Price compensation method based on flexible capacity of coal-fired unit

Abstract

The invention belongs to the technical field of power market design, and particularly relates to a price compensation method based on flexible capacity of a coal-fired unit, which comprises the following steps of: analyzing output characteristics of wind power resources and light resources according to meteorological conditions of different time periods in a year; clustering the output characteristics of the wind power resource and the light resource, and obtaining a standard scene set; according to the standard scene set, different time in one year is divided into a large wind period and a small wind period; the marginal value of the flexible capacity of the coal-fired unit in the small wind period stage is researched; and constructing a capacity price compensation mechanism based on performance payment and marginal value. According to the method, price compensation is carried out on the flexible capacity of the coal-fired unit, so that reasonable benefits of the coal-fired unit in the electricity market can be guaranteed. Normal operation and sustainable development of a coal-fired unit can be maintained, so that stable operation of a power system is guaranteed, and the problem of possible periodic shortage or insufficiency of the capacity of the power system is effectively solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power market design, and in particular relates to a price compensation method based on the flexibility capacity of a coal-fired unit. Background Art

[0002] However, with the deepening of the marketization of the power market, the problem of insufficient capacity during peak hours may be particularly prominent. And based on the historical experience of foreign countries with marketized power and the actual problems encountered in the development of my country's power market, it can be predicted that the power system capacity may be periodically short or insufficient in the future.

[0003] On the other hand, with a stable coal supply, the capacity of coal-fired units is less affected by changes in natural conditions, and is therefore considered a reliable source of electricity supply. Thanks to this attribute, dispatch systems often use the stable output provided by coal-fired power stations to cover the needs of base load and intermediate load. As the amount of wind and solar power connected to the grid continues to rise, coal-fired power generation plays an increasingly important role in supplying backup capacity and regulating peak loads in the face of more volatile renewable energy.

[0004] Therefore, at the current stage, ensuring reasonable profits for coal-fired units is an important measure to grasp my country's energy structure and promote the stable operation of the power system.

[0005] Therefore, it is necessary to invent a price compensation method based on the flexibility capacity of coal-fired units to ensure reasonable profits for coal-fired units. Summary of the invention

[0006] The purpose of the present invention is to provide a price compensation method based on the flexibility capacity of coal-fired units, so as to achieve the purpose of ensuring reasonable profits of coal-fired units.

[0007] To achieve the above object, the present invention adopts the following specific technical solution: a price compensation method based on the flexibility capacity of coal-fired units, comprising the following steps:

[0008] According to the meteorological conditions in different time periods of the year, the output characteristics of wind resources and light resources are analyzed; the output characteristics of wind resources and light resources are clustered and a standard scene set is obtained; according to the standard scene set, different times of the year are divided into high wind period and low wind period;

[0009] Establish a capacity price compensation mechanism based on performance payment and marginal value.

[0010] Furthermore, the method of dividing the Northeast region into a strong wind period and a light wind period in a year, analyzing the output characteristics of wind resources and light resources, clustering the output characteristics of wind resources and light resources, and obtaining a standard scene set specifically includes the following steps:

[0011] Approximate wind speed data with the Weibull function, analyze the relationship between wind turbine power output and wind speed, and provide an analysis of wind resource output characteristics;

[0012] Analysis of optical resource output characteristics;

[0013] Cluster the output characteristics of wind resources and light resources and obtain a standard scenario set;

[0014] The study of the marginal value of the flexibility capacity of coal-fired units during the low wind period specifically includes the following steps:

[0015] Calculate coal consumption costs;

[0016] Calculate the environmental costs of power generation companies;

[0017] Calculate the fixed costs of power generation companies;

[0018] Give the marginal value of the flexible capacity of coal-fired units.

[0019] Furthermore, the use of the Weber function to approximate the wind speed data, analyze the relationship between the wind turbine power output and the wind speed, and provide a wind resource output characteristic analysis, specifically including:

[0020] The functions of Weibull probability density function f(v) and cumulative distribution function F(v) are shown below:

[0021]

[0022] Where: k is the shape parameter; c is the scale parameter; v is the wind speed; V m is the average wind speed; V mp is the most likely wind speed; P D is the wind energy density; P A is the actual wind energy density; ρ a is the air density;

[0023] For the Weibull distribution function, the expressions for its variance and standard deviation are as follows:

[0024]

[0025] The gamma function Γ(z) is obtained by the following formula:

[0026]

[0027] The wind resource output is modeled as follows:

[0028]

[0029] Where: Represents the output forecast value of a single unit j in a wind farm; ν(t) represents the wind speed of the wind turbine at time t (in m / s); Represents the wind turbine cut-in wind speed (unit: m / s); Represents the wind turbine cut-out wind speed (unit: m / s); represents the rated wind speed of the wind turbine (unit: m / s); ψ(ν(t)) represents the rated output power of the wind turbine (unit: MW); represents the upper power limit of wind turbine j at time t; ω1ω2ω3 represent the wind rotor power coefficient, the mechanical efficiency of the wind turbine transmission device, and the mechanical efficiency of the wind turbine generator respectively; ρ is the air density; d is the wind rotor diameter; Represents the predicted total output of wind power at time t.

[0030] Furthermore, the optical resource output characteristic analysis specifically includes:

[0031] In order to accurately characterize the daily fluctuation pattern of extraterrestrial solar radiation, the expression to describe the daily variation of extraterrestrial solar radiation I0 is as follows:

[0032]

[0033] Where: SC is the solar constant, n is the number of days;

[0034] Actual sunlight intensity I B The expression is as follows:

[0035] I B =Ae -om (14)

[0036]

[0037] Where: I B is the actual solar intensity, A is the extraterrestrial solar radiation flux, o is the optical depth, and m is the atmospheric mass.

[0038] Since the solar radiation received by different regions is not the same, a simulated probability distribution model of solar radiation is introduced here, and its probability density function f(I B ) is as follows:

[0039]

[0040] Where: I B is the actual solar intensity, I B,max is the maximum light intensity, Γ is the gamma function, α and β are shape functions. The expression for light resource output modeling is as follows:

[0041]

[0042] Where: is the predicted total output of photovoltaic station j at time t; η pν is the photovoltaic power conversion efficiency; S pν is the effective area of ​​the photovoltaic array; temp0 is the ambient temperature.

[0043] Furthermore, the calculation of the coal consumption cost specifically includes:

[0044] The formula for calculating coal consumption cost is as follows:

[0045]

[0046] In the formula: is the winning bid electricity of power generation enterprise i in the medium and long-term market in period t; ɑi, bi, ci are the coefficients of the coal consumption characteristic function of power generation enterprise i; For power generation companies Coal consumption rate under output; is the coal consumption of power generation enterprise i in period t; ρ coal is the unit coal price of the quarter; is the coal consumption cost of power generation enterprise i in period t.

[0047] Furthermore, the calculation of the environmental cost of the power generation enterprise specifically includes:

[0048] The environmental cost expression of power generation enterprises is as follows:

[0049]

[0050] Where: N is the additional environmental cost incurred by power generation company i in the scenario of deep peak load regulation and pre-clearing during period t; e is the type of pollutant emission; e,k is the unit taxable amount of the kth pollutant; G e,k is the pollution equivalent value of the kth pollutant; is the emission of pollutant k in period t;

[0051] Air pollutants include sulfur dioxide (SO2), nitrogen oxides (NO x and smoke; the calculation method of sulfur dioxide emissions is as follows:

[0052]

[0053] Where: represents the additional coal consumption of power generation enterprise i in period t; The additional coal consumption of power generation enterprise i in period t is The emission of sulfur dioxide under the condition of is the received basic sulfur content of the coal; is the conversion rate of coal sulfur to flue gas sulfur; is the molar mass ratio of SO2 to S; The desulfurization efficiency of the desulfurization equipment;

[0054] The calculation method for nitrogen oxide emissions is as follows:

[0055]

[0056] Where: The additional coal consumption of power generation enterprise i in period t is In the case of nitrogen oxides NO x emissions; is the received nitrogen content of the coal; is the conversion rate of coal combustion nitrogen to flue gas nitrogen; Nitrogen oxides NO x The molar mass ratio of N to N; The denitrification efficiency of the denitrification equipment; NO generated from fuel nitrogen x Accounts for all NO x ratio of emissions;

[0057] The calculation method of smoke emission is as follows:

[0058]

[0059] Where: The additional coal consumption of power generation enterprise i in period t is Smoke emission under the condition of TSP is the ash content of the coal; d TSP is the percentage of fly ash carried out in the flue gas in the ash content; C FA is the percentage of combustible matter in smoke; η TSP It is the dust removal efficiency of the dust removal equipment.

[0060] Furthermore, the calculation of the fixed costs of the power generation enterprise specifically includes:

[0061] The fixed cost allocation expression of thermal power generation enterprises in period t is as follows:

[0062]

[0063] Where: f gz , f gy are the fixed cost depreciation and operation and maintenance costs of the thermal power generation unit in the power generation enterprise in the same year; w , f pThey are the annual fixed cost budgets of wind farms and photovoltaic power plants in the power generation enterprise; Y is the number of days in the contract year, and T is the number of time periods divided into each day;

[0064] Based on the coal consumption cost, environmental cost of power enterprises and fixed cost of power generation enterprises, the marginal value of the flexible capacity of coal-fired units is:

[0065]

[0066] Furthermore, the construction of a capacity price compensation mechanism based on performance payment and marginal value specifically includes:

[0067] The specific calculation method of the performance payment amount is as follows:

[0068] PP=PPR×(ACP-Br×CSO) (28)

[0069] Where: PP is Performance Payments, PPR is Performance Payment Rate, ACP is the actual capacity provided of the unit, Br is the Balancing Ratio, CSO is the capacity supply obligation assumed in the monthly auction market;

[0070] The calculation method of the equilibrium ratio Br is:

[0071]

[0072] Where: O total is the total capacity duty for the month, L t is the load at time t, R t is the reserve capacity requirement at time t;

[0073] The capacity compensation price P when considering the marginal value is expressed as:

[0074] P=α1·PP+α2·P0(30)

[0075] α1 and α2 are compensation coefficients, which are determined according to the clustered scenarios, and α1+α2=1; P0 is the marginal value of the flexible capacity of the coal-fired unit.

[0076] A price compensation system based on the flexibility capacity of a coal-fired unit is used to implement a price compensation method based on the flexibility capacity of a coal-fired unit, comprising:

[0077] Resource characteristic analysis and scenario set acquisition module: Analyze the characteristics of wind and light resources in Northeast China, cluster the output characteristics of wind and light resources, and obtain a standard scenario set representing the annual power generation characteristics of renewable energy;

[0078] Marginal value calculation module: used to calculate the marginal value of the flexible capacity of coal-fired units during low wind periods, taking into account factors such as coal consumption cost, environmental cost and fixed cost, and deriving accurate marginal value;

[0079] Price compensation mechanism building module: used to build a capacity price compensation mechanism based on performance payment and marginal value.

[0080] A readable storage medium stores a computer-readable program, which, when called, executes a price compensation method based on the flexibility capacity of a coal-fired unit.

[0081] The present invention can achieve the following technical effects:

[0082] The present invention can ensure reasonable income of coal-fired units in the power market by compensating the flexible capacity of coal-fired units. This helps maintain the normal operation and sustainable development of coal-fired units. In the context of my country's coal-based energy structure, it gives full play to the advantages of coal-fired units that power generation is less affected by natural conditions and has stable supply, thereby ensuring the stable operation of the power system and effectively dealing with the periodic shortage or insufficiency of power system capacity.

[0083] The present invention calculates the coal consumption cost, environmental cost and fixed cost in detail, and comprehensively considers the major expenditures during the operation of coal-fired units, making the cost accounting more accurate and reasonable. The marginal value of the flexible capacity of coal-fired units determined on this basis can truly reflect the value contribution of the units under different working conditions, provide a scientific data basis for the price compensation mechanism, and ensure the rationality and fairness of the compensation price. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0085] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation of the present invention.

[0086] refer to Figure 1 The purpose of the present invention is to provide a price compensation method based on the flexibility capacity of coal-fired units. The method is implemented in the following steps:

[0087] Step 1: Analyze the output characteristics of wind resources and light resources according to the meteorological conditions in different time periods of the year; cluster the output characteristics of wind resources and light resources, and obtain a standard scene set; divide different times of the year into high wind period and low wind period according to the standard scene set; Step 101: Approximate the wind speed data with the Weibull function, analyze the relationship between the power output of the wind turbine and the wind speed, and provide an analysis of the output characteristics of wind resources;

[0088] Step 102: Analyze the optical resource output characteristics;

[0089] Step 103: clustering the output characteristics of wind resources and light resources, and obtaining a standard scenario set;

[0090] Step 2: Study the marginal value of the flexible capacity of coal-fired units during low wind periods;

[0091] Step 201, calculating the coal consumption cost;

[0092] Step 202, calculating the environmental cost of the power generation enterprise;

[0093] Step 203, calculating the fixed cost of the power generation enterprise;

[0094] Step 204: Combining steps 201, 202 and 203, the marginal value of the flexible capacity of the coal-fired units is given;

[0095] Step 3: Establish a capacity price compensation mechanism based on performance payment and marginal value.

[0096] The specific embodiments of the method of the present invention are specifically given below;

[0097] Step 1: Analyze the output characteristics of wind resources and light resources according to the meteorological conditions in different time periods of the year; cluster the output characteristics of wind resources and light resources, and obtain a standard scene set; and divide different times of the year into high wind periods and low wind periods according to the standard scene set;

[0098] Step 101, analyzing wind speed data with the Weibull function, obtaining the relationship between wind turbine power output and wind speed, and providing wind resource output characteristic analysis;

[0099] The Weibull function is used as an empirical model to approximate the measured wind speed data at the selected location; the fitted Weibull function is used to calculate the wind power generation potential of the location; the Weibull probability density function f(v) and the cumulative distribution function F(v) are shown below:

[0100]

[0101] Where: k is the shape parameter; c is the scale parameter; v is the wind speed;

[0102] When applying the fitted Weibull function to study the wind resources in a specific area, we not only focus on the approximate expression of wind speed data. More importantly, through this empirical model, we can gain insight into and calculate the key characteristics of wind resources from equations (3) to (5), including but not limited to the average wind speed V m , the most likely wind speed V mp , and wind energy density P D These indicators are of great significance for the evaluation and utilization of wind resources. Furthermore, in order to compare the consistency and difference between the wind characteristics estimated by the model and the actual observed values, the actual wind energy density P A The calculation of is an essential step, which is based on equation (6).

[0103]

[0104] Where: V m is the average wind speed; V mp is the most likely wind speed; P D is the wind energy density; P A is the actual wind energy density; ρ a is the air density;

[0105] This description further deepens the understanding of the wind energy assessment model and clarifies the actual wind energy P A The key physical parameter considered in the calculation is air density ρ a , and its value is concretized as 1.225kg / m 3 , which is the average value under standard atmospheric conditions. For the Weibull distribution function, the expressions for its variance and standard deviation are as follows:

[0106]

[0107] The gamma function Γ(z) is obtained by the following formula:

[0108]

[0109] Formula (9) is the general expression of the gamma function, where the range of x is 0 to positive infinity; z can be any complex number except a non-positive integer;

[0110] There is a strong relationship between the power output of wind turbines and wind speed. The wind resource output is modeled as follows:

[0111]

[0112] Where: Represents the output forecast value of a single unit j in a wind farm; ν(t) represents the wind speed of the wind turbine at time t (in m / s); Represents the wind turbine cut-in wind speed (unit: m / s); Represents the wind turbine cut-out wind speed (unit: m / s); represents the rated wind speed of the wind turbine (unit: m / s); ψ(ν(t)) represents the rated output power of the wind turbine (unit: MW); represents the upper power limit of wind turbine j at time t; ω1ω2ω3 represent the wind rotor power coefficient, the mechanical efficiency of the wind turbine transmission device, and the mechanical efficiency of the wind turbine generator respectively; ρ is the air density; d is the wind rotor diameter; Represents the predicted total output of wind power at time t. It can be seen that there is an inseparable and close relationship between the output power of wind turbines and wind speed.

[0113] Step 102: Analysis of optical resource output characteristics

[0114] In order to more accurately describe and calculate the contribution of photovoltaic power generation, it is necessary to conduct in-depth mathematical description and quantitative analysis of the output characteristics of light resources.

[0115] In order to accurately characterize the daily fluctuation pattern of extraterrestrial solar radiation, the expression to describe the daily variation of extraterrestrial solar radiation I0 is as follows:

[0116]

[0117] Where: SC is the solar constant and n is the number of days. The solar constant is an estimate of the average annual solar radiation outside the Earth, and the most commonly accepted value is 1367W / m2. However, in clear weather, the maximum radiation of the beam on the surface is only 70% of the solar radiation outside the Earth. The attenuation of the incident radiation of the beam on the surface is a function of the distance the beam must travel through the atmosphere. Commonly used models regard the attenuation as an exponential decay function: the expression is as follows:

[0118] I B =Ae -om (14)

[0119]

[0120] Where: I B is the actual solar intensity, A is the extraterrestrial solar radiation flux, o is the optical depth, and m is the atmospheric mass.

[0121] Since the solar radiation received by different regions is not the same, a simulated probability distribution model of solar radiation is introduced here, and its probability density function f(I B ) is as follows:

[0122]

[0123] Where: I B is the actual solar intensity, IB,max is the maximum light intensity, Γ is the gamma function, α and β are shape functions. The expression for light resource output modeling is as follows:

[0124]

[0125] Where: is the predicted total output of photovoltaic station j at time t; η pν is the photovoltaic power conversion efficiency; S pν is the effective area of ​​the photovoltaic array; temp0 is the ambient temperature. From the analysis of the equation, we know that the output power and light intensity of the photovoltaic station are closely related.

[0126] Step 103: clustering the output characteristics of wind resources and light resources, and obtaining a standard scenario set;

[0127] First, based on the improved k-means algorithm of the density canopy, the annual power generation data of renewable energy sources such as wind resources and light resources are simplified by using efficient clustering technology, and a standard scene set representing the annual power generation characteristics of renewable energy can be developed. These scene sets can be used as equivalent substitutes for power generation conditions in different time periods. In this way, we can not only understand the power supply capacity of renewable energy in different time periods while ensuring high accuracy and efficiency.

[0128] To solve this problem, the present invention proposes an improvement measure based on density canopy to better adapt to the cluster analysis of annual power generation data of renewable energy. The canopy algorithm is an unsupervised pre-clustering algorithm, which is often used as a pre-processing step of the k-means algorithm or hierarchical clustering algorithm.

[0129] The basic idea of ​​the canopy algorithm clustering is: the canopy algorithm sets two distance thresholds T1 and T2, randomly selects the initial cluster center, and calculates the Euclidean distance between the sample and the initial center. The samples are classified into corresponding clusters according to the threshold. Finally, the clustered data is divided into n classes. The cluster number and cluster center of the canopy algorithm are used as input parameters of the k-means algorithm, and the clustering of the data set is completed. For a given data set Data = {x1, x2, ..., x n}, the sample element m in Data is x m ={x m1 ,x m2 ,...x mr}, 1≤m≤n, where r is x m The number of attributes; in addition, d(x p ,x q ) represents the Euclidean distance between two elements, where x p ={x p1 ,xp2 ,x p3 ,...,x pr}, x q ={x q1 ,x q2 ,...,x qr}. The expression of the average distance MeanDis(Data) of all sample elements in the data set Data is as follows:

[0130]

[0131] The expression of sample element i in the data set Data is as follows:

[0132]

[0133] According to formula (21), ρ(i) is the number of samples that satisfy the condition that the distance from other samples to point i is less than MeanDis(Data). When the samples meet this condition, a cluster is formed, and the expression of the average distance a(i) of the samples in the cluster is as follows:

[0134]

[0135] Cluster s(i) represents the distance between sample element i and another sample element j with higher local density. If the local density of sample point i is the largest, then s(i) is defined as max{d(i,j)}. If there exists ρ(j)>ρ(i), then it is defined as The clustering s(i) calculation expression is as follows:

[0136]

[0137] The dataset Data is divided into k clusters. Cluster C j The center of (j≤k) is c j Then the sum of the square errors of the clustering results is the sum of the square distances between each cluster sample and its cluster center. The solution expression is as follows:

[0138]

[0139] The present invention uses the actual output of new energy power stations in the Northeast region, including wind power stations and photovoltaic power stations, and conducts in-depth characteristic analysis. The power generation capacity of wind power stations at various times of the year has significant random fluctuations, and at many times, the power generation can be reduced to a level close to zero. Although there is uncertainty in the power generation efficiency of wind power, observing a longer time period can show obvious seasonal changes in wind power, usually lower power generation in summer and higher in winter, and this seasonal change has obvious identifiable characteristics.

[0140] In the construction of renewable energy scenarios, canopy algorithm clustering is used to group different time periods of the year according to meteorological conditions such as wind speed, wind direction, temperature, and similarities in power generation to form a representative standard scenario set. According to the standard scenario set, different times of the year are divided into high wind periods and low wind periods. During the high wind period, the power generation capacity of new energy power stations is stronger, and there is no need to compensate for the flexibility capacity of coal-fired units. During the low wind period, the power generation capacity of new energy power stations is weaker, and the power generation capacity is insufficient, so coal-fired units need to increase their output. At this time, it is necessary to compensate for the flexibility capacity of coal-fired units.

[0141] Step 2: Study the marginal value of the flexible capacity of coal-fired units during low wind periods;

[0142] Step 201, calculating the coal consumption cost;

[0143] Coal consumption cost is the main operating cost of thermal power units in the normal peak load regulation stage. In the deep peak load regulation stage, thermal power units will incur other operating costs, but coal consumption cost still accounts for a large proportion of the operating costs. The formula for calculating coal consumption cost is as follows:

[0144]

[0145] In the formula: is the winning bid electricity of power generation enterprise i in the medium and long-term market in period t; ɑi, bi, ci are the coefficients of the coal consumption characteristic function of power generation enterprise i; For power generation companies Coal consumption rate under output; is the coal consumption of power generation enterprise i in period t; ρ coal is the unit coal price of the season; is the coal consumption cost of power generation enterprise i in period t.

[0146] Step 202, calculating the environmental cost of the power generation enterprise;

[0147] Power generation companies produce a lot of pollutants during the power generation process, and they need to pay environmental protection taxes. The environmental cost of power generation companies is expressed as follows:

[0148]

[0149] Where: N is the additional environmental cost incurred by power generation company i in the scenario of deep peak load regulation and pre-clearing during period t; e is the type of pollutant emission; e,k is the unit taxable amount of the kth pollutant; G e,k is the pollution equivalent value of the kth pollutant; is the emission of pollutant k in period t;

[0150] Air pollutants include sulfur dioxide (SO2), nitrogen oxides (NO x and smoke. The calculation method of sulfur dioxide emissions is as follows:

[0151]

[0152] Where: represents the additional coal consumption of power generation enterprise i in period t; The additional coal consumption of power generation enterprise i in period t is The emission of sulfur dioxide under the condition of is the received basic sulfur content of the coal; is the conversion rate of coal sulfur to flue gas sulfur; is the molar mass ratio of SO2 to S; It is the desulfurization efficiency of the desulfurization equipment.

[0153] The calculation method for nitrogen oxide emissions is as follows:

[0154]

[0155] Where: The additional coal consumption of power generation enterprise i in period t is In the case of nitrogen oxides NO x Emissions is the received nitrogen content of the coal; is the conversion rate of coal combustion nitrogen to flue gas nitrogen; Nitrogen oxides NO x The molar mass ratio of N to N; The denitrification efficiency of the denitrification equipment; NO generated from fuel nitrogen x Accounts for all NO x The ratio of emissions.

[0156] The calculation method of smoke emission is as follows:

[0157]

[0158] Where: The additional coal consumption of power generation enterprise i in period t is Smoke emission under the condition of TSP is the ash content of the coal; d TSP is the percentage of fly ash carried out in the flue gas in the ash content; C FA is the percentage of combustible matter in smoke; η TSP It is the dust removal efficiency of the dust removal equipment.

[0159] Step 203, calculating the fixed cost of the power generation enterprise;

[0160] Fixed costs account for a relatively high proportion of the costs of power generation companies, and cannot be ignored in the cost accounting of large-scale electricity transactions. Fixed costs are expenditures that are not directly related to electricity production. Generally, the allocation of fixed costs for the next year can be basically determined at the beginning of the year, so they can be regarded as fixed values. The fixed costs of thermal power units include depreciation and operation and maintenance costs (wages, welfare expenses, material costs, repair costs, and other expenses). The fixed costs of new energy fields include equipment purchase costs, construction costs, basic reserves, construction period interest, operation and maintenance costs, and other expenses, which can all be regarded as fixed values, and fixed costs are regarded as the accumulation of various costs. The new energy studied in this invention is wind farms and photovoltaic power stations. The expression for the allocation of fixed costs of thermal power in time period t is as follows:

[0161]

[0162] Where: f gz , f gy are the fixed cost depreciation and operation and maintenance costs of the thermal power generation unit in the power generation enterprise in the same year; w , f p They are the annual fixed cost budgets for wind farms and photovoltaic power stations within the power generation enterprise; Y is the number of days in the contract year, and T is the number of time periods divided into each day.

[0163] Step 204: Combining steps 201, 202 and 203, based on coal consumption costs, environmental costs of power companies and fixed costs of power generation companies, the marginal value of the flexible capacity of coal-fired units is:

[0164]

[0165] This method calculates the coal consumption cost, environmental cost and fixed cost in detail, and comprehensively considers the main expenditures in the operation of coal-fired units, making the cost accounting more accurate and reasonable. The marginal value of the flexible capacity of coal-fired units determined on this basis can truly reflect the value contribution of the units under different operating conditions, provide a scientific data basis for the price compensation mechanism, and ensure the rationality and fairness of the compensation price.

[0166] Step 3: Establish a capacity price compensation mechanism based on performance payment and marginal value;

[0167] Performance payment is the practice of evaluating the performance of available generators at critical moments. The reserve capacity margin fluctuates over time. When the reserve capacity is about to fall below the reserve demand, the reserve capacity demand of the regional node is first met by rescheduling the system's internal resources. When the rescheduling cannot meet the reserve capacity demand, performance payment is required.

[0168] At times of scarcity, capacity bearers who fail to fulfill their power generation responsibilities will be paid performance payments based on the system's balancing ratio and the actual output of the units, as well as the capacity responsibilities assumed in the capacity market. At the same time, additional payments will be made as rewards to capacity owners who can proactively provide additional output. This performance payment mechanism is relative, consistent with the principle of "whoever benefits pays" in the market, and complements the capacity market. Its essence is that in times of scarcity, the capacity market benefits generated by output lower than the unit's capacity responsibility are transferred to opportunity benefits. This payment method provides an incentive mechanism to encourage suppliers to provide more stable capacity support and flexible and adjustable spare capacity to meet the system's needs for long-term abundance and the lack of flexible and adjustable resources in certain regions. The specific calculation method for the performance payment amount is as follows:

[0169] PP=PPR×(ACP-Br×CSO) (33)

[0170] In the formula: PP is performance payment, PPR is performance payment rate, ACP is the actual capacity provided of the unit, Br is the balancing ratio, and CSO is the capacity supply obligation assumed in the monthly auction market.

[0171] The calculation method of the equilibrium ratio Br is:

[0172]

[0173] Where: O total is the total capacity duty for the month, L t is the load at time t, R t is the reserve capacity requirement at time t;

[0174] The capacity compensation price P when considering the marginal value is expressed as:

[0175] P=α1·PP+α2·P0 (35)

[0176] α1 and α2 are determined according to the clustered scenarios, α1+α2=1; the price compensation strategy can be flexibly adjusted according to the stability of wind power efficiency. When the wind power efficiency is stable, a higher α2 is set so that the compensation price more reasonably reflects the value of the unit; otherwise, a higher α1 is set. P0 is the marginal value of the flexible capacity of the coal-fired unit.

[0177] The present invention also proposes a price compensation system based on the flexibility capacity of coal-fired units, which is used to implement a price compensation method based on the flexibility capacity of coal-fired units, including:

[0178] Resource characteristic analysis and scenario set acquisition module: It is used to divide the Northeast region into high wind period and low wind period in a year, analyze the output characteristics of wind resources by approximating wind speed data with the Weibull function, calculate relevant parameters through specific expressions, analyze and model the daily fluctuation pattern and attenuation of light resources, and then cluster the output characteristics of wind resources and light resources based on the improved k-means algorithm of density canopy to obtain the standard scenario set representing the annual power generation characteristics of renewable energy;

[0179] Marginal value calculation module: used to calculate the marginal value of the flexible capacity of coal-fired units during the low wind period, including the calculation of coal consumption cost, based on the coal consumption characteristic function coefficient, the winning bid electricity, the coal consumption rate, the coal price, etc.; the calculation of the environmental cost of power generation enterprises, taking into account various pollutant emissions and related parameters; the calculation of the fixed cost of power generation enterprises, determining the fixed costs of thermal power and new energy stations and allocating them, so as to obtain the marginal value;

[0180] Price compensation mechanism construction module: used to construct a capacity price compensation mechanism based on performance payment and marginal value, clarify the conditions and calculation method of performance payment, calculate the performance payment according to the unit's real-time available power generation capacity, balance ratio, capacity responsibility and performance payment rate, and determine the capacity compensation price in combination with marginal value.

[0181] The present invention also proposes a readable storage medium having a computer-readable program stored thereon, and when the computer-readable program is called, a price compensation method based on the flexibility capacity of the coal-fired unit is executed.

[0182] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0183] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0184] Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. Those skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

[0185] The above specific implementations of the present invention do not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A price compensation method based on the flexibility capacity of coal-fired units, characterized in that: The following steps are involved: According to the meteorological conditions in different time periods of the year, the output characteristics of wind resources and light resources are analyzed; the output characteristics of wind resources and light resources are clustered and a standard scene set is obtained; according to the standard scene set, different times of the year are divided into high wind period and low wind period; Study the marginal value of the flexible capacity of coal-fired units during low wind periods; Establish a capacity price compensation mechanism based on performance payment and marginal value.

2. The price compensation method based on the flexibility capacity of coal-fired units according to claim 1 is characterized in that: The output characteristics of wind resources and light resources are analyzed according to the meteorological conditions in different time periods of the year; the output characteristics of wind resources and light resources are clustered, and a standard scene set is obtained; and different times of the year are divided into high wind periods and low wind periods according to the standard scene set; Specifically include the following steps: Approximate wind speed data with the Weibull function, analyze the relationship between wind turbine power output and wind speed, and provide an analysis of wind resource output characteristics; Analysis of optical resource output characteristics; Cluster the output characteristics of wind resources and light resources and obtain a standard scenario set; The study of the marginal value of the flexibility capacity of coal-fired units during the low wind period specifically includes the following steps: Calculate coal consumption costs; Calculate the environmental costs of power generation companies; Calculate the fixed costs of power generation companies; Give the marginal value of the flexible capacity of coal-fired units.

3. The price compensation method based on the flexibility capacity of coal-fired units according to claim 2 is characterized in that: The method of approximating wind speed data with the Weber function, analyzing the relationship between wind turbine power output and wind speed, and providing wind resource output characteristic analysis specifically includes: The functions of Weibull probability density function f(v) and cumulative distribution function F(v) are shown below: Where: k is the shape parameter; c is the scale parameter; v is the wind speed; V m is the average wind speed; V mp is the most likely wind speed; P D is the wind energy density; P A is the actual wind energy density; ρ a is the air density; For the Weibull distribution function, the expressions for its variance and standard deviation are as follows: The gamma function Γ(z) is obtained by the following formula: The wind resource output is modeled as follows: Where: Represents the output forecast value of a single unit j in a wind farm; ν(t) represents the wind speed of the wind turbine at time t (in m / s); Represents the wind turbine cut-in wind speed (unit: m / s); Represents the wind turbine cut-out wind speed (unit: m / s); represents the rated wind speed of the wind turbine (unit: m / s); ψ(ν(t)) represents the rated output power of the wind turbine (unit: MW); represents the upper power limit of wind turbine j at time t; ω1ω2ω3 represent the wind rotor power coefficient, the mechanical efficiency of the wind turbine transmission device, and the mechanical efficiency of the wind turbine generator respectively; ρ is the air density; d is the wind rotor diameter; Represents the predicted total output of wind power at time t.

4. The price compensation method based on the flexibility capacity of coal-fired units according to claim 3 is characterized in that: The optical resource output characteristic analysis specifically includes: In order to accurately characterize the daily fluctuation pattern of extraterrestrial solar radiation, the expression to describe the daily variation of extraterrestrial solar radiation I0 is as follows: Where: SC is the solar constant, n is the number of days; Actual sunlight intensity I B The expression is as follows: I B =Yes -om (14) Where: I B is the actual solar intensity, A is the extraterrestrial solar radiation flux, o is the optical depth, and m is the atmospheric mass. Since the solar radiation received by different regions is not the same, a simulated probability distribution model of solar radiation is introduced here, and its probability density function f(I B ) is as follows: Where: I B is the actual solar intensity, I B,max is the maximum light intensity, Γ is the gamma function, α and β are shape functions. The expression for light resource output modeling is as follows: Where: is the predicted total output of photovoltaic station j at time t; η pν is the photovoltaic power conversion efficiency; S pν is the effective area of ​​the photovoltaic array; temp0 is the ambient temperature.

5. The price compensation method based on the flexibility capacity of coal-fired units according to claim 2 is characterized in that: The calculation of coal consumption cost specifically includes: The formula for calculating coal consumption cost is as follows: In the formula: is the winning bid electricity of power generation enterprise i in the medium and long-term market in period t; ɑi, bi, ci are the coefficients of the coal consumption characteristic function of power generation enterprise i; For power generation companies Coal consumption rate under output; is the coal consumption of power generation enterprise i in period t; ρ coal is the unit coal price of the quarter; is the coal consumption cost of power generation enterprise i in period t.

6. The price compensation method based on the flexibility capacity of coal-fired units according to claim 5 is characterized in that: The calculation of the environmental cost of power generation enterprises specifically includes: The environmental cost expression of power generation enterprises is as follows: Where: N is the additional environmental cost incurred by power generation company i in the scenario of deep peak load regulation and pre-clearing during period t; e is the type of pollutant emission; e,k is the unit taxable amount of the kth pollutant; G e,k is the pollution equivalent value of the kth pollutant; is the emission of pollutant k in period t; Air pollutants include sulfur dioxide (SO2), nitrogen oxides (NO x and smoke; the calculation method of sulfur dioxide emissions is as follows: Where: represents the additional coal consumption of power generation enterprise i in period t; The additional coal consumption of power generation enterprise i in period t is The emission of sulfur dioxide under the condition of is the received basic sulfur content of the coal; is the conversion rate of coal sulfur to flue gas sulfur; is the molar mass ratio of SO2 to S; The desulfurization efficiency of the desulfurization equipment; The calculation method for nitrogen oxide emissions is as follows: Where: The additional coal consumption of power generation enterprise i in period t is In the case of nitrogen oxides NO x emissions; is the received nitrogen content of the coal; is the conversion rate of coal combustion nitrogen to flue gas nitrogen; Nitrogen oxides NO x The molar mass ratio of N to N; The denitrification efficiency of the denitrification equipment; NO generated from fuel nitrogen x Accounts for all NO x ratio of emissions; The calculation method of smoke emission is as follows: Where: The additional coal consumption of power generation enterprise i in period t is Smoke emission under the condition of TSP is the ash content of the coal; d TSP is the percentage of fly ash carried out in the flue gas in the ash content; C FA is the percentage of combustible matter in smoke; η TSP It is the dust removal efficiency of the dust removal equipment.

7. The price compensation method based on the flexibility capacity of coal-fired units according to claim 6 is characterized in that: The calculation of fixed costs of power generation enterprises specifically includes: The fixed cost allocation expression of thermal power generation enterprises in period t is as follows: Where: f gz , f gy are the fixed cost depreciation and operation and maintenance costs of the thermal power generation unit in the power generation enterprise in the same year; w , f p They are the annual fixed cost budgets of wind farms and photovoltaic power plants in the power generation enterprise; Y is the number of days in the contract year, and T is the number of time periods divided into each day; Based on the coal consumption cost, environmental cost of power enterprises and fixed cost of power generation enterprises, the marginal value of the flexible capacity of coal-fired units is:

8. The price compensation method based on the flexibility capacity of coal-fired units according to claim 7 is characterized in that: The construction of a capacity price compensation mechanism based on performance payment and marginal value specifically includes: The specific calculation method of the performance payment amount is as follows: PP=PPR×(ACP-Br×CSO) (28) Where: PP is Performance Payments, PPR is Performance Payment Rate, ACP is the actual capacity provided of the unit, Br is the Balancing Ratio, CSO is the capacity supply obligation assumed in the monthly auction market; The calculation method of the equilibrium ratio Br is: Where: O total is the total capacity duty for the month, L t is the load at time t, R t is the reserve capacity requirement at time t; The capacity compensation price P when considering the marginal value is expressed as: P=α1·PP+α2·P0(30) α1 and α2 are compensation coefficients, which are determined according to the clustered scenarios, and α1+α2=1; P0 is the marginal value of the flexible capacity of the coal-fired unit.

9. A price compensation system based on the flexibility capacity of coal-fired units, characterized in that: include: Resource characteristic analysis and scenario set acquisition module: Analyze the characteristics of wind and light resources in Northeast China, cluster the output characteristics of wind and light resources, and obtain a standard scenario set representing the annual power generation characteristics of renewable energy; Marginal value calculation module: used to calculate the marginal value of the flexible capacity of coal-fired units during low wind periods, taking into account factors such as coal consumption cost, environmental cost and fixed cost, and deriving accurate marginal value; Price compensation mechanism building module: used to build a capacity price compensation mechanism based on performance payment and marginal value.

10. A readable storage medium, characterized in that: A computer-readable program is stored thereon, and when the computer-readable program is called, a price compensation method based on the flexibility capacity of a coal-fired unit as described in any one of claims 1-8 is executed.

Images