A method and system for determining a sending end new energy base external sending direct current curve

Abstract

The application provides a method and system for determining a sending terminal new energy base external DC transmission curve. For the researched new energy base, full period simulation analysis is carried out based on the new energy scale and output characteristics. A mathematical optimization model with the minimum of power supply and new energy consumption is established by comprehensively considering the power supply and new energy consumption factors, the new energy installed capacity, the new energy output characteristics, the DC rated power and the DC utilization hour data. The mathematical optimization model is established by comprehensively considering the power supply and new energy consumption factors, and the sending DC transmission curve can be obtained after solving. The method can obtain the sending terminal new energy base external DC transmission curve, thereby providing a reference for planning and operation.

Description

Technical Field

[0001] This invention relates to the field of power system planning, and in particular to a method and system for determining the DC transmission curve of a new energy base at the sending end. Background Technology

[0002] With the planning and deployment of large-scale wind power and photovoltaic bases in desert, Gobi, and arid regions, these areas will become the "main battlefield" for the development and construction of future new energy bases. The unique characteristics of these areas bring new challenges to the construction of large-scale new energy bases, and the power transmission curve schemes of these bases urgently need to be optimized. Summary of the Invention

[0003] This invention proposes a method and system for determining the DC transmission curve of a renewable energy base at the sending end. For the renewable energy base under study, a full-time simulation analysis is performed based on the scale and output characteristics of the renewable energy source. Taking into account both power supply security and renewable energy consumption factors, a mathematical optimization model is established, and the DC transmission curve can be obtained after solving the model. This method can obtain the DC transmission curve of the renewable energy base at the sending end, providing a reference for planning and operation.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for determining the DC transmission curve of a new energy base at the sending end includes:

[0006] Collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated DC power, and the DC utilization hours within the system under study;

[0007] A mathematical optimization model is established based on data on the scale of new energy installed capacity, the characteristics of new energy output, DC rated power, and DC utilization hours, with the goal of minimizing the amount of abandoned electricity and the power shortage.

[0008] The DC curve is obtained by solving the mathematical optimization model.

[0009] As a further improvement to this invention, a mathematical optimization model is established using data on new energy installed capacity, new energy output characteristics, DC rated power, and DC utilization hours, with the objective of minimizing abandoned power and power shortage. This model includes:

[0010] The objective function of the established optimization model is:

[0011] min k1*E d +k2*P lossmax

[0012] In the formula, k1 is the cost per kilowatt-hour of the electricity transferred, and k2 is the annual cost of insufficient power; E d P represents the total amount of power wasted by the system. lossmax This represents the maximum power output when there is insufficient power.

[0013] The constraints to be considered are:

[0014] 1) Power balance constraint at time i:

[0015] p wind，i *C wind +p solar，i *C solar +P loss，i -P d，i =P ZL，i

[0016] In the formula, p wind，i p solar，i These are the per-unit values ​​of the theoretical wind power and photovoltaic power output at time i, respectively; C wind C solar These represent the installed capacity of wind power and solar power, respectively; P loss，i The power is insufficient at time i; P d，i P represents the power abandoned at time i. ZL，i The DC output power at time i;

[0017] The following constraints must also be met;

[0018] E d =∑ i P d，i

[0019]

[0020] (2) DC shape constraint:

[0021] P ZL，i =x i *P low，day +(1-x i )*P high，day

[0022] In the formula, P low，day P high，day These represent the low-step and high-step power values ​​of the DC power output curve on day 1; x i The variable is 0-1, describing the state of the DC curve, where 1 represents a low step and 0 represents a high step.

[0023] x i-1 -x i ≤s start，i

[0024] x i -x i-1 ≤s close，i

[0025] In the formula, s start，i s close，iThese are 0-1 variables, representing the state from a low step to a high step or from a high step to a low step, respectively.

[0026]

[0027]

[0028] In the formula, N s N c These represent the number of times each day the steps change from high to low.

[0029] (3) Total power constraint:

[0030] ∑ i P zL，i =E ZL =P ZLN *T

[0031] In the formula, E ZL P represents the total DC charge; ZLN T represents the rated DC power; T represents the DC utilization hours.

[0032] As a further improvement to this invention, if the wind power and photovoltaic installed capacity are not given in advance, the following constraints need to be considered in the model:

[0033] ∑ i (p wind，i *C wind +p solar，i *C solar )=α*E zL

[0034] In the formula, α represents the proportion of electricity generated from new energy sources.

[0035] As a further improvement to the present invention, if the curve for one month is constrained to have fixed high and low steps, then the constraint added to the model is as follows:

[0036]

[0037]

[0038] In the formula, day1 and day2 are any two days of the month.

[0039] A system for determining the DC transmission curve of a new energy base at the sending end, comprising:

[0040] The data acquisition module is used to collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated DC power, and the DC utilization hours within the system under study.

[0041] The modeling module is used to establish a mathematical optimization model with the goal of minimizing abandoned power and power shortage based on data such as the installed capacity of new energy, the output characteristics of new energy, the rated power of DC, and the utilization hours of DC.

[0042] The solver module is used to solve the mathematical optimization model to obtain the DC curve.

[0043] As a further improvement of the present invention, the modeling module is specifically used for:

[0044] The objective function of the established optimization model is:

[0045] min k1*E d +k2*P lossmax

[0046] In the formula, k1 is the cost per kilowatt-hour of the electricity transferred, and k2 is the annual cost of insufficient power; E d P represents the total amount of power wasted by the system. lossmax This represents the maximum power output when there is insufficient power.

[0047] The constraints to be considered are:

[0048] 1) Power balance constraint at time i:

[0049] p wind，i *C wind +p solar，i *C solar +P loss，i -P d，i =P ZL，i

[0050] In the formula, p wind，i p solar，i These are the per-unit values ​​of the theoretical wind power and photovoltaic power output at time i, respectively; C wind C solar These represent the installed capacity of wind power and solar power, respectively; P loss，i The power is insufficient at time i; P d，i P represents the power abandoned at time i. ZL，i The DC output power at time i;

[0051] The following constraints must also be met;

[0052] E d =∑ i P d，i

[0053]

[0054] (2) DC shape constraint:

[0055] P ZL，i =x i *Plow，day +(1-x i )*P high，day

[0056] In the formula, P low，day P high，day These represent the low-step and high-step power values ​​of the DC power output curve on day 1; x i The variable is 0-1, describing the state of the DC curve, where 1 represents a low step and 0 represents a high step.

[0057] x i-1 -x i ≤s start，i

[0058] x i -x i-1 ≤s close，i

[0059] In the formula, s start，i s close，i These are 0-1 variables, representing the state from a low step to a high step or from a high step to a low step, respectively.

[0060]

[0061]

[0062] In the formula, N s N c These represent the number of times each day the steps change from high to low.

[0063] (3) Total power constraint:

[0064] ∑ i P ZL，i =E ZL =P ZLN *T

[0065] In the formula, E ZL P represents the total DC charge; ZLN T represents the rated DC power; T represents the DC utilization hours.

[0066] As a further improvement of the present invention, the modeling module is also used for:

[0067] If wind power and solar power installations are not specified in advance, the following constraints need to be considered in the model:

[0068] ∑ i (p wind，i *C wind +p solar，i *C solar )=α*E zL

[0069] In the formula, α represents the proportion of electricity generated from new energy sources.

[0070] As a further improvement of the present invention, the modeling module is also used for:

[0071] If the curve is constrained to have fixed heights and steps for one month, then the following constraints are added to the model:

[0072]

[0073]

[0074] In the formula, day1 and day2 are any two days of the month.

[0075] A device for determining the DC transmission curve of a new energy base at the sending end, comprising:

[0076] memory,

[0077] processor,

[0078] The processor is configured to execute the method for determining the DC transmission curve of the sending-end new energy base.

[0079] A computer-readable storage medium, characterized in that, when the instructions in the storage medium are executed by a processor, the processor is able to execute the method for determining the DC transmission curve of the sending-end new energy base.

[0080] Compared with the prior art, the beneficial effects of the present invention are:

[0081] This invention proposes a method for determining the DC transmission curve of a renewable energy base. For the renewable energy base under study, a full-time simulation analysis is conducted based on the scale and output characteristics of the renewable energy source. Taking into account both power supply security and renewable energy consumption factors, a mathematical optimization model is established, and the DC transmission curve can be obtained after solving the model. This method can obtain the DC transmission curve of the renewable energy base, providing a reference for planning and operation. The method of this invention can quantitatively calculate the transmission curve of the renewable energy base, and is characterized by convenient and rapid calculation. This method comprehensively considers power supply security and renewable energy consumption, establishes an optimized mathematical model, and solves for the DC curve. Using this method, the power transmission curve of the external DC transmission can be optimized, providing a reference for planning and operation. Attached Figure Description

[0082] Figure 1 This is a flowchart of the strategy of the present invention;

[0083] Figure 2 This is a typical weekly diagram;

[0084] Figure 3This is a schematic diagram of the system structure for determining the DC transmission curve of a new energy base at the sending end according to the present invention;

[0085] Figure 4 This is a schematic diagram of an electronic device structure according to the present invention. Detailed Implementation

[0086] The following is a detailed description of an example of the DC transmission curve formulation for a certain new energy base. It should be emphasized that the following description is merely illustrative and is not intended to limit the scope or application of the invention.

[0087] like Figure 1 As shown, the first objective of this invention is to provide a method for determining the DC transmission curve of a new energy base at the sending end, comprising the following steps:

[0088] Collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated DC power, and the DC utilization hours within the system under study;

[0089] A mathematical optimization model is established based on data on the scale of new energy installed capacity, the characteristics of new energy output, DC rated power, and DC utilization hours, with the goal of minimizing the amount of abandoned electricity and the power shortage.

[0090] The DC curve is obtained by solving the mathematical optimization model.

[0091] The method of the present invention will be described in detail below with reference to specific embodiments and accompanying drawings.

[0092] The specific steps for this method are as follows:

[0093] (1) Collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated power of DC, and the number of DC utilization hours in the system under study;

[0094] The installed capacity of new energy sources is 4 million kilowatts of wind power and 9 million kilowatts of photovoltaic power. The theoretical output of new energy sources is 8760 per unit value. The rated DC power is 8 million kilowatts. The DC utilization hours are 4000 hours.

[0095] (2) Establish a mathematical optimization model with the goal of minimizing the amount of abandoned electricity and the power shortage;

[0096] The objective function of the established optimization model is:

[0097] min k1*E d +k2*P lossmax

[0098] In the formula, d P represents the total amount of power wasted by the system. lossmax This represents the maximum power required to compensate for insufficient power supply. k1 is set at 0.5 yuan / kWh; k2 is temporarily calculated based on the annual pumped storage fee of 700 yuan / kW.

[0099] The constraints to be considered are:

[0100] 1) Power balance constraint at time i:

[0101] p wind , i *C eind +p solar , i *C solar +P loss，i -P d，i =P ZL，i (1)

[0102] In the formula, p wind , i p solar , i These are the per-unit values ​​of the theoretical output of wind power and photovoltaic power at time i, respectively. loss，i The power is insufficient at time i; P d，i Let be the power abandoned at time i;

[0103] P ZL，i Let be the DC output power at time i.

[0104] C wind C solar The installed capacity of wind power and photovoltaic power are 4 million and 9 million kilowatts, respectively.

[0105] The following constraints must also be met.

[0106] E d =∑ i P d，i (2)

[0107]

[0108] 2) DC shape constraint:

[0109] P ZL，i =x i *P low，day +(1-x i )*P high，day (4)

[0110] In the formula, P low，day P high，day These represent the low-step and high-step power values ​​of the DC power output curve on day 1; x i The variable is 0-1, describing the state of the DC curve, where 1 represents a low step and 0 represents a high step.

[0111] x i-1 -x i ≤sstart , i (5)

[0112] x i -x i-1 ≤s close , i (6)

[0113] In the formula, s start , i s close , i These are 0-1 variables, representing the state from a low step to a high step or from a high step to a low step, respectively.

[0114]

[0115]

[0116] In the formula, N s N c These represent the number of times the high and low steps change each day.

[0117] 3) Total power consumption constraint:

[0118] ∑ i P zL，i =E ZL =P ZLN *T (9)

[0119] In the formula, E ZL P represents the total DC charge; ZLN The rated power is 8 million kilowatts; T is the DC utilization hours, 4,000 hours.

[0120] 4) Daytime constraints

[0121] If the curve is constrained to have fixed heights and steps for one month, then the following constraints are added to the model:

[0122]

[0123]

[0124] (3) Solve the above model to obtain the DC transmission curve.

[0125] The first month's DC high-step capacity was 6337MW, and the low-step capacity was 2364MW. A typical weekly diagram is shown below.

[0126] like Figure 3 As shown, the present invention also provides a system for determining the DC transmission curve of a new energy base at the sending end, comprising:

[0127] The data acquisition module is used to collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated DC power, and the DC utilization hours within the system under study.

[0128] The modeling module is used to establish a mathematical optimization model with the goal of minimizing abandoned power and power shortage based on data such as the installed capacity of new energy, the output characteristics of new energy, the rated power of DC, and the utilization hours of DC.

[0129] The solver module is used to solve the mathematical optimization model to obtain the DC curve.

[0130] like Figure 4 As shown, another object of the present invention is to provide a device for determining the DC transmission curve of a new energy base at the sending end, comprising:

[0131] memory,

[0132] processor,

[0133] The processor is configured to execute the method for determining the DC transmission curve of the sending-end new energy base.

[0134] The present invention also provides a computer-readable storage medium, wherein when the instructions in the storage medium are executed by a processor, the processor is able to perform a method for determining the DC transmission curve of a new energy base at the sending end.

[0135] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0136] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0137] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0138] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for determining the DC transmission curve of a new energy base at the sending end, characterized in that, include: Collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated DC power, and the DC utilization hours within the system under study; A mathematical optimization model is established based on data on the scale of new energy installed capacity, the characteristics of new energy output, DC rated power, and DC utilization hours, with the goal of minimizing the amount of abandoned electricity and the power shortage. Solving the mathematical optimization model yields the DC curve; A mathematical optimization model is established based on data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated power of DC power, and the utilization hours of DC power, with the objective of minimizing the amount of abandoned power and the power shortage. This model includes: The objective function of the established optimization model is: min * + * In the formula, The cost per kilowatt-hour for the electricity moved. Annual cost for insufficient power supply; This represents the total amount of electricity wasted by the system. This represents the maximum power output when there is insufficient power. The constraints to be considered are: 1) No. Momentary power balance constraints: * * + In the formula, , The first The theoretical per-unit output values ​​of wind power and photovoltaic power at any given time; , These refer to the installed capacity of wind power and solar power, respectively. For the first Constantly low on power; For the first Power curtailment at any given time; For the first DC power output at all times; The following constraints must also be met; (2) DC shape constraint: In the formula, , The first Low-step and high-step power of the DC transmission curve; The variable is 0-1, describing the state of the DC curve, where 1 represents a low step and 0 represents a high step. In the formula, , These are 0-1 variables, representing the state from a low step to a high step or from a high step to a low step, respectively; In the formula, , These represent the number of times each day the steps change from high to low. (3) Total power constraint: In the formula, This represents the total DC power. DC rated power; This refers to the number of DC utilization hours.

2. The method for determining the DC transmission curve of a new energy base at the sending end according to claim 1, characterized in that, If wind power and solar power installations are not specified in advance, the following constraints need to be considered in the model: In the formula, This represents the proportion of electricity generated from new energy sources.

3. The method for determining the DC transmission curve of a new energy base at the sending end according to claim 1, characterized in that, If the curve is constrained to have fixed heights and steps for one month, then the following constraints are added to the model: In the formula, the first , Tianweidi Any two days of the month.

4. A system for determining the DC transmission curve of a new energy base at the sending end, characterized in that, include: The data acquisition module is used to collect data on the installed capacity of new energy sources, the output characteristics of new energy sources, the rated DC power, and the DC utilization hours within the system under study. The modeling module is used to establish a mathematical optimization model with the goal of minimizing abandoned power and power shortage based on data such as the installed capacity of new energy, the output characteristics of new energy, the rated power of DC, and the utilization hours of DC. The solver module is used to solve the mathematical optimization model to obtain the DC curve; The modeling module is specifically used for: The objective function of the established optimization model is: min * + * In the formula, The cost per kilowatt-hour for the electricity moved. Annual cost for insufficient power supply; This represents the total amount of electricity wasted by the system. This represents the maximum power output when there is insufficient power. The constraints to be considered are: 1) No. Momentary power balance constraints: * * + In the formula, , The first The theoretical per-unit output values ​​of wind power and photovoltaic power at any given time; , These refer to the installed capacity of wind power and solar power, respectively. For the first Constantly low on power; For the first Power curtailment at any given time; For the first DC power output at all times; The following constraints must also be met; (2) DC shape constraint: In the formula, , The first Low-step and high-step power of the DC transmission curve; The variable is 0-1, describing the state of the DC curve, where 1 represents a low step and 0 represents a high step. In the formula, , These are 0-1 variables, representing the state from a low step to a high step or from a high step to a low step, respectively; In the formula, , These represent the number of times each day the steps change from high to low. (3) Total power constraint: In the formula, This represents the total DC power. DC rated power; This refers to the number of DC utilization hours.

5. The system for determining the DC transmission curve of a new energy base at the sending end according to claim 4, characterized in that, The modeling module is also used for: If wind power and solar power installations are not specified in advance, the following constraints need to be considered in the model: In the formula, This represents the proportion of electricity generated from new energy sources.

6. The system for determining the DC transmission curve of a new energy base at the sending end according to claim 4, characterized in that, The modeling module is also used for: If the curve is constrained to have fixed heights and steps for one month, then the following constraints are added to the model: In the formula, the first , Tianweidi Any two days of the month.

7. A device for determining the DC transmission curve of a new energy base at the sending end, characterized in that, include: memory, processor, The processor is configured to perform the method for determining the DC transmission curve of the sending-end new energy base as described in any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor, the processor is able to perform the method for determining the DC transmission curve of the sending-end new energy base as described in any one of claims 1 to 3.

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