A method for optimizing the clearing of power carbon reduction

Abstract

The present invention provides a method for optimizing and clearing the power carbon reduction amount, which includes collecting the quotation data on both sides of the power generation load and then performing clearing using a full-time clearing model; the clearing includes regular clearing and guaranteed consumption clearing; the regular clearing is that both conventional power sources and renewable energy are added to the spot market, and the day-ahead market clearing result is obtained through the above full-time clearing model; the guaranteed consumption clearing is triggered after renewable energy curtailment occurs in the market, and the curtailed units participate in the secondary market clearing according to the corrected curtailed energy consumption quotation, the curtailed energy consumption quotation is less than the market minimum price limit, and the power generation volume transferred by some conventional units after the secondary clearing obtains settlement compensation. This method realizes the guaranteed consumption of renewable energy on the premise of maintaining the market pricing and resource optimization and allocation functions.

Description

Technical Field

[0001] The present invention relates to the technical field of power data processing, and specifically to a method for optimizing and clearing power carbon reduction amount. Background Art

[0002] There is a need to design a scientific and reasonable method for optimizing and clearing power carbon reduction amount to achieve the guaranteed consumption of renewable energy while maintaining the market pricing and resource optimization allocation functions. Summary of the Invention

[0003] The purpose of the present invention is to provide a method for optimizing and clearing power carbon reduction amount to achieve the guaranteed consumption of renewable energy while maintaining the market pricing and resource optimization allocation functions.

[0004] To this end, the present invention provides the following technical solutions:

[0005] A method for optimizing and clearing power carbon reduction amount, the steps of which include collecting the bid data on both sides of the power generation load and then performing clearing using a full-time clearing model; the clearing includes regular clearing and guaranteed consumption clearing; the regular clearing is that both conventional power sources and renewable energy are added to the spot market, and the day-ahead market clearing result is obtained through the above full-time clearing model; the guaranteed consumption clearing is triggered after renewable energy curtailment occurs in the market, and the curtailed units participate in the secondary market clearing according to the corrected curtailed energy consumption bid price, the curtailed energy consumption bid price is less than the market minimum price limit, and the power generation volume transferred by some conventional units after the secondary clearing obtains settlement compensation.

[0006] In at least one embodiment, the establishment of the full-time clearing model and the process of calculating the electricity price based on this model include:

[0007] 1) Establish an objective function and perform clearing with the maximization of social welfare as the optimization objective:

[0008]

[0009] In the formula, T represents the total number of time periods; L and G respectively represent the total number of load users and the total number of generating units; q load (l,t) and q gen (g,t) respectively represent the cleared electricity quantity of load l and generating unit g in time period t; B and C respectively represent the electricity consumption income and the power generation cost; C start is the total start-up cost of all units within the specified time period;

[0010] 2) System operation constraints, including system supply-demand balance constraints, line transmission capacity constraints, unit power generation capacity constraints, load electricity consumption capacity constraints, unit ramp-up and ramp-down constraints, virtual bidding ratio constraints, and unit start-stop constraints;

[0011] 3) Electricity price calculation, including nodal marginal price and unified price on the load side;

[0012] Among them, the nodal marginal price is:

[0013]

[0014] In the formula, D is the nodal load; λ is the shadow price of the system balance constraint; η is the shadow price of the line power flow constraint; is the power flow transfer factor of the node to the transmission line, indicating the power flow distributed by the net load on node n on line c;

[0015] The unified price on the load side is to correct the power flow transfer factor of each node to the transmission line in the following way:

[0016]

[0017] In the formula: ω represents the weight in the correction process; F 0 (n,c) represents the original power flow transfer factor calculated from the topological relationship of the line itself; F 1 (n,c) represents the corrected power flow transfer factor; N is the number of nodes.

[0018] In at least one embodiment, during the second clearing, the power generation side conducts secondary settlement accordingly, specifically:

[0019]

[0020] In the formula: is the total revenue of the unit i with reduced output in the second clearing at time t; is the total revenue of the unit i with increased output in the second clearing at time t; and are the long-term time-sharing net contract electricity quantity and the winning bid electricity quantity in the first clearing of unit i at time t respectively; and are the reduced power generation and increased power generation of unit i at time t in the second clearing respectively; L 1,i,t and L 2,i,t are the nodal electricity prices of unit i at time t in the first clearing and the second clearing respectively.

[0021] Compared with the prior art, the advantages of the present invention are:

[0022] 1. In the power generation side of the liquidation method of the present invention, under the requirement that the nodal price pricing mechanism is adopted and the unified price is adopted on the load side, a price conversion method for converting the actual load nodes into virtual load center nodes is proposed. The virtual load center node is one or more virtual market connection points. The load-side market members declare on the virtual node, and the clearing price is made based on the nodal marginal price of the virtual node, which simplifies the business logic and is conducive to business prediction and the alleviation of local grid congestion by marketized loads.

[0023] 2. In view of the phenomenon that new energy is prone to power and energy curtailment, after renewable energy curtailment occurs in the market, the curtailed units participate in the secondary clearing of the market according to the corrected curtailment accommodation quotation, and the curtailment accommodation quotation is less than the market minimum price limit. After the secondary clearing, the power generation volume transferred by some conventional units obtains settlement compensation to achieve the guaranteed consumption of renewable energy, and an effective spot mechanism is proposed to solve the problem of guaranteed consumption of renewable energy. Specific implementation manner

[0024] The present invention will be described below. The specific implementation manners described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0025] The power carbon emission reduction amount optimization clearing method includes the steps of collecting the quotation data on both sides of the power generation load and then performing clearing using the full-time clearing model; the clearing includes conventional clearing and guaranteed consumption clearing; the conventional clearing is that conventional power sources and renewable energy are both added to the spot market, and the day-ahead market clearing result is obtained through the above full-time clearing model; the guaranteed consumption clearing is triggered after renewable energy curtailment occurs in the market, and the curtailed units participate in the secondary clearing of the market according to the corrected curtailment accommodation quotation, the curtailment accommodation quotation is less than the market minimum price limit, and after the secondary clearing, the power generation volume transferred by some conventional units obtains settlement compensation.

[0026] Among them, the establishment of the full-time clearing model and the process of calculating the electricity price based on this model include:

[0027] 1) Establish an objective function and perform clearing with the maximization of social welfare as the optimization goal:

[0028]

[0029] In the formula, T represents the total number of time periods; L and G respectively represent the total number of load users and the total number of generating units; q load (l,t), q gen (g,t) respectively represent the cleared electricity volume of load l and generating unit g in time period t; B and C respectively represent the electricity consumption income and the power generation cost; C start is the total start-up cost of all units within the specified time period;

[0030] 2) System operation constraints, including system supply-demand balance constraints, line transmission capacity constraints, generator capacity constraints, load electricity consumption capacity constraints, generator ramp-up and ramp-down constraints, virtual bidding ratio constraints, and generator start-stop constraints;

[0031] 3) Electricity price calculation, including nodal marginal price and unified load-side price;

[0032] Among them, the nodal marginal price is:

[0033]

[0034] In the formula, D is the nodal load; λ is the shadow price of the system balance constraint; η is the shadow price of the line power flow constraint; is the power flow transfer factor of the node to the transmission line, representing the power flow of the net load on node n distributed on line c;

[0035] The unified load-side price is to correct the power flow transfer factor of each node to the transmission line in the following way:

[0036]

[0037] In the formula: ω represents the weight in the correction process; F 0 (n, c) represents the original power flow transfer factor calculated from the topological relationship of the line itself; F 1 (n, c) represents the corrected power flow transfer factor; N is the number of nodes.

[0038] More specifically, the system supply-demand balance constraint is:

[0039]

[0040] In the formula: λ(t) represents the shadow price of the system supply-demand balance.

[0041] The line transmission capacity constraint is:

[0042]

[0043] η (t): q qine (c) ≥ -Q line (c),

[0044] In the formula: q line (c) represents the power flow on line c; Q line (c) represents the maximum positive power flow that line c can withstand; η(t) represents the shadow price of the line transmission capacity constraint at time period t; η (t) represent the positive power flow and the reverse power flow respectively.

[0045] The power generation capacity constraint of the unit is as follows:

[0046]

[0047] ε (t):q gen (, g, t) ≥ Q gen (g),

[0048] In the formula: Qgen (g) represent the upper limit and lower limit of the output of generator set g respectively; ε (t) represent the shadow prices of the upper limit and lower limit of the unit's power generation capacity constraint respectively.

[0049] The electricity consumption capacity constraint of the load is as follows:

[0050] ζ(t):q load (1, t) ≤ Q load (l),

[0051] In the formula: Q load (l) represents the maximum value of the declared electricity quantity of load l, which can be regarded as the actual electricity consumption capacity of the load; ζ(t) represents the shadow price of the load's electricity consumption capacity constraint.

[0052] The ramp-up and ramp-down constraints of the unit are as follows:

[0053]

[0054] σ (t):q gen (g, t) - q gen (g, t - 1) ≥ -Δ(g),

[0055] In the formula: Δ(g) represents the fastest adjustment power level of generator set g; represents the ramp-up shadow price of the unit's adjustment power constraint; σ (t) represents the ramp-down shadow price of the unit's adjustment power constraint.

[0056] The virtual bidding ratio constraint is as follows:

[0057] Q v (t) ≤ Q r (t) × θ,

[0058] In the formula: Q v (t) represents the virtual bidding electricity quantity in time period t when the market member participates in the day-ahead market bidding; Q r (t) represents the actual load demand or power generation capacity in time period t; θ is the preset maximum ratio.

[0059] The start-stop constraints of the unit are as follows:

[0060]

[0061] In the formula: M 1 (t) represents the start-up instruction of the unit at time period t; M 0 (t) represents the shutdown instruction of the unit at time period t, and both are 0 / 1 values; the constraint is defined as that once the unit has a start-up signal, it cannot be shut down within the specified n time periods.

[0062] More specifically, during the second clearing, the power generation side conducts secondary settlement correspondingly, and the process is as follows:

[0063]

[0064] In the formula: is the total revenue of unit i with reduced output during the second clearing at time period t; is the total revenue of unit i with increased output during the second clearing at time period t; and are the long-term time-sharing net contract power and the winning bid power in the first clearing of unit i at time period t respectively; and are the reduced power generation and increased power generation of unit i during the second clearing at time period t respectively; L 1,i,t and L 2,i,t are the nodal electricity prices of unit i at time period t in the first clearing and the second clearing respectively.

[0065] It should be noted that the present invention is not limited to the above embodiments. According to the creative spirit of the present invention, those skilled in the art can also make other changes, and these changes made based on the creative spirit of the present invention should be included within the scope of protection required by the present invention.

Claims

1. A method for optimizing the clearing of power carbon reduction Characterized in that The steps of this method include collecting the quotation data on both sides of the power generation load and then performing clearing using the full-time clearing model; the clearing includes regular clearing and guaranteed consumption clearing; the regular clearing is that both conventional power sources and renewable energy are added to the spot market, and the day-ahead market clearing result is obtained through the above full-time clearing model; the guaranteed consumption clearing is triggered after renewable energy curtailment occurs in the market, and the curtailed units participate in the secondary clearing of the market according to the corrected curtailment consumption quotation, and the curtailment consumption quotation is less than the market minimum price limit, and the power generation volume transferred by some conventional units after the secondary clearing obtains settlement compensation; Among them, the establishment of the full-time clearing model and the process of calculating the electricity price based on this model include: 1) Establish an objective function, and perform clearing with the maximization of social welfare as the optimization goal: Wherein, T represents the total number of time periods; L and G respectively represent the total number of load users and the total number of generating units; q load (l, t), q gen (g, t) respectively represent the electricity cleared by load l and generating unit g in time period t; B and C respectively represent the electricity consumption revenue and the power generation cost; C start is the total start-up cost of all units within the specified time period; 2) System operation constraints, including system supply-demand balance constraints, line transmission capacity constraints, unit power generation capacity constraints, load power consumption capacity constraints, unit ramp-up and ramp-down constraints, virtual bidding ratio constraints, and unit start-stop constraints; 3) Electricity price calculation, including nodal marginal price and unified load-side price; Among them, the nodal marginal price is: where D is the node load; λ is the shadow price of the system balance constraint; η is the shadow price of the line power flow constraint; is the power flow transfer factor of the node to the transmission line, indicating the power flow distributed by the net load on node n on line c; The unified load-side price corrects the power flow transfer factor of each node to the transmission line in the following way: Where: ω represents the weight in the correction process; F 0 (n, c) represents the original power flow transfer factor calculated from the topological relationship of the line itself; F 1 (n, c) represents the corrected power flow transfer factor; N is the number of nodes; Among them, during the secondary clearing, the power generation side corresponds to secondary settlement, specifically: In the formula: is the total revenue of unit i with reduced output during the second clearing in period t; is the total revenue of unit i with increased output during the second clearing in period t; and are the long-term time-sharing net contract electricity quantity and the winning bid electricity quantity of unit i in period t during the first clearing respectively; and are the reduced power generation and increased power generation of unit i in period t during the second clearing respectively; L 1,i,t and L 2,i,t are the nodal electricity prices of unit i in period t during the first clearing and the second clearing respectively.

2. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The system supply-demand balance constraint is: In the formula: λ(t) represents the shadow price of system supply-demand balance.

3. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The line transmission capacity constraint is: where: q line (c) represents the power flow on line c; Q line (c) represents the maximum positive power flow that line c can withstand; η(t) represents the shadow price of the line transmission capacity constraint in time period t; η(t) represents the positive power flow and the reverse power flow respectively.

4. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The unit power generation capacity constraint is: Where: Q gen (g) represent the upper and lower limits of the output of generator set g respectively; ε(t) represent the shadow prices of the upper and lower limits of the generator capacity constraint respectively.

5. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The load power consumption capacity constraint is: ζ(t): q load (l, t) ≤ Q load (l), Where: Q load (l) represents the maximum value of the declared electricity consumption of load l, which can be regarded as the actual electricity consumption capacity of the load; ζ(t) represents the shadow price of the load electricity consumption capacity constraint.

6. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The unit ramp-up and ramp-down constraint is: Where: Δ(g) represents the fastest adjustment power level of unit g; represents the ramp shadow price of the unit's adjustment power constraint; σ (t) represents the landslide shadow price of the unit's adjustment power constraint.

7. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The virtual bidding ratio constraint is: Q v ψ(t) ≤ Q r ψ(t) × θ, Where: Q v (t) represents the virtual bidding electricity quantity of period t when market members participate in the day-ahead market bidding; Q r (t) represents the actual load demand or generation capacity in period t; θ is the preset maximum ratio.

8. The method for optimizing the clearing of power carbon reduction according to claim 1 Characterized in that The unit start-stop constraint is: Where: M 1 (t) represents the start-up command of the unit in time period t; M 0 (t) represents the shutdown command of the unit in time period t, and both are 0 / 1 values; the constraint is defined as that once the unit has a start-up signal, it cannot be shut down within the specified n time periods.

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