A method for analyzing external effects of electricity market mechanisms

Abstract

The present invention discloses a method for analyzing the external effects of an electricity market mechanism, and belongs to the technical field of electricity market mechanism analysis. The present invention can analyze the external effects and impacts of potential dispatchable or integrable resources outside the market on the behavior of market entities and the system from a dynamic development perspective, and then analyze the advantages and disadvantages, potential risks and benefits of the electricity market mechanism. This method can achieve a quantitative assessment of the incentive compatibility of the market mechanism, can objectively and accurately analyze the advantages and disadvantages of the market mechanism, and can reflect the potential risks and benefits of the market mechanism through the relationship between multi-dimensional system-level indicators and individual-level indicators. Compared with the existing relatively static market mechanism analysis methods, the method in this article can analyze problems from a dynamic development perspective.

Description

Technical Field

[0001] The present invention belongs to the technical field of power market mechanism analysis, and in particular relates to a method for analyzing external effects of a power market mechanism. Background Art

[0002] At present, existing methods mainly focus on analyzing and evaluating the internal effects of the electricity market mechanism, that is, under the conditions of given market resources and participants, in a relatively static and stable market internal competition environment, the market behavior of various market entities and their impact on the electricity market and power system are analyzed, such as bidding strategies, game models, market equilibrium analysis, etc. However, there is still a gap in the research on the external effects of the electricity market mechanism, that is, analyzing the impact of potential, non-market dispatchable or integrable external resources on the behavior of market entities and the system from a dynamic development perspective. In order to fill this technical gap and analyze the electricity market mechanism from a more comprehensive perspective, the present invention proposes an external effect analysis method for the electricity market mechanism. Summary of the Invention

[0003] In view of the problems existing in the above background technology, the present invention proposes a method for analyzing the external effects of the electricity market mechanism.

[0004] To this end, the present invention adopts the following technical solution: A method for analyzing the external effects of an electricity market mechanism comprises the following steps:

[0005] Step 1: General definition of electricity market mechanisms

[0006] Taking the day-ahead electricity market as the research object, we first establish a general electricity market model. An electricity market mechanism consists of three parts: a clearing model, a price mechanism, and a settlement method. The price mechanism is the core of the market mechanism. The price mechanism usually determines the market price based on the clearing model, while the settlement method pays the market participants according to the price mechanism.

[0007] The general electricity market clearing model can be abstracted into the optimization model shown in formula (1). This clearing model usually takes maximizing the global social welfare W as the optimization goal, which is equal to the electricity value U minus the global operating cost C. The constraints include the power balance constraint F, the physical constraint H of the generator and GES, and the network constraint J.

[0008]

[0009] Among them, P i G represents the power curve supplied by generator i; n represents the total number of generators participating in the market; P D Represents the power demand curve of the load. For the sake of convenience, the system load is regarded as a whole P D, in practice it can be further written into the form of the load vector of each node;

[0010] Formula (2) gives the price mechanism based on the clearing model (1), and formula (3) gives the corresponding settlement method.

[0011] π=f(W,P1 G ,P2 G ,…,P n G ,P D ,F,H,J) (2)

[0012]

[0013] Where π represents the market price of electricity determined by the price mechanism f; I represents the income I obtained by each generator from the market under the settlement mechanism τ i and Load Payment I D The vectors that together form;

[0014] Formulas (1)-(3) together constitute the electricity market based on a certain market mechanism, denoted as Θ. The corresponding mathematical expression is shown in formula (4):

[0015]

[0016] Step 2: General definition of external resources

[0017] The general definition of external resources is external power generation resources or external regulation resources that do not participate in market competition, denoted as x. External resources x have their own cost functions and constraints, as shown in Equation (5). In practice, the reason why external resources do not participate in the market is that x only represents energy storage resources or distributed generation resources that have not yet been built, or flexible load resources that have not yet been integrated, or generalized energy storage resources that do not meet market access conditions.

[0018]

[0019] Among them, X i G P represents the set of external resources that can be dispatched by market entity i; (x) represents the power curve or regulation curve provided by the external resource x; C (x) Indicates P (x) The corresponding cost; y represents the total cost of calling x; e (x) and l (x) They represent the equality and inequality constraints that x must satisfy, respectively. For the market Θ, X i G , x, y, C (x) 、e (x) 、l (x) and P(x) are considered external variables;

[0020] Step 3: Positive / negative externalities of individual / system-level indicators

[0021] When market subject i calls external variable x, the market clearing model will become formula (6):

[0022]

[0023] Where W′, C′, and H′ represent the global social welfare, global cost function, and physical constraints of the generator under the influence of x and i, respectively;

[0024] Individual i participating in market Θ always maximizes his profit r i As the goal, the individual-level indicator of market entity i can be defined as formula (7):

[0025]

[0026] in, The decision variables in expression (6) are The optimal solution of C i G0 Represents the electricity supply curve of market entity i the required production costs;

[0027] The external effect is denoted as Γ, and the external variable P (x) For the individual-level indicator r i The external effect is recorded as Its mathematical definition is formula (8):

[0028]

[0029] The purple line shows the path through which external resources produce external effects on system-level and individual-level indicators;

[0030] In market Θ, if external resources x help market entity i increase its profit r i ,Right now Then define x for the individual level indicator r i Produces positive external effects; all P (x) Defined as the set of positive external variables of subject i, denoted as The corresponding mathematical expression is formula (9):

[0031]

[0032] Where G is the set of generators participating in market Θ; X is the set of all external resources of all market entities; argmax W and argmax W' respectively represent W and W' in the optimization model for solving equations (1) and (6);

[0033] If the subject in the market Θ is rational enough, the subject will exclude the i negative external effects, so there is usually where Ω i←x Represents the external variable P actually called by subject i (x) Therefore, in the analysis of the external effects of the electricity market mechanism, external variables are considered. Impact on system-level indicators;

[0034] For any x and P (x) All of them may indirectly affect the market clearing results by serving market subject i, and thus affect various important system-level indicators, including the global social welfare W′ * , total load payment α * , renewable energy consumption rate β * , Net load peak-to-valley difference γ * , formula (10) gives the general mathematical definition of these system-level indicators:

[0035]

[0036] In order to explain the external effects on system-level indicators, we take the global social welfare W as an example. The analysis methods of other indicators are similar. (x) The external effect of the system-level indicator W is denoted as Γ W←x , defined as formula (11):

[0037]

[0038] The positive external effect of system-level indicators is defined as: The external variable P in (x) Under the action of , the system-level index increases, that is, Γ W←x ≥0; the market mechanism Θ generates positive external effects on the system in the process of guiding market entities to utilize external resources x for profit; therefore, the positive external effects on system-level indicators can reveal that the performance of the market mechanism Θ is relatively good and is compatible with the incentives of market entity i and external resources x;

[0039] On the contrary, the negative externality of the system-level indicator is defined as: The external variable P in (x) Under the action of , the system-level index is reduced, that is, ΓW←x <0. This means that individual profit-seeking behavior will harm the interests of the system as a whole, and the market mechanism Θ is flawed in this respect.

[0040] Taking into account the complementarity of the positive and negative external effects of system-level indicators, the mathematical definition formula of the positive external effects of global social welfare W is given here, as shown in formula (12):

[0041]

[0042] Define external variable P (x) The set of all simulation sequences is Ω (x) ; Obviously the set Ω (x) There is a certain mapping relationship between the external effect Γ and the external effect Γ. By repeatedly simulating different variables P (x) And the corresponding Γ is obtained, and the numerical relationship between the two can be observed;

[0043] The maximum point of individual-level external effect is defined as the set Ω (x) The individual level indicator r i External variable P reaches its maximum value (x) The mathematical definition of the location is formula (13):

[0044]

[0045] The maximum point of system-level external effect is defined as the set Ω (x) The external variable P that makes the system-level indicator reach the maximum value (x) The mathematical definition of the location is formula (14):

[0046]

[0047] At this point, the external effect analysis model considering a single market player calling on external resources has been established. Similarly, it can be easily extended to the analysis model considering multiple market players calling on external resources at the same time.

[0048] Step 4: Multi-agent external effect analysis method considering external generalized energy storage

[0049] The external GES resources belonging to market entity i are denoted as x i .x i ∈X i G The cost function and constraints are shown in Equations (15)-(18):

[0050]

[0051]

[0052]

[0053]

[0054] in, represents the external generalized energy storage x i Provided adjustment curve; express The amount of adjustment; for The cost coefficient of t is the time period; Δt is the time interval; T is the total number of time periods; Represents x i Capacity, maximum capacity, and minimum capacity in time period t; x i Power amplitude, maximum discharge power, and maximum charging power in time period t;

[0055] Consider x i and The operating constraints of generator i become formula (19):

[0056]

[0057] Among them, G represents the set of power generators participating in the market; and Respectively indicate that when calling x i Before, the maximum and minimum output power of generator i in time period t; and Respectively indicate that when calling x i Afterwards, the maximum and minimum output power of generator i in time period t; and Respectively indicate that when calling x i Before, the maximum and minimum ramp rates of generator i in period t; and Respectively indicate that when calling x i Afterwards, the maximum and minimum ramp rates of generator i in period t;

[0058] In the day-ahead electricity market based on the LMP mechanism, the market clearing model considering multi-agent external variables is shown in Equations (20)-(26):

[0059]

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] Among them, W LMP represents the global social welfare under the LMP mechanism; here the electricity value U is regarded as a constant; C i P P represents the quotation function of the amount of electricity provided by subject i; t D represents the load demand during period t; Indicates calling x i The power amplitude of subject i in time period t; Indicates calling x i The electricity supply curve of subject i; The power consumption per period The quotation coefficient of represents the cost of charging and discharging energy of market entity k; represents the power amplitude of subject k in time period t; P k B represents the electricity supply curve of subject k; m is the total number of GES participating in the market; B represents the set of all GES participating in the day-ahead electricity market; They represent the capacity, maximum capacity, and minimum capacity of subject k in time period t respectively; They represent the power score, maximum discharge power, and maximum charging power of subject k in time period t respectively; is the cost coefficient of the charge and discharge amount in a single period, which can be regarded as the battery charge and discharge cycle cost; for simplicity, the last equation of formula (26) stipulates that the total amount of electricity provided by GES is zero;

[0067] The pricing method of the LMP mechanism is shown in formula (27); the marginal electricity price π LMP The value of is equal to the (vector) value of the Lagrange multiplier of the first equality constraint in Equation (26), which represents the marginal price of the electricity market in each period;

[0068]

[0069] Here, the symbol dual(·) represents the (vector) value of the Lagrange multiplier of a certain constraint.

[0070] Under the LMP mechanism, according to π LMP For settlement, the individual level indicator r of any generator i i It can be calculated using formula (28):

[0071]

[0072] in, The amount of electricity produced by generator i in time period t Cost coefficient;

[0073] For the market based on the LMP mechanism, the system-level indicators under the influence of external GES are calculated using formula (29);

[0074]

[0075] Here, W * 、U * 、C * Respectively represent W in formulas (20)-(26) LMP , U, C's optimal value; G R represents the set of renewable energy generators; P Dnet Represents the net load curve; P t Dnet represents the net load in time period t;

[0076] External variables belonging to RE generator i The simulation sequence of is generated by formula (30):

[0077]

[0078] Where v is an external variable Serial number; V represents the simulation sequence Resolution; P i Gfore Represents the power prediction curve of RE generator i, that is, its maximum output power P i Gmax ; Indicates P i Gfore The power amplitude during the period t;

[0079] exist With the help of the RE generator i, the new maximum output power becomes As v changes from 0 to 2V, its value is within the original output upper limit P i Gfore to its inverted value Therefore, the external variable sequence It can simulate a relatively complete external effect. Finally, the external generalized storage i Provided Adjustment The numerical relationship between the individual-level / system-level indicators can be expressed as formula (31):

[0080]

[0081] Where ξ(·) represents A certain mapping relationship with each indicator.

[0082] The above method can be used to obtain the distribution of positive / negative external effects of individual-level indicators and system-level indicators in any market mechanism Θ when any subject calls on any external resource. This can then determine the incentive compatibility between the market mechanism Θ and each indicator, and analyze the advantages and disadvantages, nature and characteristics, and potential risks of the market mechanism.

[0083] The present invention can achieve the following beneficial effects: 1. The present invention can analyze the external effects and impacts of potential dispatchable or integrable resources outside the market on the behavior of market entities and the system from a dynamic development perspective, and further analyze the advantages and disadvantages, potential risks and benefits of the electricity market mechanism. 2. The present invention can achieve a quantitative assessment of the incentive compatibility of the market mechanism, can objectively and accurately analyze the advantages and disadvantages of the market mechanism, and can reflect the potential risks and benefits of the market mechanism through the relationship between multi-dimensional system-level indicators and individual-level indicators. Compared with existing relatively static market mechanism analysis methods, the method in this paper can analyze problems from a dynamic development perspective. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] Figure 1 Schematic diagram of the electricity market external effects of the present invention. DETAILED DESCRIPTION

[0085] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings. The described embodiments are only for illustration and explanation of the present invention and do not constitute the sole limitation of the present invention.

[0086] like Figure 1 As shown, a method for analyzing external effects of a power market mechanism according to the present invention includes the following steps:

[0087] Step 1: General definition of electricity market mechanisms

[0088] Taking the day-ahead electricity market as the research object, we first establish a general electricity market model. The main participants in the electricity market usually include thermal power generators, renewable energy (RE) generators and generalized D energy storage (GES). Figure 1 As shown in Figure 1, an electricity market mechanism consists of three parts: a clearing model, a price mechanism, and a settlement method. The price mechanism is the core of the market mechanism and is usually based on the clearing model to determine the market price. The settlement method pays each market player according to the price mechanism.

[0089] The general electricity market clearing model can be abstracted into the optimization model shown in formula (1). This clearing model usually takes maximizing the global social welfare W as the optimization goal, which is equal to the electricity value U minus the global operating cost C. The constraints include the power balance constraint F, the physical constraint H of the generator and GES, and the network constraint J.

[0090]

[0091] Among them, P i G represents the power curve supplied by generator i; n represents the total number of generators participating in the market; P D Represents the power demand curve of the load. For the sake of convenience, the system load is regarded as a whole P D , in practice it can be further written into the form of the load vector of each node;

[0092] Formula (2) gives the price mechanism based on the clearing model (1), and formula (3) gives the corresponding settlement method.

[0093] π=f(W,P1 G ,P2 G ,…,P n G ,P D ,F,H,J) (2)

[0094]

[0095] Where π represents the market price of electricity determined by the price mechanism f; I represents the income I obtained by each generator from the market under the settlement mechanism τ i and Load Payment I D The vectors that together form;

[0096] Formulas (1)-(3) together constitute the electricity market based on a certain market mechanism, denoted as Θ. The corresponding mathematical expression is shown in formula (4):

[0097]

[0098] Step 2: General definition of external resources

[0099] The general definition of an external resource is an external generation resource or external regulation resource that does not participate in market competition, denoted as x. External resource x may be an energy storage system, a virtual power plant, or a flexible load aggregator, etc. At the same time, external resource x has its own cost function and constraints, as shown in Equation (5). In practice, the reason why external resources do not participate in the market is that x only represents energy storage resources or distributed generation resources that have not yet been built, or flexible load resources that have not yet been integrated, or generalized energy storage resources that do not meet market access conditions (for example, their energy storage capacity does not meet the minimum capacity required by the market).

[0100]

[0101] Among them, X i G P represents the set of external resources that can be dispatched by market entity i; (x) represents the power curve or regulation curve provided by the external resource x; C (x) Indicates P (x) The corresponding cost; y represents the total cost of calling x; e (x) and l (x) They represent the equality and inequality constraints that x must satisfy, respectively. For the market Θ, X i G , x, y, C (x) 、e (x) 、l (x) and P (x) are considered external variables;

[0102] If market entity i pays fee C (x) If the power to use external resources x is obtained, the electricity curve P supplied by market subject i will be i G Re-recorded like Figure 1 As shown in Figure 1, with the help of external resources x, market subject i can report a set of new constraints and quotations to the market operator, such as new output constraints, ramping constraints, electricity prices, etc. In any case, the goal of market subject i is to use external resources x to make more profits from the market. It should be noted that the market operator always considers subject i integrated with x as a whole and includes it in the clearing model (1). In other words, in the real electricity market, the market operator neither knows nor cares whether each market subject calls external resources, but only focuses on the electricity trading transactions that the market Θ itself should execute. Without loss of generality, we assume that the external resources x belonging to market subject i only serve subject i and cannot be called by the power grid dispatch center or other market subjects. A typical manifestation of external resources in the real market is that a power generator integrates a large number of local flexible loads or builds a new energy storage system, thereby creating more profits for itself in the market;

[0103] Step 3: Positive / negative externalities of individual / system-level indicators

[0104] When market subject i calls external variable x, the market clearing model will become formula (6):

[0105]

[0106] Where W′, C′, and H′ represent the global social welfare, global cost function, and physical constraints of the generator under the influence of x and i, respectively;

[0107] Individual i participating in market Θ always maximizes his profit r i As the goal, the individual-level indicator of market entity i can be defined as formula (7):

[0108]

[0109] in, The decision variables in expression (6) are The optimal solution of C i G0 Represents the electricity supply curve of market entity i the required production costs;

[0110] The external effect is denoted as Γ, and the external variable P (x) For the individual-level indicator r i The external effect is recorded as Its mathematical definition is formula (8):

[0111]

[0112] The purple line shows the path through which external resources produce external effects on system-level and individual-level indicators;

[0113] In market Θ, if external resources x help market entity i increase its profit r i ,Right now Then define x for the individual level indicator r i Produces positive external effects; all P (x) Defined as the set of positive external variables of subject i, denoted as The corresponding mathematical expression is formula (9):

[0114]

[0115] Where G is the set of generators participating in market Θ; X is the set of all external resources of all market entities; argmax W and argmax W' respectively represent W and W' in the optimization model for solving equations (1) and (6);

[0116] If the subject in the market Θ is rational enough, the subject will exclude the i negative external effects, so there is usually where Ω i←x Represents the external variable P actually called by subject i (x) Therefore, in the analysis of the external effects of the electricity market mechanism, external variables are considered. Impact on system-level indicators;

[0117] For any x and P (x) All of them may indirectly affect the market clearing results by serving market subject i, and thus affect various important system-level indicators, including the global social welfare W′ * , total load payment α * , renewable energy consumption rate β * , Net load peak-to-valley difference γ * , formula (10) gives the general mathematical definition of these system-level indicators:

[0118]

[0119] For ease of explanation, we assume that system-level metrics always favor increasing values. Although some system-level metrics actually favor decreasing values, this assumption can be satisfied by adding a negative sign to these metrics.

[0120] In order to explain the external effects on system-level indicators, we take the global social welfare W as an example. The analysis methods of other indicators are similar. (x) The external effect of the system-level indicator W is denoted as Γ W←x , defined as formula (11):

[0121]

[0122] The positive external effect of system-level indicators is defined as: The external variable P in (x) Under the action of , the system-level index increases, that is, Γ W←x ≥0; the market mechanism Θ generates positive external effects on the system in the process of guiding market entities to utilize external resources x for profit; therefore, the positive external effects on system-level indicators can reveal that the performance of the market mechanism Θ is relatively good and is compatible with the incentives of market entity i and external resources x;

[0123] On the contrary, the negative externality of the system-level indicator is defined as: The external variable P in (x) Under the action of , the system-level index is reduced, that is, ΓW←x <0. This means that individual profit-seeking behavior will harm the interests of the system as a whole, and the market mechanism Θ is flawed in this respect.

[0124] Taking into account the complementarity of the positive and negative external effects of system-level indicators, the mathematical definition formula of the positive external effects of global social welfare W is given here, as shown in formula (12):

[0125]

[0126] Furthermore, it should be noted that the external effect analysis method proposed in this paper can quantitatively evaluate the incentive compatibility of various system-level indicators (not just the four indicators mentioned in this article), thereby identifying the strengths and weaknesses of the market mechanism. At the same time, the external effect analysis method can be seen as a further extension and expansion of the concept of incentive compatibility in traditional markets. On the one hand, it extends to any individual-level and system-level indicators, rather than a single economic indicator. On the other hand, it goes beyond the internal scope of the market and quantifies the incentive compatibility of the electricity market mechanism from the perspective of external resources and dynamic development.

[0127] Considering that in the actual electricity market, power generators may have complete or incomplete market information, any P in (x) All of these can be invoked by market entity i. Therefore, in order to observe a more complete set of external effects, this paper uses an external variable simulation method to analyze the positive and negative effects of a large number of individual-level profit-seeking behaviors on system-level indicators. This can further infer the possible evolutionary directions of individuals and systems driven by market mechanisms, as well as the changing trends of important indicators.

[0128] Define external variable P (x) The set of all simulation sequences is Ω (x) ; Obviously the set Ω (x) There is a certain mapping relationship between P and external effect Γ. (x) It is difficult to formulate the mathematical relationship between and Γ, but by repeatedly simulating different variables P (x) And the corresponding Γ is obtained, and the numerical relationship between the two can be observed;

[0129] The maximum point of individual-level external effect is defined as the set Ω (x) The individual level indicator r i The external variable P reaches its maximum value (x) The mathematical definition of the location is formula (13):

[0130]

[0131] The maximum point of system-level external effect is defined as the set Ω(x) The external variable P that makes the system-level indicator reach the maximum value (x) The mathematical definition of the location is formula (14):

[0132]

[0133] At this point, the external effect analysis model considering a single market player calling on external resources has been established. Similarly, it can be easily extended to the analysis model considering multiple market players calling on external resources at the same time.

[0134] Step 4: Multi-agent external effect analysis method considering external generalized energy storage

[0135] This paper further proposes a specific external effect analysis method, namely a multi-agent external effect analysis method that considers external generalized energy storage. Here, the electricity market mechanism selects the locational marginal price (LMP) mechanism widely used in the actual electricity market. Similarly, the analysis method in this paper can also be derived to other market mechanisms. External resources select external generalized energy storage, and external power generation resources are not considered (because the impact of pure power generation resources on the market is more obvious. When its marginal cost is lower than the market marginal price, it will definitely be called upon, and vice versa). The market entities that call upon external generalized energy storage are only renewable energy generators, because thermal power generators usually do not need to call upon external generalized energy storage due to their strong regulation capabilities. In addition, it is stipulated that power generation is positive and power consumption is negative.

[0136] The external GES resources belonging to market entity i are denoted as x i .x i ∈X i G The cost function and constraints are shown in Equations (15)-(18):

[0137]

[0138]

[0139]

[0140]

[0141] in, represents the external generalized energy storage x i Provided adjustment curve; express The amount of adjustment; for The cost coefficient of t is the time period; Δt is the time interval; T is the total number of time periods; Represents x i Capacity, maximum capacity, and minimum capacity in time period t; x i Power amplitude, maximum discharge power, and maximum charging power in time period t;

[0142] Consider x i and The operating constraints of generator i become formula (19):

[0143]

[0144] Among them, G represents the set of power generators participating in the market; and Respectively indicate that when calling x i Before, the maximum and minimum output power of generator i in time period t; and Respectively indicate that when calling x i Afterwards, the maximum and minimum output power of generator i in time period t; and Respectively indicate that when calling x i Before, the maximum and minimum ramp rates of generator i in period t; and Respectively indicate that when calling x i Afterwards, the maximum and minimum ramp rates of generator i in period t;

[0145] In the day-ahead electricity market based on the LMP mechanism, the market clearing model considering multi-agent external variables is shown in Equations (20)-(26):

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153] Among them, W LMP represents the global social welfare under the LMP mechanism; here the electricity value U is regarded as a constant; P represents the quotation function of the amount of electricity provided by subject i; tD represents the load demand during period t; Indicates calling x i The power amplitude of subject i in time period t; Indicates calling x i The electricity supply curve of subject i; The power consumption per period The quotation coefficient of represents the cost of charging and discharging energy of market entity k; represents the power amplitude of subject k in time period t; represents the electricity supply curve of subject k; m is the total number of GES participating in the market; B represents the set of all GES participating in the day-ahead electricity market; They represent the capacity, maximum capacity, and minimum capacity of subject k in time period t respectively; They represent the power score, maximum discharge power, and maximum charging power of subject k in time period t respectively; is the cost coefficient of the charge and discharge amount in a single period, which can be regarded as the battery charge and discharge cycle cost; for simplicity, the last equation of formula (26) stipulates that the total amount of electricity provided by GES is zero;

[0154] The pricing method of the LMP mechanism is shown in formula (27); the marginal electricity price π LMP The value of is equal to the (vector) value of the Lagrange multiplier of the first equality constraint in Equation (26), which represents the marginal price of the electricity market in each period;

[0155]

[0156] Here, the symbol dual(·) represents the (vector) value of the Lagrange multiplier of a certain constraint.

[0157] Under the LMP mechanism, according to π LMP For settlement, the individual level indicator r of any generator i i It can be calculated using formula (28):

[0158]

[0159] in, The amount of electricity produced by generator i in time period t Cost coefficient;

[0160] For the market based on the LMP mechanism, the system-level indicators under the influence of external GES are calculated using formula (29);

[0161]

[0162] Here, W * 、U * 、C* Respectively represent W in formulas (20)-(26) LMP , U, C's optimal value; G R represents the set of renewable energy generators; P Dnet Represents the net load curve; P t Dnet represents the net load in time period t;

[0163] External variables belonging to RE generator i The simulation sequence of is generated by formula (30):

[0164]

[0165] Where v is an external variable Serial number; V represents the simulation sequence Resolution; P i Gfore Represents the power prediction curve of RE generator i, that is, its maximum output power P i Gmax ; Indicates P i Gfore The power amplitude during the period t;

[0166] exist With the help of the RE generator i, the new maximum output power becomes As v changes from 0 to 2V, its value is within the original output upper limit P i Gfore to its inverted value Therefore, the external variable sequence It can simulate a relatively complete external effect. Finally, the external generalized storage i Provided Adjustment The numerical relationship between the individual-level / system-level indicators can be expressed as formula (31):

[0167]

[0168] Where ξ(·) represents A certain mapping relationship with each indicator.

[0169] The above method can be used to obtain the distribution of positive / negative external effects of individual-level indicators and system-level indicators in any market mechanism Θ when any subject calls on any external resource. This can then determine the incentive compatibility between the market mechanism Θ and each indicator, and analyze the advantages and disadvantages, nature and characteristics of the market mechanism, potential risks (for example, being unfavorable to a certain system-level indicator and generating negative external effects) and benefits (for example, promoting a certain indicator to generate positive external effects), etc.

[0170] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for analyzing the external effects of electricity market mechanisms is characterized by The following steps are involved: Step 1: General definition of electricity market mechanisms First, a general electricity market model is established. The electricity market mechanism consists of three parts: a clearing model, a price mechanism, and a settlement method. The price mechanism is the core of the market mechanism. The price mechanism determines the market price based on the clearing model, while the settlement method pays each market player according to the price mechanism. The electricity market clearing model can be abstracted into the optimization model shown in formula (1). This clearing model usually takes maximizing the global social welfare W as the optimization objective, which is equal to the electricity value U minus the global operating cost C. The constraints include the power balance constraint F, the physical constraint H of the generator and GES, and the network constraint J. in, represents the power curve supplied by generator n; n represents the total number of generators participating in the market; P D The power demand curve represents the load, and the system load is regarded as a whole P D , written in the form of the load vector of each node; Formula (2) gives the price mechanism based on the clearing model (1), and formula (3) gives the corresponding settlement method; Where π represents the market price of electricity determined by the price mechanism f; I represents the income I obtained by each generator from the market under the settlement mechanism τ n and Load Payment I D The vectors that together form; Formulas (1)-(3) together constitute the electricity market based on a certain market mechanism, denoted as Θ. The corresponding mathematical expression is shown in formula (4): Step 2: General definition of external resources The general definition of external resources is external power generation resources or external regulation resources that do not participate in market competition, denoted as x. External resources x have their own cost functions and constraints, as shown in Equation (5). In practice, the reason why external resources do not participate in the market is that x only represents energy storage resources or distributed generation resources that have not yet been built, or flexible load resources that have not yet been integrated, or generalized energy storage resources that do not meet market access conditions. in, P represents the set of external resources that can be dispatched by market entity i; (x) represents the power curve or regulation curve provided by the external resource x; C (x) Indicates P (x) The corresponding cost; y represents the total cost of calling x; e (x) and l (x) They represent the equality and inequality constraints that x must satisfy, respectively. For the market Θ, y, C (x) 、e (x) 、l (x) and P (x) are considered external variables; Step 3: Positive / negative externalities of individual / system-level indicators When market subject i calls external resource x, the market clearing model becomes formula (6): Where W′, C′, and H′ represent the global social welfare, global cost function, and physical constraints of the generator under the influence of x and i, respectively; Individual i participating in market Θ always maximizes his profit r i As the goal, the individual-level indicator of market entity i can be defined as formula (7): in, The decision variables in expression (6) are The optimal solution of Represents the electricity supply curve of market entity i the required production costs; The external effect is denoted as Γ, and the external variable P (x) For the individual-level indicator r i The external effect is recorded as Its mathematical definition is formula (8): In market Θ, if external resources x help market entity i increase its profit r i ,Right now Then define x for the individual level indicator r i Produces positive external effects; all P (x) Defined as the set of positive external variables of subject i, denoted as The corresponding mathematical expression is formula (9): Where G is the set of generators participating in market Θ; X is the set of all external resources of all market entities; argmax W and argmax W' respectively represent W and W' in the optimization model for solving equations (1) and (6); If the subject in the market Θ is rational enough, the subject will exclude the i negative external effects, so there is usually where Ω i←x Represents the external variable P actually called by subject i (x) Therefore, in the analysis of the external effects of the electricity market mechanism, external variables are considered. Impact on system-level indicators; For any x and P (x) All of them may indirectly affect the market clearing results by serving market subject i, and thus affect various important system-level indicators, including the global social welfare W′ * , total load payment α * , renewable energy consumption rate β * , Net load peak-to-valley difference γ * , formula (10) gives the general mathematical definition of these system-level indicators: In order to explain the external effects on system-level indicators, we take the global social welfare W as an example. The analysis methods of other indicators are similar. (x) The external effect of the system-level indicator W is denoted as Γ W←x , defined as formula (11): The positive external effect of system-level indicators is defined as: The external variable P in (x) Under the action of , the system-level index increases, that is, Γ W←x ≥0; the market mechanism Θ generates positive external effects on the system in the process of guiding market entities to utilize external resources x for profit; therefore, the positive external effects on system-level indicators can reveal that the performance of the market mechanism Θ is relatively good and is compatible with the incentives of market entity i and external resources x; On the contrary, the negative externality of the system-level indicator is defined as: The external variable P in (x) Under the action of , the system-level index is reduced, that is, Γ W←x <0; Taking into account the complementarity of the positive and negative external effects of system-level indicators, the mathematical definition formula of the positive external effects of global social welfare W is given here, as shown in formula (12): Define external variable P (x) The set of all simulation sequences is Ω (x) ; Obviously the set Ω (x) There is a certain mapping relationship between the external effect Γ and the external effect Γ. By repeatedly simulating different variables P (x) And the corresponding Γ is obtained, and the numerical relationship between the two can be observed; The maximum point of individual-level external effect is defined as the set Ω (x) The individual level indicator r i The external variable P reaches its maximum value (x) The mathematical definition of the location is formula (13): The maximum point of system-level external effect is defined as the set Ω (x) The external variable P that makes the system-level indicator reach the maximum value (x) The mathematical definition of the location is formula (14): At this point, the external effect analysis model considering a single market player calling on external resources has been established. Similarly, it can be easily extended to the analysis model considering multiple market players calling on external resources at the same time. Step 4: Multi-agent external effect analysis method considering external generalized energy storage The external GES resources belonging to market entity i are denoted as x i ;x i ∈X i G The cost function and constraints are shown in Equations (15)-(18): in, represents the external generalized energy storage x i Provided adjustment curve; express The amount of adjustment; for The cost coefficient of t is the time period; Δt is the time interval; T is the total number of time periods; Represents x i Capacity, maximum capacity, and minimum capacity in time period t; x i Power amplitude, maximum discharge power, and maximum charging power in time period t; Consider x i and The operating constraints of generator i become formula (19): Among them, G represents the set of power generators participating in the market; and Respectively indicate that when calling x i Before, the maximum and minimum output power of generator i in time period t; and Respectively indicate that when calling x i Afterwards, the maximum and minimum output power of generator i in time period t; and Respectively indicate that when calling x i Before, the maximum and minimum ramp rates of generator i in period t; and Respectively indicate that when calling x i Afterwards, the maximum and minimum ramp rates of generator i in period t; In the day-ahead electricity market based on the LMP mechanism, the market clearing model considering multi-agent external variables is shown in Equations (20)-(26): Among them, W LMP represents the global social welfare under the LMP mechanism; here the electricity value U is regarded as a constant; P represents the quotation function of the amount of electricity provided by subject i; t D represents the load demand during period t; Indicates calling x i The power amplitude of subject i in time period t; Indicates calling x i The electricity supply curve of subject i; The power consumption per period The quotation coefficient of represents the cost of charging and discharging energy of market entity k; represents the power amplitude of subject k in time period t; represents the electricity supply curve of subject k; m is the total number of GES participating in the market; B represents the set of all GES participating in the day-ahead electricity market; They represent the capacity, maximum capacity, and minimum capacity of subject k in time period t respectively; They represent the power score, maximum discharge power, and maximum charging power of subject k in time period t respectively; is the cost coefficient of the charge and discharge amount in a single period, which can be regarded as the battery charge and discharge cycle cost; for simplicity, the last equation of formula (26) stipulates that the total amount of electricity provided by GES is zero; The pricing method of the LMP mechanism is shown in formula (27); the marginal electricity price π LMP The value of is equal to the vector value of the Lagrange multiplier of the first equality constraint in equation (26), which represents the marginal price of the electricity market in each period; The symbol dual(·) represents the vector value of the Lagrange multiplier of a constraint. Under the LMP mechanism, according to π LMP For settlement, the individual level indicator r of any generator i i It can be calculated using formula (28): in, The amount of electricity produced by generator i in time period t Cost coefficient; For the market based on the LMP mechanism, the system-level indicators under the influence of external GES are calculated using formula (29); Here, W * 、U * 、C * Respectively represent W in formulas (20)-(26) LMP , U, C's optimal value; G R represents the set of renewable energy generators; P Dnet Represents the net load curve; P t Dnet represents the net load in time period t; External variables belonging to RE generator i The simulation sequence of is generated by formula (30): Where v is an external variable Serial number; V represents the simulation sequence Resolution; P i Gfore Represents the power prediction curve of RE generator i, that is, its maximum output power P i Gmax ; Indicates P i Gfore The power amplitude in time period t; exist With the help of the RE generator i, the new maximum output power becomes As v changes from 0 to 2V, its value is within the original output upper limit P i Gfore to its inverted value Therefore, the external variable sequence It can simulate a relatively complete external effect; finally, the external generalized storage x i Provided Adjustment The numerical relationship between the individual-level / system-level indicators can be expressed as formula (31): Where ξ(·) represents A certain mapping relationship with each indicator; The above method can be used to obtain the distribution of positive / negative external effects of individual-level indicators and system-level indicators in any market mechanism Θ when any subject calls on any external resource. This can then determine the incentive compatibility between the market mechanism Θ and each indicator, and analyze the advantages and disadvantages, nature and characteristics, and potential risks of the market mechanism.

2. The method for analyzing external effects of a power market mechanism according to claim 1 is characterized by: The entities participating in the electricity market in step 1 include thermal power generators, renewable energy generators and generalized energy storage.

3. The method for analyzing external effects of a power market mechanism according to claim 2 is characterized by: In step 2, the external resource x is an energy storage system, a virtual power plant, or a flexible load aggregator.

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