CN111724040B - Frequency modulation service cross-chain transaction method considering participation of high-energy-consumption user - Google Patents

Frequency modulation service cross-chain transaction method considering participation of high-energy-consumption user Download PDF

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CN111724040B
CN111724040B CN202010457521.5A CN202010457521A CN111724040B CN 111724040 B CN111724040 B CN 111724040B CN 202010457521 A CN202010457521 A CN 202010457521A CN 111724040 B CN111724040 B CN 111724040B
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沈鑫
熊峻
谭太洋
余恒洁
赵静
骆钊
李玲芳
朱欣春
陈义宣
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Abstract

The invention relates to a frequency modulation service cross-link trading method considering high-energy-consumption user participation, which comprises the following steps: step 10) researching a frequency modulation service transaction mechanism based on a block chain technology and considering participation of high-energy-consumption users; step 20) designing a clearing method of frequency modulation risks of the high-energy-consumption user according to a trading mechanism due to the fact that the actual response of the high-energy-consumption user is deviated from the expected value of the frequency modulation, and introducing a CVaR method to quantify the risk degree of the high-energy-consumption user participating in the frequency modulation market; step 30) establishing an exchange process on a frequency modulation service chain based on the chain code; step 40), taking an IEEE14 node system as an example, simulating 1: 00-0: 00 (next day), analyzing the influence of frequency modulation risk on clearing result and frequency modulation compensation cost cross-link allocation.

Description

Frequency modulation service cross-chain transaction method considering participation of high-energy-consumption user
Technical Field
The invention relates to a frequency modulation service cross-link trading method considering high-energy consumer participation, and belongs to the technical field of power system frequency modulation services.
Background
In recent years, China accelerates the construction pace of the frequency modulation auxiliary service market and brings out market reformation supported by multiple policies. By the end of 2019, frequency modulation markets of 6 provinces (regions, cities and regions) such as Shandong, Shanxi and Guangdong are put into operation (including simulation operation and trial operation), and are jointly operated with a main energy spot market, an auxiliary service system meeting the reform requirement of the Chinese power market is actively constructed, and certain market operation experience is accumulated.
At present, market participants of Chinese frequency modulation auxiliary service are mainly various power generation resources, objects from frequency modulation service providers to frequency modulation service cost sharing belong to power generation sides, and the unilateral market obviously cannot adapt to development requirements and is in contradiction to the fair principle of trading. The block chain is used as a decentralized trading technology, academic communities have shown application of the technology in the power market and obtained related applications, such as load power utilization response and intelligent power distribution and sale trading, but the application of the block chain technology in combination with the frequency modulation market is rarely discussed, and the potential of the block chain in promoting digital upgrading and governing of the frequency modulation market needs to be mined.
Disclosure of Invention
With the development of the frequency modulation auxiliary service market, the problem that the user side cannot fully participate in the frequency modulation market is increasingly highlighted, and the two aspects of frequency modulation service and frequency modulation compensation cost are shared. In order to solve the technical problems, the invention provides a frequency modulation service cross-link trading method considering high-energy-consumption user participation, and the problems of opaque responsibility determination, low trading efficiency and the like in a frequency modulation market are effectively solved.
The technical scheme of the invention is as follows: a frequency modulation service cross-link transaction method considering high-energy-consumption user participation comprises the following steps:
step 10) researching a frequency modulation service transaction mechanism considering participation of high-energy-consumption users based on a block chain technology;
step 20) designing a clearing method of the frequency modulation risk of the high-energy-consumption user according to a trading mechanism due to the fact that the actual response of the high-energy-consumption user is deviated from the expected Value of the frequency modulation, and introducing a CVaR (condition Value at Risk) method to quantify the risk degree of the high-energy-consumption user participating in the frequency modulation market;
step 30) establishing an exchange flow on the frequency modulation service chain based on the chain code, so that the high efficiency and the public transparency of the frequency modulation service exchange are realized;
step 40), taking an IEEE14 node system as an example, simulating 1: 00-0: 00 (next day), analyzing the influence of frequency modulation risk on clearing results and frequency modulation compensation cost cross-chain allocation.
The specific construction process of researching the frequency modulation service transaction mechanism based on the blockchain technology and considering the participation of the high-energy-consumption user in the step 10) is as follows:
step 101) carrying out feasibility analysis of high-energy users participating in the frequency modulation market, bringing the high-energy industrial users into the frequency modulation service market, and considering the following three aspects:
step 1011) from the current frequency modulation service market in China, a power generation side is adopted to share all frequency modulation responsibilities, and the zero-sum game of the power generation side improves the operation cost of a power generator;
step 1012) the high-energy-consumption user has the characteristics of high power consumption occupation ratio on the load side, large capacity, high power consumption and the like, and plays a role in absorbing renewable energy;
step 1013), DR of a high-energy-consumption user has a considerable frequency modulation potential, a frequency modulation service market is opened at the load side, frequency modulation resources of the type are preferentially developed as frequency modulation service providers, and the actual needs of the frequency modulation auxiliary service market in China are better met.
Step 102) considering a frequency modulation service transaction mechanism participated by a high-energy-consumption user, performing cross-chain transaction, and constructing a frequency modulation service transaction framework based on a relay cross-chain technology.
The specific construction process of the clearing method for researching the frequency modulation risk of the high-energy-consumption user in the step 20) is as follows:
step 201) high-energy consumption user frequency modulation performance risk measurement is carried out.
A CVaR (condition Value at Risk) method is introduced to quantify the risk degree of the high-energy consumer participating in the frequency modulation market. Conditional risk value (CVaR) is an improved risk analysis based on risk value (VaR) and is used to represent the conditional mean of loss over VaR at a certain confidence level.
Risk of frequency modulation for high energy consuming user i
Figure BDA0002509828360000021
Represented by the formula (1):
Figure BDA0002509828360000022
in the formula, f (x)iλ) is a constructed auxiliary function, xiThe scalar quantity in the frequency modulation mileage of the high-energy consumer i, the optimization result of lambda is defined as the VaR value of the frequency modulation operation cost of the high-energy consumer, theta is the confidence coefficient,
Figure BDA0002509828360000023
is (a)p1，p2，……p) The method is characterized in that the frequency modulation comprehensive index of a high-energy consumer i is obtained under historical data, and the historical data is obtained by applying an AGC test to a scheduling mechanism by the high-energy consumer.
The overall risk of g users with high energy consumption entering the frequency modulation market is shown in equation (2):
Figure BDA0002509828360000031
the risk metric constraint for high energy consumer participation in fm services is as follows:
the risk value constraint is as shown in equation (3):
Figure BDA0002509828360000032
the risk value is not a negative constraint as shown in equation (4):
0≤Sz,z＝1,2,…H (4)
in the formula, the risk value of the high-energy-consumption user i in the scene z must be smaller than the limit value S allowed by the market in the corresponding scene systemz。
Step 202) researching a market clearing mechanism for metering the frequency modulation risk of the high-energy-consumption user.
Aiming at the lowest frequency modulation service cost, and assuming that the main energy of the system is cleared, the frequency modulation service market is cleared, and the network loss is ignored, the simplified method is expressed as the following formula (5):
Figure BDA0002509828360000033
in the formula (I), the compound is shown in the specification,
Figure BDA0002509828360000034
the service cost for considering the participation of the high-energy-consumption user in frequency modulation is taken into consideration;
Figure BDA0002509828360000035
is the frequency modulation service capacity cost of the generator set;
Figure BDA0002509828360000036
the cost of frequency modulation capacity for high-energy users;
Figure BDA0002509828360000037
mileage cost for frequency modulation service of the generator set;
Figure BDA0002509828360000038
mileage cost for frequency modulation services for high energy consuming users; η market risk preference coefficient. Wherein the capacity cost can also be expressed as shown in equation (6):
Figure BDA0002509828360000039
in the formulaT is the scheduling time of the transaction day, T is the scheduling time set of the transaction day, j is the node number, and N is the system node set;
Figure BDA00025098283600000310
and
Figure BDA00025098283600000311
respectively corresponding to scalar quantities in the up-down frequency modulation capacity of the generator set on the j node at the time t,
Figure BDA00025098283600000312
and
Figure BDA00025098283600000313
respectively corresponding to the bid price of the upper and lower frequency modulation capacity on the j node at the time t;
Figure BDA00025098283600000314
respectively corresponding to scalar quantities in the up-down frequency modulation capacity of the high-energy consumption user on the node at the time t,
Figure BDA00025098283600000315
and
Figure BDA00025098283600000316
and respectively corresponding to the bid prices of the upper and lower frequency modulation capacities of the high energy consumption users on the node j at the time t.
The service cost of the fm mileage is expressed as follows:
Figure BDA0002509828360000041
in the formula (I), the compound is shown in the specification,
Figure BDA0002509828360000042
respectively corresponding to scalar quantities in the up-down frequency modulation mileage and the down-down frequency modulation mileage of the generator set on the j node at the time t;
Figure BDA0002509828360000043
Figure BDA0002509828360000044
respectively corresponding to scalar quantities in the up-down frequency modulation mileage of the high-energy consumption user on the j node at the time t;
Figure BDA0002509828360000045
and
Figure BDA0002509828360000046
respectively corresponding to the bidding prices of the up-frequency-modulation mileage and the down-frequency-modulation mileage of the generator set on the j node at the time t;
Figure BDA0002509828360000047
and
Figure BDA0002509828360000048
and respectively corresponding to the upper and lower frequency-modulated mileage bidding prices of the high-energy-consumption user on the node j at the time t.
The constraints of the transaction method are classified into the following categories, as shown in equations (8) to (11):
Figure BDA0002509828360000049
Figure BDA00025098283600000410
Figure BDA00025098283600000411
Figure BDA00025098283600000412
in the formula (I), the compound is shown in the specification,
Figure BDA00025098283600000413
and
Figure BDA00025098283600000414
the maximum limit values of the upper and lower frequency modulation capacities of the high energy consumption users on the j node at the time t respectively correspond to the maximum limit values of the upper and lower frequency modulation capacities of the high energy consumption users on the j node at the time t;
Figure BDA00025098283600000415
and
Figure BDA00025098283600000416
the minimum limit values of the upper frequency modulation mileage and the lower frequency modulation mileage of the high energy consumption users on the j node at the t moment respectively correspond to the t moment;
Figure BDA00025098283600000417
and
Figure BDA00025098283600000418
respectively corresponding to the maximum limit values of the upper and lower frequency-modulation mileage of the high-energy-consumption user on the j node at the time t;
and 30) establishing an exchange process on the frequency modulation service chain based on the chain code, wherein the exchange process comprises a pre-clearing stage, an intra-day clearing stage and a cost settlement stage.
Step 301) pre-clearing stage
Before 10:00 a day, the market operating organization issues next-day frequency modulation market information, including frequency modulation service providers, frequency modulation responsibility investigation objects, frequency modulation capacity demand values in all periods, frequency modulation mileage quotation ranges, reporting frequency modulation capacity ranges and other requirements.
And (3) 10:00-12:00 a day, the frequency modulation service provider reports the frequency modulation capacity and the frequency modulation mileage price in each time period of 24 hours the day, and the network collection node acquires relevant data and writes the data into a block. The quotation information of the FM service provider is sealed and stored by adopting asymmetric encryption, and Public and Private keys (Private keys) are stored in a key storage address (Keystore _ address) of the chain code.
Before 13:00 a day, the scheduling mechanism carries out day-ahead prearrangement after safety check, and as a result, a boundary condition of a next-day power generation plan is formed, and when the next-day power generation plan is compiled, frequency modulation capacity is reserved for power generation units which win the bid in each time interval prearrangement
Step 302) intraday clearing stage
30 minutes before a clearing starting point T, a private key is distributed to the scheduling mechanism by the chain code, quotation information is decrypted, meanwhile, a network monitoring node records the decryption process of the scheduling mechanism, the scheduling mechanism clears by adopting a method for metering high-energy-consumption user frequency modulation risk, the chain code calls an external commercial solver through an Application Programming Interface (API), calculation is transferred to the lower part of a chain, and security check is carried out.
And continuously inquiring whether the chain code reaches an operation starting point T, if so, starting data writing into the block by the actual load curve and the actual output curve of the power generation side and the high-energy consumer side, simultaneously recording the frequency modulation output data of the frequency modulation service provider in real time and writing into the block, and if not, returning to the clear calculation.
Step 303) fee settlement phase
And completing the sharing of the frequency modulation cost before the next day of 9:00, analyzing the frequency modulation responsibility of the previous transaction day by a scheduling mechanism, sharing in proportion, submitting the sharing result to a verification node and a supervision node for consensus, starting an error quitting and error supplementing link if the consensus fails, and calculating the settlement cost again when the settlement cost of the frequency modulation market is wrong due to related technical support system errors or other reasons to obtain a corrected settlement result and releasing the corrected settlement result to market members in time. And if the settlement consensus is passed, triggering the chain transfer transaction on the chain code.
And the chain code starts cross-chain transaction, the name-giving node in the network locks the account address ResAccount _ a and the amount Vol of the frequency modulation responsible party on the previous transaction day according to the frequency modulation responsibility analysis result of the scheduling mechanism, and simultaneously the name-giving node locks the account address SerACCount _ b of the frequency modulation service provider to complete cross-chain payment transaction.
And paying by the frequency modulation responsible party, sending a response signal ReceiptMess after the frequency modulation service provider receives the frequency modulation compensation fee, verifying the response signal output by the account address provided by all the nomination nodes by the verification node, packaging the transaction and writing the transaction into a block, and finishing the frequency modulation transaction.
The invention has the beneficial effects that: the invention applies the cross-link transaction technology in the block chain to the frequency modulation market, can effectively solve the problems of opaque responsibility determination, low transaction efficiency and the like in the frequency modulation market, realizes the completion of frequency modulation service transaction from clearing to settlement in the day, and improves the transaction efficiency and the openness and transparency.
Drawings
Fig. 1 is a chain code flow chart of a frequency modulation service cross-chain transaction method considering high-energy consumption user participation according to the present invention;
FIG. 2 is a schematic diagram of an IEEE14 node system according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating a bid amount result according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the frequency modulation capacity clearing result of Case1 in the embodiment of the present invention;
FIG. 5 is a schematic diagram of the frequency modulation capacity clearing result of Case2 in the embodiment of the present invention;
FIG. 6 is a schematic diagram of the frequency-modulated mileage clearing result of Case1 in the embodiment of the present invention;
FIG. 7 is a schematic diagram of the frequency-modulated mileage clearing result of Case2 in the embodiment of the present invention;
FIG. 8 is a diagram illustrating account information prior to a transaction in accordance with an embodiment of the present invention;
FIG. 9 is a diagram illustrating FM cost transfer records in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments, but not all embodiments, of the present invention; all other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1: as shown in fig. 1to 9, a cross-link trading method for fm service considering high energy consumption user participation includes the following steps:
step 10) researching a frequency modulation service transaction mechanism considering participation of high-energy-consumption users based on a block chain technology;
step 20) designing a clearing method of the frequency modulation risk of the high-energy-consumption user according to a trading mechanism due to the fact that the actual response of the high-energy-consumption user is deviated from the expected Value of the frequency modulation, and introducing a CVaR (condition Value at Risk) method to quantify the risk degree of the high-energy-consumption user participating in the frequency modulation market;
and step 30) establishing an exchange process on the frequency modulation service chain based on the chain code, so that the high efficiency and the public transparency of the frequency modulation service exchange are realized.
Step 40), taking an IEEE14 node system as an example, simulating 1: 00-0: 00 (next day), analyzing the influence of frequency modulation risk on clearing results and frequency modulation compensation cost cross-chain allocation.
The specific construction process of researching the frequency modulation service transaction mechanism based on the blockchain technology and considering the participation of the high-energy-consumption user in the step 10) is as follows:
step 101) carrying out feasibility analysis of high-energy users participating in the frequency modulation market, bringing the high-energy industrial users into the frequency modulation service market, and considering the following three aspects:
step 1011) from the current frequency modulation service market in China, a power generation side is adopted to share all frequency modulation responsibilities, and the zero-sum game of the power generation side improves the operation cost of a power generator;
step 1012) the high-energy-consumption user has the characteristics of high power consumption occupation ratio on the load side, large capacity, high power consumption and the like, and plays a role in absorbing renewable energy;
step 1013), DR of a high-energy-consumption user has a considerable frequency modulation potential, a frequency modulation service market is opened at the load side, frequency modulation resources of the type are preferentially developed as frequency modulation service providers, and the actual needs of the frequency modulation auxiliary service market in China are better met.
Step 102) considering a frequency modulation service transaction mechanism participated by a high-energy-consumption user, performing cross-chain transaction, and constructing a frequency modulation service transaction framework based on a relay cross-chain technology.
The specific construction process of the clearing method for researching the frequency modulation risk of the high-energy-consumption user in the step 20) is as follows:
step 201) high-energy consumption user frequency modulation performance risk measurement is carried out.
A CVaR (condition Value at Risk) method is introduced to quantify the risk degree of the high-energy consumer participating in the frequency modulation market. Conditional risk value (CVaR) is an improved risk analysis based on risk value (VaR) and is used to represent the conditional mean of loss over VaR at a certain confidence level.
Risk of frequency modulation for high energy consuming user i
Figure BDA0002509828360000071
Represented by the formula (1):
Figure BDA0002509828360000072
in the formula, f (x)iλ) is a constructed auxiliary function, xiThe scalar quantity in the frequency modulation mileage of the high-energy consumer i, the optimization result of lambda is defined as the VaR value of the frequency modulation operation cost of the high-energy consumer, theta is the confidence coefficient,
Figure BDA0002509828360000073
is (a)p1，p2，……p) The method is characterized in that frequency modulation comprehensive indexes of a high-energy consumer i are obtained under historical data, and the historical data is obtained by applying AGC tests to a scheduling mechanism by the high-energy consumer.
The overall risk of g high-energy users entering the frequency modulation market is shown in formula (2):
Figure BDA0002509828360000074
the risk metric constraint for high-energy users to participate in frequency modulation services is as follows:
the risk value constraint is shown in equation (3):
Figure BDA0002509828360000075
the risk value is not a negative constraint as shown in equation (4):
0≤Sz,z＝1,2,…H (4)
where a high energy consuming user i is in scene zMust be less than the market-allowed limit S in the corresponding scenario systemz。
Step 202) researching a market clearing mechanism for metering the frequency modulation risk of the high-energy-consumption user.
Aiming at the lowest frequency modulation service cost, and assuming that the main energy of the system is cleared, the frequency modulation service market is cleared, and the network loss is ignored, the simplified method is expressed as the following formula (5):
Figure BDA0002509828360000081
in the formula (I), the compound is shown in the specification,
Figure BDA0002509828360000082
the service cost of high-energy-consumption users participating in frequency modulation is considered;
Figure BDA0002509828360000083
is the frequency modulation service capacity cost of the generator set;
Figure BDA0002509828360000084
the cost of frequency modulation capacity for high-energy users;
Figure BDA0002509828360000085
mileage cost for frequency modulation service of the generator set;
Figure BDA0002509828360000086
mileage cost for frequency modulation services for high energy consuming users; η market risk preference coefficient. Wherein the capacity cost can also be expressed as shown in equation (6):
Figure BDA0002509828360000087
in the formula, T is the scheduling time of a transaction day, T is the scheduling time set of the transaction day, j is the node number, and N is the system node set;
Figure BDA0002509828360000088
and
Figure BDA0002509828360000089
respectively corresponding to scalar quantities in the up-down frequency modulation capacity of the generator set on the j node at the time t,
Figure BDA00025098283600000810
and
Figure BDA00025098283600000811
respectively corresponding to the bid prices of the upper and lower frequency modulation capacity on the j node at the time t;
Figure BDA00025098283600000812
respectively corresponding to scalar quantities in the up-down frequency modulation capacity of the high-energy consumption user on the node at the time t,
Figure BDA00025098283600000813
and
Figure BDA00025098283600000814
and respectively corresponding to the bid prices of the upper and lower frequency modulation capacities of the high energy consumption users on the node j at the time t.
The service cost of the frequency-modulated mileage is expressed as shown in equation (7):
Figure BDA00025098283600000815
in the formula (I), the compound is shown in the specification,
Figure BDA00025098283600000816
respectively corresponding to scalar quantities in the up-down frequency modulation mileage and the down-down frequency modulation mileage of the generator set on the j node at the time t;
Figure BDA00025098283600000817
Figure BDA00025098283600000818
respectively corresponding to scalar quantities in the up-down frequency modulation mileage of the high-energy consumption user on the j node at the time t;
Figure BDA00025098283600000819
and
Figure BDA00025098283600000820
respectively corresponding to the bidding prices of the up-frequency-modulation mileage and the down-frequency-modulation mileage of the generator set on the j node at the time t;
Figure BDA00025098283600000821
and
Figure BDA00025098283600000822
and respectively corresponding to the upper and lower frequency-modulated mileage bidding prices of the high-energy-consumption user on the node j at the time t.
The constraints of the transaction method are classified into the following categories, as shown in equations (8) to (11):
Figure BDA00025098283600000823
Figure BDA00025098283600000824
Figure BDA00025098283600000825
Figure BDA00025098283600000826
in the formula (I), the compound is shown in the specification,
Figure BDA00025098283600000827
and
Figure BDA00025098283600000828
respectively corresponding to the maximum limit values of the upper and lower frequency modulation capacities of the high energy consumption users on the j node at the time t;
Figure BDA00025098283600000829
and
Figure BDA00025098283600000830
respectively corresponding to the upper and lower frequency modulation mileage minimum limit values of the high energy consumption user on the j node at the time t;
Figure BDA00025098283600000831
and
Figure BDA00025098283600000832
respectively corresponding to the maximum limit values of the upper and lower frequency-modulation mileage of the high-energy-consumption user on the j node at the time t;
and in the step 30), an exchange process on the frequency modulation service chain based on the chain code is researched, wherein the exchange process comprises a pre-clearing stage, a daily clearing stage and a cost settlement stage.
Step 301) pre-clearing stage
Before 10:00 a day, the market operating organization issues next-day frequency modulation market information, including frequency modulation service providers, frequency modulation responsibility expedition objects, frequency modulation capacity demand values of all periods, frequency modulation mileage quotation ranges, reporting frequency modulation capacity ranges and other requirements.
And (3) 10:00-12:00 a day, the frequency modulation service provider reports the frequency modulation capacity and the frequency modulation mileage price in each time period of 24 hours the day, and the network collection node acquires relevant data and writes the data into a block. The quotation information of the FM service provider is sealed and stored by adopting asymmetric encryption, and Public and Private keys (Private keys) are stored in a key storage address (Keystore _ address) of the chain code.
Before 13:00 a day, the scheduling mechanism carries out day-ahead prearrangement after safety check, and as a result, a boundary condition of a next-day power generation plan is formed, and when the next-day power generation plan is compiled, frequency modulation capacity is reserved for power generation units which win the bid in each time interval prearrangement
Step 302) intraday clearing stage
30 minutes before a clearing starting point T, a private key is distributed to the scheduling mechanism by the chain code, quotation information is decrypted, meanwhile, a network monitoring node records the decryption process of the scheduling mechanism, the scheduling mechanism clears by adopting a method for metering high-energy-consumption user frequency modulation risk, the chain code calls an external commercial solver through an Application Programming Interface (API), calculation is transferred to the lower part of a chain, and security check is carried out.
And continuously inquiring whether the chain code reaches an operation starting point T, if so, starting data writing into the block by the actual load curve and the actual output curve of the power generation side and the high-energy consumer side, simultaneously recording the frequency modulation output data of the frequency modulation service provider in real time and writing into the block, and if not, returning to the clear calculation.
Step 303) fee settlement phase
And completing the sharing of the frequency modulation cost before the next day of 9:00, analyzing the frequency modulation responsibility of the previous transaction day by a scheduling mechanism, sharing in proportion, submitting the sharing result to a verification node and a supervision node for consensus, starting an error quitting and error supplementing link if the consensus fails, and calculating the settlement cost again when the settlement cost of the frequency modulation market is wrong due to related technical support system errors or other reasons to obtain a corrected settlement result and releasing the corrected settlement result to market members in time. And if the settlement consensus is passed, triggering the chain transfer transaction on the chain code.
And the chain code starts cross-chain transaction, the name-giving node in the network locks the account address ResAccount _ a and the amount Vol of the frequency modulation responsible party on the previous transaction day according to the frequency modulation responsibility analysis result of the scheduling mechanism, and simultaneously the name-giving node locks the account address SerACCount _ b of the frequency modulation service provider to complete cross-chain payment transaction.
And paying by the frequency modulation responsible party, sending a response signal ReceiptMess after the frequency modulation service provider receives the frequency modulation compensation fee, verifying the response signal output by the account address provided by all the nomination nodes by the verification node, packaging the transaction and writing the transaction into a block, and finishing the frequency modulation transaction.
Specifically, in this embodiment, an IEEE14 node system is taken as an example, and the structure is shown in fig. 2, which simulates 1: 00-0: 00 (next day), setting high-energy-consumption users HL9, HL12 and HL13 at nodes 9, 12 and 13, wherein the nodes G1, G2, G3, G6 and G8 are conventional frequency modulation units. The upper and lower frequency modulation mileage quotation range (element/MW) is 3-15 (element/MW), the upper and lower frequency modulation capacity quotation range is 7-20 (element/MW), and the minimum unit of the declared price is 0.1 element/MW.
Two scenarios are set to comparatively analyze the influence of the frequency modulation risk of the high-energy-consumption user in the transaction:
case 1: in spite of the frequency modulation risk of high-energy-consumption users, it is assumed herein that the frequency modulation performance comprehensive indexes of the normal units G1, G2, G3, G6 and G8 are respectively 0.9, 0.8, 0.6, 0.7 and 0.5, and the frequency modulation performance comprehensive indexes of HL9, HL12 and HL13 are respectively 0.75, 0.7 and 0.8.
Case 2: considering the frequency modulation risk of a high-energy user, the frequency modulation performance comprehensive index of a conventional unit is unchanged, adopting a Monte Carlo simulation method for the frequency performance index of the high-energy user, and simulating 8000 groups of frequency modulation test data for the user to obtain a corresponding probability density function. Under the condition that the confidence coefficient is 95%, the frequency modulation performance comprehensive indexes of all users approximately meet normal distribution, namely N (0.8,0.3) (0.7,0.4) and N (0.6, 0.3), the frequency modulation performance comprehensive indexes of HL9, HL12 and HL13 are considered to be 0.8, 0.7 and 0.6 with the probability of 0.95.
The chain code calls a commercial solver Gurobe clearing calculation through API, the quoted clearing result is shown in an attached figure 3, analysis shows that the change trend of the capacity clearing price and the mileage clearing price is consistent with the change trend of the frequency modulation capacity demand in the system on the trading day, the frequency modulation peak load process is started, the frequency modulation clearing average price is increased, the frequency modulation clearing price is increased when the frequency modulation resource enters valley load, and the shortage that the market compensates the opportunity cost of the frequency modulation resource is reflected.
The frequency modulation capacity clearing results of Case1 and Case2 are shown in the attached figures 4 and 5, the frequency modulation capacity needs to have high energy consumption user winning capacity only in the peak load period, and most of the rest needs are still borne by the conventional units G1, G2, G3 and G8. In terms of fm capacity, the market position of high energy consumers is a supplemental support for capacity. Comparing fig. 6 and fig. 7, it can be seen that the bid amount of the frequency modulation capacity of the high energy consuming users in Case2 is obviously reduced under the condition of counting the frequency modulation risk, and the total bid amount of the capacities of HL9, HL12 and HL13 is reduced by 49.5%, 52.4% and 56.5% compared with that of Case 1.
The frequency-modulated mileage clearing results of the Case1 and the Case2 are shown in the attached drawings 6 and 7, the peak-valley time of the frequency-modulated mileage requirement is different from the frequency-modulated capacity, and the peak-valley transition period of the main energy requirement occurs when the frequency-modulated mileage requirement is increased. Compared with the frequency modulation capacity requirement, the frequency modulation mileage clearing result shows that the conventional unit still bears the main frequency modulation mileage requirement, high-energy consumption users obtain a medium scalar quantity with a higher proportion, three high-energy consumption users have winning bid in each transaction period in Case1, but in Case2, the winning bid quantity of the high-energy consumption users is seriously shrunk, and the total winning bid quantities of the capacities of HL9, HL12 and HL13 are reduced by 45.8%, 67.3% and 94.6% in a same ratio. Therefore, the influence of frequency modulation risks on the distribution of frequency modulation mileage is more obvious, and the worse the frequency modulation comprehensive index is, the middle scalar quantity is greatly reduced in the market for counting the frequency modulation risks.
Secondly, considering cross-chain allocation of frequency modulation compensation cost, analyzing and calculating according to the frequency modulation responsibility of the current day, and allocating coefficients of each unit and high-energy-consumption users are shown in table 1. Assuming that the conversion rate of Token and renminbi is 1Token to 1 yuan, the transaction is realized on the Z-leader platform, and the account information before the transaction is shown in fig. 8. The fm fee chain settlement table 2 shows.
TABLE 1 analytical results of frequency modulation responsibilities
Figure BDA0002509828360000111
TABLE 2 frequency modulation cost statistics
Up-modulation capacity charge (Token) 18846
Lower frequency modulation capacity charge (Token) 17655
Up frequency mileage charge (Token) 15781
Lower frequency-modulation mileage charge (Token) 18734
Total (Token) 71016
The obtained fm fee transfer record is shown in fig. 9, the transaction list contains a unique hash value (TxHash), a Token for the transaction, a transaction chain code is developed based on Go language, the state of the transaction is also shown, 8 transactions are all valid, and Org1MSP node in the network performs trust endorsement for each transaction. G1, G2, G3, G6, G8, HL9, HL12 and HL13 all transfer Token to a common Hash address (ic7b43f06baedb620c5af70f3d290fe85cd1a29c5), namely, the address on the dispatching relay chain, and then the cost is distributed according to the actual output of frequency modulation, so that the settlement period of the frequency modulation cost is shortened to the day.
The invention provides a frequency modulation service cross-chain trading method considering participation of high-energy-consumption users, which constructs a frequency modulation market cross-chain trading method of high-energy-consumption users by relying on a block chain technology under the condition of counting frequency modulation risks of the high-energy-consumption users, and explains through a calculation example: 1. the risk of high-energy users participating in the frequency modulation market directly affects the self income, and the frequency modulation service providers pay attention to the improvement of the self frequency modulation performance. 2. The introduction of the trading method enables the user side to play the 'dual role' of a server and a distributor in the frequency modulation market, and the participation degree of the user side in the market is deepened. 3. The cross-link trading technology realizes the digital transformation of the frequency modulation auxiliary service market in the aspects of information evidence storage, frequency modulation data storage and the like of trading. 4. The block chain technology power-assisted scheduling mechanism improves the public transparency of the whole market while the supervision and control of the frequency modulation market.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.

Claims (2)

1. A frequency modulation service cross-link transaction method considering high-energy-consumption user participation is characterized in that: the method comprises the following steps:
step 10) researching a frequency modulation service transaction mechanism considering participation of high-energy-consumption users based on a block chain technology;
step 20) designing a clearing method of frequency modulation risks of high-energy-consumption users according to a trading mechanism, and introducing a Condition Value at Risk method, CVaR (short for CVaR) method, to quantify the Risk degree of the high-energy-consumption users participating in the frequency modulation market;
step 30) establishing an exchange process on a frequency modulation service chain based on the chain code;
step 40) analyzing the influence of the frequency modulation risk on the clear result and the cross-chain allocation of the frequency modulation compensation cost;
the specific construction process of the clearing method for researching the frequency modulation risk of the high-energy-consumption user in the step 20) is as follows:
step 201) carrying out high-energy consumption user frequency modulation performance risk measurement;
a CVaR method is introduced to quantify the risk degree of the high-energy consumer participating in the frequency modulation market; conditional risk value CVaR is an improved risk analysis based on the risk value VaR to represent the conditional mean of loss over VaR at a certain confidence level:
risk of frequency modulation for high energy consuming user i
Figure FDA0003614480770000011
Represented by the formula (1):
Figure FDA0003614480770000012
in the formula, f (x)iλ) is a constructed auxiliary function, xiScalar quantity in frequency modulation mileage of high-energy consumer i, and optimization result of lambda is defined as frequency modulation operation cost of high-energy consumerThe value of VaR, theta is the confidence level,
Figure FDA0003614480770000015
is (K)p1，Kp2，......KpH) The method is characterized in that frequency modulation comprehensive indexes of a high-energy consumer i are obtained under H pieces of historical data, and the historical data are obtained by requesting an AGC test from the high-energy consumer to a scheduling mechanism;
the overall risk of g users with high energy consumption entering the frequency modulation market is shown in equation (2):
Figure FDA0003614480770000013
the risk metric constraint for high energy consumer participation in fm services is as follows:
the risk value constraint is as shown in equation (3):
Figure FDA0003614480770000014
the risk value is not a negative constraint as shown in equation (4):
0≤Sz，z＝1，2，…H (4)
in the formula, the risk value of the high-energy-consumption user i in the scene z must be smaller than the limit value S allowed by the market in the corresponding scene systemz；
Step 202) researching and designing a market clearing mechanism with high-energy user frequency modulation risk;
aiming at the lowest frequency modulation service cost, and assuming that the main energy of the system is cleared, the frequency modulation service market is cleared, and the network loss is ignored, the simplified method is expressed as the following formula (5):
Figure FDA0003614480770000021
in the formula (I), the compound is shown in the specification,
Figure FDA0003614480770000022
the service cost of high-energy-consumption users participating in frequency modulation is considered;
Figure FDA0003614480770000023
is the frequency modulation service capacity cost of the generator set;
Figure FDA0003614480770000024
the cost of frequency modulation capacity for high-energy users;
Figure FDA0003614480770000025
mileage cost for frequency modulation service of the generator set;
Figure FDA0003614480770000026
mileage cost for frequency modulation services for high energy consuming users; η market risk preference coefficient, where the capacity cost can also be expressed as shown in equation (6):
Figure FDA0003614480770000027
in the formula, T is the scheduling time of a transaction day, T is the scheduling time set of the transaction day, j is the node number, and N is the system node set;
Figure FDA0003614480770000028
and
Figure FDA0003614480770000029
respectively corresponding to scalar quantities in the up-down frequency modulation capacity of the generator set on the j node at the time t,
Figure FDA00036144807700000210
and
Figure FDA00036144807700000211
respectively corresponding to the bid prices of the upper and lower frequency modulation capacity on the j node at the time t;
Figure FDA00036144807700000212
respectively corresponding to scalar quantities in the up-down frequency modulation capacity of the high-energy consumption user on the node at the time t,
Figure FDA00036144807700000213
and
Figure FDA00036144807700000214
respectively corresponding to the bid prices of the upper and lower frequency modulation capacities of the high energy consumption users on the j node at the time t;
the service cost of the frequency-modulated mileage is expressed as shown in equation (7):
Figure FDA00036144807700000215
in the formula (I), the compound is shown in the specification,
Figure FDA00036144807700000216
respectively corresponding to scalar quantities in the up-down frequency modulation mileage and the down-down frequency modulation mileage of the generator set on the j node at the time t;
Figure FDA00036144807700000217
Figure FDA00036144807700000218
respectively corresponding to scalar quantities in the up-down frequency modulation mileage of the high-energy consumption user on the j node at the time t;
Figure FDA00036144807700000219
and
Figure FDA00036144807700000220
respectively corresponding to the bidding prices of the up-frequency-modulation mileage and the down-frequency-modulation mileage of the generator set on the j node at the time t;
Figure FDA00036144807700000221
and
Figure FDA00036144807700000222
respectively corresponding to the upper and lower frequency-modulated mileage bidding prices of the high-energy-consumption user on the node j at the time t:
the constraints of the transaction method are classified into the following categories, as shown in equations (8) to (11):
Figure FDA00036144807700000223
Figure FDA00036144807700000224
Figure FDA00036144807700000225
Figure FDA00036144807700000226
in the formula (I), the compound is shown in the specification,
Figure FDA00036144807700000227
and
Figure FDA00036144807700000228
the maximum limit values of the upper and lower frequency modulation capacities of the high energy consumption users on the j node at the time t respectively correspond to the maximum limit values of the upper and lower frequency modulation capacities of the high energy consumption users on the j node at the time t;
Figure FDA00036144807700000229
and
Figure FDA00036144807700000230
respectively corresponding to the upper and lower frequency modulation mileage minimum limit values of the high energy consumption user on the j node at the time t;
Figure FDA00036144807700000231
and
Figure FDA00036144807700000232
respectively corresponding to the maximum limit values of the upper and lower frequency-modulation mileage of the high-energy-consumption user on the j node at the time t;
researching an exchange process on a frequency modulation service chain based on the chain code in the step 30), wherein the exchange process comprises a pre-clearing stage, a daily clearing stage and a cost settlement stage;
step 301) Pre-flush stage
Before 10:00 a day, a market operating organization issues next-day frequency modulation market information, which comprises a frequency modulation service provider, a frequency modulation responsibility investigation object, frequency modulation capacity demand values of all time periods, a frequency modulation mileage quotation range and a reported frequency modulation capacity range;
the frequency modulation service provider reports the frequency modulation capacity and the frequency modulation mileage price in each time period of 24 hours the day, and the network collection node acquires related data and writes the data into a block; the quotation information of the frequency modulation service provider is sealed and stored in an asymmetric encryption way, and Public and Private keys Public key and Private key are stored in a key storage address Keystore _ address of a chain code;
before 13:00 a day, the scheduling mechanism carries out day-ahead prearrangement after safety check, and as a result, a boundary condition of a next-day power generation plan is formed, and frequency modulation capacity is reserved for power generation units winning a bid in each time interval prearrangement when the next-day power generation plan is compiled;
step 302) intraday clearing stage
30 minutes before clearing the starting point T, the chain code distributes a private key to the scheduling mechanism and decrypts quotation information, meanwhile, a network monitoring node records the decryption process of the scheduling mechanism, the scheduling mechanism clears the private key by adopting a method for counting high energy consumption user frequency modulation risk, the chain code calls an external commercial solver through an Application Programming Interface (API), the calculation is transferred to the lower part of the chain, and security check is carried out;
continuously inquiring whether a chain code reaches an operation starting point T, if so, starting data writing into a block by an actual load curve and an actual output curve of a power generation side and a high-energy consumer side, simultaneously recording frequency modulation output data of a frequency modulation service provider in real time and writing into the block, and if not, returning to clear calculation;
step 303) fee settlement phase
Completing the apportionment of frequency modulation cost before the next day of 9:00, analyzing the frequency modulation responsibility of the previous transaction day by a scheduling mechanism, apportioning according to proportion, submitting the apportionment result to a verification node and a supervision node for consensus, starting a difference quit error-compensating link if the consensus fails, and calculating the settlement cost again when the settlement cost of the frequency modulation market is wrong due to technical support system errors or other reasons to obtain a corrected settlement result and releasing the corrected settlement result to market members in time; if the settlement consensus is passed, triggering chain-crossing transfer transaction on the chain code;
the chain code starts cross-chain transaction, the nomination node in the network locks the account address ResAccount _ a and the amount Vol of the frequency modulation responsible party on the previous transaction day according to the frequency modulation responsibility analysis result of the scheduling mechanism, and simultaneously the nomination node locks the account address SerACCount _ b of the frequency modulation service provider to complete cross-chain payment transaction;
and paying by the frequency modulation responsible party, sending a response signal ReceiptMess after the frequency modulation service provider receives the frequency modulation compensation fee, verifying the response signal output by the account address provided by all the nomination nodes by the verification node, packaging the transaction and writing the transaction into a block, and finishing the frequency modulation transaction.
2. A frequency modulation service cross-chain trading method considering high energy consumption user participation according to claim 1, characterized in that: the specific construction process of researching the frequency modulation service transaction mechanism based on the blockchain technology and considering the participation of the high-energy-consumption user in the step 10) is as follows:
step 101) carrying out feasibility analysis of high-energy consumption users participating in a frequency modulation market, and bringing high-energy consumption industrial users into a frequency modulation service market;
step 102) considering a frequency modulation service transaction mechanism participated by a high-energy-consumption user, performing cross-chain transaction, and constructing a frequency modulation service transaction framework based on a relay cross-chain technology.
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