An emergency energy supply planning method, device, storage medium and system

Abstract

The application discloses an energy supply planning method and device under an emergency, a storage medium and a system. By considering the influence of an emergency such as a disease pandemic, combining the different influences of different regions under external events, and building an energy supply cost optimization model considering the impact of events such as pandemics, the energy supply cost is reasonably optimized. The energy supply planning management method, device, storage medium and system under the emergency improve the energy supply planning efficiency and accuracy under the emergency.

Description

Technical Field

[0001] This invention relates to the field of energy supply planning technology under emergencies, and in particular to a method, apparatus, computer-readable storage medium and system for energy supply planning under emergencies. Background Technology

[0002] Global pandemics or wars leading to power generation shortages can result in insufficient energy supply, potentially causing power shortages for primary loads providing essential services, such as hospitals. Pandemics or wars will impact energy supply and normal operation in multiple ways, including personnel, service investment, and system infrastructure. For example, infections may cause insufficient personnel to operate plants, disruptions to liquid or solid fuel delivery, or problems with natural gas supply. To optimize energy supply for users during external events such as pandemics or wars, it is necessary to develop energy cost optimization models that account for the varying degrees of impact from these events in different regions, and to rationally optimize energy supply costs.

[0003] Existing technologies primarily focus on research into changes in energy system supply and user demand under long-term and gradual events (such as climate change or energy policy).

[0004] However, existing technologies still have the following shortcomings: they lack consideration of the impact of sudden events caused by unforeseen circumstances on changes in energy system supply and user demand.

[0005] Therefore, there is a current need for a method, apparatus, computer-readable storage medium, and system for energy planning in the event of an emergency, in order to overcome the aforementioned deficiencies in the prior art. Summary of the Invention

[0006] This invention provides a method, apparatus, computer-readable storage medium, and system for energy supply planning during emergencies, thereby improving the efficiency and accuracy of energy supply planning during emergencies.

[0007] An embodiment of the present invention provides an energy supply planning method under emergency events. The energy supply planning method includes: acquiring an energy supply planning data set and emergency situation user data; constructing a cost optimization objective function based on a preset emergency event energy supply cost model set; the emergency event energy supply cost model set includes a system energy supply cost model and an affected area energy supply cost model; calculating a cost optimization scheduling strategy based on a preset emergency event impact constraint set, the emergency event scheduling data set, and emergency situation user data, and performing energy supply planning under emergency events based on the cost optimization scheduling strategy.

[0008] As an improvement to the above scheme, the energy supply cost model for the affected area is as follows: In the formula, B′ and G′ represent the parts of B and G that are severely affected by the sudden event, respectively; C represents the power gained from the external region at time t; G ε and ε represent the total energy supply cost of the energy system and its impact factor on G, respectively; ε is determined based on the actual energy distribution in the area affected by the emergency and the historical energy demand of users; C G Cost is constrained by the factor ε; the smaller ε is, the lower C is. G It has the least impact on energy supply in areas severely affected by emergencies.

[0009] As an improvement to the above scheme, the system energy supply cost model is as follows: In the formula, T represents the optimization time, t represents the sampling time, i and j represent the counting variables, B and G represent the number of nodes in the energy system and the number of the largest energy source among all energy sources, respectively; if the number of a certain type of energy source G″ is less than G, when j>G″, the energy that the energy source can supply is recorded as 0. and These represent the power injected into node i at time t by the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The power obtained from the upstream power grid at time t; c gn c go c h c S c n c v and c r These represent the energy supply costs of the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively.

[0010] As an improvement to the above scheme, the set of constraints for the impact of emergencies includes total energy demand constraints, affected load constraints, node load power balance constraints, energy reserve constraints, power plant personnel number constraints, solid and liquid fuel supply constraints, and natural gas fuel supply constraints.

[0011] As an improvement to the above scheme, the affected load constraint condition is as follows:

[0012]

[0013] As an improvement to the above scheme, the constraint on the number of personnel in the power plant is as follows: In the formula, w gn w go w hw S w n w v and w r These represent the number of personnel required to operate a natural gas power plant, a coal-fired power plant, a hydroelectric power plant, a photovoltaic power plant, a nuclear power plant, a wind power plant, and a primary renewable energy power plant or power plant to generate 1 MW of power, respectively. t max and W t min These represent the upper and lower limits of the number of power generation workers that can be provided in the area severely affected by the sudden event at time t.

[0014] As an improvement to the above scheme, the solid-liquid fuel supply constraint is as follows: In the formula, f go and f n F represents the amount of liquid or solid fuel required for a coal-fired power plant and a nuclear power plant to generate 1 MW of power, respectively. t max and F t min These represent the upper and lower limits of the amount of liquid or solid fuel that can be provided at time t in areas severely affected by a sudden event.

[0015] Another embodiment of the present invention provides an energy supply planning device for emergencies. The energy supply planning device includes a data acquisition unit, a model building unit, and a solution scheduling unit. The data acquisition unit is used to acquire energy supply planning data sets and emergency situation user data. The model building unit is used to construct a cost optimization objective function based on a preset emergency event energy supply cost model set. The emergency event energy supply cost model set includes a system energy supply cost model and an affected area energy supply cost model. The solution scheduling unit is used to calculate and obtain a cost optimization scheduling strategy based on a preset emergency event impact constraint set, the emergency event scheduling data set, and emergency situation user data, and to perform energy supply planning under emergencies based on the cost optimization scheduling strategy.

[0016] Another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the power supply planning method under emergency conditions as described above.

[0017] Another embodiment of the present invention provides an energy supply planning system for emergencies. The energy supply planning system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the energy supply planning method for emergencies as described above.

[0018] Compared with existing technologies, this technical solution has the following beneficial effects:

[0019] This invention provides a method, apparatus, computer-readable storage medium, and system for energy supply planning under emergencies. By considering the impact of emergencies such as pandemics and taking into account the different impacts of external events on different regions, an energy supply cost optimization model considering the impact of pandemics and other events is established to reasonably optimize energy supply costs. This method, apparatus, computer-readable storage medium, and system for energy supply planning and management under emergencies improves the efficiency and accuracy of energy supply planning under emergencies. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating an energy supply planning method under emergency conditions provided by an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram of the structure of an energy supply planning device under emergency conditions provided in an embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Specific Implementation Example 1

[0024] Unexpected events include, but are not limited to, external events such as disease pandemics or wars. Because these external events occur suddenly and are quite large in scale, they often affect the energy supply and normal operation of the energy system in many aspects such as personnel input, service investment and system infrastructure in the short term. As a result, the long-term energy supply planning models commonly used in existing technologies do not match the actual situation, and the energy supply planning strategies used to deal with them are less efficient.

[0025] In this regard, the present invention first describes a method for energy supply planning under emergency events. Figure 1 This is a flowchart illustrating an energy supply planning method under emergency conditions provided by an embodiment of the present invention.

[0026] like Figure 1 As shown, the energy supply planning method includes:

[0027] S1: Obtain energy supply planning data sets and emergency user data.

[0028] To perform subsequent model analysis and solution, the input data and parameters of the optimization model must first be obtained. The input data and coefficients come from the power supply company and the electricity user, specifically including: 1) Input data and coefficients from the power supply company, including T, B, B′, G, G′, ε, c gn c go c h c S c n c v c r , w gn w go w h w S w n w v w r W t max W t min f go f n F t max F t min G gn G t max G t min The power conversion equation coefficients and upper and lower limits of power conversion efficiency of the power supply unit units; the upper and lower limits of the power supply unit's constraints on unit start-up, shutdown, ramp-up, cold start, hot start, minimum shutdown, and operating time; the energy flow equation coefficients and upper and lower limits of the energy supply lines of the energy system; 2) Data from power users include

[0029] S2: Based on the pre-set emergency energy supply cost model group, construct the cost optimization objective function.

[0030] The emergency energy supply cost model group includes a system energy supply cost model and an affected area energy supply cost model.

[0031] In one embodiment, the energy supply cost model for the affected area is as follows:

[0032]

[0033] In the formula, B′ and G′ represent the parts of B and G that are severely affected by the sudden event, respectively; C represents the power gained from the external region at time t; Gε and ε represent the total energy supply cost of the energy system and its impact factor on G, respectively; ε is determined based on the actual energy distribution in the area affected by the emergency and the historical energy demand of users; C G Cost is constrained by the factor ε; the smaller ε is, the lower C is. G It has the least impact on energy supply in areas severely affected by emergencies.

[0034] In one embodiment, the system energy supply cost model is as follows:

[0035]

[0036] In the formula, T represents the optimization time, t represents the sampling time, i and j represent the counting variables, and B and G represent the number of nodes in the energy system and the number of the largest energy source among all energy sources, respectively. If the number of a certain type of energy source G″ is less than G, when j>G″, the energy that the energy source can supply is recorded as 0; and These represent the power injected into node i at time t by the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The power obtained from the upstream power grid at time t; c gn c go c h c S c n c v and c r These represent the energy supply costs of the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively.

[0037] Among them, the first renewable energy power plant or power plant is other renewable energy power plants or power plants with a low installed capacity.

[0038] In one embodiment, the cost optimization objective function is: minC.

[0039] S3: Based on the preset set of constraints on the impact of emergencies, the set of emergency scheduling data, and the user data of emergencies, calculate and obtain the cost optimization scheduling strategy of the cost optimization objective function, and perform energy supply planning under emergencies based on the cost optimization scheduling strategy.

[0040] After obtaining the cost optimization objective function, i.e., solving it based on the constraints to be considered under unforeseen events, the model ultimately outputs the cost over the future time range T. p j,t R t C and CG The output data will be used for energy consumption regulation in areas severely affected by emergencies and for the entire energy system within a future time range of T.

[0041] In one embodiment, the set of constraints for the impact of the emergency includes total energy demand constraints, affected load constraints, node load power balance constraints, energy reserve constraints, power plant personnel number constraints, solid and liquid fuel supply constraints, and natural gas fuel supply constraints.

[0042] In one embodiment, the total energy demand constraint is:

[0043]

[0044] In the formula, This represents the load energy demand of the i-th node at time t.

[0045] In one embodiment, the affected load constraint is:

[0046]

[0047] In the formula, This represents the load energy demand of the i-th node at time t.

[0048] In one embodiment, the node load power balance constraint is:

[0049]

[0050] In the formula, and These represent the energy demand (MW) of commercial users, residential users, industrial users, and basic social services at the i-th node at time t.

[0051] In one embodiment, the energy reserve constraint is:

[0052]

[0053] In the formula, p represents the maximum power supply of the standby unit j (MW). j,t R represents the power supply (MW) of standby unit j at time t. t The rotating reserve power (MW) represents the power available at time t.

[0054] In one embodiment, the constraint on the number of personnel at the power plant is as follows:

[0055]

[0056] In the formula, wgn w go w h w S w n w v and w r These represent the number of personnel required to operate a natural gas power plant, a coal-fired power plant, a hydroelectric power plant, a photovoltaic power plant, a nuclear power plant, a wind power plant, and a primary renewable energy power plant or power plant to generate 1 MW of power, respectively. t max and W t min These represent the upper and lower limits of the number of power generation workers that can be provided in the area severely affected by the sudden event at time t.

[0057] In one embodiment, the solid-liquid fuel supply constraint is:

[0058]

[0059] In the formula, f go and f n F represents the amount of liquid or solid fuel required for a coal-fired power plant and a nuclear power plant to generate 1 MW of power, respectively. t max and F t min These represent the upper and lower limits of the amount of liquid or solid fuel that can be provided at time t in areas severely affected by a sudden event.

[0060] In one embodiment, the natural gas fuel supply constraint is:

[0061]

[0062] In the formula, G gn This represents the amount of natural gas (tons / MW) required for a natural gas generator to produce 1 MW of power. and These represent the upper and lower limits of the amount of natural gas that can be provided at time t in areas severely affected by sudden events.

[0063] In practical applications, in addition to the constraints mentioned above, the following constraints are also considered: a. Power conversion equations and power conversion efficiency constraints for power supply units such as diesel, fuel oil, coal, natural gas, nuclear energy, and pumped storage; b. Limitations on machine start-up, shutdown, ramp-up, cold start, hot start, minimum downtime, and operating time imposed by power supply units; c. Restrictions on the transportation and distribution of fuels such as natural gas; d. Energy flow equations and line power supply constraints for energy system power supply lines, such as power flow equations for power lines and restrictions on line voltage, current, power, and heat generation; e. Power balance at energy system nodes, i.e., the power injected into a node at any given time equals the power flowing out of the node.

[0064] This invention describes an energy supply planning method under emergencies. By considering the impact of emergencies such as pandemics and taking into account the different impacts of external events on different regions, an energy supply cost optimization model considering the impact of events such as pandemics is built to reasonably optimize energy supply costs. This energy supply planning and management method under emergencies improves the efficiency and accuracy of energy supply planning under emergencies. Specific Implementation Example 2

[0066] In addition to the methods described above, embodiments of the present invention also disclose an energy supply planning device for emergencies. Figure 2 This is a schematic diagram of the structure of an energy supply planning device under emergency conditions provided in an embodiment of the present invention.

[0067] like Figure 2 As shown, the energy planning device includes a data acquisition unit 11, a model building unit 12, and a solution scheduling unit 13.

[0068] The data acquisition unit 11 is used to acquire energy supply planning data sets and emergency user data.

[0069] The model building unit 12 is used to construct a cost optimization objective function based on a preset emergency energy supply cost model group; the emergency energy supply cost model group includes a system energy supply cost model and an affected area energy supply cost model.

[0070] The scheduling unit 13 is used to calculate and obtain the cost optimization scheduling strategy of the cost optimization objective function based on the preset set of constraints on the impact of emergencies, the set of emergency scheduling data, and emergency situation user data, and to perform energy supply planning under emergencies based on the cost optimization scheduling strategy.

[0071] If the integrated unit of the energy supply planning device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. Another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the energy supply planning method under emergency conditions as described above.

[0072] The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0073] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between units indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0074] This invention describes an energy supply planning device and computer-readable storage medium for emergency events. By considering the impact of emergencies such as pandemics and taking into account the different impacts of external events on different regions, an energy supply cost optimization model considering the impact of events such as pandemics is built to reasonably optimize energy supply costs. This energy supply planning and management device and computer-readable storage medium for emergency events improve the efficiency and accuracy of energy supply planning under emergencies. Specific Implementation Example 3

[0076] In addition to the methods and apparatus described above, embodiments of the present invention also describe an energy supply planning system under emergency events.

[0077] The energy supply planning system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the energy supply planning method under emergency conditions as described above.

[0078] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the device, connecting various parts of the device via various interfaces and lines.

[0079] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0080] This invention describes an energy supply planning system for emergencies. By considering the impact of emergencies such as pandemics and taking into account the different impacts of external events on different regions, an energy supply cost optimization model is built that takes into account the impact of events such as pandemics. This system optimizes energy supply costs and improves the efficiency and accuracy of energy supply planning under emergencies.

[0081] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for energy supply planning under emergency events, characterized in that, The energy supply planning method includes: Acquire energy supply planning data sets and emergency user data; Based on a pre-defined set of emergency energy supply cost models, a cost optimization objective function is constructed; the emergency energy supply cost model set includes a system energy supply cost model and an affected area energy supply cost model. Based on the preset set of constraints on the impact of emergencies, the energy supply planning data set, and the user data of emergencies, the cost optimization scheduling strategy of the cost optimization objective function is calculated and obtained, and energy supply planning under emergencies is carried out according to the cost optimization scheduling strategy. The energy supply cost model for the affected area is as follows: In the formula, B′ and G′ represent the parts of B and G that are severely affected by the sudden event, respectively; C represents the power gained from the external region at time t; G ε and ε represent the total energy supply cost of the energy system and its impact factor on G, respectively; ε is determined based on the actual energy distribution in the area affected by the emergency and the historical energy demand of users; C G Cost is constrained by the factor ε; the smaller ε is, the lower C is. G It has the least impact on energy supply in areas severely affected by emergencies. and These represent the power injected into node i at time t by the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The power obtained from the upstream power grid at time t; c gn c go c h c S c n c v and c r These represent the energy supply costs of the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The system energy supply cost model is as follows: In the formula, T represents the optimization time, t represents the sampling time, i and j represent the counting variables, B and G represent the number of nodes in the energy system and the number of the largest energy source among all energy sources, respectively; if the number of a certain type of energy source G″ is less than G, when j>G″, the energy that the energy source can supply is recorded as 0. and These represent the power injected into node i at time t by the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The power obtained from the upstream power grid at time t; c gn c go c h c S c n c v and c r These represent the energy supply costs of the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The set of constraints on the impact of the emergency includes total demand constraints for energy supply load, constraints on affected loads, constraints on nodal load power balance, constraints on energy reserves, constraints on the number of personnel in power plants, constraints on solid and liquid fuel supply, and constraints on natural gas fuel supply.

2. The energy supply planning method under emergency events according to claim 1, characterized in that, The affected load constraints are as follows: In the formula, This represents the load energy demand of the i-th node at time t.

3. The energy supply planning method under emergency events according to claim 2, characterized in that, The constraint on the number of personnel at the power plant is as follows: In the formula, w gn w go w h w S w n w v and w r These represent the number of personnel required to operate a natural gas power plant, a coal-fired power plant, a hydroelectric power plant, a photovoltaic power plant, a nuclear power plant, a wind power plant, and a primary renewable energy power plant or power plant to generate 1 MW of power, respectively. t max and W t min These represent the upper and lower limits of the number of power generation workers that can be provided in the area severely affected by the sudden event at time t.

4. The energy supply planning method under emergency events according to claim 3, characterized in that, The solid-liquid fuel supply constraints are as follows: In the formula, f go and f n F represents the amount of liquid or solid fuel required for a coal-fired power plant and a nuclear power plant to generate 1 MW of power, respectively. t max and F t min These represent the upper and lower limits of the amount of liquid or solid fuel that can be provided at time t in areas severely affected by a sudden event.

5. A power supply planning device for emergencies, characterized in that, The energy supply planning device includes a data acquisition unit, a model building unit, and a solution scheduling unit, wherein... The data acquisition unit is used to acquire energy supply planning data sets and emergency user data. The model building unit is used to construct a cost optimization objective function based on a preset emergency energy supply cost model set; the emergency energy supply cost model set includes a system energy supply cost model and an affected area energy supply cost model. The solution scheduling unit is used to calculate and obtain the cost optimization scheduling strategy of the cost optimization objective function based on the preset set of constraints on the impact of emergencies, the set of energy supply planning data, and the user data of emergencies, and to carry out energy supply planning under emergencies based on the cost optimization scheduling strategy. The energy supply cost model for the affected area is as follows: In the formula, B′ and G′ represent the parts of B and G that are severely affected by the sudden event, respectively; C represents the power gained from the external region at time t; G ε and ε represent the total energy supply cost of the energy system and its impact factor on G, respectively; ε is determined based on the actual energy distribution in the area affected by the emergency and the historical energy demand of users; C G Cost is constrained by the factor ε; the smaller ε is, the lower C is. G It has the least impact on energy supply in areas severely affected by emergencies. and These represent the power injected into node i at time t by the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The power obtained from the upstream power grid at time t; c gn c go c h c S c n c v and c r These represent the energy supply costs of the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The system energy supply cost model is as follows: In the formula, T represents the optimization time, t represents the sampling time, i and j represent the counting variables, B and G represent the number of nodes in the energy system and the number of the largest energy source among all energy sources, respectively; if the number of a certain type of energy source G″ is less than G, when j>G″, the energy that the energy source can supply is recorded as 0. and These represent the power injected into node i at time t by the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The power obtained from the upstream power grid at time t; c gn c go c h c S c n c v and c r These represent the energy supply costs of the j-th natural gas power plant, coal-fired power plant, hydropower plant, photovoltaic power plant, nuclear power plant, wind power plant, and the first renewable energy power plant or power plant, respectively. The set of constraints on the impact of the emergency includes total demand constraints for energy supply load, constraints on affected loads, constraints on nodal load power balance, constraints on energy reserves, constraints on the number of personnel in power plants, constraints on solid and liquid fuel supply, and constraints on natural gas fuel supply.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the power supply planning method under an emergency as described in any one of claims 1 to 4.

7. An energy supply planning system for emergencies, characterized in that, The energy supply planning system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the energy supply planning method under any one of claims 1 to 4.

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