New energy base photo-thermal and electrochemical energy storage configuration method considering frequency support

Abstract

The invention relates to the technical field of electric power, and particularly discloses a new energy base photo-thermal and electrochemical energy storage configuration method considering frequency support, which comprises the following steps: establishing a virtual inertia model of a photo-thermal power station and electrochemical energy storage, and simulating the inertia response of a synchronous generator set by controlling the output power of an electrochemical energy storage system; obtaining a virtual inertia constant of the electrochemical energy storage system; performing uncertainty modeling on wind and light power generation output; based on deterministic constraint conditions, constructing a photo-thermal heat storage and electrochemical energy storage capacity optimization configuration model; and inputting the virtual inertia constant into the photo-thermal heat storage and electrochemical energy storage capacity optimization configuration model for solving, and determining the heat storage capacity of the photo-thermal power station and the rated power and capacity of electrochemical energy storage. The method has the advantages that the capacities of photo-thermal heat storage and electrochemical energy storage are optimally configured, and the frequency supporting capacity and the climbing peak regulation capacity of the system can be remarkably improved, so that the stability and the reliability of the power system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and particularly to a method for configuring solar thermal and electrochemical energy storage in a new energy base considering frequency support. Background Art

[0002] With the advancement of energy transformation and the rapid development of clean energy, solar thermal power plants, as an important part of the renewable energy system, have received extensive attention. A solar thermal power plant with a heat storage system not only has the characteristics of being renewable, clean, and sustainable, but also has a frequency support ability and flexibility regulation ability comparable to thermal power units. It is an indispensable flexibility resource for achieving 100% new energy penetration. The "solar thermal energy storage +" new energy base has become a new route for exploring multi-energy complementarity and integrated development.

[0003] Currently, there have been many studies on the optimal configuration of the "solar thermal energy storage +" new energy base. To address the challenges brought by the time-varying electricity price mechanism in the electricity spot market and the grid connection of renewable energy, many studies have focused on the heat storage optimization configuration and comprehensive performance improvement of the new energy-solar thermal combined power generation system. These studies have fully considered the coupling relationship between power generation units, market electricity price changes, and the characteristics of wind and solar resources, and designed various optimization models. Among them, some models aim to achieve the optimal configuration of the heat storage system and power generation plan to improve the efficiency and economy of the external transmission capacity; some have deeply studied the performance and economy of solar thermal power plants, and determined the optimal configuration of the collector area and heat storage capacity by comprehensively considering factors such as power generation efficiency, cost, reliability, and confidence capacity. In addition, there are also studies that have proposed a rolling optimization configuration model for the challenges of grid frequency modulation stability, and optimized the operation strategy of the thermal energy storage system of solar thermal power plants. At the same time, in order to enhance the ability of the power system to cope with the fluctuations of renewable energy, an innovative optimization model of the solar thermal-pumped storage-battery composite energy storage system has been developed. By optimizing the capacity configuration of the hybrid energy storage device, the cost is reduced and the system stability is enhanced. Another study has proposed a deep peak shaving cost model to evaluate the efficiency loss compensation mechanism of solar thermal power plants when reducing output, and developed a day-ahead optimal scheduling model to reduce the system operation cost. These studies provide strong support for the optimal design and operation of the new energy-solar thermal combined power generation system.

[0004] The current research on the optimal configuration of solar thermal energy storage capacity mainly focuses on improving new energy power generation efficiency, reducing costs, enhancing grid stability, etc. Moreover, in terms of enhancing grid stability, the frequency modulation ability and peak shaving ability are studied separately, and there are few articles that consider both the frequency support ability and peak shaving ability of solar thermal power plants at the same time. The frequency support ability and peak shaving ability belong to the flexibility regulation abilities of short time scales and medium to long time scales respectively, and both abilities are crucial for enhancing the flexibility of the "solar thermal energy storage +" new energy base. Summary of the Invention

[0005] The object of the present invention is to overcome the shortcomings of the prior art and provide a method for configuring solar thermal and electrochemical energy storage in a new energy base considering frequency support.

[0006] The object of the present invention is achieved by the following technical solutions: A method for configuring solar thermal and electrochemical energy storage in a new energy base considering frequency support, including:

[0007] Based on the frequency support requirements of the power system, establish a virtual inertia model of the solar thermal power plant and the electrochemical energy storage, equivalently convert the inertia response ability of the synchronous generator set and the virtual inertia of the electrochemical energy storage system, and simulate the inertia response of the synchronous generator set by controlling the output power of the electrochemical energy storage system to obtain the virtual inertia constant of the electrochemical energy storage system.

[0008] Model the uncertainty of the wind and solar power output, adopt the chance-constrained programming model, quantify the prediction error of the wind and solar power output through the normal distribution, and convert it into a deterministic constraint condition.

[0009] Based on the deterministic constraint conditions, construct an optimization configuration model for the solar thermal energy storage and the electrochemical energy storage capacity with the goal of maximizing the system frequency support ability and minimizing the comprehensive operation cost.

[0010] Input the virtual inertia constant into the optimization configuration model for the solar thermal energy storage and the electrochemical energy storage capacity to solve, determine the heat storage capacity of the solar thermal power plant and the rated power and capacity of the electrochemical energy storage, and output the optimization configuration plan.

[0011] Specifically, the rotor mechanical energy of the synchronous generator set is expressed by the following formula:

[0012]

[0013] where, E k is the mechanical energy of the rotor; J S is the moment of inertia of the synchronous generator; p n 2 is the number of pole pairs of the generator; ω k is the angular velocity of the synchronous generator;

[0014] The system inertia constant H of the synchronous generator set sys is defined as the ratio of the rotor mechanical energy to the unit capacity:

[0015]

[0016] where, E n,k is the kinetic energy of each generator rotor; S n is the rated capacity of each generator, and N is the number of synchronous generator sets in the system. Specifically, the electrochemical energy is equivalently converted into the rotor kinetic energy:

[0017]

[0018] Wherein, E e is the electrochemical energy, in J e is the equivalent moment of inertia of the electrochemical energy storage system;

[0019]

[0020] Wherein, k e is the virtual inertia control coefficient;

[0021] The virtual inertia constant H of the electrochemical energy storage system is obtained through formula (3) and formula (4) e :

[0022]

[0023] Take k e as 1, at this time the virtual inertia of the electrochemical energy storage system is half of the current energy.

[0024] Specifically, the chance-constrained programming model is expressed as:

[0025]

[0026] Wherein: Pr{·} is the probability that a random event occurs; g k (x i , ξ j ) ≤ 0 is the constraint condition containing random variables; y l (x i ) is the rigid constraint condition to be satisfied; x i is the decision variable; ξ j is the random variable; k and l are the numbers of constraint conditions respectively; f represents the minimum value of the probability that the decision makes the constraint condition hold not less than the confidence level α, and g k (x i , ξ j ) is the prediction error of the wind and light output.

[0027] Specifically, in step S2, a prediction error model of wind and light power is constructed through a normal distribution:

[0028]

[0029] Wherein: X i and Y i are random variables; is the variance; is the power prediction error of the photovoltaic; is the power prediction error of the wind power.

[0030] Specifically, the chance-constrained programming model is converted into a deterministic equivalent form and linearized, where g(x, ξ) is transformed into g(x, ξ) = h(x) - ξ; the constraint Pr{g k (x i , ξ j ) ≤ 0} ≥ α, (k = 1, 2,..., n) can be converted to:

[0031] Pr{h k (x i ) ≤ ξ j} ≥ α, (k = 1, 2,..., n) (9)

[0032] If there exists a number K a such that the probability that K a ≤ ξ is α, then as long as h(x) ≤ K a ≤ ξ, the constraint Pr{g k (x i , ξ j ) ≤ 0} ≥ α, (k = 1, 2,..., n) can be satisfied. According to the random variable ξ and the distribution function φ, the chance constraint condition is transformed into a deterministic rigid constraint condition:

[0033] h(x) ≤ φ -1 (1 - α) (2)

[0034] where: φ -1 represents the inverse cumulative probability density function of the random variable ξ.

[0035] Specifically, the comprehensive objective function of the optimization configuration model of the solar-thermal energy storage and electrochemical energy storage capacity is expressed as:

[0036]

[0037] where F is the comprehensive optimization objective of the maximum frequency stability support ability and the lowest comprehensive operation cost; f 1 (x) is the objective of maximizing the system inertia constant, f 2 (x) is the objective of maximizing the primary frequency regulation reserve capacity of the system; f 3 (x) is the objective of minimizing the comprehensive cost of the CSP power station, is the relative minimum inertia, △P t L is the load change value at time t, f 0 is the nominal frequency of the system, RoCoF max is the maximum value of the frequency change rate, are the primary frequency regulation reserve capacities of the i-th electric energy storage, thermal power unit, and solar-thermal power station respectively, C sys is the comprehensive cost of the system: T is the time period of the optimization configuration, taking 8760 hours, Ng , N csp and N E are the numbers of thermal power units, solar thermal power units, and electrochemical energy storage respectively;

[0038] min f 3 (x) = min(C sys ) = min(C csp + C g + C w + C v + C e ) (12)

[0039] Wherein, C csp is the comprehensive operating cost of the CSP power station, C g is the thermal power cost, C w is the curtailment cost of wind power, C v is the curtailment cost of photovoltaic power, C e is the energy storage investment cost.

[0040] Specifically, the constraint conditions of the optimization configuration model for the solar thermal energy storage and electrochemical energy storage capacity include system power balance constraints, solar thermal power station operation constraints, thermal power constraints, electrochemical energy storage constraints, wind-solar constraints, and frequency security constraints.

[0041] A photovoltaic-thermal and electrochemical energy storage configuration device for a new energy base considering frequency support, comprising:

[0042] A virtual inertia constant calculation module for constructing a virtual inertia model of a solar thermal power station and an electrochemical energy storage;

[0043] A constraint condition generation module for constructing a chance-constrained programming model to obtain deterministic constraint conditions;

[0044] A configuration generation module for constructing an optimization configuration model for the solar thermal energy storage and electrochemical energy storage capacity according to the deterministic constraint conditions, and taking maximizing the system frequency support ability and minimizing the comprehensive operating cost as the objectives, and inputting the virtual inertia constant calculated by the virtual inertia constant calculation module into the optimization configuration model for the solar thermal energy storage and electrochemical energy storage capacity to generate an optimization configuration plan.

[0045] A computer device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the steps of the photovoltaic-thermal and electrochemical energy storage configuration method for a new energy base considering frequency support are implemented.

[0046] A computer program product, comprising computer programs / instructions, which implement the steps of the photovoltaic-thermal and electrochemical energy storage configuration method for a new energy base considering frequency support when executed by a processor.

[0047] The present invention has the following advantages:

[0048] The optimization configuration model of the heat storage capacity and the electrochemical energy storage capacity of the solar thermal power station proposed by the present invention takes into account the flexibility adjustment capabilities on short time scales and medium to long time scales, namely the frequency support capability and the peak shaving capability. This is crucial for enhancing the flexibility of the "solar thermal energy storage +" new energy base. By optimizing the configuration of the heat storage of the solar thermal power and the capacity of the electrochemical energy storage, the present invention can significantly improve the frequency support capability and the ramp peak shaving capability of the system, thereby enhancing the stability and reliability of the power system. The present invention uses the chance-constrained programming (CCP) model in uncertainty modeling to handle the uncertainty of wind and solar power generation. By quantifying the prediction error of wind and solar power generation, the impact on the power system is reduced, and the accuracy and practicality of the model are improved. Brief Description of the Drawings

[0049] Figure 1 It is a schematic flow chart of the configuration method of the present invention;

[0050] Figure 2 It is a schematic diagram showing the influence of the heat storage duration on the capacity of the solar thermal power station and the electrical energy storage;

[0051] Figure 3 It is a schematic diagram showing the influence of the heat storage duration on the frequency support capability and the cost;

[0052] Figure 4 It is a schematic diagram showing the influence of the increase in the capacity of the solar thermal power station on the system under fixed parameters;

[0053] Figure 5 It is a schematic diagram showing the influence of the change in the capacity of the solar thermal power station on the system;

[0054] Figure 6 It is a schematic diagram showing the influence of the change in the capacity of the solar thermal power station on the electrical energy storage;

[0055] Figure 7 It is a schematic diagram showing the influence of the wind-solar ratio on the capacity of the solar thermal power station and the electrical energy storage;

[0056] Figure 8 It is a schematic diagram showing the influence of the wind-solar ratio on the frequency support capability and the cost;

[0057] Figure 9 It is a schematic diagram showing the influence of the wind-solar ratio on the capacity of the solar thermal power station and the electrical energy storage when the thermal power is 0;

[0058] Figure 10 It is a schematic diagram showing the influence of the wind-solar ratio on the frequency support capability and the cost when the new energy penetration rate is 100%; Detailed Embodiments

[0059] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Usually, the components of the embodiments of the present invention described and shown in the accompanying drawings herein can be arranged and designed in various different configurations.

[0060] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0061] It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0062] The present invention will be further described below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following. As Figures 1 to 10 shown, a method for configuring solar thermal and electrochemical energy storage in a new energy base considering frequency support, characterized by comprising the following steps:

[0063] Step S1: Based on the frequency support requirements of the power system, establish a virtual inertia model for the solar thermal power plant and the electrochemical energy storage. Equivalently convert the inertial response ability of the synchronous generator set and the virtual inertia of the electrochemical energy storage system. Simulate the inertial response of the synchronous generator set by controlling the output power of the electrochemical energy storage system to obtain the virtual inertia constant of the electrochemical energy storage system. During the frequency regulation process, the synchronous generator set is the main resource, providing inertia support and frequency regulation ability on a long time scale. The electrochemical energy storage system can also provide virtual inertia and primary frequency regulation support. The inertial response of the synchronous generator set is simulated through the virtual inertia droop control method. The primary frequency regulation ability is related to the system frequency regulation reserve capacity. In terms of the inertial response ability, there are significant differences between the synchronous generator set and the electrochemical energy storage. The inertial support ability of the synchronous generator set is fixed and related to the inherent inertia constant and the rated capacity. The electrochemical energy storage system provides inertial support mainly considering the short time scale. The virtual inertia is related to the transient parameters. If it is necessary to consider both the short time scale frequency support ability and the medium and long time scale system capacity optimization, the virtual inertia of the electrochemical energy storage system needs to be related to its inherent characteristics such as the rated power and the rated electricity.

[0064] The inertia constant of the synchronous generator set is related to the mechanical energy of the rotor. The mechanical energy of the rotor of the synchronous generator set is expressed by the following formula:

[0065]

[0066] In the formula, E k is the mechanical energy of the rotor; J S is the moment of inertia of the synchronous generator; is the number of pole pairs of the generator; ω k is the angular velocity of the synchronous generator;

[0067] The system inertia constant H sys of the synchronous generator set is defined as the ratio of the mechanical energy of the rotor to the unit capacity:

[0068]

[0069] In the formula, E n,k is the kinetic energy of each generator rotor; S n is the rated capacity of each generator, and N is the number of synchronous generator sets in the system. When the system has a frequency deviation, the electrochemical energy storage system participates in the inertial response by controlling the rapid increase of the output power. The power of the synchronous generator set providing the inertial response comes from the rotor kinetic energy, while the power of the electrochemical energy storage system comes from the electrochemical energy. Therefore, when deriving the virtual inertia applicable to the medium and long time scale of the electrochemical energy storage system, the electrochemical energy is regarded as the equivalent rotor kinetic energy. The electrochemical energy E e is given by the following formula:

[0070]

[0071] In the formula, E e is the electrochemical energy, in J e is the equivalent moment of inertia of the electrochemical energy storage system;

[0072]

[0073] In the formula, k e is the virtual inertia control coefficient;

[0074] The virtual inertia constant H of the electrochemical energy storage system is obtained through formula (3) and formula (4) e :

[0075]

[0076] Take k e as 1. At this time, the virtual inertia of the electrochemical energy storage system is half of the current energy.

[0077] Model the uncertainty of the output of wind and solar power. Adopt the chance-constrained programming model. Quantify the prediction error of wind and solar power output through the normal distribution and convert it into deterministic constraint conditions; The chance-constrained programming model quantifies the uncertainty of wind and solar power generation by tolerating a certain deviation of new energy output with a confidence probability;

[0078] The said chance-constrained programming model is expressed as:

[0079]

[0080] In the formula, Pr{·} is the probability of the random event occurring; g k (x i , ξ j ) ≤ 0 is the constraint condition containing random variables; y l (x i ) is the rigid constraint condition that needs to be satisfied; x i is the decision variable; ξ j is the random variable; k and l are the numbers of constraint conditions respectively; represents the minimum value that makes the probability of the constraint condition hold not less than the confidence level α, and g k (x i , ξ j ) is the prediction error of wind and solar power output.

[0081] Construct the prediction error model of wind and solar power through the normal distribution:

[0082]

[0083] In the formula: X i , Y i are random variables; is the variance; is the power prediction error of the photovoltaic; is the power prediction error of the wind power.

[0084] Chance-constrained programming belongs to the category of nonlinear programming problems. In order to enable the model to call the CPLEX solver in MTALB - YALMIP for optimization operations, it is necessary to convert the chance-constrained conditions into a deterministic equivalent form and linearize them. The present invention uses an analytical method for deterministic transformation. When the decision variables and random variables can be separated, the chance-constrained programming model is converted into a deterministic equivalent form and linearized. Among them, g(x,ξ) is transformed into g(x,ξ) = h(x) - ξ; the constraint condition Pr{g k (x i ,ξ j ) ≤ 0} ≥ α, (k = 1, 2,..., n) can be transformed into:

[0085] Pr{h k (x i ) ≤ ξ j} ≥ α, (k = 1, 2,..., n) (9)

[0086] If there exists a number K a , such that the probability that K a ≤ ξ is α, then as long as h(x) ≤ K a ≤ ξ at this time, the constraint condition Pr{g k (x i ,ξ j ) ≤ 0} ≥ α, (k = 1, 2,..., n) can be satisfied. According to the random variable ξ and the distribution function φ, the chance-constrained condition is transformed into a deterministic rigid constraint condition:

[0087] h(x) ≤ φ -1 (1 - α) (3)

[0088] In the formula, φ -1 represents the inverse cumulative probability density function of the random variable ξ;

[0089] Based on the deterministic constraint conditions, an optimal configuration model for the thermal energy storage and electrochemical energy storage capacity of a solar thermal power plant is constructed with the goal of maximizing the system frequency support capacity and minimizing the comprehensive operating cost;

[0090] The virtual inertia constant is input into the optimal configuration model for the thermal energy storage and electrochemical energy storage capacity of a solar thermal power plant for solution to determine the heat storage capacity of the solar thermal power plant and the rated power and capacity of the electrochemical energy storage, and an optimal configuration plan is output.

[0091] The economy in the planning problem is a key factor. Most domestic and foreign studies take the lowest overall operating cost of the system as the objective function. Starting from the overall benefits after the addition of CSP power plants, this invention takes into account the investment cost, operating cost, and frequency support ability, uses the CSP power plant and the electrochemical energy storage capacity as decision variables, and takes the strongest frequency support ability and the lowest overall operating cost of the CSP power plant as the comprehensive objective function. The comprehensive objective function of the optimized configuration model of the solar thermal energy storage and electrochemical energy storage capacity is expressed as:

[0092]

[0093] In the formula, F is the comprehensive optimization objective of the maximum frequency stability support ability and the lowest overall operating cost; f 1 (x) is the objective of maximizing the system inertia constant, and f 2 (x) is the objective of maximizing the primary frequency regulation reserve capacity of the system; f 3 (x) is the objective of the lowest comprehensive cost of the CSP power plant, is the relative minimum inertia, is the load change value at time t, and f 0 is the nominal frequency of the system, and RoCoF max is the maximum value of the frequency change rate, are the primary frequency regulation reserve capacities of the i-th electric energy storage, thermal power unit, and solar thermal power plant respectively. T is the time period of the optimized configuration, taking 8760 hours, and N g 、N csp and N E are the numbers of thermal power units, solar thermal units, and electrochemical energy storage respectively. C sys is the overall cost of the system:

[0094] f 1 (x) describes the system inertia margin with the gap from the relative minimum inertia requirement to represent the objective of maximizing the system inertia constant:

[0095]

[0096] f 2 (x) describes the primary frequency regulation reserve margin with the primary frequency regulation reserve capacity of the system to represent the objective of maximizing the primary frequency regulation reserve capacity of the system:

[0097]

[0098] For the annual dispatch, this study considers that the comprehensive cost includes the operating costs of solar thermal power plants, thermal power units, wind power generation, photovoltaic power generation, and electrochemical energy storage systems, as well as the investment costs of solar thermal power plants and electrochemical energy storage systems, to form the objective of the lowest comprehensive cost f 3 (x):

[0099] min f 3 (x) = min(C sys ) = min(C csp + C g + C w + C v + C e ) (12)

[0100] Wherein, C csp is the comprehensive operation cost of the CSP power station, C g is the thermal power cost, C w is the curtailment cost of wind power, C v is the curtailment cost of solar power, C e is the energy storage investment cost. Taking the peak shaving cost CSP power station operation cost CSP power station investment cost C INV The sum of the three is used as the comprehensive operation cost of the CSP power station. Since the factors involved in the CSP power station investment cost are numerous, in order to simplify the model, the present invention only considers the construction costs of three sub-modules, namely SF, PB, and TES;

[0101]

[0102] Wherein, is the output of the solar thermal power station; is the peak shaving cost coefficient; η 1 , η 2 , η 3 are the unit load factors of the units; is the output of the solar thermal power station; b i , k i , S i are the cost coefficients; C SF is the construction cost of SF, C PB is the construction cost of PB, C TES is the construction cost of TES, U i,t is the start-stop state of the unit.

[0103] The thermal power cost includes the power generation cost of the unit, the flexible start-stop cost of thermal power, and the load shedding cost of the system:

[0104]

[0105] Wherein, and are respectively the unit power generation cost and the unit start-stop cost of thermal power i; is the thermal power output, the primary frequency regulation reserve capacity, and the start-stop capacity of thermal power i at time t.

[0106] The wind and solar cost mainly considers the curtailment cost of wind and solar power:

[0107]

[0108]

[0109] In the formula: are the unit costs of curtailed wind power and curtailed solar power respectively; are the curtailed power of the i-th wind power and photovoltaic power at time t respectively.

[0110] The energy storage investment cost mainly considers the investment cost of the power module of the energy storage and the investment cost of the energy storage part:

[0111]

[0112] In the formula, is the unit power investment cost of the energy storage; is the rated power of the i-th energy storage; is the unit capacity investment cost of the energy storage; is the rated capacity of the i-th energy storage.

[0113] Furthermore, the constraint conditions of the optimization configuration model of the solar thermal energy storage and electrochemical energy storage capacity include system power balance constraint, solar thermal power plant operation constraint, thermal power constraint, electrochemical energy storage constraint, wind-solar constraint and frequency security constraint.

[0114] The system power balance constraint is:

[0115]

[0116] In the formula, are the outputs of wind power generation and photovoltaic power generation respectively, are the charging and discharging powers of the energy storage system respectively, is the load power, is the load shedding power of the load at time t. The prediction errors of wind-solar output directly affect the actual output fluctuations of wind power generation and photovoltaic power generation; through chance-constrained programming, they are modeled as random variables and transformed into deterministic constraint conditions, so that the optimization model can comprehensively consider the influence of prediction errors on the outputs of wind power generation and photovoltaic power generation, and finally realize the stable and economic operation of a high-proportion renewable energy power grid.

[0117] The solar thermal power plant operation constraint is:

[0118]

[0119] In the formula, is the operation state of the i-th solar thermal power plant (1 represents operation, 0 represents shutdown), is the minimum output of the i-th unit, are the minimum start-up and shutdown times of the \(i\)-th thermal power unit respectively, are the up and down ramp rates of the \(i\)-th CSP plant respectively, is the available thermal power of the CSP plant generated from solar irradiance data, is the efficiency of the power generation link, are the charging and discharging powers of the thermal energy storage system respectively, is the current capacity of the thermal energy storage system, is the charging and discharging efficiency of the thermal energy storage system, is the minimum capacity of the thermal energy storage system, \(\rho\) FLH is the number of hours that the CSP plant operates without sunlight at the rated power; is the maximum output thermal power of the TES.

[0120] Thermal power constraint:

[0121]

[0122] In the formula, is the operating state of the \(i\)-th thermal power unit (1 represents operating, 0 represents shutdown), is the minimum technical output of the \(i\)-th unit, is the maximum technical output of the \(i\)-th unit, is the minimum start-up time of the \(i\)-th thermal power unit, is the minimum shutdown time of the \(i\)-th thermal power unit, are the up and down ramp rates of the \(i\)-th thermal power unit respectively.

[0123] The electrochemical energy storage constraint is:

[0124]

[0125] In the formula, are the charge and discharge states respectively, is the rated capacity of the electrical energy storage system, is the charging and discharging efficiency of the electrical energy storage system, is the current capacity of the electrical energy storage system, are the maximum and minimum capacities of the electrical energy storage system respectively.

[0126] Wind and solar constraint is:

[0127]

[0128] In the formula, are the maximum outputs of wind power and photovoltaic power respectively.

[0129] Frequency security constraint, the inertia of the system is the sum of the inertias of the currently operating thermal power units, CSP plants and the virtual inertia of the electrochemical energy storage, are the inertia constants of the i-th thermal power unit and the CSP plant, respectively, is the virtual inertia of the i-th electrochemical energy storage system, is the start-stop status of the thermal power unit and the CSP plant, is the rated capacity of the thermal power unit and the CSP plant.

[0130]

[0131] In the process of ensuring system frequency security, it is crucial to evaluate two key indicators, RoCoF and Nadir, which reflect the system's frequency support ability. RoCoF reflects the rapidity of frequency change after an emergency event occurs, while Nadir refers to the lowest frequency reached before the frequency recovery process

[21] . Therefore, when considering frequency security constraints, it is necessary to ensure that the frequency change rate does not exceed the preset threshold. At the same time, it is also necessary to ensure that the lowest point of the frequency is higher than the minimum value f min , and the frequency security constraint is given by the following formula:

[0132]

[0133]

[0134] In the formula: △P t L is the load change value at time t, and △f bd is the dead zone of the governor.

[0135] Frequency support ability evaluation index

[0136] The frequency support ability coefficient FSCC (Frequency Support Capability Coefficient) is used to evaluate the system's frequency support ability. FSCC consists of inertia support ability and primary frequency regulation ability, and its equation is as follows.

[0137]

[0138] Taking the historical data of a wind-solar new energy base in Gansu as the original data. The corresponding load capacity of this base is 3000 MW, the total installed capacity of wind and solar is 3070 MW, of which the installed capacity of wind power is 1514 MW and the installed capacity of photovoltaic is 1556 MW. The main parameters of the CSP plant are shown in the following table:

[0139] Table 1 CSP plant parameters

[0140]

[0141] The thermal energy storage system is the key for a solar thermal power plant to overcome the intermittency problem of solar energy resources. The energy storage duration is the core parameter of the thermal energy storage system, usually measured by "Full Load Hours" (FLH), which refers to the continuous number of hours that the thermal energy storage system can support power generation when operating at the full load capacity of the power plant. It directly affects the power output capacity of the power plant when there is no solar energy input (such as at night or on cloudy days). Under the actual boundary of the base, by adjusting the energy storage duration, from Figure 2 The results show that when the energy storage duration increases, the installed capacity of the solar thermal power plant gradually decreases, and the rated power of the electrochemical energy storage gradually increases.

[0142] From Figure 3 The results show that when the energy storage duration increases, the system FSCC gradually decreases. When the energy storage duration increases, the total system cost first decreases and then increases, and the inflection point of change is when the energy storage duration is 10 hours. Therefore, for the example of this invention, it is most appropriate to set the energy storage duration of the solar thermal power plant to 10 hours.

[0143] Optimization calculations are carried out according to the actual installed capacity of the base, and the results are shown in the following table. The optimized configuration capacity of the solar thermal power plant is 1560 MW, the optimized configuration capacity of the rated power of the electrochemical energy storage is 451.4 MW, the rated electricity is 1475.5 MWh, the rated discharge time of the energy storage is about 3 hours, the total cost is 14.26 billion yuan, and the FSCC is 1.2011. Reducing the installed capacity of thermal power in the new energy base of wind and solar is crucial for the green transformation of energy. The reduction of thermal power capacity can increase the proportion of renewable energy and enhance the cleanliness and sustainability of the power grid. At the same time, the low marginal cost of renewable energy helps to reduce the operation cost of the power grid, improve the economic efficiency of the system, and enhance the operation flexibility of the power system. Therefore, optimization calculations are carried out by gradually reducing the installed capacity of thermal power. According to the results in Table 2, as the installed capacity of thermal power gradually decreases, the installed capacity of the solar thermal power plant, the capacity of the electrochemical energy storage, and the comprehensive cost of the system all show a gradually increasing trend. Especially when the new energy penetration rate is 100%, that is, when the installed capacity of thermal power drops to 0, the installed capacity of the solar thermal power plant reaches 4695 MW, which is an increase of 3135 MW compared with the case where the installed capacity of thermal power is 1560 MW, and the increase exceeds twice the thermal power capacity. This is because the power generation output of the solar thermal power plant is affected by the light intensity and almost no energy input can be obtained at night. At the same time, due to the significant increase in the installed capacity of the solar thermal power plant, the FSCC also increases accordingly.

[0144] Table 2 Optimization calculation results

[0145]

[0146] To evaluate the impact of the CSP power plant capacity connection on the operation characteristics of this base, first, while keeping the installed capacity of other power sources in this base unchanged, increase the installed capacity of the solar thermal power plant from 1600 MW to 2400 MW. FromFigure 4 As shown in the figure, when the installed capacity of the solar thermal power plant gradually increases, both the FSCC and the system comprehensive cost gradually increase.

[0147] Secondly, restore the rated power and rated capacity of the electrochemical energy storage to decision variables, and adjust the installed capacity of the solar thermal power plant from 800 MW to 2400 MW. Figure 5 The results show that when the installed capacity of the solar thermal power plant gradually increases, the FSCC also gradually increases. However, when the installed capacity of the solar thermal power plant is less than 1400 MW, as the installed capacity of the solar thermal power plant increases, the system comprehensive cost rapidly decreases. When the installed capacity of the solar thermal power plant is greater than 1400 MW, as the installed capacity of the solar thermal power plant increases, the system comprehensive cost begins to gradually rise.

[0148] From Figure 6 The results show that when the installed capacity of the solar thermal power plant is less than 1400 MW, as the installed capacity of the solar thermal power plant decreases, both the rated power and the rated electricity of the electrochemical energy storage rapidly increase. This indicates that when the installed capacity of the solar thermal power plant is less than 1400 MW, the output of thermal power, wind power, photovoltaic power, and solar thermal power cannot meet the load demand at most times, and the system needs the electrochemical energy storage for power support more and more frequently, resulting in a rapid increase in the rated electricity of the electrochemical energy storage and thus a rapid increase in the system comprehensive cost.

[0149] As wind energy and solar energy have become the two major pillars in the field of renewable energy, rationally allocating the wind-solar ratio to achieve the efficient utilization of resources and the stability of power generation has become an issue of wide concern in the industry and academia. Wind energy and solar energy have obvious complementarity - solar power generation mainly occurs during the day, while wind power generation depends more on night-time and unstable wind conditions. Therefore, by reasonably adjusting the wind-solar ratio, the capacity of the solar thermal power plant and the electrochemical energy storage can be further optimized, improving the economy and reliability of the entire power system.

[0150] First, under the actual boundary conditions of the base, adjust the installed capacity ratio of wind-solar power generation. The results are as Figure 7 shown. When the proportion of wind power generation gradually increases, the installed capacity of the solar thermal power plant first decreases linearly and then gradually increases. The inflection point of the installed capacity of the solar thermal power plant occurs when the wind-solar ratio is 3:1. When the proportion of wind power generation gradually increases, the rated power of the electrochemical energy storage first shows a slightly increasing trend and changes to a linear decreasing trend when the wind-solar ratio is 1:2.

[0151] According to Figure 8It can be seen from the results that when the proportion of wind power generation gradually increases, the change law of the system FSCC is similar to that of the installed capacity of the solar thermal power station, which linearly decreases, then increases, and then shows a downward trend. And due to the influence of the decrease in the capacity of the electrochemical energy storage, the increase of FSCC is relatively slow after the wind-solar ratio reaches 3:1. At the same time, when the proportion of wind power generation gradually increases, the total system cost gradually decreases. Thus, for this example, the wind-solar installed capacity ratio of 3:1 is more appropriate, because when the wind-solar installed capacity ratio is less than 3:1, although the FSCC will increase, the total system cost increases significantly; when the wind-solar installed capacity ratio is greater than 3:1, although the total system cost will further decrease, the FSCC will decline.

[0152] At the same time, considering the influence of the wind-solar ratio on the system when the new energy penetration rate is 100%, the installed capacity of thermal power is adjusted to 0, and the ratio of the installed capacity of wind power generation and solar power generation is adjusted. As Figure 9 shown, when the proportion of wind power generation gradually increases, the change laws of the installed capacity of the solar thermal power station and the rated power of the electrochemical energy storage are similar to those under the actual boundary conditions.

[0153] According to Figure 10 the results, it can be seen that when considering the new energy penetration rate of 100% and the proportion of wind power generation gradually increases, the total system cost is similar to that under the actual boundary conditions, and the inflection points of the changes in the capacity of the solar thermal power station and the electrochemical energy storage are both at the wind-solar ratio of 1:1. The change law of the system FSCC is also similar to that under the actual boundary conditions, and the decline rate of FSCC becomes significantly smaller after the wind-solar ratio reaches 1:1. Thus, for the case of a new energy penetration rate of 100%, the ideal wind power generation installed capacity ratio is 1:1.

[0154] A solar thermal and electrochemical energy storage configuration device for a new energy base considering frequency support, comprising:

[0155] A virtual inertia constant calculation module, configured to construct a virtual inertia model of a solar thermal power station and an electrochemical energy storage;

[0156] A constraint condition generation module, configured to construct an opportunity constraint programming model to obtain deterministic constraint conditions;

[0157] A configuration generation module, configured to construct an optimization configuration model for the capacity of solar thermal energy storage and electrochemical energy storage according to the deterministic constraint conditions, and taking maximizing the system frequency support ability and minimizing the comprehensive operation cost as the objectives, input the virtual inertia constant calculated by the virtual inertia constant calculation module into the optimization configuration model for the capacity of solar thermal energy storage and electrochemical energy storage to generate an optimization configuration plan.

[0158] A computer device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of a method for configuring solar thermal and electrochemical energy storage in a new energy base considering frequency support.

[0159] A computer program product includes a computer program / instructions. When the computer program / instructions are executed by a processor, they implement the steps of a method for configuring solar thermal and electrochemical energy storage in a new energy base considering frequency support.

[0160] As mentioned above, only the preferred embodiments of the present invention are described, and there is no limitation in any form to the present invention. Any person skilled in the art can make many possible changes and modifications to the technical solution of the present invention, or modify it into equivalent embodiments with equivalent changes, without departing from the scope of the technical solution of the present invention. Therefore, any changes, modifications, equivalent changes, and modifications made to the above embodiments based on the technical solution of the present invention without departing from the content of the technical solution of the present invention all fall within the protection scope of this technical solution.

Claims

1. A method for configuring solar thermal and electrochemical energy storage for a new energy base considering frequency support, characterized in that: include: Based on the frequency support requirements of the power system, a virtual inertia model of the CSP power station and electrochemical energy storage is established. The inertial response capability of the synchronous generator set is equivalently converted to the virtual inertia of the electrochemical energy storage system. The inertial response of the synchronous generator set is simulated by controlling the output power of the electrochemical energy storage system to obtain the virtual inertia constant of the electrochemical energy storage system. Model the uncertainty of wind and solar power output, adopt the chance-constrained programming model, quantify the forecast error of wind and solar power output through normal distribution, and convert it into deterministic constraints; Based on deterministic constraints, a capacity optimization configuration model for CSP and electrochemical energy storage is constructed with the objective function of maximizing the system frequency support capability and minimizing the comprehensive operating cost. The virtual inertia constant is input into the optimal configuration model of CSP heat storage and electrochemical energy storage capacity to determine the heat storage capacity of the CSP power station and the rated power and capacity of the electrochemical energy storage, and the optimal configuration plan is output.

2. The method for configuring photothermal and electrochemical energy storage in a new energy base considering frequency support according to claim 1 is characterized in that: The rotor mechanical energy of the synchronous generator set is expressed by the following formula: In the formula, E k is the mechanical energy of the rotor; J S is the moment of inertia of the synchronous generator; is the number of pole pairs of the generator; ω k is the angular velocity of the synchronous generator; The system inertia constant H of the synchronous generator set sys Defined as the ratio of rotor mechanical energy to unit capacity: In the formula, E n,k is the kinetic energy of each generator rotor; S n is the rated capacity of each generator, and N is the number of synchronous generator sets in the system.

3. The method for configuring photothermal and electrochemical energy storage in a new energy base considering frequency support according to claim 2 is characterized in that: The electrochemical energy is equivalent to the rotor kinetic energy, including: In the formula, E e is the electrochemical energy, J e is the equivalent moment of inertia of the electrochemical energy storage system; In the formula, k e is the virtual inertia control coefficient; The virtual inertia constant H of the electrochemical energy storage system is obtained by formula (3) and formula (4): e : Take k e is 1, at which point the virtual inertia of the electrochemical energy storage system is half of the current energy.

4. The method for configuring photothermal and electrochemical energy storage in a new energy base considering frequency support according to claim 1 is characterized in that: The chance constrained programming model is expressed as: Where: Pr{·} is the probability of a random event being established; g k (x i ,ξ j )≤0 is a constraint condition containing random variables; y l (x i ) is the rigid constraint condition that needs to be satisfied; x i is the decision variable; j is a random variable; k and l are the number of constraints respectively; Indicates that the probability that the decision makes the constraint condition true is not less than the minimum value of the confidence level α, g k (x i ,ξ j ) is the wind and solar power output prediction error.

5. The method for configuring photothermal and electrochemical energy storage in a new energy base considering frequency support according to claim 4 is characterized in that: The formula for quantifying the prediction error of wind and solar power output using normal distribution is: Where: X i , Y i is a random variable; is the variance; is the photovoltaic power prediction error, is the wind power prediction error.

6. The method for configuring photothermal and electrochemical energy storage in a new energy base considering frequency support according to claim 5 is characterized in that: The chance-constrained programming model is converted into a deterministic equivalent form and linearized, where g(x,ξ) is converted to g(x,ξ)=h(x)-ξ; the constraint condition Pr{g k (x i ,ξ j )≤0}≥α,(k=1,2,...,n) can be converted to: Pr{h k (x i )≤ξ j }≥α,(k=1,2,...,n) (9) If there exists a number K a , so that K a ≤ξ with a probability of α. Then, as long as h(x)≤K a ≤ξ, the condition Pr{g k (x i ,ξ j )≤0}≥α,(k=1,2,...,n) can be satisfied. According to the random variable ξ and the distribution function φ, the chance constraint is transformed into a deterministic rigid constraint: h(x)≤φ -1 (1-a) (1) Where: φ -1 represents the inverse cumulative probability density function of the random variable ξ.

7. The method for configuring photothermal and electrochemical energy storage in a new energy base considering frequency support according to claim 1, characterized in that: The comprehensive objective function of the CST and electrochemical energy storage capacity optimization configuration model is expressed as: In the formula, F is the comprehensive optimization goal of maximizing the frequency stability support capacity and minimizing the comprehensive operation cost; f1(x) is the goal of maximizing the system inertia constant, f2(x) is the goal of maximizing the primary frequency regulation reserve capacity of the system; f3(x) is the goal of minimizing the comprehensive cost of the CSP power station, is the relative minimum inertia, is the load change value at time t, f0 is the nominal frequency of the system, RoCoF max is the maximum frequency change rate, are the primary frequency regulation reserve capacities of the i-th electric energy storage, thermal power unit, and solar thermal power station, respectively. sys is the system comprehensive cost, T is the time period of the optimal configuration, which is 8760 hours, and N g 、N csp and N E They are the number of thermal power units, solar thermal units, and electrochemical energy storage units; The minimum comprehensive cost target f3(x) is: minf3(x)=min(C sys )=min(C csp +C g +C w +C v +C e ) (12) In the formula, C csp is the comprehensive operating cost of the CSP power station, C g is the thermal power cost, C w is the wind curtailment cost, C v is the cost of abandoned light, C e The investment cost of energy storage.

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