CN113743989A - Shared energy storage combined frequency modulation trading method based on block chain and decentralized trading theory - Google Patents

Shared energy storage combined frequency modulation trading method based on block chain and decentralized trading theory Download PDF

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CN113743989A
CN113743989A CN202111003274.2A CN202111003274A CN113743989A CN 113743989 A CN113743989 A CN 113743989A CN 202111003274 A CN202111003274 A CN 202111003274A CN 113743989 A CN113743989 A CN 113743989A
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王亦婷
裴佑
裴哲义
邱伟强
章天晗
杨莉
林振智
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Zhejiang University ZJU
State Grid Qinghai Electric Power Co Ltd
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Abstract

The invention discloses a distributed trading method for sharing energy storage to participate in fire storage combined frequency modulation under a block chain architecture. The method comprises the following steps: step 1: an operation mode of combined frequency modulation of the shared energy storage and the thermal power generating unit is provided, and a thermal power generating unit energy storage configuration quantity model based on the frequency modulation performance is constructed; step 2: aiming at the operation mode of the shared energy storage and thermal power generating unit, a transaction method based on a scattered transaction theory is provided; and step 3: constructing a shared energy storage quotation object selection model based on a plurality of Logit models and a price negotiation model based on a Robin Steven model; and 4, step 4: and constructing an optimal purchasing decision model of the thermal power generating unit, and solving and determining a transaction object. The trading method can effectively improve the overall trading rate of the market, thereby improving the utilization rate of the distributed energy storage resources.

Description

Shared energy storage combined frequency modulation trading method based on block chain and decentralized trading theory
Technical Field
The invention relates to the technical field of block chains and energy storage, in particular to a shared energy storage combined frequency modulation trading method based on block chains and a scattered trading theory
Background
Under the background of deep global energy transformation, the power generation proportion of renewable energy sources is continuously improved. Due to natural instability of wind power and photovoltaic power generation, the rotational inertia of a power system is reduced, and the frequency modulation pressure is increased. The energy storage system, particularly a battery energy storage system, has the rapid and accurate response capability, the frequency modulation efficiency of unit power is higher, the rotary standby capacity of the power system can be reduced, and the carbon emission of thermal power is reduced. At present, the frequency modulation operation mode and the transaction mechanism aiming at small micro energy storage in China are not mature, so that a large amount of distributed energy storage resources are not effectively utilized. Related research provides a shared energy storage mode, and an energy storage owner leases idle energy storage to a client with a requirement by separating ownership and use right of the energy storage, so that equipment sharing is realized. But at present, no trading method research aiming at sharing energy storage to participate in frequency modulation exists at home and abroad. Therefore, it is necessary to provide a shared energy storage combined frequency modulation trading method based on a block chain and a decentralized trading theory, so as to improve the utilization rate of energy storage resources.
Disclosure of Invention
The invention provides a distributed transaction method for sharing energy storage to participate in fire storage combined frequency modulation under a block chain architecture. The method firstly provides an operation mode that distributed energy storage participates in thermal power combined frequency modulation in a shared energy storage mode, and designs a combined frequency modulation decentralized transaction mechanism considering the distributed energy storage and the preference of a thermal power unit based on the mode; a union chain architecture comprising a consensus mechanism and an intelligent contract is constructed, and a transaction information classification management method considering the privacy of a transaction main body is provided; and constructing a trading method based on a scattered trading theory, and simulating a market trading result.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a shared energy storage combined frequency modulation trading method based on a block chain and a scattered trading theory comprises the following steps:
step 1: an operation mode of combined frequency modulation of the shared energy storage and the thermal power generating unit is provided, and a thermal power generating unit energy storage configuration quantity model based on the frequency modulation performance is constructed;
step 2: aiming at a combined frequency modulation operation mode of a shared energy storage and thermal power generating unit, a trading method based on a scattered trading theory is provided;
and step 3: constructing a shared energy storage quotation object selection model based on a plurality of Logit models and a price negotiation model based on a Robin Steven model;
and 4, step 4: and constructing an optimal purchasing decision model of the thermal power generating unit, and solving and determining a transaction object.
In the above technical solution, further, in step 1, the thermal power generating unit energy storage configuration quantity model based on the frequency modulation performance is as follows:
the model is expressed by a frequency modulation performance growth function of the thermal power generating unit, and the frequency modulation performance K of the thermal power generating unitpThe relational expression of the lifting percentage alpha and the unit configuration energy storage proportion beta is as follows, and approximately presents a quadratic function relationship in a certain range. And if the unit configuration energy storage ratio exceeds the maximum energy storage configuration ratio, the frequency modulation performance enters a saturation region and is not promoted any more.
Figure BDA0003236329780000021
In the formula, x1，x2，x3A coefficient value that is a function of frequency modulation performance; alpha is alphamaxFrequency modulation for unitsA performance limit; beta is amaxAnd configuring an energy storage proportion for the unit.
The gain obtained by the thermal power generating unit participating in secondary frequency modulation (AGC) is related to the frequency modulation performance, and the additional gain obtained by the thermal power generating unit j performing fire storage combined frequency modulation is obtained
Figure BDA0003236329780000022
Is composed of
Figure BDA0003236329780000023
In the formula (I), the compound is shown in the specification,
Figure BDA0003236329780000024
the frequency modulation performance of the thermal power generating unit j during independent operation is achieved; p is the unit price of clearing in the frequency modulation market; djThe distance is the frequency modulation distance of the thermal power generating unit j; alpha is alphajAnd improving the percentage of the frequency modulation performance of the thermal power generating unit j.
Furthermore, the trading method based on the scattered trading theory in the step 2 comprises the following steps:
compared with the energy storage capacity required by a thermal power generating unit, the single distributed energy storage capacity is small, so that the actual control problem is combined, the shared energy storage capacity is supposed to be inseparable, the whole energy storage capacity needs to be rented, the transaction is not allowed to be changed after the transaction is completed, the transaction target is the use right of the shared energy storage equipment, the quoted price is the lease price per hour of unit power, the lease duration is 4 hours, and the transaction deadline is 1 hour before the start of the lease period. In the decentralized transaction mode, due to information and time limitations, the number of transaction objects actually contacted by the transaction subject is limited, and it is assumed that each energy storage owner has the greatest chance to contact with T at most in each transaction periodNNegotiation of each thermal power generating unit, wherein each negotiation opportunity is defined as a transaction turn, and the maximum transaction turn is defined as TN。
And starting a trading period, the thermal power generating unit node issues demand information for energy storage on the block chain platform, the energy storage node issues rentable capacity information, information such as demand and credit of the thermal power generating unit is inquired from the block chain platform, and one thermal power generating unit is selected as a quotation object according to self trading preference and historical trading records. Next, the parties to the transaction conduct several rounds of price negotiations. And selecting the rented shared energy storage with the self benefit maximization as the target according to the negotiation result. And after each round of transaction is finished, the thermal power generating unit updates the demand information, and the energy storage units which are not committed continue to select the quotation objects. And each main body of the market continuously carries out the dispersed transaction through continuously updated market information until the transaction time period is finished.
The block chain is a combined frequency modulation block chain based on an alliance chain structure, and the specific structure is as follows:
(1) authenticating the node: an authentication (CA) node is arranged in the block chain network and is responsible for the admission and authorization of all the shared energy storage nodes and thermal power unit nodes in the frequency modulation transaction channel, and a unique digital signature is issued to the nodes on the chain. These shared energy storage nodes and thermal power plant unit nodes are referred to as Peer-to-Peer (Peer) nodes.
(2) Intelligent contract: the intelligent contracts comprise settlement contracts, resource sharing contracts and credit sharing contracts; a. and (4) settling the contract, wherein after the transaction time interval is ended, the thermal power generating unit and the shared energy storage which reach the transaction respectively confirm the transaction by using digital signatures, and the intelligent contract automatically completes the charge settlement and the transfer of the energy storage control right after being verified. And clearing the transaction cost by reading the transaction unit price and the transaction amount according to the settlement contract on the thermal power unit node, and transferring the lease cost from the thermal power unit account to the shared energy storage account. b. The energy storage equipment is accessed to the block chain network through the Internet of things technology and has a unique resource locator and a corresponding access control strategy, and the access control strategy determines that the node with a specific address can only control the charging and discharging power of the energy storage. After the verification cost reaches the account, the resource sharing contract on the energy storage node adds the address of the thermal power unit node into the accessible address by modifying the access control strategy, and automatically fails after the lease time is over, so that the energy storage control authority transfer with time limit is realized. c. And updating the transaction credit scores of the nodes according to the behaviors of the thermal power generating unit and the energy storage nodes by the credit score contract after the lease time is ended. The credit rating judgment basis is whether the energy storage equipment exceeds an appointed SoC limit value under the control of the thermal power unit node, and whether the shared energy storage node privately controls the charging and discharging power of energy storage.
(3) A consensus algorithm: the m energy storage nodes with the highest trading credit and the n thermal power unit nodes in the frequency modulation trading market are set as sequencing nodes, and generally, the high credit nodes have stronger willingness to maintain stable operation of the market. When the raw sequencing service is started, a master node is randomly generated in m + n nodes participating in consensus, and the rest m + n-1 nodes are slave nodes.
(4) Management of private data: the data are divided into public data and private data according to the privacy of the data, and the distributed account book on each node is divided into a public account book and a private account book through a set technology, so that classified storage of the data is realized.
The public data is transaction information disclosed in a transaction process, and comprises the demand and the transaction credit score of the thermal power generating unit for energy storage, the selling capacity of the shared energy storage and other attributes. The information needs backup storage of all nodes, and all nodes have query authority. The private data comprises the transaction record and the quotation information of each node, and is only stored in the account books of the nodes of both transaction sides and is not disclosed to other nodes. The private data uplink also needs sequencing service verification, but the sequencing node can only query the hash value after data encryption and cannot directly read the data content.
Furthermore, the method for constructing the shared energy storage offer object selection model based on multiple Logit models and the price negotiation model based on the rubenstanen model in step 3 is as follows:
the method comprises the following steps of (1) sharing an energy storage quotation object selection model based on a plurality of Logit models:
when a quotation object is selected, the shared energy storage is used as a decision maker, the number of the alternative schemes is the number of the thermal power generating units, and the scheme attributes comprise a transaction record, credit, the demand of the thermal power generating units and random factors.
The shared energy storage considers the latest H times of transaction conditions when selecting the quotation object, and the influence degree of the transaction records follows the information processing principle of 'close to light and far', thenTransaction record matching score of shared energy storage i and thermal power generating unit j
Figure BDA0003236329780000041
Is composed of
Figure BDA0003236329780000042
Figure BDA0003236329780000043
In the formula, ri,j,hIn order to be the result of the intersection,
Figure BDA0003236329780000044
the method is a trading score reference value, and the values of the trading score reference value under various conditions { first-round bargain, non-first-round bargain, quoted non-bargain and non-quoted } are {2,1, -1 and 0 };
Figure BDA0003236329780000045
the price is the transaction price;
Figure BDA0003236329780000046
is the average trading unit price of energy i.
Each shared energy storage i has a credit acceptance lower bound
Figure BDA0003236329780000047
Credit score of thermal power generating unit j
Figure BDA0003236329780000048
Is lower than
Figure BDA0003236329780000049
When the two are not matched in trust, the credit matching distribution of the shared energy storage i and the thermal power generating unit j is determined
Figure BDA00032363297800000410
Is composed of
Figure BDA0003236329780000051
The shared energy storage has demand preferences, and the offer selection thereof can be influenced by the demand of the thermal power generating unit and the purchased energy storage. In order to improve the transaction probability, the preferred shared energy storage can be quoted to the thermal power generating unit with larger demand in the first round of transaction. In subsequent trading rounds, the thermal power generating unit with small energy storage purchasing proportion tends to purchase energy storage continuously, so that the energy storage purchased by the thermal power generating unit is mainly considered. Demand matching distribution of shared energy storage i and thermal power generating unit j in T-th round of transaction
Figure BDA0003236329780000052
Is composed of
Figure BDA0003236329780000053
In the formula, T is the current transaction turn;
Figure BDA0003236329780000054
in order to share the capacity of the stored energy,
Figure BDA0003236329780000055
is the demand of the thermal power generating unit,
Figure BDA0003236329780000056
capacity, m, purchased from energy storage i for thermal power generating unit j in round t transactionj,tAnd (4) the shared energy storage quantity purchased in the t round transaction for the thermal power generating unit j.
The shared energy storage can select the quotation object according to three preferences such as transaction loyalty, transaction trust and demand. Selecting different preferences of thermal power generating units for sharing stored energy, and adopting transaction loyalty weighted value
Figure BDA0003236329780000057
Transaction confidence weighting value
Figure BDA0003236329780000058
And demand weight value
Figure BDA0003236329780000059
Quantifying the influence degree of the 3 attributes, namely the weight vector omega of the shared energy storage iiIs composed of
Figure BDA00032363297800000510
The shared energy storage i selects a preference function U for quoting to the fire engine set j in the T-th round of transactioni,j,TIs composed of
Ui,j,T＝Vi,j,T+εi,j
Figure BDA00032363297800000511
In the formula, Vi,j,TIs the composite match preference value; epsiloni,jIs a market random factor.
Random term epsilon is assumed by a multi-term Logit modeli,jObeying the double exponential distribution, the quotation probability p of the shared energy storage i to the thermoelectric generator set j in the T round of transactioni,j,TIs composed of
Figure BDA00032363297800000512
Price negotiation model based on the rubenstanen model:
the shared energy storage adopts a linear quotation strategy, negotiation is carried out between the shared energy storage and the thermal power generating unit according to unit price, and the maximum negotiation return is set as kmaxThe price acceptance range of the shared energy storage i is
Figure BDA0003236329780000061
Minimum accepted price
Figure BDA0003236329780000062
Energy storage single frequency modulation related to cost of sharing energy storage frequency modulationCost of
Figure BDA0003236329780000063
Namely the loss cost of the energy storage battery, and the equivalent charge-discharge cycle number n can be usedeqThe calculation is carried out, and the price negotiation model is as follows:
Figure BDA0003236329780000064
Figure BDA0003236329780000065
Figure BDA0003236329780000066
Figure BDA0003236329780000067
in the formula, CinOne-time investment cost; cmaFor operating maintenance costs; n is a radical offailThe maximum charge-discharge cycle number is obtained;
Figure BDA0003236329780000068
and
Figure BDA0003236329780000069
respectively representing the lowest expected yield and the highest expected yield of the shared energy storage i, wherein k is the current negotiation turn;
the thermal power generating unit constructs a quotation interval according to the highest yield and the lowest yield expected by the thermal power generating unit
Figure BDA00032363297800000610
And a correction quotation strategy considering the transaction completion degree and the transaction rounds is adopted, the transaction completion degree x is defined as the ratio of the purchased stored energy of the thermal power generating unit to the maximum demand quantity of the thermal power generating unit, and the thermal power generating unit can expect to achieve the transaction completion degree x in different transaction rounds T. When the thermal power generating unit is inThe expected transaction completion degree is not reached under the current transaction turn, and the thermal power generating unit can increase the price yielding amplitude to improve the transaction probability so as to quickly purchase the stored energy. Otherwise, the price yielding amplitude is shortened. By a price correction factor deltajAnd correcting the quotation strategy of the thermal power generating unit. The price negotiation model is as follows:
Figure BDA00032363297800000611
Figure BDA00032363297800000612
Figure BDA00032363297800000613
Figure BDA0003236329780000071
in the formula (I), the compound is shown in the specification,
Figure BDA0003236329780000072
respectively representing the lowest expected yield and the highest expected yield of the thermal power generating unit j; Δ RjPurchasing the income obtained by the required maximum capacity energy storage for the thermal power generating unit j; phi is ajAnd the influence factor constant represents the influence degree of the thermal power generating unit j quotation strategy on the market trading condition. m istAnd the quantity of stored energy purchased for the t-th round of the thermal power generating unit.
Furthermore, in step 4, the optimal procurement decision model of the thermoelectric generator set is as follows:
if the shared energy storage offer is lower than the offer of the thermal power generating unit, the negotiation between the two parties is considered to be successful, and the transaction price after the price negotiation in the k rounds is obtained
Figure BDA0003236329780000073
Comprises the following steps:
Figure BDA0003236329780000074
the thermal power generating unit determines whether to finally make a business or not in a profit maximization mode, and the total purchase amount does not exceed the maximum demand amount. For the successfully negotiated shared energy storage i, the thermal power generating unit j can finally decide to sign or reject according to the extra income and the transaction price thereof by taking the maximization of the income as a target, wherein the optimal purchasing strategy is represented as:
Figure BDA0003236329780000075
Figure BDA0003236329780000076
in the formula (f)jThe method comprises the steps of obtaining a frequency modulation performance growth function of a thermal power generating unit j; x is the number ofi,tIndicating whether the thermal power generating unit purchases the stored energy i, x in the t round of transactioni,t∈{0,1}。
The invention has the beneficial effects that:
firstly, the method provides a business mode that distributed small energy storage participates in fire storage combined frequency modulation in a shared energy storage mode, effectively reduces a capacity threshold of energy storage participating in frequency modulation, and constructs a thermal power generating unit energy storage configuration quantity model based on frequency modulation performance;
secondly, a transaction method based on a dispersion theory between the shared energy storage unit and the thermal power generating unit is designed, and a frequency modulation transaction chain based on an alliance chain architecture is designed;
and thirdly, constructing a decentralized transaction model by using the method, and simulating the process of determining a transaction object and a transaction price by using the shared energy storage and thermal power generating unit. The method can fully consider the trading preferences of different market subjects, effectively promote the trading of the thermal power generating unit and the shared energy storage, and apply the idle energy storage resources to the frequency modulation of the power grid.
And fourthly, the method is easy to operate, provides reference for the practical popularization of the shared energy storage frequency modulation operation mode and the design of a matched transaction mechanism, and has certain practical significance.
Drawings
FIG. 1 is a block chain-based overall transaction architecture of the present invention.
Fig. 2 is a schematic diagram of frequency modulation performance improvement of a thermal power generating unit.
Fig. 3 is a flow chart of distributed transaction between the thermal power generating unit and the shared energy storage.
Fig. 4 is a schematic diagram of a consensus process for calculating the matching degree between the shared energy storage and the thermal power generating unit credit.
Detailed Description
The drawings are for illustrative purposes only and are not to be construed as limiting the patent; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted. The positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the present patent.
The invention relates to a shared energy storage combined frequency modulation trading method based on a block chain and a scattered trading theory, which comprises the following steps:
step 1: an operation mode of combined frequency modulation of the shared energy storage and the thermal power generating unit is provided, and a thermal power generating unit energy storage configuration quantity model based on the frequency modulation performance is established. The specific implementation method of the step is as follows:
frequency modulation performance K of thermal power generating unitpThe relational expression of the lifting percentage alpha and the unit configuration energy storage proportion beta is as follows, and approximately presents a quadratic function relationship in a certain range. And if the unit configuration energy storage ratio exceeds the maximum energy storage configuration ratio, the frequency modulation performance enters a saturation region and is not promoted any more.
Figure BDA0003236329780000081
In the formula, x1，x2，x3A coefficient value that is a function of frequency modulation performance; alpha is alphamaxThe limit value of the frequency modulation performance of the unit is set; beta is amaxAnd configuring an energy storage proportion for the unit.
Additional benefit obtained by carrying out fire storage combined frequency modulation on thermal power generating unit j
Figure BDA0003236329780000082
Is composed of
Figure BDA0003236329780000083
In the formula (I), the compound is shown in the specification,
Figure BDA0003236329780000084
the frequency modulation performance of the thermal power generating unit j during independent operation is achieved; p is the unit price of clearing in the frequency modulation market; djThe distance is the frequency modulation distance of the thermal power generating unit j; alpha is alphajAnd improving the percentage of the frequency modulation performance of the thermal power generating unit j.
Step 2: a transaction method based on a scattered transaction theory is provided, and a united frequency modulation block chain based on a united chain architecture is designed. The specific implementation method of the step is as follows:
compared with the energy storage capacity required by a thermal power generating unit, the single distributed energy storage capacity is small, so that the actual control problem is combined, the shared energy storage capacity is supposed to be inseparable, the whole energy storage capacity needs to be rented, the transaction is not allowed to be changed after the transaction is completed, the transaction target is the use right of the shared energy storage equipment, the quoted price is the lease price per hour of unit power, the lease duration is 4 hours, and the transaction deadline is 1 hour before the start of the lease period. In the decentralized transaction mode, due to information and time limitations, the number of transaction objects actually contacted by the transaction subject is limited, and it is assumed that each energy storage owner has the greatest chance to contact with T at most in each transaction periodNNegotiation of each thermal power generating unit, wherein each negotiation opportunity is defined as a transaction turn, and the maximum transaction turn is defined as TN。
And starting a trading period, the thermal power generating unit node issues demand information for energy storage on the block chain platform, the energy storage node issues rentable capacity information, information such as demand and credit of the thermal power generating unit is inquired from the block chain platform, and one thermal power generating unit is selected as a quotation object according to self trading preference and historical trading records. Next, the parties to the transaction conduct several rounds of price negotiations. And selecting the rented shared energy storage with the self benefit maximization as the target according to the negotiation result. And after each round of transaction is finished, the thermal power generating unit updates the demand information, and the energy storage units which are not committed continue to select the quotation objects. And each main body of the market continuously carries out the dispersed transaction through continuously updated market information until the transaction time period is finished.
The joint frequency modulation block chain based on the alliance chain structure is as follows:
(1) an authentication (CA) node is arranged in the block chain network and is responsible for the admission and authorization of all the shared energy storage nodes and thermal power unit nodes in the frequency modulation transaction channel, and a unique digital signature is issued to the nodes on the chain. These shared energy storage nodes and thermal power plant unit nodes are referred to as Peer-to-Peer (Peer) nodes.
(2) After the transaction period is finished, the thermal power generating unit and the shared energy storage which achieve the transaction respectively confirm the transaction by using digital signatures, and the intelligent contract automatically completes the charge settlement and the transfer of the energy storage control right after being verified. And clearing the transaction cost by reading the transaction unit price and the transaction amount according to the settlement contract on the thermal power unit node, and transferring the lease cost from the thermal power unit account to the shared energy storage account. The energy storage equipment is connected to a block chain network through the Internet of things technology and has a unique resource locator and a corresponding access control strategy, and the access control strategy determines that the node with a specific address can only control the charging and discharging power of the stored energy. After the verification cost reaches the account, the resource sharing contract on the energy storage node adds the address of the thermal power unit node into the accessible address by modifying the access control strategy, and automatically fails after the lease time is over, so that the energy storage control authority transfer with time limit is realized. And after the lease time is finished, updating the transaction credit score of each node according to the behaviors of the thermal power generating unit and the energy storage node by the intelligent contract. The credit rating judgment basis is whether the energy storage equipment exceeds an appointed SoC limit value under the control of the thermal power unit node, and whether the shared energy storage node privately controls the charging and discharging power of energy storage.
(3) The m energy storage nodes with the highest trading credit and the n thermal power unit nodes in the frequency modulation trading market are set as sequencing nodes, and generally, the high credit nodes have stronger willingness to maintain stable operation of the market. When the raw sequencing service is started, a master node is randomly generated in m + n nodes participating in consensus, and the rest m + n-1 nodes are slave nodes.
(4) The data are divided into public data and private data according to the privacy of the data, and the distributed account book on each node is divided into a public account book and a private account book through a set technology, so that classified storage of the data is realized.
The public data is transaction information disclosed in a transaction process, and comprises the demand and the transaction credit score of the thermal power generating unit for energy storage, the selling capacity of the shared energy storage and other attributes. The information needs backup storage of all nodes, and all nodes have query authority. The private data comprises the transaction record and the quotation information of each node, and is only stored in the account books of the nodes of both transaction sides and is not disclosed to other nodes. The private data uplink also needs sequencing service verification, but the sequencing node can only query the hash value after data encryption and cannot directly read the data content.
And step 3: a shared energy storage quotation object selection model based on a plurality of Logit models and a price negotiation model based on a Robin Steiny model are constructed. The specific implementation method of the step is as follows:
when a quotation object is selected, the shared energy storage is used as a decision maker, the number of the alternative schemes is the number of the thermal power generating units, and the scheme attributes comprise a transaction record, credit, the demand of the thermal power generating units and random factors.
The latest H-time transaction condition is considered when the shared energy storage selects the quotation object, and the influence degree of transaction records follows the information processing principle of 'close to light and far', so that the transaction records of the shared energy storage i and the thermal power generating unit j are matched and divided
Figure BDA0003236329780000101
Is composed of
Figure BDA0003236329780000102
Figure BDA0003236329780000103
In the formula, ri,j,hIn order to be the result of the intersection,
Figure BDA0003236329780000104
the method is a trading score reference value, and the values of the trading score reference value under various conditions { first-round bargain, non-first-round bargain, quoted non-bargain and non-quoted } are {2,1, -1 and 0 };
Figure BDA0003236329780000105
the price is the transaction price;
Figure BDA0003236329780000106
is the average trading unit price of energy i.
Each shared energy storage i has a credit acceptance lower bound
Figure BDA0003236329780000111
Credit score of thermal power generating unit j
Figure BDA0003236329780000112
Is lower than
Figure BDA0003236329780000113
When the two are not matched in trust, the credit matching distribution of the shared energy storage i and the thermal power generating unit j is determined
Figure BDA0003236329780000114
Is composed of
Figure BDA0003236329780000115
The shared energy storage has demand preferences, and the offer selection thereof can be influenced by the demand of the thermal power generating unit and the purchased energy storage. In order to improve the transaction probability, the preferred shared energy storage can be quoted to the thermal power generating unit with larger demand in the first round of transaction. In subsequent trading rounds, the thermal power generating unit with small energy storage purchasing proportion tends to purchase energy storage continuously, so that the energy storage purchased by the thermal power generating unit is mainly considered. Demand matching distribution of energy storage i and thermal power generating unit j in T-th round of transaction
Figure BDA0003236329780000116
Is composed of
Figure BDA0003236329780000117
In the formula, T is the current transaction turn;
Figure BDA0003236329780000118
in order to share the capacity of the stored energy,
Figure BDA0003236329780000119
is the demand of the thermal power generating unit,
Figure BDA00032363297800001110
the capacity purchased from the energy storage i in the t round transaction for the thermal power generating unit j,mj,tand (4) the shared energy storage quantity purchased in the t round transaction for the thermal power generating unit j.
In summary, the present application considers that the shared energy storage selects the quotation object according to three preferences, such as transaction loyalty, transaction trust and demand. Selecting different preferences of thermal power generating units for sharing stored energy, and adopting transaction loyalty weighted value
Figure BDA00032363297800001111
Transaction confidence weighting value
Figure BDA00032363297800001112
And demand weight value
Figure BDA00032363297800001113
Quantifying the influence degree of the 3 attributes, namely the attribute weight vector omega of the shared energy storage iiIs composed of
Figure BDA00032363297800001114
Then the shared energy storage i selects to be on fire in the T round of transactionPreference function U of motor group j quotationi,j,TIs composed of
Ui,j,T＝Vi,j,T+εi,j
Figure BDA00032363297800001115
In the formula, Vi,j,TIs the composite match preference value; epsiloni,jIs a market random factor.
And (3) assuming that a random term epsilon obeys double exponential distribution by the multi-term Logit model, and sharing the quotation probability p of the stored energy i to the fire generator set j in the T-th round of transactioni,j,TIs composed of
Figure BDA0003236329780000121
The shared energy storage adopts a linear quotation strategy, negotiation is carried out between the shared energy storage and the thermal power generating unit according to unit price, and the maximum negotiation return is set as kmaxThe price acceptance range of the shared energy storage i is
Figure BDA0003236329780000122
Minimum accepted price
Figure BDA0003236329780000123
Cost associated with sharing energy storage frequency modulation, cost of energy storage single frequency modulation
Figure BDA0003236329780000124
Namely the loss cost of the energy storage battery, and the equivalent charge-discharge cycle number n can be usedeqThe calculation is carried out, and the price negotiation model is as follows:
Figure BDA0003236329780000125
Figure BDA0003236329780000126
Figure BDA0003236329780000127
Figure BDA0003236329780000128
in the formula, CinOne-time investment cost; cmaFor operating maintenance costs; n is a radical offailThe maximum charge-discharge cycle number is obtained;
Figure BDA0003236329780000129
and
Figure BDA00032363297800001210
the lowest and highest expected profitability for the shared energy storage i, respectively, and k is the current negotiation round.
The thermal power generating unit constructs a quotation interval according to the highest yield and the lowest yield expected by the thermal power generating unit
Figure BDA00032363297800001211
And a correction quotation strategy considering the transaction completion degree and the transaction rounds is adopted, the transaction completion degree x is defined as the ratio of the purchased stored energy of the thermal power generating unit to the maximum demand quantity of the thermal power generating unit, and the thermal power generating unit can expect to achieve the transaction completion degree x in different transaction rounds T. When the thermal power generating unit does not reach the expected transaction completion degree under the current transaction turn, the thermal power generating unit can increase the price yielding range to improve the transaction probability so as to quickly purchase the stored energy. Otherwise, the price yielding amplitude is shortened. By a price correction factor deltajAnd correcting the quotation strategy of the thermal power generating unit. The price negotiation model is as follows:
Figure BDA00032363297800001212
Figure BDA0003236329780000131
Figure BDA0003236329780000132
Figure BDA0003236329780000133
in the formula (I), the compound is shown in the specification,
Figure BDA0003236329780000134
respectively representing the lowest expected yield and the highest expected yield of the thermal power generating unit j; Δ RjPurchasing the income obtained by the required maximum capacity energy storage for the thermal power generating unit j; phi is ajAnd the influence factor constant represents the influence degree of the thermal power generating unit j quotation strategy on the market trading condition. m istAnd the quantity of stored energy purchased for the t-th round of the thermal power generating unit.
And 4, step 4: and constructing an optimal purchasing decision model of the thermal power generating unit, and solving and determining a transaction object. The specific implementation method of the step is as follows:
if the shared energy storage offer is lower than the offer of the thermal power generating unit, the negotiation between the two parties is considered to be successful, and the transaction price after the price negotiation in the k rounds is obtained
Figure BDA0003236329780000135
Comprises the following steps:
Figure BDA0003236329780000136
the thermal power generating unit determines whether to finally make a business or not in a profit maximization mode, and the total purchase amount does not exceed the maximum demand amount. For the successfully negotiated shared energy storage i, the thermal power generating unit j can finally decide to sign or reject according to the utility function and the transaction price thereof and with the goal of maximizing the income, and the optimal purchasing strategy is expressed as follows:
Figure BDA0003236329780000137
Figure BDA0003236329780000138
in the formula (f)jThe method comprises the steps of obtaining a frequency modulation performance growth function of a thermal power generating unit j; x is the number ofi,tIndicating whether the thermal power generating unit purchases the stored energy i, x in the t round of transactioni,t∈{0,1}。

Claims (5)

1. A shared energy storage combined frequency modulation trading method based on a block chain and a scattered trading theory is characterized by comprising the following steps
Step 1: an operation mode of combined frequency modulation of the shared energy storage and the thermal power generating unit is provided, and a thermal power generating unit energy storage configuration quantity model based on the frequency modulation performance is constructed;
step 2: aiming at the operation mode of the shared energy storage and thermal power generating unit, a transaction method based on a scattered transaction theory is provided;
and step 3: constructing a shared energy storage quotation object selection model based on a plurality of Logit models and a price negotiation model based on a Robin Steven model;
and 4, step 4: and constructing an optimal purchasing decision model of the thermal power generating unit, and solving and determining a transaction object.
2. The shared energy storage combined frequency modulation trading method based on the blockchain and decentralized trading theory according to claim 1, characterized in that: in the step 1, the thermal power generating unit energy storage configuration quantity model based on the frequency modulation performance is as follows:
the model is expressed by a frequency modulation performance growth function of the thermal power generating unit, and the frequency modulation performance K of the thermal power generating unitpThe relational expression of the promotion percentage alpha and the unit configuration energy storage ratio beta is as follows:
Figure FDA0003236329770000011
in the formula, x1，x2，x3A coefficient value that is a function of frequency modulation performance; alpha is alphamaxFrequency modulation for unitsA performance limit; beta is amaxConfiguring an energy storage proportion for the unit;
the gain obtained by the thermal power generating unit participating in secondary frequency modulation is related to the frequency modulation performance, and the additional gain obtained by the thermal power generating unit j performing combined frequency modulation is obtained
Figure FDA0003236329770000012
Is composed of
Figure FDA0003236329770000013
In the formula (I), the compound is shown in the specification,
Figure FDA0003236329770000014
the frequency modulation performance of the thermal power generating unit j during independent operation is achieved; alpha is alphajImproving the percentage of the frequency modulation performance of the thermal power generating unit j; p is the unit price of clearing in the frequency modulation market; djAnd the frequency modulation mileage of the thermal power generating unit j is obtained.
3. The shared energy storage combined frequency modulation trading method based on the blockchain and decentralized trading theory according to claim 1, characterized in that: the trading method based on the scattered trading theory in the step 2 comprises the following steps:
assuming that the shared energy storage capacity is not divisible, the shared energy storage capacity needs to be rented integrally, the transaction is not allowed to be changed after the transaction is completed, the transaction target is the use right of the shared energy storage equipment, the quoted price is the lease price per hour of unit power, the lease duration is 4 hours, and the transaction deadline is 1 hour before the start of a lease period; in the decentralized transaction mode, due to information and time limitations, the number of transaction objects actually contacted by the transaction subject is limited, and it is assumed that each energy storage owner has the greatest chance to contact with T at most in each transaction periodNNegotiation of each thermal power generating unit, wherein each negotiation opportunity is defined as a transaction turn, and the maximum transaction turn is defined as TN；
Starting a trading period, issuing demand information for energy storage by thermal power generating unit nodes on a block chain platform, issuing rentable capacity information by the energy storage nodes, inquiring demand and credit information of the thermal power generating units from the block chain platform, and selecting one thermal power generating unit as a quotation object according to trading preference and historical trading records; then, both parties of the transaction negotiate prices in a plurality of rounds; the thermal power generating unit selects the rented shared energy storage with the self benefit maximization as a target according to the negotiation result; after each round of transaction is finished, the thermal power generating unit updates the demand information, and the stored energy which is not committed continues to select the quotation object; all main bodies of the market continuously carry out decentralized trading through continuously updated market information until the trading period is finished;
the block chain is a combined frequency modulation block chain based on an alliance chain structure, and the specific structure is as follows:
(1) authenticating the node: the authentication node is responsible for the admission and authorization of all shared energy storage nodes and thermal power unit nodes in the frequency modulation transaction channel and issues a unique digital signature to the linked node; the shared energy storage node and the thermal power generating unit node are called peer-to-peer nodes;
(2) intelligent contract: the intelligent contracts comprise settlement contracts, resource sharing contracts and credit sharing contracts; a. the method comprises the following steps of (1) settling a contract, confirming a transaction by using digital signatures respectively for a thermal power generating unit and a shared energy storage unit which reach the transaction after a transaction time interval is ended, and automatically finishing expense settlement and energy storage control right transfer after an intelligent contract is verified; clearing the transaction cost by reading the transaction unit price and the transaction amount according to a settlement contract on the thermal power unit node, and transferring the lease cost from the thermal power unit account to the shared energy storage account; b. the energy storage equipment is accessed to a block chain network through the Internet of things technology and has a unique resource locator and a corresponding access control strategy, and the access control strategy is used for determining the charge and discharge power of the node control energy storage of a specific address; after the verification cost reaches the account, the resource sharing contract on the energy storage node adds the address of the thermal power unit node into the accessible address by modifying the access control strategy, and automatically fails after the lease time is over, so that the energy storage control authority is transferred in a time limit manner; c. the credit scoring contract updates the transaction credit scoring of each node according to the behaviors of the thermal power generating unit and the energy storage node after the lease time is ended; the credit rating judgment basis is that whether the energy storage equipment crosses the appointed charge state limit value under the control of the thermal power unit node, and whether the shared energy storage node privately controls the charge and discharge power of energy storage;
(3) a consensus algorithm: setting m energy storage nodes with the highest trading credit and n thermal power unit nodes in a frequency modulation trading market as sequencing nodes, randomly generating a main node in m + n nodes participating in consensus when a Raft sequencing service is started, and setting the rest m + n-1 nodes as slave nodes;
(4) management of private data: the data are divided into public data and private data according to the privacy of the data, and the distributed accounts on each node are divided into public accounts and private accounts through a set technology, so that classified storage of the data is realized;
the public data is transaction information disclosed in a transaction process, and comprises the demand of the thermal power unit for energy storage, the transaction credit score and the selling capacity of shared energy storage; the public data needs all nodes to be backed up and stored, and all nodes have query authority; the private data comprises the transaction record and the quotation information of each node, and is only stored in the accounts of the nodes of both transaction parties and is not disclosed to other nodes; the private data uplink also needs sequencing service verification, but the sequencing node can only query the hash value after data encryption and cannot directly read the data content.
4. The shared energy storage combined frequency modulation trading method based on the blockchain and decentralized trading theory according to claim 1, characterized in that: the method for constructing the shared energy storage quotation object selection model based on the multiple Logit models and the price negotiation model based on the Robin Steiny model in the step 3 is as follows:
the method comprises the following steps of (1) sharing an energy storage quotation object selection model based on a plurality of Logit models:
when a quotation object is selected, the shared energy storage is used as a decision maker, the number of alternative schemes is the number of thermal power generating units, and the scheme attributes comprise a transaction record, credit, the demand of the thermal power generating units and random factors;
the shared energy storage considers the latest H times of deals when selecting the quotation object, and the dealsThe influence degree of the records follows the information processing principle of 'close to light and far', and the transaction records of the shared energy storage i and the thermal power generating unit j are matched
Figure FDA0003236329770000031
Is composed of
Figure FDA0003236329770000032
Figure FDA0003236329770000033
In the formula, ri,j,hIn order to be the result of the intersection,
Figure FDA0003236329770000034
the method is a trading score reference value, and the values of the trading score reference value under various conditions { first-round bargain, non-first-round bargain, quoted non-bargain and non-quoted } are {2,1, -1 and 0 };
Figure FDA0003236329770000035
the price is the transaction price;
Figure FDA0003236329770000036
the average bargain unit price of the stored energy i;
each shared energy storage i has a credit acceptance lower bound
Figure FDA0003236329770000041
Credit score of thermal power generating unit j
Figure FDA0003236329770000042
Is lower than
Figure FDA0003236329770000043
When the two are not matched in trust, the credit matching distribution of the shared energy storage i and the thermal power generating unit j is determined
Figure FDA0003236329770000044
Is composed of
Figure FDA0003236329770000045
The shared energy storage has demand preference, and the quotation selection of the shared energy storage is influenced by the demand of the thermal power generating unit and the purchased energy storage; in order to improve the transaction probability, the preferred shared energy storage can quote a thermal power generating unit with larger demand in the first round of transaction; in subsequent transaction rounds, the thermal power generating unit with small energy storage purchase proportion tends to purchase energy storage continuously, so the purchased energy storage of the thermal power generating unit needs to be considered; demand matching distribution of shared energy storage i and thermal power generating unit j in T-th round of transaction
Figure FDA0003236329770000046
Is composed of
Figure FDA0003236329770000047
In the formula, T is the current transaction turn;
Figure FDA0003236329770000048
in order to share the capacity of the stored energy,
Figure FDA0003236329770000049
is the demand of the thermal power generating unit,
Figure FDA00032363297700000410
capacity, m, purchased from energy storage i for thermal power generating unit j in round t transactionj,tThe shared energy storage quantity purchased by the thermal power generating unit j in the t round of transaction;
the shared energy storage selects a quotation object according to three preferences of transaction loyalty, transaction trust, demand and the like, and selects the non-operation of the thermal power generating unit for embodying the shared energy storageWith preference, transaction loyalty weight value
Figure FDA00032363297700000411
Transaction confidence weighting value
Figure FDA00032363297700000412
And demand weight value
Figure FDA00032363297700000413
Quantifying the influence degree of the 3 attributes, namely the weight vector omega of the shared energy storage iiIs composed of
Figure FDA00032363297700000414
The shared energy storage i selects a preference function U for quoting to the fire engine set j in the T-th round of transactioni,j,TIs composed of
Ui,j,T＝Vi,j,T+εi,j
Figure FDA00032363297700000415
In the formula, Vi,j,TIs the composite match preference value; epsiloni,jIs a market random factor;
random term epsilon is assumed by a multi-term Logit modeli,jObeying the double exponential distribution, the quotation probability p of the shared energy storage i to the thermoelectric generator set j in the T round of transactioni,j,TIs composed of
Figure FDA0003236329770000051
Price negotiation model based on the rubenstanen model:
the shared energy storage adopts a linear quotation strategy, negotiation is carried out between the shared energy storage and the thermal power generating unit according to unit price, and the maximum negotiation return is set as kmaxSharing the stored energy i priceThe grid acceptance range is
Figure FDA0003236329770000052
Minimum accepted price
Figure FDA0003236329770000053
Cost associated with sharing energy storage frequency modulation, cost of energy storage single frequency modulation
Figure FDA0003236329770000054
Namely the loss cost of the energy storage battery, and the equivalent charge-discharge cycle number n can be usedeqThe calculation is carried out, and the price negotiation model is as follows:
Figure FDA0003236329770000055
Figure FDA0003236329770000056
Figure FDA0003236329770000057
Figure FDA0003236329770000058
in the formula, CinOne-time investment cost; cmaFor operating maintenance costs; n is a radical offailThe maximum charge-discharge cycle number is obtained; r isi minAnd ri maxRespectively representing the lowest expected yield and the highest expected yield of the shared energy storage i, wherein k is the current negotiation turn;
the thermal power generating unit constructs a quotation interval according to the highest yield and the lowest yield expected by the thermal power generating unit
Figure FDA0003236329770000059
A correction quotation strategy considering the transaction completion degree and the transaction rounds is adopted, the transaction completion degree x is defined as the ratio of the purchased stored energy of the thermal power generating unit to the maximum demand of the thermal power generating unit, and the thermal power generating unit can expect to achieve the transaction completion degree x in different transaction rounds T; when the thermal power generating unit does not reach the expected transaction completion degree under the current transaction turn, the thermal power generating unit can increase the price yielding amplitude to increase the transaction probability so as to quickly purchase the stored energy; otherwise, the price yielding amplitude is shortened; by a price correction factor deltajCorrecting a quotation strategy of the thermal power generating unit; the price negotiation model is as follows:
Figure FDA00032363297700000510
Figure FDA0003236329770000061
Figure FDA0003236329770000062
Figure FDA0003236329770000063
in the formula (I), the compound is shown in the specification,
Figure FDA0003236329770000064
respectively representing the lowest expected yield and the highest expected yield of the thermal power generating unit j; Δ RjPurchasing the income obtained by the required maximum capacity energy storage for the thermal power generating unit j; phi is ajThe influence factor constant represents the influence degree of the j quotation strategy of the thermal power generating unit under the market trading condition; m istAnd the quantity of stored energy purchased for the t-th round of the thermal power generating unit.
5. The shared energy storage combined frequency modulation trading method based on the blockchain and decentralized trading theory according to claim 1, characterized in that: the optimal purchasing decision model of the thermoelectric generator set in the step 4 is as follows:
if the shared energy storage offer is lower than the offer of the thermal power generating unit, the negotiation between the two parties is considered to be successful, and the transaction price after the price negotiation in the k rounds is obtained
Figure FDA0003236329770000065
Comprises the following steps:
Figure FDA0003236329770000066
the thermal power generating unit determines whether final transaction is carried out or not according to the maximum profit, and the total purchase amount does not exceed the maximum demand amount; for the successfully negotiated shared energy storage i, the thermal power generating unit j can finally decide to sign or reject according to the extra income and the transaction price thereof by taking the maximization of the income as a target, wherein the optimal purchasing strategy is represented as:
Figure FDA0003236329770000067
Figure FDA0003236329770000068
in the formula (f)jThe method comprises the steps of obtaining a frequency modulation performance growth function of a thermal power generating unit j; x is the number ofi,tIndicating whether the thermal power generating unit purchases the stored energy i, x in the t round of transactioni,t∈{0,1}。
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