A method for optimizing the structure of external power supply from a new energy base

Abstract

The present invention belongs to the technical field of power transmission mode of new energy base, and specifically relates to a method for optimizing the power transmission structure of new energy base, comprising the following steps: obtaining historical operation data of various types of power sources in large-scale new energy bases, and establishing output models of various types of power sources after data cleaning; establishing a dual objective function based on the output models of various types of power sources, which is to maximize the annual average equivalent benefit of the new energy base and minimize the annual carbon emissions; providing constraints of the dual objective function, and establishing a power transmission configuration model for the new energy base according to the dual objective function and the constraints; optimizing the configuration model of the power transmission configuration model for the new energy base; the present invention proposes a power structure optimization configuration method for maximizing the annual average equivalent benefit of the new energy base and minimizing the annual carbon emissions, and constructs a multi-objective optimization model with power capacity and energy storage scale as decision variables.

Description

Technical Field

[0001] The present invention belongs to the technical field of power transmission modes for new energy bases, and in particular relates to a method for optimizing the structure of power transmission for new energy bases. Background Art

[0002] Under the guidance of achieving the "dual carbon" goals, vigorously developing renewable energy such as wind power and solar power generation and gradually replacing fossil energy has become an important consensus to accelerate the construction of a new power system and promote the green and low-carbon transformation of energy.

[0003] In order to cope with the randomness and volatility of wind and solar power generation and realize stable and reliable power transmission from new energy bases, power generation companies vigorously promote wind power, photovoltaic, thermal power, nuclear power, energy storage and other multi-energy complementary systems. In this system, new energy sources such as wind power and photovoltaic become the main power sources, and thermal power and energy storage serve as supporting power sources for flexible adjustment. How to reasonably allocate the installed capacity of thermal power, energy storage, wind power and photovoltaic to meet the electricity demand of the receiving end; how to use the regulation capacity of thermal power and energy storage to achieve the coordination and optimization of different types of power sources; how to increase the proportion of new energy such as wind and solar in the transmitted power, reduce the carbon emissions of the overall transmitted power, and ensure the optimal economy of the overall transmitted power. These are the core issues of optimizing the structure of the transmitted power from new energy bases.

[0004] Existing research still has obvious deficiencies in the optimization of power structure for power transmission from large-scale renewable energy bases. Most studies focus on single-target optimization, such as reducing wind and solar power abandonment, maximizing renewable energy consumption, or minimizing total costs, but lack comprehensive consideration of construction costs, operating costs, time costs, electricity sales and subsidy benefits, and carbon emissions throughout the life cycle of the power source, making it difficult to achieve the optimal configuration of the power source. In addition, the transmission power curve fails to fully match the demand curve of the receiving power grid, affecting the economic operation of the power source side.

[0005] Therefore, the existing solutions still have much room for improvement in coping with fluctuations in new energy, improving system economics, controlling carbon emissions and improving power transmission efficiency. Summary of the invention

[0006] The present invention is a method for optimizing the structure of power transmission from a new energy base, which aims to improve the economy of power transmission from the entire new energy base, while reducing the carbon emissions of the new energy base, and achieving the optimal balanced configuration of various types of power capacity and energy storage scale of the new energy base.

[0007] To achieve the above purpose, the present invention adopts the following specific technical scheme: A method for optimizing the structure of power supply delivered from a new energy base, comprising the following steps:

[0008] Obtain historical operating data of various types of power sources in large-scale new energy bases, and establish output models of various types of power sources after data cleaning;

[0009] Based on the output models of various types of power sources, a dual objective function is established to maximize the annual average equivalent benefits of the new energy base and minimize the annual carbon emissions;

[0010] The constraints of the dual objective function are given; and the configuration model of the external power supply of the new energy base is established based on the dual objective function and the constraints;

[0011] The non-dominated sorting genetic algorithm NSGA-II with integrated elite strategy is used to optimize the configuration model of the external power supply of the new energy base and obtain the Pareto optimal solution set;

[0012] According to the specific needs of the new energy base, the most suitable configuration plan is selected from the Pareto optimal solution set.

[0013] Furthermore, the output models of various types of power sources are established, including thermal power output models;

[0014] The thermal power output model can be expressed by the following formula:

[0015] P th (t) = P th_R ×η th ×α th (1)

[0016] Where: P th_R is the rated installed power of the thermal power unit; η th is the average efficiency of thermal power units; α th is the output factor of the thermal power unit;

[0017] The output factor of thermal power units is adjusted according to the difference between the demand of the receiving power grid and the output of other power sources other than thermal power, and the operation economy of the thermal power units is comprehensively considered, and the minimum output is not less than 30%; the output factor expression is as follows;

[0018]

[0019] Where: P re (t) is the power demand of the receiving power grid; P ot (t) All types of power output except thermal power units.

[0020] Furthermore, the output model of each type of power source specifically includes a nuclear power output model; the output model of the nuclear power output model is as follows:

[0021] P nc (t) = P nc_R ·ηnc (3)

[0022] Where: P nc_R is the rated installed capacity of nuclear power; η nc is the average efficiency of nuclear power plants.

[0023] Furthermore, the output models of various types of power sources are specifically established to include a photovoltaic output model; the photovoltaic output model can be expressed by the following formula:

[0024]

[0025] Where: P pv_R is the rated installed power, G(t) is the light intensity at time t, G STC is the light intensity under standard test conditions; k is the power temperature coefficient; η PV is the efficiency of the photovoltaic power generation system; T C (t) is the temperature of the photovoltaic panel at time t, T STC is the reference temperature;

[0026]

[0027] Where: T EN (t) is the ambient temperature at that time.

[0028] Furthermore, the output models of various types of power sources include a wind power output model; the wind power output model is represented by the following formula:

[0029]

[0030] Where: u ci is the cut-in wind speed; u R is the rated wind speed, P wi_R is the rated power; u co To cut out wind speed.

[0031] Furthermore, the output model also includes an energy storage output model; the charging process of the energy storage output model is expressed by the formula:

[0032] E(t)=(1-σ sdr Δt)E(t-1)+P ESS (t)Δtη c (7)

[0033] The discharge process is expressed as:

[0034] E(t)=(1-σ sdr Δt)E(t-1)-P ESS (t)Δtη D (8)

[0035] Where, E(t) is the remaining power of the energy storage medium at the end of time t; P ESS is the charge and discharge power of the energy storage medium at time t; sdr is the self-discharge rate of the energy storage medium; η C and η D are the charging and discharging efficiencies of the energy storage medium, respectively; Δt is the duration of each calculation window;

[0036] The maximum allowable charge and discharge power of the energy storage medium at time t is determined by its own charge and discharge characteristics and the remaining power at time t, and its expression is as follows;

[0037] While charging:

[0038] P st (t) = min{P max,C ,[E max -(1-σ sdr Δt)E(t-1)] / η C Δt}(9)

[0039] When discharging:

[0040] P st (t) = -min{P max,D ,[(1-σ sdr Δt)E(t-1)-E min ]η D / Δt}(10)

[0041] Where P st (t) is the maximum allowable charge and discharge power of the energy storage medium at time t; P max,C and P max,D are the maximum charging and discharging power of the energy storage medium, respectively, and P max,C and P max,D The values ​​of are all positive; max and E min are the upper and lower limits of the energy storage medium capacity constraints respectively.

[0042] Furthermore, based on the output models of various types of power sources, a dual objective function is established to maximize the annual average equivalent benefits of the new energy base and minimize the annual carbon emissions, including:

[0043] The objective function is established by maximizing the annual average equivalent income of the new energy base as follows:

[0044] f1=max(IC) (11)

[0045] Among them, I is the average annual income of the new energy base, and C is the average annual cost of the new energy base;

[0046]

[0047] Where: Q i is the average annual power output of different types of power sources; Price i The on-grid electricity price of different types of power sources shall be determined according to national or local policies; Isub j is the government subsidy income for photovoltaic, wind power and energy storage power stations; r is the discount rate; m j The life cycle of photovoltaic, wind power and energy storage power stations;

[0048] C is the average annual cost of the new energy base, which can be expressed as follows:

[0049]

[0050] Where: C i ,RE i are the initial construction investment and residual value of thermal power, photovoltaic power, wind power, nuclear power and energy storage station respectively; K i It is the operation and maintenance cost coefficient of thermal power, photovoltaic, wind power, nuclear power and energy storage station;

[0051] The objective function is established by minimizing annual carbon emissions as follows:

[0052] f2=min(CE con +CE ope +CE ret ) (15)

[0053] Among them, CE con ,CE ope ,CE ret They are the average annual carbon emissions of the construction, operation and decommissioning stages of various types of power sources and energy storage stations in new energy bases allocated to their entire life cycle;

[0054]

[0055] Where: C i , are the initial construction investments for thermal power, photovoltaic power, wind power, nuclear power and energy storage stations; EF con,i is the carbon emission factor of the corresponding power source type or energy storage station during the construction process; m i The life cycle of the corresponding power source type and energy storage station;

[0056]

[0057] Where: Q i is the average annual power output of different types of power sources; EF ope,i The carbon emission factors generated by the consumption of raw materials during the operation phase of different power types;

[0058]

[0059] Where: RE i are the residual values ​​of thermal power, photovoltaic power, wind power, nuclear power and energy storage stations; EF ret,i is the carbon emission factor of the corresponding power source type or energy storage station.

[0060] Furthermore, the constraints include: power balance constraints, power output constraints, energy storage station operation constraints, transmission channel utilization hour constraints, wind and solar power abandonment rate constraints, and new energy power proportion constraints;

[0061] The power balance constraint is expressed as follows:

[0062] P th (t)+P nc (t)+P pv (t)+P wi (t)+P st (t) = P re (t)(19)

[0063] Where: P th (t), P nc (t), P pv (t), P wi (t), P st (t) are the real-time outputs of thermal power, nuclear power, photovoltaic power, wind power and energy storage respectively; P re (t) is the power demand of the receiving power grid;

[0064] The power output constraint is expressed as follows:

[0065]

[0066] Where: P th_R , P nc_R , P pv_R , P wi_R They are the installed capacity of thermal power, nuclear power, photovoltaic power and wind power in large-scale new energy bases;

[0067] The energy storage station operation constraints are expressed as follows:

[0068] E min ≤E(t)≤E max (twenty one)

[0069] Where: E(t) is the remaining power of the energy storage medium at the end of time t; E max and E min are the upper and lower limits of the energy storage medium capacity constraints respectively;

[0070] The hourly constraint of the outbound channel is expressed as follows:

[0071]

[0072] Where: P dc_R is the rated transmission capacity of the new energy base transmission channel; T dc_min The minimum utilization hours of the transmission channel of the new energy base;

[0073] The wind and solar power abandonment rate constraint is expressed as follows:

[0074]

[0075] Where: P pv_R , P wi_R are the installed capacity of photovoltaic and wind power in large-scale new energy bases; T wi , T pv are the theoretical utilization hours of local wind power and photovoltaic power respectively; R wi , R pv are the maximum values ​​of wind and solar power abandonment rates respectively;

[0076] The new energy electricity proportion constraint is expressed as follows:

[0077]

[0078] Where: R dc It is the minimum value of the proportion of electricity of new energy sources such as wind and solar power transmitted through the transmission channel. A new energy base transmission power structure optimization system can realize a new energy base transmission power structure optimization; including:

[0079] Model building module, used to build output models of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations;

[0080] A new energy base transmission power configuration model building module, based on the output model established by the model building module, builds a dual objective function of maximizing the annual average equivalent income of the new energy base and minimizing the annual carbon emissions, with the scale of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations as decision variables, and a new energy base transmission power configuration model based on source-load power balance, power output, energy storage charging and discharging, transmission channel utilization hours, wind and solar power abandonment rate and new energy power proportion as conditions;

[0081] The optimization calculation module uses the non-dominated sorting genetic algorithm NSGA-II with an integrated elite strategy to optimize the configuration model of the external power supply of the new energy base and obtain the Pareto optimal solution set;

[0082] The scheme selection module selects the most suitable configuration scheme from the Pareto optimal solution set obtained by the optimization calculation module according to the specific needs of the new energy base.

[0083] A computer-readable storage medium stores computer program instructions that can be executed by a processor. When the processor executes the computer program instructions, the steps of a method for optimizing the structure of external power supply from a new energy base can be implemented.

[0084] The present invention can achieve the following technical effects:

[0085] Compared with traditional research, the present invention establishes a more comprehensive and accurate power output model by comprehensively considering the output characteristics and carbon emissions of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations throughout their life cycle.

[0086] The present invention proposes a power structure optimization configuration method aimed at maximizing the annual average equivalent benefit of a new energy base and minimizing the annual carbon emissions, and constructs a multi-objective optimization model with power capacity and energy storage scale as decision variables.

[0087] By adopting the non-dominated sorting genetic algorithm (NSGA-II) with integrated elite strategy, the present invention realizes the optimal configuration of power supply capacity and energy storage scale of the new energy base, effectively improves the economy of the new energy base, reduces carbon emissions, and achieves the optimal balance of the external power supply structure of the new energy base. In addition, the present invention also takes into account multiple constraints such as source-load power balance, power output, energy storage charging and discharging, external transmission channel utilization hours, wind and solar power abandonment rate, and new energy power proportion, ensuring the practical application value of the optimization results and the reliability of system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 It is the overall flow chart of the present invention;

[0089] Figure 2 This is a schematic diagram of power transmission from a large-scale new energy base. DETAILED DESCRIPTION

[0090] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation of the present invention.

[0091] refer to Figure 1-2 A method for optimizing the structure of power transmission from a new energy base comprises the following steps:

[0092] S1. Obtain the historical operation data of various types of power sources in large-scale new energy bases, and establish output models of various types of power sources after data cleaning;

[0093] S2. Based on the output models of various types of power sources, a dual objective function is established to maximize the annual average equivalent benefits of the new energy base and minimize the annual carbon emissions;

[0094] S3. Give the constraints of the dual objective function, and establish a new energy base external power supply configuration model based on the dual objective function and the constraints;

[0095] S4. The non-dominated sorting genetic algorithm NSGA-II with integrated elite strategy is used to optimize the configuration model of the external power supply of the new energy base and obtain the Pareto optimal solution set.

[0096] S5. According to the specific needs of the new energy base, select the most suitable configuration plan from the Pareto optimal solution set.

[0097] Furthermore, in step S1, the output models of various types of power sources are established, including: thermal power output model, nuclear power output model, photovoltaic output model and wind power output model; thermal power is an adjustable power source for large-scale new energy bases, and its output is closely related to the installed capacity, efficiency and output factor of thermal power units.

[0098] The thermal power output model can be expressed by the following formula:

[0099] P th (t) = P th_R ×η th ×α th (1)

[0100] Where: P th_R is the rated installed power of the thermal power unit; η th is the average efficiency of thermal power units; α th is the output factor of the thermal power unit;

[0101] The output factor of a thermal power unit is adjusted based on the difference between the demand of the receiving power grid and the output of other power sources other than thermal power, and the operating economy of the thermal power unit is comprehensively considered, with the minimum output not less than 30%. The output factor expression is as follows;

[0102]

[0103] Where: P re (t) is the power demand of the receiving power grid; P ot (t) All types of power output except thermal power units.

[0104] Furthermore, as an efficient and stable power source, nuclear power is used as the base core in the external power structure of large-scale new energy bases and does not participate in the regulation of power supply. Its output is mainly affected by the thermal energy conversion efficiency and the efficiency of steam turbine-based generators. The output model of the nuclear power output model is as follows:

[0105] P nc (t) = P nc_R ·η nc (3)

[0106] Where: P nc_R is the rated installed capacity of nuclear power; η nc is the average efficiency of nuclear power plants.

[0107] Furthermore, the photovoltaic power generation system uses solar panels to absorb sunlight and convert it directly into electrical energy. The power of photovoltaic power generation is not only related to the light intensity, but also to the ambient temperature and meteorological conditions; the photovoltaic output model can be expressed as follows:

[0108]

[0109] Where: P pv_R is the rated installed power, G(t) is the light intensity at time t, G STC is the light intensity under standard test environment, set to 1. k is the power temperature coefficient. η PV is the efficiency of the photovoltaic power generation system; T C (t) is the temperature of the photovoltaic panel at time t, T STC The reference temperature is 25°C.

[0110]

[0111] Where: T EN (t) is the ambient temperature at that time.

[0112] Furthermore, the wind power output model can be expressed as follows:

[0113]

[0114] Where: u ci is the cut-in wind speed; u R is the rated wind speed, P wi_R is the rated power; u co To cut out wind speed.

[0115] Further, in step S1, the output model also includes an energy storage output model; the remaining power of the energy storage medium changes continuously during the charging and discharging process, and the amount of change is related to the charging and discharging power and self-discharge during the period; the energy storage output model includes a charging process and a discharging process;

[0116] The charging process of the energy storage output model is expressed as follows:

[0117] E(t)=(1-σ sdr Δt)E(t-1)+P ESS (t)Δtη c (7)

[0118] The discharge process is expressed as:

[0119] E(t)=(1-σ sdr Δt)E(t-1)-P ESS (t)Δtη D (8)

[0120] Where, E(t) is the remaining power of the energy storage medium at the end of time t; P ESS is the charge and discharge power of the energy storage medium at time t; sdr is the self-discharge rate of the energy storage medium; η C and η D are the charging and discharging efficiencies of the energy storage medium, respectively; Δt is the duration of each calculation window;

[0121] The maximum allowable charge and discharge power of the energy storage medium at time t is determined by its own charge and discharge characteristics and the remaining power at time t, and its expression is as follows.

[0122] While charging:

[0123] P st (t) = min{P max,C ,[E max -(1-σ sdr Δt)E(t-1)]η C Δt}(9)

[0124] When discharging:

[0125] P st (t) = -min{P max,D ,[(1-σ sdr Δt)E(t-1)-E min ]η D / Δt}(10)

[0126] Where P st (t) is the maximum allowable charge and discharge power of the energy storage medium at time t; P max,C and P max,D are the maximum charging and discharging power of the energy storage medium, respectively, and P max,C and P max,D The values ​​of are all positive; max and E minare the upper and lower limits of the energy storage medium capacity constraints respectively; min{} function is the minimum value function.

[0127] Furthermore, in step S2, in order to ensure the economic feasibility of power transmission from large-scale new energy bases, the present invention comprehensively evaluates the costs and benefits of various power sources over their entire life cycle, and based on the output models of various types of power sources, establishes a dual objective function of maximizing the annual average equivalent benefits of the new energy base and minimizing the annual carbon emissions, specifically including:

[0128] The objective function is established by maximizing the annual average equivalent income of the new energy base as follows:

[0129] f1=max(IC)(11)

[0130] Among them, I is the average annual income of the new energy base, and C is the average annual cost of the new energy base;

[0131] The average annual income I of the new energy base mainly includes electricity sales income, subsidy income and residual value recovery. The electricity sales income is the power generation income of various types of power sources such as thermal power, photovoltaic power, wind power, nuclear power, etc.; the subsidy income is mainly the subsidies given by government departments to support the construction of photovoltaic power, wind power and energy storage stations; the residual value recovery is the residual value of various types of power sources and energy storage stations after the life cycle is deducted from the various expenses such as demolition, labor and transportation.

[0132]

[0133] Where: Q i is the average annual power output of different types of power sources; Price i The on-grid electricity price of different types of power sources shall be determined according to national or local policies; Isub j is the government subsidy income for photovoltaic, wind power and energy storage power stations; r is the discount rate; m j The life cycle of photovoltaic, wind power and energy storage power stations;

[0134] The average annual cost C of a new energy base mainly includes construction costs and operation and maintenance costs. The construction cost includes the annual value of the initial construction investment costs of thermal power, photovoltaic, wind power, nuclear power and other types of power sources and energy storage stations; the operation and maintenance cost is the daily operation, maintenance and repair costs of various types of power stations and energy storage stations.

[0135] C is the average annual cost of the new energy base, which is expressed as follows:

[0136]

[0137] Where: C i ,RE i They are the initial construction investment and residual value of thermal power, photovoltaic power, wind power, nuclear power and other types of power sources and energy storage stations; K iIt is the operation and maintenance cost coefficient of thermal power, photovoltaic, wind power, nuclear power and other types of power sources and energy storage stations, which is determined by historical operation data;

[0138] Furthermore, in order to ensure that large-scale new energy bases are low-carbon, the present invention comprehensively considers the carbon emissions of various types of power sources and energy storage stations during their entire life cycle during construction, operation, and decommissioning, and establishes an objective function based on minimizing annual carbon emissions as follows:

[0139] f2=min(CE con +CE ope +CE ret )(15)

[0140] Among them, CE con ,CE ope ,CE ret They are the average annual carbon emissions of the construction, operation and decommissioning stages of various types of power sources and energy storage stations in new energy bases allocated to their entire life cycle;

[0141] The carbon emissions during the construction phase are mainly the carbon emissions generated during the raw materials, equipment manufacturing, transportation, and construction of various types of power sources and energy storage stations;

[0142]

[0143] Where: C i EF and EF are the initial construction investments of thermal power, photovoltaic power, wind power, nuclear power and other types of power sources and energy storage stations; con,i The carbon emission factor of raw materials, equipment manufacturing, transportation, and construction process is comprehensively considered for the corresponding power source type or energy storage station during the construction process; m i The life cycle of the corresponding power source type and energy storage station;

[0144] The carbon emissions during the operation phase are mainly due to the carbon emissions generated by the raw materials consumed in the power generation process and the spare parts consumed in operation and maintenance. The carbon emissions generated by spare parts are small and can be ignored.

[0145]

[0146] Where: Q i is the average annual power output of different types of power sources; EF ope,i The carbon emission factors generated by the consumption of raw materials during the operation phase of different power types;

[0147] The carbon emissions in the decommissioning stage mainly come from the dismantling of equipment, waste disposal and transportation of various types of power sources and energy storage stations.

[0148]

[0149] Where: RE i are the residual values ​​of thermal power, photovoltaic power, wind power, nuclear power and other types of power sources and energy storage stations; EF ret,i The carbon emission factors for equipment dismantling, waste treatment and transportation are comprehensively considered for the corresponding power source type or energy storage station.

[0150] Furthermore, in step S3, the constraints include: power balance constraint, power output constraint, energy storage station operation constraint, transmission channel utilization hour constraint, wind and solar power abandonment rate constraint, and new energy power proportion constraint;

[0151] At any time, the sum of the outputs of all types of power sources and energy storage is equal to the power demand of the receiving grid. The power balance constraint is expressed as follows:

[0152] P th (t)+P nc (t)+P pv (t)+P wi (t)+P st (t) = P re (t)(19)

[0153] Where: P th (t), P nc (t), P pv (t), P wi (t), P st (t) are the real-time outputs of thermal power, nuclear power, photovoltaic power, wind power and energy storage respectively; P re (t) is the power demand of the receiving power grid;

[0154] The power output constraint is expressed as follows:

[0155]

[0156] Where: P th_R , P nc_R , P pv_R , P wi_R They are the installed capacity of thermal power, nuclear power, photovoltaic power and wind power in large-scale new energy bases respectively; at any time, the output of each type of power source should be between its upper and lower limits.

[0157] The power of the energy storage station at any time should be between the upper and lower limits. The energy storage station operation constraints are expressed as follows:

[0158] E min ≤E(t)≤E max (twenty one)

[0159] Where: E(t) is the remaining power of the energy storage medium at the end of time t; E max and E minare the upper and lower limits of the energy storage medium capacity constraints respectively;

[0160] In order to ensure the economic efficiency of the power transmission channel, the utilization hours throughout the year should not be less than the specified minimum value. The utilization hour constraint of the transmission channel is expressed as follows:

[0161]

[0162] Where: P dc_R is the rated transmission capacity of the new energy base transmission channel; T dc_min The minimum utilization hours of the new energy base transmission channel; generally 4,500 hours.

[0163] The wind and photovoltaic abandonment rates in the new energy base should be less than the specified maximum value. The wind and photovoltaic abandonment rate constraint is expressed as follows:

[0164]

[0165] Where: P pv_R , P wi_R are the installed capacity of photovoltaic and wind power in large-scale new energy bases; T wi 、T pv are the theoretical utilization hours of local wind power and photovoltaic power respectively; R wi , R pv are the maximum values ​​of wind and solar power abandonment rates respectively;

[0166] The constraint on the proportion of renewable energy electricity is expressed as follows:

[0167] The proportion of new energy such as wind power and photovoltaics exported from new energy bases shall not be less than the prescribed proportion.

[0168]

[0169] Where: R dc It is the minimum value of the proportion of electricity from new energy sources such as wind and solar power transmitted through the transmission channel.

[0170] Furthermore, in step S4, the non-dominated sorting genetic algorithm (NSGA-II) with integrated elite strategy is used to optimize the configuration of the power capacity and energy storage scale of the new energy base in the new energy base external power configuration model. The relevant parameters of various types of power sources and energy storage power stations (such as output model parameters, cost-benefit parameters, constraint parameters, etc.) are input into the algorithm, and the optimization is carried out through continuous cycles of iterations. In each iteration, the advantages and disadvantages of individuals (different combinations of power capacity and energy storage scale) are evaluated according to the objective function, and excellent individuals are selected according to non-dominated sorting and congestion calculations for crossover and mutation operations, gradually approaching the optimal solution, and finally obtaining the Pareto optimal solution set.

[0171] Furthermore, in step S5, the obtained Pareto optimal solution set is analyzed, and the annual average equivalent income and annual carbon emission objective function values ​​corresponding to each solution are compared. According to the actual needs of the new energy base, such as the emphasis on economy, the restriction requirements on carbon emissions, etc., the most suitable configuration scheme is selected from the solution set. For example, if the new energy base pays more attention to economic benefits, a scheme with a higher annual average equivalent income can be selected; if there are strict requirements on carbon emissions, a scheme with a lower annual carbon emission is preferred, so as to achieve the optimal balance between the economy and cleanliness of the new energy base's external power supply structure.

[0172] This application also proposes a new energy base external power supply structure optimization system, which can implement a new energy base external power supply structure optimization method; including:

[0173] A model building module is used to build output models of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations; wherein the thermal power output model is related to the installed capacity, efficiency and output factor of the thermal power unit, the nuclear power output model is affected by the thermal energy conversion efficiency and the efficiency of the steam turbine-based generator, the photovoltaic output model is related to the light intensity, ambient temperature and meteorological conditions, the wind power output model is represented by a piecewise nonlinear wind speed power curve, and the output model of the energy storage power station includes the charging and discharging process and the calculation of the maximum allowable charging and discharging power, and the model building module is also used to obtain the historical operation data and climate conditions of the location of the large-scale new energy base, and establish the output models of various types of power sources and the charging and discharging models of the energy storage power station after data cleaning processing;

[0174] A new energy base transmission power configuration model building module, based on the output model established by the model building module, builds a dual objective function of maximizing the annual average equivalent income of the new energy base and minimizing the annual carbon emissions, with the scale of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations as decision variables, and a new energy base transmission power configuration model based on source-load power balance, power output, energy storage charging and discharging, transmission channel utilization hours, wind and solar power abandonment rate and new energy power proportion as conditions;

[0175] The optimization calculation module uses the non-dominated sorting genetic algorithm NSGA-II with an integrated elite strategy to optimize the configuration model of the external power supply of the new energy base and obtain the Pareto optimal solution set;

[0176] The scheme selection module selects the most suitable configuration scheme from the Pareto optimal solution set obtained by the optimization calculation module according to the specific needs of the new energy base.

[0177] The present application also proposes a computer-readable storage medium, on which computer program instructions that can be executed by a processor are stored. When the processor executes the computer program instructions, a method for optimizing the structure of external power supply from a new energy base can be implemented.

[0178] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0179] Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. Those skilled in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

[0180] The above specific implementations of the present invention do not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for optimizing the structure of power supply delivered from a new energy base, characterized in that: The following steps are involved: Obtain historical operating data of various types of power sources in large-scale new energy bases, and establish output models of various types of power sources after data cleaning; Based on the output models of various types of power sources, a dual objective function is established to maximize the annual average equivalent benefits of the new energy base and minimize the annual carbon emissions; Give the constraints of the dual objective function; And establish the configuration model of the external power supply of the new energy base based on the dual objective function and constraint conditions; The non-dominated sorting genetic algorithm NSGA-II with integrated elite strategy is used to optimize the configuration model of the external power supply of the new energy base and obtain the Pareto optimal solution set; According to the specific needs of the new energy base, the most suitable configuration plan is selected from the Pareto optimal solution set.

2. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: The output models of various types of power sources are established, including thermal power output models; The thermal power output model is expressed by the following formula: P th (t)=P th_R ×η th ×α th (1) Where: P th_R is the rated installed power of the thermal power unit; η th is the average efficiency of thermal power units; α th is the output factor of the thermal power unit; the output factor is expressed by the following formula: Where: P re (t) is the power demand of the receiving power grid; P ot (t) refers to the output of other types of power sources except thermal power units.

3. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: The output models of various types of power sources are established, including a nuclear power output model; The output model of the nuclear power output model is expressed by the following formula: P nc (t)=P nc_R ·or nc (3) Where: P nc_R is the rated installed capacity of nuclear power; η nc is the average efficiency of nuclear power plants.

4. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: The output models of various types of power sources include a photovoltaic output model; the photovoltaic output model is represented by the following formula: Where: P pv_R is the rated installed power, G(t) is the light intensity at time t, G STC is the light intensity under standard test conditions; k is the power temperature coefficient; η PV is the efficiency of the photovoltaic power generation system; T C (t) is the temperature of the photovoltaic panel at time t, T STC is the reference temperature; Where: T EN (t) is the ambient temperature at that time.

5. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: The output models of various types of power sources include wind power output models; the wind power output model is represented by the following formula: Where: u ci is the cut-in wind speed; u R is the rated wind speed, P wi_R is the rated power; u co To cut out wind speed.

6. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: The output model also includes an energy storage output model; the charging process of the energy storage output model is expressed by the formula: E(t)=(1-σ sdr Δt)E(t-1)+P ESS (t)Δtη c (7) The discharge process is expressed as: E(t)=(1-σ sdr Δt)E(t-1)-P ESS (t)Δtη D (8) Where, E(t) is the remaining power of the energy storage medium at the end of time t; P ESS is the charge and discharge power of the energy storage medium at time t; sdr is the self-discharge rate of the energy storage medium; η C and η D are the charging and discharging efficiencies of the energy storage medium, respectively; Δt is the duration of each calculation window; The maximum allowable charge and discharge power of the energy storage medium at time t is determined by its own charge and discharge characteristics and the remaining power at time t, and its expression is as follows; While charging: P st (t)=min{P max,C ,[E max -(1-s sdr Δt)E(t-1)]| / η C Δt} (9) When discharging: P st (t)=-min{P max,D ,[(1-σ sdr Δt)E(t-1)-E min ]or D / Δt} (10) Where P st (t) is the maximum allowable charge and discharge power of the energy storage medium at time t; P max,C and P max,D are the maximum charging and discharging power of the energy storage medium, respectively, and P max,C and P max,D The values ​​of are all positive; E max and E min are the upper and lower limits of the energy storage medium capacity constraints respectively.

7. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: Based on the output models of various types of power sources, a dual objective function is established to maximize the annual average equivalent benefits of the new energy base and minimize the annual carbon emissions. Specifically, The objective function is established by maximizing the annual average equivalent income of the new energy base as follows: f1=max(IC) (11) Among them, I is the average annual income of the new energy base, and C is the average annual cost of the new energy base; Where: Q i is the average annual power output of different types of power sources; Price i The on-grid electricity price of different types of power sources needs to be determined according to national or local policies; Isub j is the government subsidy income for photovoltaic, wind power and energy storage power stations; r is the discount rate; m j The life cycle of photovoltaic, wind power and energy storage power stations; C is the average annual cost of the new energy base, which can be expressed as follows: Where: C i ,RE i are the initial construction investment and residual value of thermal power, photovoltaic power, wind power, nuclear power and energy storage station respectively; K i It is the operation and maintenance cost coefficient of thermal power, photovoltaic, wind power, nuclear power and energy storage station; The objective function is established by minimizing annual carbon emissions as follows: f2=min(CE con +CE ope +CE ret ) (15) Among them, CE con ,CE ope ,CE ret They are the average annual carbon emissions of the construction, operation and decommissioning stages of various types of power sources and energy storage stations in new energy bases allocated to their entire life cycle; Where: C i EF and EF are the initial construction investments of thermal power, photovoltaic power, wind power, nuclear power and energy storage stations respectively; con,i is the carbon emission factor of the corresponding power source type or energy storage station during the construction process; m i The life cycle of the corresponding power source type and energy storage station; Where: Q i is the average annual power output of different types of power sources; EF ope,i The carbon emission factors generated by the consumption of raw materials during the operation phase of different power types; Where: RE i are the residual values ​​of thermal power, photovoltaic power, wind power, nuclear power and energy storage stations; EF ret,i is the carbon emission factor of the corresponding power source type or energy storage station.

8. The method for optimizing the structure of power supply delivered from a new energy base according to claim 1, characterized in that: The constraints include: power balance constraints, power output constraints, energy storage station operation constraints, transmission channel utilization hour constraints, wind and solar power abandonment rate constraints, and new energy power proportion constraints; The power balance constraint is expressed as follows: P th (t)+P nc (t)+P pv (t)+P wi (t)+P st (t)=P re (t)(19) Where: P th (t), P nc (t), P pv (t), P wi (t), P st (t) are the real-time outputs of thermal power, nuclear power, photovoltaic power, wind power and energy storage respectively; P re (t) is the power demand of the receiving power grid; The power output constraint is expressed as follows: Where: P th_R , P nc_R , P pv_R , P wi_R They are the installed capacity of thermal power, nuclear power, photovoltaic power and wind power in large-scale new energy bases; The energy storage station operation constraints are expressed as follows: E min ≤E(t)≤E max (21) Where: E(t) is the remaining power of the energy storage medium at the end of time t; E max and E min are the upper and lower limits of the energy storage medium capacity constraints respectively; The hourly constraint of the outbound channel is expressed as follows: Where: P dc_R is the rated transmission capacity of the new energy base transmission channel; T dc_min The minimum utilization hours of the transmission channel of the new energy base; The wind and solar power abandonment rate constraint is expressed as follows: Where: P pv_R , P wi_R are the installed capacity of photovoltaic and wind power in large-scale new energy bases; T wi , T pv are the theoretical utilization hours of local wind power and photovoltaic power respectively; R wi , R pv are the maximum values ​​of wind and solar power abandonment rates respectively; The new energy electricity proportion constraint is expressed as follows: Where: R dc It is the minimum value of the proportion of electricity from new energy sources such as wind and solar power transmitted through the transmission channel.

9. A new energy base outbound power supply structure optimization system, characterized in that: A method for optimizing the structure of power transmission from a new energy base can be implemented as described in any one of claims 1 to 8; comprising: Model building module, used to build output models of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations; A new energy base transmission power configuration model building module, based on the output model established by the model building module, builds a dual objective function of maximizing the annual average equivalent income of the new energy base and minimizing the annual carbon emissions, with the scale of thermal power, nuclear power, photovoltaic, wind power and energy storage power stations as decision variables, and a new energy base transmission power configuration model based on source-load power balance, power output, energy storage charging and discharging, transmission channel utilization hours, wind and solar power abandonment rate and new energy power proportion as conditions; The optimization calculation module uses the non-dominated sorting genetic algorithm NSGA-II with an integrated elite strategy to optimize the configuration model of the external power supply of the new energy base and obtain the Pareto optimal solution set; The scheme selection module selects the most suitable configuration scheme from the Pareto optimal solution set obtained by the optimization calculation module according to the specific needs of the new energy base.

10. A computer-readable storage medium, characterized in that: Computer program instructions that can be executed by a processor are stored thereon. When the processor executes the computer program instructions, a method for optimizing the structure of external power supply from a new energy base as described in any one of claims 1-8 can be implemented.

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