income and running cost in the market through the source network load storage target function with optimal profitAnd the start-stop cost and the scene probability of the gas turbine set. Trading income of source network stored in market through market trading volume G_p,s,tAnd electricity price lambda_p,tAnd (4) multiplying the two components. Gas turbine set start-stop cost is by starting to stop variableAnd start-stop base cost S^GTAnd (4) multiplying the two components. The scene probability comprises a photovoltaic output scene probability pi(s) and a power price scene probability pi (p). T is the total time period number in one day; ns and np are the number of photovoltaic scenes and the number of electricity price scenes respectively：

The operating cost of a gas turbine can be expressed as a piecewise linear function:

wherein a is fixed production cost;is an operating variable of the gas turbine; k is a radical of_jGenerating cost slope for the j section of the gas turbine;is the output of the gas turbine during the period t.

The source network load storage aggregator profit function constraints include gas turbine constraints, energy storage system constraints, electricity market trading volume constraints and power balance constraints:

the gas turbine constraints are:

wherein, g^GT,max、g^GT,minMaximum and minimum output power of the gas turbine, respectively; r is^U、r^DThe upward and downward ramp rates of the gas turbine;the upper limit of the output of the j section of the gas turbine is; t is t^su、t^sdMinimum on-off time of the gas turbine; t is t^su,0、t^sd，0Respectively, the initial on-off time of the gas turbine.

The energy storage system constraints are:

wherein the content of the first and second substances,is the charge capacity of the ESS; eta_c、η_dRespectively the charge-discharge efficiency of the ESS;respectively the charge and discharge capacity of the ESS; s^es,min、S^es,maxRespectively the upper limit and the lower limit of the electric capacity of the ESS; g^esc,max、g^esd,maxRespectively the maximum charge and discharge power of the ESS.

The electric power market trading volume constraint is as follows:

wherein the content of the first and second substances,the maximum purchase and sale electricity quantity stored in the DAM is charged for the source network.

The power balance constraint is:

wherein the content of the first and second substances,output for renewable energy;for load demand in source net load storage。

The specific method of the step 4 comprises the following steps:

in the matching process, after the two transaction parties submit the quotes, the quotes of the buyers are arranged from high to low, and the optimal buying price is the highest quote of the buyers; and arranging the offers of the seller from low to high, wherein the optimal selling price is the lowest offer of the seller. And when the optimal buying price is greater than or equal to the optimal selling price, the buyer and the seller reach transaction matching, and the actual transaction price is the average value of the quoted prices of the buyer and the seller. If the transaction matching can not be completed in the current round of transaction period, the buyer and the seller need to update the quoted price according to the optimal buying price/optimal selling price until the electricity is sold out or the transaction time is cut off.

The invention has the following beneficial effects: establishing a source network load storage interaction model of a car pooling algorithm, realizing optimal scheduling and transaction clearing of distributed energy equipment and promoting consumption of clean energy; the method can apply the car pooling model to the source network charge storage interactive transaction, and improves the efficiency of distributed energy transaction and market clearing, so that the problem of difficulty in improving the consumption of renewable energy is solved.

Drawings

FIG. 1 is a block diagram of a two-way auction incentive mechanism-based taxi sharing type interactive transaction clearing matching process.

Detailed Description

The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

Embodiment 1, as shown in fig. 1, a method for adjusting a limited electric quantity of clean energy based on source network load and store interaction includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode;

(2) constructing a source network load storage transaction management mode based on a point-to-point mode;

(3) forming a source network load storage market trading architecture based on a car pooling algorithm;

(4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism.

Embodiment 2, a method for adjusting limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The distributed energy nodes are formed by aggregating distributed energy such as photovoltaic power stations, gas turbines, electric vehicles, energy storage systems and flexible loads through advanced information technology and software systems, and each distributed energy and load have the characteristic of dispersion autonomy and can be regarded as an energy node, and the distributed energy nodes are divided into 3 types, namely energy purchasing nodes, energy selling nodes and idle nodes. The idle node refers to a node which does not participate in energy trading in the current trading period.

Embodiment 3, a method for adjusting limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The source network charge storage aggregator, namely a control center of a source network charge storage operator, can provide information consultation, transaction management and wireless communication service for each distributed energy node in source network charge storage, and comprises three main parts, namely a transaction processing center, an account storage center and a transaction record storage center.

Embodiment 4, a method for adjusting a limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The intelligent electric meter aims at realizing information transmission between the distributed energy nodes and the source network charge storage aggregator, and each distributed energy node needs to be provided with the intelligent electric meter and has the functions of calculating and recording electric power transaction amount in real time. Meanwhile, the distributed energy nodes can also pay and collect encrypted digital currency according to the transaction records of the intelligent electric meter.

Embodiment 5, a method for adjusting limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The specific method of the step 2 comprises the following steps: the source network charge storage trading and management mode based on point-to-point trading is characterized in that the consensus process is completed by all distributed energy nodes in the source network charge storage, and the consensus process can be divided into 5 steps which are respectively as follows: energy node authentication, energy optimization scheduling, energy transaction matching, energy transaction settlement and data block generation.

Embodiment 6, a method for adjusting a limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The energy node authentication step is that the distributed energy nodes need to be registered in a source network load storage aggregator before being added into the source network load storage, and information such as real identity ID, energy type, tradable amount, actual address and the like of the distributed energy nodes is reported. And after the source network load storage aggregator is audited, corresponding public and private key pairs and digital wallet addresses are issued to all distributed energy nodes through an asymmetric encryption technology and are stored in an account storage center.

Embodiment 7, a method for adjusting a limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. And the energy optimization scheduling step is that after the energy trading role is determined, the source network load storage aggregator performs optimization scheduling by taking the maximum accumulated profit as a target according to the energy information of each distributed energy node to obtain the day-ahead planned output of each distributed energy node, and sends the day-ahead planned output to each distributed energy node.

Embodiment 8, a method for adjusting a limited electric quantity of clean energy based on source network load-store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. And the energy transaction matching step is that after the day-ahead optimization scheduling is finished, in order to promote the local consumption of the distributed energy, the transaction matching between the distributed power supply and the fixed load is further realized by adopting a point-to-point transaction technology in the source network load storage. After the trade match is completed, the source grid load stores the remaining electricity for sale to the electricity market. Before the transactions are matched, the energy purchasing node/the energy selling node sends the demand information to a transaction processing center of the source network charge storage aggregator, wherein the demand information comprises information such as expected transaction electric quantity, expected transaction time and expected price quotation. The source network storage aggregator uses a continuous bidirectional auction mechanism to carry out transaction matching between the energy purchasing node and the energy selling node. After the transaction matching is completed, the energy purchasing node and the energy selling node perform power transmission.

Embodiment 9, a method for adjusting a limited electric quantity of clean energy based on source network load and store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. And the energy transaction settlement step is that after the transaction matching between the distributed energy nodes is completed, the energy purchasing node transfers the energy currency from the digital wallet to a wallet address provided by the energy selling node and adopts a private key for signature. And the energy selling node downloads the public key corresponding to the energy purchasing node from the account storage center of the source network charge storage aggregator, and decrypts the received energy payment information so as to verify that the payment information comes from the corresponding energy purchasing node.

Embodiment 10, a method for adjusting a limited electric quantity of clean energy based on source network load-store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. And the data block generation step comprises the steps that the distributed energy source node which obtains the accounting right broadcasts block information to other nodes of the system, and the other nodes continue to broadcast the data block to other nodes after auditing and signing the data block. Each node compares the audit result with the results of other nodes and replies to the accounting node. If the other nodes agree on the block, the accounting node sends the currently audited data block to all other nodes for storage. After the work is completed, the block is added to the energy point-to-point transaction in time sequence.

Embodiment 11, a method for adjusting a limited amount of electricity in clean energy based on source network load-store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The specific method of the step 3 comprises the following steps: the goal of maximizing the total platform revenue in analogy to car-pooling algorithmsAnd the standard function forms an optimal target function and constraint of the profit of the source network load storage aggregator. The source network load storage aggregator trading income and running cost in the market through the source network load storage target function with optimal profitAnd the start-stop cost and the scene probability of the gas turbine set. Trading income of source network stored in market through market trading volume G_p,s,tAnd electricity price lambda_p,tAnd (4) multiplying the two components. Gas turbine set start-stop cost is by starting to stop variableAnd start-stop base cost S^GTAnd (4) multiplying the two components. The scene probability comprises a photovoltaic output scene probability pi(s) and a power price scene probability pi (p). T is the total time period number in one day; n is_s、n_pRespectively, the number of photovoltaic scenes and the number of electricity price scenes:

the operating cost of a gas turbine can be expressed as a piecewise linear function:

wherein a is fixed production cost;is an operating variable of the gas turbine; k is a radical of_jGenerating cost slope for the j section of the gas turbine;is the output of the gas turbine during the period t.

The source network load storage aggregator profit function constraints include gas turbine constraints, energy storage system constraints, electricity market trading volume constraints and power balance constraints:

the gas turbine constraints are:

wherein, g^GT,max、g^GT,minMaximum and minimum output power of the gas turbine, respectively; r is^U、r^DThe upward and downward ramp rates of the gas turbine;the upper limit of the output of the j section of the gas turbine is; t is t^su、t^sdMinimum on-off time of the gas turbine; t is t^su,0、t^sd，0Respectively, the initial on-off time of the gas turbine.

The energy storage system constraints are:

wherein the content of the first and second substances,is the charge capacity of the ESS; eta_c、η_dRespectively the charge-discharge efficiency of the ESS;respectively the charge and discharge capacity of the ESS; s^es,min、S^es,maxRespectively the upper limit and the lower limit of the electric capacity of the ESS; g^esc,max、g^esd,maxRespectively the maximum charge and discharge power of the ESS.

The electric power market trading volume constraint is as follows:

wherein the content of the first and second substances,the maximum purchase and sale electricity quantity stored in the DAM is charged for the source network.

The power balance constraint is:

wherein the content of the first and second substances,output for renewable energy;the load demand in the source network load store.

Embodiment 11, a method for adjusting a limited amount of electricity in clean energy based on source network load-store interaction, includes the following steps:

(1) constructing a source network load storage transaction management framework based on a point-to-point mode; (2) constructing a source network load storage transaction management mode based on a point-to-point mode; (3) forming a source network load storage market trading architecture based on a car pooling algorithm; (4) and constructing a car sharing type interactive transaction clearing model based on a bidirectional auction incentive mechanism. The specific method of the step 4 comprises the following steps:

in the matching process, after the two transaction parties submit the quotes, the quotes of the buyers are arranged from high to low, and the optimal buying price is the highest quote of the buyers; and arranging the offers of the seller from low to high, wherein the optimal selling price is the lowest offer of the seller. And when the optimal buying price is greater than or equal to the optimal selling price, the buyer and the seller reach transaction matching, and the actual transaction price is the average value of the quoted prices of the buyer and the seller. If the transaction matching can not be completed in the current round of transaction period, the buyer and the seller need to update the quoted price according to the optimal buying price/optimal selling price until the electricity is sold out or the transaction time is cut off.

Establishing a source network load storage interaction model of a car pooling algorithm, realizing optimal scheduling and transaction clearing of distributed energy equipment and promoting consumption of clean energy; the method can apply the car pooling model to the source network charge storage interactive transaction, and improves the efficiency of distributed energy transaction and market clearing, so that the problem of difficulty in improving the consumption of renewable energy is solved.