Source-grid-load-storage coordinated optimal dispatch method for grid-forming islanded power grid, and device and medium

Abstract

A source-grid-load-storage coordinated optimal dispatch method for a grid-forming islanded power grid, and a device and a medium. The method comprises: acquiring a topological structure, power grid parameters and load forecasting data of a grid-forming islanded power grid, and on the basis of an operating mode of the grid-forming islanded power grid, obtaining a power flow distribution of the grid-forming islanded power grid (S101); acquiring forecasting data on the basis of the power flow distribution of the grid-forming islanded power grid, and constructing a source-grid-load-storage coordinated optimal dispatch model for the grid-forming islanded power grid by means of comprehensively taking into account carbon trading and demand response mechanisms, using, as an objective, the minimization of the costs of the grid-forming islanded power grid for operation and maintenance, wind and solar curtailment penalties, energy-storage life degradation, demand-response load reduction compensation and carbon trading, and using the power balance of the grid-forming islanded power grid, operating limit values of devices, energy-storage charge / discharge cycles and user satisfaction as constraints (S102); by means of using a set duration as a step size, using a linear programming method to solve the source-grid-load-storage coordinated optimal dispatch model for the grid-forming islanded power grid, so as to obtain an optimal dispatch scheme for each power generation device in the grid-forming islanded power grid (S103); and implementing the source-grid-load-storage coordinated optimal dispatch for the grid-forming islanded power grid (S104).

Description

Methods, equipment, and media for coordinated optimization scheduling of source-grid-load-storage in grid-type isolated power grids

[0001] This application claims priority to Chinese Patent Application No. 202510195278.7, filed on February 20, 2025, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of power grid dispatching, for example to a method, equipment and medium for coordinated optimization dispatching of sources, grids, loads and storage in a grid-type islanded power grid. Background Technology

[0003] Due to the impact of natural disasters such as extreme weather, once the connection between the power system's end points and the main grid is disconnected, an islanded power grid is formed. Islanded power grids are relatively small in scale and have low rotational inertia, posing certain difficulties for their dispatch and operation. Inappropriate dispatch and control measures may lead to instability in the islanded power grid. Meanwhile, constructing islanded power grids primarily based on new energy sources is also one of the main development directions of future new energy systems. Therefore, designing a method and scheme for coordinated optimization dispatch of power generation, grid, load, and storage in islanded power grids has significant practical engineering value.

[0004] In recent years, with the increasing depletion of traditional energy sources and the growing prominence of environmental problems, accelerating the development and utilization of new energy sources has become a global consensus. Future new power systems will primarily rely on wind and solar power generation, and most wind and solar power generation is located at the end of the power grid, where a high proportion of new energy power systems has already been formed.

[0005] Therefore, in terminal power grids with a high proportion of renewable energy, the dispatch and operation of isolated grids becomes more difficult if grid interconnection failures occur. Furthermore, isolated grids primarily composed of renewable energy are also one of the main development models for future new power systems and energy systems. Currently, there are few application scenarios for the coordinated optimization dispatch of isolated grids primarily composed of renewable energy, and it remains in the theoretical research stage. Moreover, most conventional renewable energy grid connection methods are grid-following control, using phase-locked loops to collect frequency and phase signals from the grid output. These methods lack the ability to actively support voltage and frequency, and cannot guarantee the safe and stable operation of isolated grids. Summary of the Invention

[0006] This application provides a method, equipment, and medium for coordinated optimization scheduling of source, grid, load, and storage in a grid-type isolated power grid, which can ensure the safe and stable operation of the isolated power grid.

[0007] Firstly, this application provides a method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid, including:

[0008] Obtain the topology, grid parameters, and load forecast data of the grid-type islanded power grid, and obtain the power flow distribution of the grid-type islanded power grid based on its operating mode;

[0009] Based on the power flow distribution of the grid-type islanded power grid, predictive data with a set resolution for the day-ahead scheduling period of new energy sources is obtained. Taking into account carbon trading and demand response mechanisms, with the objectives of minimizing the operation and maintenance of the grid-type islanded power grid, wind and solar curtailment penalties, energy storage lifespan loss, demand response load reduction compensation, and carbon trading costs, and with constraints such as the power balance of the grid-type islanded power grid, equipment operating limits, energy storage charging and discharging times, and user satisfaction, a collaborative optimization scheduling model for the grid-type islanded power grid source-grid-load-storage is constructed.

[0010] Using the set duration as the step size, the linear programming method is used to solve the source-grid-load-storage collaborative optimization scheduling model of the grid-type islanded power grid, and obtain the optimal scheduling scheme for each power generation device of the grid-type islanded power grid.

[0011] Based on the optimized scheduling scheme for each generating unit of the grid-type islanded power grid, the coordinated optimized scheduling of power generation, grid, load and storage in the grid-type islanded power grid is realized.

[0012] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned grid-type islanded power grid source-grid-load-storage coordinated optimization scheduling method.

[0013] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for coordinated optimization scheduling of source, grid, load and storage in a grid-type islanded power grid. Attached Figure Description

[0014] Figure 1 is a flowchart illustrating a method for coordinated optimization scheduling of power sources, grids, loads, and storage in a grid-type islanded power grid according to an embodiment of this application.

[0015] Figure 2 is a schematic diagram of a two-level collaborative optimization scheduling process for day-ahead and intraday scheduling provided in an embodiment of this application;

[0016] Figure 3 is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0018] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] In an exemplary embodiment, this application provides a method for coordinated optimization scheduling of power generation, grid, load, and storage in a grid-type islanded power grid. This method is executed by a computer device, specifically a terminal or server, or both. In this embodiment, the method is described using a server as an example. As shown in Figure 1, the method includes:

[0020] S101: Obtain the topology, grid parameters, and load forecast data of the grid-type islanded power grid, and obtain the power flow distribution of the grid-type islanded power grid based on its operating mode. The grid-type islanded power grid is hereinafter referred to as the islanded power grid or the power grid.

[0021] S102: Based on the power flow distribution of a grid-type islanded power grid, predictive data with a set resolution for the day-ahead dispatch period of renewable energy is obtained. Taking into account carbon trading and demand response mechanisms, and aiming to minimize the operation and maintenance of the grid-type islanded power grid, wind and solar curtailment penalties, energy storage lifespan loss, demand response load reduction compensation, and carbon trading costs, a collaborative optimization dispatch model for the grid-type islanded power grid's power generation, grid, load, and storage is constructed, constrained by the grid-type islanded power grid's power balance, equipment operating limits, energy storage charge / discharge cycles, and user satisfaction. The collaborative optimization dispatch model for the grid-type islanded power grid's power generation, grid, load, and storage is expressed as follows:

[0022] ;

[0023] In the formula, T represents the dispatching period, X represents the number of power grid devices, and X WF X represents the number of wind turbine units in the power grid. PV X represents the number of photovoltaic power generation systems. bat X represents the number of grid-connected energy storage batteries. L Indicates the number of grid loads; c i',t For the i-th power grid ' The operating and maintenance cost of a production device at time t, P i',t For the i-th power grid ' The output power of each production device at time t; c i''WF,t For the i-th'' The cost of wind curtailment penalty for typhoon turbines at time t, P i''WF,t For the i-th '' The reported power output of the typhoon generator at time t, P ' i''WF,t For the i-th '' The actual output power of the typhoon generator at time t; c i'''PV,t For the i-th ''' The cost of curtailment penalty for a photovoltaic system at time t, P i'''PV,t For the i-th ''' The reported power of the photovoltaic system at time t, P ' i'''PV,t For the i-th ''' The actual output power of the photovoltaic system at time t; ci''''bat,t is the i-th... '''' The initial investment cost of an energy storage battery, L ibat,t c represents the percentage of lifespan reduction of the energy storage battery; i'''''L,t For the i-th ''''' The load reduction compensation price at time t, P i'''''L,t For the i-th ''''' The load power P before the demand response at time t is given. ' i'''''L,t For the i-th ''''' The load power after the demand response at time t; c CE,t Let β be the carbon emission cost at time t. CEO,t Let β be the carbon emissions at time t. CEc,t Let β be the amount of carbon captured at time t. CEr,t Let be the carbon quota at time t, and F be the objective function.

[0024] In some implementations, the day-ahead scheduling period for new energy sources is 24 hours prior to the new energy source launch, with a set duration of 15 minutes. For example, to achieve coordinated and optimized scheduling of isolated power grids during the day-ahead 24 hours, forecast data with a resolution of 15 minutes (min) can be obtained within the 24 hours prior to the new energy source launch.

[0025] S103: Using a set time interval as the step size, the linear programming method is used to solve the source-grid-load-storage collaborative optimization scheduling model of the grid-type islanded power grid, and obtain the optimal scheduling scheme for each power generation device of the grid-type islanded power grid.

[0026] For example, when using linear programming with a step size of 15 minutes, the resulting optimal scheduling schemes for each power generation device in the isolated power grid are 96 optimal scheduling schemes for the previous 24 hours.

[0027] S104: Based on the optimized scheduling scheme of each generating device in the grid-type islanded power grid, realize the coordinated optimized scheduling of source, grid, load and storage in the grid-type islanded power grid.

[0028] By implementing S101 to S104 above, this application can efficiently utilize the wind and solar renewable energy of isolated power grids. Combined with load forecast data from the day-ahead dispatch period of the isolated power grid, and using the network topology of the isolated power grid as a platform, it analyzes the power flow distribution characteristics of the isolated power grid and constructs a basic framework for optimized dispatching of "source-grid-load-storage" from both the supply and demand sides. Taking into account carbon trading and user satisfaction, and aiming to minimize the operation and maintenance of the grid-type isolated power grid, wind and solar curtailment penalties, energy storage lifespan reduction, demand response load reduction compensation, and carbon trading costs, and constrained by the power balance of the grid-type isolated power grid, equipment operating limits, energy storage charge / discharge cycles, and user satisfaction, a collaborative optimized dispatching model for source-grid-load-storage of the grid-type isolated power grid is constructed to ensure the safe and stable operation of the isolated power grid. Furthermore, this application also has the advantages of simple implementation and high engineering practical value.

[0029] In another exemplary embodiment of this application, in order to further achieve economical, low-carbon, and reliable operation of the islanded power grid, the power balance of the grid-type islanded power grid is represented as follows:

[0030] .

[0031] In the formula, P i and Q i These represent the active and reactive power injected into node i in an islanded power grid, respectively. i and U j θ represents the voltage magnitudes at nodes i and j, respectively. ij G represents the voltage phase angle difference between node i and node j. ij and B ij , respectively, are the real and imaginary parts of the element in the i-th row and j-th column of the node admittance matrix. n is the total number of nodes in the islanded power grid.

[0032] In some embodiments, the equipment operation limit constraints specifically include: energy storage battery constraints, energy storage battery state of charge constraints, thermal power unit output power constraints, gas turbine generator unit output power constraints, wind farm output power constraints, photovoltaic power station output power constraints, power system node voltage limit constraints, and power system transmission line transmission power constraints, wherein:

[0033] (1) The constraints of the energy storage battery are expressed as:

[0034] -P max-charge ≤P ibat,t ≤-P max-discharge .

[0035] In the formula, -P max-charge -P represents the maximum charging power of the energy storage battery. max-discharge P represents the maximum discharge power of the energy storage battery. ibat,t This refers to the power of the energy storage battery.

[0036] (2) The state of charge constraint of the energy storage battery is expressed as:

[0037] SOC min ≤SOC(t) ≤SOC max .

[0038] In the formula, SOC min The State of Charge (SOC) is the minimum value for the state of charge of an energy storage battery. max This represents the upper limit of the state of charge (SOC) of the energy storage battery. SOC(t) is the state of charge of the energy storage battery at time t.

[0039] The energy balance of the energy storage battery during a dispatch cycle is as follows:

[0040] SOC(t=0) = SOC(t=T).

[0041] (3) The output power constraints of thermal power units, gas turbine generator sets, wind farms, and photovoltaic power stations are expressed as follows:

[0042] .

[0043] In the formula, P Gi,t Let P be the output power of the thermal power unit at time t. Gi,min P Gi,max These are the upper and lower limits of the output power of thermal power units, P GTi,t The output power of the gas turbine unit at time t, P GTi,min P GTi,max These are the upper and lower limits of the output power of the gas turbine unit, P. WFi,t P PVi,t P represents the output power of the wind turbine and the photovoltaic power generation system at time t, respectively. WFi,max P PVi,max These represent the maximum output power of the wind turbine and the photovoltaic power generation system, respectively.

[0044] (4) The voltage limit constraint of the power system node is expressed as:

[0045] .

[0046] In the formula, U i,t U represents the voltage at node i at time t. i,max and U i,min This represents the maximum and minimum voltages of node i.

[0047] (5) Power transmission constraints of power system transmission lines:

[0048] .

[0049] In the formula, P ij,tP represents the line transmission power at time t. ij,max This indicates the maximum power transmitted through the line.

[0050] In another exemplary embodiment of this application, in order to improve the power supply reliability of an islanded power grid, it is necessary to reduce some electrical load in extreme scenarios to maintain system power balance. Compensation is required for the reduced load. Based on this, the following applies:

[0051] .

[0052] In the formula, P iLs,t Let P be the amount of electrical load transferred at time t, with positive for incoming load and negative for outgoing load. iLc,t P represents the electrical load interrupted at time t. iLs,t,min and P iLs,t,max P represents the maximum and minimum transferable electrical load values ​​at time t, respectively. iLc,t,max Let t be the maximum interruptible value of the electrical load at time t.

[0053] In another exemplary embodiment of this application, the demand response mechanism may cause user dissatisfaction and discomfort. Therefore, user satisfaction needs to be used as a constraint indicator. Based on this, the user satisfaction constraint adopted above can be expressed as:

[0054] .

[0055] In the formula, S e For user satisfaction.

[0056] In another exemplary embodiment of this application, in order to improve the real-time performance and economy of power optimization dispatch and achieve economical, low-carbon, and reliable operation of the islanded power grid, the optimization dispatch scheme can also be modified in real time during the implementation of S103 above. Based on this, the process of modifying the optimization dispatch scheme includes:

[0057] S1. Real-time monitoring of the operating status of the grid-type islanded power grid, acquisition of electrical load data, and real-time acquisition of daily forecast data for m hours of renewable energy. m is an integer greater than 0. For example, acquiring 4 hours (h) of daily forecast data for renewable energy.

[0058] S2. Compare the predicted data of new energy within m hours during the day with the predicted data of new energy within the daytime scheduling period with a resolution of a set duration to obtain the comparison deviation.

[0059] S3. Based on the comparison deviation, a collaborative optimization scheduling model for source-grid-load-storage of grid-type islanded power grid is adopted. With a set time period as the calculation step size, the optimization scheduling scheme of each power generation device in the grid-type islanded power grid is continuously and dynamically corrected in real time to obtain the optimization scheduling scheme of new energy in m hours per day.

[0060] For example, by comparing the predicted data of new energy m hours within a day with the predicted data of the previous 24 hours, and based on the deviation of the compared data, the configuration scheme of the optimized scheduling is corrected in real time according to the constructed grid-type islanded power grid source-grid-load-storage collaborative optimization scheduling model with a calculation step of 15 minutes, and further obtains the optimized scheduling scheme for 4 hours within a day, giving 16 optimized scheduling schemes within a day.

[0061] The optimized scheduling scheme for the next 4 hours of the day is corrected in real time using a rolling method with a rolling cycle of 15 minutes. The optimized scheduling scheme for the next 4 hours is obtained by rolling the scheme, which is the final optimized scheduling scheme for the next 4 hours of the day.

[0062] S4. Based on the optimized scheduling scheme of new energy within m hours per day, adjust the optimized scheduling scheme of each power generation device in the grid-type islanded power grid in real time to obtain the final optimized scheduling scheme of each power generation device in the grid-type islanded power grid.

[0063] For example, as shown in Figure 2, which illustrates the two-level collaborative optimization scheduling method for the day-ahead and intraday periods, the optimization scheduling scheme modification process provided in this application can mainly include two parts: two-level optimization scheduling for the day-ahead 24 hours and intraday 4 hours. During the day-ahead 24-hour scheduling, the dispatch center needs to obtain the day-ahead 24-hour renewable energy power forecast data, the day-ahead 24-hour load forecast data, and the network topology of the isolated power grid to construct the day-ahead 24-hour optimization scheduling model for the isolated power grid (i.e., the network-type isolated power grid source-grid-load-storage collaborative optimization scheduling model used for the day-ahead 24-hour optimization scheduling of the isolated power grid).

[0064] During the daily operation of the isolated power grid, key operational parameters are monitored in real time, including load parameters, network topology, power supply equipment status, energy storage system charge status, and renewable energy plant operation status. Based on the measured load and compared with the previous 24-hour load forecast data, combined with the 4-hour renewable energy output forecast data, the 4-hour optimized scheduling scheme is re-solved using the established previous 24-hour optimized scheduling model for the isolated power grid. The previous 24-hour scheduling scheme, with a 15-minute resolution, yields 96 optimized scheduling results, forming the previous 24-hour energy scheduling plan. The 4-hour optimized scheduling scheme, also with a 15-minute resolution, is solved using the 4-hour optimized scheduling model, yielding 16 optimized results, forming the 4-hour energy optimized scheduling scheme. The 4-hour scheduling is integrated with the daily renewable energy output forecast, using a 15-minute rolling cycle. The optimized scheduling scheme for the next 4 hours is updated every 15 minutes, and this cycle is repeated to complete the daily collaborative optimized scheduling plan for the isolated power grid.

[0065] In another exemplary embodiment of this application, incorporating carbon emission trading into optimized scheduling is a key step in achieving low carbon emissions. This embodiment uses a daily carbon allowance reset system that does not accumulate; the total carbon allowance within a scheduling cycle is:

[0066] .

[0067] In the formula, This refers to the total amount of carbon allowances. Let λ be the emission quota per unit output, λ be the carbon quota coefficient, and M be the total production of the system.

[0068] In some embodiments, a carbon quota mechanism that conforms to the operating characteristics of islanded power grids is proposed, and the carbon trading cost for each time period is expressed as follows:

[0069] .

[0070] In the formula, The carbon trading cost for period t. The reward amount per unit of carbon allowance. The penalty amount. Carbon capture amount, This refers to carbon emissions.

[0071] When carbon emissions exceed carbon quotas, the system (i.e., a grid-connected islanded power grid) needs to purchase carbon emission rights, and the carbon trading price increases with the higher the carbon emission range. Therefore, to further control carbon emissions, this application adopts a tiered carbon trading mechanism, that is, using segmented compensation prices to determine demand response load reduction compensation. For example, three time-period compensation prices are used for optimal scheduling calculations. The model using the tiered carbon trading mechanism is expressed as follows:

[0072] .

[0073] In the formula, δ represents the carbon trading price, μ represents the length of the carbon emission range, and k represents the increase rate of the carbon trading price. This refers to the tiered carbon trading costs.

[0074] Based on the above description, in practical applications, the implementation process of the source-grid-load-storage coordinated optimization scheduling method for grid-type islanded power grids provided in this application can be described as follows:

[0075] This study acquires the day-ahead 24-hour renewable energy output forecast and load data for isolated power grids, as well as the state of charge (SOC) of energy storage systems. Considering carbon trading and demand response mechanisms, and aiming to minimize isolated power grid operation and maintenance, wind and solar curtailment penalties, energy storage lifespan reduction, load reduction compensation, and carbon trading costs, while constraining isolated power grid power balance, equipment operating limits, energy storage charge / discharge cycles, and user satisfaction, a grid-based isolated power grid source-grid-load-storage collaborative optimization scheduling model is constructed. A linear programming method is used to solve the grid-based isolated power grid source-grid-load-storage collaborative optimization scheduling model, obtaining the day-ahead 24-hour isolated power grid scheduling plan and providing the day-ahead 24-hour output plan for the isolated power grid's power supply equipment. Based on the measured load data of the isolated power grid and the intraday 4-hour renewable energy forecast data, the day-ahead optimized scheduling scheme is adjusted in real time according to the established optimization scheduling model. Through grid-based technology and a day-ahead and intraday two-stage scheduling method, economical, low-carbon, and reliable operation of the isolated power grid can be achieved.

[0076] In some embodiments, when constructing a dispatch configuration scheme for an islanded power grid using the method provided in this application, the safe and reliable operation of the islanded power grid is taken as a prerequisite. The objective is to minimize the sum of maintenance costs of islanded power grid operating equipment, wind and solar curtailment costs, load reduction compensation costs, and carbon emission costs. Constraints include power balance and equipment operating limits of the islanded power grid. A tiered carbon trading mechanism and user satisfaction are also considered to construct a coordinated optimization dispatch model for the source-grid-load-storage system of a grid-connected islanded power grid. Carbon emission costs comprehensively consider both carbon emissions and carbon quotas, with the carbon emission cost coefficient calculated using a tiered carbon trading mechanism model. Power balance includes the balance of active and reactive power in the power system. Operating limits include the output limits of power supply equipment and the operating limits of the network and nodes. Based on the established optimization dispatch model, a linear programming method is used to solve the problem and obtain the output dispatch scheme for the islanded power grid's power supply equipment.

[0077] As can be seen, this application addresses the difficulty of dispatching isolated power grids with a high proportion of renewable energy terminals by proposing to improve the dispatch level of isolated power grids using grid-based technology. It ensures the safe and reliable operation of isolated power grids through grid-based wind power, photovoltaic and energy storage systems. With the goal of minimizing the total operating cost of isolated power grids, a grid-based isolated power grid source-grid-load-storage collaborative optimization dispatch model is constructed to obtain a real-time optimized dispatch scheme for isolated power grids.

[0078] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram is shown in Figure 3. The computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device stores data on the coordinated optimization scheduling of power generation, grid, load, and storage in a grid-type islanded power grid. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a coordinated optimization scheduling method for power generation, grid, load, and storage in a grid-type islanded power grid.

[0079] Those skilled in the art will understand that the structure shown in Figure 3 is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0080] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0081] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0082] The user information (including user device information, user personal information, etc.) and data (including data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0083] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0084] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include distributed databases based on blockchain, etc. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc.

[0085] This application provides a method, equipment, and medium for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid. Addressing the difficulty of scheduling in islanded power grids with a high proportion of renewable energy terminals, it proposes to improve the scheduling level of islanded power grids by utilizing grid-type technology. Using the network topology of the grid-type islanded power grid as a platform, it analyzes the power flow distribution characteristics of the grid-type islanded power grid and constructs a basic framework for optimized scheduling of "source-grid-load-storage" from both the supply and demand sides. Combining forecast data with a set resolution for the day-ahead dispatch period of new energy sources, and comprehensively considering carbon trading and user satisfaction, this study aims to minimize the operation and maintenance costs, wind and solar curtailment penalty costs, energy storage lifespan loss costs, demand response load reduction compensation costs, and carbon trading costs of grid-type islanded power grids. Constrained by power balance, equipment operating limits, energy storage charge / discharge cycles, and user satisfaction, a collaborative optimization dispatch model for the generation, grid, load, and storage of grid-type islanded power grids is constructed. This model proactively supports grid voltage and frequency. Ultimately, it yields optimized dispatch schemes for each power generation device in the grid-type islanded power grid, achieving collaborative optimization dispatch of generation, grid, load, and storage, and ensuring the safe and stable operation of the islanded power grid.

Claims

1. A method for coordinated optimization scheduling of power generation, grid, load, and storage in a grid-type islanded power grid, comprising: Obtain the topology, grid parameters, and load forecast data of the grid-type islanded power grid, and obtain the power flow distribution of the grid-type islanded power grid based on its operating mode; Based on the power flow distribution of the grid-type islanded power grid, predictive data with a set resolution for the day-ahead scheduling period of new energy sources is obtained. Taking into account carbon trading and demand response mechanisms, with the objectives of minimizing the operation and maintenance of the grid-type islanded power grid, wind and solar curtailment penalties, energy storage lifespan loss, demand response load reduction compensation, and carbon trading costs, and with constraints such as the power balance of the grid-type islanded power grid, equipment operating limits, energy storage charging and discharging times, and user satisfaction, a collaborative optimization scheduling model for the grid-type islanded power grid source-grid-load-storage is constructed. Using the set duration as the step size, the linear programming method is used to solve the source-grid-load-storage collaborative optimization scheduling model of the grid-type islanded power grid, and obtain the optimal scheduling scheme for each power generation device of the grid-type islanded power grid. Based on the optimized scheduling scheme for each generating unit of the grid-type islanded power grid, the coordinated optimized scheduling of power generation, grid, load and storage in the grid-type islanded power grid is realized.

2. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1, wherein, The coordinated optimization scheduling model for source-grid-load-storage in the grid-type islanded power grid is expressed as follows: ； In the formula, T represents the dispatching period, X represents the number of power grid devices, and X WF X represents the number of wind turbine units in the power grid. PV X represents the number of photovoltaic power generation systems. bat X represents the number of grid-connected energy storage batteries. L Indicates the number of grid loads; c i',t For the i-th power grid ' The operating and maintenance cost of a production device at time t, P i',t For the i-th power grid ' The output power of each production device at time t; c i''WF,t For the i-th '' The cost of wind curtailment penalty for typhoon turbines at time t, P i''WF,t For the i-th '' The reported power output of the typhoon generator at time t, P ' i''WF,t For the i-th '' The actual output power of the typhoon generator at time t; c i'''PV,t For the i-th ''' The cost of curtailment penalty for a photovoltaic system at time t, P i'''PV,t For the i-th ''' The reported power of the photovoltaic system at time t, P ' i'''PV,t For the i-th ''' The actual output power of the photovoltaic system at time t; ci''''bat,t is the i-th '''' The initial investment cost of an energy storage battery, L ibat,t c represents the percentage of lifespan reduction of the energy storage battery; i'''''L,t For the i-th ''''' The load reduction compensation price at time t, P i'''''L,t For the i-th ''''' The load power P before the demand response at time t is given. ' i'''''L,t For the i-th ''''' The load power after the demand response at time t; c CE,t Let β be the carbon emission cost at time t. CEO,t Let β be the carbon emissions at time t. CEc,t Let β be the amount of carbon captured at time t. CEr,t Let be the carbon quota at time t, and F be the objective function.

3. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1, wherein, The new energy daytime scheduling period is 24 hours before the new energy day; the set duration is 15 minutes.

4. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1 further includes, in the process of solving the coordinated optimization scheduling model of source-grid-load-storage in a grid-type islanded power grid using linear programming with the set time period as the step size to obtain the optimized scheduling scheme for each generating device of the grid-type islanded power grid, the following steps are performed: Real-time monitoring of the operation status of the grid-type islanded power grid, acquisition of power load data, and real-time acquisition of daily m-hour forecast data of new energy sources; By comparing the daily m-hour forecast data of new energy sources with the forecast data of new energy sources with a set resolution of time during the daytime dispatch period, the comparison deviation is obtained. Based on the aforementioned comparison deviation, the source-grid-load-storage collaborative optimization scheduling model of the grid-type islanded power grid is adopted. With the set duration as the calculation step size, the optimization scheduling scheme of each power generation device of the grid-type islanded power grid is continuously and dynamically corrected in real time to obtain the optimization scheduling scheme of new energy m hours per day. Based on the optimized scheduling scheme of new energy within m hours per day, the optimized scheduling scheme of each power generation device in the grid-type islanded power grid is adjusted in real time to obtain the final optimized scheduling scheme of each power generation device in the grid-type islanded power grid.

5. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1, wherein, The power balance of the grid-type islanded power grid is expressed as follows: ； In the formula, P i and Q i These represent the active and reactive power injected into node i in the islanded power grid, respectively; U i and U j These are the voltage amplitudes at nodes i and j, respectively. θ ij G represents the voltage phase angle difference between node i and node j. ij and B ij , respectively, are the real and imaginary parts of the element in the i-th row and j-th column of the node admittance matrix; n is the total number of nodes in the islanded power grid.

6. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1, wherein, The equipment operation limits include: energy storage battery constraints, energy storage battery state of charge constraints, thermal power unit output power constraints, gas turbine generator set output power constraints, wind farm output power constraints, photovoltaic power station output power constraints, power system node voltage limits, and power system transmission line transmission power constraints.

7. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1, wherein, User satisfaction constraints are expressed as follows: ； In the formula, P iLc,t P represents the electrical load interrupted at time t. i'''''L,t For the i-th ''''' The load power before the demand response at time t, S e For user satisfaction.

8. The method for coordinated optimization scheduling of source-grid-load-storage in a grid-type islanded power grid according to claim 1, wherein, Segmented compensation pricing is used to determine demand response load reduction compensation.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the source-grid-load-storage coordinated optimization scheduling method for any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the source-grid-load-storage coordinated optimization scheduling method for a grid-type islanded power grid as described in any one of claims 1-8.

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