Connection system and method suitable for green electricity transaction and electric energy market

Abstract

The invention discloses a connection method suitable for green electricity transaction and an electric energy market, and relates to the technical field of green electricity transaction, and the method specifically comprises the steps: 1, determining a green electricity transaction point, and carrying out the real-time monitoring of green electricity and electric energy transaction data in the green electricity transaction point; step 2, determining a supply-demand relationship balance index of the electric energy market, determining an electric energy basic price and an electric energy price error interval based on the supply-demand relationship balance index of the electric energy market, and determining a theoretical electric energy price formula by integrating the electric energy basic price and the supply-demand relationship balance index of the electric energy market; step 2, determining a supply-demand relationship balance index of green electricity transaction, and determining a unit green electricity average transaction price formula by adding a green electricity added value based on an electric energy basic price and a theoretical electric energy price formula, and step 4, constructing a green electricity transaction platform of a green electricity transaction point, and providing a transaction service for a green electricity power supplier and an electricity purchaser.

Description

Technical Field

[0001] The present invention belongs to the technical field of green electricity trading, and specifically relates to a system and method for connecting green electricity trading with an electric energy market. Background Art

[0002] In pursuit of sustainable development, zero-carbon energy, mainly renewable energy, is gradually becoming the main energy source of the power system. This change not only reflects the importance of environmental protection, but also indicates a major adjustment in the design of trading products in the power market. With the continuous development of the power market and the establishment of a carbon emissions trading system, the demand for clean energy by power users has increased dramatically, and the demand for a green power trading mechanism has become increasingly urgent.

[0003] Traditional electricity market price evaluation is mainly based on the power generation of non-renewable energy such as fossil energy, which cannot accurately reflect the environmental protection attributes and market value of green electricity. How to quantify the added value of green electricity based on the traditional electricity market price evaluation and reflect the environmental protection attributes and market value of green electricity through green electricity price evaluation are the problems that need to be solved in the current method of connecting green electricity trading with the electricity energy market. Summary of the invention

[0004] The purpose of the present invention is to provide a system and method for connecting green electricity trading with the electric energy market, so as to solve the technical problem of how to achieve the connection between green electricity trading and the electric energy market in the prior art.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The connection method between green electricity trading and the electricity energy market includes:

[0007] Step 1. Determine the green electricity trading points and conduct real-time monitoring of the green electricity and electric energy trading data within the green electricity trading points. The green electricity trading points represent the geographical scope and spatial area for green electricity trading. The power suppliers and electricity buyers for green electricity trading and electric energy trading are determined at the green electricity trading points. By connecting the data systems of both parties to the green electricity trading and electric energy trading, the green electricity trading data and electric energy trading data are collected in real time.

[0008] Step 2: Analyze the impact of the supply and demand relationship in the electricity market in each time zone on the changes in electricity prices. Determine the supply and demand balance index of the electricity market through electricity trading data. Based on the supply and demand balance index of the electricity market, determine the error range between the basic electricity price and the electricity price. Determine the theoretical electricity price formula by combining the basic electricity price with the supply and demand balance index of the electricity market.

[0009] Step 3: Determine the supply and demand balance index of green electricity trading through green electricity trading data, and determine the average unit green electricity trading price formula by adding the added value of green electricity based on the basic electricity price and theoretical electricity price formula;

[0010] Step 4: Build a green electricity trading platform for green electricity trading points to provide trading services for green electricity suppliers and buyers. Restrict the trading information of green electricity suppliers and buyers based on the formula of average trading price of unit green electricity. The green electricity trading platform matches power supply enterprises and buyers based on the green electricity trading matching degree according to the trading information.

[0011] Furthermore, the transaction data in step one includes supply data, consumption data, sales data, transaction price data and transaction time data. The green electricity transaction time data is used to determine the green electricity transaction time area, and the duration of each green electricity transaction time area is set to t. Each green electricity transaction time area contains at least one green electricity transaction. The green electricity transaction data contained in all green electricity transactions in each green electricity transaction time area is determined, and the same method is used to determine the electric energy transaction data contained in all electric energy transactions in each electric energy transaction time area.

[0012] Furthermore, in step 2, the formula represents the supply and demand balance index of the electric energy market, where x represents the xth time zone in chronological order, Lm(x) represents the supply and demand balance index in the electric energy transaction data of the xth time zone, q(x) represents the electric energy sales volume in the x-1th time zone, r(x-1) represents the electric energy consumption in the x-1th time zone, s(x) represents the electric energy supply in the xth time zone, and k q (x) represents the sales weight coefficient of the xth time period, k r (x) represents the consumption weight coefficient of the x-th time zone, and determines the basic electricity price and the error range of the electricity price based on the supply and demand balance index of the electricity market.

[0013] The supply and demand balance index is calculated by extracting the time zone in the historical electricity data where the electricity price remains unchanged for T time, T≤t, so as to determine the balance interval [a1, a2], where a2 is greater than e, a1 is less than e, and e is the median of the balance interval. The average electricity price when the supply and demand balance index is equal to e is taken as the basic electricity price. The electricity price error interval is obtained by calculating the difference between the basic electricity price and the electricity price corresponding to each supply and demand balance index in the balance interval, which is [y1, y2]. The theoretical electricity price formula is determined by combining the basic electricity price and the supply and demand balance index of the electricity market.

[0014] Using the formula represents the theoretical electricity price in each time zone, where f(x) represents the theoretical electricity price in the xth time zone, and f(x1) represents the basic unit electricity price in the time zone x1. The basic unit electricity price refers to the price of purchasing 1 unit of non-green electricity. Non-green electricity refers to electricity generated by non-renewable energy. The supply and demand balance index of the electricity market in the time zone x1 is equal to e. a and f are constant values. The error between the theoretical electricity price and the actual electricity price is determined within [y1, y2], and the specific sizes of a and f are determined when the error range is minimized, thereby determining the specific formula for the theoretical electricity price.

[0015] Furthermore, in step 3, we use the formula represents the supply-demand balance index of green electricity trading, where x represents the xth time zone in chronological order, Ld(x) represents the supply-demand balance index in the green electricity trading data of the xth time zone, Q(x-1) represents the green electricity sales volume in the x-1th time zone, R(x-1) represents the green electricity consumption in the x-1th time zone, S(x) represents the green electricity supply in the xth time zone, and k Q represents the green electricity sales weight coefficient, k R Represents the green electricity consumption weight coefficient.

[0016] Based on the basic electricity price and theoretical electricity price formula, the average transaction price formula of unit green electricity is determined by adding the added value of green electricity. The specific method is as follows:

[0017] Using the formula represents the average transaction price of green electricity per unit, where x represents the xth time zone, f(x1) represents the basic price of electricity per unit in the xth time zone, and k a (x) represents the weight coefficient of green electricity added value in the x-th time zone, d(x) represents the unit environmental value of green electricity in the x-th time zone, which refers to the carbon emission treatment cost saved by using 1 unit of green electricity compared with using 1 unit of non-green electricity, c(x) represents the cost value of green electricity in the x-th time zone, which refers to the additional cost generated by using green electricity compared with using non-green electricity, r(x) represents the green electricity sales quantity in the x-th time zone, which refers to the unit sales quantity of green electricity, and b(x) represents the unit green electricity subsidy in the x-th time zone, which refers to the subsidy value obtained by purchasing 1 unit of green electricity.

[0018] Furthermore, the minimum selling price lower limit and the maximum power purchase upper limit set in step 4, the green power trading platform matches the power supply enterprise and the power purchase enterprise through the green power transaction matching degree according to the transaction information, and uses the formula represents the green electricity transaction matching degree between the power supply enterprise and the power purchase enterprise, where i represents the i-th power supply enterprise, j represents the j-th power purchase enterprise, and O x(i, j) represents the green electricity transaction matching degree between the ith power supply enterprise and the jth power purchasing enterprise in the xth time zone, g is a constant, s(i, x) represents the power supply of the ith power supply enterprise in the xth time zone, w(j, x) represents the power purchase amount of the jth power purchasing enterprise in the xth time zone, n(j, x) represents the lower limit of the selling price of the ith power supply enterprise in the xth time zone, and m(i, x) represents the upper limit of the power purchase amount of the ith power purchasing enterprise in the xth time zone. The green electricity trading platform calculates the green electricity transaction matching degree of different power supply enterprises and power purchasing enterprises based on the transaction information, and matches the power supply enterprises and power purchasing enterprises that report the transaction information to the platform according to the level of green electricity transaction matching, giving priority to matching the power supply enterprises and power purchasing enterprises with the highest green electricity transaction matching degree.

[0019] The present invention also provides a connection system applicable to green electricity trading and electric energy market, which is applied to a connection method applicable to green electricity trading and electric energy market, specifically including:

[0020] The green electricity transaction data monitoring module is used to monitor the green electricity and electric energy transaction data in real time within the green electricity transaction point. The green electricity transaction point represents the geographical scope and spatial area where green electricity transactions are conducted. The power supplier and the power buyer who conduct green electricity transactions and electric energy transactions are determined in the green electricity transaction point. By connecting the data systems of both parties of the green electricity transaction and the electric energy transaction, the green electricity transaction data and the electric energy transaction data are collected in real time.

[0021] The electricity price evaluation module determines the supply and demand balance index and the basic electricity price of the electricity market by comparing the electricity supply data, electricity consumption data and electricity sales data. The electricity price error interval is obtained by calculating the difference between the basic electricity price and the electricity price corresponding to each supply and demand balance index in the balance interval. The theoretical electricity price formula is determined by combining the basic electricity price and the supply and demand balance index of the electricity market. The theoretical electricity price of each time zone is determined according to the theoretical electricity price formula.

[0022] The green electricity transaction price evaluation module determines the supply and demand balance index of green electricity transactions by comparing the green electricity supply data, green electricity consumption data and green electricity sales data. Based on the basic electricity price and theoretical electricity price formula, the unit green electricity average transaction price formula is determined by adding the green electricity added value. The unit green electricity average transaction price in each time zone is determined according to the unit green electricity average transaction price formula.

[0023] The green electricity trading platform management module builds a green electricity trading platform based on the information of each power supplier and power buyer at the green electricity trading point. The enterprise reports to the platform the transaction information including the specific amount of electricity supplied or purchased by the enterprise, the lower limit of the unit green electricity sales price or the upper limit of the unit green electricity purchase. According to the average unit green electricity transaction price in the time zone, the lower limit of the unit green electricity sales price or the upper limit of the unit green electricity purchase in the transaction information is restricted. The green electricity trading platform matches the power supply enterprise and the power buyer through the green electricity transaction matching degree according to the transaction information.

[0024] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0025] 1. The present invention calculates the supply-demand balance index of the electric energy market, takes the average electric energy price when the supply-demand balance index is equal to a specific value as the basic electric energy price, and determines the theoretical electric energy price in each time zone by combining the basic electric energy price with the supply-demand balance index. This price can provide price guidance for market participants, help them better grasp the market price dynamics, and improve the stability and sustainability of the market;

[0026] 2. The present invention is based on the basic price per unit of electric energy and expresses the average transaction price per unit of green electricity by adding the added value of green electricity, which helps to improve the rationality of setting the transaction price per unit of green electricity. Based on determining the unit electric energy price and the green electricity supply in each time zone, the changing trend of the green electricity transaction price with the change of the electric energy price is revealed, which improves the accuracy of predicting the price trend of the future green electricity market based on the price dynamics of the electric energy market;

[0027] 3. The present invention improves the establishment of a green electricity trading platform, centrally processes the transaction information of power supply enterprises and power purchasing enterprises, and can quickly match the supply and demand parties. Enterprises only need to declare transaction information on the platform according to demand, including specific electricity volume, the lower limit of the unit green electricity sales price or the upper limit of electricity purchase. The platform can automatically calculate the matching degree based on this information and quickly find the most suitable trading party. This method simplifies the transaction process, reduces the intermediate links, and thus significantly improves the efficiency of green electricity transactions. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 A step diagram showing a method for linking green electricity trading with the electric energy market;

[0030] Figure 2 A method step diagram for obtaining the average transaction price of unit green electricity is shown;

[0031] Figure 3 A flowchart of a system for linking green electricity trading with the electric energy market is shown. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Embodiment 1, as Figure 1 , Figure 2 As shown, the method for connecting green electricity trading with the electric energy market proposed in this embodiment specifically includes the following steps:

[0034] Step 1: determine the green electricity trading point, and monitor the green electricity and electric energy trading data in the green electricity trading point in real time. The green electricity trading point represents the geographical scope and spatial area for green electricity trading. In this embodiment, the green electricity trading point is determined by province, that is, each green electricity trading point corresponds to the geographical scope and spatial area of ​​each province. The power supplier and the power buyer who conduct green electricity trading and electric energy trading are determined in the green electricity trading point. By connecting the data systems of the two parties of green electricity trading and electric energy trading, the green electricity trading data and electric energy trading data are collected in real time;

[0035] The transaction data includes supply data, consumption data, sales data, transaction price data and transaction time data. The green electricity transaction time data is used to determine the green electricity transaction time area. Each green electricity transaction time area contains at least one green electricity transaction. All green electricity transaction data in each green electricity transaction time area are determined, and the duration of each time area is set to t. In this embodiment, t is equal to one week. The same method is used to determine all electric energy transaction data in each electric energy transaction time area.

[0036] Step 2: Determine the balance index of supply and demand in the electric energy market through electric energy transaction data, determine the error range between the basic electric energy price and the electric energy price based on the balance index of supply and demand in the electric energy market, and determine the theoretical electric energy price formula by combining the basic electric energy price and the balance index of supply and demand in the electric energy market;

[0037] Determine the supply and demand relationship between the power supplier and the power buyer, collect historical power transaction data, and determine the supply and demand balance index of the power market by comparing the power supply data, power consumption data and power sales data. The specific formula for the supply and demand balance index of power trading is as follows:

[0038]

[0039] The historical electric energy transaction data are divided according to the order of electric energy transaction time, where x represents the xth time zone in the time sequence, Lm(x) represents the supply and demand balance index in the electric energy transaction data in the xth time zone, q(x) represents the electric energy sales volume in the x-1th time zone, r(x-1) represents the electric energy consumption in the x-1th time zone, s(x) represents the electric energy supply in the xth time zone, and k q (x) represents the sales weight coefficient of the xth time period, k r (x) represents the consumption weight coefficient of the xth time zone. These weight coefficients can be determined according to specific circumstances and needs, and are usually jointly formulated and confirmed by professionals or relevant stakeholders. For example, when the electricity demand in the xth time zone increases, k q (x) and k r (x) There is an increase with respect to the previous time period, and the enhancement ratio is equal to the increase ratio of electricity demand with respect to the previous time period.

[0040] The supply and demand balance index is calculated by extracting the time zone in the historical electric energy data where the electric energy price remains unchanged for T time, T≤t, and T is equal to t / 2 in this embodiment, so as to determine the balance interval [a1, a2], where a2 is greater than e, a1 is less than e, and e is the median of the balance interval. If the supply and demand balance index of a time zone is less than a1, it is judged that the electric energy supply in the time zone is greater than the electric energy demand. If the supply and demand balance index of a time zone is greater than a2, it is judged that the electric energy supply in the time zone is less than the electric energy demand. If the supply and demand balance index of a time zone is within the balance interval, it is judged that the electric energy supply in the time zone meets the electric energy demand. The average electric energy price when the supply and demand balance index is equal to e is taken as the basic electric energy price. By calculating the difference between the basic electric energy price and the electric energy prices corresponding to each supply and demand balance index in the balance interval, the electric energy price error interval is obtained as [y1, y2].

[0041] The theoretical electricity price formula is determined by integrating the basic electricity price and the supply and demand balance index of the electricity market. The specific formula is as follows:

[0042]

[0043] Among them, f(x) represents the theoretical electricity price in the xth time zone, f(x1) represents the basic price of unit electricity in the time zone x1, the supply and demand balance index of the electricity market in the time zone x1 is equal to e, a and f are constant values, and the error value between the theoretical electricity price and the actual electricity price is determined to be within [y1, y2], and the specific sizes of a and f when the error range is minimum, thereby determining the specific formula of the theoretical electricity price.

[0044] Step 3: Determine the supply and demand balance index of green electricity trading through green electricity trading data, and determine the average unit green electricity trading price formula by adding the added value of green electricity based on the basic electricity price and theoretical electricity price formula;

[0045] Determine the supply and demand relationship between green electricity suppliers and electricity buyers, collect historical green electricity transaction data, and determine the supply and demand balance index of green electricity transactions by comparing green electricity supply data, green electricity consumption data and green electricity sales data. The specific formula for the supply and demand balance index of green electricity transactions is as follows:

[0046]

[0047] The historical electric energy transaction data are divided according to the electric energy transaction time sequence, where x represents the xth time zone in the time sequence, Ld(x) represents the supply and demand balance index in the green electricity transaction data in the xth time zone, Q(x-1) represents the green electricity sales in the x-1th time zone, R(x-1) represents the green electricity consumption in the x-1th time zone, S(x) represents the green electricity supply in the xth time zone, and k Q represents the green electricity sales weight coefficient, k R Represents the weight coefficient of green electricity consumption. These weight coefficients can be determined according to specific circumstances and needs, and are usually jointly formulated and confirmed by professionals or relevant stakeholders.

[0048] Determine all green electricity transaction price data within a time zone, obtain the average green electricity transaction price of the corresponding green electricity transaction point in the time zone, and obtain the changing trend of the average green electricity transaction price in different time zones by drawing a time series graph of the average green electricity transaction price.

[0049] Furthermore, based on the basic electricity price and theoretical electricity price formula, the average transaction price formula of unit green electricity is determined by adding the added value of green electricity. The specific formula is as follows:

[0050]

[0051] Where x represents the xth time zone, v(x) represents the average transaction price of green electricity per unit in the xth time zone, f(x1) represents the basic price of electricity per unit in the xth time zone, and ka (x) represents the weight coefficient of green electricity added value in the x-th time zone, d(x) represents the unit environmental value of green electricity in the x-th time zone, c(x) represents the cost value of green electricity in the x-th time zone, r(x) represents the sales volume of green electricity in the x-th time zone, and b(x) represents the unit green electricity subsidy in the x-th time zone.

[0052] Furthermore, the unit electricity basic price refers to the price of purchasing 1 unit of non-green electricity. Non-green electricity refers to electricity generated by non-renewable energy. In this embodiment, 1 unit refers to 1MWh of electricity.

[0053] The unit environmental value of green electricity refers to the carbon emission treatment cost saved by using one unit of green electricity compared to using one unit of non-green electricity, such as the penalty, tax or cost avoided in the carbon trading market due to the reduction of carbon emissions;

[0054] Green electricity cost value refers to the additional cost of using green electricity compared to using non-green electricity, such as the increased grid access fee and technology upgrade cost due to the use of green electricity;

[0055] Green electricity sales volume refers to the sales volume of green electricity units;

[0056] Unit green electricity subsidy refers to the subsidy value obtained by purchasing 1 unit of green electricity;

[0057] Based on determining the unit electricity price and green electricity supply in each time zone, the average unit green electricity transaction price is obtained, thereby determining the changing trend of the green electricity transaction price in each time zone as the electricity price changes.

[0058] Step 4: Build a green electricity trading platform for green electricity trading points to provide trading services for green electricity suppliers and buyers. Restrict the trading information of green electricity suppliers and buyers according to the formula of average trading price of green electricity per unit. The green electricity trading platform matches power supply enterprises and buyers based on the green electricity trading matching degree according to the trading information.

[0059] In the green electricity trading platform, enterprises report transaction information to the platform according to demand. The transaction information includes power supply information or power purchase information. The transaction information needs to include the specific amount of power supplied or purchased by the enterprise. The power supply enterprise needs to set the lower limit of the unit green electricity price in the transaction information, and the power purchasing enterprise needs to set the upper limit of the unit green electricity purchase in the transaction information. The unit green electricity in the same time area has a settable minimum price lower limit and a maximum purchase upper limit. The price difference U is set. The theoretical electricity price is determined by the average unit electricity price in the electricity market in the current time area. Then, the balance index of the supply and demand relationship of the electricity in the time area is calculated, and the supply and demand balance index of the green electricity transaction in the time area is combined to determine the average transaction price of the unit green electricity in the time area. The lower limit of the minimum price in the same time area is equal to v(x)-U, and the upper limit of the purchase of electricity in the same time area is equal to v(x)+U, where U is determined according to specific circumstances and needs, and is usually jointly formulated and confirmed by professionals or relevant stakeholders. In this embodiment, it is set The green electricity trading platform matches power supply enterprises and power purchasing enterprises through the green electricity trading matching degree based on the transaction information. The specific formula for the green electricity trading matching degree between power supply enterprises and power purchasing enterprises is as follows:

[0060]

[0061] Where i represents the i-th power supply enterprise, j represents the j-th power purchasing enterprise, O x (i, j) represents the green electricity transaction matching degree between the ith power supply enterprise and the jth power purchasing enterprise in the xth time zone, g is a constant, s(i, x) represents the power supply of the ith power supply enterprise in the xth time zone, w(j, x) represents the power purchase amount of the jth power purchasing enterprise in the xth time zone, n(j, x) represents the lower limit of the selling price of the ith power supply enterprise in the xth time zone, and m(i, x) represents the upper limit of the power purchase amount of the ith power purchasing enterprise in the xth time zone. The green electricity trading platform calculates the green electricity transaction matching degree of different power supply enterprises and power purchasing enterprises based on the transaction information, and matches the power supply enterprises and power purchasing enterprises that report the transaction information to the platform according to the level of green electricity transaction matching, giving priority to matching the power supply enterprises and power purchasing enterprises with the highest green electricity transaction matching degree. If no transaction occurs between the matched power supply enterprises and power purchasing enterprises, the power supply enterprises and power purchasing enterprises will continue to be matched with potential transaction objects with high green electricity transaction matching degree according to the level of green electricity transaction matching degree, so as to improve transaction efficiency.

[0062] The green electricity trading platform integrates resources from all parties, uses green electricity trading matching to optimize the trading process, reduce transaction costs, and promote the effective connection between green electricity trading and the electricity energy market.

[0063] Embodiment 2, as Figure 3As shown, the connection system applicable to green electricity trading and electric energy market proposed in this embodiment specifically includes the following contents:

[0064] The green electricity transaction data monitoring module is used to monitor the green electricity and electric energy transaction data in the green electricity transaction point in real time. The green electricity transaction point represents the geographical scope and spatial area for green electricity transaction. The power supplier and the electricity buyer who conduct green electricity transaction and electric energy transaction are determined in the green electricity transaction point. By connecting the data systems of the two parties of green electricity transaction and electric energy transaction, the green electricity transaction data and electric energy transaction data are collected in real time, and the green electricity transaction time area is determined. Each time area contains at least one green electricity transaction. The green electricity transaction data contained in all green electricity transactions in each time area are determined, and the electric energy transaction data contained in all electric energy transactions in each time area are determined using the same method.

[0065] The electric energy price evaluation module determines the supply and demand balance index of the electric energy market by comparing the electric energy supply data, the electric energy consumption data and the electric energy sales data, and sets the balance interval of the supply and demand balance index according to the specific situation and demand. If the supply and demand balance index of a time zone is less than the minimum value of the balance interval, it is judged that the electric energy supply in the time zone is greater than the electric energy demand. If the supply and demand balance index of a time zone is greater than the maximum value of the balance interval, it is judged that the electric energy supply in the time zone is less than the electric energy demand. If the supply and demand balance index of a time zone is within the balance interval, it is judged that the electric energy supply in the time zone meets the electric energy demand. The average electric energy price when the supply and demand balance index is equal to e is taken as the basic electric energy price. The electric energy price error interval is obtained by calculating the difference between the basic electric energy price and the electric energy price corresponding to each supply and demand balance index in the balance interval. The theoretical electric energy price formula is determined by combining the basic electric energy price and the supply and demand balance index of the electric energy market.

[0066] The green electricity transaction price evaluation module determines the supply and demand balance index of green electricity transactions by comparing the green electricity supply data, green electricity consumption data and green electricity sales data, determines all green electricity transaction price data in a time zone, and obtains the average green electricity transaction price for the corresponding green electricity transaction point in the time zone. Based on the basic electricity price and the theoretical electricity price formula, the unit green electricity average transaction price formula is determined by adding the green electricity added value, and the unit green electricity average transaction price is obtained based on the unit electricity price and green electricity supply in each time zone, thereby determining the changing trend of the green electricity transaction price in each time zone with the change of electricity price.

[0067] The green electricity trading platform management module builds a green electricity trading platform based on the information of each power supplier and power purchaser at the green electricity trading point. The enterprise reports the trading information to the platform according to the demand. The trading information includes power supply information or power purchase information. The trading information needs to include the specific amount of power supplied or purchased by the enterprise. The power supply enterprise needs to set the lower limit of the unit green electricity sales price in the trading information, and the power purchaser needs to set the upper limit of the unit green electricity purchase in the trading information. The unit green electricity in the same time and region has a settable minimum lower limit of sales price and maximum upper limit of power purchase. The green electricity trading platform matches the power supply enterprise and the power purchaser through the green electricity trading matching degree according to the trading information, so as to achieve the purpose of improving trading efficiency.

[0068] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0069] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for linking green electricity trading with the electricity energy market, characterized in that: include: Step 1: determine the green electricity trading point, monitor the green electricity and electric energy trading data in the green electricity trading point in real time, determine the power supplier and power buyer who conduct green electricity trading and electric energy trading in the green electricity trading point, and collect the green electricity trading data and electric energy trading data in real time by connecting the data systems of the two parties of the green electricity trading and electric energy trading; Step 2: Determine the balance index of supply and demand in the electric energy market through electric energy transaction data, determine the error range between the basic electric energy price and the electric energy price based on the balance index of supply and demand in the electric energy market, and determine the theoretical electric energy price formula by combining the basic electric energy price and the balance index of supply and demand in the electric energy market; Step 3: Determine the supply and demand balance index of green electricity trading through green electricity trading data, and determine the average unit green electricity trading price formula by adding the added value of green electricity based on the basic electricity price and theoretical electricity price formula; Step 4: Build a green electricity trading platform for green electricity trading points to provide trading services for green electricity suppliers and buyers. Restrict the trading information of green electricity suppliers and buyers based on the formula of average trading price of unit green electricity. The green electricity trading platform matches power supply enterprises and buyers based on the green electricity trading matching degree according to the trading information.

2. The method for connecting green electricity trading with the electric energy market according to claim 1 is characterized in that: Green electricity transaction data and electric energy transaction data, including: Green electricity transaction data includes green electricity supply data, green electricity consumption data, green electricity sales data, green electricity transaction price data and green electricity transaction time data; Electric energy transaction data includes electric energy supply data, electric energy consumption data, electric energy sales data, electric energy transaction price data and electric energy transaction time data.

3. The method for connecting green electricity trading with the electric energy market according to claim 1 is characterized in that: Determine the balance index of supply and demand in the electric energy market. The specific method is as follows: Using the formula represents the supply and demand balance index of the electric energy market, where x represents the xth time zone in chronological order, Lm(x) represents the supply and demand balance index in the electric energy transaction data of the xth time zone, q(x) represents the electric energy sales volume in the x-1th time zone, r(x-1) represents the electric energy consumption in the x-1th time zone, s(x) represents the electric energy supply in the xth time zone, and k q (x) represents the sales weight coefficient of the xth time period, k r (x) represents the consumption weight coefficient of the x-th time zone.

4. The method for connecting green electricity trading with the electric energy market according to claim 1 is characterized in that: Based on the balance index of supply and demand in the electric energy market, the error range between the basic price of electric energy and the price of electric energy is determined. The specific method is as follows: The supply and demand balance index is calculated by extracting the time zone in the historical electric energy data where the electric energy price remains unchanged for T time, T≤t, so as to determine the balance interval [a1, a2], where a2 is greater than e, a1 is less than e, and e is the median of the balance interval. The average electric energy price when the supply and demand balance index is equal to e is taken as the basic electric energy price. The difference between the basic electric energy price and the electric energy price corresponding to each supply and demand balance index in the balance interval is calculated to obtain the electric energy price error interval [y1, y2].

5. The method for connecting green electricity trading with the electric energy market according to claim 4 is characterized in that: The theoretical electricity price formula is determined by integrating the basic electricity price and the supply and demand balance index of the electricity market. The specific method is: Using the formula represents the theoretical electricity price in each time zone, where f(x) represents the theoretical electricity price in the xth time zone, and f(x1) represents the basic unit electricity price in the time zone x1. The basic unit electricity price refers to the price of purchasing 1 unit of non-green electricity. Non-green electricity refers to electricity generated by non-renewable energy. The supply and demand balance index of the electricity market in the time zone x1 is equal to e. a and f are constant values. The error between the theoretical electricity price and the actual electricity price is determined within [y1, y2], and the specific sizes of a and f are determined when the error range is minimized, thereby determining the specific formula for the theoretical electricity price.

6. The method for connecting green electricity trading with the electric energy market according to claim 1 is characterized in that: Determine the supply and demand balance index of green electricity trading. The specific method is as follows: Using the formula represents the supply-demand balance index of green electricity trading, where x represents the xth time zone in chronological order, Ld(x) represents the supply-demand balance index in the green electricity trading data of the xth time zone, Q(x-1) represents the green electricity sales volume in the x-1th time zone, R(x-1) represents the green electricity consumption in the x-1th time zone, S(x) represents the green electricity supply in the xth time zone, and k Q represents the green electricity sales weight coefficient, k R Represents the green electricity consumption weight coefficient.

7. The method for connecting green electricity trading with the electric energy market according to claim 1 is characterized in that: Based on the basic electricity price and theoretical electricity price formula, the average transaction price formula of unit green electricity is determined by adding the added value of green electricity. The specific method is as follows: Using the formula represents the average transaction price of green electricity per unit, where x represents the xth time zone, f(x1) represents the basic price of electricity per unit in the xth time zone, and k a (x) represents the weight coefficient of green electricity added value in the x-th time zone, d(x) represents the unit environmental value of green electricity in the x-th time zone, c(x) represents the cost value of green electricity in the x-th time zone, r(x) represents the sales volume of green electricity in the x-th time zone, and b(x) represents the unit green electricity subsidy in the x-th time zone.

8. The method for connecting green electricity trading with the electric energy market according to claim 1 is characterized in that: The green electricity trading platform matches power supply enterprises and power purchasing enterprises based on the green electricity trading matching degree according to the transaction information. The specific method is as follows: The minimum selling price and the maximum power purchase limit are set. The green power trading platform matches the power supply enterprises and power purchase enterprises based on the green power trading matching degree according to the transaction information, and uses the formula represents the green electricity transaction matching degree between the power supply enterprise and the power purchase enterprise, where i represents the i-th power supply enterprise, j represents the j-th power purchase enterprise, and O x (i, j) represents the green electricity transaction matching degree between the ith power supply enterprise and the jth power purchasing enterprise in the xth time zone, g is a constant, s(i, x) represents the power supply of the ith power supply enterprise in the xth time zone, w(j, x) represents the power purchase amount of the jth power purchasing enterprise in the xth time zone, n(j, x) represents the lower limit of the selling price of the ith power supply enterprise in the xth time zone, and m(i, x) represents the upper limit of the power purchase amount of the ith power purchasing enterprise in the xth time zone. The green electricity trading platform calculates the green electricity transaction matching degree of different power supply enterprises and power purchasing enterprises based on the transaction information, and matches the power supply enterprises and power purchasing enterprises that report the transaction information to the platform according to the level of green electricity transaction matching, giving priority to matching the power supply enterprises and power purchasing enterprises with the highest green electricity transaction matching degree.

9. A system for connecting green electricity trading and electric energy market, applied to the method for connecting green electricity trading and electric energy market as claimed in any one of claims 1 to 8, characterized in that: Specifically include: The green electricity transaction data monitoring module is used to monitor the green electricity and electric energy transaction data in real time within the green electricity transaction point. The green electricity transaction point represents the geographical scope and spatial area where green electricity transactions are conducted. The power supplier and the power buyer who conduct green electricity transactions and electric energy transactions are determined in the green electricity transaction point. By connecting the data systems of both parties of the green electricity transaction and the electric energy transaction, the green electricity transaction data and the electric energy transaction data are collected in real time. The electricity price evaluation module determines the supply and demand balance index and the basic electricity price of the electricity market by comparing the electricity supply data, electricity consumption data and electricity sales data. The electricity price error interval is obtained by calculating the difference between the basic electricity price and the electricity price corresponding to each supply and demand balance index in the balance interval. The theoretical electricity price formula is determined by combining the basic electricity price and the supply and demand balance index of the electricity market. The theoretical electricity price of each time zone is determined according to the theoretical electricity price formula. The green electricity transaction price evaluation module determines the supply and demand balance index of green electricity transactions by comparing the green electricity supply data, green electricity consumption data and green electricity sales data. Based on the basic electricity price and theoretical electricity price formula, the unit green electricity average transaction price formula is determined by adding the green electricity added value. The unit green electricity average transaction price in each time zone is determined according to the unit green electricity average transaction price formula. The green electricity trading platform management module builds a green electricity trading platform based on the information of each power supplier and power buyer at the green electricity trading point. The enterprise reports to the platform the transaction information including the specific amount of electricity supplied or purchased by the enterprise, the lower limit of the unit green electricity sales price or the upper limit of the unit green electricity purchase. According to the average unit green electricity transaction price in the time zone, the lower limit of the unit green electricity sales price or the upper limit of the unit green electricity purchase in the transaction information is restricted. The green electricity trading platform matches the power supply enterprise and the power buyer through the green electricity transaction matching degree according to the transaction information.

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