Integrated energy system restoration optimization method and system considering integrated demand response

Abstract

This invention discloses a method and system for optimizing the recovery of integrated energy systems considering comprehensive demand response, relating to the field of integrated energy system recovery technology. It includes establishing a comprehensive demand response model based on the multi-energy complementarity characteristics of integrated energy systems; establishing a discrete load model and a full-stage power recovery process model considering comprehensive demand response; and establishing an optimization model for the recovery of integrated energy systems considering comprehensive demand response. The integrated energy system recovery optimization method provided by this invention, based on the multi-energy complementarity characteristics in the context of integrated energy systems, takes comprehensive demand response into account during the system recovery process. It can fully utilize the synergistic coupling characteristics of integrated energy systems, improve the recovery capability of integrated energy systems, accelerate the recovery process, and reduce losses caused by power outages. This invention achieves better results in terms of recovery capability, accelerated process, and reduced losses.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system recovery technology, specifically to an integrated energy system recovery optimization method that takes into account integrated demand response. Background Technology

[0002] Rapid economic development has led to a significant increase in modern society's reliance on electricity, placing higher demands on power quality and reliability. Integrated energy systems enable bidirectional coupling and complementarity between different forms of energy, offering greater flexibility and reliability. After a failure, leveraging the complementary relationships of energy coupling provides unique advantages for fault recovery. However, current research on disasters and failures in integrated energy systems largely focuses on the pre-disaster prevention phase, primarily concentrating on assessing and improving pre-disaster reliability and resilience. Research on the collaborative recovery of systems after disasters is limited. The highly coupled nature of integrated energy systems brings greater flexibility to the recovery process but also increases its complexity. Fully utilizing the coupling characteristics of integrated energy systems and coordinating and optimizing coupled equipment during the recovery phase are crucial for improving recovery efficiency and speed.

[0003] Integrated demand response is an extension and expansion of traditional electricity demand response within the context of integrated energy systems. Under the architecture of integrated energy systems, the coupling between different forms of energy in production, transmission, and consumption becomes increasingly strong. The characteristics of mutual coupling and conversion between different forms of energy make it possible for users to autonomously choose their energy consumption methods among different energy flows. Furthermore, as a typical application of multi-energy coupling and supply, integrated energy systems greatly promote the restoration of power supply and improve the speed of recovery in the power system. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that existing integrated energy system restoration methods suffer from inflexible load management, low restoration efficiency, poor flexibility, and the optimization problem of how to reduce power outage losses and accelerate the restoration process.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a comprehensive energy system recovery optimization method considering integrated demand response, comprising: establishing a comprehensive demand response model based on the multi-energy complementarity characteristics of the comprehensive energy system; establishing a discrete power load model and a full-stage power recovery process model considering integrated demand response; and establishing a comprehensive energy system recovery optimization model considering integrated demand response.

[0007] As a preferred embodiment of the integrated energy system recovery optimization method considering comprehensive demand response described in this invention, the establishment of the comprehensive demand response model includes a modeling process. Users can change their energy consumption patterns by modifying energy conversion equipment through convertible loads without affecting their load demand. The energy supply conversion relationship of the convertible loads is expressed as follows:

[0008]

[0009] in, Let represent the natural gas, electricity, and heat supplied to the integrated energy system by the natural gas network, distribution network, and heating network at time t, respectively, and γ, β, and γ be the energy supply ratio coefficients of natural gas, electricity, and heat, respectively. These represent the proportions of natural gas used for gas supply, power generation, heating, and cooling at time t, respectively. These represent the proportions of electrical energy used for gas production, power generation, heating, and cooling at time t, respectively. and Let represent the proportions of heat energy used for heating and cooling at time t, respectively. The constraints between the various proportion coefficients are expressed as follows:

[0010]

[0011]

[0012]

[0013] The integrated demand response and its various energy relationships are represented as follows:

[0014]

[0015] in, Let be the natural gas, electricity, heat, and cooling load values ​​participating in IDR at time t. Let be the interruptible load values ​​for natural gas, electricity, heat, and cooling at time t, respectively. Let be the transferable load values ​​of natural gas, electricity, heat, and cooling at time t, respectively. These represent the convertible load values ​​for natural gas, electricity, heat, and cooling at time t.

[0016] As a preferred embodiment of the integrated energy system recovery optimization method considering comprehensive demand response described in this invention, the discrete power load model includes, for example, a substation node in a distribution network, where the distribution network node connects to N discrete loads through the substation, with load sizes of [L1, L2, ..., L...]. N During node recovery, the amount of data recovered by the node needs to be recovered from the L1-L nodes connected to the node. N The combined values ​​for medium loads are selected. In a power system, the loads connected to nodes are discrete, and the load size of a node is expressed as follows:

[0017]

[0018] in, The load size of the node. Let ω represent the discrete load values ​​connected to the node. Let ω be a binary variable representing the connection status of load ω. When load ω connects to the system at time t... The actual load on a node is composed of all loads connected to that node. The load value consists of discretely distributed values. Without considering overall demand response, the node's load recovery decision is the set of discrete load combinations. Considering overall demand response, the node's load recovery decision is based on the discrete load combinations, with a factor of size [missing value]. The flexibility margin.

[0019] As a preferred embodiment of the integrated energy system recovery optimization method considering comprehensive demand response described in this invention, the power full-stage recovery process model includes a power source recovery model. During the recovery process, the power output increases with the input of the restored load. During the power output increase process, the ramp rate satisfies the constraint expressed as follows:

[0020]

[0021] in, Let be the output of power source s at time t+1. The upper limit of power supply ramp rate, Ω gen For a power supply set, during the entire recovery process, the output of the power supply satisfies the upper and lower limit constraints, as expressed as:

[0022]

[0023] in, and These represent the minimum and maximum technical output of power supply s, respectively.

[0024] As a preferred embodiment of the integrated energy system restoration optimization method considering comprehensive demand response described in this invention, the full-stage power restoration process model further includes a grid reconfiguration model, in which nodes and lines that have been restored during the grid restoration process are no longer de-energized, represented as:

[0025]

[0026]

[0027] in, and Ω represents the binary auxiliary variables for node n and line l, respectively. A value of 1 indicates that node n and line l have been restored. bus and Ω line Let be the set of nodes and the set of lines in the system, respectively. The necessary but not sufficient condition for line recovery is that the first and last nodes have been recovered, expressed as:

[0028]

[0029] in, Ω is the set of lines connected to node n. time Let be the set of time steps in the entire recovery process. A necessary condition for node recovery is that at least one connected path has been restored, expressed as:

[0030]

[0031] Taking into account both manual operation and line closing time, if neither of the adjacent lines of any given line has been restored, then any given line cannot be restored, which is expressed as:

[0032]

[0033] in, Let k be the set of lines adjacent to line k.

[0034] As a preferred embodiment of the integrated energy system recovery optimization method considering comprehensive demand response described in this invention, the full-stage power recovery process model further includes a discrete load recovery model, in which the load is only restored after one node is restored, expressed as:

[0035]

[0036] in, Let n be a binary auxiliary variable representing the load recovery state of node n. When this occurs, it indicates that the load on node n begins to recover. Loads that do not require demand response during the recovery process will no longer be cut off, as expressed as:

[0037]

[0038] in, The load power restored at node n This represents the maximum load value for node n. For load nodes that do not consider demand response, and considering line power flow constraints, the load restored at each time step does not exceed a preset upper limit, expressed as:

[0039]

[0040] Among them, P L,rampTo define the upper limit of the load recovery amount per hour step, and considering the discreteness of the power load, the discreteness constraint of the load recovery process is expressed as:

[0041]

[0042] Where ω is the ω-th load connected to node n. Let n be the set of loads connected to node n. Let ω be the binary variable for load recovery. When load ω recovers at time t, ω = 1. Let ω be the load value.

[0043] As a preferred embodiment of the integrated energy system recovery optimization method considering comprehensive demand response described in this invention, the integrated energy system recovery optimization model includes an importance index, and the objective function of the recovery optimization model is to maximize the load recovery amount and the importance index of the recovered load, expressed as:

[0044]

[0045] in, and I represents the electrical load and thermal load restored at time t, respectively. bus,n This serves as an indicator of the importance of each node.

[0046] Another objective of this invention is to provide an integrated energy system recovery optimization system that considers comprehensive demand response. This system can analyze the discrete nature of loads in the power system through the recovery process module and provide detailed recovery strategies for each recovery stage, thus solving the problems of insufficient flexibility and low efficiency in the current recovery process.

[0047] As a preferred embodiment of the integrated energy system recovery and optimization system considering comprehensive demand response according to the present invention, it includes: a demand response module, a recovery process module, and a system recovery module; the demand response module is used to establish a comprehensive demand response model based on the multi-energy complementarity characteristics of the integrated energy system; the recovery process module is used to establish a discrete power load model and a full-stage power recovery process model considering comprehensive demand response; and the system recovery module is used to establish an integrated energy system recovery and optimization model considering comprehensive demand response.

[0048] A computer device includes a memory and a processor, the memory storing a computer program, characterized in that the processor executes the computer program to implement a comprehensive energy system recovery optimization method that takes into account integrated demand response.

[0049] A computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of a comprehensive energy system recovery optimization method that takes into account integrated demand response.

[0050] The beneficial effects of the present invention are as follows: The integrated energy system recovery optimization method considering comprehensive demand response provided by the present invention is based on the multi-energy complementarity characteristics under the background of integrated energy, establishes a comprehensive demand response model in the integrated energy system, and takes comprehensive demand response into account in the system recovery process. It can make full use of the synergistic coupling characteristics of the integrated energy system, improve the recovery capability of the integrated energy system, accelerate the recovery process of the integrated energy system, and reduce the losses caused by power outages. The present invention achieves better results in terms of recovery capability, acceleration process and loss reduction. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort. Wherein:

[0052] Figure 1 The overall flowchart of the integrated energy system recovery optimization method considering comprehensive demand response provided in the first embodiment of the present invention is shown.

[0053] Figure 2 The system topology diagram is provided for the integrated energy system recovery optimization method considering comprehensive demand response, as shown in the second embodiment of the present invention.

[0054] Figure 3 The diagram shows the load recovery status at each time step of the integrated energy system recovery optimization method considering comprehensive demand response provided in the second embodiment of the present invention.

[0055] Figure 4 The diagram shows the total power output and total load recovery of the integrated energy system recovery optimization method considering comprehensive demand response provided in the second embodiment of the present invention.

[0056] Figure 5 The overall flowchart of the integrated energy system recovery optimization system considering comprehensive demand response is provided for the third embodiment of the present invention. Detailed Implementation

[0057] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0058] Example 1

[0059] Reference Figure 1 As one embodiment of the present invention, a comprehensive energy system recovery optimization method considering integrated demand response is provided, comprising:

[0060] S1: Based on the multi-energy complementarity characteristics of the integrated energy system, establish an integrated demand response model.

[0061] Furthermore, establishing a comprehensive demand response model includes the modeling process.

[0062] It should be noted that users can change their energy consumption patterns by modifying energy conversion equipment through convertible loads without affecting their load demand. The energy supply and conversion relationship of convertible loads is expressed as follows:

[0063]

[0064] in, Let represent the natural gas, electricity, and heat supplied to the integrated energy system by the natural gas network, distribution network, and heating network at time t, respectively, and α, β, and γ be the energy supply ratio coefficients of natural gas, electricity, and heat, respectively. These represent the proportions of natural gas used for gas supply, power generation, heating, and cooling at time t, respectively. These represent the proportions of electrical energy used for gas production, power generation, heating, and cooling at time t, respectively. and Let represent the proportions of heat energy used for heating and cooling at time t, respectively. The constraints between the various proportion coefficients are expressed as follows:

[0065]

[0066]

[0067]

[0068] The integrated demand response and its various energy relationships are represented as follows:

[0069]

[0070] in, Let be the natural gas, electricity, heat, and cooling load values ​​participating in IDR at time t. Let be the interruptible load values ​​for natural gas, electricity, heat, and cooling at time t, respectively. Let be the transferable load values ​​of natural gas, electricity, heat, and cooling at time t, respectively. These represent the convertible load values ​​for natural gas, electricity, heat, and cooling at time t.

[0071] It should also be noted that electricity demand response (EDR) involves electricity retailers instructing users to change their electricity consumption during specific time periods through electricity prices or incentive policies. This manifests as changes in demand-side electricity consumption within a unit of time, i.e., the horizontal shift and reduction of demand-side load over time. Because this can affect users' energy comfort, it reduces user participation and load controllability, failing to fully realize users' load response potential. In contrast, integrated demand response (ICR) not only reflects changes in users' energy consumption within a unit of time but also includes changes in the form of energy used within that time period. ICR utilizes various energy conversion devices to achieve mutual conversion between energy sources. This means that users can choose their energy supply method based on the current electricity, heat, and natural gas prices, thereby reducing operating costs and alleviating system energy supply pressure. ICR uses energy type as the vertical axis and time as the horizontal axis. Compared to electricity demand response, which simply focuses on horizontal time shifts and energy reductions, ICR extends demand-side response behavior by combining vertical energy type conversion with horizontal time shifts. This effectively stimulates load flexibility, improves users' energy comfort, and better realizes the response potential of the demand side.

[0072] It should also be noted that, based on different response methods of integrated demand response, the loads that users respond to autonomously in integrated demand response can be divided into three types according to their characteristics: loads that can be reduced, loads that can be transferred, and loads that can be converted. Users can respond to the operational needs of the superior by rationally selecting their integrated demand response behavior, making full use of the coupling relationship between different energy sources and the peak-valley time difference, so as to achieve coordinated optimization of the user's own energy consumption and the operation of the integrated energy system. Loads that users can increase or decrease the energy consumption of a certain energy source based on price signals or incentive mechanisms are loads that can be reduced. Loads whose total energy consumption is determined within the dispatch cycle but can be shifted over time within the dispatch cycle are loads that can be transferred. The above two types of loads are the same as those in traditional electricity demand response. Since the energy conversion equipment in the integrated energy system provides users with the opportunity to switch between different energy consumption modes, loads that can be converted are the main difference between integrated demand response and electricity demand response.

[0073] S2: Establish a discrete power load model and a full-stage power recovery process model that take into account comprehensive demand response.

[0074] Furthermore, the discrete load model of electricity includes a substation node in the distribution network as an example.

[0075] It should be noted that the distribution network node connects to N discrete loads through a substation, with load sizes of [L1, L2, ..., L]. N During node recovery, the amount of data recovered by the node needs to be recovered from the L1-L nodes connected to the node. N The combined values ​​for medium loads are selected. In a power system, the loads connected to nodes are discrete, and the load size of a node is expressed as follows:

[0076]

[0077] in, The load size of the node. Let ω represent the discrete load values ​​connected to the node. Let ω be a binary variable representing the connection status of load ω. When load ω connects to the system at time t... The actual load on a node is composed of all loads connected to that node. The load value consists of discretely distributed values. Without considering overall demand response, the node's load recovery decision is the set of discrete load combinations. Considering overall demand response, the node's load recovery decision is based on the discrete load combinations, with a factor of size [missing value]. The flexibility margin.

[0078] It should also be noted that loads in a power system are connected through transformers, substations, etc. In reality, when a substation node restores power, the load power of that node is not continuously variable, but rather a series of discrete values ​​composed of several connected loads.

[0079] Furthermore, the full-stage power recovery process model includes a power source recovery model.

[0080] It should be noted that during the recovery process, the power output increases as the restored load is put into operation. During the power output increase process, the ramp rate satisfies the constraint as follows:

[0081]

[0082] in, Let be the output of power source s at time t+1. The upper limit of power supply ramp rate, Ω gen For a power supply set, during the entire recovery process, the output of the power supply satisfies the upper and lower limit constraints, as expressed as:

[0083]

[0084] in, and These represent the minimum and maximum technical output of power supply s, respectively.

[0085] Furthermore, the full-stage power restoration process model also includes a grid reconfiguration model.

[0086] It should be noted that during the network restoration process, the restored nodes and lines will no longer be powered off, as indicated by:

[0087]

[0088]

[0089] in, and Ω represents the binary auxiliary variables for node n and line l, respectively. A value of 1 indicates that node n and line l have been restored. bus and Ω line Let be the set of nodes and the set of lines in the system, respectively. The necessary but not sufficient condition for line recovery is that the first and last nodes have been recovered, expressed as:

[0090]

[0091] in, Ω is the set of lines connected to node n. time Let be the set of time steps in the entire recovery process. A necessary condition for node recovery is that at least one connected path has been restored, expressed as:

[0092]

[0093] Taking into account both manual operation and line closing time, if neither of the adjacent lines of any given line has been restored, then any given line cannot be restored, which is expressed as:

[0094]

[0095] in, Let k be the set of lines adjacent to line k.

[0096] Furthermore, the full-stage power recovery process model also includes a discrete load recovery model.

[0097] It should be noted that the load is only restored after a node is restored, as shown below:

[0098]

[0099] in, Let n be a binary auxiliary variable representing the load recovery state of node n. When this occurs, it indicates that the load on node n begins to recover. Loads that do not require demand response during the recovery process will no longer be cut off, as expressed as:

[0100]

[0101] in, The load power restored at node n This represents the maximum load value for node n. For load nodes that do not consider demand response, and considering line power flow constraints, the load restored at each time step does not exceed a preset upper limit, expressed as:

[0102]

[0103] Among them, P L,ramp To define the upper limit of the load recovery amount per hour step, and considering the discreteness of the power load, the discreteness constraint of the load recovery process is expressed as:

[0104]

[0105] Where ω is the ω-th load connected to node n. Let n be the set of loads connected to node n. Let ω be the binary variable for load recovery. When load ω recovers at time t, ω = 1. Let ω be the load value.

[0106] It should also be noted that in most existing studies on power system restoration, the restoration process is generally divided into three stages: black start, grid reconfiguration, and load restoration. However, in actual restoration, there are usually no clear boundaries between different restoration stages. This is because during power restoration, in order to ensure the power flow constraints of the system, the load power needs to be restored synchronously according to the generating power of the units. This is to ensure the real-time balance between the source and load in the system. Therefore, load restoration is also carried out synchronously during power restoration. In order to form a complete path from the power source to the load, the corresponding lines need to be restored. Therefore, the grid reconfiguration process will inevitably accompany the power restoration and load restoration processes. Therefore, with the full-stage restoration of the power system as the main goal, the restoration process is not artificially divided into stages. The following modeling of power source, grid, and load restoration is based solely on the restoration object as the classification standard, and the restoration processes of power source, grid, and load are carried out simultaneously without distinguishing the order of time.

[0107] S3: Establish a comprehensive energy system recovery optimization model that takes into account integrated demand response.

[0108] Furthermore, the integrated energy system recovery optimization model includes importance indicators.

[0109] It should be noted that the objective function of the recovery optimization model is to maximize the load recovery amount and the importance index of the recovered load, expressed as:

[0110]

[0111] in, and I represents the electrical load and thermal load restored at time t, respectively. bus,n This serves as an indicator of the importance of each node.

[0112] It should also be noted that in reality, the pipelines of natural gas and heating networks are usually buried underground and are not easily affected by special circumstances such as extreme weather. The probability of failure is extremely low. Therefore, this paper believes that the failure only occurred in the power system, while the natural gas and heating systems did not fail. However, under extreme weather conditions, the supply of natural gas and heat is limited, and the demand for natural gas and heat loads increases. In addition, some heat sources are electric-to-heat equipment, so power outages due to power system failures will also affect the normal operation of the heating system.

[0113] It should also be noted that the recovery model comprehensively considers integrated demand response constraints, natural gas system operation constraints, thermal system operation constraints, power flow constraints, frequency constraints, equipment operation constraints, and power balance constraints.

[0114] Example 2

[0115] Reference Figures 2-4 As an embodiment of the present invention, a comprehensive energy system recovery optimization method considering integrated demand response is provided. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0116] A case study is conducted using a combined energy system that couples a modified IEEE 39-node power system, a 44-node thermal system, and a 20-node Belgian natural gas system. The system topology is as follows: Figure 2 As shown, the following assumptions are made in the example: Only the power system in the integrated energy system experiences a fault. The power outage leads to an interruption in the heat supply, and the supply of natural gas and heat is limited, resulting in a large demand for heat and natural gas. At the start of recovery, the black start phase of the generator units has been completed, meaning they have all reached their minimum technical output. The recovery model proposed in this paper is used to optimize the subsequent recovery strategy. During the recovery process, no phases are divided; the recovery of power sources, the grid, and loads occurs simultaneously. Not all nodes in the power system have loads; some nodes only serve as grid connections and have no connected loads. The example uses a 5-minute time step for power system recovery, with the recovery start time being the first time step. A total of 61 time steps are set. In the following analysis, time is represented by the number of time steps calculated from the start of recovery; for example, t = 15 represents the 15th time step after the start of recovery.

[0117] As shown in Table 1, the model of this invention completed the restoration of all loads at the 20th time step, with a total restored power load of 78708.18 MWh and a maximum restored power load of 1413.38 MW. To further illustrate the power load restoration, the load restoration status of each power load node in the system is displayed below. Figure 3 In terms of heat load, the total recovery amount is 30214 MWh.

[0118] Table 1. Recovery Results of the Model of the Invention

[0119] recover Example Results Restore completion time 20 o'clock Electrical load recovery value 1413.38MW Total electrical load restoration 78708.18MWh Heat load recovery 30214MWh

[0120] from Figure 4 It can be seen that the amount of power load restored by the system in the first two time steps is relatively small, with a restoration amount of 157.78MW in the first time step and 481.47MW in the second time step. However, the output of various power sources is at a high level at these two times, far exceeding the load restoration amount at that time. At this time, excess power is stored through energy storage. In the third time step, the electrical energy stored in the energy storage in the first two time steps is released, and the system restores a large amount of power load at this time. The power load restoration amount in the third time step increases dramatically, reaching 717.89MW. At this time, not only does the power output increase, but the discharge of energy storage greatly promotes the system's power load restoration process. Furthermore, in the subsequent 4th to 6th time steps, energy storage releases a large amount of power, supporting the load restoration in this period and increasing the total load restoration of the system.

[0121] Example 3

[0122] Reference Figure 5 As an embodiment of the present invention, an integrated energy system recovery optimization system considering comprehensive demand response is provided, including: a demand response module, a recovery process module, and a system recovery module.

[0123] The demand response module is used to establish a comprehensive demand response model based on the multi-energy complementarity characteristics of the integrated energy system; the recovery process module is used to establish a discrete load model of electricity considering comprehensive demand response and a full-stage recovery process model of electricity; and the system recovery module is used to establish an optimization model for the recovery of the integrated energy system considering comprehensive demand response.

[0124] If a function 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, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0125] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0126] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0127] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc. It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0128] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A comprehensive energy system recovery optimization method considering integrated demand response, characterized in that, include: Based on the multi-energy complementarity characteristics of integrated energy systems, a comprehensive demand response model is established; Establish a discrete load model for electricity that considers comprehensive demand response and a full-stage power recovery process model; Establish a comprehensive energy system recovery optimization model that takes into account integrated demand response.

2. The integrated energy system recovery optimization method considering comprehensive demand response as described in claim 1, characterized in that: The establishment of the comprehensive demand response model includes a modeling process. Users can change their energy consumption patterns by modifying energy conversion equipment through convertible loads without affecting their load demand. The energy supply and conversion relationship of the convertible loads is expressed as follows: in, Let represent the natural gas, electricity, and heat supplied to the integrated energy system by the natural gas network, distribution network, and heating network at time t, respectively, and α, β, and γ be the energy supply ratio coefficients of natural gas, electricity, and heat, respectively. These represent the proportions of natural gas used for gas supply, power generation, heating, and cooling at time t, respectively. These represent the proportions of electrical energy used for gas production, power generation, heating, and cooling at time t, respectively. and Let represent the proportions of thermal energy used for heating and cooling at time t, respectively. The constraints between the various proportionality coefficients are expressed as follows: The integrated demand response and its various energy relationships are represented as follows: in, Let be the natural gas, electricity, heat, and cooling load values ​​participating in IDR at time t. Let be the interruptible load values ​​for natural gas, electricity, heat, and cooling at time t, respectively. Let be the transferable load values ​​of natural gas, electricity, heat, and cooling at time t, respectively. These represent the convertible load values ​​for natural gas, electricity, heat, and cooling at time t.

3. The integrated energy system recovery optimization method considering comprehensive demand response as described in claim 2, characterized in that: The discrete load model of the power grid includes a substation node in the distribution network as an example. The distribution network node is connected to N discrete loads through the substation, and the load size is [L1, L2, ..., L]. N During node recovery, the amount of data recovered by the node needs to be recovered from the L1-L nodes connected to the node. N The combined values ​​for medium loads are selected. In a power system, the loads connected to nodes are discrete, and the load size of a node is expressed as follows: in, The load size of the node. Let ω represent the discrete load values ​​connected to the node. Let ω be a binary variable representing the connection status of load ω. When load ω connects to the system at time t... The actual load on a node is composed of all loads connected to that node. The load value consists of discretely distributed values. Without considering overall demand response, the node's load recovery decision is the set of discrete load combinations. Considering overall demand response, the node's load recovery decision is based on the discrete load combinations, with a factor of size [missing value]. The flexibility margin.

4. The integrated energy system recovery optimization method considering comprehensive demand response as described in claim 3, characterized in that: The full-stage power restoration process model includes a power source restoration model. During the restoration process, the power output increases as the restored load is added. During the power output increase process, the ramp rate satisfies the following constraint: in, Let be the output of power source s at time t+1. The upper limit of power supply ramp rate, Ω gen For a power supply set, during the entire recovery process, the output of the power supply satisfies the upper and lower limit constraints, as expressed as: in, and These represent the minimum and maximum technical output of power supply s, respectively.

5. The integrated energy system recovery optimization method considering comprehensive demand response as described in claim 4, characterized in that: The full-stage power restoration process model also includes a grid reconfiguration model, in which nodes and lines that have been restored during the grid restoration process are no longer de-energized, represented as: in, and Ω represents the binary auxiliary variables for node n and line l, respectively. A value of 1 indicates that node n and line l have been restored. bus and Ω line Let be the set of nodes and the set of lines in the system, respectively. The necessary but not sufficient condition for line recovery is that the first and last nodes have been recovered, expressed as: in, Ω is the set of lines connected to node n. time Let be the set of time steps in the entire recovery process. A necessary condition for node recovery is that at least one connected path has been restored, expressed as: Taking into account both manual operation and line closing time, if neither of the adjacent lines of any given line has been restored, then any given line cannot be restored, which is expressed as: in, Let k be the set of lines adjacent to line k.

6. The integrated energy system recovery optimization method considering comprehensive demand response as described in claim 5, characterized in that: The full-stage power restoration process model also includes a discrete load restoration model, where the load is restored only after one node is restored, as shown below: in, Let n be a binary auxiliary variable representing the load recovery state of node n. When this occurs, it indicates that the load on node n begins to recover. Loads that do not require demand response during the recovery process will no longer be cut off, as expressed as: in, The load power restored at node n This represents the maximum load value for node n. For load nodes that do not consider demand response, and considering line power flow constraints, the load restored at each time step does not exceed a preset upper limit, expressed as: Among them, P L,ramp To define the upper limit of the load recovery amount per hour step, and considering the discreteness of the power load, the discreteness constraint of the load recovery process is expressed as: Where ω is the ω-th load connected to node n. Let n be the set of loads connected to node n. Let ω be the binary variable representing the recovery of load ω. When load ω recovers at time t, ω = 1. Let ω be the load value.

7. The integrated energy system recovery optimization method considering comprehensive demand response as described in claim 6, characterized in that: The integrated energy system recovery optimization model includes an importance index. The objective function of the recovery optimization model is to maximize the load recovery amount and the importance index of the recovered load, expressed as: in, and I represents the electrical load and thermal load restored at time t, respectively. bus,n This serves as an indicator of the importance of each node.

8. A system employing the integrated energy system recovery optimization method considering comprehensive demand response as described in any one of claims 1 to 7, characterized in that: It includes a demand response module, a recovery process module, and a system recovery module; The demand response module is used to establish a comprehensive demand response model based on the multi-energy complementarity characteristics of the integrated energy system. The recovery process module is used to establish a discrete power load model that considers comprehensive demand response and a full-stage power recovery process model; The system recovery module is used to establish an integrated energy system recovery optimization model that takes into account comprehensive demand response.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the integrated energy system recovery optimization method considering integrated demand response as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the integrated energy system recovery optimization method considering integrated demand response as described in any one of claims 1 to 7.

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