A user-side transaction strategy analysis method based on supply amount regulation

Abstract

The application discloses a user-side transaction strategy analysis method based on supply amount regulation, comprising the following steps: acquiring preset supply-demand response models for different types of producers and consumers, and acquiring first transaction electric power of the producers and consumers; constructing a first target optimization function, and solving the first target optimization function to obtain an optimal solution of a first transaction electricity price; completing a first-stage electric power transaction based on the first transaction electric power of each producer and consumer and the first transaction electricity price; constructing a second target optimization function, and obtaining an optimal solution of second transaction electric power of a first producer and consumer by solving the second target optimization function; analyzing and acquiring a unified second transaction price of power purchase / sale of the first producer and consumer to an upper-level power grid based on the second transaction electric power of the first producer and consumer; and completing a second-stage electric power transaction of the first producer and consumer based on the second transaction price and the second transaction electric power. The application adopts a two-stage transaction method and introduces a first parameter to realize suppression of malicious competition, thereby improving the flexibility of system platform regulation and transaction amount.

Description

Technical Field

[0001] This invention relates to the field of electricity market technology, and specifically to a user-side trading strategy analysis method based on supply regulation. Background Technology

[0002] With the popularization of distributed energy and the promotion of a new round of power reform, more and more producers and consumers with independent decision-making capabilities are entering the electricity sales market to compete. Due to the large number of producers and consumers and the small transaction scale, the traditional centralized trading system is inefficient and has a long decision-making time. Furthermore, the transactions of producers and consumers are subject to interference from individual behaviors, resulting in malicious competition. Over time, the market operating environment will deteriorate. Summary of the Invention

[0003] To address the problems existing in the prior art, this invention provides a user-side transaction strategy analysis method based on supply-demand regulation, effectively improving the active flexibility of transactions between producers and consumers and the flexibility of the system platform in regulating transaction volume. The method includes:

[0004] Obtain a preset supply and demand response model for different types of prosumers, obtain the first transaction volume of prosumers, and introduce a first parameter in the preset supply and demand response model to control the supply of different prosumers to suppress malicious competition.

[0005] Based on the difference between the first transaction electricity price and the transaction price to the grid as the revenue per unit of transaction electricity, and combined with the transaction electricity parameters, a first objective optimization function for maximizing the expected benefits for both producers and consumers, and for electricity buyers and sellers, is constructed. Solving the first objective optimization function yields the optimal solution for the first transaction electricity price.

[0006] Based on the first transaction volume and first transaction price of each producer and consumer, electricity transactions are matched for all producers and consumers, and the first stage of electricity transactions is completed between each producer and consumer based on the transaction matching information.

[0007] Determine whether each producer-consumer has surplus / shortage of electricity after the first stage of electricity trading. If so, record it as the first producer-consumer and obtain the surplus / shortage of electricity of the first producer-consumer.

[0008] Based on the objectives of maximizing the economic benefits for both the electricity purchaser and seller and maximizing the satisfaction of transaction volume requirements, a second objective optimization function is constructed. The optimal solution for the second transaction volume is obtained by solving the second objective optimization function.

[0009] Based on the analysis of the second transaction volume of the first producer-consumer, the unified second transaction price for the first producer-consumer to purchase / sell electricity from the upper-level power grid is obtained;

[0010] The second phase of electricity trading for the first producer-consumer is completed based on the second trading price and the second trading volume.

[0011] In some implementations, the first parameter is the photovoltaic supply security potential level, used to characterize the sensitivity of producer-consumer electricity to the first phase of electricity trading, wherein the photovoltaic supply security potential level ε i (t) is:

[0012]

[0013] In the formula, ε i (t) represents the photovoltaic supply security potential level of producer-consumer i at time t, and δ is the fitting coefficient. i,SC To determine the investment return period, q is the fitting adjustment coefficient, and φ is the supply growth rate.

[0014] In some implementations, the preset supply and demand response model introduces a first parameter to control the supply of different producers or consumers, including:

[0015] When ε i (t) is not greater than At that time, the supply of producers and consumers is encouraged, and the supply model is as follows:

[0016] When ε i (t) is not less than At that time, the quantity supplied by producers and consumers is punished and suppressed. The supply model is as follows:

[0017] When ε i (t) in and In the interim, the supply model is: Where ρ is the adjustment factor.

[0018] in, These represent the lower and upper limits of the photovoltaic power supply security potential level, respectively. The dividing point is adjustable. and Let represent the basic supply and adjustable supply of producer-consumer i at time t, respectively. This represents the expected upper limit of electricity sales for the electricity seller.

[0019] In some implementations, the preset supply and demand response models for different types of prosumers include residential, commercial, and industrial types, and the supply and demand response models include supply models and demand models.

[0020] The demand model for resident-type prosumers is as follows:

[0021] η is the basic load of producer-consumer i at time t. i,t∈(0,1) represents the price elasticity coefficient of producer-consumer i at time t;

[0022] The demand model for commercial prosumers is as follows:

[0023] η is the basic load of producer-consumer i at time t. i,t ∈(0,1) represents the price elasticity coefficient of producer-consumer i at time t;

[0024] The demand model for industrial prosumers is as follows:

[0025] Where τ∈[-0.1,0.1] represents the random influence factor.

[0026] In some implementations, the step of constructing a first objective optimization function for maximizing the expected benefits for both producers and consumers (power buyers and sellers) based on the difference between the first transaction price and the transaction price to the grid as the revenue per unit of traded electricity, combined with the transaction electricity parameters, includes:

[0027] max F i,t =(λ i,t -λ S )(1-α i,t )β i,t ;

[0028] max F j,t =(λ B -λ j,t )(1-α j,t )β j,t ;

[0029] Among them, F i,t For the expected benefits of electricity seller i, F j,t For the expected benefits of electricity purchaser j, λ i,t Let λ be the electricity price at time t. j,t Let λ be the electricity purchase price at that moment. S The price of electricity sold by producers and consumers to the grid, λ B α is the price at which producers and consumers purchase electricity from the grid. j,t and α i,t β represents the deviation coefficient between the expected and actual reported electricity sales volume of the buyer / seller, respectively, where k is the number of transaction rounds, and β is the coefficient of deviation. j,t and β i,t The success rates of electricity transactions for both the buyer and seller are respectively.

[0030]

[0031]

[0032] in, This represents the expected upper limit of electricity sales by the electricity seller. This represents the upper limit of the electricity purchaser's expected electricity purchase. and The electricity volume reported by the electricity purchaser and seller are respectively.

[0033] In some implementations, the construction of a second objective optimization function based on the goals of maximizing economic benefits for both the electricity buyer and seller and maximizing the satisfaction of transaction volume requirements, and the acquisition of the optimal solution for the second transaction volume by solving the second objective optimization function, includes:

[0034] Construct a social welfare maximization function and obtain multiple constraints on the social welfare maximization function. Solve the social welfare maximization function to obtain the optimal solution for the second transaction electricity.

[0035] The aforementioned social welfare maximization function is:

[0036]

[0037] Where SW represents social welfare, T represents the total number of times, Δt represents the time interval, and F represents social welfare. 1,t F represents the collective benefit of market participants in regional transactions. 2,t This refers to the network access fee paid during regional transactions. For abandoned light power, The price for the penalty of abandoning light, N B N S These represent the total number of people purchasing / selling electricity, respectively. Indicates the cost of blocking. and For the second phase of the planned electricity purchase / sale, The cost of participating in the second phase of electricity sales by party i To participate in the second phase of the electricity purchase program, For the benefit of the higher-level power grid, To make up for the final shortfall in the upper-level power grid.

[0038] In some implementations, the constraints of the social welfare maximization function include:

[0039] 1) Line transmission capacity constraints:

[0040]

[0041] 2) Power balance constraints:

[0042]

[0043] 3) Power supply constraints for producers and consumers

[0044]

[0045] 4) Electricity consumption constraints for producers and consumers

[0046]

[0047] In some implementations, the step of obtaining a unified second transaction price for the first producer-consumer's purchase / sale of electricity from the upper-level power grid based on the second transaction volume analysis includes incorporating a social welfare electricity purchase / sale compensation factor based on the supply-demand ratio in the second transaction volume. Construct a second transaction price pricing model, which includes:

[0048]

[0049]

[0050] In the formula, and These represent the purchase price and the sale price of electricity, respectively. This is the electricity sales compensation factor. D is the electricity purchase compensation factor, and D is the supply-demand ratio.

[0051] in,

[0052]

[0053] Among them, F 1,t-1 For the collective benefit of producers and consumers at time t-1, The optimal electricity sales volume for producer-consumer i. The optimal electricity purchase volume for consumer j.

[0054] The present invention provides a user-side transaction strategy analysis method based on supply regulation, which has the following beneficial effects: On the one hand, the present invention employs a first-stage electricity trading and a second-stage electricity trading to realize user-side electricity trading. The first-stage electricity trading is used for transactions between various prosumers, while the second-stage electricity trading is used for transactions between prosumers and the upstream power grid. This two-stage trading method improves the flexibility and initiative of transactions between prosumers and consumers. On the other hand, in the first-stage electricity trading process, the present invention introduces a first parameter to control and promote or inhibit the supply of different prosumers and consumers to suppress malicious competition. This considers the differences in individual prosumer and consumer behavior, improving the flexibility of the system platform in regulating transaction volume. Attached Figure Description

[0055] Figure 1 This is a flowchart illustrating an embodiment of a user-side transaction strategy analysis method based on supply regulation in this application.

[0056] Figure 2This is a flowchart illustrating another embodiment of a user-side transaction strategy analysis method based on supply regulation in this application.

[0057] Figure 3 This is a diagram depicting the producer-consumer market environment;

[0058] Figure 4 This is a diagram of the two-stage transaction structure for prosumers and consumers in this application embodiment;

[0059] Figure 5 This is a comparison chart of the first-stage distributed transaction volume of prosumers in the embodiments of this application. Detailed Implementation

[0060] See Figure 1 This application discloses a user-side transaction strategy analysis method based on supply and demand regulation, including:

[0061] Step 1: Obtain a preset supply and demand response model for different types of prosumers and obtain the first transaction volume of prosumers. The preset supply and demand response model introduces a first parameter to control the supply of different prosumers or consumers in order to suppress malicious competition.

[0062] Step 2: Based on the difference between the first transaction electricity price and the transaction price to the grid as the revenue per unit of transaction electricity, and combined with the transaction electricity parameters, construct a first objective optimization function for maximizing the expected benefits for both producers and consumers, and solve the first objective optimization function to obtain the optimal solution for the first transaction electricity price;

[0063] Step 3: Match electricity transactions for all producers and consumers based on the first transaction electricity volume and the first transaction electricity price of each producer and consumer, and complete the first stage of electricity transactions between each producer and consumer based on the transaction matching information.

[0064] Step 4: Determine whether each producer-consumer has surplus / shortage of electricity after the first stage of electricity trading. If so, record it as the first producer-consumer and obtain the surplus / shortage of electricity of the first producer-consumer.

[0065] Step 5: Based on the objectives of maximizing the economic benefits for both the electricity purchaser and seller and maximizing the satisfaction of the transaction volume demand, construct a second objective optimization function, and obtain the optimal solution for the second transaction volume by solving the second objective optimization function;

[0066] Step 6: Based on the analysis of the second transaction volume of the first producer-consumer, obtain the unified second transaction price for the first producer-consumer to purchase / sell electricity from the upper-level power grid;

[0067] Step 7: Complete the second phase of electricity trading for the first producer-consumer based on the second trading price and the second trading volume.

[0068] On the one hand, this application adopts a first-stage electricity trading and a second-stage electricity trading to realize user-side electricity trading. The first-stage electricity trading is used for the trading process between various producers and consumers, and the second-stage electricity trading is used for the trading process between producers and consumers and the upper-level power grid. The two-stage trading method improves the flexibility and initiative of the trading between producers and consumers. It can be understood that in the first-stage electricity trading process, the first trading price of different producers and consumers is different (the trading price can be the purchase price or the sales price). In the second-stage electricity trading process, the second trading price of different producers and consumers is unified (that is, the purchase price of producers and consumers is consistent, and the sales price of producers and consumers is consistent).

[0069] On the other hand, in the first phase of electricity trading, this application introduces a first parameter to control the supply of different producers and consumers in order to suppress malicious competition, taking into account the differences in individual behavior of producers and consumers, thereby improving the flexibility of the system platform in regulating the trading volume.

[0070] See Figure 2 Specifically, in step 1 above, a preset supply and demand response model for different types of prosumers is obtained, and the first transaction volume of the prosumers is obtained. The first parameter is the photovoltaic supply security potential level, used to characterize the sensitivity of the prosumer's electricity to the first stage of electricity trading. This photovoltaic supply security potential level ε i The methods for obtaining (t) include:

[0071] 11) Establish a photovoltaic investment return period model for producer-consumer i.

[0072]

[0073] In the formula, t i,SC To develop the investment return period, B i PV For photovoltaic policy subsidies, λ i PV For photovoltaic electricity price, For the installation cost of rooftop solar panels, Cost of rooftop solar power generation The number of hours used per year;

[0074] 12) Due to the discrepancy between the expected maximum supply and guarantee quantity during photovoltaic installation and the final maximum supply and guarantee quantity, the final maximum supply and guarantee quantity model is established as follows:

[0075]

[0076] In the formula, To the final maximum supply volume, δ represents the expected maximum supply volume, and δ is the fitting coefficient.

[0077] 13) Based on the description of the ultimate maximum photovoltaic supply capacity as the sum of the current photovoltaic supply capacity and the current scalable supply capacity, a model reflecting the photovoltaic supply capacity potential level is established as follows:

[0078]

[0079] In the formula, This is the initial supply guarantee for photovoltaic power. Let φ represent the growth rate of supply and demand, and q be the fitting adjustment coefficient. Then e -qt Defined as the fitting adjustment amount;

[0080] 14) The potential level of photovoltaic power supply is represented by ε. i (t) represents the result obtained through the transformation:

[0081]

[0082] In the formula, ε i (t) represents the photovoltaic supply security potential level of producer-consumer i at time t, and δ is the fitting coefficient. i,SC To determine the investment return period, q is the fitting adjustment coefficient, and φ is the supply guarantee growth rate. It can be understood that the photovoltaic supply guarantee potential level is related to the photovoltaic capacity of producers and consumers. In one implementation, the maximum photovoltaic capacity can be used as the expected maximum supply guarantee amount.

[0083] In one implementation, based on the lower limit of the photovoltaic power supply potential level. and upper limit Types of supply models for prosumers:

[0084] When ε i (t) is not greater than At that time, the supply of producers and consumers is encouraged, and the supply model is as follows:

[0085]

[0086] When ε i (t) is not less than At that time, the quantity supplied by producers and consumers is punished and suppressed. The supply model is as follows:

[0087]

[0088] When ε i (t) in and In the interim, the supply model is:

[0089]

[0090] Where ρ is the adjustment factor. These represent the lower and upper limits of the photovoltaic power supply security potential level, respectively. Preset adjustable dividing point, and Let represent the basic supply and adjustable supply of producer-consumer i at time t, respectively. This represents the expected upper limit of electricity sales for the electricity seller.

[0091] In another implementation, the supply model for prosumers is analyzed based on statistical data on their photovoltaic supply security potential, specifically the size of the confidence interval. This analysis considers the varying degrees of randomness in photovoltaic power generation costs, policy subsidies, and annual utilization rates among different prosumers, leading to different levels of photovoltaic supply security potential ε. i (t) is a random variable. In this embodiment, statistical analysis is considered on the photovoltaic supply guarantee potential level of similar prosumers to calculate the photovoltaic supply guarantee potential level of similar prosumers within a confidence level of 0.95.

[0092] For example, in the embodiments of this application, it is considered that... Figure 4 The analysis of resident, commercial, and industrial prosumers within the integrated energy community is presented below. Based on the statistical data of photovoltaic supply and protection potential levels of the same type of prosumers within the integrated energy community, the range of photovoltaic supply and protection potential levels for each type of prosumer is obtained, as shown in Table 1 below.

[0093] Table 1. Standard Range of Photovoltaic Power Supply Potential (with a confidence level of 0.95)

[0094]

[0095] Combination Figure 3 It is known that industrial producers and consumers have high photovoltaic supply security levels and reach a stable trend slowly, while residential producers and consumers do the opposite. When residential photovoltaic prices stabilize and begin to decline, industrial prices continue to rise, gradually widening the price gap. Over time, industrial profits will be high while residential losses will be high, leading to malicious competition. Therefore, this application considers encouraging the supply of residential producers and consumers, penalizing the supply of industrial producers and consumers, and determining whether to encourage or penalize the supply of commercial producers and consumers based on whether their photovoltaic supply security potential exceeds a preset adjustable threshold.

[0096] That is, the supply model of residents' prosumers adopts the above formula (5);

[0097] The supply model for commercial prosumers adopts the above formula (6);

[0098] The supply model for industrial type producers and consumers adopts the above formula (7);

[0099] Furthermore, in step 1, the "preset supply and demand response models for different types of prosumers" include residential, commercial, and industrial types, and the supply and demand response models include supply models and demand models.

[0100] Because the planned demand of household producer-consumer is easily affected by the stochastic price elasticity coefficient, the demand of household producer-consumer... for:

[0101]

[0102] In the formula, η is the basic load of producer-consumer i at time t. i,t ∈(0,1) represents the price elasticity coefficient of producer-consumer i at time t.

[0103] Commercial consumer products include photovoltaic equipment, gas turbines, and commercial loads. Among them, the introduction of gas turbines can increase flexibility, and its demand is the same as that in formula (8);

[0104] Industrial producers and consumers include photovoltaic equipment, gas turbines, energy storage, and industrial loads. Because the load curve pattern of industrial producers and consumers is fixed, their demand is not easily affected by external factors. Their demand is as follows:

[0105]

[0106] In the formula, τ∈[-0.1,0.1] represents the random influence factor.

[0107] Specifically, in step 2 above, the difference between the first transaction electricity price and the transaction price with the grid is used as the revenue per unit of transaction electricity. Combined with the transaction electricity parameters, a first objective optimization function is constructed to maximize the expected benefits for both producers and consumers in the electricity purchase and sale process.

[0108] Specifically, electricity sellers aim to sell electricity at the highest market price, while electricity buyers aim to purchase electricity at the lowest cost. Since the level of photovoltaic supply security potential affects the supply and demand of prosumers, it consequently impacts the success rate of transactions. This application's embodiments establish a first objective optimization function that maximizes the expected benefits for both prosumers and electricity sellers, including:

[0109] max F i,t =(λ i,t -λ S )(1-α i,t )β i,t (10)

[0110]

[0111] max F j,t =(λ B -λj,t )(1-α j,t )β j,t (12)

[0112]

[0113] Among them, F i,t For the expected benefits of electricity seller i, F j,t For the expected benefits of electricity purchaser j, λ i,t Let λ be the electricity price at time t. j,t Let λ be the electricity purchase price at that moment. S The price of electricity sold by producers and consumers to the grid, λ B α is the price at which producers and consumers purchase electricity from the grid. j,t and α i,t β represents the deviation coefficient between the expected and actual reported electricity sales volume of the buyer / seller, respectively, where k is the number of transaction rounds, and β is the coefficient of deviation. j,t and β i,t The success rates of electricity transactions for both the buyer and seller are respectively.

[0114]

[0115]

[0116] in, This represents the expected upper limit of electricity sales by the electricity seller. This represents the upper limit of the electricity purchaser's expected electricity purchase. and The electricity volume reported by the electricity purchaser and seller are respectively.

[0117] In step 3 above, electricity transactions are matched among all producers and consumers based on their first transaction volume and first transaction price. This matching information enables the first phase of electricity transactions to be completed between the producers and consumers. Specifically, this includes:

[0118] In the first phase of electricity trading, producers and consumers confirm and announce their identities for this round of trading, and generate sets of electricity sellers and buyers respectively. Both sellers and buyers submit their electricity prices and quantities to the platform. The platform adjusts the electricity quantities according to the rules defined above. Sellers are arranged in ascending order of price, and buyers are arranged in descending order of price, matching high and low prices based on the principle of maximizing price difference. If the matching conditions and security verification are successful, the transaction is completed; otherwise, the electricity quantity and price information need to be adjusted, and a new matching process is required.

[0119] In step 4 above, it is determined whether each producer-consumer has surplus / shortage of electricity after the first stage of electricity trading. If so, it is recorded as the first producer-consumer, and the surplus / shortage of electricity of the first producer-consumer is obtained.

[0120] Specifically, after the first phase of electricity trading (distributed trading), some producers and consumers still have surplus / shortage of electricity, which can be used to participate in the second phase of electricity trading (centralized intersection).

[0121] Step 5 above constructs a second objective optimization function based on the goals of maximizing economic benefits for both the electricity buyer and seller and maximizing the fulfillment of transaction volume requirements. The optimal solution for the second transaction volume is obtained by solving this second objective optimization function. Specifically:

[0122] In the second phase of electricity trading, both the buyer and seller report their surplus / deficit electricity to the platform, which then allocates it to the power grid. Sellers aim for maximum economic benefit, while buyers seek to maximize their own benefits and utility. Therefore, to ensure fairness, this patent proposes an improved Ramsey-theoretic social welfare maximization function, considering network congestion:

[0123]

[0124]

[0125] In the formula, SW represents social welfare, T represents the total number of times, Δt represents the time interval, and F represents social welfare. 1,t F represents the collective benefit of market participants in regional transactions. 2,t This refers to the network access fee paid during regional transactions. For abandoned light power, The price for the penalty of abandoning light, N B N S These represent the total number of people purchasing / selling electricity, respectively. Indicates the cost of blocking. and For the second phase of the planned electricity purchase / sale, The cost of participating in the second phase of electricity sales by party i To participate in the second phase of the electricity purchase program, For the benefit of the higher-level power grid, To make up for the final shortfall in the upper-level power grid.

[0126] The constraints of this social welfare maximization function include:

[0127] 1) Line transmission capacity constraints:

[0128]

[0129] 2) Power balance constraints:

[0130]

[0131] Wherein, ΔP L Indicates network loss parameters;

[0132] 3) Power supply constraints for producers and consumers

[0133]

[0134] 4) Electricity consumption constraints for producers and consumers

[0135]

[0136] By combining the above-mentioned multiple constraints of the social welfare maximization function, the optimal solution of the social welfare maximization function is obtained, thus obtaining the optimal solution for the second transaction electricity.

[0137] Step 6 above involves obtaining the unified second transaction price for the first producer-consumer's purchase / sale of electricity from the upper-level power grid based on the second transaction volume analysis. Specifically:

[0138] 61) Because the centralized market price for point-to-point electricity does not follow grid rules but is determined by supply and demand, and is dominated by all producers and consumers, and because supply and demand pricing can gain the acceptance of electricity buyers while ensuring that electricity sellers break even, a social welfare electricity purchase and sale compensation factor is proposed as follows:

[0139]

[0140]

[0141] In the formula, F 1,t-1 For the collective benefit of producers and consumers at time t-1, The optimal electricity sales volume for producer-consumer i. The optimal electricity purchase volume for consumer j.

[0142] 62) Furthermore, based on the supply-demand ratio in the second transaction volume, the social welfare power purchase and sale compensation factor from step 52) above is simultaneously introduced. A second transaction price pricing model is constructed, which adopts an improved SDR pricing method, including:

[0143]

[0144]

[0145] In the formula, and These represent the purchase price and the sale price of electricity, respectively. This is the electricity sales compensation factor. denoted as the electricity purchase compensation factor, and D as the supply-demand ratio.

[0146] Step 7 above completes the second phase of electricity trading for the first producer-consumer based on the second trading price and the second trading volume. Specifically, after the platform uniformly provides the purchase and sale price of electricity, the platform uniformly allocates the electricity until the electricity is balanced and the transaction ends. At this point, both phases of trading are completed.

[0147] Based on the above-mentioned user-side transaction strategy analysis method based on supply regulation, a specific implementation effect is explained.

[0148] Two industrial consumer groups, three commercial consumer groups, six residential consumer groups, and one power grid company were selected for the transaction.

[0149] For the first phase of distributed generation transactions considering the potential level of photovoltaic (PV) supply security, two scenarios are established: Scenario 1 is the transaction without considering the potential level of PV supply security, and Scenario 2 is the transaction with the potential level of PV supply security. A comparison of the two scenarios is provided below. Figure 5 As shown, the transaction volume of all prosumers in the first phase of distributed transactions will generally show an upward trend as the photovoltaic supply and demand potential level is considered. Therefore, regulating the transaction volume of prosumers based on the photovoltaic supply and demand level can effectively alleviate the resistance of prosumers to malicious competition and encourage them to actively participate in the first phase of transactions.

[0150] For a producer-consumer second-stage centralized transaction using the improved SDR pricing method, assuming the price λ for purchasing electricity from the grid... B The price of electricity sold to the grid is 0.7 yuan / kWh. S The price is 0.4 yuan / kWh. Scenario 1 is the SDR pricing method before the improvement, and Scenario 2 is the SDR pricing method after the improvement. As shown in Tables 2 and 3, the improved electricity purchase price is lower than the one before the improvement, and the improved electricity sales price is higher than the one before the improvement. The improved SDR can indeed effectively incentivize producers and consumers to participate in the second phase of the transaction.

[0151] Table 2 Comparison of Electricity Purchase Prices under the Second Phase of Centralized Transactions

[0152] time 7 o'clock 8 o'clock 9 o'clock 10 o'clock 11 o'clock 12 o'clock 13 o'clock 2 PM 3 PM 4 PM 5 PM 6 PM Before improvement 0.7 0.7 0.60 0.4 0.695 0.654 0.4 0.65 0.62 0.68 0.699 0.699 Improved 0.7 0.7 0.55 0.4 0.63 0.63 0.4 0.61 0.61 0.65 0.692 0.697

[0153] Table 3 Comparison of Electricity Prices under the Second Phase of Centralized Trading

[0154] time 7 o'clock 8 o'clock 9 o'clock 10 o'clock 11 o'clock 12 o'clock 13 o'clock 2 PM 3 PM 4 PM 5 PM 6 PM Before improvement 0.7 0.7 0.51 0.4 0.68 0.56 0.4 0.56 0.53 0.61 0.692 0.694 Improved 0.7 0.7 0.54 0.4 0.69 0.58 0.4 0.58 0.54 0.63 0.699 0.699

[0155] This invention is not limited to the specific embodiments described above. Any modifications made by those skilled in the art based on the above concept without creative effort are within the scope of protection of this invention.

Claims

1. A user-side transaction strategy analysis method based on supply-demand regulation, characterized in that, include: Obtain a preset supply and demand response model for different types of prosumers, obtain the first transaction volume of prosumers, and introduce a first parameter in the preset supply and demand response model to control the supply of different prosumers in order to suppress malicious competition. Based on the difference between the first transaction electricity price and the transaction price to the grid as the revenue per unit of transaction electricity, and combined with the transaction electricity parameters, a first objective optimization function for maximizing the expected benefits for both producers and consumers, and for electricity buyers and sellers, is constructed. Solving the first objective optimization function yields the optimal solution for the first transaction electricity price. Based on the first transaction volume and first transaction price of each producer and consumer, electricity transactions are matched for all producers and consumers, and the first stage of electricity transactions is completed between each producer and consumer based on the transaction matching information. Determine whether each producer-consumer has surplus / shortage of electricity after the first stage of electricity trading. If so, record it as the first producer-consumer and obtain the surplus / shortage of electricity of the first producer-consumer. Based on the objectives of maximizing the economic benefits for both the electricity purchaser and seller and maximizing the satisfaction of transaction volume requirements, a second objective optimization function is constructed. The optimal solution for the second transaction volume is obtained by solving the second objective optimization function. Based on the analysis of the second transaction volume of the first producer-consumer, the unified second transaction price for the first producer-consumer to purchase / sell electricity from the upper-level power grid is obtained; The second phase of electricity trading for the first producer-consumer is completed based on the second trading price and the second trading volume. The first parameter is the photovoltaic supply security potential level, which is used to characterize the sensitivity of producer-consumer electricity to the first phase of electricity trading. The methods for obtaining it include: 11) Establish prosumers Photovoltaic investment return period model: (1) In the formula, To develop the investment return period, For photovoltaic policy subsidies, For photovoltaic electricity price, For the installation cost of rooftop solar panels, Cost of rooftop solar power generation The number of hours used per year; 12) Due to the discrepancy between the expected maximum supply and guarantee quantity during photovoltaic installation and the final maximum supply and guarantee quantity, the final maximum supply and guarantee quantity model is established as follows: (2) In the formula, To the final maximum supply volume, For the expected maximum supply, These are the fitting coefficients; 13) Based on the description of the ultimate maximum photovoltaic supply capacity as the sum of the current photovoltaic supply capacity and the current scalable supply capacity, a model reflecting the photovoltaic supply capacity potential level is established as follows: (3) In the formula, This is the initial supply guarantee for photovoltaic power. The following uses the supply and insurance growth rate as an example. express, For the fitting adjustment coefficient, then Defined as the fitting adjustment amount; 14) / This is expressed as the potential level of photovoltaic power supply, using... This means that, through the changes, we get: (4) In the formula, For producers and consumers exist The potential level of photovoltaic power supply at any given time. These are the fitting coefficients. To develop the investment return period, The fitting adjustment coefficient is... This refers to the growth rate of supply volume.

2. The user-side transaction strategy analysis method based on supply and demand regulation according to claim 1, characterized in that, The preset supply and demand response model introduces a first parameter to control whether to promote or inhibit the supply of different producers and consumers, including: when Not greater than At that time, the supply of producers and consumers is encouraged, and the supply model is as follows: ; when Not less than At that time, the quantity supplied by producers and consumers is punished and suppressed. The supply model is as follows: ; when exist and In the interim, the supply model is: ,in As a regulating factor, ; in, , These represent the lower and upper limits of the photovoltaic power supply security potential level, respectively. The dividing point is adjustable. < < , and They represent producers and consumers, respectively. exist The basic supply and adjustable supply at any given time. , This represents the expected upper limit of electricity sales for the electricity seller.

3. The user-side transaction strategy analysis method based on supply and demand regulation according to claim 1, characterized in that, The preset supply and demand response models for different types of prosumers include residential, commercial, and industrial types, and the supply and demand response models include supply models and demand models. The demand model for resident-type prosumers is as follows: , For producers and consumers exist The basic load at any time, For producers and consumers exist Price elasticity coefficient at any given time; The demand model for commercial prosumers is as follows: , For producers and consumers exist The basic load at any time, For producers and consumers exist Price elasticity coefficient at any given time; The demand model for industrial prosumers is as follows: ,in, [-0.1, 0.1] represents the random influence factor.

4. The user-side transaction strategy analysis method based on supply and demand regulation according to claim 1, characterized in that, The first objective optimization function, which uses the difference between the first transaction electricity price and the transaction price to the grid as the revenue per unit of traded electricity, and combines this with the transaction electricity parameters to construct the maximum expected benefit for both producers and consumers (power buyers and sellers), includes: ； ； in, For electricity sellers The expected benefits For the electricity purchaser The expected benefits for The electricity price at any given time. The electricity purchase price at that moment. The price of electricity sold by producers and consumers to the grid. The price at which producers and consumers purchase electricity from the grid. and These are the deviation coefficients between the expected electricity sales volume and the actual reported electricity volume for the electricity purchaser / seller. For the number of transaction rounds, and The success rates of electricity transactions for both the buyer and seller are respectively. ； ； in, This represents the expected upper limit of electricity sales by the electricity seller. This represents the upper limit of the electricity purchaser's expected electricity purchase. and The electricity volume reported by the electricity purchaser and seller are respectively.

5. The user-side transaction strategy analysis method based on supply and demand regulation according to claim 1, characterized in that, The second objective optimization function is constructed based on the goals of maximizing the economic benefits for both the electricity purchaser and seller and maximizing the satisfaction of transaction volume requirements. The optimal solution for the second transaction volume is obtained by solving the second objective optimization function, including: Construct a social welfare maximization function and obtain multiple constraints on the social welfare maximization function. Solve the social welfare maximization function to obtain the optimal solution for the second transaction electricity. The social welfare maximization function is: ； ； in, Indicates social welfare. Total number of moments For time intervals, This indicates the collective benefits of market participants engaging in regional transactions. This refers to the network access fee paid during regional transactions. For abandoned light power, The price for abandoning light , These represent the total number of people purchasing / selling electricity, respectively. Indicates the cost of blocking. and For the second phase of the planned electricity purchase / sale, For the electricity sellers participating in the second phase The cost, For the electricity purchasers participating in the second phase The effect, For the benefit of the higher-level power grid, To make up for the final shortfall in the upper-level power grid.

6. The user-side transaction strategy analysis method based on supply and demand regulation according to claim 5, characterized in that, The constraints of the social welfare maximization function include: 1) Line transmission capacity constraints: ； 2) Power balance constraints: ； 3) Power supply constraints for prosumers: ； 4) Electricity consumption constraints for producers and consumers: 。 7. The user-side transaction strategy analysis method based on supply and demand regulation according to claim 1, characterized in that, The analysis of the second transaction volume based on the first producer-consumer yields a unified second transaction price for the first producer-consumer's purchase / sale of electricity from the upper-level power grid. This includes incorporating a social welfare electricity purchase / sale compensation factor based on the supply-demand ratio in the second transaction volume. , Construct a second transaction price pricing model, which includes: ； ； In the formula, and These represent the purchase price and the sale price of electricity, respectively. This is the electricity sales compensation factor. As a power purchase compensation factor, Supply and demand ratio; in, ， ； in, for The collective benefit of producers and consumers at time -1 For producers and consumers The optimal sales volume, For producers and consumers The optimal purchase volume.

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