Electric power system climbing demand evaluation and optimization method considering load side resources

Abstract

The invention discloses an electric power system climbing demand evaluation and optimization method considering load side resources, and the method comprises the steps: providing a calculation method for maximum upward and downward climbing demands in different time periods, including a calculation method for deterministic and uncertain climbing demands, in order to effectively cope with the fluctuation and uncertainty of loads or new energy; a climbing demand optimization model which takes minimization of the uncertainty climbing demand as an objective function and takes constraint conditions such as load adjusting quantity and demand response into consideration is provided; a gradeability optimization model which takes minimization of comprehensive consumables of the power system as an optimization target and considers constraints such as node balance and line power flow is provided; modeling is carried out on AMPL software, a solver GUROBI is called for solving, and an electric power system climbing demand evaluation and optimization scheme is obtained. The comprehensive operation consumables of the power system can be effectively reduced, and the net load peak load shifting effect on the power system is achieved, so that the operation reliability of the power system is improved, and the dispatching pressure of the power system is relieved.

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 a high proportion of new energy connected to the power system, the safe and stable operation of the power system faces unprecedented challenges. The volatility and randomness of the output of new energy units have significantly increased the peak-shaving demand of the power system. However, due to the gradual decrease in the proportion of power generation from traditional thermal power units, the peak-shaving capacity of the power system is limited, and it is difficult to cope with the rapidly changing load demand and the uncertainty of the output of new energy units. This not only reduces the economy and reliability of the power system, but may also cause stability problems in the power system. Therefore, the consideration of the impact of user-side demand response on the climbing demand in the evaluation of the power system climbing demand and the optimization of the climbing capacity and the consideration of the uncertainty of the climbing demand in the power system optimization model need to be further explored. Summary of the invention

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

[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 in that the method is performed according to 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 interconnection line power of the power system in period t; is the unadjustable power output of the power system in 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) to formula (4): is the net load change of the power system in period t; and They are the deterministic up-ramp demand and the deterministic down-ramp demand of the power system in period t respectively; is a collection of time periods;

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

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

[0016] Step 5: Based on the ramp demand, establish a ramp 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 ramping capacity optimization model of the power system, and obtain the uncertain ramping demand and the comprehensive consumables of the power system accordingly, including: uncertain up-climbing demand and uncertain down-climbing demand, comprehensive consumables of the power system, power generation consumables of thermal power units, start-up and shutdown consumables of thermal power units, loss of CO2 capture solution and consumables of carbon trading.

[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 equation (5) to calculate the uncertain ramp demand of the power system in period t: :

[0020] (5)

[0021] In formula (5): is the upper limit of 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 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] Further, 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 amount of the power system response in period t;

[0031] Step 4.3: Use equations (9) and (10) to establish the demand response constraints of the ramp 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; The electricity price for the 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 They are the minimum values ​​of satisfaction with electricity usage mode and the minimum values ​​of satisfaction with electricity cost respectively;

[0039] Further, 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 formula (13) to formula (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 consumables of thermal power units; 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; g , b g 、c g Represents the three power generation material consumption coefficients of the generator set g in period t; It represents the active power output by the generator set g during the 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 operation with ethanolamine solution; is the net CO2 capture amount of carbon capture unit c in period t; is the consumables of carbon trading during period t; is the intensity coefficient of carbon emissions; is the quota coefficient of carbon trading; is the total CO2 captured by the 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)-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 power of the energy storage at node i in period t, respectively; It represents the reactive power output by the generator set g during the 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 ramp capacity 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 difference between node i and node j in period t; is the sine value of the voltage phase angle difference between node i and node j in period t;

[0057] Step 5.4: Use equation (24) to establish the voltage constraint of the ramp 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 capacity constraints of the thermal power unit in the climbing capacity optimization model:

[0061] (25)

[0062] (26)

[0063] (27)

[0064] (28)

[0065] (29)

[0066] (30)

[0067] In formula (25) to formula (30): and are the upward climbing capacity and downward climbing capacity of the generator set g in period t respectively; and are the upward climbing rate and downward climbing rate of the 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) to formula (40): , , , It is the power range parameter of four different peak load regulation states of thermal power units; , , is the upward climbing rate of the thermal power unit under three different peak load conditions; , , is the downward climbing rate of the thermal power unit under three different peak load conditions; , , They are the three Boolean variables introduced by linearization in formula (31); , , They are the three Boolean variables introduced by linearization in equation (32);

[0080] Step 5.7: Use equation (41) to establish the system reserve constraint of the ramp capability optimization model:

[0081] (41)

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

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

[0084] (42)

[0085] Step 5.9: Use equations (43) to (46) to establish the logical constraints of the climbing ability 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 in period t; Indicates whether the generator set g starts to start in 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 time period, if the generator set g is If the time period is in the on state, =1, otherwise, let =0; represents the start and stop status of the generator set g in the t-1 period. If the generator set g is in the start state in 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 of 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 generation output of the 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, respectively; λ is the energy consumed by the carbon capture unit CO2; 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; is 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] An electronic device of the present invention includes a memory and a processor, wherein 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 as follows:

[0105] 1. The present invention proposes an evaluation and optimization model for the ramping demand of the power system considering the resources on the load side, wherein the ramping demand optimization model aims to minimize the uncertain ramping demand, reasonably regulates factors such as load regulation and demand response, and overcomes the problem of insufficient flexibility caused by the prior art that only relies on the ramping regulation of traditional thermal power units. By optimizing the participation of load-side resources and reducing the 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, 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, 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 reduces 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 climbing demands in different time periods is proposed, including an evaluation and calculation method for deterministic climbing demands and uncertain climbing demands; 2. Taking minimizing the uncertain climbing 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 climbing 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, climbing capacity of thermal power units, step-by-step climbing rate calculation, and carbon capture units, an optimization model for climbing capacity of the power system is established to optimize the unit output so that the climbing capacity meets the climbing demand and reduces system operating 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 interconnection line power of the power system in period t; is the unadjustable power output of the power system in 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 loads 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] 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 :

[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) to formula (4): is the net load change of the power system in period t; and They 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 uncertain ramp demand of the power system in period t and climbing requirements under uncertainty :

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

[0122] (5)

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

[0127] Step 4: Establish a ramp demand optimization model that takes into account 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 a 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 amount of the power system response in period t;

[0134] Step 4.3: Use equations (9) and (10) to establish the demand response constraints of the ramp 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 They are the minimum values ​​of satisfaction with electricity usage mode and satisfaction with 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 formula (13) to formula (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 consumables of thermal power units; 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; g , b g 、c g Represents the three power generation material consumption coefficients of the generator set g in period t; It represents the active power output by the generator set g during the 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 operation with ethanolamine solution; is the net CO2 capture amount of carbon capture unit c in period t; is the consumables of carbon trading during period t; is the intensity coefficient of carbon emissions; is the quota coefficient of carbon trading; is the total CO2 captured by the 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 ramp capability optimization model:

[0152] (18)

[0153] (19)

[0154] In formula (18)-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 power of the energy storage at node i in period t, respectively; It represents the reactive power output by the generator set g during the 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 ramp capacity optimization model:

[0156] (20)

[0157] (twenty one)

[0158] (twenty two)

[0159] (twenty three)

[0160] Formula (20) and Formula (21) are the calculation formulas for the line flow; Formula (22) represents the second-order cone relaxation constraint related to the auxiliary variable, and Formula (23) represents that the line 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 difference between node i and node j in period t; is the sine value of the voltage phase angle difference between node i and node j in period t;

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

[0163] (twenty four)

[0164] Formula (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 capacity constraints of the thermal power unit in the climbing capacity 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) to formula (30): and are the upward climbing capacity and downward climbing capacity of the generator set g in period t respectively; and are the upward climbing rate and downward climbing rate of the 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] Formula (31) and Formula (32) are both conditional constraints. In order to improve the solution efficiency of the model, they can be linearized, as shown in Formula (33)-Formula (36) and Formula (37)-Formula (40) respectively;

[0187] In formula (31) to formula (40): , , , It is the power range parameter of four different peak load regulation states of thermal power units; , , is the upward climbing rate of the thermal power unit under three different peak load conditions; , , is the downward climbing rate of the thermal power unit under three different peak load conditions; , , They are the three Boolean variables introduced by linearization in formula (31); , , They are the three Boolean variables introduced by linearization in equation (32);

[0188] Step 5.7: Use equation (41) to establish the system reserve constraint of the ramp capability 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 during period t;

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

[0196] (43)

[0197] (44)

[0198] (45)

[0199] (46)

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

[0201] In formula (43)-formula (46): Indicates whether the generator set g starts to start in period t; Indicates whether the generator set g starts to start in 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 time period, if the generator set g is If the time period is in the on state, =1, otherwise, let =0; represents the start and stop status of the generator set g in the t-1 period. If the generator set g is in the start state in 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 of the ramping capability optimization model:

[0203] (47)

[0204] (48)

[0205] (49)

[0206] (50)

[0207] (51)

[0208] (52)

[0209] (53)

[0210] (54)

[0211] (55)

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

[0213] In formula (47)-formula (55): is the power generation output of the 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, respectively; λ is the energy consumed by the carbon capture unit CO2; 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; is 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 ramping capacity optimization model of the power system, and obtain the uncertain ramping demand and the comprehensive consumables of the power system, including: uncertain up-climbing demand and uncertain down-climbing demand, comprehensive consumables of the power system, power generation consumables of thermal power units, start-up and shutdown consumables of thermal power units, loss of CO2 capture solution and consumables of carbon trading.

[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 on the computer-readable storage medium, and the computer program executes the steps of the above method when executed by a processor.

Claims

1. A method for evaluating and optimizing the ramping demand of a power system 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 interconnection line power of the power system in period t; is the unadjustable power output of the power system in 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) to formula (4): is the net load change of the power system in period t; and They are the deterministic up-ramp demand and the deterministic down-ramp demand of the power system in period t respectively; is a collection of time periods; Step 3: Calculate the uncertain ramp demand of the power system in period t and climbing requirements under uncertainty ; Step 4: Uncertainty of ramp-up requirements based on period t and climbing demand under uncertainty , establish a ramping demand optimization model considering load-side resources; Step 5: Based on the ramp demand, establish a ramp 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 ramping capacity optimization model of the power system, and obtain the uncertain ramping demand and the comprehensive consumables of the power system accordingly, including: uncertain up-climbing demand and uncertain down-climbing demand, comprehensive consumables of the power system, power generation consumables of thermal power units, start-up and shutdown consumables of thermal power units, loss of CO2 capture solution and consumables of carbon trading.

2. A method for evaluating and optimizing the ramping demand of a power system considering load-side resources according to claim 1, characterized in that: The step 3 is carried out as follows: Step 3.1: Use equation (5) to calculate the uncertain ramp demand of the power system in period t: : (5) In formula (5): is the upper limit of 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 load forecast error of the power system in period t; It is the upper limit of the forecast error of renewable energy output of the power system in period t.

3. A method for evaluating and optimizing the ramping demand of a power system considering load-side resources according to claim 2, characterized in that: Described step 4 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 amount of the power system response in period t; Step 4.3: Use equations (9) and (10) to establish the demand response constraints of the ramp 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; The electricity price for the 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.

4. A method for evaluating and optimizing the ramping demand of a power system considering load-side resources according to claim 3, characterized in that: The step 5 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 formula (13) to formula (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 consumables of thermal power units; 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; g , b g 、c g Represents the three power generation material consumption coefficients of the generator set g in period t; It represents the active power output by the generator set g during the 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 operation with ethanolamine solution; is the net CO2 capture amount of carbon capture unit c in period t; is the consumables of carbon trading during period t; is the intensity coefficient of carbon emissions; is the quota coefficient of carbon trading; is the total CO2 captured by the 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)-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 power of the energy storage at node i in period t, respectively; It represents the reactive power output by the generator set g during the 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 ramp capacity 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 difference between node i and node j in period t; is the sine value of the voltage phase angle difference between node i and node j in period t; Step 5.4: Use equation (24) to establish the voltage constraint of the ramp 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 capacity constraints of the thermal power unit in the climbing capacity optimization model: (25) (26) (27) (28) (29) (30) In formula (25) to formula (30): and are the upward climbing capacity and downward climbing capacity of the generator set g in period t respectively; and are the upward climbing rate and downward climbing rate of the 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) to formula (40): , , , It is the power range parameter of four different peak load regulation states of thermal power units; , , is the upward climbing rate of the thermal power unit under three different peak load conditions; , , is the downward climbing rate of the thermal power unit under three different peak load conditions; , , They are the three Boolean variables introduced by linearization in formula (31); , , They are the three Boolean variables introduced by linearization in equation (32); Step 5.7: Use equation (41) to establish the system reserve constraint of the ramp capability optimization model: (41) In formula (41): represents the reserve capacity required by the power system during period t; Step 5.8: Use equation (42) to establish the output constraint of the thermal power unit of the ramping capability optimization model: (42) Step 5.9: Use equations (43) to (46) to establish the logical constraints of the climbing ability optimization model: (43) (44) (45) (46) In formula (43)-formula (46): Indicates whether the generator set g starts to start in period t; Indicates whether the generator set g starts to start in 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 time period, if the generator set g is If the time period is in the on state, =1, otherwise, let =0; represents the start and stop status of the generator set g in the t-1 period. If the generator set g is in the start state in the t-1 period, then =1, otherwise, let =0; Step 5.9: Use equations (47) to (55) to establish the carbon capture unit constraints of the ramping capability optimization model: (47) (48) (49) (50) (51) (52) (53) (54) (55) In formula (47)-formula (55): is the power generation output of the 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, respectively; λ is the energy consumed by the carbon capture unit CO2; 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; is 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.

5. 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 as described in any one of claims 1-4, and the processor is configured to execute the program stored in the memory.

6. 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 described in any one of claims 1 to 4 are executed.

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