Main-side chain and side-chain dual-chain interactive power trading interaction method, device and storage medium

Abstract

The present invention discloses a main-chain and side-chain dual-chain interactive power transaction interaction method, device and storage medium, the method comprising: obtaining transaction declaration information of new energy power plants and power users and uploading it to the blockchain main chain; according to the transaction declaration information, with the goal of minimizing the power purchase cost of power users and maximizing the revenue of new energy power plants, calculating the market clearing electricity price and clearing electricity quantity for each time period a day ago and synchronizing them to the side chain; obtaining the power demand of power users in each time period of the day and subtracting the clearing electricity quantity of the corresponding time period a day ago, to obtain the power deviation of the corresponding time period; according to the power deviation of each time period and a preset deviation assessment threshold, determining the buyer user and seller user participating in the deviation transaction in the corresponding time period of the day and the quotation strategy; according to the buyer user and the seller user and the quotation strategy, with the goal of minimizing the cost of absorbing power deviation, calculating the deviation transaction result and synchronizing it to the main chain; the present invention can improve the efficiency and security of transactions.

Description

Technical Field

[0001] The present invention relates to a main-chain and side-chain dual-chain interactive power transaction interaction method, device and storage medium, belonging to the technical field of power market. Background Art

[0002] At present, new energy is in a critical period of transformation from a supplementary power source to a main power source. With the advancement of clean heating construction, electric heating load, as a flexible and adjustable load with time-shifting capability, has great potential in improving the consumption of new energy. Fully tapping the regulation potential of electric heating loads involved in the consumption of new energy can promote the development of the electricity trading market and coordinate the consumption of new energy in a larger energy allocation dimension.

[0003] Building an economical and convenient electricity market mechanism to promote the participation of electricity users such as electric heating in the electricity market and reducing the electricity costs of users through market transactions are the current needs of electricity users. At the same time, through transactions with new energy companies, absorbing new energy is an important measure to improve the level of new energy absorption. The current electricity market is still mainly a centralized trading model, which forms transaction clearing electricity prices and electricity through centralized bidding and matching. At the same time, during the transaction process, users' electricity usage deviations are often punished, which has hidden dangers such as complex calculations, information and transaction insecurity. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings in the prior art, provide a main chain and side chain dual chain interactive power trading method, device and storage medium, establish a main chain and side chain dual chain trading architecture, carry out day-ahead transactions between new energy power plants and power users on the main chain, and carry out intraday deviation transactions between users on the side chain, which can improve transaction efficiency and security.

[0005] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0006] In a first aspect, the present invention provides a main-chain and side-chain dual-chain interactive power trading method, comprising:

[0007] Obtain transaction declaration information of new energy power plants and power users and upload it to the blockchain main chain; the transaction declaration information is the market transaction volume and transaction electricity price for each period of the day before;

[0008] Based on the transaction declaration information, the market clearing electricity price and clearing electricity quantity for each period of the day before are calculated and synchronized to the side chain with the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants;

[0009] Obtain the power demand of the power user in each period of the day and subtract the cleared power of the corresponding period a day ago to obtain the power deviation of the corresponding period;

[0010] According to the power deviation in each period and the preset deviation assessment threshold, determine the buyer and seller users participating in the deviation transaction in the corresponding period of the day and the quotation strategy;

[0011] Based on the buyer and seller users and the quotation strategy, the deviation transaction results are calculated and synchronized to the main chain with the goal of minimizing the cost of absorbing electricity deviation.

[0012] Optionally, the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants includes:

[0013] Construct the function F that minimizes the electricity purchase cost for power users 1 and the profit maximization function F of the new energy power plant 2 ;

[0014] The electricity user's electricity purchase cost minimization function F 1 for:

[0015]

[0016] In the formula, C t is the electricity price purchased by the power user from the grid in time period t, T is the number of time periods, N is the amount of electricity purchased by power user m from the grid during period t, EH is the number of electricity users, λ m,n,t is the price of electricity purchased by power user m from renewable energy power plant n during period t, The amount of electricity purchased by electricity user m from renewable energy power plant n during period t, g m is the loss parameter of the transaction between power user m and the new energy power plant, It is the loss cost incurred by electricity user m when purchasing electricity from the renewable energy power plant during period t.

[0017] The new energy power plant profit maximization function F 2 for:

[0018]

[0019] Where N PC is the number of renewable energy power plants; is the power generation of new energy power plant n in time period t, is the power generation cost of the new energy power plant in period n and t, and a, b, and d are constants.

[0020] Optionally, the power user's power purchase cost minimization function F 1 and the profit maximization function F of the new energy power plant 2 The following constraints are met:

[0021]

[0022]

[0023]

[0024] In the formula, is the maximum power generation of new energy power plant n in time period t; is the maximum amount of electricity purchased by power user m from the grid during time period t; The maximum amount of electricity purchased by power user m from new energy power plant n in time period t;

[0025]

[0026]

[0027] In the formula, is the power demand of power user m in time period t.

[0028] Optionally, the calculation of the day-ahead market clearing electricity price and clearing electricity quantity includes:

[0029] Based on the Lagrangian dual decomposition principle, the function F that minimizes the electricity purchase cost of electricity users is 1 Decomposed into the function F that minimizes the power purchase cost of each power user m :

[0030]

[0031] Based on the Lagrangian dual decomposition principle, the function F that maximizes the revenue of the new energy power plant is 2 Decompose into the profit maximization function F of each new energy power plant n :

[0032]

[0033] Where η t Lagrange multiplier for time period t;

[0034] Combined minimization function F of power user's electricity purchase cost based on subgradient method m and the revenue maximization function F of the new energy power plant n The electricity purchase price model for power users and new energy power plants is obtained:

[0035]

[0036] In the formula, k is the number of iterations of the Lagrange multiplier, and α is the step size coefficient of the gradient descent;

[0037] The electricity purchase price model between power users and new energy power plants is iteratively solved until the electricity purchase price converges and the final electricity purchase price λ is output m，n，t and purchased electricity

[0038] The electricity purchase price convergence satisfies:

[0039] |λ m，n，t [k+1]-λ m，n，t [k]|≤ε

[0040] Where ε is the preset convergence parameter;

[0041] The final electricity purchase price λ m，n，t and purchased electricity As the day-ahead market clearing electricity price and clearing electricity quantity.

[0042] Optionally, the step of determining the buyer users and seller users who participate in the deviation transaction in the corresponding period of the day and the quotation strategy includes:

[0043] The power deviation of power user m in time period t is:

[0044] Δp m，t =p m，pre，t -p m，buy，t

[0045] In the formula, p m，pre，t 、p m，pre，t are the daily demand and day-ahead clearing electricity of power user m in time period t respectively;

[0046] The preset deviation assessment thresholds include the positive deviation threshold Δp p，m，t and negative deviation threshold Δp q，m，t ;

[0047] If Δp m，t >Δp p，m，t , then electricity user m is a buyer user in time period t, and the bidding strategy of electricity user m is:

[0048] ρ m，idbuy，t =λ m，idb u y，t p a，m，t +μ m，idbuy，t

[0049] ρ m，idbuy，t <ρ m，pdev，t

[0050] In the formula, ρ m，idbuy，t 、p a，m，t , m，pdev，t μ is the daily power purchase quotation, daily power purchase quantity, and deviation penalty fee of power user m in time period t; m，idbuy，t is a constant;

[0051] If Δp m，t <Δp q，m，t, then electricity user m is a seller user in time period t, and the bidding strategy of electricity user m is:

[0052] ρ m，idsell，t =λ m，idsell，t p b，m，t +μ m，idsell，t

[0053] ρ m，idsell，t <ρ m，qdev，t

[0054] In the formula, ρ m,idsell,t 、p b,m,t , m,qdev,t μ is the daily electricity sales quotation, daily electricity sales volume, and deviation penalty fee of power user m in time period t; m,idsell,t is a constant.

[0055] Optionally, the calculation deviation transaction result includes:

[0056] Based on the VCG auction rules, the seller users’ daily electricity sales quotations in time period t are sorted from low to high to generate a clearing queue;

[0057] Bid and clear according to the clearing queue until the following conditions are met:

[0058]

[0059]

[0060] In the formula, I and J are the number of buyer users and seller users, p a,i,t is the amount of electricity purchased by buyer user i in time period t, p b,j,t , is the daily electricity sales volume and maximum electricity sales volume of seller user j in time period t;

[0061] Get the winning bid income of the seller who successfully bids and clears the items, and calculate the final transaction price:

[0062]

[0063] Where V j,t is the winning bid revenue of seller user j in period t, ω t is the transaction price in period t;

[0064] The objective function is constructed by minimizing the cost of absorbing the demand deviation electricity of the buyer and seller users:

[0065]

[0066] Based on the minimization of the objective function, the daily electricity purchase amount p of buyer user i in time period t is calculated a,i,t, the daily electricity sales volume p of seller user j in time period t b,j,t and the transaction price ω in period t t .

[0067] In a second aspect, the present invention provides a main-chain and side-chain dual-chain interactive power transaction interactive device, the device comprising:

[0068] The declaration module is used to obtain transaction declaration information of new energy power plants and power users and upload it to the blockchain main chain; the transaction declaration information is the market transaction volume and transaction electricity price for each period of the day before.

[0069] The clearing module is used to calculate the market clearing electricity price and clearing electricity quantity for each period of the day before and synchronize them to the side chain based on the transaction declaration information with the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants;

[0070] The deviation module is used to obtain the power demand of the power user in each period of the day and subtract the cleared power of the corresponding period a day ago to obtain the power deviation of the corresponding period;

[0071] The assessment module is used to obtain the buyer and seller users who participate in the deviation transaction in the corresponding period of the day and the quotation strategy according to the power deviation in each period and the preset deviation assessment threshold;

[0072] The transaction module is used to calculate the deviation transaction results and synchronize them to the main chain based on the buyer and seller users and the quotation strategy with the goal of minimizing the cost of absorbing electricity deviation.

[0073] Optionally, the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants includes:

[0074] Construct the function F that minimizes the electricity purchase cost for power users 1 and the profit maximization function F of the new energy power plant 2 ;

[0075] The electricity user's electricity purchase cost minimization function F 1 for:

[0076]

[0077] In the formula, C t is the electricity price purchased by the power user from the grid in time period t, T is the number of time periods, N is the amount of electricity purchased by power user m from the grid during period t, EH is the number of electricity users, λ m,n,t is the price of electricity purchased by power user m from renewable energy power plant n during period t, The amount of electricity purchased by electricity user m from renewable energy power plant n during period t, g mis the loss parameter of the transaction between power user m and the new energy power plant, It is the loss cost incurred by electricity user m when purchasing electricity from the renewable energy power plant during period t.

[0078] The new energy power plant profit maximization function F 2 for:

[0079]

[0080] Where N PC is the number of renewable energy power plants; is the power generation of new energy power plant n in time period t, is the power generation cost of the new energy power plant in period n and t, and a, b, and d are constants.

[0081] Optionally, the power user's power purchase cost minimization function F 1 and the profit maximization function F of the new energy power plant 2 The following constraints are met:

[0082]

[0083]

[0084]

[0085] In the formula, is the maximum power generation of new energy power plant n in time period t; is the maximum amount of electricity purchased by power user m from the grid during time period t; The maximum amount of electricity purchased by power user m from new energy power plant n in time period t;

[0086]

[0087]

[0088] In the formula, is the power demand of power user m in time period t.

[0089] Optionally, the calculation of the day-ahead market clearing electricity price and clearing electricity quantity includes:

[0090] Based on the Lagrangian dual decomposition principle, the function F that minimizes the electricity purchase cost of electricity users is 1 Decomposed into the function F that minimizes the power purchase cost of each power user m :

[0091]

[0092] Based on the Lagrangian dual decomposition principle, the function F that maximizes the revenue of the new energy power plant is2 Decompose into the profit maximization function F of each new energy power plant n :

[0093]

[0094] Where η t Lagrange multiplier for time period t;

[0095] Combined minimization function F of power user's electricity purchase cost based on subgradient method m and the revenue maximization function F of the new energy power plant n The electricity purchase price model for power users and new energy power plants is obtained:

[0096]

[0097] In the formula, k is the number of iterations of the Lagrange multiplier, and α is the step size coefficient of the gradient descent;

[0098] The electricity purchase price model between power users and new energy power plants is iteratively solved until the electricity purchase price converges and the final electricity purchase price λ is output m，n，t and purchased electricity

[0099] The electricity purchase price convergence satisfies:

[0100] |λ m，n，t [k+1]-λ m，n，t [k]|≤ε

[0101] Where ε is the preset convergence parameter;

[0102] The final electricity purchase price λ m，n，t and purchased electricity As the day-ahead market clearing electricity price and clearing electricity quantity.

[0103] Optionally, the step of determining the buyer users and seller users who participate in the deviation transaction in the corresponding period of the day and the quotation strategy includes:

[0104] The power deviation of power user m in time period t is:

[0105] Δp m，t =p m，pre，t -p m，buy，t

[0106] In the formula, p m，pre，t 、p m，pre，t are the daily demand and day-ahead clearing electricity of power user m in time period t respectively;

[0107] The preset deviation assessment thresholds include the positive deviation threshold Δp p，m，t and negative deviation threshold Δpq，m，t ;

[0108] If Δp m，t >Δp p，m，t , then electricity user m is a buyer user in time period t, and the bidding strategy of electricity user m is:

[0109] ρ m，idbuy，t =λ m，idbuy，t p a，m，t +μ m，idbuy，t

[0110] ρ m，idbuy，t <ρ m，pdev，t

[0111] In the formula, ρ m，idbuy，t 、p a，m，t , m，pdev，t μ is the daily power purchase quotation, daily power purchase quantity, and deviation penalty fee of power user m in time period t; m，idbuy，t is a constant;

[0112] If Δp m，t <Δp q，m，t , then electricity user m is a seller user in time period t, and the bidding strategy of electricity user m is:

[0113] ρ m，idsell，t =λ m，idsell，t p b，m，t +μ m，idsell，t

[0114] ρ m，idsell，t <ρ m，qdev，t

[0115] In the formula, ρ m,idsell,t 、p b,m,t , m,qdev,t μ is the daily electricity sales quotation, daily electricity sales volume, and deviation penalty fee of power user m in time period t; m,idsell,t is a constant.

[0116] Optionally, the calculation deviation transaction result includes:

[0117] Based on the VCG auction rules, the seller users’ daily electricity sales quotations in time period t are sorted from low to high to generate a clearing queue;

[0118] Bid and clear according to the clearing queue until the following conditions are met:

[0119]

[0120]

[0121] In the formula, I and J are the number of buyer users and seller users, p a,i,tis the amount of electricity purchased by buyer user i in time period t, p b,j,t , is the daily electricity sales volume and maximum electricity sales volume of seller user j in time period t;

[0122] Get the winning bid income of the seller who successfully bids and clears the items, and calculate the final transaction price:

[0123]

[0124] Where V j,t is the winning bid revenue of seller user j in period t, ω t is the transaction price in period t;

[0125] The objective function is constructed by minimizing the cost of absorbing the demand deviation electricity of the buyer and seller users:

[0126]

[0127] Based on the minimization of the objective function, the daily electricity purchase amount p of buyer user i in time period t is calculated a,i,t , the daily electricity sales volume p of seller user j in time period t b,j,t and the transaction price ω in period t t .

[0128] In a third aspect, the present invention provides a main-side chain dual-chain interactive power trading interactive device, including a processor and a storage medium;

[0129] The storage medium is used to store instructions;

[0130] The processor is used to operate according to the instructions to execute the steps according to the above method.

[0131] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.

[0132] Compared with the prior art, the present invention has the following beneficial effects:

[0133] The present invention provides a main-chain and side-chain dual-chain interactive power transaction interaction method, device and storage medium, which carry out day-ahead transactions between new energy power plants and power users on the main chain, with the goal of minimizing the power purchase cost of power users and maximizing the revenue of new energy power plants, thereby reducing the power purchase cost of power users and increasing the revenue of new energy power plants; carry out intraday deviation transactions between power users on the side chain, and power users can purchase or sell electricity according to the power consumption of the day, avoiding deviation assessment caused by the adjustment of power consumption plans; solve the data interaction problem through synchronization between the main chain and the side chain, avoid the same chain carrying different businesses, resulting in reduced processing efficiency, thereby improving transaction efficiency; at the same time, based on blockchain interaction, it can improve transaction security. BRIEF DESCRIPTION OF THE DRAWINGS

[0134] Figure 1 This is a flow chart of a main-chain and side-chain dual-chain interactive power trading method provided in Embodiment 1 of the present invention;

[0135] Figure 2 This is a schematic diagram of the day-ahead transaction situation of the main-side dual-chain interaction provided by the first embodiment of the present invention;

[0136] Figure 3 This is a schematic diagram of the winning bid power for deviation transactions of electric heating users provided in the first embodiment of the present invention;

[0137] Figure 4 It is a schematic diagram of day-ahead transaction and intraday transaction prices provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0138] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0139] Embodiment 1:

[0140] like Figure 1 As shown, an embodiment of the present invention provides a main-chain and side-chain dual-chain interactive power trading method, comprising the following steps:

[0141] 1. Obtain transaction declaration information from new energy power plants and power users and upload it to the blockchain main chain; the transaction declaration information includes the market transaction electricity volume and transaction electricity price for each period of the day before.

[0142] The time period is usually set to 15 minutes, dividing a day into 96 time periods.

[0143] The privacy data in the transaction declaration information can be encrypted using a symmetric cryptographic algorithm, and the hash value of the encrypted privacy data can be calculated, and the encrypted transaction declaration information can be packaged and uploaded to the blockchain main chain.

[0144] 2. Based on the transaction declaration information, with the goal of minimizing the electricity purchase cost of power users and maximizing the revenue of new energy power plants, the market clearing electricity price and clearing electricity quantity for each period of the day before are calculated and synchronized to the side chain;

[0145] 2.1. Constructing the function F that minimizes the electricity purchase cost for power users 1 and the profit maximization function F of the new energy power plant 2 ;

[0146] The function F that minimizes the electricity purchase cost of electricity users 1 for:

[0147]

[0148] In the formula, C t is the electricity price purchased by the power user from the grid in time period t, T is the number of time periods, N is the amount of electricity purchased by power user m from the grid during period t, EH is the number of electricity users, λ m,n,t is the price of electricity purchased by power user m from renewable energy power plant n during period t, The amount of electricity purchased by electricity user m from renewable energy power plant n during period t, g m is the loss parameter of the transaction between power user m and the new energy power plant, It is the loss cost incurred by electricity user m when purchasing electricity from the renewable energy power plant during period t.

[0149] 2.2. Revenue maximization function F of new energy power plants 2 for:

[0150]

[0151] Where N PC is the number of renewable energy power plants; is the power generation of new energy power plant n in time period t, is the power generation cost of the new energy power plant in period n and t, and a, b, and d are constants.

[0152] 2.3. Minimization function F of electricity purchase cost for power users 1 and the profit maximization function F of the new energy power plant 2 The following constraints are met:

[0153]

[0154]

[0155]

[0156] In the formula, is the maximum power generation of new energy power plant n in time period t; is the maximum amount of electricity purchased by power user m from the grid during time period t; The maximum amount of electricity purchased by power user m from new energy power plant n in time period t;

[0157]

[0158]

[0159] In the formula, is the power demand of power user m in time period t.

[0160] 2.4. Calculation of the day-ahead market clearing price and clearing quantity includes:

[0161] 2.4.1. Minimize the electricity purchase cost function F based on the Lagrangian dual decomposition principle 1 Decomposed into the function F that minimizes the power purchase cost of each power user m :

[0162]

[0163] 2.4.2. Based on the Lagrangian dual decomposition principle, the function F that maximizes the revenue of the new energy power plant 2 Decompose into the profit maximization function F of each new energy power plant n :

[0164]

[0165] Where η t Lagrange multiplier for time period t;

[0166] 2.4.3. Combined power user electricity purchase cost minimization function F based on subgradient method m and the revenue maximization function F of the new energy power plant n The electricity purchase price model for power users and new energy power plants is obtained:

[0167]

[0168] In the formula, k is the number of iterations of the Lagrange multiplier, and α is the step size coefficient of the gradient descent;

[0169] 2.4.4. Iterate and solve the electricity purchase price model between power users and new energy power plants until the electricity purchase price converges and output the final electricity purchase price λ m,n,t and purchased electricity

[0170] The electricity purchase price convergence meets the following requirements:

[0171] |λ m，n，t [k+1]-λm，n，t [k]|≤ε

[0172] Where ε is the preset convergence parameter;

[0173] 2.4.5. The final power purchase price λ m,n,t and purchased electricity As the day-ahead market clearing electricity price and clearing electricity quantity.

[0174] 3. Obtain the power demand of the power user in each period of the day and subtract the cleared power in the corresponding period a day ago to obtain the power deviation in the corresponding period.

[0175] 4. According to the power deviation in each period and the preset deviation assessment threshold, determine the buyer and seller users participating in the deviation transaction in the corresponding period of the day and the quotation strategy; specifically including:

[0176] 4.1. The power deviation of power user m in time period t is:

[0177] Δp m，t =p m，pre，t -p m，buy，t

[0178] In the formula, p m，pre，t 、p m，pre，t are the daily demand and day-ahead clearing electricity of power user m in time period t respectively;

[0179] 4.2. The preset deviation assessment threshold includes the positive deviation threshold Δp p，m，t and negative deviation threshold Δp q，m，t ;

[0180] 4.3. If Δp m，t >Δp p，m，t , then electricity user m is a buyer user in time period t, and the bidding strategy of electricity user m is:

[0181] ρ m，idbuy，t =λ m，idbuy，t p a，m，t +μ m，idbuy，t

[0182] ρ m，idbuy，t <ρ m，pdev，t

[0183] In the formula, ρ m，idbuy，t 、p a，m，t , m，pdev，t μ is the daily power purchase quotation, daily power purchase quantity, and deviation penalty fee of power user m in time period t; m，idbuy，t is a constant;

[0184] 4.4. If Δp m，t <Δp q，m，t, then electricity user m is a seller user in time period t, and the bidding strategy of electricity user m is:

[0185] ρ m，idsell，t =λ m，idsell，t p b，m，t +μ m，idsell，t

[0186] ρ m，idsell，t <ρ m，qdev，t

[0187] In the formula, ρ m，idsell，t 、p b，m，t , m，qdev，t μ is the daily electricity sales quotation, daily electricity sales volume, and deviation penalty fee of power user m in time period t; m，idsell，t is a constant.

[0188] 5. Based on the buyer and seller users and the quotation strategy, the deviation transaction results are calculated and synchronized to the main chain with the goal of minimizing the cost of absorbing electricity deviation.

[0189] The process of calculating the deviation trading results includes:

[0190] 5.1. Based on the VCG auction rules, the seller users’ daily electricity sales quotations in time period t are sorted from low to high to generate a clearing queue;

[0191] 5.2 Bid and clear according to the clearing queue until the following conditions are met:

[0192]

[0193]

[0194] In the formula, I and J are the number of buyer users and seller users, p a,i,t is the amount of electricity purchased by buyer user i in time period t, p b,j,t , is the daily electricity sales volume and maximum electricity sales volume of seller user j in time period t;

[0195] 5.3. Obtain the winning bid income of the seller who successfully bids and clears the bid, and calculate the final transaction price:

[0196]

[0197] Where V j,t is the winning bid revenue of seller user j in period t, ω t is the transaction price in period t;

[0198] 5.4. The objective function is constructed by minimizing the cost of absorbing the demand deviation electricity of the buyer and seller users:

[0199]

[0200] 5.5. Based on the minimization of the objective function, the daily electricity purchase amount p of the buyer user i in time period t is calculated a,i,t , the daily electricity sales volume p of seller user j in time period t b,j,t and the transaction price ω in period t t .

[0201] In order to verify the above method, a network consisting of 2 wind farms, 3 photovoltaic farms, 2 energy storage users, 3 gas turbine users, 2 electric heating users, and 5 conventional load users is constructed. All resources participate in day-ahead transactions through the main chain, and electric heating users and conventional load users participate in intraday deviation transactions on the side chain.

[0202] Two scenarios, S1 and S2, are set for comparative analysis, where S1 is to conduct deviation transactions between users on the side chain, while S2 is not to conduct deviation transactions between users on the side chain.

[0203] The transaction results of the two scenarios are shown in the following table.

[0204] Table 1 Transaction results in different scenarios

[0205] Scenario Transaction cost (yuan) New energy consumption rate (%) S1 3859967.90 100.00 S2 4029300.83 93.47

[0206] It can be seen that by conducting deviation transactions on the side chain, the impact of electricity forecast deviation is effectively reduced, and the electricity traded with new energy on the previous day is completed within the day, which promotes the consumption of new energy, avoids deviation assessment, and reduces transaction costs.

[0207] The day-ahead trading situation of various resources is as follows: Figure 2 As shown in the figure, WT stands for wind power, PV stands for photovoltaic power, ES stands for energy storage, QGE stands for gas turbine, and DL stands for electric heating.

[0208] The intraday trading situation of electric heating users is as follows Figure 3 As shown. Positive values ​​indicate purchased power, and negative values ​​indicate sold power. Due to the adjustable nature of electric heating, it can flexibly adjust power and change purchase and sale behaviors, which is helpful for conventional load users to avoid transaction deviations caused by load fluctuations.

[0209] The trading prices before and during the day are as follows Figure 4As shown. The price fluctuation of intraday transactions is greater than that of the day before. The price of intraday transactions is higher and lower than that of the day before, reflecting that in a shorter trading cycle, the attribute of electricity as a commodity is more obvious, and the price trend is determined by supply and demand. Combined with the ultra-short-term load forecast, according to the intraday transaction situation, it can be seen that the period when the intraday price is higher than the day before price is basically the same as the period when electric heating users sell electricity. That is to say, during this period, the electricity consumption of conventional load users increases, demand increases, and the electricity price is raised.

[0210] Embodiment 2:

[0211] The embodiment of the present invention provides a main-chain and side-chain dual-chain interactive power transaction interactive device, the device comprising:

[0212] The declaration module is used to obtain transaction declaration information of new energy power plants and power users and upload it to the blockchain main chain; the transaction declaration information is the market transaction volume and transaction electricity price for each period of the day before.

[0213] The clearing module is used to calculate the market clearing electricity price and clearing electricity quantity for each period of the day before and synchronize them to the side chain based on the transaction declaration information with the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants;

[0214] The deviation module is used to obtain the power demand of the power user in each period of the day and subtract the cleared power of the corresponding period a day ago to obtain the power deviation of the corresponding period;

[0215] The assessment module is used to obtain the buyer and seller users who participate in the deviation transaction in the corresponding period of the day and the quotation strategy according to the power deviation in each period and the preset deviation assessment threshold;

[0216] The transaction module is used to calculate the deviation transaction results and synchronize them to the main chain based on the buyer and seller users and the quotation strategy with the goal of minimizing the cost of absorbing electricity deviation.

[0217] Specifically, the goals of minimizing the electricity purchase cost for electricity users and maximizing the profits of new energy power plants include:

[0218] Construct the function F that minimizes the electricity purchase cost for power users 1 and the profit maximization function F of the new energy power plant 2 ;

[0219] The function F that minimizes the electricity purchase cost of electricity users 1 for:

[0220]

[0221] In the formula, C t is the electricity price purchased by the power user from the grid in time period t, T is the number of time periods, N is the amount of electricity purchased by power user m from the grid during period t, EH is the number of electricity users, λ m,n,t is the price of electricity purchased by power user m from renewable energy power plant n during period t, The amount of electricity purchased by electricity user m from renewable energy power plant n during period t, g m is the loss parameter of the transaction between power user m and the new energy power plant, It is the loss cost incurred by electricity user m when purchasing electricity from the renewable energy power plant during period t.

[0222] Renewable energy power plant profit maximization function F 2 for:

[0223]

[0224] Where N PC is the number of renewable energy power plants; is the power generation of new energy power plant n in time period t, is the power generation cost of the new energy power plant in period n and t, and a, b, and d are constants.

[0225] Specifically, the electricity user's electricity purchase cost minimization function F 1 and the profit maximization function F of the new energy power plant 2 The following constraints are met:

[0226]

[0227]

[0228]

[0229] In the formula, is the maximum power generation of new energy power plant n in time period t; is the maximum amount of electricity purchased by power user m from the grid during time period t; The maximum amount of electricity purchased by power user m from new energy power plant n in time period t;

[0230]

[0231]

[0232] In the formula, is the power demand of power user m in time period t.

[0233] Specifically, the calculation of the day-ahead market clearing price and clearing quantity includes:

[0234] Based on the Lagrangian dual decomposition principle, the function F that minimizes the electricity purchase cost of electricity users is 1Decomposed into the function F that minimizes the power purchase cost of each power user m :

[0235]

[0236] Based on the Lagrangian dual decomposition principle, the function F that maximizes the revenue of the new energy power plant is 2 Decompose into the profit maximization function F of each new energy power plant n :

[0237]

[0238] Where η t Lagrange multiplier for time period t;

[0239] Combined minimization function F of power user's electricity purchase cost based on subgradient method m and the revenue maximization function F of the new energy power plant n The electricity purchase price model for power users and new energy power plants is obtained:

[0240]

[0241] In the formula, k is the number of iterations of the Lagrange multiplier, and α is the step size coefficient of the gradient descent;

[0242] The electricity purchase price model between power users and new energy power plants is iteratively solved until the electricity purchase price converges and the final electricity purchase price λ is output m,n,t and purchased electricity

[0243] The electricity purchase price convergence meets the following requirements:

[0244] |λ m，n，t [k+1]-λ m，n，t [k]|≤ε

[0245] Where ε is the preset convergence parameter;

[0246] The final electricity purchase price λ m，n，t and purchased electricity As the day-ahead market clearing electricity price and clearing electricity quantity.

[0247] Specifically, the buyer and seller users who participate in the deviation transaction in the corresponding period of the day and the quotation strategy include:

[0248] The power deviation of power user m in time period t is:

[0249] Δp m，t =p m，pre，t -p m，buy，t

[0250] In the formula, pm，pre，t 、p m，pre，t are the daily demand and day-ahead clearing electricity of power user m in time period t respectively;

[0251] The preset deviation assessment thresholds include the positive deviation threshold Δp p，m，t and negative deviation threshold Δp q，m，t ;

[0252] If Δp m，t >Δp p，m，t , then electricity user m is a buyer user in time period t, and the bidding strategy of electricity user m is:

[0253] ρ m，idbuy，t =λ m，idbuy，t p a，m，t +μ m，idbuy，t

[0254] ρ m，idbuy，t <ρ m，pdev，t

[0255] In the formula, ρ m，idbuy，t 、p a，m，t , m，pdev，t μ is the daily power purchase quotation, daily power purchase quantity, and deviation penalty fee of power user m in time period t; m，idbuy，t is a constant;

[0256] If Δp m，t <Δp q，m，t , then electricity user m is a seller user in time period t, and the bidding strategy of electricity user m is:

[0257] ρ m，idsell，t =λ m，idsell，t p b，m，t +μ m，idsell，t

[0258] ρ m，idsell，t <ρ m，qdev，t

[0259] In the formula, ρ m，idsell，t 、p b，m，t , m，qdev，t μ is the daily electricity sales quotation, daily electricity sales volume, and deviation penalty fee of power user m in time period t; m，idsell，t is a constant.

[0260] Specifically, the calculation of deviation trading results includes:

[0261] Based on the VCG auction rules, the seller users’ daily electricity sales quotations in time period t are sorted from low to high to generate a clearing queue;

[0262] Bid and clear according to the clearing queue until the following conditions are met:

[0263]

[0264]

[0265] In the formula, I and J are the number of buyer users and seller users, p a,i,t is the amount of electricity purchased by buyer user i in time period t, p b,j,t , is the daily electricity sales volume and maximum electricity sales volume of seller user j in time period t;

[0266] Get the winning bid income of the seller who successfully bids and clears the items, and calculate the final transaction price:

[0267]

[0268] Where V j,t is the winning bid revenue of seller user j in period t, ω t is the transaction price in period t;

[0269] The objective function is constructed by minimizing the cost of absorbing the demand deviation electricity of the buyer and seller users:

[0270]

[0271] Based on the minimization of the objective function, the daily electricity purchase amount p of buyer user i in time period t is calculated a,i,t , the daily electricity sales volume p of seller user j in time period t b,j,t and the transaction price ω in period t t .

[0272] Embodiment three:

[0273] Based on the first embodiment, the present invention provides a main-side chain dual-chain interactive power transaction interactive device, including a processor and a storage medium;

[0274] The storage medium is used to store instructions;

[0275] The processor is used to operate according to the instructions to execute the steps according to the above method.

[0276] Embodiment 4:

[0277] Based on the first embodiment, the embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

[0278] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0279] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0280] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0281] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0282] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A main-side chain and dual-chain interactive power trading method, It is characterized in that include: Obtain transaction declaration information of new energy power plants and power users and upload it to the blockchain main chain; The transaction declaration information is the market transaction electricity volume and transaction electricity price for each period of the previous day; Based on the transaction declaration information, the market clearing electricity price and clearing electricity quantity for each period of the day before are calculated and synchronized to the side chain with the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants; Obtain the power demand of the power user in each period of the day and subtract the cleared power of the corresponding period a day ago to obtain the power deviation of the corresponding period; According to the power deviation in each period and the preset deviation assessment threshold, determine the buyer and seller users participating in the deviation transaction in the corresponding period of the day and the quotation strategy; According to the buyer and seller users and the quotation strategy, the deviation transaction results are calculated and synchronized to the main chain with the goal of minimizing the cost of absorbing power deviation; Among them, the goal of minimizing the electricity purchase cost of electricity users and maximizing the benefits of new energy power plants includes: Constructing a function to minimize the cost of electricity purchase for power users and the profit maximization function of the new energy power plant ; The electricity user's electricity purchase cost minimization function for: ； In the formula, For electricity users during the period The electricity price purchased from the grid, is the number of time periods, For electricity users In the period Purchase electricity from the grid, is the number of electricity users, For electricity users In the period From new energy power plants Electricity purchase price, For electricity users In the period From new energy power plants Power purchased, For electricity users The loss parameters of the transaction transmission with the renewable energy power plant, For electricity users In the period Loss costs incurred from purchasing electricity from renewable energy power plants; The profit maximization function of the new energy power plant for: ； In the formula, is the number of renewable energy power plants; For new energy power plants In the period of power generation, For new energy power plants Time The cost of electricity generation, is a constant; Among them, the power user's electricity purchase cost minimization function and the profit maximization function of the new energy power plant The following constraints are met: ； ； ； In the formula, For new energy power plants In the period Maximum power generation capacity; For electricity users In the period Maximum amount of electricity purchased from the grid; For electricity users In the period From new energy power plants Maximum amount of electricity to be purchased; ； ； In the formula, For electricity users In the period The power demand.

2. According to claim 1, a main-side chain and dual-chain interactive power trading interaction method, It is characterized in that The calculation of the day-ahead market clearing electricity price and clearing electricity quantity includes: Based on the Lagrangian dual decomposition principle, the function of minimizing the electricity purchase cost of power users is constructed. Decompose into the function of minimizing the power purchase cost of each power user : ； Based on the Lagrangian dual decomposition principle, the function of maximizing the profit of new energy power plants is constructed. Decompose into the profit maximization function of each new energy power plant : ； In the formula, Time The Lagrange multiplier of ; Combined minimization function of electricity purchase cost for power users based on subgradient method and the profit maximization function of new energy power plants The electricity purchase price model for power users and new energy power plants is obtained: ； In the formula, is the number of iterations of the Lagrange multiplier, is the step size coefficient of gradient descent; Iterate and solve the electricity purchase price model between power users and new energy power plants until the electricity purchase price converges and then output the final electricity purchase price. and purchased electricity ; The electricity purchase price convergence satisfies: ； In the formula, is the preset convergence parameter; The final electricity purchase price and purchased electricity As the day-ahead market clearing electricity price and clearing electricity quantity.

3. According to claim 1, a main-side chain and dual-chain interactive power trading interaction method, It is characterized in that The buyer user and seller user who participate in the deviation transaction in the corresponding period of the day and the quotation strategy include: Electricity users In the period The power deviation is: ； In the formula, , Electricity users In the period The daily demand and day-ahead clearing electricity; The preset deviation assessment thresholds include positive deviation thresholds and negative deviation threshold ; like , then the electricity user In the period For buyers, electricity users The quotation strategy is: ； ； In the formula, , , For electricity users In the period Intraday power purchase quotation, intraday power purchase quantity, and deviation penalty fee; is a constant; like , then the electricity user In the period For sellers, electricity users The quotation strategy is: ； ； In the formula, , , For electricity users In the period Intraday electricity sales quotation, intraday electricity sales volume, and deviation penalty fees; is a constant.

4. According to claim 3, a main-side chain and side-chain interactive power trading interaction method, It is characterized in that The calculation deviation transaction results include: Based on the VCG auction rules, the seller user The daily electricity sales quotations are sorted from low to high to generate a clearing queue; Bid and clear according to the clearing queue until the following conditions are met: ； ； In the formula, , is the number of buyer users and seller users, For Buyer Users In the period The amount of electricity purchased during the day, , For seller users In the period The daily electricity sales volume and the maximum electricity sales volume; Get the winning bid income of the seller who successfully bids and clears the items, and calculate the final transaction price: ； In the formula, For seller users In the period The winning bid income, For the period The transaction price; The objective function is constructed by minimizing the cost of absorbing the demand deviation electricity of the buyer and seller users: ； Based on the minimization of the objective function calculation, the buyer user In the period Daily electricity purchase , Seller User In the period Daily electricity sales And during the period Transaction price .

5. A power trading interactive device with main-side chain and dual-chain interaction, It is characterized in that The device comprises: The declaration module is used to obtain the transaction declaration information of new energy power plants and power users and upload it to the blockchain main chain; the transaction declaration information is the market transaction volume and transaction electricity price in each period of the day before; The clearing module is used to calculate the market clearing electricity price and clearing electricity quantity for each period of the day before and synchronize them to the side chain based on the transaction declaration information with the goal of minimizing the electricity purchase cost of electricity users and maximizing the revenue of new energy power plants; The deviation module is used to obtain the power demand of the power user in each period of the day and subtract the cleared power of the corresponding period a day ago to obtain the power deviation of the corresponding period; The assessment module is used to obtain the buyer and seller users who participate in the deviation transaction in the corresponding period of the day and the quotation strategy according to the power deviation in each period and the preset deviation assessment threshold; The transaction module is used to calculate the deviation transaction results and synchronize them to the main chain based on the buyer and seller users and the quotation strategy with the goal of minimizing the cost of absorbing power deviation; Among them, the goal of minimizing the electricity purchase cost of electricity users and maximizing the benefits of new energy power plants includes: Constructing a function to minimize the cost of electricity purchase for power users and the profit maximization function of the new energy power plant ; The electricity user's electricity purchase cost minimization function for: ； In the formula, For electricity users during the period The electricity price purchased from the grid, is the number of time periods, For electricity users In the period Purchase electricity from the grid, is the number of electricity users, For electricity users In the period From new energy power plants Electricity purchase price, For electricity users In the period From new energy power plants Power purchased, For electricity users The loss parameters of the transaction transmission with the renewable energy power plant, For electricity users In the period Loss costs incurred from purchasing electricity from renewable energy power plants; The new energy power plant profit maximization function for: ； In the formula, is the number of renewable energy power plants; For new energy power plants In the period of power generation, For new energy power plants Time The cost of electricity generation, is a constant; Among them, the power user's electricity purchase cost minimization function and the profit maximization function of the new energy power plant The following constraints are met: ； ； ； In the formula, For new energy power plants In the period Maximum power generation capacity; For electricity users In the period Maximum amount of electricity purchased from the grid; For electricity users In the period From new energy power plants Maximum amount of electricity to be purchased; ； ； In the formula, For electricity users In the period The power demand.

6. A main-side chain and side-chain interactive power transaction interactive device according to claim 5, It is characterized in that The calculation of the day-ahead market clearing electricity price and clearing electricity quantity includes: Based on the Lagrangian dual decomposition principle, the function of minimizing the electricity purchase cost of power users is constructed. Decompose into the function of minimizing the power purchase cost of each power user : ； Based on the Lagrangian dual decomposition principle, the function of maximizing the profit of new energy power plants is constructed. Decompose into the profit maximization function of each new energy power plant : ； In the formula, Time The Lagrange multiplier of ; Combined minimization function of electricity purchase cost for power users based on subgradient method and the profit maximization function of new energy power plants The electricity purchase price model for power users and new energy power plants is obtained: ； In the formula, is the number of iterations of the Lagrange multiplier, is the step size coefficient of gradient descent; Iterate and solve the electricity purchase price model between power users and new energy power plants until the electricity purchase price converges and then output the final electricity purchase price. and purchased electricity ; The electricity purchase price convergence satisfies: ； In the formula, is the preset convergence parameter; The final electricity purchase price and purchased electricity As the day-ahead market clearing electricity price and clearing electricity quantity.

7. A main-chain and side-chain interactive power trading interactive device according to claim 5, It is characterized in that The buyer user and seller user who participate in the deviation transaction in the corresponding period of the day and the quotation strategy include: Electricity users In the period The power deviation is: ； In the formula, , Electricity users In the period The daily demand and day-ahead clearing electricity; The preset deviation assessment thresholds include positive deviation thresholds and negative deviation threshold ; like , then the electricity user In the period For buyers, electricity users The quotation strategy is: ； ； In the formula, , , For electricity users In the period Intraday power purchase quotation, intraday power purchase quantity, and deviation penalty fee; is a constant; like , then the electricity user In the period For sellers, electricity users The quotation strategy is: ； ； In the formula, , , For electricity users In the period Intraday electricity sales quotation, intraday electricity sales volume, and deviation penalty fees; is a constant.

8. A main-chain and side-chain interactive power trading interactive device according to claim 7, It is characterized in that The calculation deviation transaction results include: Based on the VCG auction rules, the seller user The daily electricity sales quotations are sorted from low to high to generate a clearing queue; Bid and clear according to the clearing queue until the following conditions are met: ； ； In the formula, , is the number of buyer users and seller users, For Buyer Users In the period The amount of electricity purchased during the day, , For seller users In the period The daily electricity sales volume and the maximum electricity sales volume; Get the winning bid income of the seller who successfully bids and clears the items, and calculate the final transaction price: ； In the formula, For seller users In the period The winning bid income, For the period The transaction price; The objective function is constructed by minimizing the cost of absorbing the demand deviation electricity of the buyer and seller users: ； Based on the minimization of the objective function calculation, the buyer user In the period Daily electricity purchase , Seller User In the period Daily electricity sales And during the period Transaction price .

9. A power trading interactive device with main-side chain and dual-chain interaction, It is characterized in that including processor and storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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