Virtual power plant capacity electricity price pricing method considering power failure loss

Abstract

The invention provides a virtual power plant capacity electricity price pricing method considering power failure loss. According to the method, firstly, for a large number of distributed resources and randomness and volatility of loads, monthly electric power and electric quantity balance conditions of a regional power grid in the recent year are analyzed through data provided by a power grid enterprise; secondly, according to the national total production value (GDP) and the total generating capacity of the year, the GDP value of electricity loss per kilowatt-hour is obtained through calculation, and the total capacity subsidy amount of the power grid for completing the transaction is formulated; and finally, the total amount is converted according to an insurance value conversion method in the actual financial field, further, a total capacity electric charge value paid by an actual power grid is obtained after the response rate of the virtual power plant is considered, and a standard capacity electric charge value is obtained after the total capacity electric charge value is converted to unit capacity. Through the above steps, the virtual power plant capacity electricity price pricing method considering the power failure loss is designed, and a relatively accurate capacity electricity price standard value is obtained through the calculation method.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plant capacity electricity price pricing, and in particular to a virtual power plant capacity electricity price pricing method taking power outage losses into consideration. Background Art

[0002] A virtual power plant is a power coordination and management system that uses advanced information and communication technologies and software systems to aggregate and coordinate DERs such as DG, energy storage systems, controllable loads, and electric vehicles, so that it can participate in the electricity market and grid operations as a special power plant. It mainly includes coordinated control technology, smart metering technology, and information and communication technology to provide management and auxiliary services for distribution and transmission networks.

[0003] At present, virtual power plants are still facing unreasonable capacity electricity charges, which reduces their reliability. In order to promote virtual power plants to participate in peak demand response, the power grid should give capacity subsidies to virtual power plants to encourage the active construction of virtual power plants. Therefore, in this context, the present invention proposes a virtual power plant capacity electricity price pricing method that takes into account power outage losses. It is based on a comprehensive analysis of the load data and power generation conditions of the regional power grid in the past year, and by considering factors such as power outage losses, insurance value, and virtual power plant response rate, the unit capacity electricity price is finally calculated. This method has broad application prospects and practical significance, and clarifies the theoretical basis for virtual power plants to formulate capacity electricity charges. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the shortcomings of the prior art, the present invention provides a method for pricing the capacity electricity price of a virtual power plant taking into account power outage losses, thereby solving the problems mentioned in the above background technology.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a virtual power plant capacity electricity price pricing method considering power outage losses, specifically comprising the following steps:

[0008] Step 1: Collect monthly power data of the regional power grid within the target time of the basic target, the target time is one year, and then analyze the monthly power balance of the regional power grid within the target time, where the basic target is the power plant;

[0009] Step 2: Obtain the gross national product and total power generation within the target time, calculate the gross national product per kilowatt-hour of electricity loss, and work out the total capacity subsidy that the grid needs to pay to complete the transaction;

[0010] Step 3: Then, according to the calculation result of the total capacity subsidy, the insurance value is applied to the capacity electricity fee field, and the total capacity subsidy is converted according to the insurance value;

[0011] Step 4: Convert the actual virtual power plant response rate according to the converted total capacity subsidy to obtain the total capacity electricity fee under the actual response rate;

[0012] Step 5: At this time, the total capacity electricity fee under the actual response rate is converted to unit capacity to obtain the standard value of capacity electricity fee.

[0013] As an improved technical solution, the specific method of analyzing the monthly power balance of the regional power grid within the target time in step 1 is:

[0014] First, summarize and analyze the monthly power balance of the regional power grid within a year, and mark the power demand and supply of the set month;

[0015] Then, through detailed data collection and statistical analysis of power load and power generation in each month, the supply and demand balance of the power system throughout the year is determined.

[0016] As an improved technical solution, when marking the electricity demand and supply conditions of the set months, the electricity demand and supply conditions from July to August are specifically marked.

[0017] As an improved technical solution, in step 5, the total amount of capacity electricity charges under the actual response rate is converted to unit capacity to obtain the capacity electricity charge standard value in a specific manner as follows:

[0018] Based on the analysis results of the regional power grid's power balance in July and August, the virtual power plant was enabled to participate in peak demand response in July and August, that is, capacity electricity charges were provided to the virtual power plant, and the standard value of the capacity electricity charge was obtained through a series of calculation and conversion processes.

[0019] As an improved technical solution, the specific calculation method of obtaining the standard value of capacity electricity fee through a series of calculation and conversion processes is:

[0020] F m =6Qα / kw (1)

[0021] F m =8Qα / kw (2).

[0022] As an improved technical solution, when the total capacity electricity charge under the actual response rate is obtained in step four, the actual response rate refers to the actual response capability of the virtual power plant after receiving the dispatch instruction, that is, its power supply reliability and timeliness under different load conditions.

[0023] As an improved technical solution, when converting to unit capacity to obtain the capacity electricity fee standard value in step 5, all calculation results are converted to unit capacity. By comprehensively considering the analysis results of the above steps, the unit capacity electricity price of the virtual power plant is calculated.

[0024] (III) Beneficial effects

[0025] The present invention provides a virtual power plant capacity electricity price pricing method that takes into account power outage losses. Compared with the prior art, it has the following beneficial effects:

[0026] First, the present invention proposes a method for formulating capacity electricity charges for virtual power plants, which can obtain a more reasonable capacity electricity charge under the circumstances that the rapid development of comprehensive energy and the access of large-scale new energy power generation also have strong randomness and volatility, which makes it difficult for the operation of virtual power plants; second, the present invention uses the GDP loss per kilowatt-hour of local electricity as the power outage loss, which provides a basis for dynamic adjustment for the formulation of capacity electricity charges in other regions; third, the present invention introduces insurance value into the calculation of capacity electricity charges, which helps to more accurately reflect the reliability and elasticity of power supply on the basis of calculating power outage losses. Formulating reasonable capacity electricity charges plays an important role in stimulating the positive response of virtual power plants, and the calculation results as the capacity subsidy benchmark enable this method to be widely used. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A block diagram of a virtual power plant capacity electricity price pricing method taking into account power outage losses shown in an embodiment of the present application;

[0028] Figure 2 Changes in planned adjustable capacity, average maximum adjustable output and maximum power consumption (unit: megawatt);

[0029] Figure 3 Changes in adjustable capacity, expected maximum load and reserve capacity (in megawatts);

[0030] Figure 4 Step flow and calculation process framework diagram. DETAILED DESCRIPTION

[0031] 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.

[0032] See also Figure 1-Figure 4 In order to achieve the above-mentioned purpose, the present invention proposes a virtual power plant capacity electricity price pricing method considering power outage losses, comprising the following steps:

[0033] Step 1: Analyze the monthly power balance of the regional power grid in the past year.

[0034] Step 2: Based on the gross domestic product (GDP) and total power generation for that year, calculate the GDP value of each kilowatt-hour of electricity loss and work out the total capacity subsidy the grid needs to pay to complete the transaction.

[0035] Step 3: Based on the calculation result of the total capacity subsidy in step 2, apply the insurance value to the capacity electricity fee field and convert the total capacity subsidy according to the insurance value.

[0036] Step 4: Based on the converted total capacity subsidy amount in step 3, convert it according to the actual virtual power plant response rate to obtain the total capacity electricity fee under the actual response rate.

[0037] Step 5: Based on the total amount of capacity electricity charges under the actual response rate in step 4, convert it to unit capacity to obtain the standard value of capacity electricity charges.

[0038] The power balance analysis process used in step 1 is as follows:

[0039] The power balance analysis is generally carried out on an annual basis. The commonly used traditional method is the table analysis method based on typical days. The following is an analysis of the power balance of a regional power grid in the past year based on the monthly power balance of a regional power grid in the past year. In the current power system, the power balance problem is no longer the main challenge, but the contradiction of power balance is still prominent. Therefore, the analysis of power balance has become a research focus.

[0040] Power (load) balance is an instantaneous balance. Power balance predicts whether the available installed capacity in the region can meet the peak load demand. For the annual time scale power balance analysis problem, this time we use monthly balance analysis.

[0041] The monthly power balance of a regional power grid in the past year is shown in Table 1.

[0042] Table 1 Monthly power balance of a regional power grid in the past year (unit: megawatt)

[0043]

[0044]

[0045] By analyzing the above data, we can derive the basic formula for power balance of provincial power grid:

[0046] Planned adjustable capacity = average maximum adjustable output + maximum power received (generation angle)

[0047] Planned adjustable capacity = expected maximum load + spare capacity = expected average maximum load + spare capacity (power consumption perspective)

[0048] Available installed capacity > maximum load × (1 + reserve rate), indicating that the regional power supply is sufficient. Among them, the load reserve rate is the ratio of the load reserve capacity to the maximum load of the power system. The reserve rate is related to factors such as the scale of the regional power grid and the power structure.

[0049] The changes in the planned adjustable capacity, average maximum adjustable output and maximum power consumption of a regional power grid in the past year are as follows: Figure 1 As shown, electricity consumption was at a low point in April and May. Later, as the temperature rose, high-power refrigeration equipment was put into use, which required the generator sets to increase the adjustable output and purchase electricity from other provinces to ensure the imbalance caused by extreme weather or the randomness of new energy in a certain area. Therefore, the power supply also increased. The peak of electricity consumption appeared in July and August. The adjustable output and maximum power supply were appropriately increased to meet the power balance. As the temperature dropped, the use of refrigeration equipment decreased, and the adjustable output and maximum power supply decreased accordingly. The temperature continued to drop, and high-power heating equipment began to work. The peak of electricity consumption was reached in January and February. In order to meet the peak load demand of electricity, the adjustable output and maximum power supply began to increase.

[0050] The changes in the planned adjustable capacity, expected maximum load and reserve capacity of a regional power grid in the past year are as follows: Figure 2 As shown in the figure, the analysis of planned adjustable capacity and expected maximum load is Figure 1 The reserve capacity in the power system is the capacity of the generator sets in the power grid that are in standby state and the remaining capacity that is generating electricity but not fully generated. The reason why the system needs reserve capacity is mainly due to the characteristics of the power industry production and the imbalance of users' electricity consumption. The production, transmission and consumption of electric energy are almost carried out at the same time, and electric energy cannot be stored in large quantities. The electricity consumption of users is random and unbalanced. Therefore, in order to ensure the safe, reliable and continuous power generation and supply of the power system, sufficient reserve capacity must be set.

[0051] The balance between the load and the supply and demand of the power system is planned in advance, but this plan is an estimated value of the forecast. In actual operation, the power system must meet the unexpected load requirements of the system, which also requires a certain amount of spare capacity. The figure shows the positive spare capacity and negative spare capacity. Once the load of the power grid increases, the grid dispatcher can immediately require these units to take on the load. This is the so-called positive spare capacity. At the same time, during the off-peak period, if all units have been compressed to the minimum output, if the load continues to decrease, there will be no room for further power generation, and they can only shut down. Therefore, negative spare capacity should be reserved to track the load regulation frequency.

[0052] like Figure 2As shown in the figure, there is sufficient reserve capacity in each month of the past year, and the reserve capacity is the largest in June. However, the larger the reserve capacity, the better. If the reserve capacity is set too large, the investment cost of power supply construction will increase. If the system's reserve capacity is insufficient, it will directly lead to a decrease in power supply reliability. Therefore, the size of the monthly reserve capacity is in dynamic change, which is related to equipment failure, dry season, load fluctuation and prediction error.

[0053] Step 2: Based on the gross national product (GDP) and total power generation of the year, calculate the GDP value of each kilowatt-hour of electricity loss and work out the total capacity subsidy that the grid needs to pay to complete the transaction. The specific instructions are as follows:

[0054] The definition of power outage loss is clarified and calculated. The calculation method of power outage loss needs to consider the economic losses caused by power outages to different users, the social impact and the impact on the stability of the power grid. By establishing a power outage loss calculation model, the specific impact of power outage events on various types of users is quantified to provide data support for subsequent calculations. The present invention uses GDP per kilowatt-hour of electricity loss to describe power outage losses, that is, the losses caused by power outages to the social economy.

[0055] By calculating the responsiveness of virtual power plants under different load conditions and their contribution to reducing power outages, the economic value of virtual power plants in reducing power outage losses can be clarified. This value can be converted into a subsidy basis for capacity electricity charges, thereby optimizing the subsidy mechanism for the power system. Specifically, the responsiveness of virtual power plants can be evaluated by their power supply stability and rapid response capabilities during high-load periods. Through the analysis of historical data and model prediction, the power outage reduction benefits of virtual power plants under different scenarios can be quantified. After converting this benefit into economic value, it can be used as part of the capacity electricity fee subsidy to encourage virtual power plants to improve their responsiveness and power supply reliability.

[0056] Step 3 uses the calculation result of the total capacity subsidy in step 2 as a basis, applies the insurance value to the capacity electricity fee field, and converts the total capacity subsidy according to the insurance value. The specific instructions are as follows:

[0057] The process of allocating the total capacity subsidy amount according to the insurance value needs to consider the power supply reliability and response speed of the virtual power plant at peak load to ensure that the allocated subsidy amount can maximize the overall stability and reliability of the power system. The total capacity subsidy amount obtained in step 2 is equivalent to the insurance amount, which is generally 15-20 times the insurance premium. This multiple is the converted value of the insurance value. The capacity electricity fee paid to the virtual power plant is equivalent to the insurance premium that guarantees its ready availability. Therefore, the total capacity subsidy amount is converted according to the insurance value to obtain the insurance premium that is available at any time. In this way, the capacity electricity fee of the virtual power plant can not only reflect its actual power supply capacity, but also encourage it to improve its power supply reliability and emergency response capabilities, thereby optimizing the operating efficiency of the power system.

[0058] Step 3: According to the total amount of capacity subsidies converted in step 3, the actual virtual power plant response rate is converted to obtain the total amount of capacity electricity charges under the actual response rate. The specific instructions are as follows:

[0059] The actual response rate refers to the actual response capability of the virtual power plant after receiving the dispatch instruction, that is, its power supply reliability and timeliness under different load conditions. The response behavior of the virtual power plant under various load scenarios can be analyzed in detail through historical operation data and real-time monitoring data to quantify its actual response rate. After completing the actual response rate evaluation, the converted total capacity subsidy will be adjusted according to the actual response rate. Specifically, the higher the actual response rate, the stronger the reliability of the virtual power plant in the power system, and the total capacity electricity fee it should receive should also increase accordingly; conversely, if the actual response rate is low, the total capacity electricity fee should be reduced. In this way, it can be ensured that the total capacity electricity fee more accurately reflects the actual power supply capacity and response capability of the virtual power plant.

[0060] Step 5: Convert the total amount of capacity electricity charges under the actual response rate in step 4 to the unit capacity to obtain the standard value of capacity electricity charges. The specific instructions are as follows:

[0061] Convert all calculation results to unit capacity. By comprehensively considering the analysis results of the above steps, the unit capacity electricity price of the virtual power plant is calculated. This step requires simplifying the complex calculation results into standard values ​​of unit capacity electricity prices that are easy to understand and apply, so as to facilitate operation and management in practical applications.

[0062] In order to better understand the technical solution of the present invention, it is described in detail through a specific embodiment below: based on the power balance analysis of the regional power grid from July to August in the most recent year, there was a typical summer load peak in these two months, posing a huge challenge to the safe operation of the power system. Therefore, it is planned to call on the virtual power plant to participate in market transactions from July to August in the most recent year.

[0063] The calculation process of the annual capacity electricity fee scale of the regional power grid virtual power plant is as follows:

[0064] Assume that a certain area needs to trade through a virtual power plant for m months, and the amount of electricity required for peak regulation through the virtual power plant is Q million kWh.

[0065] 1. If there is no virtual power plant, 10,000 kWh of electricity needs to be purchased through the spot market. The GDP corresponding to the unit electricity loss is 25 yuan / kWh. Because low-value loads are given priority during actual load shedding, one-third or one-quarter of 25 yuan / kWh is taken when calculating, so it costs 60 or 80 million yuan to complete the transaction.

[0066] 2. If the virtual power plant can guarantee normal operation, the capacity subsidy prepared by the power grid to complete the transaction is 6Q or 8Q yuan, and the capacity subsidy is k times the capacity electricity fee (15≤k≤20). The capacity electricity fee paid to the virtual power plant is 6Q / k or 8Q / k million yuan. The capacity of the virtual power plant connected to the year is w million kilowatts. After conversion to unit power and month, the capacity electricity price is obtained. The implementation standard is 6Q / kw yuan / kilowatt·year or 8Q / kw yuan / kilowatt·year.

[0067] 3. If part of the virtual power plant can operate normally, and the proportion coefficient of the virtual power plant that operates normally is α (0≤α≤1), the capacity electricity fee standard is set at 6Q / kw yuan / kilowatt·year or 8Q / kw yuan / kilowatt·year.

[0068] In summary, the capacity electricity fee subsidized to the virtual power plant for one year is shown in formula (3) or formula (4):

[0069] F y =6Q / k 3)

[0071] F y =8Q / k 4)

[0073] In the formula, F y Represents the capacity electricity fee paid by the grid to the virtual power plant.

[0074] The standard value of capacity electricity fee after conversion to unit power is shown in formula (5) or formula (6):

[0075] F m =6Qα / kw 5)

[0077] F m =8Qα / kw 6)

[0079] In the formula, F m Indicates the standard value of capacity electricity charge after conversion to unit power.

[0080] The coupling framework diagram of the step flow and the calculation process of the present invention is as follows: Figure 4 shown.

Claims

1. A virtual power plant capacity electricity price pricing method considering power outage losses, characterized by: The specific steps include: Step 1: Collect monthly power data of the regional power grid within the target time of the basic target, the target time is one year, and then analyze the monthly power balance of the regional power grid within the target time, where the basic target is the power plant; Step 2: Obtain the gross national product and total power generation within the target time, calculate the gross national product per kilowatt-hour of electricity loss, and work out the total capacity subsidy that the grid needs to pay to complete the transaction; Step 3: Then, according to the calculation result of the total capacity subsidy, the insurance value is applied to the capacity electricity fee field, and the total capacity subsidy is converted according to the insurance value; Step 4: Convert the actual virtual power plant response rate according to the converted total capacity subsidy to obtain the total capacity electricity fee under the actual response rate; Step 5: At this time, the total capacity electricity fee under the actual response rate is converted to unit capacity to obtain the standard value of capacity electricity fee.

2. A virtual power plant capacity electricity price pricing method considering power outage losses according to claim 1, characterized in that: The specific method of analyzing the monthly power balance of the regional power grid within the target time in step 1 is: First, summarize and analyze the monthly power balance of the regional power grid within a year, and mark the power demand and supply of the set month; Then, through detailed data collection and statistical analysis of power load and power generation in each month, the supply and demand balance of the power system throughout the year is determined.

3. A virtual power plant capacity electricity price pricing method considering power outage losses according to claim 2, characterized in that: When marking the electricity demand and supply conditions of the set months, the electricity demand and supply conditions from July to August are specifically marked.

4. A virtual power plant capacity electricity price pricing method considering power outage losses according to claim 3, characterized in that: In step 5, the specific method of converting the total amount of capacity electricity charges under the actual response rate to unit capacity to obtain the standard value of capacity electricity charges is: Based on the analysis results of the regional power grid's power balance in July and August, the virtual power plant was enabled to participate in peak demand response in July and August, that is, capacity electricity charges were provided to the virtual power plant, and the standard value of the capacity electricity charge was obtained through a series of calculation and conversion processes.

5. A virtual power plant capacity electricity price pricing method considering power outage losses according to claim 4, characterized in that: The specific calculation method of obtaining the standard value of capacity electricity fee through a series of calculation and conversion processes is as follows: F m =6Qα / kw (1) F m =8Qα / kw (2)。 6. A virtual power plant capacity electricity price pricing method considering power outage losses according to claim 1, characterized in that: When the total capacity electricity charge under the actual response rate is obtained in step 4, the actual response rate refers to the actual response capability of the virtual power plant after receiving the dispatch instruction, that is, the reliability and timeliness of its power supply under different load conditions.

7. A virtual power plant capacity electricity price pricing method considering power outage losses according to claim 1, characterized in that: When converting to unit capacity to obtain the capacity electricity fee standard value in step 5, all calculation results are converted to unit capacity. By comprehensively considering the analysis results of the above steps, the unit capacity electricity price of the virtual power plant is calculated.

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