A regional integrated energy system station network collaborative phased expansion planning method and system

Abstract

The application discloses a regional integrated energy system station-network collaborative staged expansion planning method and system, comprising the following steps: acquiring multi-energy load demand data of load points and construction resource data of energy stations, and determining an optimal weighted path of a source and a load according to available energy network paths between the load points and the energy stations to form an energy network optimization candidate path matrix; for each staged construction scheme, taking the minimum whole life cycle cost as a target, taking energy station staged planning constraints and energy transmission network staged planning constraints as constraint conditions, constructing a regional integrated energy system station-network collaborative planning model to obtain an optimal system planning configuration scheme under each staged construction scheme; and taking the system planning configuration scheme with the minimum whole life cycle cost as a final system planning configuration scheme. The energy station site selection, equipment capacity configuration and energy transmission network layout are realized, and the overall economy of the global planning of the integrated energy "source-network-load-storage" integrated system is improved.

Description

Technical Field

[0001] This invention relates to the field of integrated energy system planning technology, and in particular to a method and system for phased expansion planning of regional integrated energy system stations and networks. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Regional integrated energy systems, with their advantages of multi-energy complementarity and synergy, and source-load interaction and coordination, greatly improve the efficiency of comprehensive energy utilization, promote the local consumption of renewable energy, and achieve sustainable energy development. Regional integrated energy systems are complex and diverse in form, including energy stations, energy transmission networks, and load users. As an integrated system of "source, grid, load, and storage," its planning and design involves the optimized site selection of energy stations, the optimized configuration of energy station equipment, and the optimized layout and configuration of the transmission network. These three issues are interconnected and mutually influential.

[0004] Existing research and planning methods have the following problems when solving integrated energy system planning problems:

[0005] 1) Treating energy station site selection, energy station equipment configuration, and energy transmission network layout as three relatively separate issues, and relying on engineering experience for comparison in some design stages, leads to design schemes deviating from the optimal global source-grid-load-storage system, thereby affecting the system's energy efficiency and economy.

[0006] 2) The construction sequence of integrated energy systems should be implemented in conjunction with regional development and load growth. Existing methods mostly focus on one-time construction planning, which can easily lead to equipment redundancy in the early stage of operation and equipment aging in the later stage, failing to maximize the benefits of the equipment. On the other hand, existing extended planning methods mostly only consider one or a few types of equipment such as energy storage devices and gas turbine units, which limits the application scenarios. Summary of the Invention

[0007] To address the aforementioned issues, this invention proposes a phased expansion planning method and system for regional integrated energy system stations and networks. This method enables the selection of energy station locations, configuration of equipment capacity, and layout of the energy transmission network, achieving phased and staged joint optimization planning and improving the overall economic efficiency of the integrated energy "source-grid-load-storage" system's global planning.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] In a first aspect, the present invention provides a method for phased expansion planning of a regional integrated energy system with coordinated power station and grid operations, comprising:

[0010] Acquire multi-energy load demand data at load points and construction resource data for energy stations, and determine the optimal weighted path of source and load based on the available energy network paths between load points and energy stations to form an optimized alternative path matrix for the energy network.

[0011] The phased planning constraints for energy sites are determined based on the construction resource data of energy sites, and the phased planning constraints for the energy transmission network are determined based on the optimized alternative path matrix of the energy network.

[0012] A set of phased construction schemes for the regional integrated energy system is determined. For each phased construction scheme, the optimization objective is to minimize the total life cycle cost. The constraints are the phased planning constraints of energy sites and the phased planning constraints of the energy transmission network. A regional integrated energy system station-network collaborative planning model is constructed to obtain the optimal system planning configuration scheme under each phased construction scheme.

[0013] The system planning and configuration scheme for the regional integrated energy system is selected by traversing the set of phased construction schemes and choosing the scheme with the lowest total life cycle cost.

[0014] As an alternative implementation method, the process of forming an energy grid optimization alternative path matrix includes:

[0015] An undirected graph of the energy network is constructed based on available energy network paths and intermediate nodes. Each edge of the undirected graph of the energy network is weighted according to the actual physical distance between any adjacent nodes and the construction difficulty coefficient of the integrated energy supply network.

[0016] Determine the optimal source-load weighted path from the energy station to the load point, and after traversing all combinations of energy stations and load points, form a set of optimal source-load weighted paths;

[0017] By deleting all edges in the undirected graph of the energy network that do not pass through the optimal weighted path of the source and load, we obtain the undirected graph of the new energy network. The adjacency matrix of the undirected graph of the new energy network is the optimal alternative path matrix of the energy network.

[0018] As an alternative implementation method, a library of feasible equipment types for each energy site is determined based on the construction resource data of each energy site, so as to construct phased planning constraints for energy sites. The phased planning constraints for energy sites include equipment investment constraints, equipment operation constraints, internal network and energy balance constraints.

[0019] The equipment operation constraints include the operation constraints of gas-fired cogeneration units, gas-fired boilers, absorption chillers, electric boilers, electric chillers, heat pumps, photovoltaic, wind power and solar water heating collectors, and multi-energy storage equipment.

[0020] The station network and energy balance constraints include cooling, heating, electrical and power balance constraints and process flow network constraints.

[0021] As an alternative implementation method, the phased planning constraints of the energy transmission network include constraints on the construction and transmission of the power network, constraints on the construction and transmission of the cold and hot water transmission network in the energy network, constraints on the construction and transmission of the gas transmission network, and constraints on the power balance of the energy network.

[0022] As an alternative implementation method, the total life cycle cost includes the construction and operation and maintenance costs of the energy station and the energy transmission network.

[0023] As an alternative implementation method, the optimal system planning configuration scheme under each phased construction plan is obtained based on the regional integrated energy system station-network collaborative planning model. The specific process includes:

[0024] The regional integrated energy system station-network collaborative planning model is decomposed into an outer layer configuration optimization problem and an inner layer operation optimization problem. The outer layer configuration optimization problem aims to minimize the total life cycle cost, and the decision variables are the equipment capacity configuration of each energy station in each period and the construction capacity of each section of pipeline in the pipeline network. The inner layer operation optimization problem contains N problems, corresponding to the operation optimization problems from year 1 to year N under a given system planning configuration scheme, with the operation and maintenance cost of the corresponding year as the minimum optimization objective.

[0025] As an alternative implementation method, the system planning and configuration scheme includes the site selection of energy sites, equipment capacity configuration, and energy transmission network layout.

[0026] Secondly, the present invention provides a regional integrated energy system station-grid coordinated phased expansion planning system, comprising:

[0027] The data acquisition and processing module is configured to acquire multi-energy load demand data of load points and construction resource data of energy stations, and determine the optimal weighted path of source and load based on the available energy network paths between load points and energy stations to form an energy network optimization alternative path matrix.

[0028] The constraint construction module is configured to determine phased planning constraints for energy sites based on construction resource data of energy sites, and to determine phased planning constraints for the energy transmission network based on the energy network optimization alternative path matrix.

[0029] The phased planning determination module is configured to determine the set of phased construction schemes for the regional integrated energy system. For each phased construction scheme, the optimization objective is to minimize the total life cycle cost. The constraints are the phased planning constraints of energy sites and the phased planning constraints of the energy transmission network. The module constructs a regional integrated energy system station-network collaborative planning model to obtain the optimal system planning configuration scheme under each phased construction scheme.

[0030] The system planning determination module is configured to traverse the set of phased construction schemes and select the system planning configuration scheme with the lowest total life cycle cost as the system planning configuration scheme for the regional integrated energy system.

[0031] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0032] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0034] This invention proposes a phased expansion planning method and system for regional integrated energy system stations and networks. The resulting system planning and configuration scheme realizes the site selection, equipment configuration and energy transmission network layout of energy stations in the regional integrated energy system, realizes phased and staged joint optimization planning, improves the overall economic efficiency of the integrated energy "source, grid, load and storage" system, and realizes multi-energy coordinated and efficient operation.

[0035] This invention proposes a phased expansion planning method and system for regional integrated energy system station-network coordination. It takes into account the combination and configuration of various energy conversion and storage devices commonly used in integrated energy systems, as well as practical factors such as transmission loss of the energy transmission network. The hierarchical iterative solution method proposed for large-scale optimization models can effectively improve computational efficiency and has good engineering applicability.

[0036] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0037] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0038] Figure 1 This is a schematic diagram of the phased expansion planning method for regional integrated energy system station network coordination provided in Embodiment 1 of the present invention. Detailed Implementation

[0039] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0040] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0041] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0042] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0043] Example 1

[0044] This embodiment provides a phased expansion planning method for regional integrated energy system with coordinated station-grid operations. It is designed for multiple users within a region and can effectively realize the phased expansion planning and optimized equipment capacity configuration of the integrated regional energy system, encompassing "source, grid, load, and storage." For example... Figure 1 As shown, it includes:

[0045] Acquire multi-energy load demand data at load points and construction resource data for energy stations, and determine the optimal weighted path of source and load based on the available energy network paths between load points and energy stations to form an optimized alternative path matrix for the energy network.

[0046] The phased planning constraints for energy sites are determined based on the construction resource data of energy sites, and the phased planning constraints for the energy transmission network are determined based on the optimized alternative path matrix of the energy network.

[0047] A set of phased construction schemes for the regional integrated energy system is determined. For each phased construction scheme, the optimization objective is to minimize the total life cycle cost. The constraints are the phased planning constraints of energy sites and the phased planning constraints of the energy transmission network. A regional integrated energy system station-network collaborative planning model is constructed to obtain the optimal system planning configuration scheme under each phased construction scheme.

[0048] The system planning and configuration scheme for the regional integrated energy system is selected by traversing the set of phased construction schemes and choosing the scheme with the lowest total life cycle cost.

[0049] The system planning and configuration scheme includes the site selection of energy stations, equipment configuration, and energy transmission network layout.

[0050] In this embodiment, the location of each load point and the annual multi-energy load demand, as well as the location and construction resource data of each energy station, are obtained;

[0051] Among them, the annual multi-energy load demand data for each load point includes: hourly load demand data for cooling, heating, and electricity for typical days of each season within the planning cycle of each load point;

[0052] The construction resource data for each energy site includes the upper and lower limits of the construction capacity of various equipment such as gas-fired combined cooling, heating and power units, gas-fired boilers, electric boilers, electric refrigeration units, heat pumps, distributed photovoltaics, distributed wind power, and multi-energy storage equipment at each energy site, as well as wind and solar resource data.

[0053] In this embodiment, based on the available energy network paths between load points and energy stations, the Dijkstra algorithm is used to determine the optimal source-load weighted path from each energy station to each load point, thereby forming an optimized candidate path matrix for the energy network; specifically:

[0054] (1) Construct an undirected graph G of the energy network based on the available energy network paths and intermediate nodes, and determine the actual physical distance d between any adjacent nodes i and j. ij The construction difficulty coefficient ω of the integrated energy supply network ij Assign weight ω to each edge of the undirected graph G of the energy network. ij d ij ;

[0055] (2) Using Dijkstra's algorithm to determine energy sites To the load point The optimal weighted path of source and load is formed by traversing all combinations of energy sites and load points.

[0056] (3) Delete all edges in the undirected graph G of the energy network that do not pass through the optimal weighted path of the source and load to obtain the undirected graph of the new energy network. Its adjacency matrix is ​​the energy network optimization alternative path matrix L.

[0057] In this embodiment, a set of phased construction schemes for the regional integrated energy system is determined. For each phased construction scheme, the optimization objective is to minimize the total life-cycle cost, and the constraints are the phased planning constraints of energy stations and the phased planning constraints of the transmission network. A coordinated planning model for the regional integrated energy system is then constructed. Each phased construction scheme corresponds to the number of construction phases M and the number of years N for each phase to be put into operation. m .

[0058] In this embodiment, the phased planning constraints for energy sites are determined based on the construction resource data of the energy sites. Based on the construction resource data of each energy site, a library of equipment types that can be invested in and constructed for the energy sites is determined, and phased planning constraints for energy sites are constructed, including equipment investment constraints, equipment operation constraints, in-site network constraints, and energy balance constraints.

[0059] Specifically:

[0060] (1) The equipment investment constraint is:

[0061]

[0062] In the formula, X k,l,m Let l be the installed capacity of the k-th energy station equipment in the m-th period. Due to objective limitations, such as working capital and land area constraints, the maximum installed capacity (kW) of equipment l at the k-th energy station is determined.

[0063] (2) Equipment operation constraints include gas-fired combined heat and power (CHP) unit operation constraints, gas-fired boiler (GB) operation constraints, absorption chiller (AC) operation constraints, electric boiler (EB) operation constraints, electric chiller (EC) operation constraints, heat pump (HP) operation constraints, photovoltaic (PV), wind power (WT) and solar water heating collector (SH) operation constraints, and multi-energy storage equipment operation constraints;

[0064] in,

[0065] 1) Operating constraints of gas-fired combined heat and power (CHP) units:

[0066]

[0067]

[0068]

[0069] In the formula, and Let be the electrical and thermal output power (kW) of the CHP unit at the k-th energy site during time period t in year n; and These are the power generation efficiency and heating efficiency of the CHP unit, respectively; V k,CHP,n,t Let m³ be the natural gas consumption (m³) of the CHP unit at the k-th energy site during period t in year n. 3 / s); q G The lower heating value of natural gas (kJ / m³) 3 M n This represents the number of production periods up to the nth year; m = 0 corresponds to the region already having such equipment in operation during system planning, otherwise it starts from m = 1.

[0070] 2) Operating constraints for gas-fired boilers (GB):

[0071]

[0072]

[0073] In the formula, V represents the output thermal power (kW) of the gas-fired boiler at the k-th energy station during time period t in year n; k,GB,n,t The corresponding natural gas consumption of the gas-fired boiler (m³) 3 / s); η GB This refers to the heating efficiency of a gas-fired boiler.

[0074] 3) Operating constraints of absorption chillers (AC):

[0075]

[0076]

[0077] In the formula, and Let COP represent the output cooling power and input heating power (kW) of the absorption chiller at the k-th energy station during time period t in year n; AC This refers to the energy efficiency ratio of an absorption chiller.

[0078] 4) Electric boiler (EB) operating constraints:

[0079]

[0080]

[0081] In the formula, and P k,EB,n,t η represents the output thermal power (kW) and consumed electrical power (kW) of the electric boiler at the k-th energy station during time period t in year n; EB It refers to the heating efficiency of the electric boiler.

[0082] 5) Operating constraints of the electric chiller (EC):

[0083]

[0084]

[0085] In the formula, and P k,EC,n,t These are the cooling output power (kW) and power consumption (kW) of the electric chiller at the k-th energy station during time period t in year n; COP EC This refers to the energy efficiency ratio of the electric chiller.

[0086] 6) Heat pump (HP) operating constraints:

[0087] The mathematical expressions for the output power and input power of a heat pump are as follows, and they are applicable to air source heat pumps, water source heat pumps, and ground source heat pumps:

[0088]

[0089]

[0090]

[0091]

[0092] In the formula, and Let Q be the actual input power (kW) of the heat pump unit at the k-th energy station for heating and cooling during time period t in year n; h k,HP,n,t and Q c k,HP,n,t This represents the actual heating and cooling capacity (kW) of the heat pump unit. The actual heating and cooling COP of the heat pump unit; κ HP This is the ratio of the rated cooling capacity to the rated heating capacity of the heat pump.

[0093] Since heat pumps have both heating and cooling operating modes, but can only operate in one mode at a time, they must meet the following requirements:

[0094]

[0095]

[0096]

[0097] In the formula, and It is a 0 / 1 variable, representing the operating mode of the heat pump at any given time. It is a very large number.

[0098] 7) Operational constraints for photovoltaic (PV), wind power (WT), and solar water heating collectors (SH):

[0099]

[0100] In the formula, η k,l,n,t Let represent the electrical or thermal output (kW) of a unit capacity photovoltaic, wind, or solar water heating collector at the k-th energy site during time period t in year n.

[0101] 8) Operational constraints of multi-energy storage equipment:

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] In the formula, S k,l,n,t δ represents the stored energy (kWh) of energy storage device l at the k-th energy station at the end of time period t in year n, where l ∈ {ES, WS, IS, PS}, i.e., the energy storage device, which can be a battery, water tank, ice storage tank, or phase change thermal storage device, etc.; l It is the energy loss coefficient of the energy storage device l; and These are the energy storage capacity and energy release capacity (kW) of energy storage device l, respectively; and These are the energy storage efficiency and energy release efficiency of the energy storage device l, respectively. κ is a 0 / 1 variable representing the energy storage / release state of energy storage device l; l The energy storage / release ratio of energy storage device l; and π l These are the upper and lower limits of the state of charge of energy storage device l, respectively.

[0108] (3) The network and energy balance constraints within the station include the power balance constraints of heating, cooling, electricity and gas and the process flow network constraints;

[0109] in,

[0110] 1) Power balance constraints for heating and cooling electrical systems:

[0111]

[0112]

[0113]

[0114]

[0115] In the formula, Ω e+ ,Ω e- They are collections of power generation and power consumption equipment, respectively; Ω h+ ,Ω c+ They are collections of heat-generating and cold-generating equipment, respectively; Ω g- A collection of gas-consuming devices; Ω hs ,Ω csThey are collections of heat storage and cold storage equipment, respectively. and The purchased electricity and purchased gas volume of the k-th energy station in time period t of year n; and These represent the external power supply, heat, cooling power, and corresponding gas power of the k-th energy station during time period t in year n.

[0116] 2) Process flow network constraints:

[0117]

[0118] In this embodiment, the phased planning constraints of the power transmission network are determined based on the source-load topology characteristics of the integrated regional energy system and the energy network optimization alternative path matrix L; let n i Γ is the i-th node in the energy network; j For node n i The set of adjacent nodes, that is, the n nodes in the j-th column of matrix L whose elements are 1. i A set;

[0119] Constraints in the phased planning of energy transmission networks include: constraints on the construction and transmission of power networks, constraints on the construction and transmission of cold and hot water transmission networks in energy networks, constraints on the construction and transmission of gas transmission networks, and constraints on the power balance of energy networks;

[0120] Specifically, considering the flow and loss of network transmission, the construction and transmission of power networks between nodes must meet the following constraints:

[0121]

[0122]

[0123] In the formula, and Each is composed of node n i Flow to node n j In n i Side output power and n j Side input power; For node n i To node n j Power transmission loss rate; It is a 0-1 variable, when there is power flow in the power line and its direction is from node n. i to node n j The value is 1 when the time condition is met, and 0 otherwise; β ij,m To characterize the node n in period m i to node n j The variable for whether or not to construct a power transmission pipeline is a 0-1 variable, where 1 represents construction and 0 represents no construction. For the m-th period, from node n i to node n j The capacity of power pipeline construction.

[0124] The construction and transmission constraints of hot and cold water transmission networks and gas transmission networks in the energy grid are the same as those of the power grid, and will not be repeated here.

[0125] Let the set of energy station nodes be Ω S The set of road nodes is Ω r The set of load nodes is Ω L The power balance constraints of the entire energy network are as follows:

[0126]

[0127]

[0128]

[0129] In the formula: k j For network node n j The corresponding energy station number; and The load nodes are n respectively. j The electrical, heating, cooling, and gas power required during period t in year n; and These represent the maximum active power, thermal power, and natural gas power that the energy station node can provide, respectively.

[0130] If a single piping network is used for both heating and cooling, then the following must also be met:

[0131]

[0132]

[0133]

[0134]

[0135] In the formula, and These represent the nodes from node n. i to node n j 0-1 variables for the heating and cooling modes of water supply pipelines; This refers to the combined hot and cold water transmission capacity of the water pipeline.

[0136] In this embodiment, the optimization objective of minimizing the total lifecycle cost is:

[0137]

[0138] In the formula, and These are the present values ​​of the construction costs of the energy station and the energy transmission network, respectively. and These represent the present value of the operation and maintenance costs of the energy station and the energy transmission network, respectively.

[0139] Based on the phased construction schedule, the present value of the construction cost is:

[0140]

[0141]

[0142] In the formula, N is the planning period; γ represents the discount rate; m represents the m-th planning and construction period; N m This represents the year of production commencement in the m-th planning and construction period, where it is assumed that investment costs for each period are incurred at the beginning of the year of production commencement; Π k Let c be the set of equipment that can be installed at the k-th energy station; l The unit capacity investment cost of the equipment; In N m The residual value rate of equipment installed in the year l up to the end of the Nth year; Ω is the set of energy network nodes; For node n i to node n j The portion of the cost of building an integrated energy network that is independent of the construction capacity. and For node n i to node n j The construction costs of integrated energy networks include the unit capacity costs of power network construction, water pipeline construction, and gas pipeline construction related to the construction capacity.

[0143] The present value of operation and maintenance costs is:

[0144]

[0145]

[0146] In the formula, n represents the nth year; D n Let z be the typical day set of year n; d Indicates the equivalent number of days for a typical day (d); These represent the purchased electricity price and gas price for time period t, respectively. This is the maintenance cost coefficient corresponding to the unit power output of device l; and These are nodes n in the integrated energy network. i to node n jThe operation and maintenance cost coefficients corresponding to the unit power transmission of power lines, water pipelines, and gas pipelines in a given section. It is easy to see that the present value of the total operation and maintenance cost is the sum of the present values ​​of the annual operation and maintenance costs.

[0147] In this embodiment, since the regional integrated energy system station-network collaborative planning model is a mixed integer linear programming model, this embodiment calls the CPLEX or GUROBI solver to use the branch and bound method to solve the problem, so as to obtain the optimal system planning configuration scheme under each phase construction scheme.

[0148] When the model is large, generalized Benders decomposition or hierarchical solution methods based on intelligent algorithms can be used to decompose the above model into two sub-problems: configuration optimization and operation optimization, and solve them iteratively to improve computational efficiency.

[0149] In this embodiment, a hierarchical solution method based on intelligent algorithms is given: First, the above model is decomposed into an outer configuration optimization problem and an inner operation optimization problem. The optimization objective of the outer configuration optimization problem is to minimize the present value of the total life cycle cost, and the decision variables are the capacity configuration of each energy station equipment in each period and the construction capacity of each section of pipeline in the pipeline network. The inner operation optimization problem contains N problems, corresponding to the operation optimization problems from year 1 to year N under a given configuration scheme, and the optimization objective is to minimize the present value of the operation and maintenance cost in the corresponding year.

[0150] The solution steps are as follows:

[0151] (1) Initialize the population. Each individual in the population represents the capacity configuration of each energy station equipment in each period and the construction capacity of each section of pipeline in the pipeline network.

[0152] (2) Substitute the individuals of the population into the inner layer operation optimization problem, and call the CPLEX or GUROBI solver to obtain the annual operation plan and the corresponding present value of operation and maintenance costs.

[0153] (3) Substitute the present value of annual operation and maintenance costs obtained in step (2) into the objective function of the outer configuration optimization problem, calculate the present value of the total life cycle cost of each individual in the population, sort them from smallest to largest, and update the record of the individual with the smallest present value of total life cycle cost as the optimal individual;

[0154] (4) Selection, crossover, and mutation produce offspring populations.

[0155] (5) Determine the termination condition. If the termination condition is met, output the system planning configuration scheme corresponding to the optimal individual; otherwise, return to step (2).

[0156] The system iterates through the set of phased construction schemes, solves for the corresponding optimal system planning configuration scheme, and selects the system planning configuration scheme with the lowest total life cycle cost as the final recommended planning scheme.

[0157] Example 2

[0158] This embodiment provides a regional integrated energy system station-network coordinated phased expansion planning system, including:

[0159] The data acquisition and processing module is configured to acquire multi-energy load demand data of load points and construction resource data of energy stations, and determine the optimal weighted path of source and load based on the available energy network paths between load points and energy stations to form an energy network optimization alternative path matrix.

[0160] The constraint construction module is configured to determine phased planning constraints for energy sites based on construction resource data of energy sites, and to determine phased planning constraints for the energy transmission network based on the energy network optimization alternative path matrix.

[0161] The phased planning determination module is configured to determine the set of phased construction schemes for the regional integrated energy system. For each phased construction scheme, the optimization objective is to minimize the total life cycle cost. The constraints are the phased planning constraints of energy sites and the phased planning constraints of the energy transmission network. The module constructs a regional integrated energy system station-network collaborative planning model to obtain the optimal system planning configuration scheme under each phased construction scheme.

[0162] The system planning determination module is configured to traverse the set of phased construction schemes and select the system planning configuration scheme with the lowest total life cycle cost as the system planning configuration scheme for the regional integrated energy system.

[0163] It should be noted that the above modules correspond to the steps described in Embodiment 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0164] In further embodiments, the following is also provided:

[0165] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0166] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0167] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0168] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0169] The method in Example 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0170] Those skilled in the art will recognize that the units, i.e., algorithm steps, of the various examples described in connection with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0171] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A phased expansion planning method for coordinated regional energy system grid and station operations, characterized in that, include: Obtain multi-energy load demand data of load points and construction resource data of energy stations, and construct an undirected graph of energy network based on the available energy network paths and intermediate nodes between load points and energy stations. Assign weights to each edge of the undirected graph of energy network based on the actual physical distance between any adjacent nodes and the construction difficulty coefficient of the integrated energy supply network. Determine the optimal weighted path for source loads to form an optimal alternative path matrix for the energy grid; The phased planning constraints for energy sites are determined based on the construction resource data of energy sites, and the phased planning constraints for the energy transmission network are determined based on the energy network optimization alternative path matrix. Among them, the available equipment type library for each energy site is determined based on the construction resource data of each energy site to construct the phased planning constraints for energy sites. The phased planning constraints for energy sites include equipment investment constraints, equipment operation constraints, internal network and energy balance constraints. Constraints in the phased planning of energy transmission networks include constraints on the construction and transmission of power networks, constraints on the construction and transmission of cold and hot water transmission networks within the energy network, constraints on the construction and transmission of gas transmission networks, and constraints on the power balance of the energy network. A set of phased construction schemes for the regional integrated energy system is determined, with each phased construction scheme corresponding to a number of construction phases and the commissioning year for each phase. Based on the phased construction sequence, a discount rate is introduced for the present value of construction costs. For each phased construction scheme, the optimization objective is to minimize the total life cycle cost. The constraints are the phased planning constraints of energy sites and the phased planning constraints of the energy transmission network. A regional integrated energy system station-network collaborative planning model is constructed to obtain the optimal system planning configuration scheme under each phased construction scheme. The optimal system planning configuration scheme under each phased construction plan is obtained based on the regional integrated energy system station-network coordinated planning model. The specific process includes: The regional integrated energy system station-network collaborative planning model is decomposed into an outer-layer configuration optimization problem and an inner-layer operation optimization problem. The outer-layer configuration optimization problem aims to minimize the total life-cycle cost, with decision variables being the equipment capacity configuration of each energy station in each period and the construction capacity of each pipeline segment in the network. The inner-layer operation optimization problem includes... Each corresponds to the first to the second stage under a given system planning and configuration scheme. The annual operation optimization problem is to minimize the operation and maintenance cost of the corresponding year. The system planning and configuration scheme for the regional integrated energy system is selected by traversing the set of phased construction schemes and choosing the scheme with the lowest total life cycle cost.

2. The method for phased expansion planning of regional integrated energy system station-network coordination as described in claim 1, characterized in that, The process of forming an optimal alternative path matrix for the energy grid includes: Determine the optimal source-load weighted path from the energy station to the load point, and after traversing all combinations of energy stations and load points, form a set of optimal source-load weighted paths; By deleting all edges in the undirected graph of the energy network that do not pass through the optimal weighted path of the source and load, we obtain the undirected graph of the new energy network. The adjacency matrix of the undirected graph of the new energy network is the optimal alternative path matrix of the energy network.

3. The method for phased expansion planning of regional integrated energy system station-network coordination as described in claim 1, characterized in that, The equipment operation constraints include the operation constraints of gas-fired cogeneration units, gas-fired boilers, absorption chillers, electric boilers, electric chillers, heat pumps, photovoltaic, wind power and solar water heating collectors, and multi-energy storage equipment. The station network and energy balance constraints include cooling, heating, electrical and power balance constraints and process flow network constraints.

4. The method for phased expansion planning of regional integrated energy system station-network coordination as described in claim 1, characterized in that, The total life cycle cost includes the construction and operation and maintenance costs of energy stations and energy transmission networks.

5. The method for phased expansion planning of regional integrated energy system station-network coordination as described in claim 1, characterized in that, The system planning and configuration scheme includes the site selection of energy stations, equipment capacity configuration, and energy transmission network layout.

6. A regional integrated energy system station-network coordinated phased expansion planning system, used to implement the regional integrated energy system station-network coordinated phased expansion planning method as described in claim 1, characterized in that, include: The data acquisition and processing module is configured to acquire multi-energy load demand data of load points and construction resource data of energy stations, and determine the optimal weighted path of source and load based on the available energy network paths between load points and energy stations to form an energy network optimization alternative path matrix. The constraint construction module is configured to determine phased planning constraints for energy sites based on construction resource data of energy sites, and to determine phased planning constraints for the energy transmission network based on the energy network optimization alternative path matrix. The phased planning determination module is configured to determine the set of phased construction schemes for the regional integrated energy system. For each phased construction scheme, the optimization objective is to minimize the total life cycle cost. The constraints are the phased planning constraints of energy sites and the phased planning constraints of the energy transmission network. The module constructs a regional integrated energy system station-network collaborative planning model to obtain the optimal system planning configuration scheme under each phased construction scheme. The system planning determination module is configured to traverse the set of phased construction schemes and select the system planning configuration scheme with the lowest total life cycle cost as the system planning configuration scheme for the regional integrated energy system.

7. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-5.

Images