Electricity market transaction clearing optimization method considering new energy and thermal power bidding on same platform

Abstract

The invention belongs to the technical field of electricity market transaction optimization, and particularly relates to an electricity market transaction clearing optimization method considering new energy and thermal power bidding on the same platform. Comprising the following steps: S1, establishing a unit combination optimization model, obtaining a start-stop state variable value of each thermal power unit, determining a start-stop plan of the thermal power unit, and establishing necessary boundary conditions for economic dispatching optimization of the next stage; s2, an economic dispatching optimization model is established, economic dispatching optimization is carried out, and a power generation sequence and market clearing electricity price of each time are distributed; according to the method, a power market two-stage clearing model considering a stepped quotation strategy of different types of generator sets is constructed, the first stage is unit combination optimization, and the second stage is economic dispatching optimization; the influence of a new energy unit market entering mode, a quotation strategy and the like on the market clearing electricity price is verified, and the solving efficiency is improved through a two-stage modeling mode.

Description

Technical Field

[0001] The present invention belongs to the technical field of power market transaction optimization, and specifically relates to a power market transaction clearing optimization method considering the same-station bidding of new energy and thermal power. Background Art

[0002] As new energy power enters the post-subsidy era, due to the high pressure of subsidy funds and the fairness of power generation grid connection, the traditional fixed grid-connected electricity price and guaranteed purchase policy are not conducive to the optimal allocation of large-scale and high-proportion new energy power. Encouraging new energy to participate in power market transactions is considered to be one of the effective solutions. However, when proposing the optimization design of the market mechanism for the participation of new energy, existing studies have adopted the direct deduction of the new energy output forecast results as the boundary conditions of the net load curve, and have not adopted the method of quotation to participate in the market, or although the quotation method is adopted, it does not consider the competition relationship with thermal power on the same platform, but makes operational decisions based on the perspective of new energy individuals themselves, which is not conducive to the real evaluation of the comprehensive impact of multi-type and differentiated new energy directly participating in market transactions. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide an optimization method for clearing electricity market transactions that takes into account the bidding of new energy and thermal power on the same platform. Different proportions of new energy participating in the market and bidding strategies can be designed according to the differences in the grid-connected time and construction costs of new energy power. It can be used to analyze the quantitative results of new energy participating in spot market transactions in multiple scenarios, and provide methodological support and data basis for the optimization design of market mechanisms.

[0004] The object of the present invention is achieved by: considering the power market transaction clearing optimization method of new energy and thermal power bidding on the same platform, comprising the following steps:

[0005] S1. Establish a unit combination optimization model, obtain the start-stop state variable values ​​of each thermal power unit, determine the start-stop plan of the thermal power unit, and establish necessary boundary conditions for the next stage of economic dispatch optimization;

[0006] S2. Establish an economic dispatch optimization model, perform economic dispatch optimization, and allocate the power generation sequence and the market clearing electricity price each time.

[0007] The step S1 comprises:

[0008] (1) Determine the objective function

[0009] Minimize the overall grid dispatch costs, including unit dispatch costs, thermal power unit start-up and shutdown costs, and costs associated with energy storage system calls, as shown below;

[0010]

[0011] Where C represents the overall grid dispatching cost; t and T represent the minimum trading period and the total trading period, which are usually 1 hour and 24 hours respectively; i, j, k, and m represent the number of thermal power units, the amount of affordable new energy, the amount of subsidized new energy, and the number of energy storage devices, respectively; N, J, K, and M are the total number of units corresponding to each; and O m,t are the marginal generation costs of these generators respectively; and P m,t Respectively represent the power generation corresponding to these technologies; u i,t is a Boolean variable used to indicate the start and stop status of thermal power unit i at time t, 1 and 0 represent start and stop respectively; SU i,t and SD i,t is the cost of starting and stopping; is an exogenous parameter that controls the market access ratio; by adjusting its value, the impact of different market access ratios can be analyzed.

[0012] (2) Determine relevant constraints

[0013] ① Power balance constraints

[0014]

[0015] Among them, D t represents the power demand, F m,t Indicates the energy storage charging demand;

[0016] ② Upper and lower limits of generator output

[0017]

[0018] in, It is the technical parameter of the minimum output of thermal power units; and They represent the maximum output technical parameters of two renewable energy power generation technologies, which mainly depend on the endowment conditions of natural resources such as wind and solar energy in the case study area; G m Respectively represent the installed capacity, i.e. rated power, of units i, j, k and m;

[0019] ③Technical constraints on the operation of various power generation technologies

[0020] In addition to the above constraints, the safety constraint unit combination model also needs to consider the technical constraints of various generating units, including the climbing constraints of thermal power units, the start and stop time constraints of thermal power units, the output conversion constraints of new energy units, and the daily balance constraints of energy storage equipment.

[0021] The step S2 comprises:

[0022] (1) Objective function

[0023] The goal is to minimize the grid dispatching cost, as shown below;

[0024]

[0025] (2) Constraints

[0026] Except for the start / stop state and time constraints of the thermal power units, which are cancelled due to the direct use of the corresponding optimization results of step S1, other constraints remain the same as those in the first stage;

[0027] (3) Quotation method for generators participating in the market

[0028] The bid price of thermal power units and historical market clearing price data are shown in the following formula;

[0029]

[0030] Among them, p q-min and p q-max , respectively represent the lower and upper limits of the bidding price of the generator set in the spot market; the generator set can decide its bidding behavior within the price range according to its own operation strategy;

[0031] For thermal power units, a segmented and incremental method is used to guide their bidding, which not only encourages them to bid as close to their marginal cost as possible, but also ensures the effectiveness of the clearing model solution, as shown in the following formula;

[0032]

[0033] Among them, the thermal power units adopt the segmented and incremental bidding method, and set the corresponding bidding price according to different power output segments; α n It represents the bid price increment of the nth segment output relative to the price floor; Represents the output adjustment parameters declared in the nth paragraph;

[0034] (4) Market Clearing Price and Settlement Price

[0035] By solving the shadow price of the power balance constraint, the spot market clearing price at different trading times t is obtained. Based on the winning bid power of each unit, the average settlement price of each power generation technology is calculated. The calculation method of the average settlement price of thermal power is as follows;

[0036]

[0037] in, is the weighted average settlement price of thermal power unit i; is the real-time clearing price at time t.

[0038] The beneficial effects of the present invention are as follows: the power market transaction clearing optimization method considering the same-station bidding of new energy and thermal power of the present invention comprises the steps of S1, establishing a unit combination optimization model, obtaining the start-stop state variable value of each thermal power unit, determining the start-stop plan of the thermal power unit, and establishing necessary boundary conditions for the next stage of economic dispatch optimization; S2, establishing an economic dispatch optimization model, performing economic dispatch optimization, allocating the power generation sequence and the market clearing electricity price each time; through the above steps, the present invention constructs a two-stage power market clearing model considering the step-by-step bidding strategy of different types of power generating units, wherein the first stage is the unit combination optimization and the second stage is the economic dispatch optimization; verifies the influence of the market entry mode, bidding strategy, etc. of new energy units on the market clearing electricity price, and improves the solution efficiency through a two-stage modeling method; the present invention can design different market participation ratios and bidding strategies for new energy according to the differences in the time and construction cost of new energy power grid connection, which can be used to analyze the quantitative results of new energy participating in spot market transactions in multiple scenarios, and provide method support and data basis for the optimization design of market mechanisms. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0040] Figure 1 This is a flow chart of the current electricity market trading mechanism.

[0041] Figure 2 This is the simulation result of market clearing electricity quantity on a typical day in spring under the basic scenario.

[0042] Figure 3 This is the simulation result of market clearing electricity quantity on a typical day in summer under the basic scenario.

[0043] Figure 4 This is the simulation result of the market clearing electricity price on a typical day in spring under the basic scenario.

[0044] Figure 5 This is the simulation result of the market clearing electricity price on a typical day in summer under the basic scenario. DETAILED DESCRIPTION

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0047] 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.

[0048] The power market transaction clearing optimization method considering the same-station bidding of new energy and thermal power of the present invention comprises the following steps:

[0049] S1. Establish a unit combination optimization model, obtain the start-stop state variable values ​​of each thermal power unit, determine the start-stop plan of the thermal power unit, and establish necessary boundary conditions for the next stage of economic dispatch optimization;

[0050] S2. Establish an economic dispatch optimization model, perform economic dispatch optimization, and allocate the power generation sequence and the market clearing electricity price each time.

[0051] The electricity spot market clearing model is essentially a joint dispatch model for multiple types of generators. By matching supply and demand, the optimal dispatch order of power generation resources at the unit level is obtained, and then the shadow price of the marginal generator is obtained under the equilibrium condition of each time period, that is, the market clearing price at this time. Based on the theory of unit combination and economic dispatch, a two-stage electricity spot market clearing model is constructed.

[0052] The step S1 is the first stage. The core goal of this stage is to determine the start and stop plan of the thermal power unit, so as to establish the necessary boundary conditions for the economic dispatch optimization in the next stage, including:

[0053] (1) Determine the objective function

[0054] The formulation of the start-up and shutdown plan of thermal power units is a key prerequisite for the day-ahead power generation plan and is essential for maintaining the stability and security of the power system. Therefore, the goal of this model is to minimize the overall grid dispatching cost, including the unit dispatching cost, the start-up and shutdown costs of thermal power units, and the costs associated with the call of energy storage systems, etc. These costs are shown below;

[0055]

[0056] Where C represents the overall grid dispatching cost; t and T represent the minimum trading period and the total trading period, which are usually 1 hour and 24 hours respectively; i, j, k, and m represent the number of thermal power units, the amount of affordable new energy, the amount of subsidized new energy, and the number of energy storage devices, respectively; N, J, K, and M are the total number of units corresponding to each; and O m,t are the marginal generation costs of these generators respectively; and P m,t Respectively represent the power generation corresponding to these technologies; u i,t is a Boolean variable used to indicate the start and stop status of thermal power unit i at time t, 1 and 0 represent start and stop respectively; SU i,t and SD i,t is the cost of starting and stopping; is an exogenous parameter that controls the market access ratio; by adjusting its value, the impact of different market access ratios can be analyzed.

[0057] (2) Determine relevant constraints

[0058] ① Power balance constraints

[0059]

[0060] Among them, D t represents the power demand, F m,t Indicates the energy storage charging demand;

[0061] ② Upper and lower limits of generator output

[0062]

[0063] in, It is the technical parameter of the minimum output of thermal power units. When the output of thermal power units is too low, there will be hidden dangers in the operation of the boiler and the start-up and shutdown costs of thermal power units are high. Therefore, the minimum output power is limited. When the actual power is less than the minimum power, it is regarded as a shutdown. and They represent the maximum output technical parameters of two renewable energy power generation technologies, which mainly depend on the endowment conditions of natural resources such as wind and solar energy in the case study area; G m Respectively represent the installed capacity, i.e. rated power, of units i, j, k and m;

[0064] ③Technical constraints on the operation of various power generation technologies

[0065] In addition to the above constraints, the safety constraint unit combination model also needs to consider the technical constraints of various generating units, including the climbing constraints of thermal power units, the start and stop time constraints of thermal power units, the output conversion constraints of new energy units, and the daily balance constraints of energy storage equipment.

[0066] The step S2 is the second stage. Through the calculation of the first stage model, the start-stop state variable value of each thermal power unit can be obtained, and then on this basis, a start-stop plan for the thermal power unit that meets the safety constraints is formulated. This result is introduced as a parameter input into the second stage model for economic dispatch optimization, thereby allocating the power generation sequence and the market clearing electricity price each time. It includes:

[0067] (1) Objective function

[0068] The goal is to minimize the grid dispatching cost, but it should be noted that the start-up and shutdown costs of thermal power units have been excluded. As shown in the following formula;

[0069]

[0070] (2) Constraints

[0071] Except for the start / stop state and time constraints of the thermal power units, which are cancelled due to the direct use of the corresponding optimization results of step S1, other constraints remain the same as those in the first stage;

[0072] (3) Quotation method for generators participating in the market

[0073] At present, the mainstream pricing theory of the electricity spot market is based on the marginal cost pricing theory in microeconomics, which is also the theory adopted by countries around the world for market transactions and the design of bidding strategies for power generation units. For new energy units, the marginal cost of their power generation is zero, so they have greater flexibility in their bidding strategies. In order to ensure priority clearing, they can bid at extremely low prices; in order to maximize power generation revenue, the bid price of thermal power units and historical market clearing electricity price data are shown in the following formula;

[0074]

[0075] Among them, p q-min and p q-max , respectively represent the lower and upper limits of the bidding price of the generator set in the spot market; the generator set can decide its bidding behavior within the price range according to its own operation strategy;

[0076] For thermal power units, a segmented and incremental method is used to guide their bidding, which not only encourages them to bid as close to their marginal cost as possible, but also ensures the effectiveness of the clearing model solution, as shown in the following formula; on the one hand, through segmented bidding, it can encourage units to bid according to the actual marginal cost of power generation in different operating intervals, which helps to minimize the system operation cost. On the other hand, through incremental bidding, it can ensure that the function between power generation and bid price is a convex function, thereby ensuring the efficiency of model solution.

[0077]

[0078] Among them, the thermal power units adopt the segmented and incremental bidding method, and set the corresponding bidding price according to different power output segments; α n It represents the bid price increment of the nth segment output relative to the price floor; Represents the output adjustment parameter of the nth paragraph declaration; market designers can adjust the value of n according to actual conditions to determine the level of detail of the declared output, aiming to guide thermal power units to bid closer to their actual marginal costs.

[0079] (4) Market Clearing Price and Settlement Price

[0080] By solving the shadow price of the power balance constraint, the spot market clearing price at different trading times t is obtained. Based on the winning bid power of each unit, the average settlement price of each power generation technology is calculated. The calculation method of the average settlement price of thermal power is as follows;

[0081]

[0082] in, is the weighted average settlement price of thermal power unit i; is the real-time clearing price at time t.

[0083] The present invention proposes a method for optimizing the clearing of electricity spot market transactions by considering the same-platform bidding of new energy and thermal power. The method enables existing new energy and incremental new energy to bid on the same platform with traditional thermal power, and analyzes the impact of the entry of existing new energy into the market at a fixed ratio and the entry of the full amount of incremental new energy into the market on the market clearing price.

[0084] Use Figure 1 The application effect of the method for carrying out the power market trading mechanism shown in the figure is calculated, where the basic data are shown in Table 1, and the simulation calculation results of the market clearing electricity volume and electricity price on two typical days in spring and summer are shown in Figure 2-5 , the specific data under different market entry ratios are shown in Table 2 and Table 3. After analysis, it can be seen that in the spring weekday period, when the new energy quotation is less than or equal to the average thermal power quotation, if the scale of new energy entering the market increases, the average market clearing price will be slightly reduced, and the lower the new energy quotation, the greater the reduction; when the new energy quotation is higher than the average thermal power quotation, at this time, due to oversupply in the market, thermal power can meet the electricity demand, so when bidding on the same platform, new energy may not be able to win the bid if it quotes a high price, and the simulated settlement average price will also rise. In addition, when the scale of new energy entering the market remains unchanged, the higher the new energy quotation, the higher the market clearing average price. In the summer peak period, when the new energy quotation is less than or equal to the average thermal power price, the increase in the scale of new energy entering the market has little effect on the market clearing average price. At this time, the market electricity is in short supply, and the clearing marginal unit is thermal power; when the new energy quotation is higher than the average thermal power price, the increase in the scale of market entry will significantly increase the average clearing price. In horizontal comparison, when the scale of new energy entering the market remains unchanged, the closer the new energy quotation is to the average thermal power price, the lower the market clearing price.

[0085] Table 1 Overview of installed capacity of generators under simulation scenarios

[0086]

[0087] Table 2 Market simulation results for typical day trading in spring

[0088]

[0089] Table 3 Market simulation results for typical day trading in summer

[0090]

[0091] In summary, the power market transaction clearing optimization method considering the same-station bidding of new energy and thermal power of the present invention comprises the following steps: S1, establishing a unit combination optimization model, obtaining the start-stop state variable value of each thermal power unit, determining the start-stop plan of the thermal power unit, and establishing necessary boundary conditions for the next stage of economic dispatch optimization; S2, establishing an economic dispatch optimization model, performing economic dispatch optimization, and allocating the power generation sequence and the market clearing electricity price each time; the present invention constructs a two-stage power market clearing model considering the step-by-step quotation strategy of different types of power generating units, wherein the first stage is unit combination optimization and the second stage is economic dispatch optimization; verifies the influence of the market entry mode and quotation strategy of new energy units on the market clearing electricity price, and improves the solution efficiency through a two-stage modeling method; the present invention can design different market participation ratios and bidding strategies for new energy according to the differences in the time of grid connection and construction cost of new energy power, and can be used to analyze the quantitative results of new energy participating in spot market transactions under multiple scenarios, and provide method support and data basis for the optimization design of market mechanism.

[0092] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. An optimization method for clearing electricity market transactions considering the bidding of new energy and thermal power, characterized in that: The following steps are involved: S1. Establish a unit combination optimization model, obtain the start-stop state variable values ​​of each thermal power unit, determine the start-stop plan of the thermal power unit, and establish necessary boundary conditions for the next stage of economic dispatch optimization; S2. Establish an economic dispatch optimization model, perform economic dispatch optimization, and allocate the power generation sequence and the market clearing electricity price each time.

2. The power market transaction clearing optimization method considering the same-station bidding of new energy and thermal power as claimed in claim 1 is characterized in that: The step S1 comprises: (1) Determine the objective function Minimize the overall grid dispatch costs, including unit dispatch costs, thermal power unit start-up and shutdown costs, and costs associated with energy storage system calls, as shown below; Where C represents the overall grid dispatching cost; t and T represent the minimum trading period and the total trading period respectively; i, j, k, and m represent the number of thermal power units, the amount of affordable new energy, the amount of subsidized new energy, and the number of energy storage devices respectively; N, J, K, and M are the total number of units corresponding to each; and O m,t are the marginal generation costs of these generators respectively; and P m,t Respectively represent the power generation corresponding to these technologies; u i,t is a Boolean variable used to indicate the start and stop status of thermal power unit i at time t, 1 and 0 represent start and stop respectively; SU i,t and SD i,t is the cost of starting and stopping; is an exogenous parameter that controls the market access ratio; (2) Determine relevant constraints ① Power balance constraints Among them, D t represents the power demand, F m,t Indicates the energy storage charging demand; ② Upper and lower limits of generator output in, It is the technical parameter of the minimum output of thermal power units; and Respectively represent the maximum output technical parameters of two new energy power generation technologies; G m Respectively represent the installed capacity, i.e. rated power, of units i, j, k and m; ③Technical constraints on the operation of various power generation technologies In addition to the above constraints, the safety constraint unit combination model also needs to consider the technical constraints of various generating units, including the climbing constraints of thermal power units, the start and stop time constraints of thermal power units, the output conversion constraints of new energy units, and the daily balance constraints of energy storage equipment.

3. The power market transaction clearing optimization method considering the same-station bidding of new energy and thermal power as claimed in claim 1 is characterized in that: The step S2 comprises: (1) Objective function The goal is to minimize the grid dispatching cost, as shown below; (2) Constraints Except for the start / stop state and time constraints of the thermal power units, which are cancelled due to the direct use of the corresponding optimization results of step S1, other constraints remain the same as those in the first stage; (3) Quotation method for generators participating in the market The bid price of thermal power units and historical market clearing price data are shown in the following formula; Among them, p q-min and p q-max , respectively represent the lower and upper limits of the bidding price of power generators in the spot market; For thermal power units, a segmented and incremental approach is used to guide their bidding, as shown in the following formula; Among them, the thermal power units adopt the segmented and incremental bidding method, and set the corresponding bidding price according to different power output segments; α n It represents the bid price increment of the nth segment output relative to the price floor; Represents the output adjustment parameters declared in the nth paragraph; (4) Market Clearing Price and Settlement Price By solving the shadow price of the power balance constraint, the spot market clearing price at different trading times t is obtained. Based on the winning bid power of each unit, the average settlement price of each power generation technology is calculated. The calculation method of the average settlement price of thermal power is as follows; in, is the weighted average settlement price of thermal power unit i; is the real-time clearing price at time t.

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