Layered coordinated planning method for cold region energy base

Abstract

The invention discloses a layered coordinated planning method for a cold region energy base, which belongs to the technical field of electric power system planning and design, and comprises the following steps: obtaining annual wind and light power generation data and electric heating load demand data of a location, carrying out per-unit processing on various data, and selecting a plurality of typical scene sets to construct an energy base operation optimization model; an electric heat gas energy transmission network model is constructed, and an energy network is constrained by meeting multi-energy network operation characteristics, coupling characteristics and energy requirements of all nodes and takes the minimum sum of the investment construction cost of an energy base and the operation cost of the energy base as a target; according to the method, benefit appeals of an energy network and an energy base are comprehensively considered, a double-layer model considering the energy network and the energy base is constructed, an upper layer considers an energy network related model, a lower layer considers an energy base related model, and a heuristic algorithm is adopted for solving. The method can reduce the operation cost, improves the resource utilization efficiency, and improves the economical efficiency of the energy base and the energy network at the same time.

Description

Technical Field

[0001] The invention relates to the technical field of power system planning and design, and in particular to a hierarchical coordination planning method for cold-region energy bases. Background Art

[0002] The problem of power and heat preservation in cold-region energy bases is prominent. Energy bases contain a lot of new energy that cannot be fully absorbed, and there are economic benefits that can be tapped. The operating characteristics of cold-region energy bases seriously affect the economic cost of energy networks. Specifically, energy networks are related equipment invested and constructed in cold-region energy bases. Based on the optimization of the operating characteristics of energy bases, while improving their own economic efficiency, the economic efficiency of energy networks must also be considered, so as to achieve a common improvement in the economic efficiency of both. Therefore, it is necessary to have a planning technology suitable for cold-region energy bases. Summary of the invention

[0003] Based on the above shortcomings, the present invention provides a hierarchical coordination planning method for cold-region energy bases to solve the problem of excess new energy in energy bases and effectively improve the overall efficiency of the energy system.

[0004] The technical solution adopted by the present invention is as follows: A hierarchical coordination planning method for cold region energy bases comprises the following steps:

[0005] Step 1: Obtain the annual wind and solar power generation data and electric and thermal load demand data of the required construction area, standardize the data, and select several typical scene sets;

[0006] Step 2: Construct an operation optimization model for the cold region energy base. The cold region energy base meets the demand for electricity and heat load supply by purchasing electricity, heat and natural gas from outside, and aims to minimize the total annual operation cost.

[0007] Step 3: Construct an energy network optimization model for electricity, heat and gas, with the goal of minimizing the sum of the investment and construction cost of the cold-region energy base and its own operating cost, while constraining the energy network operation characteristics, coupling characteristics and energy demand of each node;

[0008] Step 4: Construct a two-layer model that considers the energy network and the cold-region energy base. The upper layer considers the energy network related models, and the lower layer considers the cold-region energy base related models, and uses a heuristic algorithm to solve it.

[0009] Furthermore, in step 1, the wind and solar power generation data and the annual data of electric and thermal load demand in the required construction area are first obtained, and various data are linearized by the max-min method. The formula is as follows:

[0010]

[0011] Where: and They represent the annual maximum value, minimum value, actual value at time t on the dth day and the normalized value of the lth category of data respectively;

[0012] The full year scenarios are then reduced to a few typical sets of scenarios to replace them.

[0013] Furthermore, in step one, the k-means clustering algorithm is used for scene reduction. The daily wind, solar and thermal load data are regarded as an individual, the number of clusters is specified, and the clustering algorithm is applied to obtain the cluster center. The cluster center is the typical scene obtained, and the proportion of each category is the probability of occurrence of the typical scene.

[0014] Furthermore, in step 2, it is necessary to construct an operation optimization model for the cold region energy base. The cold region energy base consists of energy storage equipment, energy conversion equipment, wind and solar power generation equipment, and electric and thermal energy demand equipment. The operation optimization model for the cold region energy base aims to minimize the sum of annual operating costs, takes the supply of electric and thermal energy as the demand, and considers a variety of energy purchase constraints, as follows:

[0015] Among them, the objective function of the cold region energy base is as follows:

[0016]

[0017] Where: subscripts i, j, and t represent the i-th cold region energy base, the j-th typical scenario, and time t, respectively; C ENBi represents the annual operating cost of the cold region energy base; J represents the number of selected typical days; pi j represents the probability of occurrence on a typical day; c buy 、c sell 、c p 、c gas 、c heat They represent the unit electricity purchase cost, unit electricity sales cost, unit wind and solar power abandonment cost, unit gas purchase cost and unit heat purchase cost respectively; They represent the power purchased, power sold, wind power abandoned, solar power abandoned, gas purchased, and heat purchased of the cold region energy base respectively;

[0018] Among them, the constraints of the cold region energy base include power balance constraints, equipment conversion constraints, energy storage characteristics constraints, and energy purchase and sales power constraints;

[0019] Among them, the power balance constraints include active and reactive power balance constraints, thermal power balance constraints and gas power balance constraints, as shown in the following formula:

[0020]

[0021] Where: It indicates that the cold energy base injects reactive power; Respectively represent the output electrical power, output thermal power and gas consumption of the cogeneration unit; Respectively represent the discharge power and charging power of the electric energy storage; They represent the electric boiler input electrical power and output thermal power respectively; Respectively represent the gas consumption and output thermal power of the gas boiler; They represent the heat release power and the heat charging power of the thermal energy storage respectively; Respectively represent active load, reactive load and thermal load;

[0022] Among them, the equipment conversion constraints include the input and output relationship constraints of the cogeneration unit, electric boiler and thermal boiler, as shown in the following formula:

[0023] The combined heat and power unit model is as follows:

[0024]

[0025] Where: Respectively represent the electricity conversion efficiency and heat conversion efficiency of the cogeneration unit; H GAS Indicates the calorific value of gas; They represent the minimum and maximum gas consumption of the cogeneration unit respectively;

[0026] The constructed gas boiler model is shown as follows:

[0027]

[0028] Where: η GB Indicates gas boiler efficiency; They respectively represent the minimum thermal power and maximum thermal power allowed to be output by the gas boiler;

[0029] The constructed electric boiler model is shown as follows:

[0030]

[0031] Where: η EB Indicates the efficiency of electric boiler; They respectively represent the minimum and maximum thermal power allowed to be output by the electric boiler;

[0032] The constructed energy storage device model is shown as follows:

[0033]

[0034] Where: ES represents the energy storage category, including electric energy storage BES and thermal energy storage HES; P i ES , They represent the original power capacity of energy storage and the power capacity of energy network investment for energy base expansion respectively; Energy storage charging efficiency and energy discharging efficiency; Δt represents the time sampling interval; Energy storage means storing energy; Respectively represent the minimum storage energy and maximum storage energy allowed by the original energy storage, and the minimum storage energy and maximum storage energy allowed by the extended energy storage; Respectively represent the energy stored at the end and start of scheduling;

[0035] The constructed purchase and sale energy power constraints are as follows:

[0036]

[0037] Where: and They respectively represent the maximum allowable electricity purchase power, the maximum allowable electricity sales power, the maximum exchange reactive power, the maximum heat purchase power and the maximum gas purchase volume.

[0038] Furthermore, in step 3, the energy network aims to minimize the total cost, and the objective function is as follows:

[0039]

[0040] Where: I, M, K, and F represent the number of cold-region energy bases, the number of nodes connected between the power grid and the upper power grid, the number of generators in the power grid, and the number of gas sources in the gas grid, respectively; C inv , C ope , C total They represent the investment cost of the energy network as a cold region energy base, the operating cost of the energy network and the total cost respectively; r and TL represent the unit electricity capacity cost, unit power capacity cost of electric energy storage equipment, unit heat capacity cost, unit power capacity cost of thermal energy storage, annual discount rate and planning period, respectively; They represent the electrical energy storage capacity, power capacity, thermal energy storage capacity and power capacity respectively; They respectively represent the power purchased and sold by the power grid to the upper-level power grid; They represent the unit electricity purchase cost and unit electricity sales cost from the superior power grid respectively; a k , b k 、c k They represent the power generated by the generator, the secondary cost item of the power generated by the generator, the primary cost item and the constant cost item respectively; Indicates the gas source output;

[0041] Energy network constraints include various energy network operation constraints and coupling constraints with various cold-region energy bases. First, the following coupling matrix is ​​defined: The power network contains the node parent power grid coupling matrix E UP , node generator coupling matrix E DG , node cold region energy base coupling matrix E ENB , node-branch coupling matrix E L ; The thermal network includes the node cold energy base coupling matrix T ENB ; The gas network includes the node gas source coupling matrix A S , node cold region energy base coupling matrix A ENB , node branch coupling matrix A L , the calculation method of each element of the node matrix is ​​as follows: except for the node-branch coupling matrix, the definition methods of other coupling matrices are the same. Taking the node-generator coupling matrix as an example, when a generator is on a node, the element value is 1, otherwise it is 0. For the node-branch coupling matrix, when the head end of the branch is a node, the element value is 1, when the tail end is a node, the element value is -1, otherwise it is 0;

[0042] The power network constraints include node active power balance constraints, node reactive power balance constraints, branch power flow constraints, node voltage phase angle constraints, generator power constraints, and power purchase and sales constraints. The formula is as follows:

[0043]

[0044] Where: They respectively represent the column vector of power purchased from the upper power grid, the column vector of power sold to the upper power grid, the column vector of active power of generators, the column vector of active load of nodes, the column vector of power purchased from the cold energy base, the column vector of power sold to the grid, the column vector of active power of lines, the column vector of reactive power injected from the upper power grid, the column vector of reactive power of generators, the column vector of reactive load of nodes, the column vector of reactive power injected from the power grid to the cold energy base, and the column vector of reactive power of lines; r mn 、x mn , δ n,j,t , δ m,max 、V n,j,t 、V m,min 、V m,max 、V 1,j,t , δ 1,j,t , u k,j,t , They respectively represent the per unit value of line resistance, the per unit value of line conductance, the size of node phase angle, the maximum value of node phase angle, node voltage, the minimum value of node voltage, the maximum value of node voltage, the reference node voltage value, the reference node phase angle value, the line active power, the line reactive power, the maximum value of line active power, the maximum value of line reactive power, the status of the generator set, the minimum value of generator active power, the maximum value of generator active power, the minimum value of generator reactive power, the maximum value of generator reactive power, the rated apparent power of the generator, the maximum down-ramp power of the generator, the maximum up-ramp power of the generator, the maximum active power purchased from the superior, the maximum active power sold to the superior and the maximum reactive power injected into the superior power grid;

[0045] The thermal network constraints include heat transfer constraints, node mass flow constraints, node thermal power balance constraints, and upper and lower limit constraints on the temperature of each node in the water supply and return network. The formula is as follows:

[0046]

[0047] Where: HS stands for heating station; HES stands for heat exchange station; Ω q+ represents the set of pipes that flow out of node q; Ω q- represents the set of pipes flowing into node q; T am,t , They respectively represent the inlet temperature of the water supply pipe, the minimum inlet temperature of the water supply pipe, the maximum inlet temperature of the water supply pipe, the inlet temperature of the return pipe, the minimum inlet temperature of the return pipe, the maximum inlet temperature of the return pipe, the outlet temperature of the water supply pipe, the outlet temperature of the return pipe, the ambient temperature, the outlet water temperature of the supply pipe node q, the outlet water temperature of the return pipe node q, the temperature of the water flowing into the HS, and the temperature of the water flowing into the HES; τ represents the time delay from the pipe inlet to the outlet; u p , L p 、c W Respectively represent the pipeline heat transfer coefficient, pipeline length and specific heat capacity of water; ms p,j,t ,ms p,min ,ms p,max 、mr p,j,t 、mr p,min 、mr p,max , They respectively represent the mass flow rate of the water supply pipe, the minimum value of the mass flow rate of the water supply pipe, the maximum value of the mass flow rate of the water supply pipe, the mass flow rate of the return pipe, the minimum value of the mass flow rate of the return pipe, the maximum value of the mass flow rate of the return pipe, the mass flow rate out of the HS, the minimum value of the mass flow rate out of the HS, the maximum value of the mass flow rate out of the HS, the mass flow rate into the HES, the minimum value of the mass flow into the HES, and the maximum value of the mass flow into the HES; Indicates the heat source output thermal power, Indicates heat load;

[0048] The natural gas network model includes natural gas node flow balance constraints, natural gas pipeline flow size constraints, gas source output power constraints, natural gas node pressure constraints, and pipeline and two-end node pressure correlation constraints. The formula is as follows:

[0049]

[0050] Where: G j,t , They represent the column vector of gas source, the column vector of pipeline flow, the column vector of gas injection flow of cold energy base and the column vector of gas load respectively; They represent pipeline flow rate and maximum pipeline flow rate respectively; C fg Represents the pipeline flow constant; sgn() represents the sign function, which takes the value of 1 when it is greater than 0, otherwise it takes the value of 0; π f,j,t , π f,min , π f,max They represent the node pressure, the minimum node pressure, and the maximum node pressure respectively; They respectively represent the node gas source output flow and the maximum output flow.

[0051] Furthermore, in step four, a hierarchical collaborative planning model of energy network and cold-region energy base is constructed. The energy network layer aims to minimize the sum of the investment and construction cost of the cold-region energy base and its own operating cost. The cold-region energy base layer, based on the investment and construction of equipment in the energy network, takes the demand for electricity and heat supply as a constraint and minimizes the total economic cost as the goal. By separately constructing the energy network optimization model and the cold-region energy base operation model, it is possible to take into account the interests of the energy network and the cold-region energy base, and achieve economical and reliable operation of the energy network and the cold-region energy base.

[0052] Furthermore, in step four, the constructed model belongs to a two-layer model. Interactive variables are required between the two layers of the model. The variable passed from the upper layer to the lower layer is the equipment construction capacity, and the variable passed from the lower layer to the upper layer is the power of interaction between the cold-region energy base and the energy network in each period, including electric power, thermal power and gas power. The solution method adopts a heuristic algorithm to solve it, and the heuristic algorithm updates the variables as the capacity of each device.

[0053] Furthermore, in step 4, the heuristic algorithm adopts a particle swarm algorithm, sets variables related to equipment capacity as particles, and continuously iterates through algorithm update rules to obtain a better solution.

[0054] Another object of the present invention is to provide a hierarchical coordination planning system for cold-region energy bases, comprising: a memory, a processor, and a computer program stored on the memory and capable of running on the processor, wherein when the computer program is executed by the processor, a hierarchical coordination planning method for cold-region energy bases as described above is implemented.

[0055] Another object of the present invention is to provide a computer-readable storage medium, on which is stored an implementation program for information transmission, and when the program is executed by a processor, the steps of a hierarchical coordination planning method for cold-region energy bases as described above are implemented.

[0056] Advantages and beneficial effects of the present invention: The present invention optimizes the economic efficiency of cold-region energy bases and energy networks through hierarchical coordination planning technology, and has many significant advantages: First, it can achieve dual optimization of cold-region energy bases and energy networks, solve the coordination problem between the two, and improve overall economic benefits. Secondly, by optimizing the operation of cold-region energy bases, it can improve energy utilization efficiency and reduce operating costs, while also improving the efficiency of energy networks and reducing resource waste. The proposed two-layer optimization model has a clear structure and can be solved efficiently; the present invention effectively solves the problem of excess new energy resources and improves its consumption efficiency, which can effectively improve the overall efficiency of the energy system and provide a theoretical basis for the optimization of energy systems in cold-region environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of the hierarchical coordination planning method for cold region energy bases of the present invention;

[0058] Figure 2 This is a block diagram of the double-layer optimization model involved in the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0060] Example 1

[0061] like Figure 1 As shown, this embodiment provides a hierarchical coordination planning method for cold region energy bases, comprising the following steps:

[0062] Step 1: Obtain the annual wind and solar power generation data and electric and thermal load demand data of the required construction area, standardize the data, and select several typical scene sets;

[0063] In this step, we first obtain the wind and solar power generation data and the annual data of electric and thermal load demand in the required construction area. All kinds of data are linearized by the max-min method. The formula is as follows:

[0064]

[0065] Where: and They represent the annual maximum value, minimum value, actual value at time t on the dth day and the normalized value of the lth category of data respectively;

[0066] After that, considering the difficulty of solving large-scale scenarios, the annual scenarios are reduced to several typical scenarios as replacements. There are many different methods for scenario reduction, such as human selection and cluster analysis. You can choose the appropriate method. For example, the k-means clustering algorithm can be used to treat the daily wind, photovoltaic and thermal load data as an individual, specify the number of clusters, and apply the clustering algorithm to obtain the cluster center. The cluster center is the typical scenario obtained, and the proportion of each category is the probability of occurrence of the typical scenario.

[0067] Step 2: Construct an operation optimization model for the cold region energy base. The cold region energy base meets the demand for electricity and heat load supply by purchasing electricity, heat and natural gas from outside, and aims to minimize the total annual operation cost.

[0068] It is necessary to build an operation optimization model for cold-region energy bases. The cold-region energy bases are composed of energy storage equipment, energy conversion equipment, wind and solar power generation equipment, and electric and thermal energy demand equipment. The operation optimization model of the cold-region energy base aims to minimize the sum of annual operating costs, takes the supply of electric and thermal energy as the demand, and considers a variety of energy purchase constraints, as follows:

[0069] Among them, the objective function of the cold region energy base is as follows:

[0070]

[0071] Where: subscripts i, j, and t represent the i-th cold region energy base, the j-th typical scenario, and time t, respectively; C ENBi represents the annual operating cost of the cold region energy base; J represents the number of selected typical days; pi j represents the probability of occurrence on a typical day; c buy 、c sell 、c p 、c gas 、c heat They represent the unit electricity purchase cost, unit electricity sales cost, unit wind and solar power abandonment cost, unit gas purchase cost and unit heat purchase cost respectively; They represent the power purchased, power sold, wind power abandoned, solar power abandoned, gas purchased, and heat purchased of the cold region energy base respectively;

[0072] Among them, the constraints of the cold region energy base include power balance constraints, equipment conversion constraints, energy storage characteristics constraints, and energy purchase and sales power constraints;

[0073] Among them, the power balance constraints include active and reactive power balance constraints, thermal power balance constraints and gas power balance constraints, as shown in the following formula:

[0074]

[0075] Where: It indicates that the cold energy base injects reactive power; Respectively represent the output electrical power, output thermal power and gas consumption of the cogeneration unit; Respectively represent the discharge power and charging power of the electric energy storage; They represent the electric boiler input electrical power and output thermal power respectively; Respectively represent the gas consumption and output thermal power of the gas boiler; They represent the heat release power and the heat charging power of the thermal energy storage respectively; Respectively represent active load, reactive load and thermal load;

[0076] Among them, the equipment conversion constraints include the input and output relationship constraints of the cogeneration unit, electric boiler and thermal boiler, as shown in the following formula:

[0077] The combined heat and power unit model is as follows:

[0078]

[0079] Where: Respectively represent the electricity conversion efficiency and heat conversion efficiency of the cogeneration unit; H GAS Indicates the calorific value of gas; They represent the minimum and maximum gas consumption of the cogeneration unit respectively;

[0080] The constructed gas boiler model is shown as follows:

[0081]

[0082] Where: η GB Indicates gas boiler efficiency; They respectively represent the minimum thermal power and maximum thermal power allowed to be output by the gas boiler;

[0083] The constructed electric boiler model is shown as follows:

[0084]

[0085] Where: η EB Indicates the efficiency of electric boiler; They respectively represent the minimum and maximum thermal power allowed to be output by the electric boiler;

[0086] The constructed energy storage device model is shown as follows:

[0087]

[0088] Where: ES represents the energy storage category, including electric energy storage BES and thermal energy storage HES; P i ES , They represent the original power capacity of energy storage and the power capacity of energy network investment for energy base expansion respectively; Energy storage charging efficiency and energy discharging efficiency; Δt represents the time sampling interval; Energy storage means storing energy; Respectively represent the minimum storage energy and maximum storage energy allowed by the original energy storage, and the minimum storage energy and maximum storage energy allowed by the extended energy storage; Respectively represent the energy stored at the end and start of scheduling;

[0089] The constructed purchase and sale energy power constraints are as follows:

[0090]

[0091] Where: and They respectively represent the maximum allowable electricity purchase power, the maximum allowable electricity sales power, the maximum exchange reactive power, the maximum heat purchase power and the maximum gas purchase volume.

[0092] Step 3: Construct an energy network optimization model for electricity, heat and gas, with the goal of minimizing the sum of the investment and construction cost of the cold-region energy base and its own operating cost, while constraining the energy network operation characteristics, coupling characteristics and energy demand of each node;

[0093] The energy network aims to minimize the total cost, and the objective function is as follows:

[0094]

[0095] Where: I, M, K, and F represent the number of cold-region energy bases, the number of nodes connected between the power grid and the upper power grid, the number of generators in the power grid, and the number of gas sources in the gas grid, respectively; C inv , C ope , C total They represent the investment cost of the energy network as a cold region energy base, the operating cost of the energy network and the total cost respectively; r and TL represent the unit electricity capacity cost, unit power capacity cost of electric energy storage equipment, unit heat capacity cost, unit power capacity cost of thermal energy storage, annual discount rate and planning period, respectively; They represent the electrical energy storage capacity, power capacity, thermal energy storage capacity and power capacity respectively; They respectively represent the power purchased and sold by the power grid to the upper-level power grid; They represent the unit electricity purchase cost and unit electricity sales cost from the superior power grid respectively; a k , b k 、c k They represent the power generated by the generator, the secondary cost item of the power generated by the generator, the primary cost item and the constant cost item respectively; Indicates the gas source output;

[0096] Energy network constraints include various energy network operation constraints and coupling constraints with various cold-region energy bases. First, the following coupling matrix is ​​defined: The power network contains the node parent power grid coupling matrix E UP , node generator coupling matrix E DG , node cold region energy base coupling matrix E ENB , node-branch coupling matrix E L ; The thermal network includes the node cold energy base coupling matrix T ENB ; The gas network includes the node gas source coupling matrix A S , node cold region energy base coupling matrix A ENB , node branch coupling matrix A L , the calculation method of each element of the node matrix is ​​as follows: except for the node-branch coupling matrix, the definition methods of other coupling matrices are the same. Taking the node-generator coupling matrix as an example, when a generator is on a node, the element value is 1, otherwise it is 0. For the node-branch coupling matrix, when the head end of the branch is a node, the element value is 1, when the tail end is a node, the element value is -1, otherwise it is 0;

[0097] The power network constraints include node active power balance constraints, node reactive power balance constraints, branch power flow constraints, node voltage phase angle constraints, generator power constraints, and power purchase and sales constraints. The formula is as follows:

[0098]

[0099] Where: They respectively represent the column vector of power purchased from the upper power grid, the column vector of power sold to the upper power grid, the column vector of active power of generators, the column vector of active load of nodes, the column vector of power purchased from the cold energy base, the column vector of power sold to the grid, the column vector of active power of lines, the column vector of reactive power injected from the upper power grid, the column vector of reactive power of generators, the column vector of reactive load of nodes, the column vector of reactive power injected from the power grid to the cold energy base, and the column vector of reactive power of lines; r mn 、x mn , δ n,j,t , δ m,max 、V n,j,t 、V m,min 、V m,max 、V 1,j,t , δ 1,j,t , u k,j,t , They respectively represent the per unit value of line resistance, the per unit value of line conductance, the size of node phase angle, the maximum value of node phase angle, node voltage, the minimum value of node voltage, the maximum value of node voltage, the reference node voltage value, the reference node phase angle value, the line active power, the line reactive power, the maximum value of line active power, the maximum value of line reactive power, the status of the generator set, the minimum value of generator active power, the maximum value of generator active power, the minimum value of generator reactive power, the maximum value of generator reactive power, the rated apparent power of the generator, the maximum down-ramp power of the generator, the maximum up-ramp power of the generator, the maximum active power purchased from the superior, the maximum active power sold to the superior and the maximum reactive power injected into the superior power grid;

[0100] The thermal network constraints include heat transfer constraints, node mass flow constraints, node thermal power balance constraints, and upper and lower limit constraints on the temperature of each node in the water supply and return network. The formula is as follows:

[0101]

[0102] Where: HS stands for heating station; HES stands for heat exchange station; Ω q+ represents the set of pipes that flow out of node q; Ω q- represents the set of pipes flowing into node q; T am,t , They respectively represent the inlet temperature of the water supply pipe, the minimum inlet temperature of the water supply pipe, the maximum inlet temperature of the water supply pipe, the inlet temperature of the return pipe, the minimum inlet temperature of the return pipe, the maximum inlet temperature of the return pipe, the outlet temperature of the water supply pipe, the outlet temperature of the return pipe, the ambient temperature, the outlet water temperature of the supply pipe node q, the outlet water temperature of the return pipe node q, the temperature of the water flowing into the HS, and the temperature of the water flowing into the HES; τ represents the time delay from the pipe inlet to the outlet; u p , L p 、c W Respectively represent the pipeline heat transfer coefficient, pipeline length and specific heat capacity of water; ms p,j,t ,ms p,min ,ms p,max 、mr p,j,t 、mr p,min 、mr p,max , They respectively represent the mass flow rate of the water supply pipe, the minimum value of the mass flow rate of the water supply pipe, the maximum value of the mass flow rate of the water supply pipe, the mass flow rate of the return pipe, the minimum value of the mass flow rate of the return pipe, the maximum value of the mass flow rate of the return pipe, the mass flow rate out of the HS, the minimum value of the mass flow rate out of the HS, the maximum value of the mass flow rate out of the HS, the mass flow rate into the HES, the minimum value of the mass flow into the HES, and the maximum value of the mass flow into the HES; Indicates the heat source output thermal power, Indicates heat load;

[0103] The natural gas network model includes natural gas node flow balance constraints, natural gas pipeline flow size constraints, gas source output power constraints, natural gas node pressure constraints, and pipeline and two-end node pressure correlation constraints. The formula is as follows:

[0104]

[0105] Where: G j,t , They represent the column vector of gas source, the column vector of pipeline flow, the column vector of gas injection flow of cold energy base and the column vector of gas load respectively; They represent pipeline flow rate and maximum pipeline flow rate respectively; C fg Represents the pipeline flow constant; sgn() represents the sign function, which takes the value of 1 when it is greater than 0, otherwise it takes the value of 0; π f,j,t , π f,min , π f,max They represent the node pressure, the minimum node pressure, and the maximum node pressure respectively; They respectively represent the node gas source output flow and the maximum output flow.

[0106] Step 4: Construct a hierarchical collaborative planning model for energy networks and cold-region energy bases. The energy network layer aims to minimize the sum of the investment and construction costs of the cold-region energy base and its own operating costs. The cold-region energy base, based on the investment and construction of equipment in the energy network, takes the demand for electricity and heat supply as a constraint and the goal of minimizing the total economic cost. By separately constructing an energy network optimization model and a cold-region energy base operation model, the interests of the energy network and the cold-region energy base can be taken into account, and the economic and reliable operation of the energy network and the cold-region energy base can be achieved. Figure 2 As shown, the constructed model belongs to a two-layer model. Interactive variables are required between the two layers. The variable passed from the upper layer to the lower layer is the equipment construction capacity, and the variable passed from the lower layer to the upper layer is the power of interaction between the cold-region energy base and the energy network in each period, including electric power, thermal power and gas power. The solution method adopts a heuristic algorithm for solution, and the heuristic algorithm updates the variable as the capacity of each device; the heuristic algorithm adopts a particle swarm algorithm, sets the equipment capacity-related variables as particles, and continuously iterates through the algorithm update rules to obtain a better solution.

[0107] This embodiment can achieve dual optimization of cold-region energy bases and energy networks, and provides theoretical guidance for the construction of cold-region energy bases.

Claims

1. A hierarchical coordination planning method for cold region energy bases, characterized in that: The following steps are involved: Step 1: Obtain the annual wind and solar power generation data and electric and thermal load demand data of the required construction area, standardize the data, and select several typical scene sets; Step 2: Construct an operation optimization model for the cold region energy base. The cold region energy base meets the demand for electricity and heat load supply by purchasing electricity, heat and natural gas from outside, and aims to minimize the total annual operation cost. Step 3: Construct an energy network optimization model for electricity, heat and gas, with the goal of minimizing the sum of the investment and construction cost of the cold-region energy base and its own operating cost, while constraining the energy network operation characteristics, coupling characteristics and energy demand of each node; Step 4: Construct a two-layer model that considers the energy network and the cold-region energy base. The upper layer considers the energy network related models, and the lower layer considers the cold-region energy base related models, and uses a heuristic algorithm to solve it.

2. A cold region energy base hierarchical coordination planning method according to claim 1, characterized in that: In step 1, first obtain the wind and solar power generation data and the annual data of electric and thermal load demand in the required construction area. All kinds of data are linearized by the max-min method. The formula is as follows: Where: and They represent the annual maximum value, minimum value, actual value at time t on the dth day and the normalized value of the lth category of data respectively; The full year scenarios are then reduced to a few typical sets of scenarios to replace them.

3. A method for hierarchical coordination planning of cold region energy bases according to claim 2, characterized in that: In step one, the k-means clustering algorithm is used to reduce the scenarios. The daily wind, solar and thermal load data are regarded as an individual. The number of clusters is specified, and the clustering algorithm is applied to obtain the cluster center. The cluster center is the typical scenario obtained, and the proportion of each category is the probability of occurrence of the typical scenario.

4. The method for hierarchical coordination planning of cold region energy bases according to claim 1 is characterized by: In step 2, it is necessary to build an operation optimization model for the cold-region energy base. The cold-region energy base consists of energy storage equipment, energy conversion equipment, wind and solar power generation equipment, and electric and thermal energy demand equipment. The operation optimization model of the cold-region energy base aims to minimize the sum of annual operating costs, takes the supply of electric and thermal energy as the demand, and considers a variety of energy purchase constraints, as follows: Among them, the objective function of the cold region energy base is as follows: Where: subscripts i, j, and t represent the i-th cold region energy base, the j-th typical scenario, and time t, respectively; C ENBi represents the annual operating cost of the cold region energy base; J represents the number of selected typical days; pi j represents the probability of occurrence on a typical day; c buy 、c sell 、c p 、c gas 、c heat They represent the unit electricity purchase cost, unit electricity sales cost, unit wind and solar power abandonment cost, unit gas purchase cost and unit heat purchase cost respectively; They represent the power purchased, power sold, wind power abandoned, solar power abandoned, gas purchased, and heat purchased of the cold region energy base respectively; Among them, the constraints of the cold region energy base include power balance constraints, equipment conversion constraints, energy storage characteristics constraints, and energy purchase and sales power constraints; Among them, the power balance constraints include active and reactive power balance constraints, thermal power balance constraints and gas power balance constraints, as shown in the following formula: Where: It indicates that the cold energy base injects reactive power; Respectively represent the output electrical power, output thermal power and gas consumption of the cogeneration unit; Respectively represent the discharge power and charging power of the electric energy storage; They represent the electric boiler input electrical power and output thermal power respectively; Respectively represent the gas consumption and output thermal power of the gas boiler; They represent the heat release power and the heat charging power of the thermal energy storage respectively; Respectively represent active load, reactive load and thermal load; Among them, the equipment conversion constraints include the input and output relationship constraints of the cogeneration unit, electric boiler and thermal boiler, as shown in the following formula: The combined heat and power unit model is as follows: Where: Respectively represent the electricity conversion efficiency and heat conversion efficiency of the cogeneration unit; H GAS Indicates the calorific value of gas; They represent the minimum and maximum gas consumption of the cogeneration unit respectively; The constructed gas boiler model is shown as follows: Where: η GB Indicates gas boiler efficiency; They respectively represent the minimum thermal power and maximum thermal power allowed to be output by the gas boiler; The constructed electric boiler model is shown as follows: Where: η EB Indicates the efficiency of electric boiler; They respectively represent the minimum and maximum thermal power allowed to be output by the electric boiler; The constructed energy storage device model is shown as follows: Where: ES represents the energy storage category, including electric energy storage BES and thermal energy storage HES; P i ES , They represent the original power capacity of energy storage and the power capacity of energy network investment for energy base expansion respectively; Energy storage charging efficiency and energy discharging efficiency; Δt represents the time sampling interval; Energy storage means storing energy; Respectively represent the minimum storage energy and maximum storage energy allowed by the original energy storage, and the minimum storage energy and maximum storage energy allowed by the extended energy storage; Respectively represent the energy stored at the end and start of scheduling; The constructed purchase and sale energy power constraints are as follows: Where: and They respectively represent the maximum allowable electricity purchase power, the maximum allowable electricity sales power, the maximum exchange reactive power, the maximum heat purchase power and the maximum gas purchase volume.

5. The hierarchical coordination planning method for cold region energy bases according to claim 1 is characterized by: In step 3, the energy network aims to minimize the total cost, and the objective function is as follows: Where: I, M, K, and F represent the number of cold-region energy bases, the number of nodes connected between the power grid and the upper power grid, the number of generators in the power grid, and the number of gas sources in the gas grid, respectively; C inv , C ope , C total They represent the investment cost of the energy network for the cold region energy base, the operating cost of the energy network and the total cost respectively; r and TL represent the unit electricity capacity cost, unit power capacity cost of electric energy storage equipment, unit heat capacity cost, unit power capacity cost of thermal energy storage, annual discount rate and planning period, respectively; They represent the electrical energy storage capacity, power capacity, thermal energy storage capacity and power capacity respectively; They respectively represent the power purchased and sold by the power grid to the upper-level power grid; They represent the unit cost of purchasing electricity from the upper-level power grid and the unit cost of selling electricity; a k , b k 、c k They represent the power generated by the generator, the secondary cost item of the power generated by the generator, the primary cost item and the constant cost item respectively; Indicates the gas source output; Energy network constraints include various energy network operation constraints and coupling constraints with various cold-region energy bases. First, the following coupling matrix is ​​defined: The power network contains the node parent power grid coupling matrix E UP , node generator coupling matrix E DG , node cold region energy base coupling matrix E ENB , node-branch coupling matrix E L ; The thermal network includes the node cold energy base coupling matrix T ENB ; The gas network includes the node gas source coupling matrix A S , node cold region energy base coupling matrix A ENB , node branch coupling matrix A L , the calculation method of each element of the node matrix is ​​as follows: except for the node-branch coupling matrix, the definition methods of other coupling matrices are the same. Taking the node-generator coupling matrix as an example, when a generator is on a node, the element value is 1, otherwise it is 0. For the node-branch coupling matrix, when the head end of the branch is a node, the element value is 1, when the tail end is a node, the element value is -1, otherwise it is 0; The power network constraints include node active power balance constraints, node reactive power balance constraints, branch power flow constraints, node voltage phase angle constraints, generator power constraints, and power purchase and sales constraints. The formula is as follows: Where: They respectively represent the column vector of power purchased from the upper power grid, the column vector of power sold to the upper power grid, the column vector of active power of generators, the column vector of active load of nodes, the column vector of power purchased from the cold energy base, the column vector of power sold to the grid, the column vector of active power of lines, the column vector of reactive power injected from the upper power grid, the column vector of reactive power of generators, the column vector of reactive load of nodes, the column vector of reactive power injected from the power grid to the cold energy base, and the column vector of reactive power of lines; r mn 、x mn ,δ n,j,t ,δ m,max 、V n,j,t 、V m,min 、V m,max 、V 1,j,t ,δ 1,j,t , u k,j,t , They respectively represent the per unit value of line resistance, the per unit value of line conductance, the size of node phase angle, the maximum value of node phase angle, node voltage, the minimum value of node voltage, the maximum value of node voltage, the reference node voltage value, the reference node phase angle value, the line active power, the line reactive power, the maximum value of line active power, the maximum value of line reactive power, the status of the generator set, the minimum value of generator active power, the maximum value of generator active power, the minimum value of generator reactive power, the maximum value of generator reactive power, the rated apparent power of the generator, the maximum down-ramp power of the generator, the maximum up-ramp power of the generator, the maximum active power purchased from the superior, the maximum active power sold to the superior and the maximum reactive power injected into the superior power grid; The thermal network constraints include heat transfer constraints, node mass flow constraints, node thermal power balance constraints, and upper and lower limit constraints on the temperature of each node in the water supply and return network. The formula is as follows: Where: HS represents the heating station; HES means heat exchange station; Ω q+ represents the set of pipes that flow out of node q; Ω q- represents the set of pipes flowing into node q; They respectively represent the inlet temperature of the water supply pipe, the minimum inlet temperature of the water supply pipe, the maximum inlet temperature of the water supply pipe, the inlet temperature of the return pipe, the minimum inlet temperature of the return pipe, the maximum inlet temperature of the return pipe, the outlet temperature of the water supply pipe, the outlet temperature of the return pipe, the ambient temperature, the outlet water temperature of the supply pipe node q, the outlet water temperature of the return pipe node q, the temperature of the water flowing into the HS, and the temperature of the water flowing into the HES; τ represents the time delay from the pipe inlet to the outlet; u p , L p 、c W Respectively represent the pipeline heat transfer coefficient, pipeline length and specific heat capacity of water; ms p,j,t ,ms p,min ,ms p,max 、mr p,j,t 、mr p,min 、mr p,max , They respectively represent the mass flow rate of the water supply pipe, the minimum value of the mass flow rate of the water supply pipe, the maximum value of the mass flow rate of the water supply pipe, the mass flow rate of the return pipe, the minimum value of the mass flow rate of the return pipe, the maximum value of the mass flow rate of the return pipe, the mass flow rate out of the HS, the minimum value of the mass flow rate out of the HS, the maximum value of the mass flow rate out of the HS, the mass flow rate into the HES, the minimum value of the mass flow into the HES, and the maximum value of the mass flow into the HES; Indicates the heat source output thermal power, Indicates heat load; The natural gas network model includes natural gas node flow balance constraints, natural gas pipeline flow size constraints, gas source output power constraints, natural gas node pressure constraints, and pipeline and two-end node pressure correlation constraints. The formula is as follows: Where: G j,t , They represent the column vector of gas source, the column vector of pipeline flow, the column vector of gas injection flow of cold energy base and the column vector of gas load respectively; They represent pipeline flow rate and maximum pipeline flow rate respectively; C fg Represents the pipeline flow constant; sgn() represents the sign function, which takes the value of 1 when it is greater than 0, otherwise it takes the value of 0; π f,j,t , π f,min , π f,max They represent the node pressure, the minimum node pressure, and the maximum node pressure respectively; They respectively represent the node gas source output flow and the maximum output flow.

6. The method for hierarchical coordination planning of cold region energy bases according to claim 1 is characterized by: In step four, a hierarchical collaborative planning model of energy network and cold-region energy base is constructed. The energy network layer aims to minimize the sum of the investment and construction cost of the cold-region energy base and its own operating cost. On the basis of the investment and construction of equipment in the energy network, the cold-region energy base takes the demand for electricity and heat supply as a constraint and the goal of minimizing the total economic cost. The energy network optimization model and the cold-region energy base operation model are constructed separately.

7. A method for hierarchical coordination planning of cold region energy bases according to claim 6, characterized in that: In step 4, the constructed model is a two-layer model. Interactive variables are required between the two layers. The variable passed from the upper layer to the lower layer is the equipment construction capacity, and the variable passed from the lower layer to the upper layer is the power of interaction between the cold-region energy base and the energy network in each period, including electric power, thermal power and gas power. The solution method uses a heuristic algorithm to solve the problem, and the heuristic algorithm updates the variable as the capacity of each device.

8. A method for hierarchical coordination planning of cold region energy bases according to claim 7, characterized in that: In step 4, the heuristic algorithm adopts a particle swarm algorithm, sets variables related to equipment capacity as particles, and continuously iterates through algorithm update rules to find a better solution.

9. A hierarchical coordination planning system for cold region energy bases, characterized in that: include: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, a hierarchical coordination planning method for cold-region energy bases is implemented as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an implementation program for information transmission, and when the program is executed by the processor, the steps of a hierarchical coordination planning method for cold-region energy bases as described in any one of claims 1-8 are implemented.

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