A Method and System for Deep Coupling Frequency Modulation of Energy Storage and Thermal Power Units

Abstract

The present invention relates to the technical field of power system frequency modulation, and discloses a method and system for deep coupling frequency modulation of energy storage and thermal power units, including: constructing a power system frequency modulation model containing an energy storage power supply. Taking the lowest system operation cost as the objective function, combining the constraints of thermal power units and the operation constraints of the energy storage system, constructing a thermal power - energy storage optimal scheduling model considering frequency response constraints. Decomposing the optimal scheduling model into a master problem and a sub - problem, and obtaining the unit output power plan that meets the system frequency modulation requirements and operation constraints through iterative solution. According to the obtained unit output power plan, the output powers of thermal power units and the energy storage system are adjusted in real time to achieve stable frequency regulation of the power system. The present invention realizes the rapid response and flexible adjustment of frequency modulation resources, improves the frequency modulation efficiency of the power system. The optimal scheduling model effectively reduces the operation cost of the power system. It ensures that the power system can still operate stably under the condition of large - scale grid connection of new energy sources.

Description

Technical Field

[0001] The present invention relates to the technical field of power system frequency regulation, and specifically to a method and system for deep coupling frequency regulation of energy storage and thermal power units. Background Art

[0002] With the large-scale grid connection of renewable energy, the frequency stability of the power system faces severe challenges. Although traditional thermal power units have a certain frequency regulation ability, their response speed is slow and the cost is high. Due to the characteristics of fast response and flexible regulation of the energy storage system, it has become an important means to improve the frequency regulation performance of the power system. However, how to achieve deep coupling between energy storage and thermal power and give full play to the advantages of both is a hot topic in the current research on power system frequency regulation technology. Summary of the Invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is that although traditional thermal power units have a certain frequency regulation ability, their response speed is slow and the cost is high.

[0005] To solve the above technical problem, the present invention provides the following technical solutions: A method for deep coupling frequency regulation of energy storage and thermal power units, including: constructing a power system frequency regulation model containing an energy storage power source;

[0006] Taking the minimum system operation cost as the objective function, combining the constraints of thermal power units and the operation constraints of the energy storage system, constructing a thermal power-energy storage optimal scheduling model considering frequency response constraints;

[0007] Decomposing the optimal scheduling model into a master problem and a sub-problem, and obtaining the unit output plan that meets the system frequency regulation requirements and operation constraints through iterative solution;

[0008] According to the obtained unit output plan, adjusting the output power of thermal power units and the energy storage system in real time to achieve stable frequency regulation of the power system;

[0009] Taking the minimum system operation cost as the objective function includes constructing an optimal scheduling model for deep coupling frequency regulation of energy storage and thermal power units with economy as the objective function;

[0010] Constructing an optimal scheduling model for deep coupling frequency regulation of energy storage and thermal power units with economy as the objective function, which is expressed as:

[0011]

[0012] Among them, C represents the system operation cost, C G represents the operation cost of thermal power units, C ES represents the operation cost of the energy storage system; T represents time, N G represents the number of thermal power units, NES Denotes the number of energy storage power stations; α i Denotes the energy consumption cost coefficient of thermal power unit i, β i Denotes the energy consumption cost coefficient of thermal power unit i, γ i Denotes the energy consumption cost coefficient of thermal power unit i, u i,t Denotes the start flag of unit i at time t, v i,t Denotes the stop flag of unit i at time t, U i,t Denotes the operating status of unit i at time t, C on G,t Denotes the start-up cost coefficient of thermal power unit i, Denotes the shutdown cost coefficient of thermal power unit i; C es,price Denotes the unit price of the operating cost of the energy storage system, P G,i,t Denotes the power generation power of thermal power unit i; P C,i,t Denotes the charging power of the energy storage system, P D,i,t Denotes the discharging power of the energy storage system;

[0013] The constraints of thermal power units include unit output constraints, unit ramp rate constraints and unit start-stop time constraints. To maintain the safe and stable operation of the regional power grid, during the combined thermal energy storage frequency regulation, reserve capacity needs to be configured during the actual operation of thermal power units, and reserve capacity constraint conditions are added;

[0014] The constraints of thermal power units include unit output constraints, unit ramp rate constraints and unit start-stop time constraints, which are expressed as:

[0015]

[0016] Among them, P min G,i Denotes the minimum output limit of thermal power unit i, P real G,i,t-1 Denotes the actual output of thermal power unit i at time t-1, P max G,i Denotes the maximum output limit of thermal power unit i, R up,i Denotes the upper ramp rate limit of thermal power unit i, R dn,i Denotes the lower ramp rate limit of thermal power unit i, P G,i,t-1 Denotes the power generation power of thermal power unit i at the previous moment; t0 denotes the current time t, t off Denotes the minimum shutdown time of the thermal power unit, t on Denotes the minimum start-up time of the thermal power unit; Denotes the operating status of unit i at time t, U t-1 i Denotes the operating status of unit i at time t-1;

[0017] To maintain the safe and stable operation of the regional power grid, when combined thermal energy and energy storage participate in frequency regulation, reserve capacity needs to be configured during the actual operation of thermal power units. The reserve capacity constraint condition is expressed as:

[0018]

[0019] Where: represents the positive spinning reserve capacity borne by thermal power unit i at time t, represents the negative spinning reserve capacity borne by thermal power unit i at time t; u i,t represents the on-off flag of unit i at time t;

[0020] The operation constraints of the energy storage system include the rated power constraint of the energy storage and the state of charge (SOC) constraint of the energy storage, which are expressed as:

[0021]

[0022] Where, P EN represents the rated power limit of energy storage system i, SOC min i represents the minimum SOC boundary allowed for the operation of energy storage system i, SOC max i represents the maximum SOC boundary allowed for the operation of energy storage system i;

[0023] At the same moment, the energy storage system cannot charge and discharge simultaneously. The operation state constraint expression of the energy storage system is:

[0024]

[0025] Where: γ d,i,t represents the charging variable of energy storage system i at time t, γ c,i,t represents the charge-discharge variable of energy storage system i at time t;

[0026] The reserve capacity of the energy storage specifically considers factors such as the rated power, capacity of the energy storage, and the charge-discharge efficiency of the energy storage system. The reserve capacity of the energy storage is expressed as:

[0027]

[0028] Where, represents the minimum reserve capacity of the energy storage, represents the maximum reserve capacity of the energy storage; P C,i,t represents the power provided by thermal power unit i at time t; P D,i,t represents the power provided by energy storage system i at time t; E i,t represents the capacity of the energy storage at time t; represents the positive reserve capacity provided by energy storage system i at time t, Denote the negative reserve capacity provided by energy storage system \(i\) at time \(t\). Denote the positive reserve auxiliary state variable. Denote the negative reserve auxiliary state variable; when the energy storage system \(i\) provides reserve flux at time \(t\), set it to 1, otherwise set it to 0; \(M\) represents a sufficiently large positive number.

[0029] The operation constraints of the energy storage system also include dynamic frequency response constraints, expressed as:

[0030]

[0031] Wherein, Denote the maximum frequency change rate when the system is subjected to a limit power disturbance, \(f\) lim Denote the limit value of the maximum frequency change rate of the system; \(\Delta f\) ∞ Denote the steady-state frequency deviation of the system, \(\Delta f\) dz Denote the frequency modulation dead zone, \(f\) sta Denote the limit value of the steady-state frequency deviation of the system; \(f\) t max Denote the maximum frequency deviation under the limit power disturbance of the system, \(\Delta f\) max Denote the limit value of the maximum frequency deviation of the system; \(\Delta P\) represents the regulation power quantity; \(\alpha\) represents the frequency regulation coefficient; \(\omega\) n Denote the rated angular frequency; Denote the initial phase of frequency modulation; Denote the current phase of frequency modulation; \(d\) represents the duty cycle; \(D\) G Denote the generator damping coefficient, \(D\) L Denote the load damping coefficient; \(R\) represents the generator resistance; \(t\) z Denote the moment when the lowest frequency point is reached; \(\omega\) r Denote the current angular frequency.

[0032] As a preferred scheme of the frequency modulation method for deep coupling of energy storage and thermal power units according to the present invention, wherein: the construction of the power system frequency modulation model including energy storage power sources includes that in the model, the thermal power units use the governor - steam turbine frequency modulation response model to output frequency modulation power, and the energy storage system uses a frequency modulation controller to respond to the system frequency modulation command.

[0033] As a preferred scheme of the frequency modulation method for deep coupling of energy storage and thermal power units according to the present invention, wherein: the decomposition of the optimal scheduling model into a master problem and a sub - problem, and obtaining the unit output plan that meets the system frequency modulation requirements and operation constraints through iterative solution includes using the Benders decomposition method to decompose the optimal scheduling model into a master problem and a sub - problem, first obtaining the basic operation parameters of the thermal power units and energy storage in the power system, and obtaining the initial load data \(P_L\) of the system.

[0034] Solve the master problem according to the thermal power - energy storage optimal scheduling model, calculate the unit combination scheduling plan that meets the conventional constraints, and obtain the start - stop status \(U\) of each energy storage and thermal power unit at time \(t\). i,t Output power plan \(P\) g,t \(P\) ES,t .

[0035] Substitute the output power plans of each energy storage and thermal power unit into the sub - problem to check the system's maximum frequency response constraint. If no violation is detected, the optimization is completed, and the real - time output power status of each unit is output. If a violation is detected, return the Benders cut to the master problem to re - optimize the unit scheduling. The Benders cut is expressed as:

[0036]

[0037] Among them, represents the steady - state power change of thermal power unit \(g\) for frequency regulation, \(P\) g,t represents the transient power change of thermal power unit \(g\) for frequency regulation, \(\Delta P\) L,t represents the system load change at time \(t\), represents the power change of photovoltaic unit \(i\) at time \(t\). \(N\) V represents the upper limit of the power change of the energy storage system. represents the power regulation deviation of energy storage system \(i\) at time \(t\). \(N\) B represents the upper limit of the power regulation deviation of the energy storage system.

[0038] Complete the optimization and output the real - time output power status of each unit.

[0039] An energy storage and thermal power unit deep - coupling frequency - modulation system, characterized in that it includes,

[0040] A frequency - modulation model establishment module, which constructs a frequency - modulation model of a power system containing an energy storage power source.

[0041] An optimal scheduling model construction module, with the minimum system operation cost as the objective function, combines the constraints of thermal power units and the operation constraints of the energy storage system, and constructs a thermal power - energy storage optimal scheduling model considering frequency response constraints.

[0042] A model solution module, which decomposes the optimal scheduling model into a master problem and a sub - problem, and obtains the output power plan of the unit that meets the system frequency - modulation requirements and operation constraints through iterative solution.

[0043] A real - time control module, according to the obtained unit output power plan, adjusts the output power of thermal power units and the energy storage system in real time to achieve frequency - stability regulation of the power system.

[0044] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method described above are implemented.

[0045] A computer-readable storage medium stores a computer program thereon. When the computer program is executed by a processor, the steps of the method described above are implemented.

[0046] Advantages of the present invention: Through the deep coupling of energy storage and thermal power, the rapid response and flexible adjustment of frequency modulation resources are achieved, and the frequency modulation efficiency of the power system is improved. The optimization scheduling model aims to minimize the system operation cost and is solved in combination with frequency response constraints, effectively reducing the operation cost of the power system. The output power of thermal power units and energy storage systems is adjusted in real time to ensure that the power system can still operate stably under the condition of large-scale grid connection of new energy. Description of the Drawings

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. Among them:

[0048] Figure 1 It is the overall flowchart of a method for deep coupling frequency modulation of energy storage and thermal power units provided by the first embodiment of the present invention.

[0049] Figure 2 It is the frequency regulation control range diagram under continuous disturbance of a method for deep coupling frequency modulation of energy storage and thermal power units provided by the second embodiment of the present invention. Detailed Embodiments

[0050] To make the above objects, features, and advantages of the present invention more obvious and understandable, the detailed embodiments of the present invention will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] Embodiment 1, referring to Figure 1 , which is an embodiment of the present invention, provides a method for deep coupling frequency modulation of energy storage and thermal power units, including:

[0052] S1: Construct a frequency modulation model of a power system including an energy storage power source.

[0053] In the model, the thermal power unit uses the governor - steam turbine frequency modulation response model to output the frequency modulation power, and the energy storage system uses the frequency modulation controller to respond to the system frequency modulation command.

[0054] S2: Taking the minimum system operation cost as the objective function, combining the constraints of thermal power units and the operation constraints of the energy storage system, a thermal power - energy storage optimal dispatching model considering frequency response constraints is constructed.

[0055] Construct an in - depth coupled frequency modulation optimal dispatching model for energy storage and thermal power units with economy as the objective function, expressed as:

[0056]

[0057] Among them, \(C\) represents the system operation cost, \(C\) G represents the operation cost of the thermal power unit, \(C\) ES represents the operation cost of the energy storage system. \(T\) represents time, \(N\) G represents the number of thermal power units, \(N\) ES represents the number of energy storage power stations. \(\alpha\) i represents the energy consumption cost coefficient of thermal power unit \(i\), \(\beta\) i represents the energy consumption cost coefficient of thermal power unit \(i\), \(\gamma\) i represents the energy consumption cost coefficient of thermal power unit \(i\), \(u\) i,t represents the start - up flag of unit \(i\) at time \(t\), \(v\) i,t represents the stop flag of unit \(i\) at time \(t\), \(U\) i,t represents the operation state of unit \(i\) at time \(t\), \(C\) on G,t represents the start - up cost coefficient of thermal power unit \(i\), represents the shut - down cost coefficient of thermal power unit \(i\). \(C\) es,price represents the unit price of the energy storage system operation cost, \(P\) G,i,t represents the power generation power of thermal power unit \(i\). \(P\) C,i,t represents the charging power of the energy storage system, \(P\) D,i,t represents the discharging power of the energy storage system.

[0058] The constraints of thermal power units include unit output constraints, unit ramp - up constraints, and unit start - up and shutdown time constraints, expressed as:

[0059]

[0060] Among them, \(P\) min G,i represents the minimum output limit of thermal power unit \(i\), \(P\) real G,i,t-1 represents the actual output of thermal power unit \(i\) at time \(t - 1\), \(P\) max G,i represents the maximum output limit of thermal power unit \(i\), \(R\) up,iRepresents the upper ramp rate limit of thermal power unit i, R dn,i Represents the lower ramp rate limit of thermal power unit i, P G,i,t-1 Represents the power generation of thermal power unit i at the previous moment. t0 represents the current moment t, t off Represents the minimum shutdown time of the thermal power unit, t on Represents the minimum startup time of the thermal power unit. Represents the operating state of unit i at time t, U t-1 i Represents the operating state of unit i at time t-1.

[0061] To maintain the safe and stable operation of the regional power grid, during the combined thermal energy and energy storage frequency regulation, reserve capacity needs to be configured during the actual operation of thermal power units. The reserve capacity constraint condition is expressed as:

[0062]

[0063] Among them: Represents the positive spinning reserve capacity borne by thermal power unit i at time t, Represents the negative spinning reserve capacity borne by thermal power unit i at time t. u i,t Represents the startup flag of unit i at time t.

[0064] The operating constraints of the energy storage system include the rated power constraint of the energy storage and the state of charge constraint of the energy storage, which are expressed as:

[0065]

[0066] Among them, P EN Represents the rated power limit of energy storage system i, SOC min i Represents the minimum SOC boundary allowed for the operation of energy storage system i, SOC max i Represents the maximum SOC boundary allowed for the operation of energy storage system i.

[0067] At the same moment, the energy storage system cannot charge and discharge simultaneously. The operating state constraint expression of the energy storage system is:

[0068]

[0069] Among them: γ d,i,t Represents the charging variable of energy storage system i at time t, γ c,i,t Represents the charge and discharge variable of energy storage system i at time t.

[0070] The reserve capacity of the energy storage specifically considers factors such as the rated power and capacity of the energy storage, and the charge and discharge efficiency of the energy storage system. The reserve capacity of the energy storage is expressed as:

[0071]

[0072] Among them, represents the minimum reserve capacity of energy storage, represents the maximum reserve capacity of energy storage. P C,i,t represents the power provided by thermal power unit i at time t. P D,i,t represents the power provided by energy storage system i at time t. E i,t represents the capacity of energy storage at time t. represents the positive reserve capacity provided by energy storage system i at time t, represents the negative reserve capacity provided by energy storage system i at time t, represents the positive reserve auxiliary state variable, represents the negative reserve auxiliary state variable. When energy storage system i provides reserve flux at time t, it is set to 1, otherwise it is set to 0. M represents a sufficiently large positive number.

[0073] It should be noted that the dynamic frequency response constraint of the energy storage coupled unit in the power system is one of the key factors to ensure the stable operation of the system. In the frequency modulation model of the power system with energy storage power supply, the energy storage system quickly responds to the system frequency modulation command through its frequency modulation controller and cooperates with the thermal power unit to jointly regulate the system frequency.

[0074] The dynamic frequency response constraint includes the maximum frequency change rate constraint, the steady-state frequency deviation constraint, and the maximum frequency deviation constraint. These constraint conditions limit the range and rate of frequency change of the system under different operating conditions, ensuring that the system can maintain a safe and stable operating state at any time. Specifically, when the system is subjected to a limit power disturbance, the energy storage system can quickly respond and cooperate with the thermal power unit to jointly regulate, so that the system frequency change rate does not exceed the set maximum value. At the same time, during the regulation process, the steady-state frequency deviation of the system is also controlled within the allowable range to ensure power supply quality and system stability.

[0075] In addition, the dynamic frequency response constraint of the energy storage coupled unit also considers factors such as the rated power, capacity, and charge-discharge efficiency of the energy storage system, ensuring that the energy storage system can fully play its frequency modulation role while avoiding performance degradation or safety risks caused by overcharging or over-discharging. The combined effect of these constraint conditions enables the energy storage coupled unit to play a more stable and efficient frequency modulation role in the power system, improving the overall performance and reliability of the power system.

[0076] The operating constraints of the energy storage system also include the dynamic frequency response constraint, which is expressed as:

[0077]

[0078] Among them, Represents the maximum frequency change rate when the system is subjected to a limit power disturbance, f lim Represents the limit value of the maximum frequency change rate of the system. Δf ∞ Represents the steady-state frequency deviation of the system, Δf dz Represents the dead band of frequency regulation, f sta Represents the limit value of the steady-state frequency deviation of the system. f t max Represents the maximum frequency deviation under the limit power disturbance of the system, Δf max Represents the limit value of the maximum frequency deviation of the system. ΔP represents the amount of regulation power. α represents the frequency regulation coefficient. ω n Represents the rated angular frequency. Represents the initial phase of frequency regulation. Represents the current phase of frequency regulation. d represents the duty cycle. D G Represents the generator damping coefficient, D L Represents the load damping coefficient. R represents the generator resistance. t z Represents the moment when the lowest frequency point is reached. ω r Represents the current angular frequency.

[0079] S3: Decompose the optimal scheduling model into a master problem and a sub-problem, and obtain the unit output plan that meets the system frequency regulation requirements and operation constraints through iterative solution.

[0080] It should be noted that when constructing the combined optimal dispatching model of thermal power and energy storage, the minimization of the system frequency regulation operation cost is taken as the core objective function, and at the same time, the conventional operation constraints of the system and the key dynamic frequency response constraints are comprehensively considered to ensure the comprehensiveness and accuracy of the model. Due to the non-linear characteristics of the system maximum frequency deviation constraint, the traditional linearization method is no longer applicable, so the Benders decomposition method is adopted as the solution strategy. This method is decomposed into two relatively independent but closely related parts: the master problem and the sub-problem. The master problem mainly deals with the optimal solution without considering the system maximum frequency deviation constraint, aiming to initially determine the start-stop states and target output plans of each thermal power unit and energy storage system. Subsequently, these initial solutions are passed as input data to the sub-problem for strict verification of the system maximum frequency deviation constraint. In the sub-problem, if it is found that there is a situation where the system maximum frequency deviation constraint is not satisfied, corresponding Benders cuts are generated according to the verification results and fed back to the master problem. These Benders cuts, as additional constraint conditions, guide the master problem to further optimize the solution in the subsequent iterative process, making the optimization result gradually approach the direction that satisfies the system maximum frequency deviation. Through the iterative solution process between the master problem and the sub-problem, and the effective application of Benders cuts, an optimal solution that satisfies all the operation constraints of the system (including dynamic frequency response constraints) can finally be obtained, and the specific output values of each unit are output. This process not only solves the non-linear problem of the system maximum frequency deviation constraint, but also realizes the minimization of the system frequency regulation operation cost, providing scientific decision-making support for the safe, economic and efficient operation of the power system.

[0081] The Benders decomposition method is used to decompose the optimal dispatching model into a master problem and a sub-problem. First, the basic operation parameters of the thermal power units and energy storage in the power system are obtained, and the initial load data PL of the system is obtained.

[0082] Solve the master problem according to the combined optimal dispatching model of thermal power and energy storage, calculate the unit combination dispatching scheme that satisfies the conventional constraints, and obtain the start-stop states U of each energy storage and thermal power unit at time t respectively i,t 、output plans P g,t 、P ES,t .

[0083] Substitute the output plans of each energy storage and thermal power unit into the sub-problem for verification of the system maximum frequency response constraint. If no over-limit situation is detected, the optimization is completed and the real-time output states of each unit are output. If it is detected that there is an over-limit situation, a Benders cut is returned to the master problem to re-optimize the unit dispatching. The Benders cut is expressed as:

[0084]

[0085] Among them, Indicates the steady-state power change of the thermal power unit g, P g,t Indicates the transient power change of the thermal power unit g, ΔP L,t Indicates the system load change at time t Indicates the power change of the photovoltaic unit i at time t. N V Indicates the upper limit of the power change of the energy storage system Indicates the power regulation deviation of the energy storage system i at time t. N B Indicates the upper limit of the power regulation deviation of the energy storage system

[0086] Complete the optimization and output the real-time output status of each unit

[0087] S4: According to the obtained unit output plan, adjust the output power of the thermal power unit and the energy storage system in real time to achieve the frequency stability regulation of the power system

[0088] The computer device can be a server. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store the data cluster data of the power monitoring system. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through the network connection. When the computer program is executed by the processor, it realizes a deep coupling frequency modulation method for energy storage and thermal power units

[0089] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0090] Embodiment 2. Refer to Figure 2 , which is an embodiment of the present invention, provides a method and system for deep coupling frequency modulation of energy storage and thermal power units. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0091] In order to verify the effectiveness of the proposed thermal power-energy storage optimal scheduling strategy, this study designed a case based on a 120-minute continuous time load disturbance for verification. Figure 2It shows the system frequency fluctuations before and after applying the control strategy of the present invention. Through comparative analysis, it can be significantly observed that after adjusting with the strategy of the present invention, the fluctuations of the system frequency have been significantly improved compared with the initial state, showing a more stable state. To further quantify this effect, Table 1 summarizes the maximum frequency deviation indexes of the system initial frequency and the frequency after adjusting with the strategy of the present invention in the positive and negative directions.

[0092] Table 1 Comparison of maximum frequency deviation indexes

[0093] parameter positive maximum frequency deviation negative maximum frequency deviation initial frequency 0.068 -0.061 adjusted frequency 0.025 -0.021

[0094] The data comparison clearly shows that the control strategy of the present invention demonstrates excellent performance in effectively stabilizing the system frequency fluctuations. Specifically, if ±0.033Hz is used as the over-limit threshold of the frequency fluctuation, then the system frequency after adjusting with the strategy of the present invention fully meets this strict requirement and realizes the stable operation of the system. This conclusion not only verifies the effectiveness of the proposed strategy but also provides a solid theoretical basis for its popularization and application in the actual power system.

[0095] Embodiment 3, an embodiment of the present invention, provides a deep-coupling frequency modulation system for energy storage and thermal power units, including a data acquisition module, a model construction module, an optimal scheduling module, and a real-time control module. The data acquisition module is used to collect power system load data and new energy photovoltaic power data. The model construction module constructs a power system frequency modulation model with energy storage power sources according to the collected data. The optimal scheduling module uses the Benders decomposition method to solve the model based on the constructed frequency modulation model and the optimal scheduling model to obtain the unit output plan. The real-time control module adjusts the output powers of the thermal power units and the energy storage system in real time according to the unit output plan output by the optimal scheduling module.

[0096] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A method for deep coupling frequency modulation of energy storage and thermal power generation units, characterized in that: include: Construct a frequency regulation model of the power system including energy storage power source; Taking the lowest system operating cost as the objective function, combined with the constraints of thermal power units and the operating constraints of energy storage systems, a thermal power-energy storage optimization scheduling model considering frequency response constraints is constructed. The optimization scheduling model is decomposed into a main problem and sub-problems, and the unit output plan that meets the system frequency regulation requirements and operation constraints is obtained through iterative solution; According to the solved unit output plan, the output power of the thermal power unit and the energy storage system is adjusted in real time to achieve stable frequency regulation of the power system; Taking the lowest system operating cost as the objective function includes building a frequency regulation optimization scheduling model with deep coupling of energy storage and thermal power units with economy as the objective function; Taking economy as the objective function, a frequency regulation optimization scheduling model of deep coupling between energy storage and thermal power units is constructed, which can be expressed as: Among them, C represents the system operation cost, C G represents the operating cost of thermal power units, C ES represents the operating cost of the energy storage system; T represents time, N G Indicates the number of thermal power units, N ES Represents the number of energy storage power stations; α i represents the energy consumption cost coefficient of thermal power unit i, β i represents the energy consumption cost coefficient of thermal power unit i, γ i represents the energy consumption cost coefficient of thermal power unit i, u i,t represents the start-up flag of unit i at time t, v i,t represents the stop sign of unit i at time t, U i,t represents the operating status of unit i at time t, C on G,t represents the startup cost coefficient of thermal power unit i, C off G,i represents the shutdown cost coefficient of thermal power unit i; C es,price Represents the unit price of energy storage system operation cost, P G,i,t represents the power generation of thermal power unit i; P C,i,t Represents the charging power of the energy storage system, P D,i,t Indicates the discharge power of the energy storage system; The constraints of thermal power units include unit output constraints, unit ramp constraints, and unit start and stop time constraints. In order to maintain the safe and stable operation of the regional power grid, when thermal power units are combined with power storage for frequency regulation, spare capacity needs to be configured in the actual operation of thermal power units, and spare capacity constraints need to be added. The constraints of thermal power units include unit output constraints, unit ramp constraints, and unit start and stop time constraints, which can be expressed as: Among them, P min G,i Represents the minimum output limit of thermal power unit i, P real G,i,t-1 represents the actual output of thermal power unit i at time t-1, P max G,i represents the maximum output limit of thermal power unit i, R up,i represents the climbing speed limit of thermal power unit i, R dn,i represents the down-slope speed limit of thermal power unit i, P G,i,t-1 represents the power generation of thermal power unit i at the previous moment; t0 represents the current moment t, t off Indicates the minimum shutdown time of the thermal power unit, t on Indicates the minimum start-up time of the thermal power unit; represents the operating status of unit i at time t, represents the operating status of unit i at time t-1; In order to maintain the safe and stable operation of the regional power grid, when the thermal power generation unit is combined with the thermal power generation unit for frequency regulation, it is necessary to configure the spare capacity in the actual operation of the thermal power unit. The spare capacity constraint condition is expressed as: in: represents the positive spinning reserve capacity of thermal power unit i at time t, represents the negative spinning reserve capacity of thermal power unit i at time t; u i,t Indicates the start-up flag of unit i at time t; The operation constraints of the energy storage system include energy storage rated power constraints and energy storage charge rate constraints, which are expressed as: Among them, P EN represents the rated power limit of energy storage system i, It represents the minimum SOC boundary allowed for the operation of energy storage system i, SOC max i represents the maximum SOC boundary allowed for the operation of energy storage system i; At the same time, the energy storage system cannot be charged and discharged at the same time. The energy storage system operation state constraint expression is: Where: γ d,i,t represents the charging variable of energy storage system i at time t, γ c,i,t represents the charge and discharge variables of energy storage system i at time t; The reserve capacity of energy storage specifically considers the rated power, capacity and charging and discharging efficiency of the energy storage system. The reserve capacity of energy storage is expressed as: in, represents the minimum reserve capacity of energy storage, Indicates the maximum reserve capacity of energy storage; P C,i,t represents the power provided by thermal power unit i at time t; P D,i,t Indicates the power provided by energy storage system i at time t; E i,t represents the energy storage capacity at time t; represents the positive reserve capacity provided by energy storage system i at time t, represents the negative reserve capacity provided by energy storage system i at time t, Indicates the positive standby auxiliary state variable, represents the negative backup auxiliary state variable; when the energy storage system i provides the backup flux at time t, it is set to 1, otherwise it is set to 0; M represents a sufficiently large positive number; The operation constraints of the energy storage system also include dynamic frequency response constraints, which are expressed as: in, It represents the maximum frequency change rate when the system is subjected to the extreme power disturbance, f lim Indicates the maximum frequency change rate limit of the system; Δf ∞ Represents the system steady-state frequency deviation, Δf dz Indicates the frequency modulation dead zone, f sta Indicates the system steady-state frequency deviation limit; f t max Indicates the maximum frequency deviation under the system limit power disturbance, Δf max Indicates the maximum frequency deviation limit of the system; ΔP indicates the adjustment power; α indicates the frequency adjustment coefficient; ω n Indicates the rated angular frequency; Indicates the initial phase of FM; Indicates the current phase of frequency modulation; d indicates the duty cycle; D G Denotes the generator damping coefficient, D L represents the load damping coefficient; R represents the generator resistance; t z Indicates the time when the lowest frequency point is reached; ω r Indicates the current angular frequency.

2. The method for deep coupling frequency modulation of energy storage and thermal power generation units according to claim 1, characterized in that: The construction of the power system frequency regulation model containing the energy storage power source includes: the thermal power unit in the model uses the governor-turbine frequency regulation response model to output frequency regulation power, and the energy storage system uses the frequency regulation controller to respond to the system frequency regulation command.

3. The method for deep coupling frequency modulation of energy storage and thermal power generation units according to claim 2, characterized in that: Decomposing the optimization dispatch model into a main problem and sub-problems, and obtaining the unit output plan that meets the system frequency regulation requirements and operation constraints through iterative solution includes: using the Benders decomposition method to decompose the optimization dispatch model into a main problem and sub-problems, first obtaining the basic operating parameters of the thermal power units and energy storage in the power system, and obtaining the system initial load data PL; The main problem is solved according to the thermal power-energy storage optimization scheduling model, and the unit combination scheduling plan that meets the conventional constraints is calculated. The start and stop status U of each energy storage and thermal power unit at time t is obtained respectively. i,t , output plan P g,t , P ES,t ; Substitute the output plans of energy storage and thermal power units into the sub-problem to check the system maximum frequency response constraint. If there is no over-limit situation, the optimization is completed and the real-time output status of each unit is output; if there is an over-limit situation, return to the main problem to re-optimize the unit scheduling by Benders cut, where Benders cut is expressed as: in, Indicates the frequency regulation steady-state power change of thermal power unit g, P gt Indicates the transient power change of thermal power unit g, ΔP L,t represents the change in system load at time t, N represents the power change of photovoltaic unit i at time t; V Indicates the upper limit of the power change of the energy storage system; represents the power regulation deviation of energy storage system i at time t; N B Indicates the upper limit of the power regulation deviation of the energy storage system; After the optimization is completed, the real-time output status of each unit is output.

4. A deep coupling frequency modulation system of energy storage and thermal power generation units using the method according to any one of claims 1 to 3, characterized in that: Establish a frequency regulation model module and construct a power system frequency regulation model including energy storage power source; Construct an optimization dispatch model module, take the lowest system operation cost as the objective function, combine the constraints of thermal power units and the operation constraints of energy storage systems, and construct a thermal power-energy storage optimization dispatch model that considers frequency response constraints; The model solving module decomposes the optimization scheduling model into main problems and sub-problems, and obtains the unit output plan that meets the system frequency regulation requirements and operation constraints through iterative solving; The real-time control module adjusts the output power of the thermal power units and the energy storage system in real time according to the solved unit output plan to achieve stable frequency regulation of the power system.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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