A power system ramping demand assessment and optimization method considering load-side resources

Abstract

The present invention discloses a method for evaluating and optimizing the ramping demand of a power system that takes load-side resources into consideration. The method includes: in order to effectively address the volatility and uncertainty of loads or new energy sources, a method for calculating the maximum upward and downward ramping demands in different time periods is proposed, including methods for calculating deterministic and uncertain ramping demands; a ramping demand optimization model is proposed that takes minimizing the uncertain ramping demand as the objective function and takes into account constraints such as load regulation and demand response; a ramping capability optimization model is proposed that takes minimizing the comprehensive consumables of the power system as the optimization goal and takes into account constraints such as node balance and line flow; a model is built on the AMPL software and the solver GUROBI is called for solution to obtain a ramping demand evaluation and optimization scheme for the power system. The present invention can effectively reduce the comprehensive operating consumables of the power system, achieve the effect of peak shaving and valley filling of the net load of the power system, thereby improving the operational reliability of the power system and alleviating the dispatching pressure of the power system.

Description

Technical Field

[0001] The present invention relates to the field of power system ramp analysis, and in particular to a power system ramp demand evaluation and optimization method considering load-side resources. Background Art

[0002] With the integration of a high proportion of renewable energy into the power system, the safe and stable operation of the power system faces unprecedented challenges. The volatility and randomness of renewable energy unit output have significantly increased the peak-shaving demand of the power system. However, as the proportion of power generation from traditional thermal power units gradually decreases, the power system's peak-shaving capacity is limited, making it difficult to cope with rapidly changing load demand and the uncertainty of renewable energy unit output. This not only reduces the economic and reliability of the power system but also may cause stability issues. Therefore, further exploration is needed to consider the impact of user-side demand response on ramping demand in power system ramping demand assessment and ramping capacity optimization, and to consider the uncertainty of ramping demand in power system optimization models. Summary of the Invention

[0003] In order to overcome the deficiencies in the above-mentioned prior art, the present invention provides a method for evaluating and optimizing the ramping demand of a power system taking into account load-side resources, so as to effectively cope with the impact of the intermittency and volatility brought about by a high proportion of renewable energy power generation on the operation of the power system, enhance the flexibility and regulation capability of the power system, and thus achieve more stable and safe power system operation.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] The method for evaluating and optimizing the ramping demand of a power system considering load-side resources of the present invention is characterized by being performed in the following steps:

[0006] Step 1: Use formula (1) to calculate the net load of the power system in period t :

[0007] (1)

[0008] In formula (1), is the total load demand of the power system in period t; is the new energy power of the power system in period t; is the external power tie line power of the power system in period t; is the unregulated power output of the power system during period t;

[0009] Step 2: Use equations (2) to (4) to calculate the deterministic ramp demand of the power system in period t and the demand for climbing under certainty :

[0010] (2)

[0011] (3)

[0012] (4)

[0013] In formula (2)-formula (4): is the net load change of the power system in period t; and are the deterministic up-ramp demand and the deterministic down-ramp demand of the power system in period t, respectively; Set for time period;

[0014] Step 3: Calculate the uncertainty ramp demand of the power system in period t and climbing demand under uncertainty ;

[0015] Step 4: Uncertainty-based ramp-up requirements during period t and climbing demand under uncertainty , establish a ramping demand optimization model considering load-side resources;

[0016] Step 5: Based on the ramping requirements, establish a ramping capability optimization model for the power system;

[0017] Step 6. Use the commercial solver GUROBI to solve the ramping demand optimization model considering load-side resources and the power system's ramping capacity optimization model, and accordingly obtain the uncertain ramping demand and the comprehensive consumables of the power system, including: uncertain up-ramp demand and uncertain down-ramp demand, comprehensive consumables of the power system, power generation consumables of thermal power units, start-up and shutdown consumables of thermal power units, CO2 capture solution loss, and carbon trading consumables.

[0018] The method for evaluating and optimizing the ramping demand of a power system considering load-side resources according to the present invention is also characterized in that step 3 is performed as follows:

[0019] Step 3.1: Use formula (5) to calculate the uncertainty ramp demand of the power system in period t :

[0020] (5)

[0021] In formula (5): is the upper limit of the load forecast error of the power system in period t; is the lower limit of the forecast error of renewable energy output of the power system in period t;

[0022] Step 3.2: Use Equation (6) to calculate the ramp demand of the power system under uncertainty in period t :

[0023] (6)

[0024] In formula (6): is the lower limit of the load forecast error of the power system in period t; is the upper limit of the forecast error of renewable energy output of the power system in period t;

[0025] Furthermore, step 4 is performed as follows:

[0026] Step 4.1: Use formula (7) to establish the objective function of the ramp demand optimization model:

[0027] (7)

[0028] Step 4.2: Use formula (8) to establish the load regulation constraint of the ramp demand optimization model:

[0029] (8)

[0030] In formula (8): is the power change of the power system in time period t;

[0031] Step 4.3: Use equations (9) and (10) to establish the demand response constraints of the ramping demand optimization model:

[0032] (9)

[0033] (10)

[0034] In formula (9)-formula (10): is the demand elasticity coefficient between period t and period τ; is the total load demand forecast value of the power system in period t; The electricity price for the period τ before the user participates in demand response; is the electricity price in period t before the user participates in demand response; The change in electricity price during the τ period after the user participates in demand response; and are the minimum and maximum electricity prices in period t after the user participates in demand response;

[0035] Step 4.4: Use equations (11) and (12) to establish the constraints of electricity consumption mode satisfaction and electricity cost satisfaction:

[0036] (11)

[0037] (12)

[0038] In formula (11)-formula (12): and are the minimum values ​​of satisfaction with electricity usage methods and the minimum values ​​of satisfaction with electricity costs, respectively;

[0039] Further, the step 5 is performed as follows:

[0040] Step 5.1: Use equations (13) to (17) to establish the objective function of the gradeability optimization model:

[0041] (13)

[0042] (14)

[0043] (15)

[0044] (16)

[0045] (17)

[0046] In formulas (13) to (17): G i represents the set of generators connected to node i; N represents the set of all nodes in the power system; C i represents the set of carbon capture units connected to node i; F is the comprehensive consumables of the power system; F P It is the power generation consumable material of thermal power unit; F O It is the starting and stopping consumables of thermal power units; V is the loss of CO2 capture solution; F Y Consumables for carbon trading; a g 、b g 、c g Represents the three power consumption coefficients of generator group g in period t; It represents the active power output by generator group g during period t; Indicates the start and stop status of the generator set g during the t period. If the generator set g is in the start state during the t period, then =1, otherwise, let =0;S g It is the starting and stopping consumables of the generator set g; is the consumable coefficient of ethanolamine solution; is the loss coefficient for ethanolamine solution operation; is the net CO2 capture amount of carbon capture unit c during period t; is the consumables for carbon trading during period t; is the intensity coefficient of carbon emissions; is the quota coefficient for carbon trading; is the total CO2 captured by carbon capture unit c during period t;

[0047] Step 5.2: Use (18)-(19) to establish the node balance constraints of the climbing ability optimization model:

[0048] (18)

[0049] (19)

[0050] In formula (18) and formula (19): W i represents the set of new energy units connected to node i; Represents a collection of lines; is the net output of the carbon capture unit c during period t; It represents the predicted active power value of the new energy unit w in period t; represents the actual active power flow value of line ij between node i and node j in period t; represents the active power of the load at node i in period t; and are the charging and discharging powers of the energy storage at node i during period t; It represents the reactive power output by generator group g during period t; represents the reactive power flow of line ij in period t; represents the reactive power of the load at node i in period t;

[0051] Step 5.3: Use equations (20) to (23) to establish the line flow constraints of the ramping capability optimization model:

[0052] (20)

[0053] (twenty one)

[0054] (twenty two)

[0055] (twenty three)

[0056] In formula (20)-formula (23): and are the conductance and susceptance corresponding to the element in the i-th row and j-th column of the node admittance matrix respectively; is the auxiliary variable of node i in period t, and = ; is the first auxiliary variable of line ij in period t, and ; is the second auxiliary variable of line ij in period t, and ; is the shunt susceptance of line ij; represents the maximum apparent power of line ij; is the voltage of node i at time t; is the cosine value of the voltage phase angle difference between node i and node j during period t; is the sine value of the voltage phase angle difference between node i and node j during period t;

[0057] Step 5.4: Use equation (24) to establish the voltage constraint of the ramping capability optimization model:

[0058] (twenty four)

[0059] In formula (24): and are the minimum and maximum values ​​of the node voltage respectively;

[0060] Step 5.5: Use equations (25) to (30) to establish the climbing capability constraints of the thermal power unit in the climbing capability optimization model:

[0061] (25)

[0062] (26)

[0063] (27)

[0064] (28)

[0065] (29)

[0066] (30)

[0067] In formula (25)-formula (30): and are the upward climbing capability and downward climbing capability of generator set g during period t respectively; and are the upward climbing rate and downward climbing rate of generator set g in period t respectively; and are the maximum and minimum active output of generator set g respectively;

[0068] Step 5.6: Use equations (31) to (40) to establish the step-by-step ramp rate constraints of the thermal power unit in the ramp capability optimization model:

[0069] (31)

[0070] (32)

[0071] (33)

[0072] (34)

[0073] (35)

[0074] (36)

[0075] (37)

[0076] (38)

[0077] (39)

[0078] (40)

[0079] In formula (31)-formula (40): 、 、 、 The power range parameters of the four different peak-shaving states of the thermal power unit; 、 、 is the upward climbing rate of the thermal power unit under three different peak regulation states; 、 、 is the downward climbing rate of the thermal power unit under three different peak regulation states; 、 、 are the three Boolean variables introduced by linearization in formula (31); 、 、 are the three Boolean variables introduced by linearization in formula (32);

[0080] Step 5.7: Use formula (41) to establish the system backup constraint of the gradeability optimization model:

[0081] (41)

[0082] In formula (41): represents the reserve capacity required by the power system in period t;

[0083] Step 5.8: Use equation (42) to establish the thermal power unit output constraint of the ramping capability optimization model:

[0084] (42)

[0085] Step 5.9: Use equations (43) to (46) to establish the logical constraints of the gradeability optimization model:

[0086] (43)

[0087] (44)

[0088] (45)

[0089] (46)

[0090] In formula (43)-formula (46): Indicates whether the generator set g starts to start during the period t; Indicates whether the generator set g starts to start during the period t; The minimum continuous startup time of the thermal power unit; is the minimum downtime of the thermal power unit; T is the number of time periods in the scheduling cycle; Indicates the duration of startup or shutdown of thermal power units within the scheduling cycle; Indicates that the generator set g is The start and stop status of the period, if the generator set g is If the time period is in the power-on state, =1, otherwise, let =0; Indicates the start and stop status of generator set g during the t-1 period. If generator set g is in the start state during the t-1 period, then =1, otherwise, let =0;

[0091] Step 5.9: Use equations (47) to (55) to establish the carbon capture unit constraints for the ramping capability optimization model:

[0092] (47)

[0093] (48)

[0094] (49)

[0095] (50)

[0096] (51)

[0097] (52)

[0098] (53)

[0099] (54)

[0100] (55)

[0101] In formula (47)-formula (55): is the power output of carbon capture unit c during period t; is the carbon capture energy consumption of carbon capture unit c during period t; and are the upper and lower limits of the output power of the conventional thermal power part of the carbon capture unit c; λ is the energy consumed per unit CO2 of carbon capture; is the carbon emission intensity of the carbon capture unit c; η is the carbon capture efficiency; is the maximum flue gas split ratio of the carbon capture unit c during period t; is the fixed energy consumption of the carbon capture unit c; is the operating energy consumption of carbon capture unit c during period t; The amount of CO2 provided by the storage tank during period t; is the diversion ratio of the carbon capture power plant in period t; The volume of solution required to provide carbon dioxide to the storage tank during time t; and are the molar masses of ethanolamine solution and carbon dioxide, respectively; is the analysis amount of the regeneration tower; is the concentration of ethanolamine solution; is the density of ethanolamine solution.

[0102] The electronic device of the present invention includes a memory and a processor, and is characterized in that the memory is used to store a program that supports the processor to execute the power system ramp demand assessment and optimization method, and the processor is configured to execute the program stored in the memory.

[0103] The present invention provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and the computer program executes the steps of the power system ramp demand assessment and optimization method when the computer program is executed by a processor.

[0104] Compared with the prior art, the beneficial effects of the present invention are embodied in:

[0105] 1. The present invention proposes a power system ramping demand assessment and optimization model that takes load-side resources into consideration. The ramping demand optimization model aims to minimize uncertain ramping demand and rationally regulates factors such as load regulation and demand response. This overcomes the problem of insufficient flexibility caused by relying solely on ramping regulation of traditional thermal power units in the existing technology. By optimizing the participation of load-side resources and reducing ramping demand, the flexibility of the power system is significantly improved, the participation of renewable energy in the power system is increased, the net load of the power system is reduced in peak and valley, and the peak-shaving pressure of the power system is effectively alleviated.

[0106] 2. The present invention proposes a climbing capacity optimization model that takes minimizing the comprehensive consumables of the power system as the optimization goal and considers constraints such as node balance and line flow. It optimizes the output distribution of thermal power units and renewable energy units, effectively reduces the operating time of thermal power units, thereby reducing the comprehensive consumables cost of the power system and improving the operating efficiency and safety of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0107] Figure 1 is a flow chart of the method of the present invention;

[0108] Figure 2 This is a schematic diagram of the climbing requirements of the method of the present invention. DETAILED DESCRIPTION

[0109] In this embodiment, in order to effectively deal with the volatility and uncertainty of loads or new energy, a method for evaluating and optimizing the ramping demand of a power system considering load-side resources is proposed. The method is to reduce the ramping demand of the power system by optimizing the participation of load-side resources to alleviate the peak-shaving pressure of traditional thermal power units, including: 1. A calculation method for determining the maximum upward and downward ramping demands in different time periods is proposed, including an evaluation and calculation method for deterministic ramping demands and uncertain ramping demands; 2. Taking minimizing the uncertain ramping demand as the objective function, and considering constraints such as load regulation, user-side demand response, satisfaction with electricity usage methods, and satisfaction with electricity costs, a ramping demand optimization model considering load-side resources is established; 3. Taking minimizing the comprehensive consumables of the power system as the optimization goal, considering constraints such as node balance, line flow, thermal power unit climbing capacity, step-by-step climbing rate calculation, and carbon capture units, a power system climbing capacity optimization model is established to optimize the unit output so that the climbing capacity meets the climbing demand and reduces system operation consumables. Specifically, if Figure 1 As shown, the steps are as follows:

[0110] Step 1: Use formula (1) to calculate the net load of the power system in period t :

[0111] (1)

[0112] In formula (1), is the total load demand of the power system in period t; is the new energy power of the power system in period t; is the external power tie line power of the power system in period t; is the unregulated power output of the power system during period t;

[0113] Step 2: The ramp demand of the power system mainly includes the up-ramp demand and the down-ramp demand. Figure 2 In the above equation, the net load change refers to the difference in net loads in different time periods. When the prediction error is taken into account, both the upward and downward ramping demands are greater than the net load change. In the actual operation of the power system, in order to effectively deal with the volatility and uncertainty of load or new energy, it is necessary to determine the maximum upward and downward ramping demands in different time periods, such as Figure 2 As shown in the shadow.

[0114] Calculate the deterministic ramp demand of the power system in period t using equations (2) to (4): and the demand for climbing under certainty :

[0115] (2)

[0116] (3)

[0117] (4)

[0118] Formula (2) represents the calculation method of the net load change; Formula (3) represents the calculation method of the deterministic up-ramp demand; Formula (4) represents the calculation method of the deterministic down-ramp demand;

[0119] In formula (2)-formula (4): is the net load change of the power system in period t; and are the deterministic up-ramp demand and the deterministic down-ramp demand of the power system in period t, respectively; For the time range considered, in the embodiment, the time range is taken as 24 hours a day.

[0120] Step 3: Calculate the uncertainty ramp demand of the power system in period t and climbing demand under uncertainty :

[0121] Step 3.1: Use formula (5) to calculate the uncertainty ramp demand of the power system in period t :

[0122] (5)

[0123] In formula (5): is the upper limit of the load forecast error of the power system in period t; is the lower limit of the forecast error of renewable energy output of the power system in period t;

[0124] Step 3.2: Use Equation (6) to calculate the ramp demand of the power system under uncertainty in period t :

[0125] (6)

[0126] In formula (6): is the lower limit of the load forecast error of the power system in period t; is the upper limit of the forecast error of renewable energy output of the power system in period t.

[0127] Step 4: Establish a ramping demand optimization model that considers load-side resources:

[0128] Step 4.1: Use formula (7) to establish the objective function of the ramp demand optimization model:

[0129] (7)

[0130] Step 4.2: Use formula (8) to establish the load regulation constraint of the ramp demand optimization model:

[0131] (8)

[0132] Formula (8) indicates that in one scheduling cycle, the sum of the load changes is 0, that is, the total load remains unchanged;

[0133] In formula (8): is the power change of the power system in time period t;

[0134] Step 4.3: Use equations (9) and (10) to establish the demand response constraints of the ramping demand optimization model:

[0135] (9)

[0136] (10)

[0137] (9)-In formula (10): is the demand elasticity coefficient between period t and period τ; is the total load demand forecast value of the power system in period t; The electricity price for the period τ before the user participates in demand response; The change in electricity price during the τ period after the user participates in demand response; and are the minimum and maximum electricity prices in period t after the user participates in demand response.

[0138] Step 4.4: Use equations (11) and (12) to establish the constraints of electricity consumption mode satisfaction and electricity cost satisfaction:

[0139] (11)

[0140] (12)

[0141] Formula (11) is the electricity consumption mode satisfaction constraint; Formula (12) is the electricity cost satisfaction index constraint;

[0142] In formula (11)-formula (12): and are the minimum values ​​of satisfaction with electricity usage mode and electricity cost respectively.

[0143] Step 5: Establish a ramping capability optimization model for the power system:

[0144] Step 5.1: Use equations (13) to (17) to establish the objective function of the gradeability optimization model:

[0145] (13)

[0146] (14)

[0147] (15)

[0148] (16)

[0149] (17)

[0150] In formulas (13) to (17): G i represents the set of generators connected to node i; N represents the set of all nodes in the power system; C i represents the set of carbon capture units connected to node i; F is the comprehensive consumables of the power system; F P It is the power generation consumable material of thermal power unit; F O It is the starting and stopping consumables of thermal power units; V is the loss of CO2 capture solution; F Y Consumables for carbon trading; a g 、b g 、c g Represents the three power consumption coefficients of generator group g in period t; It represents the active power output by generator group g during period t; Indicates the start and stop status of the generator set g during the t period. If the generator set g is in the start state during the t period, then =1, otherwise, let =0;S g It is the starting and stopping consumables of the generator set g; is the consumable coefficient of ethanolamine solution; is the loss coefficient for ethanolamine solution operation; is the net CO2 capture amount of carbon capture unit c during period t; is the consumables for carbon trading during period t; is the intensity coefficient of carbon emissions; is the quota coefficient for carbon trading; is the total CO2 captured by carbon capture unit c during period t;

[0151] Step 5.2: Use (18)-(19) to establish the node active and reactive balance constraints of the ramping capability optimization model:

[0152] (18)

[0153] (19)

[0154] In formula (18) and formula (19): W i represents the set of new energy units connected to node i; Represents a collection of lines; is the net output of the carbon capture unit c during period t; It represents the predicted active power value of the new energy unit w in period t; represents the actual active power flow value of line ij between node i and node j in period t; represents the active power of the load at node i in period t; and are the charging and discharging powers of the energy storage at node i during period t; It represents the reactive power output by generator group g during period t; represents the reactive power flow of line ij in period t; represents the reactive power of the load at node i in period t;

[0155] Step 5.3: Use equations (20) to (23) to establish the line flow constraints of the ramping capability optimization model:

[0156] (20)

[0157] (twenty one)

[0158] (twenty two)

[0159] (twenty three)

[0160] Formulas (20) and (21) are the calculation formulas for line power flow; Formula (22) represents the second-order cone relaxation constraint related to the auxiliary variable, and Formula (23) indicates that the line power flow is within the threshold range;

[0161] In formula (20)-formula (23): and are the conductance and susceptance corresponding to the element in the i-th row and j-th column of the node admittance matrix respectively; is the auxiliary variable of node i in period t, and = ; is the first auxiliary variable of line ij in period t, and ; is the second auxiliary variable of line ij in period t, and ; is the shunt susceptance of line ij; represents the maximum apparent power of line ij; is the voltage of node i at time t; is the cosine value of the voltage phase angle difference between node i and node j during period t; is the sine value of the voltage phase angle difference between node i and node j during period t;

[0162] Step 5.4: Use equation (24) to establish the voltage constraint of the ramping capability optimization model:

[0163] (twenty four)

[0164] Equation (24) indicates that the node voltage is within the threshold range;

[0165] In formula (24): and are the minimum and maximum node voltages, respectively;

[0166] Step 5.5: Use equations (25) to (30) to establish the climbing capability constraints of the thermal power unit in the climbing capability optimization model:

[0167] (25)

[0168] (26)

[0169] (27)

[0170] (28)

[0171] (29)

[0172] (30)

[0173] Formula (25) indicates that the upward climbing capacity provided by all units is not less than the uncertain upward climbing demand of the system; Formula (26) indicates that the downward climbing capacity of all units is not less than the uncertain downward climbing demand of the system; Formula (27) indicates that the upward climbing capacity of the unit is not greater than the upward climbing rate of the unit; Formula (28) indicates that the downward climbing capacity of the unit is not greater than the downward climbing rate of the unit; Formula (29) indicates that the upward climbing capacity of the unit is not greater than the difference between the maximum output and the current output of the unit; Formula (30) indicates that the downward climbing capacity of the unit is not greater than the difference between the current output and the minimum output of the unit;

[0174] In formula (25)-formula (30): and are the upward climbing capability and downward climbing capability of generator set g during period t respectively; and are the upward climbing rate and downward climbing rate of generator set g in period t respectively; and are the maximum and minimum active output of generator set g respectively;

[0175] Step 5.6: Use equations (31) to (40) to establish the step-by-step ramp rate constraints of the thermal power unit in the ramp capability optimization model:

[0176] (31)

[0177] (32)

[0178] (33)

[0179] (34)

[0180] (35)

[0181] (36)

[0182] (37)

[0183] (38)

[0184] (39)

[0185] (40)

[0186] Equations (31) and (32) are both conditional constraints. In order to improve the efficiency of the model solution, they can be linearized, as shown in Equations (33)-(36) and (37)-(40), respectively.

[0187] In formula (31)-formula (40): 、 、 、 The power range parameters of the four different peak-shaving states of the thermal power unit; 、 、 is the upward climbing rate of the thermal power unit under three different peak regulation states; 、 、 is the downward climbing rate of the thermal power unit under three different peak regulation states; 、 、 are the three Boolean variables introduced by linearization in formula (31); 、 、 are the three Boolean variables introduced by linearization in formula (32);

[0188] Step 5.7: Use formula (41) to establish the system backup constraint of the gradeability optimization model:

[0189] (41)

[0190] Formula (41) indicates that the sum of the maximum outputs of the operating units is not less than the sum of the total load demand and the reserve capacity;

[0191] In formula (41): represents the reserve capacity required by the power system in period t;

[0192] Step 5.8: Use equation (42) to establish the thermal power unit output constraint of the ramping capability optimization model:

[0193] (42)

[0194] Formula (42) indicates that the output of the generator set should not be less than its minimum output and not greater than its maximum output;

[0195] Step 5.9: Use equations (43) to (46) to establish the logical constraints of the gradeability optimization model:

[0196] (43)

[0197] (44)

[0198] (45)

[0199] (46)

[0200] Formula (43) represents the logical relationship between the three Boolean variables; Formula (44) indicates that the sum of the Boolean variables for the generator set to start and the Boolean variables for the generator set to start is not greater than 1; Formula (45) and Formula (46) respectively represent the minimum continuous start-up time constraint and the minimum shutdown time constraint of the generator set;

[0201] In formula (43)-formula (46): Indicates whether the generator set g starts to start during the period t; Indicates whether the generator set g starts to start during the period t; The minimum continuous startup time of the thermal power unit; is the minimum downtime of the thermal power unit; T is the number of time periods in the scheduling cycle; Indicates the duration of startup or shutdown of thermal power units within the scheduling cycle; Indicates that the generator set g is The start and stop status of the period, if the generator set g is If the time period is in the power-on state, =1, otherwise, let =0; Indicates the start and stop status of generator set g during the t-1 period. If generator set g is in the start state during the t-1 period, then =1, otherwise, let =0;

[0202] Step 5.9: Use equations (47) to (55) to establish the carbon capture unit constraints for the ramping capability optimization model:

[0203] (47)

[0204] (48)

[0205] (49)

[0206] (50)

[0207] (51)

[0208] (52)

[0209] (53)

[0210] (54)

[0211] (55)

[0212] Equations (48) and (49) indicate that the carbon capture unit under the comprehensive flexible operation mode reduces the net output of the power plant by increasing the amount of carbon dioxide captured during the low load period, and has a wider adjustment range than conventional thermal power units; Equations (50) and (55) represent the capture energy consumption of the carbon capture unit;

[0213] In formula (47)-formula (55): is the power output of carbon capture unit c during period t; is the carbon capture energy consumption of carbon capture unit c during period t; and are the upper and lower limits of the output power of the conventional thermal power part of the carbon capture unit c; λ is the energy consumed per unit CO2 of carbon capture; is the carbon emission intensity of the carbon capture unit c; η is the carbon capture efficiency; is the maximum flue gas split ratio of the carbon capture unit c during period t; is the fixed energy consumption of the carbon capture unit c; is the operating energy consumption of carbon capture unit c during period t; The amount of CO2 provided by the storage tank during period t; is the diversion ratio of the carbon capture power plant in period t; The volume of solution required to provide carbon dioxide to the storage tank during time t; and are the molar masses of ethanolamine solution and carbon dioxide, respectively; is the analysis amount of the regeneration tower; is the concentration of ethanolamine solution; is the density of ethanolamine solution.

[0214] Step 6. Use the commercial solver GUROBI to solve the ramping demand optimization model considering load-side resources and the power system's ramping capacity optimization model to obtain the uncertain ramping demand and the comprehensive consumables of the power system, including: uncertain up-ramp demand and uncertain down-ramp demand, comprehensive consumables of the power system, power generation consumables of thermal power units, start-up and shutdown consumables of thermal power units, CO2 capture solution loss, and carbon trading consumables.

[0215] In this embodiment, an electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0216] In this embodiment, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are executed.

Claims

1. A method for evaluating and optimizing power system ramping demand considering load-side resources, characterized in that: Proceed as follows: Step 1: Use formula (1) to calculate the net load of the power system in period t : (1) In formula (1), is the total load demand of the power system in period t; is the new energy power of the power system in period t; is the external power tie line power of the power system in period t; is the unregulated power output of the power system during period t; Step 2: Use equations (2) to (4) to calculate the deterministic ramp demand of the power system in period t and the demand for climbing under certainty : (2) (3) (4) In formula (2)-formula (4): is the net load change of the power system in period t; and are the deterministic up-ramp demand and the deterministic down-ramp demand of the power system in period t, respectively; Set for time period; Step 3: Calculate the uncertainty ramp demand of the power system in period t and climbing demand under uncertainty ; Step 3.1: Use formula (5) to calculate the uncertainty ramp demand of the power system in period t : (5) In formula (5): is the upper limit of the load forecast error of the power system in period t; is the lower limit of the forecast error of renewable energy output of the power system in period t; Step 3.2: Use Equation (6) to calculate the ramp demand of the power system under uncertainty in period t : (6) In formula (6): is the lower limit of the load forecast error of the power system in period t; is the upper limit of the forecast error of renewable energy output of the power system in period t; Step 4: Uncertainty-based ramp-up requirements during period t and climbing demand under uncertainty , establish a ramping demand optimization model considering load-side resources; Step 5: Based on the ramping requirements, establish a ramping capability optimization model for the power system; Step 6. Use the commercial solver GUROBI to solve the ramping demand optimization model considering load-side resources and the power system's ramping capacity optimization model, and accordingly obtain the uncertain ramping demand and the comprehensive consumables of the power system, including: uncertain up-ramp demand and uncertain down-ramp demand, comprehensive consumables of the power system, power generation consumables of thermal power units, start-up and shutdown consumables of thermal power units, CO2 capture solution loss, and carbon trading consumables.

2. A method for evaluating and optimizing power system ramping demand considering load-side resources according to claim 1, characterized in that: The fourth step is carried out as follows: Step 4.1: Use formula (7) to establish the objective function of the ramp demand optimization model: (7) Step 4.2: Use formula (8) to establish the load regulation constraint of the ramp demand optimization model: (8) In formula (8): is the power change of the power system in time period t; Step 4.3: Use equations (9) and (10) to establish the demand response constraints of the ramping demand optimization model: (9) (10) In formula (9)-formula (10): is the demand elasticity coefficient between period t and period τ; is the total load demand forecast value of the power system in period t; The electricity price for the period τ before the user participates in demand response; is the electricity price in period t before the user participates in demand response; The change in electricity price during the τ period after the user participates in demand response; and are the minimum and maximum electricity prices in period t after the user participates in demand response; Step 4.4: Use equations (11) and (12) to establish the constraints of electricity consumption mode satisfaction and electricity cost satisfaction: (11) (12) In formula (11)-formula (12): and They are the minimum values ​​of satisfaction with electricity usage methods and the minimum values ​​of satisfaction with electricity costs, respectively.

3. The method for evaluating and optimizing the ramping demand of a power system considering load-side resources according to claim 2, characterized in that: The step five is carried out as follows: Step 5.1: Use equations (13) to (17) to establish the objective function of the gradeability optimization model: (13) (14) (15) (16) (17) In formulas (13) to (17): G i represents the set of generators connected to node i; N represents the set of all nodes in the power system; C i represents the set of carbon capture units connected to node i; F is the comprehensive consumables of the power system; F P It is the power generation consumable material of thermal power unit; F O It is the starting and stopping consumables of thermal power units; V is the loss of CO2 capture solution; F Y Consumables for carbon trading; a g 、b g 、c g Represents the three power consumption coefficients of generator group g in period t; It represents the active power output by generator group g during period t; Indicates the start and stop status of the generator set g during the t period. If the generator set g is in the start state during the t period, then =1, otherwise, let =0;S g It is the starting and stopping consumables of the generator set g; is the consumable coefficient of ethanolamine solution; is the loss coefficient for ethanolamine solution operation; is the net CO2 capture amount of carbon capture unit c during period t; is the consumables for carbon trading during period t; is the intensity coefficient of carbon emissions; is the quota coefficient for carbon trading; is the total CO2 captured by carbon capture unit c during period t; Step 5.2: Use (18)-(19) to establish the node balance constraints of the climbing ability optimization model: (18) (19) In formula (18) and formula (19): W i represents the set of new energy units connected to node i; Represents a collection of lines; is the net output of the carbon capture unit c during period t; It represents the predicted active power value of the new energy unit w in period t; represents the actual active power flow value of line ij between node i and node j in period t; represents the active power of the load at node i in period t; and are the charging and discharging powers of the energy storage at node i during period t; It represents the reactive power output by generator group g during period t; represents the reactive power flow of line ij in period t; represents the reactive power of the load at node i in period t; Step 5.3: Use equations (20) to (23) to establish the line flow constraints of the ramping capability optimization model: (20) (21) (22) (23) In formula (20)-formula (23): and are the conductance and susceptance corresponding to the element in the i-th row and j-th column of the node admittance matrix respectively; is the auxiliary variable of node i in period t, and = ; is the first auxiliary variable of line ij in period t, and ; is the second auxiliary variable of line ij in period t, and ; is the shunt susceptance of line ij; represents the maximum apparent power of line ij; is the voltage of node i at time t; is the cosine value of the voltage phase angle difference between node i and node j during period t; is the sine value of the voltage phase angle difference between node i and node j during period t; Step 5.4: Use equation (24) to establish the voltage constraint of the ramping capability optimization model: (24) In formula (24): and are the minimum and maximum values ​​of the node voltage respectively; Step 5.5: Use equations (25) to (30) to establish the climbing capability constraints of the thermal power unit in the climbing capability optimization model: (25) (26) (27) (28) (29) (30) In formula (25)-formula (30): and are the upward climbing capability and downward climbing capability of generator set g during period t respectively; and are the upward climbing rate and downward climbing rate of generator set g in period t respectively; and are the maximum and minimum active output of generator set g respectively; Step 5.6: Use equations (31) to (40) to establish the step-by-step ramp rate constraints of the thermal power unit in the ramp capability optimization model: (31) (32) (33) (34) (35) (36) (37) (38) (39) (40) In formula (31)-formula (40): 、 、 、 The power range parameters of the four different peak-shaving states of the thermal power unit; 、 、 is the upward climbing rate of the thermal power unit under three different peak regulation states; 、 、 is the downward climbing rate of the thermal power unit under three different peak regulation states; 、 、 are the three Boolean variables introduced by linearization in formula (31); 、 、 are the three Boolean variables introduced by linearization in formula (32); Step 5.7: Use formula (41) to establish the system backup constraint of the gradeability optimization model: (41) In formula (41): represents the reserve capacity required by the power system in period t; Step 5.8: Use equation (42) to establish the thermal power unit output constraint of the ramping capability optimization model: (42) Step 5.9: Use equations (43) to (46) to establish the logical constraints of the gradeability optimization model: (43) (44) (45) (46) In formula (43)-formula (46): Indicates whether the generator set g starts to start during the period t; Indicates whether the generator set g starts to start during the period t; The minimum continuous startup time of the thermal power unit; is the minimum downtime of thermal power units; T is the number of time periods in the scheduling cycle; Indicates the duration of startup or shutdown of thermal power units within the scheduling cycle; Indicates that the generator set g is The start and stop status of the period, if the generator set g is If the time period is in the power-on state, =1, otherwise, let =0; Indicates the start and stop status of generator set g during the t-1 period. If generator set g is in the start state during the t-1 period, then =1, otherwise, let =0; Step 5.9: Use equations (47) to (55) to establish the carbon capture unit constraints for the ramping capability optimization model: (47) (48) (49) (50) (51) (52) (53) (54) (55) In formula (47)-formula (55): is the power output of carbon capture unit c during period t; is the carbon capture energy consumption of carbon capture unit c during period t; and are the upper and lower limits of the output power of the conventional thermal power part of the carbon capture unit c; λ is the energy consumed per unit CO2 of carbon capture; is the carbon emission intensity of the carbon capture unit c; η is the carbon capture efficiency; is the maximum flue gas split ratio of the carbon capture unit c during period t; is the fixed energy consumption of the carbon capture unit c; is the operating energy consumption of carbon capture unit c during period t; The amount of CO2 provided by the storage tank during period t; is the diversion ratio of the carbon capture power plant in period t; The volume of solution required to provide carbon dioxide to the storage tank during time t; and are the molar masses of ethanolamine solution and carbon dioxide, respectively; is the analysis amount of the regeneration tower; is the concentration of ethanolamine solution; is the density of ethanolamine solution.

4. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the power system ramp demand assessment and optimization method according to any one of claims 1 to 3, and the processor is configured to execute the program stored in the memory.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the power system ramp demand assessment and optimization method according to any one of claims 1 to 3 are executed.

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