Rural comprehensive energy network planning method for rural energy transformation and terminal

Abstract

The invention discloses a rural comprehensive energy network planning method and terminal for rural energy transformation, and the method comprises the steps: building mathematical models of energy supply equipment, energy conversion equipment and energy storage equipment based on a typical structure of a rural comprehensive energy network; in addition, a regulation and control load model considering agricultural production is constructed, a rural comprehensive energy network planning multi-objective function including dimensions of system economic benefits, environmental benefits, energy efficiency and the like is established, and constraint conditions of an energy network planning optimization model are set, so that the rural comprehensive energy network planning optimization model is formed. And carrying out iteration on the capacity of each type of equipment, obtaining the optimal capacity when iteration convergence is carried out, and substituting the optimal capacity into the rural comprehensive energy network planning optimization model to generate a planning scheme. And compared with isolated planning of a power grid and a heat supply network, organic coordination and multi-energy complementation among different energy sources are realized, and the utilization efficiency of rural energy sources is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy grid planning, and in particular to a planning method and terminal for a rural integrated energy grid oriented to rural energy transformation. Background Art

[0002] In the context of sustained development of the rural economy, the consumption level of coal, fuel oil, electricity and natural gas in rural households has increased significantly, and the energy consumption structure in rural areas is gradually transforming to commodity energy consumption. Under this trend, the demand for electricity, heat, gas, cooling and other energy in rural areas continues to increase.

[0003] However, the scattered residence of rural residents has increased the cost of energy transmission. At the same time, rural areas are overly dependent on traditional disposable energy such as coal, fuel oil, straw, and lack efficient energy infrastructure, resulting in insufficient energy supply reliability and increased carbon emissions, causing serious waste of resources.

[0004] It is worth noting that renewable energy resources such as wind energy, solar energy and biomass energy are widely distributed in rural areas. However, the development and planning of various energy resources in rural areas are relatively independent, and there is no overall linkage and coordination of energy, so it is difficult to maximize the utilization efficiency of resources. Therefore, it is urgent to rationally plan and utilize various energy sources in rural areas.

[0005] However, most of the current research on energy network planning in rural areas focuses on small-scale local microgrids or microheat networks, and there is a lack of research on the planning of electric-thermal coupled networks or even integrated energy networks. In addition, current research lacks analysis of the degree of dependence of different energy supply structures on external energy, and the role division and construction path of the investment and construction entities of rural integrated energy networks are not clear enough.

[0006] In summary, the present invention provides a planning method and terminal for a rural integrated energy network for rural energy transformation. Summary of the invention

[0007] The purpose of the present invention is to provide a planning method and terminal for a rural integrated energy network for rural energy transformation, which can integrate and utilize various energy resources such as wind energy, solar energy, biomass energy, etc. in rural areas, and at the same time can effectively increase the consumption of new energy and improve energy utilization.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] The present invention proposes a planning method and terminal for a rural integrated energy network for rural energy transformation, comprising the following steps:

[0010] Summarize the supply and consumption characteristics of rural energy, propose a typical structure of rural integrated energy network for rural energy transformation, and analyze the planning optimization characteristics and key technologies of rural integrated energy network;

[0011] Based on the typical structure of the rural comprehensive energy network, mathematical models of the energy supply equipment, energy conversion equipment and energy storage equipment are constructed. In addition, a load regulation model considering agricultural production is constructed, a multi-objective function for the rural comprehensive energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established, and constraints of the energy network planning optimization model are set, thereby forming a rural comprehensive energy network planning optimization model, and iterating the capacity of each equipment. When the iteration converges, the optimal capacity is obtained, and the optimal capacity is substituted into the rural comprehensive energy network planning optimization model to generate a planning scheme.

[0012] Preferably, the mathematical model of energy supply equipment, energy conversion equipment and energy storage equipment established in the typical structure of the rural integrated energy network includes:

[0013] Wind turbine power generation model:

[0014]

[0015] Where P WT (t) represents the power generation of the wind turbine at time t, ν input (t) represents the cut-in wind speed at time t, ν rated (t) represents the rated wind speed at time t, ν output (t) represents the cut-out wind speed at time t, ν(t) represents the wind speed at time t, Indicates the rated power of the fan.

[0016] Distributed photovoltaic power generation model:

[0017]

[0018] Where P pv Represents the power generation of distributed photovoltaics, P SIC Indicates the maximum power generation of distributed photovoltaic under rated conditions, G lNG Represents the solar radiation intensity, G STC represents the solar radiation intensity under rated conditions, k represents the power temperature coefficient of the solar panel, T c Indicates the actual operating temperature of the solar panel, T r Indicates the panel temperature under standard test conditions.

[0019] Solar thermal power generation collection link model:

[0020]

[0021] Where η d-th represents the light-to-heat conversion efficiency, S SF represents the mirror field area, The direct normal radiation intensity value represented by represents the heat loss caused by adjusting the light field tracking strategy, η cur represents the heat loss coefficient, It indicates the thermal power transferred to the heat conducting medium by the heat collecting link.

[0022] CSP heat storage model:

[0023]

[0024] In the formula, represents the thermal storage power of the thermal storage subsystem at time t, represents the heat release power of the heat storage subsystem at time t, represents the thermal power transferred from the heat transfer medium to the heat storage subsystem, represents the thermal power transferred from the heat storage subsystem to the heat conducting medium, η cha represents the heat storage efficiency of the heat storage subsystem, η dis represents the heat release efficiency of the heat storage subsystem, represents the heat storage capacity of the heat storage subsystem at time t, represents the heat storage capacity of the heat storage subsystem at time t-1, η loss represents the heat loss rate of the heat storage subsystem.

[0025] Solar thermal power generation model:

[0026]

[0027] Where η th-e represents the thermoelectric conversion efficiency, It represents the thermal power transferred by the heat conducting medium to the power generation subsystem.

[0028] Biomass Biogas Combined Heat and Power Gas Turbine Model:

[0029]

[0030] Q wat (t) = CV(t)ΔT;

[0031] Where V GT (t) represents the amount of natural gas consumed by the gas turbine at time t, L NG represents the lower calorific value of natural gas, Δt represents the time step, P CHP,e (t) represents the electric power generated by the gas turbine at time t, η CHP,e represents the power generation efficiency of the gas turbine, Q wat(t) represents the heat generated by the hot water module, C represents the specific heat capacity of the flue gas, V(t) represents the volume of the flue gas entering the hot water module, and ΔT represents the temperature change of the flue gas in the hot water module.

[0032] Biomass biogas cogeneration waste heat boiler model:

[0033]

[0034] Where P CHP.yr (t) represents the power of waste heat generated by the gas turbine, η CHP.yr represents the waste heat utilization efficiency, η loss Indicates the operating loss ratio.

[0035] From the above description, it can be seen that the biomass biogas cogeneration system refers to a system that uses methane produced by biomass as the main fuel, reacts with oxygen, and releases a large amount of high-flow airflow, thereby driving the rapid operation of power equipment such as gas turbines to provide electricity to users. In addition, the high-temperature gas generated after the operation of the gas turbine is reused by equipment such as waste heat boilers to deliver heat to users. The use of a stepped energy utilization rate can reduce the operating costs of the system. At the same time, since the gas is burned under oxygen-rich conditions, the emission of exhaust gas can be reduced.

[0036] Energy storage battery model:

[0037]

[0038] In the formula, E SOC (t+1) and E SOC (t) represents the storage capacity of the energy storage battery at time t+1 and t, α represents the self-discharge rate of the energy storage battery, η EES,C and η EES,D Represents the charging and discharging efficiency of the energy storage battery, R EES,C and R EES,D represents the charging and discharging state variables of the energy storage battery, and Indicates the upper and lower limits of the charging and discharging status of the energy storage battery.

[0039] From the above description, we can see that in the integrated energy grid, the supply of natural resources such as solar energy and wind energy is highly random, which will lead to significant fluctuations in the output of photovoltaic, wind turbine and other power generation equipment, which may directly affect the stability of the energy grid operation. Energy storage batteries have the function of smoothing fluctuations and shaving peaks and filling valleys, and are a key device to ensure reliable energy use for users.

[0040] Thermal storage tank model:

[0041]

[0042] Where, T SOC (t+1) and T SOC (t) represents the heat storage capacity of the heat storage tank at time t+1 and t, β represents the heat dissipation loss of the heat storage tank, η TES,C and η TES,D Represents the heat absorption and heat release efficiency of the heat storage tank, R TES,C and R TES,D represents the heat absorption and release state variables of the heat storage tank, and Indicates the upper and lower limits of the heat absorption and heat release states of the energy storage battery.

[0043] From the above description, it can be seen that in the later operation of the energy grid, on the one hand, due to the different energy prices in different periods, it is possible to consider storing heat in the heat storage tank during low-price periods and releasing heat during high-price periods to reduce the purchase of external energy; on the other hand, considering the output volatility of equipment such as wind turbines and photovoltaics, the heat storage tank can be used together with the energy storage battery to store excess energy.

[0044] Light environment control load model:

[0045]

[0046] In the formula, I N Represents the total intensity of greenhouse solar radiation, I day It represents the intensity of supplementary lighting during the day, P represents the total power required for supplementary lighting in the greenhouse, and A represents the area of ​​the glass greenhouse.

[0047] Thermal environment control load model:

[0048] Q=C ht A cover (T in -T out )+ρ i N c V[c p (T in -T out )+h va (W in -W out )];

[0049] Where Q represents the heat demand power of the greenhouse, C ht represents the heat transfer coefficient of glass, A cover Indicates the greenhouse glass coverage area, T in represents the temperature in the greenhouse, T out represents the ambient temperature outside the greenhouse, ρ i Indicates the air density in the greenhouse, N c represents the ventilation frequency of the greenhouse, V represents the volume of the greenhouse, c prepresents the constant pressure specific heat capacity of the air in the greenhouse, h va represents the latent heat of vaporization of water, W in Indicates the humidity content of the air in the greenhouse, W out Indicates the humidity content of the air outside the greenhouse.

[0050] Preferably, a multi-objective function of a rural integrated energy network planning optimization model is established based on the energy equipment and control load model:

[0051] Economic objective function:

[0052] minf1=C INV +C OPT +C RE +C PUR ;

[0053] In the formula, C INV represents the annual value of energy network investment cost, C OPT represents the annual value of energy grid operation and maintenance cost, C RE Represents the equipment replacement cost value, C PUR Represents the cost of purchased energy.

[0054] From the above description, it can be seen that the minimum annual cost of the energy network is used as the objective function to reflect the economic benefits of the rural integrated energy network planning optimization model.

[0055] Environmental objective function:

[0056]

[0057] In the formula, represents the carbon emission coefficient of the electrical energy in the external system, Indicates the carbon emission coefficient of the system biogas, Indicates the system's biogas consumption.

[0058] From the above description, it can be seen that the minimum annual carbon emissions of the energy network is used as the objective function to reflect the environmental benefits of the rural integrated energy network planning optimization model.

[0059] Energy efficiency objective function:

[0060]

[0061] In the formula, E i represents the energy supply of device i, W i Represents the energy consumption of device i.

[0062] From the above description, it can be seen that the ratio of energy supply and consumption of energy supply equipment is used as the objective function to reflect the comprehensive energy efficiency of the rural integrated energy network planning optimization model.

[0063] The established rural integrated energy network planning optimization model also includes:

[0064] Determine the investment capacity constraints, planning area constraints, grid power supply constraints, equipment power supply operation constraints and energy balance constraints of the rural comprehensive energy network planning optimization model.

[0065] From the above description, it can be seen that setting investment capacity constraints can ensure the participation of governments, enterprises and rural residents in the construction of integrated energy networks; setting planning area constraints can ensure site resources for equipment installation; setting grid power supply constraints can alleviate grid power supply pressure and ensure stable grid operation; setting equipment function operation constraints can ensure equipment output efficiency and extend equipment service life; setting energy balance constraints can ensure the balance of supply and demand of electricity, gas, heat and other energies in the energy network at any time.

[0066] Furthermore, the rural integrated energy network planning optimization model is used to iterate the construction capacity of each device, and when the iteration converges, the optimal capacity includes:

[0067] Set the construction location of each equipment;

[0068] Predict the day-ahead output power of wind power, photovoltaic, solar thermal, biomass gas cogeneration, energy storage and other equipment, and obtain the upper and lower bounds of each equipment’s output;

[0069] Set initial parameters such as the number of iterations, and randomly select models of different devices to determine the initial population;

[0070] Under the condition of satisfying the constraints of each device, the fitness values ​​of different populations are obtained;

[0071] Update the iteration positions of different populations, and determine the optimal capacity of each device with the optimal fitness value while meeting the set number of iterations.

[0072] From the above description, it can be seen that by iterating the equipment capacity until convergence, the optimal capacity can be obtained, so as to obtain the corresponding rural integrated energy network planning scheme under the optimal capacity.

[0073] Another embodiment of the present invention provides a planning terminal for a rural integrated energy network for rural energy transformation, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the various steps of the above-mentioned rural integrated energy network planning method when executing the computer program.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] The present invention proposes a typical structure of a rural integrated energy network for rural energy transformation. Based on this structure, mathematical models of energy supply equipment, energy conversion equipment and energy storage equipment are constructed. In addition, a load regulation model considering agricultural production is constructed, a multi-objective function of rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established, and constraints of the energy network planning optimization model are set, thereby forming a rural integrated energy network planning optimization model, and iterating the capacity of each device, and obtaining the optimal capacity when the iteration converges, and substituting the optimal capacity into the rural integrated energy network planning optimization model to generate a planning scheme. Compared with isolated planning of power grids and heat networks, it is more conducive to achieving organic coordination and multi-energy complementarity between different energy sources, and improving rural energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Figure 1 is a flow chart of the method in the present invention;

[0077] Figure 2 It is a schematic diagram of the terminal structure in the present invention. DETAILED DESCRIPTION

[0078] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0079] The present invention provides a planning method for a rural integrated energy network for rural energy transformation, comprising the following steps:

[0080] Summarize the supply and consumption characteristics of rural energy, propose a typical structure of rural integrated energy network for rural energy transformation, and analyze the planning optimization characteristics and key technologies of rural integrated energy network;

[0081] Based on the typical structure of the rural comprehensive energy network, mathematical models of the energy supply equipment, energy conversion equipment and energy storage equipment are constructed. In addition, a load regulation model considering agricultural production is constructed, a multi-objective function for the rural comprehensive energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established, and constraints of the energy network planning optimization model are set, thereby forming a rural comprehensive energy network planning optimization model, and iterating the capacity of each equipment. When the iteration converges, the optimal capacity is obtained, and the optimal capacity is substituted into the rural comprehensive energy network planning optimization model to generate a planning scheme.

[0082] From the above description, it can be seen that the beneficial effects of the present invention are: a typical structure of a rural integrated energy network for rural energy transformation is proposed, and mathematical models of energy supply equipment, energy conversion equipment and energy storage equipment are constructed based on this structure. In addition, a load regulation model considering agricultural production is constructed, a multi-objective function for rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established, and constraints of the energy network planning optimization model are set, thereby forming a rural integrated energy network planning optimization model, and iterating the capacity of each device, and obtaining the optimal capacity when the iteration converges, and substituting the optimal capacity into the rural integrated energy network planning optimization model to generate a planning scheme. Compared with the isolated planning of power grids and heat networks, it is more conducive to achieving organic coordination and multi-energy complementarity between different energy sources, and improving rural energy utilization efficiency.

[0083] Furthermore, the mathematical models of energy supply equipment, energy conversion equipment and energy storage equipment are established according to the typical structure of the rural integrated energy network, including:

[0084] Wind turbine power generation model:

[0085]

[0086] Where P WT (t) represents the power generation of the wind turbine at time t, ν input (t) represents the cut-in wind speed at time t, ν rated (t) represents the rated wind speed at time t, ν output (t) represents the cut-out wind speed at time t, ν(t) represents the wind speed at time t, Indicates the rated power of the fan.

[0087] Distributed photovoltaic power generation model:

[0088]

[0089] Where P pv Represents the power generation of distributed photovoltaics, P SIC Indicates the maximum power generation of distributed photovoltaic under rated conditions, G lNG Represents the solar radiation intensity, G STC represents the solar radiation intensity under rated conditions, k represents the power temperature coefficient of the solar panel, T c Indicates the actual operating temperature of the solar panel, T r Indicates the panel temperature under standard test conditions.

[0090] Solar thermal power generation collection link model:

[0091]

[0092] Where η d-th represents the light-to-heat conversion efficiency, S SF represents the mirror field area, The direct normal radiation intensity value represented by represents the heat loss caused by adjusting the light field tracking strategy, η cur represents the heat loss coefficient, It indicates the thermal power transferred to the heat conducting medium by the heat collecting link.

[0093] CSP heat storage model:

[0094]

[0095] In the formula, represents the thermal storage power of the thermal storage subsystem at time t, represents the heat release power of the heat storage subsystem at time t, represents the thermal power transferred from the heat transfer medium to the heat storage subsystem, represents the thermal power transferred from the heat storage subsystem to the heat conducting medium, η cha represents the heat storage efficiency of the heat storage subsystem, η dis represents the heat release efficiency of the heat storage subsystem, represents the heat storage capacity of the heat storage subsystem at time t, represents the heat storage capacity of the heat storage subsystem at time t-1, η loss represents the heat loss rate of the heat storage subsystem.

[0096] Solar thermal power generation model:

[0097]

[0098] Where η th-e represents the thermoelectric conversion efficiency, Q t H-P It represents the thermal power transferred by the heat conducting medium to the power generation subsystem.

[0099] Biomass Biogas Combined Heat and Power Gas Turbine Model:

[0100]

[0101] Q wat (t) = CV(t)ΔT;

[0102] Where V GT (t) represents the amount of natural gas consumed by the gas turbine at time t, L NG represents the lower calorific value of natural gas, Δt represents the time step, P CHP,e (t) represents the electric power generated by the gas turbine at time t, η CHP,e represents the power generation efficiency of the gas turbine, Q wat(t) represents the heat generated by the hot water module, C represents the specific heat capacity of the flue gas, V(t) represents the volume of the flue gas entering the hot water module, and ΔT represents the temperature change of the flue gas in the hot water module.

[0103] Biomass biogas cogeneration waste heat boiler model:

[0104]

[0105] Where P CHP.yr (t) represents the power of waste heat generated by the gas turbine, η CHP.yr represents the waste heat utilization efficiency, η loss Indicates the operating loss ratio.

[0106] From the above description, it can be seen that the biomass biogas cogeneration system refers to a system that uses methane produced by biomass as the main fuel, reacts with oxygen, and releases a large amount of high-flow airflow, thereby driving the rapid operation of power equipment such as gas turbines to provide electricity to users. In addition, the high-temperature gas generated after the operation of the gas turbine is reused by equipment such as waste heat boilers to deliver heat to users. The use of a stepped energy utilization rate can reduce the operating costs of the system. At the same time, since the gas is burned under oxygen-rich conditions, the emission of exhaust gas can be reduced.

[0107] Energy storage battery model:

[0108]

[0109] In the formula, E SOC (t+1) and E SOC (t) represents the storage capacity of the energy storage battery at time t+1 and t, α represents the self-discharge rate of the energy storage battery, η EES,C and η EES,D Represents the charging and discharging efficiency of the energy storage battery, R EES,C and R EES,D represents the charging and discharging state variables of the energy storage battery, and Indicates the upper and lower limits of the charging and discharging status of the energy storage battery.

[0110] From the above description, we can see that in the integrated energy grid, the supply of natural resources such as solar energy and wind energy is highly random, which will lead to significant fluctuations in the output of photovoltaic, wind turbine and other power generation equipment, which may directly affect the stability of the energy grid operation. Energy storage batteries have the function of smoothing fluctuations and shaving peaks and filling valleys, and are a key device to ensure reliable energy use for users.

[0111] Thermal storage tank model:

[0112]

[0113] Where, T SOC (t+1) and T SOC (t) represents the heat storage capacity of the heat storage tank at time t+1 and t, β represents the heat dissipation loss of the heat storage tank, η TES,C and η TES,D Represents the heat absorption and heat release efficiency of the heat storage tank, R TES,C and R TES,D represents the heat absorption and release state variables of the heat storage tank, and Indicates the upper and lower limits of the heat absorption and heat release states of the energy storage battery.

[0114] From the above description, it can be seen that in the later operation of the energy grid, on the one hand, due to the different energy prices in different periods, it is possible to consider storing heat in the heat storage tank during low-price periods and releasing heat during high-price periods to reduce the purchase of external energy; on the other hand, considering the output volatility of equipment such as wind turbines and photovoltaics, the heat storage tank can be used together with the energy storage battery to store excess energy.

[0115] Light environment control load model:

[0116]

[0117] In the formula, I N Represents the total intensity of greenhouse solar radiation, I day It represents the intensity of supplementary lighting during the day, P represents the total power required for supplementary lighting in the greenhouse, and A represents the area of ​​the glass greenhouse.

[0118] Thermal environment control load model:

[0119] Q=C ht A cover (T in -T out )+ρ i N c V[c p (T in -T out )+h va (W in -W out )];

[0120] Where Q represents the heat demand power of the greenhouse, C ht represents the heat transfer coefficient of glass, A cover Indicates the greenhouse glass coverage area, T in represents the temperature in the greenhouse, T out represents the ambient temperature outside the greenhouse, ρ i Indicates the air density in the greenhouse, N c represents the ventilation frequency of the greenhouse, V represents the volume of the greenhouse, c prepresents the constant pressure specific heat capacity of the air in the greenhouse, h va represents the latent heat of vaporization of water, W in Indicates the humidity content of the air in the greenhouse, W out Indicates the humidity content of the air outside the greenhouse.

[0121] Furthermore, a multi-objective function of a rural integrated energy network planning optimization model is established based on the energy equipment and control load model:

[0122] Economic objective function:

[0123] minf1=C INV +C OPT +C RE +C PUR ;

[0124] In the formula, C INV represents the annual value of energy network investment cost, C OPT represents the annual value of energy grid operation and maintenance cost, C RE Represents the equipment replacement cost value, C PUR Represents the cost of purchased energy.

[0125] From the above description, it can be seen that the minimum annual cost of the energy network is used as the objective function to reflect the economic benefits of the rural integrated energy network planning optimization model.

[0126] Environmental objective function:

[0127]

[0128] In the formula, represents the carbon emission coefficient of the electrical energy in the external system, Indicates the carbon emission coefficient of the system biogas, P t bio Indicates the system's biogas consumption.

[0129] From the above description, it can be seen that the minimum annual carbon emissions of the energy network is used as the objective function to reflect the environmental benefits of the rural integrated energy network planning optimization model.

[0130] Energy efficiency objective function:

[0131]

[0132] In the formula, E i represents the energy supply of device i, W i Represents the energy consumption of device i.

[0133] From the above description, it can be seen that the ratio of energy supply and consumption of energy supply equipment is used as the objective function to reflect the comprehensive energy efficiency of the rural integrated energy network planning optimization model.

[0134] Furthermore, the established rural integrated energy network planning optimization model also includes:

[0135] Determine the investment capacity constraints, planning area constraints, grid power supply constraints, equipment power supply operation constraints and energy balance constraints of the rural comprehensive energy network planning optimization model.

[0136] From the above description, it can be seen that setting investment capacity constraints can ensure the participation of governments, enterprises and rural residents in the construction of integrated energy networks; setting planning area constraints can ensure site resources for equipment installation; setting grid power supply constraints can alleviate grid power supply pressure and ensure stable grid operation; setting equipment function operation constraints can ensure equipment output efficiency and extend equipment service life; setting energy balance constraints can ensure the balance of supply and demand of electricity, gas, heat and other energies in the energy network at any time.

[0137] Furthermore, the rural integrated energy network planning optimization model is used to iterate the construction capacity of each device, and when the iteration converges, the optimal capacity includes:

[0138] Set the construction location of each equipment;

[0139] Predict the day-ahead output power of wind power, photovoltaic, solar thermal, biomass gas cogeneration, energy storage and other equipment, and obtain the upper and lower bounds of each equipment’s output;

[0140] Set initial parameters such as the number of iterations, and randomly select models of different devices to determine the initial population;

[0141] Under the condition of satisfying the constraints of each device, the fitness values ​​of different populations are obtained;

[0142] Update the iteration positions of different populations, and determine the optimal capacity of each device with the optimal fitness value while meeting the set number of iterations.

[0143] From the above description, it can be seen that by iterating the equipment capacity until convergence, the optimal capacity can be obtained, so as to obtain the corresponding rural integrated energy network planning scheme under the optimal capacity.

[0144] Please refer to Figure 2 Another embodiment of the present invention provides a planning terminal for a rural integrated energy network for rural energy transformation, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the above-mentioned rural integrated energy network planning method is implemented.

[0145] The above-mentioned rural integrated energy network planning method and terminal for rural energy transformation of the present invention are suitable for planning of rural integrated energy networks considering multiple energy resources such as wind energy, solar energy, biomass energy, etc., and can improve the efficiency of rural energy utilization. The following is an explanation through specific implementation methods:

[0146] Embodiment 1

[0147] Please refer to Figure 1 , a planning method for a rural integrated energy network for rural energy transformation, comprising the steps of:

[0148] S1. Summarize the supply and consumption characteristics of rural energy, propose a typical structure of rural integrated energy network for rural energy transformation, and analyze the optimization characteristics and key technologies of integrated energy network planning. Based on the typical structure of rural integrated energy network, establish a multi-objective function of rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions.

[0149] S11. Based on the typical structure of the rural integrated energy network, a multi-objective function for rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established:

[0150] Economic objective function:

[0151] minf1=C INV +C OPT +C RE +C PUR ;

[0152] In the formula, C INV represents the annual value of energy network investment cost, C OPT represents the annual value of energy grid operation and maintenance cost, C RE Represents the equipment replacement cost value, C INV Represents the cost of energy purchase. The minimum annual cost of energy network is used as the objective function to reflect the economic benefits of the rural comprehensive energy network planning optimization model.

[0153] in,

[0154]

[0155] In the formula, I represents the set of equipment component types, i represents the equipment type, represents the unit capacity investment cost of equipment i, M i represents the total configuration capacity of device i, y i represents the equipment life, r represents the discount rate, represents the annual operation and maintenance cost per unit capacity of equipment i, T represents the system operation period, represents the price of purchasing electricity from the large power grid, Pi ele Indicates the amount of electricity purchased.

[0156] Environmental objective function:

[0157]

[0158] In the formula, represents the carbon emission coefficient of the electrical energy in the external system, Indicates the carbon emission coefficient of the system biogas, P t bio Represents the consumption of biogas in the system. The minimum annual carbon emission of the energy network is used as the objective function to reflect the environmental benefits of the rural comprehensive energy network planning optimization model.

[0159] Energy efficiency objective function:

[0160]

[0161] In the formula, E i represents the energy supply of device i, W i Represents the energy consumption of equipment i. The ratio of energy supply and consumption of energy supply equipment is used as the objective function to reflect the comprehensive energy efficiency of the rural integrated energy network planning optimization model.

[0162] S12. Determine the investment capacity constraints, planning area constraints, grid power supply constraints, equipment power supply operation constraints and energy balance constraints of the rural comprehensive energy network planning optimization model.

[0163] S121. Determine investment capacity constraints to ensure that governments, enterprises and rural residents can participate in the construction of an integrated energy network:

[0164] T max ≥f in (n);

[0165] Where, T max represents the maximum investment capacity of rural integrated energy network, f in (n) represents the sum of the initial investment costs of n equipment.

[0166] S122. Determine the planning area constraints to ensure site resources for equipment installation:

[0167]

[0168] In the formula, m i represents the land area occupied by the installation of the i-th equipment, AZ max Represents the available land area that can be used to build an integrated energy system.

[0169] S123. Determine the power supply constraints of the power grid to ensure stable operation of the power grid:

[0170]

[0171] Where D max Indicates the maximum power supply capacity of the power grid. represents the power consumption of the i-th device, represents the power generation of the i-th device, It represents the electricity load designed within the rural integrated energy network, and S represents the safety electricity coefficient.

[0172] S124. Determine the equipment function operation constraints to ensure equipment output efficiency:

[0173]

[0174] In the formula, represents the minimum power supplied by the i-th device, represents the maximum power supplied by the i-th device, represents the ramp rate of the i-th device reducing its output, It represents the ramp rate of the output increase of the i-th device.

[0175] S125. Determine energy balance constraints to ensure the balance of supply and demand of electricity, gas, heat and other energies in the energy grid at any time:

[0176] P i′ (t)+P buy (t) = P Load (t)+P loss (t);

[0177] Where P i′ (t) represents the energy supply of the energy supply equipment during period t, P buy (t) represents the amount of energy purchased from the external system during period t, P Load (t) represents the energy grid load during period t, P loss (t) represents the active power loss of the energy network during period t.

[0178] S2. Use the rural integrated energy network planning optimization model to iterate the capacity of each device, and when the iteration converges, obtain the optimal capacity, and substitute the optimal capacity into the rural integrated energy network planning optimization model to generate a planning solution.

[0179] S21. Setting the initial construction location of each equipment;

[0180] S22. Predict the day-ahead output power of wind power, photovoltaic power, solar thermal power, biomass biogas cogeneration, energy storage and other equipment, and obtain the upper and lower bounds of the output of each device;

[0181] S23, setting initial parameters such as the number of iterations and step size, and randomly selecting models of different devices to determine the initial population;

[0182] S24, obtaining fitness values ​​of different populations under the condition that the constraints of each device are satisfied;

[0183] S25. Update the iteration positions of different populations, and determine the optimal capacity of each device with the optimal fitness value while satisfying the set number of iterations.

[0184] In this embodiment, the number of initialization iterations is 1, and the capacity of the i-th device is CA i ;

[0185] Under the constraints of the i-th equipment, the predicted output of the i-th equipment is used to obtain the fitness value of the i-th equipment model. The iteration position of the i-th equipment model is updated, and the optimal capacity CA of the equipment is determined by the optimal fitness value under the condition of satisfying the set number of iterations. i .

[0186] Embodiment 2

[0187] Please refer to Figure 2 A planning terminal 1 for a rural integrated energy network for rural energy transformation includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, each step of a rural integrated energy network planning method of embodiment 1 is implemented.

[0188] In summary, the present invention provides a planning method and terminal for a rural integrated energy network for rural energy transformation, proposes a typical structure of a rural integrated energy network for rural energy transformation, and constructs mathematical models of energy supply equipment, energy conversion equipment, and energy storage equipment based on this structure. In addition, a load control model considering agricultural production is constructed, a multi-objective function for rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency, etc. is established, and constraints of the energy network planning optimization model are set, thereby forming a rural integrated energy network planning optimization model, and iterating the capacity of each device, and obtaining the optimal capacity when the iteration converges, and substituting the optimal capacity into the rural integrated energy network planning optimization model to generate a planning scheme. Compared with isolated planning of power grids and heat networks, it is more conducive to achieving organic coordination and multi-energy complementarity between different energy sources, and improving rural energy utilization efficiency.

[0189] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0190] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A planning method for a rural integrated energy network for rural energy transformation, characterized by: The following steps are involved: S1. Summarize the supply and consumption characteristics of rural energy, propose a typical structure of rural integrated energy network for rural energy transformation, analyze the optimization characteristics and key technologies of integrated energy network planning, and establish a multi-objective function of rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions based on the typical structure of rural integrated energy network; S2. Based on the typical structure of the rural comprehensive energy network, mathematical models of the energy supply equipment, energy conversion equipment and energy storage equipment are constructed. In addition, a load regulation model considering agricultural production is constructed, a multi-objective function for the rural comprehensive energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established, and constraints of the energy network planning optimization model are set, thereby forming a rural comprehensive energy network planning optimization model, and iterating the capacity of each equipment. When the iteration converges, the optimal capacity is obtained, and the optimal capacity is substituted into the rural comprehensive energy network planning optimization model to generate a planning scheme.

2. The planning method of rural integrated energy network for rural energy transformation according to claim 1 is characterized by: The step S1 is specifically as follows: S11. Based on the typical structure of the rural integrated energy network, a multi-objective function for rural integrated energy network planning including system economic benefits, environmental benefits, energy efficiency and other dimensions is established: Economic objective function: minf1=C INV +C OPT +C RE +C PUR ; In the formula, C INV represents the annual value of energy network investment cost, C OPT represents the annual value of energy grid operation and maintenance cost, C RE Represents the equipment replacement cost value, C INV represents the cost of purchasing energy externally, and the minimum annual cost of the energy network is used as the objective function to reflect the economic benefits of the rural comprehensive energy network planning optimization model; in, In the formula, I represents the set of equipment component types, i represents the equipment type, represents the unit capacity investment cost of equipment i, M i represents the total configuration capacity of device i, y i represents the equipment life, r represents the discount rate, represents the annual operation and maintenance cost per unit capacity of equipment i, T represents the system operation period, represents the price of purchasing electricity from the large power grid, P i ele Indicates the amount of electricity purchased; Environmental objective function: In the formula, represents the carbon emission coefficient of the electrical energy in the external system, Indicates the carbon emission coefficient of the system biogas, P t bio Represents the consumption of biogas in the system. The minimum annual carbon emission of the energy network is used as the objective function to reflect the environmental benefits of the rural comprehensive energy network planning optimization model; Energy efficiency objective function: In the formula, E i represents the energy supply of device i, W i represents the energy consumption of equipment i, and the ratio of energy supply and consumption of energy supply equipment is used as the objective function reflecting the comprehensive energy efficiency of the rural integrated energy network planning optimization model; S12. Determine the investment capacity constraints, planning area constraints, grid power supply constraints, equipment power supply operation constraints and energy balance constraints of the rural comprehensive energy network planning optimization model.

3. The planning method of rural integrated energy network for rural energy transformation according to claim 2 is characterized by: The step S12 is specifically as follows: S121. Determine investment capacity constraints to ensure that governments, enterprises and rural residents can participate in the construction of an integrated energy network: T max ≥f in (n); Where, T max represents the maximum investment capacity of rural integrated energy network, f in (n) represents the sum of the initial investment costs of n equipment; S122. Determine the planning area constraints to ensure site resources for equipment installation: In the formula, m i represents the land area occupied by the installation of the i-th equipment, AZ max represents the available land area for building an integrated energy system; S123. Determine the power supply constraints of the power grid to ensure stable operation of the power grid: Where D max Indicates the maximum power supply capacity of the power grid. represents the power consumption of the i-th device, represents the power generation of the i-th device, represents the power load designed inside the rural integrated energy network, and S represents the safety power consumption coefficient; S124. Determine the operating constraints of equipment functions to ensure equipment output efficiency: In the formula, represents the minimum power supplied by the i-th device, represents the maximum power supplied by the i-th device, represents the ramp rate of the i-th device reducing its output, It represents the ramp rate of the output increase of the i-th device; S125. Determine energy balance constraints to ensure the supply and demand balance of electricity, gas, heat and other energies in the energy grid at any time: P i′ (t)+P buy (t)=P Load (t)+P loss (t); Where P i′ (t) represents the energy supply of the energy supply equipment during period t, P buy (t) represents the energy purchased from the external system during period t, P Load (t) represents the energy grid load during period t, P loss (t) represents the active power loss of the energy grid during period t.

4. The planning method and terminal of the rural integrated energy network for rural energy transformation according to claim 1 are characterized by: The step S2 is specifically as follows: S21. Setting the initial construction location of each equipment; S22. Predict the day-ahead output power of wind power, photovoltaic power, solar thermal power, biomass biogas cogeneration, energy storage and other equipment, and obtain the upper and lower bounds of the output of each device; S23, setting initial parameters such as the number of iterations and step length, and randomly selecting models of different devices to determine the initial population; S24, obtaining fitness values ​​of different populations under the condition that the constraints of each device are satisfied; S25. Update the iteration positions of different populations, and determine the optimal capacity of each device with the optimal fitness value while satisfying the set number of iterations.

5. The planning method of rural integrated energy network for rural energy transformation according to claim 1 is characterized by: The mathematical models of energy supply equipment, energy conversion equipment and energy storage equipment established in the typical structure of the rural integrated energy network include: Wind turbine power generation model: Where P WT (t) represents the power generation of the wind turbine at time t, ν input (t) represents the cut-in wind speed at time t, ν rated (t) represents the rated wind speed at time t, ν output (t) represents the cut-out wind speed at time t, ν(t) represents the wind speed at time t, Indicates the rated power of the fan; Distributed photovoltaic power generation model: Where P pv Represents the power generation of distributed photovoltaics, P SIC Indicates the maximum power generation of distributed photovoltaic under rated conditions, G lNG Represents the solar radiation intensity, G STC represents the solar radiation intensity under rated conditions, k represents the power temperature coefficient of the solar panel, T c Indicates the actual operating temperature of the solar panel, T r Indicates the panel temperature under standard test conditions; Solar thermal power generation collection link model: Where η d-th represents the light-to-heat conversion efficiency, S SF represents the mirror field area, The direct normal radiation intensity value represented by represents the heat loss caused by adjusting the light field tracking strategy, η cur represents the heat loss coefficient, It indicates the thermal power transferred from the heat collecting link to the heat conducting medium; CSP heat storage model: In the formula, represents the thermal storage power of the thermal storage subsystem at time t, represents the heat release power of the heat storage subsystem at time t, represents the thermal power transferred from the heat transfer medium to the heat storage subsystem, represents the thermal power transferred from the heat storage subsystem to the heat conducting medium, η cha represents the heat storage efficiency of the heat storage subsystem, η dis represents the heat release efficiency of the heat storage subsystem, represents the heat storage capacity of the heat storage subsystem at time t, represents the heat storage capacity of the heat storage subsystem at time t-1, η loss represents the heat loss rate of the heat storage subsystem; Solar thermal power generation model: Where η th-e represents the thermoelectric conversion efficiency, It indicates the heat power transferred from the heat-conducting medium to the power generation subsystem; Biomass biogas combined heat and power gas turbine model: Q wat (t)=CV(t)ΔT; Where V GT (t) represents the amount of natural gas consumed by the gas turbine at time t, L NG represents the lower calorific value of natural gas, Δt represents the time step, P CHP,e (t) represents the electric power generated by the gas turbine at time t, η CHP,e represents the power generation efficiency of the gas turbine, Q wat (t) represents the heat generated by the hot water module, C represents the specific heat capacity of the flue gas, V(t) represents the volume of the flue gas entering the hot water module, and ΔT represents the temperature change of the flue gas in the hot water module; Biomass biogas cogeneration waste heat boiler model: Where P CHP.yr (t) represents the power of waste heat generated by the gas turbine, η CHP.yr represents the waste heat utilization efficiency, η loss Indicates the operating loss ratio; From the above description, it can be seen that the biomass biogas cogeneration system refers to a system that uses methane produced by biomass as the main fuel, reacts with oxygen, and releases a large amount of high-flow airflow, thereby driving the rapid operation of power equipment such as gas turbines to provide electricity to users; in addition, the high-temperature gas generated after the operation of the gas turbine is reused by equipment such as waste heat boilers, thereby delivering heat to users; the use of a stepped energy utilization rate can reduce the operating costs of the system. At the same time, since the gas is burned under oxygen-rich conditions, the emission of waste gas can be reduced; Energy storage battery model: In the formula, E SOC (t+1) and E SOC (t) represents the storage capacity of the energy storage battery at time t+1 and t, α represents the self-discharge rate of the energy storage battery, η EES,C and η EES,D Represents the charging and discharging efficiency of the energy storage battery, R EES,C and R EES,D represents the charging and discharging state variables of the energy storage battery, and Indicates the upper and lower limits of the charging and discharging status of the energy storage battery; From the above description, we can see that in the integrated energy grid, the supply of natural resources such as solar energy and wind energy is highly random, which will lead to significant fluctuations in the output of photovoltaic, wind turbine and other power generation equipment, which may directly affect the stability of the energy grid operation; energy storage batteries have the function of smoothing fluctuations and shaving peaks and filling valleys, and are a key device to ensure reliable energy use for users; Thermal storage tank model: Where, T SOC (t+1) and T SOC (t) represents the heat storage capacity of the heat storage tank at time t+1 and t, β represents the heat loss of the heat storage tank, η TES,C and η TES,D Represents the heat absorption and heat release efficiency of the heat storage tank, R TES,C and R TES,D represents the heat absorption and release state variables of the heat storage tank, and Indicates the upper and lower limits of the heat absorption and heat release state of the energy storage battery; From the above description, we can know that in the later operation of the energy grid, on the one hand, due to the different energy prices in different periods, it is possible to store heat in the heat storage tank during low-price periods and release heat during high-price periods to reduce the purchase of external energy; on the other hand, considering the output volatility of wind turbines, photovoltaics and other equipment, the heat storage tank can be used together with the energy storage battery to store excess energy; Light environment control load model: In the formula, I N Represents the total intensity of greenhouse solar radiation, I day It represents the intensity of supplementary lighting during the day, P represents the total power required for supplementary lighting in the greenhouse, and A represents the area of ​​the glass greenhouse; Thermal environment control load model: Q=C ht A cover (T in -T out )+ρ i N c V[c p (T in -T out )+h va (W in -W out )]; Where Q represents the heat demand power of the greenhouse, C ht represents the heat transfer coefficient of glass, A cover Indicates the greenhouse glass coverage area, T in represents the temperature in the greenhouse, T out represents the ambient temperature outside the greenhouse, ρ i Indicates the air density in the greenhouse, N c represents the ventilation frequency of the greenhouse, V represents the volume of the greenhouse, c p represents the constant pressure specific heat capacity of the air in the greenhouse, h va represents the latent heat of vaporization of water, W in Indicates the humidity content of the air in the greenhouse, W out Indicates the humidity content of the air outside the greenhouse.

6. A planning terminal for a rural integrated energy network for rural energy transformation, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the processor implements the various steps of the method for planning a rural integrated energy network as described in any one of claims 1 to 5.

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