A method and system for centralized clearing of day-ahead flexibility certificates market

Abstract

The application discloses a centralized clearing method and system for a day-ahead flexibility certificate market, and the method is a centralized clearing method for a day-ahead flexibility certificate market based on self-adaptive robustness under a high-proportion new energy system. In the flexibility certificate market, new energy power generators and flexibility resources are respectively taken as buyers and sellers to trade the flexibility certificates which externally reflect the flexibility attributes of the flexibility resources in the market, the flexibility certificate market adopts the self-adaptive robust method to clear, and the new energy power generators can participate in the day-ahead electric energy market clearing only by purchasing a certain amount of certificates in the flexibility certificate market.

Description

Technical Field

[0001] The present invention belongs to the field of electric energy technology and relates to a centralized clearing method and system for a day-ahead flexibility certificate market. Background Art

[0002] The proportion of renewable energy installed capacity in power systems continues to increase. As of the end of December 2021, the cumulative installed capacity of renewable energy power generation reached 1.06 billion kilowatts, accounting for 44.8% of total installed power capacity, including 328 million kilowatts of wind power and 306 million kilowatts of solar power. In a context of high renewable energy penetration, renewable energy bears the primary responsibility for power generation, and flexibility resources will become the most direct and important means of addressing the uncertainty and volatility of renewable energy output. New power systems dominated by renewable energy require a substantial amount of flexibility resources to ensure stable and reliable system operation. However, current research on flexibility resources in power systems with high renewable energy penetration focuses on flexibility assessment and pricing, with less research on mechanisms to promote the effective participation of flexibility resources in the market. Furthermore, the marginal cost of renewable energy generation is very low, potentially even decreasing to zero, which lowers the marginal cost of the system. This results in insufficient benefits for flexibility resources from participating in system balancing in power systems with high renewable energy penetration, reducing social enthusiasm for investment and development in flexibility resources, and thus hindering further growth in the level of renewable energy absorption and penetration. Furthermore, the system balancing costs currently arising from the uncertainty of renewable energy are borne by the entire system. Summary of the Invention

[0003] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a centralized clearing method and system for the day-ahead flexibility certificate market to solve the problem in the prior art that the new energy absorption level and penetration rate of flexibility resources in the process of participating in system balancing are not high.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions:

[0005] A centralized clearing method for a day-ahead flexibility certificate market includes the following steps:

[0006] The operating costs, TFC sales revenue, and TFC purchase costs of each power generation method are obtained to establish a first objective function. The optimization goal of the first objective function is to minimize the total cost of the individual energy storage system in the TFC market and the day-ahead electricity market. After optimizing the first objective function, the clearing results of each individual power generation method are obtained. The conditions satisfied during the optimization process of the first objective function are that the increase or decrease in output borne by the flexibility resource is less than the transaction value in the flexibility certificate market, and the output process of the flexibility resource meets the line capacity constraints.

[0007] The maximum output forecast value of the new energy power generation company in the 96 time periods of the operation day is used to obtain the quantity standard of flexibility certificates purchased by the new energy power generation company. The eligibility for online purchase is determined by whether the quantity of flexibility certificates purchased by the new energy power generation company meets the quantity standard of flexibility certificates.

[0008] Based on the clearing results of each individual energy storage method and the new energy power generators participating in the transaction on that day, the day-ahead electricity energy market is cleared through the second objective function. The optimization goal of the second objective function is to clear the electricity energy market and minimize the power generation cost of the power system.

[0009] A further improvement of the present invention is:

[0010] Preferably, the first objective function is:

[0011]

[0012] Among them, t∈T is the operating day period; and They are the output of traditional thermal power units, wind turbine units and photovoltaic units during period t on the operating day respectively; p RWu and p RPv are the unit output costs of traditional thermal power unit k, wind turbine unit and photovoltaic unit respectively; The number of flexibility vouchers sold for the flexibility resource during time period t on the operating day; The number of flexibility certificates purchased by the renewable energy generator during the t period on the operation day; The price quoted for selling flexibility vouchers for flexibility resources during time period t on the operating day; It is the quotation for new energy power generators to purchase flexibility certificates during the t period on the operation day.

[0013] Preferably, the constraints of the first objective function include power balance constraints, the output range of each power generation mode, the purchase and sale range of flexibility certificates, the line power transmission range constraints of each power generation mode, the deviation range constraints between the actual output and the predicted value of the new energy power generation mode, and the increase or decrease in the output of the thermal power unit in adjacent time periods to meet its own climbing needs.

[0014] Preferably, when processing the deviation range constraint between the actual output and the predicted value generated by the new energy power generation mode, the output increase or decrease value borne by each flexibility resource is set not to exceed the transaction value of the flexibility resource in the flexibility certificate market; and the upper limit of the output increase or decrease value borne by each flexibility resource is set not to exceed the market clearing result of the flexibility resource.

[0015] Preferably, when the line in the power system fluctuates, the following equations (45) and (46) are used to constrain the line capacity in the power system so that it does not exceed the limit:

[0016]

[0017]

[0018] Among them, P lmax and P lmin are the power passing through line n during period t on the operating day Upper and lower limits; D ii 、F ii , G ii and H ii This is a quantity set during the adaptive robust derivation process and has no actual physical meaning.

[0019] Preferably, the quantity standard of flexibility certificates purchased by the new energy power generator is:

[0020] Q=k*P pre-day

[0021] k=k base *(1+k h )

[0022] k,k base ,k h ∈[0,1]

[0023] Among them, Q is the number of flexibility certificates that new energy power generators need to purchase, P pre-day is the maximum output forecast value of the new energy power generator in the 96 time periods of the operation day, k is the ratio of the number of flexibility certificates that the new energy power generator needs to purchase to the maximum output forecast value of the new energy power generator in the 96 time periods of the operation day, k base The base ratio for purchasing flexibility certificates for all new energy generators, k h It is the previous forecast deviation ratio of new energy power generators.

[0024] Preferably, the second objective function is:

[0025]

[0026] Among them, t∈T is the operating day period. It is a 01 variable indicating that the traditional thermal power unit is turned on during the t period of the operating day; if the thermal power unit is turned on, its value is 1, otherwise it is 0. is the startup cost of traditional thermal power unit k, and They are the output of traditional thermal power units, wind turbine units and photovoltaic units during the t period of the operating day, p RWu and p RPv are the unit output costs of traditional thermal power units k, wind turbines and photovoltaic units respectively.

[0027] Preferably, the constraint condition of the second objective function is:

[0028]

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] t=1,2,...,T (11)

[0035] in, is the load demand during period t on the operating day; P lmax and P lmin are the power passing through line n during period t on the operating day Upper and lower limits of P Gmax and P Gmin They are the output of traditional thermal power units during the operation day t period Upper and lower limits of P RWmax and P RWmin They are the wind turbine outputs during period t on the operating day. Upper and lower limits of P RWmax and P RWmin They are the wind turbine outputs during period t on the operating day. Upper and lower limits; and are the output values ​​of traditional thermal power units during period t and period t-1 on the operating day, respectively.

[0036] Preferably, the flexibility resource is one or more of pumped storage, virtual power plant and electrochemical energy storage.

[0037] A centralized clearing system for the day-ahead flexibility voucher market, comprising:

[0038] The certificate market clearing unit is used to obtain the operating costs, TFC sales revenue, and TFC purchase costs of each power generation method, establish a first objective function, and optimize the first objective function to minimize the total cost of the individual energy storage system in the TFC market and the day-ahead electricity market. After optimizing the first objective function, the clearing results of each individual power generation method are obtained. The optimization process of the first objective function satisfies the conditions that the increase or decrease in output borne by the flexibility resource is less than the transaction value in the flexibility certificate market, and the output process of the flexibility resource meets the line capacity constraint.

[0039] The qualification confirmation unit is used to obtain the quantity standard of flexibility certificates purchased by the new energy power generation company through the maximum value of the output forecast value of the new energy power generation company in the 96 time periods of the operation day, and determine whether the new energy power generation company is eligible for online purchase by checking whether the quantity of flexibility certificates purchased by the new energy power generation company meets the quantity standard;

[0040] The day-ahead electricity energy market clearing unit is used to clear the day-ahead electricity energy market through a second objective function based on the clearing results of each individual energy storage method and the new energy power generators participating in the transaction on that day. The optimization goal of the second objective function is to clear the electricity energy market and minimize the power generation cost of the power system.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] This invention discloses a centralized clearing method for the day-ahead flexibility voucher market. This method is based on an adaptive and robust centralized clearing method for the day-ahead flexibility voucher market in systems with a high proportion of new energy. In the flexibility voucher market, new energy generators and flexibility resources act as buyers and sellers, respectively, trading flexibility vouchers that externalize the flexibility attributes of the flexibility resources. The flexibility voucher market uses an adaptive and robust clearing method. New energy generators can only participate in the day-ahead electricity energy market clearing if they purchase a certain number of vouchers in the flexibility voucher market.

[0043] The centralized clearing process of the flexibility voucher market designed by the present invention adopts an adaptive robust method. The difference from the traditional robust method is that the former is a single-layer structure, while the latter is a double-layer structure, and the solution process is more efficient. The adaptive robust optimization method achieves the goal of the original robust optimization by finding the "worst case" of the uncertainty that is most likely to invalidate the robust constraint, and replaces the original robust constraint with the constraint group when the uncertainty is in the "worst case", thereby simplifying the solution process. When the adaptive robust method is used to enable flexibility resources to participate in the system power balance, the current flowing through the line will not exceed the line capacity no matter how it changes, that is, the physical constraints of the system power transmission are met; the adaptive adjustment of the flexibility voucher market clearing to the uncertainty of renewable energy power generation is achieved, thereby improving the feasibility of the flexibility voucher market.

[0044] Furthermore, flexibility certificates are the positive externalization of the flexibility attributes of flexibility resources. Flexibility resources can obtain additional income by selling flexibility certificates, and new energy power generators obtain the right to participate in the day-ahead electricity energy market clearing by purchasing flexibility certificates. This enables flexibility resources to obtain additional income corresponding to their flexible attributes, ensuring that when the actual output of new energy power generators deviates from the predicted output, the system can call on flexibility resources to balance electricity, so that the cost of this part of the system balancing electricity is borne by the new energy power generators, realizing the principle of "whoever brings the problem should solve it", that is, the reasonable distribution of costs, which increases the enthusiasm of flexibility resources to participate in the system electricity balance, further promotes the consumption of new energy, and makes the power system more stable and reliable.

[0045] Furthermore, by limiting the conditions, it is achieved that when the actual output of renewable energy and the predicted value have any deviation within a certain range, the new power flow distribution of the system can meet the physical constraints, that is, when each line reaches its own maximum power flow, it still does not exceed the line capacity, so that the flexibility certificate system can make adaptive adjustments to the uncertainty of renewable energy power generation, thereby improving the feasibility of the flexibility certificate market. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This paper presents the centralized clearing process of the flexibility voucher market based on an adaptive robust method and the subsequent day-ahead electricity energy market clearing process.

[0047] Figure 2 This is the IEEE-57 node diagram used in the examples of the present invention, where G represents a traditional thermal power unit, W represents a wind power unit, PV represents a photovoltaic unit, and FR represents a flexible resource.

[0048] Figure 3 This is the result of centralized clearing of the flexibility voucher market in this example of the present invention. DETAILED DESCRIPTION

[0049] The present invention is described in further detail below with reference to the accompanying drawings:

[0050] In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention; the terms "first", "second", and "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance; in addition, unless otherwise expressly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be a communication between the internal parts of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0051] The flexibility resources described in the present invention refer to energy storage (including pumped storage, virtual power plants, electrochemical energy storage) and thermal power units after deep adjustment transformation in the power system that can effectively cope with the volatility and uncertainty brought about by new energy, avoid the abandonment of new energy power, and meet the power supply reliability and load requirements. The power system includes traditional thermal power, new energy power generation, flexibility resources and loads. Flexibility resources need to have a certain climbing ability and climbing speed. When the output of new energy is short or fluctuating, and deviates from the predicted value, they can respond to changes in output demand in a timely and rapid manner, adjust their own output to meet the system load requirements, and ensure the smooth and reliable power supply of the system.

[0052] The flexibility certificate described in the present invention refers to a certificate for a certain amount of spare capacity purchased by a new energy power generator from a flexibility resource, which serves as a "license" for new energy to participate in the day-ahead electricity market clearing. The flexibility certificate is the positive externalization of the flexibility attribute of the flexibility resource and has financial attributes. The flexibility resource obtains the corresponding flexibility certificate by providing spare capacity and sells it to the new energy power generator, thereby obtaining a certain amount of income; the new energy power generator obtains the corresponding amount of spare capacity and the right to participate in the day-ahead electricity market clearing by purchasing the flexibility certificate. According to the predicted output of the new energy power generator for 96 time periods on the operating day, the power of the maximum output period is selected as the benchmark value to determine the spare capacity that the new energy power generator needs to purchase; only when the new energy power generator purchases the corresponding amount of flexibility certificates can it be qualified to participate in the day-ahead electricity market clearing.

[0053] The Tradable Flexibility Certificate (TFC) market described in the present invention is a market for trading flexibility certificates, which is cleared before the existing day-ahead electricity energy market. Market entities sign option contracts, that is, new energy power generators purchase the right to call on flexibility resources to increase or decrease output in the market. Whether this part of the spare capacity is used depends on the specific output of the new energy. Since electricity has special properties compared to other commodities, such as the need for real-time balancing and transmission is constrained by line capacity, transactions in the flexibility certificate market must meet certain physical constraints and be cleared by independent operating organizations. The type of flexibility certificate market belongs to the ancillary service market. During the transaction process, the relevant market entities can be divided into four categories according to the production link, transmission link, consumption link, and management link.

[0054] Energy storage (including pumped hydro, virtual power plants, and electrochemical energy storage) and thermal power units undergoing deep regulation and retrofitting, which are suppliers of flexibility certificates, generate a certain amount of spare capacity and obtain corresponding flexibility certificates for sale. New energy generators, also generated by the production process, generate a certain amount of flexibility certificates and obtain corresponding spare capacity and the right to participate in the day-ahead electricity market clearing by purchasing certain flexibility certificates. This paper studies the behavior of wind power and photovoltaic power in the flexibility certificate market. The transmission and distribution networks are responsible for transmitting the electricity that may be generated in the future as a result of transactions in the flexibility certificate market, but do not participate in the market transaction process as a buyer or seller. The management phase is an independent operating organization, acting as the organizer of flexibility certificate market transactions. It is responsible for administrative matters such as registering market participants, setting a reference price range for flexibility certificates, organizing market clearing, and conducting physical verification. It does not participate in the market transaction process as a buyer or seller. The day-ahead market for flexibility certificates predates the current day-ahead energy and electricity market and generally requires clearing to meet line capacity constraints. The flexibility voucher market, with its underlying trading entity, the flexibility voucher, externalizes the flexible nature of flexibility resources, transforming them into a tradable commodity while also reflecting the opportunity cost of the corresponding reserve capacity. Flexibility vouchers possess financial attributes, and trading them is conducted through option contracts. Clearing of the flexibility voucher market occurs earlier than in the current day-ahead energy and electricity market, and must occur while satisfying line capacity constraints.

[0055] The flexibility voucher in the present invention is to externalize the flexible attributes of flexibility resources. New energy power generators and flexibility resources act as buyers and sellers of flexibility vouchers, respectively, and trade in the flexibility voucher market. Flexibility resources can increase their own profits by selling flexibility vouchers. When purchasing flexibility vouchers, new energy power generators sign option contracts, which is equivalent to purchasing a corresponding amount of spare (upward and downward) capacity of flexibility resources. Market clearing is organized by independent operating organizations. Only when new energy power generators purchase a certain amount of vouchers can they participate in the subsequent day-ahead electricity market clearing. The specific amount is related to the accuracy of the historical forecasts of new energy power generators. This ensures that new energy power generators can solve a certain range of output forecast deviation problems by calling on flexibility resources. Whether to use this right or how much to use is determined based on the actual forecast deviation on the operating day. The flexibility voucher market uses market means to solve the uncertainty problem brought about by the grid connection of new energy, and realizes the reasonable allocation of system spare capacity costs, thereby improving the enthusiasm of flexibility resources and thus improving the stability of new energy power supply. It is of great significance to high-proportion new energy systems.

[0056] One embodiment of the present invention discloses a day-ahead electricity energy market clearing system, as shown in the attached Figure 1 As shown, it includes a voucher market clearing unit, a new energy power generator grid access qualification confirmation unit and a day-ahead electricity energy market clearing unit.

[0057] Voucher market clearing unit,

[0058] The flexibility voucher market clearing adopts an adaptive robust method. By establishing corresponding objective functions and corresponding constraints, this clearing method enables flexibility resources to meet the impact of new energy prediction errors within a certain range on the power system, and still meet line capacity constraints after line flow fluctuations.

[0059] The qualification confirmation unit is used to confirm the grid access qualifications of new energy power generators.

[0060] After the flexibility certificate market is cleared, the number of flexibility certificates purchased by each new energy power generator is evaluated to see whether it meets the standard, as shown in formula (1). Where Q is the number of flexibility certificates that the new energy power generator needs to purchase, P pre-day is the maximum output forecast value of the new energy power generator in the 96 time periods of the operation day. k is the ratio of the number of flexibility certificates that the new energy power generator needs to purchase to the maximum output forecast value of the new energy power generator in the 96 time periods of the operation day, k base The base ratio for purchasing flexibility certificates for all new energy generators, k hThe percentage of past forecast deviations for renewable energy generators. Determining the purchase ratio of flexibility certificates in this manner effectively helps renewable energy generators improve their forecasting capabilities. When a renewable energy generator reaches the required number of flexibility certificates, it is eligible to participate in the day-ahead electricity market clearing; otherwise, it is ineligible for grid access. The number of flexibility certificates required varies from renewable energy generator to renewable energy generator.

[0061] Q=k*P pre-day (1)

[0062] k=k base *(1+k h ) (2)

[0063] k,k base ,k h ∈[0,1](3)

[0064] The day-ahead electricity market clearing unit,

[0065] The results of the flexibility voucher market clearing will determine the eligibility of flexibility vouchers for grid access, which in turn will influence the subsequent clearing of the day-ahead energy market. The second objective function and constraints for clearing the day-ahead energy market are shown below. The optimization goal of the second objective function is to clear the energy market and minimize system generation costs.

[0066]

[0067] Among them, t∈T is the operating day period. It is a 01 variable indicating the startup of the traditional thermal power unit during the t period of the operating day; if the thermal power unit is started, its value is 1, otherwise it is 0. is the startup cost of traditional thermal power unit k. and They are the output of traditional thermal power units, wind turbine units and photovoltaic units during period t on the operating day. p RWu and p RPv are the unit output costs of traditional thermal power unit k, wind turbine unit, and photovoltaic unit, respectively. The constraints of the above equations are shown in equations (5)-(11):

[0068]

[0069]

[0070]

[0071]

[0072]

[0073]

[0074] t=1,2,...,T (11)

[0075] Among them, p RW0 is the original price of wind power, p TFC The price of the flexibility certificate.

[0076] With respect to the above-mentioned voucher market clearing unit, one embodiment of the present invention discloses a flexibility voucher market clearing method according to the present invention, which is a centralized clearing method based on adaptive robustness. The objective function is to minimize the total cost of the entire power system in the TFC market and the day-ahead electricity energy market, as shown in formula (12). The five items from left to right are the thermal power operation cost, wind power operation cost, photovoltaic operation cost, TFC sales income and TFC purchase cost. Formulas (13) to (25) are constraints. Among them, formula (13) is a power balance constraint, which means that the output values ​​of the system's traditional thermal power units, wind power units and photovoltaic units are equal to the load demand. Formulas (14) to (16) respectively represent the output range constraints of the system's traditional thermal power units, wind power units and photovoltaic units. Formulas (17) and (18) respectively represent the purchase and sale ranges of flexibility vouchers. Formula (19) represents the line power transmission range constraint, that is, it does not exceed the line capacity. When wind power and photovoltaic power output fluctuate, Equations (20) and (21) represent the deviation range constraints between actual wind power and photovoltaic power output due to uncertainty and volatility, respectively, where δ is the maximum proportion of renewable energy fluctuations in output. Equation (22) indicates that the reserve capacity purchased in the TFC market will be used to smooth out fluctuations in renewable energy output within a certain range. Equation (23) indicates that the increase or decrease in the output of traditional thermal power units in adjacent time periods must meet the unit's own ramping constraints. Equation (24) represents the clearing period.

[0077]

[0078] Among them, t∈T is the operating day period; and They are the output of traditional thermal power units, wind turbine units and photovoltaic units during period t on the operating day. p RWu and p RPv are the unit output costs of traditional thermal power unit k, wind turbine unit and photovoltaic unit respectively; The number of flexibility vouchers sold for the flexibility resource during time period t on the operating day; The number of flexibility certificates purchased by the renewable energy generator during the t period on the operation day; The price quoted for selling flexibility vouchers for flexibility resources during time period t on the operating day; It is the quotation for new energy power generators to purchase flexibility certificates during the t period on the operation day.

[0079]

[0080] is the load demand during period t on the operating day.

[0081]

[0082] P Gmax and P Gmin They are the output of traditional thermal power units during the operation day t period upper and lower limits.

[0083]

[0084] P RWmax and P RWmin They are the wind turbine outputs during period t on the operating day. upper and lower limits.

[0085]

[0086] P RPmax and P RPmin They are the output of photovoltaic units during period t on the operating day upper and lower limits.

[0087]

[0088] F dmax The number of flexibility certificates purchased by renewable energy generators during the t period of the operating day upper limit.

[0089]

[0090] F smax The number of flexibility vouchers sold for flexibility resources during period t on the operating day upper limit.

[0091]

[0092] P lmax and P lmin are the power passing through line n during period t on the operating day upper and lower limits.

[0093]

[0094]

[0095] and respectively are the actual output of wind turbine and photovoltaic generator in the operation day t, and the fluctuation value relative to the previous prediction. δ is the maximum proportion of new energy fluctuation in output.

[0096]

[0097]

[0098] and respectively are the output values of traditional thermal power generators in the operation day t and t-1. ΔP Gmax is the maximum change of traditional thermal power generator output in adjacent time period.

[0099] t = 1, 2, …, T (24)

[0100] Firstly, formula (22) is processed. Set θ ii , which satisfies formula (25) and formula (26). θ ii represents the proportion of the output increase or decrease of the flexibility resource purchased at the ith node in the system due to the deviation between the actual value and the predicted value of new energy in the total amount of new energy output deviation. In formula (25), the PTDF factor (power transfer distribution factor, which can be multiplied by the change of each node output or load to obtain the power transmitted on the line, and the PTDF factor is determined by the system network structure) is used to determine the situation that these output fluctuations are reflected on each line. Since the line flow has directionality, for example, the power flow on the line between points A and B may be A→B or B→A. Due to the factor in PTDF, it is +1 when the node output leads to the line power flow direction being the same as the positive direction, -1 when it is opposite, and 0 when there is no relationship. According to the positive and negative classification discussion, the inequality constraint of line flow constraint is changed; finally, it is obtained that when the flexibility resource output changes within a certain range (because the new energy output fluctuation has a certain range), the power flowing on the line must satisfy the inequality constraint condition of line capacity constraint. When there is no flexibility resource at the ith node in the system, θ ii = 0. The output increase or decrease of each flexibility resource should not exceed its transaction value in the flexibility certificate market, that is, formula (27), where is the line correlation matrix of flexibility resource. Formula (20), formula (21) and formula (27) are combined to obtain formula (28).

[0101]

[0102] 0≤θ ii ≤1 (26)

[0103]

[0104]

[0105] Since it is necessary to ensure that when the actual output of renewable energy deviates, the increase or decrease in the output of the purchased flexible resources will not cause system line congestion, it is necessary to make the range of Equation (28) less than or equal to the range of Equation (27), that is, the left end of Equation (28) is greater than or equal to the left end of Equation (27), and the right end of Equation (28) is less than or equal to the right end of Equation (27). In this way, the upper limit of the output increase or decrease value borne by each flexible resource does not exceed its market clearing result, thereby achieving adaptive adjustment of the TFC system clearing to the uncertainty of renewable energy generation, that is, Equations (29) and (30).

[0106]

[0107]

[0108] Next, we further explain the fluctuation of line power due to the fluctuation of renewable energy and the output of flexible resources. When considering the fluctuation of line power, the line power is expressed as Equation (31).

[0109]

[0110] in, and are the line correlation matrices of wind power and photovoltaic power in the system, is the power transmission distribution factor matrix. Combining wind power and photovoltaic power as new energy output, Equation (31) is simplified to obtain Equation (32).

[0111]

[0112] in, Represents the change in the output of new energy at node ii. Extract the right side of the equation (32) and combine similar terms to obtain:

[0113]

[0114] make We get formula (34).

[0115]

[0116] when hour,

[0117]

[0118] when hour,

[0119]

[0120] when hour,

[0121]

[0122] when hour,

[0123]

[0124] It will not be less than the sum of the left-hand terms of equations (35) to (38), nor will it be greater than the sum of the right-hand terms of equations (35) to (38). Let

[0125]

[0126]

[0127]

[0128]

[0129] Then there is

[0130]

[0131] and

[0132]

[0133] Combining equations (19) and (44), we can get

[0134]

[0135]

[0136] That is, the TFC market clearing results must be able to meet the line power limit under the condition of errors in the new energy forecast. By replacing Equation (22) of the original model with Equations (29) to (30), and adding Equations (39) to (42) and (45) to (46), we can perform centralized clearing based on adaptive robustness and obtain the flexibility voucher market clearing results under the condition that the line capacity does not exceed the limit.

[0137] The flexibility voucher market described in the present invention solves the uncertainty problem brought about by the grid connection of new energy through a function process, and realizes the reasonable allocation of the system's spare capacity costs, thereby improving the enthusiasm of flexibility resources and thus improving the stability of new energy power supply, which is of great significance to high-proportion new energy systems; the clearing method of the adaptive robust method simplifies the solution process, realizes the adaptive adjustment of the flexibility voucher market clearing to the uncertainty of new energy power generation, and improves the feasibility of the flexibility voucher market.

[0138] Example 1

[0139] The flexibility voucher market described in this invention has been established in the IEEE-57 node system (see Appendix Figure 2 ) was simulated in the flexibility certificate market, effectively simulating the behavior of flexibility resources and new energy power producers in the flexibility certificate market, and showing the transaction process of flexibility certificates; and from the output of each generator set and the node marginal electricity price in the day-ahead electricity market, it was shown that the impact of the flexibility certificate market clearing on the subsequent day-ahead electricity market clearing.

[0140] The following is a further description in conjunction with specific embodiments. Figure 2 For the application of IEEE-57 node system, the parameters of the system are shown in Table 1 and Table 2 below.

[0141] Table 1 Wind power parameters

[0142] Serial number Node location Maintenance cost (yuan / MW) 1 38 3.9 2 41 3.3 3 32 3.6 4 21 3 5 12 3.45 6 55 3.15 7 8 3.66

[0143] Table 2 Photovoltaic power generation parameters

[0144] Serial number Node location Maintenance cost (yuan / MW) 1 14 6 2 30 7 3 3 6.5 4 29 6.8

[0145] Table 3 Flexibility resource parameters

[0146]

[0147]

[0148] Attachment Figure 2 The red mark FR is the flexibility resource, which is distributed at nodes 4, 3, 47, 27, 13, 34, 55, 8, 19, 56, 52, 6, 1, and 23. The black mark G is the traditional thermal power generation, which is distributed at nodes 1, 2, 6, 8, and 9; W is the wind power, which is distributed at nodes 38, 41, 32, 21, 12, 55, and 8; PV is the photovoltaic power generation, which is distributed at nodes 14, 30, 3, and 29. Before the day-ahead electricity energy market is cleared, the adaptive robust method is used to clear the flexibility certificate market with the minimum total cost as the objective function, and the number of flexibility certificates purchased by each new energy source is compared with the number it should purchase as the entry condition for the day-ahead electricity energy market. Only new energy sources that purchase a sufficient number of flexibility certificates can participate in the day-ahead electricity energy market clearing. Appendix Figure 3 The supply and demand relationship for the flexibility certificate market clearing during a specific time period is shown in red, with the supply curve and the demand curve in blue. The intersection of the two indicates that 249.711 units of flexibility certificates were traded in the market at a marginal price of 115 yuan. After the intersection, demand for flexibility certificates cannot be met, and demand for flexibility certificates cannot be met after the intersection. This means that when the demand-side bid is lower than the supply-side bid, no transaction can be completed. This method of mutually agreeing on quantity and price guarantees prevents unilateral exercise of market power.

[0149] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A centralized clearing method for the day-ahead flexibility certificate market, characterized in that: The following steps are involved: The operating costs, TFC sales revenue, and TFC purchase costs of each power generation method are obtained to establish a first objective function. The optimization goal of the first objective function is to minimize the total cost of the individual energy storage system in the TFC market and the day-ahead electricity market. After optimizing the first objective function, the clearing results of each individual power generation method are obtained. The conditions satisfied during the optimization process of the first objective function are that the increase or decrease in output borne by the flexibility resource is less than the transaction value in the flexibility certificate market, and the output process of the flexibility resource meets the line capacity constraints. The first objective function is: （12） in, The operating day period; 、 and Operation days Output of traditional thermal power units, wind turbine units and photovoltaic units during the time period; 、 and Traditional thermal power units , the unit output cost of wind turbines and photovoltaic units; For flexibility resources on operation day the number of flexibility certificates sold during the period; For new energy power generators in operation day The number of flexibility vouchers purchased during the time period; For flexibility resources on operation day Quotation for selling flexibility certificates during the period; For new energy power generators in operation day Quotation for purchasing flexibility certificates during time periods; The constraints of the first objective function include power balance constraints, the output range of each power generation mode, the purchase and sale range of flexibility certificates, the line power transmission range constraints of each power generation mode, the deviation range of the actual output of renewable energy power generation mode from the predicted value, and the increase or decrease of the output of thermal power units in adjacent time periods to meet their own ramping requirements; When the line capacity in the power system fluctuates, the following equations (45) and (46) are used to constrain the line capacity in the power system so that it does not exceed the limit: （45） （46） Among them, and Operation days Time Route Power passing through Upper and lower limits; 、 、 and It is a quantity set in the adaptive robust derivation process and has no actual physical meaning; The maximum output forecast value of the new energy power generation company in the 96 time periods of the operation day is used to obtain the quantity standard of flexibility certificates purchased by the new energy power generation company. The eligibility for online purchase is determined by whether the quantity of flexibility certificates purchased by the new energy power generation company meets the quantity standard of flexibility certificates. Based on the clearing results of each individual energy storage method and the new energy generators participating in the transaction on that day, the day-ahead electricity market is cleared using a second objective function. The optimization goal of the second objective function is to clear the electricity market and minimize the power system's generation cost. The second objective function is: （4） in, The operating day period; Operation day The 01 variable of the traditional thermal power unit startup during the period; if the thermal power unit is started, its value is 1, otherwise it is 0. For traditional thermal power units The startup cost, 、 and Operation days Output of traditional thermal power units, wind turbine units and photovoltaic units during the period, 、 and Traditional thermal power units , the unit output cost of wind turbines and photovoltaic units; The constraints of the second objective function are: （5） （6） （7） （8） （9） （10） in, Operation day Time period load demand; and Operation days Time Route Power passing through Upper and lower limits; and Operation days Output of traditional thermal power units during the period Upper and lower limits; and Operation days Wind turbine output during the period Upper and lower limits; and Operation days Wind turbine output during the period Upper and lower limits; and Operation days Time period and The output value of traditional thermal power units during the period.

2. A centralized clearing method for the day-ahead flexibility voucher market according to claim 1, characterized in that: When processing the deviation range constraint between the actual output and the forecast value of renewable energy power generation, the output increase or decrease value borne by each flexibility resource is set to not exceed the transaction value of the flexibility resource in the flexibility certificate market; The upper limit of the output increase or decrease borne by each flexibility resource is set not to exceed the market clearing result of the flexibility resource.

3. The centralized clearing method for the day-ahead flexibility voucher market according to claim 1, characterized in that: The quantity standards for the flexibility certificates purchased by the new energy power generators are as follows: in, The number of flexibility certificates that new energy generators need to purchase is standard. It is the maximum value of the output forecast value of the new energy power generator in the 96 periods of the operation day. The ratio of the number of flexibility certificates that new energy power generators need to purchase to the maximum output forecast of new energy power generators in the 96 operating hours of the day is: The base ratio for purchasing flexibility certificates for all new energy generators, It is the previous forecast deviation ratio of new energy power generators.

4. The centralized clearing method for the day-ahead flexibility voucher market according to claim 1, characterized in that: The flexibility resources are one or more of pumped storage, virtual power plant and electrochemical energy storage.

5. A centralized clearing system for the day-ahead flexibility certificate market for implementing the method of claim 1, characterized in that: include: The certificate market clearing unit is used to obtain the operating costs, TFC sales revenue, and TFC purchase costs of each power generation method, and establish a first objective function. The optimization goal of this first objective function is to minimize the total cost of the individual energy storage system in the TFC market and the day-ahead electricity market. After optimizing the first objective function, the clearing results of each individual power generation method are obtained. The optimization process of the first objective function satisfies the conditions that the increase or decrease in output borne by the flexibility resource is less than the transaction value in the flexibility certificate market, and the output process of the flexibility resource meets the line capacity constraint. The qualification confirmation unit is used to obtain the quantity standard of flexibility certificates purchased by the new energy power generation company through the maximum value of the output forecast value of the new energy power generation company in the 96 time periods of the operation day, and determine whether the new energy power generation company is eligible for online purchase by checking whether the quantity of flexibility certificates purchased by the new energy power generation company meets the quantity standard; The day-ahead electricity energy market clearing unit is used to clear the day-ahead electricity energy market through a second objective function based on the clearing results of each individual energy storage method and the new energy power generators participating in the transaction on that day. The optimization goal of the second objective function is to clear the electricity energy market and minimize the power generation cost of the power system.

Images