New energy output optimization method and device for whole power generation process

Abstract

The invention discloses a new energy output optimization method for a whole power generation process, and relates to the technical field of new energy, and the method comprises the steps: constructing theoretical, available and actual output models for the whole power generation process of new energy (wind power and photovoltaic), and then constructing a new energy actual output optimization model with new energy consumption as a target. And finally, obtaining a wind power and photovoltaic optimal output strategy by solving the optimal solution of the new energy actual output optimization model. The invention further discloses a new energy output optimization device oriented to the whole power generation process, the whole power generation process of new energy from resources to electric energy is combined, and the new energy output optimization method has high practical guiding significance in promoting new energy consumption.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and in particular to a new energy output optimization method and device for the entire power generation process. Background Art

[0002] With the rapid growth of large-scale photovoltaic, wind power and other new energy installed capacity, the high proportion of new energy grid connection has aggravated the complexity of power system operation. Its inherent volatility and intermittent characteristics have posed a severe challenge to maintaining the real-time balance of power supply and demand. At present, the scale of new energy installed capacity has exceeded the limit that the system can absorb, resulting in frequent new energy power abandonment and serious waste of wind and solar resources. In view of this, in order to effectively alleviate the problem of new energy power abandonment, it is necessary to reasonably optimize the output of photovoltaic and wind power with the goal of new energy absorption.

[0003] At present, the common research methods for new energy consumption capacity mainly involve typical day method, random production simulation method, and time series production simulation method. However, the current mainstream methods do not fully consider the various factors that limit the level of wind and solar consumption in the process of new energy power generation, resulting in a large discrepancy between the theoretical research results and the actual results of new energy consumption. In view of this, how to combine the entire process of new energy power generation "from resources to electricity" and study the optimization of new energy output with the goal of promoting new energy consumption is an urgent problem to be solved. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the existing technology and provide a new energy output optimization method and device for the entire power generation process. The proposed method comprehensively considers various factors that limit the wind and solar power consumption level in the new energy power generation process, and has a strong practical guiding significance for further improving the new energy consumption level.

[0005] The present invention adopts the following technical solutions to solve the above technical problems:

[0006] In a first aspect, a new energy output optimization method for the entire power generation process proposed by the present invention includes:

[0007] For the whole process of renewable energy power generation, renewable energy includes wind farms and photovoltaics, and constructs new energy theoretical output model, available output model and actual output model respectively;

[0008] Based on the output of the whole power generation process of the new energy theoretical output model, available output model and actual output model, a new energy actual output optimization model with the goal of new energy consumption is constructed;

[0009] By solving the optimal solution of the optimization model for the actual output of new energy, the optimal output strategy for wind power and photovoltaic power is obtained.

[0010] As a further optimization scheme of the new energy output optimization method for the whole power generation process described in the present invention, the new energy theoretical output model is calculated in the following manner. The new energy theoretical output model includes the theoretical output power of photovoltaic output and the theoretical output power of wind power generation, wherein:

[0011] The theoretical output power of photovoltaic power is expressed as

[0012]

[0013] Among them, P PV is the actual output of the photovoltaic output device; P PV,N is the rated output of the photovoltaic output device; G N is the standard solar radiation intensity; α pv is the power temperature coefficient of the photovoltaic output device; T C is the temperature of the photovoltaic output device; T STC is the battery temperature under standard test conditions; G is the actual solar radiation intensity, which obeys Beta distribution, and T0 is the ambient temperature;

[0014] The theoretical output power of wind power generation is expressed as

[0015]

[0016] Among them, v N is the rated wind speed; v in and v out are the cut-in wind speed and the cut-out wind speed respectively; P WT,N and P WT are rated power and output power respectively, v is wind speed, and it obeys Weibull distribution.

[0017] As a further optimization scheme of the new energy output optimization method for the whole power generation process described in the present invention, the new energy available output model is calculated in the following manner, and the new energy available output model includes the available output model of the wind farm and the available output model of the photovoltaic power station, wherein:

[0018] Available output model of wind farms

[0019]

[0020] in, is the available output of the wind farm, P WT,x is the available output of the xth wind turbine in the wind farm, X is the total number of wind turbines in the wind farm, Provide power for wind farms that are blocked;

[0021]

[0022] Among them, X1, X2, and X3 are the number of units for planned maintenance, unplanned outage, and accompanying outage in the wind farm respectively;

[0023] Available output model of photovoltaic power station

[0024]

[0025] Among them, Y is the total number of photovoltaic modules in the photovoltaic power station, The photovoltaic power station is blocked from outputting power. is the available output of the photovoltaic power station, P PV,y The available output of the yth photovoltaic module in the photovoltaic power station;

[0026]

[0027] Among them, Y1, Y2, and Y3 are the number of photovoltaic components that are scheduled for maintenance, unplanned outages, and accompanying outages in the photovoltaic power station, respectively.

[0028] As a further optimization scheme of the new energy output optimization method for the whole power generation process described in the present invention, the actual output model of new energy is calculated in the following way, which is as follows:

[0029] The actual output model of new energy is expressed as

[0030]

[0031] in, They are the actual outputs of wind farms and photovoltaic power stations respectively.

[0032] As a further optimization scheme of the new energy output optimization method for the whole power generation process described in the present invention, the new energy actual output optimization model includes:

[0033] From the perspective of sequential production simulation, an output optimization model is constructed with the maximum output of new energy within the operating time as the optimization goal, that is,

[0034]

[0035] Where T is the total running time of the sequential production simulation, are the actual outputs of the nth photovoltaic power station and the mth wind farm, respectively. F is the maximum output of renewable energy during operation. t is the operation period. N is the number of photovoltaic power stations and M is the number of wind farms.

[0036] As a further optimization scheme of the new energy output optimization method for the whole power generation process described in the present invention, the constraints of the new energy actual output optimization model include power balance constraints, spinning reserve constraints, unit climbing constraints, new energy station output constraints, node flow constraints, N-1 safety constraints of node voltage and N-1 safety constraints of line transmission power; wherein,

[0037] Power balance constraints

[0038]

[0039] Where O is the number of thermal power units in the power system; P TH,o (t) is the active power output of the oth thermal power unit at time t; P L (t) is the total load of the system at time t;

[0040] Spinning reserve constraints

[0041]

[0042] in, is the upper limit of active output of the oth thermal power unit; P re is the positive spinning reserve of the power system; S o (t) is a binary variable representing the operating status of the oth thermal power unit at time t, S o When S(t) is equal to 1, it means that the oth thermal power unit is in operation at time t. o When (t) is equal to 0, it means that the oth thermal power unit is in shutdown state at time t;

[0043] Unit climbing constraint

[0044]

[0045] Among them, P TH,o (t-1) is the active power output of the oth thermal power unit at time t-1, ΔUP TH,o and ΔDP TH,o are the maximum upward and downward climbing powers of the oth thermal power unit respectively;

[0046] Output constraints of new energy stations

[0047]

[0048] in, They represent the available output of the nth photovoltaic power station and the mth wind farm at time t respectively;

[0049] Node power flow constraints

[0050]

[0051] Among them, P TH,i (t) and P L,i (t) are the active power of thermal power, photovoltaic power, wind power and load of the i-th node at the t-th moment; Q TH,i (t) and Q L,i (t) are the reactive power of thermal power, photovoltaic power, wind power and load at the i-th node at the t-th moment; G ij , B ij and δ ij (t) are the conductance, reactance and phase angle between the ith node and the jth node, N ND is the total number of system nodes, U i (t) is the voltage amplitude of the ith node at time t, U j (t) is the voltage amplitude of the jth node at time t;

[0052] N-1 safety constraints on node voltage

[0053]

[0054] Among them, U i,min and U i,max are the lower and upper limits of the voltage at the i-th node respectively; and are the voltage amplitudes of the i-th node in the base state and the d-th N-1 fault event respectively; N FT is the number of N-1 faults in the power system, and Z is the number of nodes in the power system;

[0055] N-1 safety constraint on line transmission power

[0056]

[0057] Among them, P L,l (t) and P L,l,max are respectively the active power and the maximum transmission power transmitted by the lth line; and are the active power of the lth line in the base state and the dth N-1 fault event respectively; N L is the number of branches in the power system, G ii is the self-conductance of the ith node.

[0058] As a further optimization scheme of the new energy output optimization method for the whole power generation process described in the present invention, the optimal output strategy of wind power and photovoltaic power is obtained by solving the optimal solution of the actual output optimization model of new energy; the details are as follows:

[0059] The key time section flow constraint selection method is adopted and combined with the deep neural network decision algorithm to solve the actual output optimization model of renewable energy, and then the optimal output strategy of wind power and photovoltaic is obtained.

[0060] In the second aspect, a new energy output optimization device for the entire power generation process includes a construction module, an optimization module and a calculation module; wherein,

[0061] The construction module is used for the whole process of renewable energy power generation. New energy includes wind farms and photovoltaics. The theoretical output model, available output model and actual output model of new energy are constructed respectively.

[0062] The optimization module builds an optimization model for the actual output of new energy with the goal of absorbing new energy based on the output of the entire power generation process of the new energy theoretical output model, the available output model and the actual output model;

[0063] The calculation module is used to obtain the optimal output strategy of wind power and photovoltaic power by solving the optimal solution of the optimization model of the actual output of new energy.

[0064] In a third aspect, an embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein when the processor executes the computer program, the steps of the new energy output optimization method for the entire power generation process as described in the first aspect or any corresponding embodiment thereof are implemented.

[0065] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the new energy output optimization method for the entire power generation process as described in the first aspect or any corresponding embodiment thereof are implemented.

[0066] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0067] This application first focuses on the entire process of new energy (wind power, photovoltaic) power generation, and constructs new energy theoretical, available, and actual output models respectively, then constructs a new energy actual output optimization model with the goal of new energy consumption, and finally solves the optimal solution of the new energy actual output optimization model to obtain the optimal output strategy for wind power and photovoltaic. The proposed method comprehensively considers various factors that limit the level of wind and solar power consumption in the process of new energy power generation, and has a strong practical guiding significance for further improving the level of new energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow chart of the new energy output optimization method for the whole power generation process in the present invention;

[0069] Figure 2 It is the result of the new energy output consumption under the total operation time of the production simulation with different time sequences in the present invention;

[0070] Figure 3 It is the result of the new energy consumption rate under the total operation time of the production simulation with different time sequences in the present invention;

[0071] Figure 4 It is the result of energy output consumption under different voltage amplitude upper limits in the present invention. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0075] Reference Figure 1 to Figure 4 , is an embodiment of the present invention, which provides a new energy output optimization method for the entire power generation process, including:

[0076] S101: For the entire process of new energy (wind power, photovoltaic) power generation, construct new energy theoretical output model, available output model and actual output model, including:

[0077] The new energy theoretical output model is calculated in the following way. The new energy theoretical output model includes the theoretical output power of photovoltaic power and the theoretical output power of wind power generation.

[0078] Photovoltaic output is mainly affected by solar irradiance and temperature. The theoretical output power of photovoltaic output is expressed as

[0079]

[0080] Among them, P PV is the actual output of the photovoltaic output device; P PV,N is the rated output of the photovoltaic output device; G N is the standard solar radiation intensity; α pv is the power temperature coefficient of the photovoltaic output device; T C is the temperature of the photovoltaic output device; T STC is the battery temperature under standard test conditions; G is the actual solar radiation intensity, which obeys Beta distribution, and T0 is the ambient temperature;

[0081] The theoretical output power of wind power generation is expressed as

[0082]

[0083] Among them, v N is the rated wind speed; v in and v out are the cut-in wind speed and the cut-out wind speed respectively; P WT,N and P WT are rated power and output power respectively, v is wind speed, and it obeys Weibull distribution.

[0084] The available output model of new energy is calculated in the following way. The available output model of new energy includes the available output model of wind farm and the available output model of photovoltaic power station.

[0085] Available output model of wind farms

[0086]

[0087] in, is the available output of the wind farm, P WT,x is the available output of the xth wind turbine in the wind farm, X is the total number of wind turbines in the wind farm, Provide power for wind farms that are blocked;

[0088]

[0089] Among them, X1, X2, and X3 are the number of units for planned maintenance, unplanned outage, and accompanying outage in the wind farm respectively;

[0090] Available output model of photovoltaic power station

[0091]

[0092] Among them, Y is the total number of photovoltaic modules in the photovoltaic power station, The photovoltaic power station is blocked from outputting power. is the available output of the photovoltaic power station, P PV,y The available output of the yth photovoltaic module in the photovoltaic power station;

[0093]

[0094] Among them, Y1, Y2, and Y3 are the number of photovoltaic components that are scheduled for maintenance, unplanned outages, and accompanying outages in the photovoltaic power station, respectively.

[0095] The actual output model of new energy is expressed as

[0096]

[0097] in, They are the actual outputs of wind farms and photovoltaic power stations respectively.

[0098] S102: Based on the output of the whole power generation process of the new energy theoretical output model, the available output model and the actual output model, a new energy actual output optimization model with the goal of new energy consumption is constructed, including:

[0099] The actual output optimization model of new energy includes:

[0100] From the perspective of sequential production simulation, an output optimization model is constructed with the maximum output of new energy within the operating time as the optimization goal, that is,

[0101]

[0102] Where T is the total running time of the sequential production simulation, are the actual outputs of the nth photovoltaic power station and the mth wind farm, respectively. F is the maximum output of renewable energy during operation. t is the operation period. N is the number of photovoltaic power stations and M is the number of wind farms.

[0103] The constraints of the optimization model for the actual output of renewable energy include power balance constraints, spinning reserve constraints, unit ramp constraints, renewable energy station output constraints, node power flow constraints, N-1 safety constraints of node voltage, and N-1 safety constraints of line transmission power.

[0104] Power balance constraints

[0105]

[0106] Where O is the number of thermal power units in the power system; P TH,o (t) is the active power output of the oth thermal power unit at time t; P L (t) is the total load of the system at time t;

[0107] Spinning reserve constraints

[0108]

[0109] in, is the upper limit of active output of the oth thermal power unit; P re is the positive spinning reserve of the power system; S o (t) is a binary variable representing the operating status of the oth thermal power unit at time t, S o When S(t) is equal to 1, it means that the oth thermal power unit is in operation at time t. o When (t) is equal to 0, it means that the oth thermal power unit is in shutdown state at time t;

[0110] Unit climbing constraint

[0111]

[0112] Among them, P TH,o (t-1) is the active power output of the oth thermal power unit at time t-1, ΔUP TH,o and ΔDP TH,o are the maximum upward and downward climbing powers of the oth thermal power unit respectively;

[0113] Output constraints of new energy stations

[0114]

[0115] in, They represent the available output of the nth photovoltaic power station and the mth wind farm at time t respectively;

[0116] Node power flow constraints

[0117]

[0118] Among them, P TH,i (t) and P L,i (t) are the active power of thermal power, photovoltaic power, wind power and load of the i-th node at the t-th moment; Q TH,i (t) and Q L,i (t) are the reactive power of thermal power, photovoltaic power, wind power and load at the i-th node at the t-th moment; G ij , B ij and δ ij (t) are the conductance, reactance and phase angle between the ith node and the jth node, N ND is the total number of system nodes, U i (t) is the voltage amplitude of the ith node at time t, U j (t) is the voltage amplitude of the jth node at time t;

[0119] N-1 safety constraints on node voltage

[0120]

[0121] Among them, U i,min and U i,max are the lower and upper limits of the voltage at the i-th node respectively; and are the voltage amplitudes of the i-th node in the base state and the d-th N-1 fault event respectively; N FT is the number of N-1 faults in the power system, and Z is the number of nodes in the power system;

[0122] N-1 safety constraint on line transmission power

[0123]

[0124] Among them, P L,l (t) and P L,l,max are respectively the active power and the maximum transmission power transmitted by the lth line; and are the active power of the lth line in the base state and the dth N-1 fault event respectively; N L is the number of branches in the power system, G ii is the self-conductance of the ith node.

[0125] S103: Solving the optimal solution of the optimization model for the actual output of new energy to obtain the optimal output strategy for wind power and photovoltaic power, including using a key time section flow constraint selection method and combining a deep neural network decision algorithm to solve the optimization model for the actual output of new energy, and then obtaining the optimal output strategy for wind power and photovoltaic power.

[0126] An embodiment of the present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the steps of the new energy output optimization method for the entire power generation process as described in any of the above-mentioned embodiments are implemented.

[0127] An embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the new energy output optimization method for the entire power generation process as described in any of the above-mentioned embodiments.

[0128] In summary, this solution constructs a theoretical, available, and actual output model for the entire process of new energy (wind power, photovoltaic) power generation, and then constructs a new energy actual output optimization model with the goal of new energy consumption, and obtains the optimal output strategy of wind power and photovoltaic by solving the optimal solution of the new energy actual output optimization model, so as to grasp the reasons for new energy abandonment in the entire process "from resources to electric energy", and thus give the optimal output strategy of new energy. The method proposed in the present invention comprehensively considers various factors that limit the level of wind and solar consumption in the process of new energy power generation, and has a strong practical guiding significance for further improving the level of new energy consumption.

[0129] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0130] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0131] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0132] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0133] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0134] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A new energy output optimization method for the entire power generation process, characterized in that: include: For the whole process of renewable energy power generation, renewable energy includes wind farms and photovoltaics, and constructs new energy theoretical output model, available output model and actual output model respectively; Based on the output of the whole power generation process of the new energy theoretical output model, available output model and actual output model, a new energy actual output optimization model with the goal of new energy consumption is constructed; By solving the optimal solution of the optimization model for the actual output of new energy, the optimal output strategy for wind power and photovoltaic power is obtained.

2. A new energy output optimization method for the entire power generation process as claimed in claim 1, characterized in that: The new energy theoretical output model is calculated in the following way. The new energy theoretical output model includes the theoretical output power of photovoltaic power and the theoretical output power of wind power generation. The theoretical output power of photovoltaic power is expressed as Among them, P PV is the actual output of the photovoltaic output device; P PV,N is the rated output of the photovoltaic output device; G N is the standard solar radiation intensity; α pv is the power temperature coefficient of the photovoltaic output device; T C is the temperature of the photovoltaic output device; T STC is the battery temperature under standard test conditions; G is the actual solar radiation intensity, which obeys Beta distribution, and T0 is the ambient temperature; The theoretical output power of wind power generation is expressed as Among them, v N is the rated wind speed; v in and v out are the cut-in wind speed and the cut-out wind speed respectively; P WT,N and P WT are rated power and output power respectively, v is wind speed, and it obeys Weibull distribution.

3. A new energy output optimization method for the entire power generation process as claimed in claim 1, characterized in that: The available output model of new energy is calculated in the following way. The available output model of new energy includes the available output model of wind farm and the available output model of photovoltaic power station. Available output model of wind farms in, is the available output of the wind farm, P WT,x is the available output of the xth wind turbine in the wind farm, X is the total number of wind turbines in the wind farm, To provide power for wind farms that are blocked; Among them, X1, X2, and X3 are the number of units for planned maintenance, unplanned outage, and accompanying outage in the wind farm respectively; Available output model of photovoltaic power station Among them, Y is the total number of photovoltaic modules in the photovoltaic power station, The photovoltaic power station is blocked from outputting power. is the available output of the photovoltaic power station, P PV,y The available output of the yth photovoltaic module in the photovoltaic power station; Among them, Y1, Y2, and Y3 are the number of photovoltaic components that are scheduled for maintenance, unplanned outages, and accompanying outages in the photovoltaic power station, respectively.

4. A new energy output optimization method for the entire power generation process as claimed in claim 3, characterized in that: The actual output model of new energy is calculated in the following way, as follows: The actual output model of new energy is expressed as in, They are the actual outputs of wind farms and photovoltaic power stations respectively.

5. A new energy output optimization method for the entire power generation process as claimed in claim 2, characterized in that: The actual output optimization model of new energy includes: From the perspective of time-series production simulation, an output optimization model is constructed with the maximum output of new energy within the operating time as the optimization goal, that is, Where T is the total running time of the sequential production simulation, are the actual outputs of the nth photovoltaic power station and the mth wind farm, respectively. F is the maximum output of renewable energy during operation. t is the operation period. N is the number of photovoltaic power stations and M is the number of wind farms.

6. A new energy output optimization method for the entire power generation process as claimed in claim 5, characterized in that: The constraints of the optimization model for the actual output of renewable energy include power balance constraints, spinning reserve constraints, unit ramp constraints, renewable energy station output constraints, node power flow constraints, N-1 safety constraints of node voltage, and N-1 safety constraints of line transmission power. Power balance constraints Where O is the number of thermal power units in the power system; P TH,o (t) is the active power output of the oth thermal power unit at time t; P L (t) is the total load of the system at time t; Spinning reserve constraints in, is the upper limit of active output of the oth thermal power unit; P re is the positive spinning reserve of the power system; S o (t) is a binary variable representing the operating status of the oth thermal power unit at time t, S o When S(t) is equal to 1, it means that the oth thermal power unit is in operation at time t. o When (t) is equal to 0, it means that the oth thermal power unit is in shutdown state at time t; Unit climbing constraint Among them, P TH,o (t-1) is the active power output of the oth thermal power unit at time t-1, ΔUP TH,o and ΔDP TH,o are the maximum upward and downward climbing powers of the oth thermal power unit respectively; Output constraints of new energy stations in, They represent the available output of the nth photovoltaic power station and the mth wind farm at time t respectively; Node power flow constraints Among them, P TH,i (t) and P L,i (t) are the active power of thermal power, photovoltaic power, wind power and load of the i-th node at the t-th moment; Q TH,i (t) and Q L,i (t) are the reactive power of thermal power, photovoltaic power, wind power and load at the i-th node at the t-th moment; G ij , B ij and δ ij (t) are the conductance, reactance and phase angle between the ith node and the jth node, N ND is the total number of system nodes, U i (t) is the voltage amplitude of the ith node at time t, U j (t) is the voltage amplitude of the jth node at time t; N-1 safety constraints on node voltage Among them, U i,min and U i,max are the lower and upper limits of the voltage at the i-th node respectively; and are the voltage amplitudes of the i-th node in the base state and the d-th N-1 fault event respectively; N FT is the number of N-1 faults in the power system, and Z is the number of nodes in the power system; N-1 safety constraint on line transmission power Among them, P L,l (t) and P L,l,max are respectively the active power and the maximum transmission power transmitted by the lth line; and are the active power of the lth line in the base state and the dth N-1 fault event respectively; N L is the number of branches in the power system, G ii is the self-conductance of the ith node.

7. A new energy output optimization method for the entire power generation process as claimed in claim 1, characterized in that: The optimal output strategy for wind power and photovoltaic power is obtained by solving the optimal solution of the optimization model for the actual output of new energy; the details are as follows: The key time section flow constraint selection method is adopted and combined with the deep neural network decision algorithm to solve the actual output optimization model of renewable energy, and then the optimal output strategy of wind power and photovoltaic is obtained.

8. A new energy output optimization device for the entire power generation process, characterized in that: It includes building module, optimization module and calculation module; among them, The construction module is used for the whole process of renewable energy power generation. New energy includes wind farms and photovoltaics. The theoretical output model, available output model and actual output model of new energy are constructed respectively. The optimization module builds an optimization model for the actual output of new energy with the goal of absorbing new energy based on the output of the entire power generation process of the new energy theoretical output model, the available output model and the actual output model; The calculation module is used to obtain the optimal output strategy of wind power and photovoltaic power by solving the optimal solution of the optimization model of the actual output of new energy.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor executes the computer program, the steps of the new energy output optimization method for the entire power generation process as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the new energy output optimization method for the entire power generation process as described in any one of claims 1 to 7 are implemented.

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