Special project power transmission pricing method and system adaptive to Saggou crude energy base

Abstract

The invention discloses a special project power transmission pricing method and system adapted to a Saggou crude energy base, and the method comprises the steps: constructing a special project power transmission price double-layer optimization model based on electric energy-standby combined clearing according to a power market clearing model and a standby adjustment mechanism; adjusting the special project power transmission price double-layer optimization model by using a scene analysis method so as to obtain an optimal solution of the special project power transmission price double-layer optimization model; and determining the power transmission price of the special power transmission project according to the optimal solution. According to a power market clearing model and a standby adjustment mechanism, a special project power transmission price double-layer optimization model is constructed, so that adverse effects on a system caused by uncertainty of renewable energy sources can be effectively dealt with, renewable energy source consumption is promoted, and the model is adjusted so as to improve the utilization rate of the renewable energy sources. The power transmission price and the actual cross-regional power transmission demand can be planned according to the transaction condition of the power market, the actual operation condition of the power grid can be better reflected, and the method is suitable for a novel power system with high-proportion renewable energy access.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission engineering, and in particular to a power transmission pricing method and system for a special project adapted to a Shagohuang energy base. Background Art

[0002] Under the dual carbon goals, my country is accelerating the construction of large-scale wind and solar bases with a focus on the Shagohuang area, relying on the cross-regional special project transmission channels to ensure the consumption of large-scale wind and solar bases. With the access of a high proportion of renewable energy, the base transmission special transmission project has changed from transmitting deterministic electricity mainly based on thermal power to stochastic and volatile electricity mainly based on wind and solar power. At the same time, the accelerated construction of a unified national electricity market system will promote the joint operation of the medium- and long-term, spot, and auxiliary service markets, enhance the marketization of cross-regional electricity transactions, and make cross-regional transmission more determined by market competition mechanisms.

[0003] At present, when formulating the transmission price of inter-regional special transmission projects, most studies adopt the transmission pricing method based on deterministic electricity. This type of method verifies the expected inter-regional transmission volume of the transmission channel by multiplying the number of hours of transmission channel design utilization by the construction capacity of the transmission channel. Other studies establish a transmission price optimization model in the context of the power market to determine the transmission price, but do not consider the uncertainty of the large-scale access of renewable energy to the results of power market clearing, cannot reflect the actual situation of power grid operation, and are difficult to adapt to the new power system in the future. Therefore, for the transmission pricing problem of inter-regional special transmission projects, there is a lack of a solution that considers the uncertainty of renewable energy and the results of power market transactions. Summary of the invention

[0004] The present invention provides a special project transmission pricing method and system adapted to the Shagohuang Energy Base, introduces an electricity market clearing model and a reserve adjustment mechanism, and uses a scenario analysis method to construct a special project transmission price two-layer optimization model based on electricity-reserve joint clearing. The transmission price can be planned according to the electricity market transaction situation, and the uncertainty of renewable energy output can be effectively dealt with.

[0005] In order to achieve the above objectives, in a first aspect, an embodiment of the present invention provides a special project transmission pricing method adapted to the Shagohuang Energy Base, comprising:

[0006] According to the electricity market clearing model and reserve regulation mechanism, a two-layer optimization model of transmission price for special projects based on joint clearing of electricity and reserve is constructed;

[0007] Using the scenario analysis method to adjust the two-layer optimization model of the power transmission price of the special project, so that the two-layer optimization model of the power transmission price of the special project can obtain the optimal solution;

[0008] The transmission price of the special transmission project is determined according to the optimal solution.

[0009] As an improvement of the above scheme, the two-layer optimization model of transmission price for special projects includes an upper model and a lower model;

[0010] The upper model is a transmission price optimization model for inter-regional special projects, and the transmission price optimization model for inter-regional special projects takes maximizing the transmission revenue of the special transmission project as the optimization goal;

[0011] The lower model is a day-ahead market electricity-reserve joint clearing model, and the day-ahead market electricity-reserve joint clearing model takes minimizing the total power generation cost as the optimization goal.

[0012] As an improvement of the above scheme, the use of scenario analysis method to adjust the special project power transmission price double-layer optimization model so that the special project power transmission price double-layer optimization model obtains the optimal solution includes:

[0013] Using a scenario analysis method, inputting a preset transmission amount into the upper model to obtain a transmission price of a current iteration, and passing the transmission price of the current iteration to the lower model;

[0014] So that the lower model can carry out power market clearing according to the current iterative transmission price and obtain a clearing result;

[0015] Calculate the transmission capacity of the current iteration of the special power transmission project according to the clearing result;

[0016] If the transmission price of the current iteration and the transmission amount of the current iteration are not the optimal solutions of the two-layer optimization model of the special project transmission price, the transmission amount of the current iteration will be returned to the upper model for the next iteration until the two-layer optimization model of the special project transmission price obtains the optimal solution.

[0017] As an improvement of the above solution, the calculation formula of the objective function of the upper model is:

[0018]

[0019] The constraint condition of the upper model is the annual permissible income constraint;

[0020] The calculation formula for the annual permissible income constraint is:

[0021]

[0022] Where R is the transmission revenue of the special transmission project; p e is the electricity transmission price; T is the total number of time periods; is the transmission capacity of the special transmission project during period t; C C is the capacity transmission fee; R rIt is the annual permitted income of the special transmission project.

[0023] As an improvement of the above solution, the calculation formula of the objective function of the lower model is:

[0024] minC=C E +C R +C B +C C

[0025] Where, C is the total cost of power generation; C E is the total electricity purchase cost of the receiving power grid; C R is the system's spare capacity cost; C B Balancing costs for renewable energy output deviation; C C for capacity transmission charges;

[0026] The constraints of the lower model include: system power balance constraints, line active power flow constraints, thermal power unit output constraints, renewable energy unit output constraints, standby capacity constraints, thermal power unit ramp constraints, minimum start and stop time constraints, maximum start and stop number constraints and daily execution power constraints.

[0027] As an improvement of the above solution, the calculation formula of the system power balance constraint is:

[0028]

[0029] The calculation formula of the line active power flow constraint is:

[0030]

[0031] Where P t is the load forecast value for period t; K is the number of declared sections; It is the collection of thermal power units in the area; is the winning bid output of thermal power unit i participating in the kth period of the day-ahead market clearing during period t; is the collection of renewable energy units within the area; is the winning bid output of renewable energy unit j participating in the day-ahead market clearing during period t; is the transmission capacity of the special transmission project during period t; is the maximum transmission power of line l; Ω G is the set of thermal power units; S F,l-i and S F,l-j are the generator output power transfer distribution factors of node F where thermal power unit i and renewable energy unit j are located on line l; Ω RES is a collection of the renewable energy units.

[0032] As an improvement of the above solution, the scenario analysis method is used to input the preset transmission volume into the upper model to obtain the current iteration transmission price, including:

[0033] Using scenario analysis method, inputting the preset power transmission amount into the upper model;

[0034] According to the objective function and constraints of the upper model, the transmission price of the current iteration is formulated through a two-part transmission price.

[0035] As an improvement to the above scheme, the two-part transmission price includes:

[0036] The transmission price consists of two parts: a fixed capacity price and a variable quantity price.

[0037] In a second aspect, an embodiment of the present invention provides a special project transmission pricing system adapted to the Shagohuang Energy Base, including:

[0038] The optimization model building module is used to build a two-layer optimization model of transmission price for special projects based on the joint clearing of power and reserve according to the power market clearing model and reserve adjustment mechanism;

[0039] An optimal solution obtaining module, used for adjusting the two-layer optimization model of the power transmission price of the special project by using a scenario analysis method, so that the two-layer optimization model of the power transmission price of the special project obtains an optimal solution;

[0040] The power transmission price determination module is used to determine the power transmission price of the special power transmission project according to the optimal solution.

[0041] Compared with the prior art, the embodiment of the present invention discloses a special project transmission pricing method and system adapted to the Shagohuang Energy Base, which constructs a double-layer optimization model of special project transmission price based on electric energy-reserve joint clearing according to the power market clearing model and the reserve adjustment mechanism; uses the scenario analysis method to adjust the special project transmission price double-layer optimization model so that the special project transmission price double-layer optimization model obtains the optimal solution; and determines the transmission price of the special transmission project according to the optimal solution. According to the power market clearing model and the reserve adjustment mechanism, the construction of a special project transmission price double-layer optimization model based on electric energy-reserve joint clearing can effectively deal with the adverse effects of the uncertainty of renewable energy on the system, promote the consumption of renewable energy, and adjust the model. It can plan the transmission price and the actual demand for cross-regional transmission according to the power market transaction situation, better reflect the actual operation of the power grid, and adapt to the new power system with a high proportion of renewable energy access. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a special project power transmission pricing method adapted to the Shagohuang energy base provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a double-layer optimization model framework for power transmission prices for a special project provided by an embodiment of the present invention;

[0044] Figure 3 It is a structural diagram of a special project transmission pricing system adapted to the Shagohuang Energy Base provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] It should be noted that the terms "comprises" and "specifically" and any variations of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0047] See also Figure 1 , Figure 1 The present invention provides a flowchart of a method for pricing a special power transmission project adapted to the Shagohuang energy base, which includes:

[0048] S1, based on the power market clearing model and reserve regulation mechanism, a two-layer optimization model of transmission price for special projects based on power-reserve joint clearing is constructed;

[0049] S2, using a scenario analysis method to adjust the two-layer optimization model of the power transmission price of the special project, so that the two-layer optimization model of the power transmission price of the special project obtains an optimal solution;

[0050] S3, determining the transmission price of the special transmission project according to the optimal solution.

[0051] Specifically, the two-layer optimization model of power transmission price for special projects includes an upper model and a lower model;

[0052] The upper model is a transmission price optimization model for inter-regional special projects, and the transmission price optimization model for inter-regional special projects takes maximizing the transmission revenue of the special transmission project as the optimization goal;

[0053] The lower model is a day-ahead market electricity-reserve joint clearing model, and the day-ahead market electricity-reserve joint clearing model takes minimizing the total power generation cost as the optimization goal.

[0054] Exemplarily, the upper layer is a transmission price optimization model for inter-regional special projects, which plans the transmission price of electricity volume based on the simulation results of known inter-regional transmission volume, and passes the transmission price to the lower layer model; the lower layer is a day-ahead market clearing model, which carries out electricity market clearing based on the known inter-regional transmission price planning results, calculates the transmission volume of inter-regional special transmission projects according to the clearing results, and returns the transmission volume to the upper layer model for planning the transmission price.

[0055] Specifically, the step S2 includes:

[0056] Using a scenario analysis method, inputting a preset transmission amount into the upper model to obtain a transmission price of a current iteration, and passing the transmission price of the current iteration to the lower model;

[0057] So that the lower model can carry out power market clearing according to the current iterative transmission price and obtain a clearing result;

[0058] Calculate the transmission capacity of the current iteration of the special power transmission project according to the clearing result;

[0059] If the transmission price of the current iteration and the transmission amount of the current iteration are not the optimal solutions of the two-layer optimization model of the special project transmission price, the transmission amount of the current iteration will be returned to the upper model for the next iteration until the two-layer optimization model of the special project transmission price obtains the optimal solution.

[0060] For example, Figure 2 As shown, Figure 2A schematic diagram of a two-layer optimization model framework for special project transmission prices provided in an embodiment of the present invention, wherein the upper layer is a cross-region special project transmission price optimization model, wherein the cross-region special project transmission price optimization model takes maximizing the transmission revenue of the special transmission project as the optimization goal, and achieving a cash flow balance during the operating period as a condition, and plans the transmission price of the electricity volume through a two-part transmission price based on the simulation results of the cross-regional transmission volume of the known special transmission project, and passes the transmission price to the lower model. The lower layer is the day-ahead market electricity-reserve joint clearing model, which takes the minimum total cost of power generation as the optimization goal. Based on the known inter-regional transmission price planning results, the forecast error and output deviation of renewable energy are comprehensively considered. According to conventional SCUC constraints (such as system power balance constraints, line active power flow constraints, etc.), renewable energy constraints (such as renewable energy unit output constraints) and medium- and long-term contract constraints (such as maximum start-stop times constraints and daily execution power constraints, etc.), day-ahead electricity-reserve joint clearing is carried out. According to the output of each unit inside and outside the region in the clearing results and the node marginal electricity price, the transmission capacity of the inter-regional special transmission project is calculated, and the transmission capacity is returned to the upper model. The decision variables of the upper and lower optimization problems are used as parameters of the other problem respectively, and the two-layer model is iterated until the optimal solution is obtained.

[0061] It should be noted that the scenario analysis method is a method of generating a large number of scenarios to simulate the operating status of the power system to ensure the applicability of the dispatching plan. The reserve adjustment mechanism means that when the actual output of the renewable energy unit is less than the bid output a few days ago, the upper reserve capacity of the system needs to be called to meet the load demand; when the actual output of the renewable energy unit is greater than the bid output a few days ago, the lower reserve capacity of the system needs to be called to reduce the abandonment of renewable energy. Special power transmission project: The transmission channel for the outbound transmission of resources from the Shagohuang wind and solar base is used to ensure the outbound transmission and consumption of resources from the wind and solar base. Two-part transmission price: The transmission price consists of a fixed capacity price and a variable electricity price. The fixed capacity price is to allocate the total capacity electricity fee to each kilowatt of capacity, which does not change with the change of electricity. The variable electricity price is to allocate the total electricity fee to each kilowatt according to the expected transmission volume, which changes with the change of electricity. Electricity-reserve joint clearing: When carrying out market clearing, the electricity energy market and the reserve ancillary service market are considered in a coordinated manner, with the minimum sum of the total power generation cost and the total reserve cost of the unit as the optimization goal, and the electricity energy and reserve capacity are jointly cleared.

[0062] In the embodiment of the present invention, the two-part transmission price mechanism is more in line with the characteristics of transmission project costs, can control the profits of the power grid company within a reasonable range, and effectively reduce the operating risks of the transmission enterprise.

[0063] Specifically, the calculation formula of the objective function of the upper model is:

[0064]

[0065] The objective function of the upper model consists of two parts: the electricity transmission cost and the capacity transmission cost.

[0066]

[0067] C C = r·R r (3)

[0068]

[0069] The constraint condition of the upper model is the annual permissible income constraint;

[0070] The calculation formula for the annual permissible income constraint is:

[0071]

[0072] Where R is the transmission revenue of the special transmission project; p e is the electricity transmission price; T is the total number of time periods; is the transmission capacity of the special transmission project during period t; C C is the capacity transmission fee; S long Provide a scene set for long-term typical scenery; For the long-term typical wind and solar power output scenario l The probability of the scenario; is the long-term typical wind and solar power output scenario s in period t l The amount of inter-regional transmission under the above conditions; r is the ratio of the transmission fee of the capacity to the annual permitted income; R r The annual permitted income of the special power transmission project; z C is depreciation expense; 1 C′ is labor cost; o It is the operation and maintenance fee excluding the labor cost mentioned above.

[0073] It should be noted that the annual allowable income of the special power transmission project is R r Based on covering costs and obtaining reasonable returns, the annual net cash flow during the project operation period is discounted according to the internal rate of return of capital, and the calculation is carried out with the goal of achieving a balance of cash flow revenue and expenditure during the entire operation period. The corresponding formula is as follows:

[0074]

[0075] In the formula, Y represents the total number of years of operation; C I is the annual cash inflow value, corresponding to the annual permitted income R of the special power transmission project in formula (3) r ; C O is the annual cash outflow value; (CI -C O ) y is the net cash flow in the yth year; IRR is the internal rate of return on capital, which is 8%.

[0076] Among them, the annual cash inflow value C I That is, the annual allowable income R of the special power transmission project to achieve a cumulative net cash flow discount value NPV of zero r , annual cash outflow value C O The calculation formula is as follows:

[0077] C O =C inv +C pay +C int +C ope +C tax (7)

[0078] In the formula, C inv C is the capital investment; pay The principal of the loan to be repaid; int C is the interest expense; ope C is the operation and maintenance fee including labor costs; tax For taxes.

[0079] Specifically, the calculation formula of the objective function of the lower model is:

[0080] minC=C E +C R +C B +C C (8)

[0081] Where, C is the total cost of power generation; C E is the total electricity purchase cost of the receiving power grid; C R is the system's spare capacity cost; C B Balancing costs for renewable energy output deviation; C C for capacity transmission charges;

[0082] The constraints of the lower model include: system power balance constraints, line active power flow constraints, thermal power unit output constraints, renewable energy unit output constraints, standby capacity constraints, thermal power unit ramp constraints, minimum start and stop time constraints, maximum start and stop number constraints and daily execution power constraints.

[0083] It should be noted that the objective function of the lower model consists of four parts: the total electricity purchase cost of the receiving power grid, the system's reserve capacity cost, the balancing cost of renewable energy output deviation, and the inter-regional capacity transmission cost.

[0084] The total electricity purchase cost of the receiving power grid C E:Since the units at the Shagohuang base outside the region need to participate in the spot power market in the region and compete with the units in the region, the price they declare needs to add the special project electricity transmission price on the basis of the short-term marginal cost. The total power purchase cost of the receiving power grid is divided into three parts: the power generation cost of thermal power units, the power generation cost of renewable energy, and the start-up and shutdown cost of thermal power units. The expression is:

[0085]

[0086] In the formula, T is the total number of time periods, K is the number of declared time periods, and are the collections of thermal power units outside and within the area respectively; and are the collection of renewable energy units outside and within the region respectively; and They are the bid price and winning bid output of thermal power unit i participating in the kth period of the day-ahead market clearing in period t; and are the bid price and winning output of renewable energy unit j participating in the day-ahead market clearing in period t; Ω G is the set of thermal power units; i,t and z i,t are the startup state variable and shutdown state variable of thermal power unit i in period t respectively; and are the single startup cost and single shutdown cost of thermal power unit i respectively.

[0087] The system's spare capacity cost C R The expression is:

[0088]

[0089] In the formula, and They are the capacity quotations for upward and downward reserve of thermal power unit i in period t respectively; and They are the clearing capacity of thermal power unit i during period t when it is adjusted up or down.

[0090] Renewable energy output deviation balancing cost C B The expression is:

[0091]

[0092] In the formula, S short is a set of short-term typical wind and solar power output scenarios; ss For the short-term typical wind and solar power output scenario s The probability of the scenario; and are the actual call prices for upward and downward reserve adjustments during period t, respectively; and They are short-term typical wind and solar power output scenarios in period t. s The actual amount of upward and downward reserve calls; c loss is the load shedding price, s is a typical short-term wind and solar power output scenario in period t s The load shedding capacity; c curt Penalize the price of curtailing wind and solar power. s is a typical short-term wind and solar power output scenario in period t s of abandoned wind and solar power.

[0093] in,

[0094]

[0095]

[0096] Where: and are the upper reserve and lower reserve requirements of the system during period t respectively; s is a typical short-term wind and solar power output scenario in period t s Load change; Ω RES is a collection of the renewable energy units; They are the winning bid output of renewable energy unit j participating in the day-ahead market clearing during period t; is the short-term typical wind and solar output scenario s of renewable energy unit j in period t s The amount of load under.

[0097] The meaning of formula (12) is: when the actual output of renewable energy is less than the bid output, if the output deviation is less than the system's adjustable upper reserve capacity, the actual call amount of the system's upper reserve is equal to the output deviation; if the output deviation exceeds the upper reserve capacity range, the actual call amount of the system's upper reserve is equal to the total adjustable upper reserve of the system, and the part that still cannot meet the power balance is load shedding. When the actual output of renewable energy is greater than the bid output, if the output deviation is less than the system's adjustable lower reserve capacity, the actual call amount of the system's lower reserve is equal to the output deviation; if the output deviation exceeds the lower reserve capacity range, the actual call amount of the system's lower reserve is equal to the total adjustable lower reserve of the system, and the part of renewable energy that still cannot be absorbed is abandoned.

[0098] Capacity transmission fee C C The expression of is the same as that of the previous model (3) and will not be repeated here.

[0099] Specifically, the calculation formula of the system power balance constraint is:

[0100]

[0101] in,

[0102]

[0103] The calculation formula of the line active power flow constraint is:

[0104]

[0105] Where P t is the load forecast value for period t; K is the number of declared sections; and They are respectively the collection of thermal power units outside and within the area; and are the collection of renewable energy units outside and within the region respectively; is the winning bid output of thermal power unit i participating in the kth period of the day-ahead market clearing during period t; is the winning bid output of renewable energy unit j participating in the day-ahead market clearing during period t; is the transmission capacity of the special transmission project during period t; is the maximum transmission power of line l; Ω G is the set of thermal power units; S F,l-i and S F,l-j are the generator output power transfer distribution factors of node F where thermal power unit i and renewable energy unit j are located on line l; Ω RES is a collection of the renewable energy units.

[0106] The calculation formula for the output constraint of thermal power units is:

[0107]

[0108] In the formula, and is the maximum and minimum technical output of thermal power unit i; I i,t It is a 0-1 variable, indicating the operating status of thermal power unit i during period t.

[0109] The calculation formula for the output constraint of renewable energy units is:

[0110]

[0111] In the formula, is the output forecast value of renewable energy unit j in period t.

[0112] Reserve capacity constraint: The system's reserve capacity is provided by the thermal power units in the startup state. The reserve capacity provided by the units must be less than their remaining maximum adjustable space. The calculation formula is:

[0113]

[0114] In the formula, I i,t It is a 0-1 variable, indicating the operating status of thermal power unit i during period t.

[0115] The calculation formula of the thermal power unit climbing constraint is:

[0116]

[0117] In the formula, is the winning bid output of thermal power unit i participating in the kth period of the day-ahead market clearing in period t-1; and are the clearing capacity of thermal power unit i during period t-1 when it is adjusted upward or downward; is the maximum ramp rate of thermal power unit i; I i,t-1 is a 0-1 variable, indicating the operating status of thermal power unit i in period t-1; is the maximum ramp-down rate of thermal power unit i.

[0118] The calculation formula for the minimum start-stop time constraint is:

[0119]

[0120] Where, T U and T D They are the minimum continuous running time and the minimum continuous downtime respectively.

[0121] The calculation formula for the maximum start-stop times constraint is:

[0122]

[0123] y i,t -z i,t =I i,t -I i,t-1 (30)

[0124] y i,t +z i,t ≤1 (31)

[0125] In the formula, and are the maximum startup times and maximum shutdown times of thermal power unit i respectively.

[0126] The calculation formula for daily execution power constraint is:

[0127]

[0128] In the formula, and are the contract electricity of thermal power unit i and renewable energy unit j decomposed into hours and days for medium- and long-term contracts respectively; Δt is the time variable; the output of thermal power unit at each moment must meet the contract hour decomposition, while the output of renewable energy unit only needs to meet the contract day execution electricity constraint for the total contract execution electricity on the planned day.

[0129] Specifically, the scenario analysis method is used to input the preset power transmission amount into the upper model to obtain the current iteration power transmission price, including:

[0130] Using scenario analysis method, inputting the preset power transmission amount into the upper model;

[0131] According to the objective function and constraints of the upper model, the transmission price of the current iteration is formulated through a two-part transmission price.

[0132] Specifically, the two-part transmission price includes:

[0133] The transmission price consists of two parts: a fixed capacity price and a variable quantity price.

[0134] It should be noted that the two-part transmission price is composed of a fixed capacity price and a variable electricity price. The fixed capacity price is the total capacity fee allocated to each kilowatt capacity, which does not change with the change of electricity volume. The variable electricity price is the total electricity fee allocated to each kilowatt-hour according to the expected transmission volume, which changes with the change of electricity volume.

[0135] The embodiment of the present invention discloses a special project transmission pricing method adapted to the Shagohuang Energy Base. According to the power market clearing model and the reserve adjustment mechanism, a special project transmission price double-layer optimization model based on the joint clearing of electric energy and reserve is constructed; the special project transmission price double-layer optimization model is adjusted by the scenario analysis method so that the special project transmission price double-layer optimization model obtains the optimal solution; the transmission price of the special transmission project is determined according to the optimal solution. According to the power market clearing model and the reserve adjustment mechanism, the construction of a special project transmission price double-layer optimization model based on the joint clearing of electric energy and reserve can effectively deal with the adverse effects of the uncertainty of renewable energy on the system, promote the consumption of renewable energy, and adjust the model. It can plan the transmission price and the actual demand for cross-regional transmission according to the power market transaction situation, better reflect the actual operation of the power grid, and adapt to the new power system with a high proportion of renewable energy access.

[0136] Figure 3 1 is a structural diagram of a special project transmission pricing system adapted to the Shagohuang energy base provided by an embodiment of the present invention. The special project transmission pricing system 10 adapted to the Shagohuang energy base includes:

[0137] The optimization model building module 11 is used to build a double-layer optimization model of transmission price for special projects based on power-reserve joint clearing according to the power market clearing model and the reserve adjustment mechanism;

[0138] The optimal solution obtaining module 12 is used to adjust the special project power transmission price double-layer optimization model by using the scenario analysis method, so that the special project power transmission price double-layer optimization model obtains the optimal solution;

[0139] The power transmission price determination module 13 is used to determine the power transmission price of the special power transmission project according to the optimal solution.

[0140] Specifically, the two-layer optimization model of power transmission price for special projects includes an upper model and a lower model;

[0141] The upper model is a transmission price optimization model for inter-regional special projects, and the transmission price optimization model for inter-regional special projects takes maximizing the transmission revenue of the special transmission project as the optimization goal;

[0142] The lower model is a day-ahead market electricity-reserve joint clearing model, and the day-ahead market electricity-reserve joint clearing model takes minimizing the total power generation cost as the optimization goal.

[0143] Specifically, the optimal solution obtaining module 12 is used to:

[0144] Using a scenario analysis method, inputting a preset transmission amount into the upper model to obtain a transmission price of a current iteration, and passing the transmission price of the current iteration to the lower model;

[0145] So that the lower model can carry out power market clearing according to the current iterative transmission price and obtain a clearing result;

[0146] Calculate the transmission capacity of the current iteration of the special power transmission project according to the clearing result;

[0147] If the transmission price of the current iteration and the transmission amount of the current iteration are not the optimal solutions of the two-layer optimization model of the special project transmission price, the transmission amount of the current iteration will be returned to the upper model for the next iteration until the two-layer optimization model of the special project transmission price obtains the optimal solution.

[0148] Specifically, the scenario analysis method is used to input the preset power transmission amount into the upper model to obtain the current iteration power transmission price, including:

[0149] Using scenario analysis method, inputting the preset power transmission amount into the upper model;

[0150] According to the objective function and constraints of the upper model, the transmission price of the current iteration is formulated through a two-part transmission price.

[0151] Specifically, the two-part transmission price includes:

[0152] The transmission price consists of two parts: a fixed capacity price and a variable quantity price.

[0153] A special project transmission pricing system adapted to the Shagohuang Energy Base provided in an embodiment of the present invention can implement all processes of the special project transmission pricing method adapted to the Shagohuang Energy Base in the above-mentioned embodiment. The functions of each module in the system and the technical effects achieved are respectively the same as the functions and technical effects achieved by the special project transmission pricing method adapted to the Shagohuang Energy Base in the above-mentioned embodiment, and will not be repeated here.

[0154] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A special project power transmission pricing method adapted to the Shagohuang energy base, characterized in that: include: According to the electricity market clearing model and reserve regulation mechanism, a two-layer optimization model of transmission price for special projects based on joint clearing of electricity and reserve is constructed; Using the scenario analysis method to adjust the two-layer optimization model of the power transmission price of the special project, so that the two-layer optimization model of the power transmission price of the special project can obtain the optimal solution; The transmission price of the special transmission project is determined according to the optimal solution.

2. The special project power transmission pricing method adapted to the Shagohuang energy base as claimed in claim 1 is characterized in that: The two-layer optimization model of power transmission price for special projects includes an upper model and a lower model; The upper model is a transmission price optimization model for inter-regional special projects, and the transmission price optimization model for inter-regional special projects takes maximizing the transmission revenue of the special transmission project as the optimization goal; The lower model is a day-ahead market electricity-reserve joint clearing model, and the day-ahead market electricity-reserve joint clearing model takes minimizing the total power generation cost as the optimization goal.

3. The special project power transmission pricing method adapted to the Shagohuang energy base as claimed in claim 2 is characterized in that: The method of adjusting the two-layer optimization model of the power transmission price of the special project by using the scenario analysis method so as to obtain the optimal solution of the two-layer optimization model of the power transmission price of the special project includes: Using a scenario analysis method, inputting a preset transmission amount into the upper model to obtain a transmission price of a current iteration, and passing the transmission price of the current iteration to the lower model; So that the lower model can carry out power market clearing according to the current iterative transmission price and obtain a clearing result; Calculate the transmission capacity of the current iteration of the special power transmission project according to the clearing result; If the transmission price of the current iteration and the transmission amount of the current iteration are not the optimal solutions of the two-layer optimization model of the special project transmission price, the transmission amount of the current iteration will be returned to the upper model for the next iteration until the two-layer optimization model of the special project transmission price obtains the optimal solution.

4. The special project power transmission pricing method adapted to the Shagohuang energy base as claimed in claim 2 is characterized in that: The calculation formula of the objective function of the upper model is: The constraint condition of the upper model is the annual permissible income constraint; The calculation formula for the annual permissible income constraint is: Where R is the transmission revenue of the special transmission project; p e The price of electricity transmission for the amount of electricity; T is the total number of time periods; is the transmission capacity of the special transmission project during period t; C C is the capacity transmission fee; R r It is the annual permitted income of the special transmission project.

5. The special project power transmission pricing method adapted to the Shagohuang energy base as claimed in claim 2 is characterized in that: The calculation formula of the objective function of the lower model is: minC=C E +C R +C B +C C Where, C is the total cost of power generation; C E is the total electricity purchase cost of the receiving power grid; C R is the system's spare capacity cost; C B Balancing costs for renewable energy output deviations; C C for capacity transmission charges; The constraints of the lower model include: system power balance constraints, line active power flow constraints, thermal power unit output constraints, renewable energy unit output constraints, standby capacity constraints, thermal power unit ramp constraints, minimum start and stop time constraints, maximum start and stop number constraints and daily execution power constraints.

6. The power transmission pricing method for a special project adapted to the Shagohuang energy base as claimed in claim 5 is characterized in that: The calculation formula of the system power balance constraint is: The calculation formula of the line active power flow constraint is: Where P t is the load forecast value for period t; K is the number of declared sections; It is the collection of thermal power units in the area; is the winning bid output of thermal power unit i participating in the kth period of the day-ahead market clearing during period t; is the collection of renewable energy units within the area; is the winning bid output of renewable energy unit j participating in the day-ahead market clearing during period t; is the transmission capacity of the special transmission project during period t; is the maximum transmission power of line l; Ω G is the set of thermal power units; S F，l-i and S F，l-j are the generator output power transfer distribution factors of node F where thermal power unit i and renewable energy unit j are located on line l; Ω RES is a collection of the renewable energy units.

7. The power transmission pricing method for a special project adapted to the Shagohuang Energy Base as claimed in claim 3 is characterized in that: The scenario analysis method is used to input the preset transmission volume into the upper model to obtain the current iteration transmission price, including: Using scenario analysis method, inputting the preset power transmission amount into the upper model; According to the objective function and constraints of the upper model, the transmission price of the current iteration is formulated through a two-part transmission price.

8. The power transmission pricing method for a special project adapted to the Shagohuang Energy Base as claimed in claim 7 is characterized in that: The two-part transmission price includes: The transmission price consists of two parts: a fixed capacity price and a variable quantity price.

9. A special project transmission pricing system adapted to the Shagohuang Energy Base, characterized in that: include: The optimization model building module is used to build a two-layer optimization model of transmission price for special projects based on the joint clearing of power and reserve according to the power market clearing model and reserve adjustment mechanism; An optimal solution obtaining module, used for adjusting the two-layer optimization model of the power transmission price of the special project by using a scenario analysis method, so that the two-layer optimization model of the power transmission price of the special project obtains an optimal solution; The power transmission price determination module is used to determine the power transmission price of the special power transmission project according to the optimal solution.

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