A planning method for an integrated energy system of electric cooling, heating and fertilizer cogeneration

Abstract

The present invention provides a method for planning an electric combined cooling, heating and fertilizer energy system, constructs a framework of an integrated energy system based on biomass and photovoltaic power supply; establishes a distributed photovoltaic grid-connected capacity assessment model, establishes a biomass supply capacity assessment model; establishes an operation benefit optimization model for the integrated energy system, and constructs operation constraints; uses a genetic algorithm to iteratively solve the optimization model to obtain a calculation result, uses the calculation result as an iterative starting point, uses an interior point method to perform secondary optimization, determines the optimal solution of the optimization model, and uses the optimal solution as the final electric combined cooling, heating and fertilizer energy system planning scheme. The present invention can effectively improve the economy, comprehensiveness and energy saving of rural energy systems, and achieve friendly and high-quality supply of comprehensive energy needs of rural users.

Description

Technical Field

[0001] The present invention belongs to the technical field of integrated energy system planning, and in particular relates to a method for planning an integrated energy system for electric heating, cooling and fertilizer multi-generation. Background Art

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

[0003] In recent years, based on the severe situation of the continuous depletion of traditional fossil energy, the highly concerned ecological and environmental protection requirements in the energy field, the diversified end-users and the continued growth in high-quality energy demand, integrated energy systems of different scales are regarded as key technologies for improving energy efficiency, meeting multi-energy needs, and reducing resource waste. Research in multiple fields such as the planning, operation, and sustainable development policies of integrated energy systems has been widely carried out.

[0004] In the existing integrated energy system planning methods, according to the different types of system input energy or regional resource endowments, it can be divided into different scenarios such as traditional integrated energy system planning, "photovoltaic +" integrated energy system planning, and "biomass +" integrated energy system planning. However, these methods all have certain shortcomings: on the one hand, the traditional integrated energy system planning purchases electricity and natural gas from regional energy companies, and meets the comprehensive energy needs of regional users through equipment selection optimization and capacity configuration, but does not consider the local development of resources and energy supply. The benefits of such integrated energy systems are limited. On the other hand, clean power technology in the power sector represented by distributed photovoltaic power generation has developed the fastest and was first included in the integrated energy system planning. However, my country's photovoltaic power generation mostly adopts the grid-connected mode. Due to the constraints of the grid operation, its grid-connected capacity is limited, and therefore it cannot support regional energy needs on a large scale.

[0005] In addition, thanks to its advantages such as abundant reserves and huge development potential, the multi-energy supply potential of biomass has gradually been taken into consideration in the planning of integrated energy systems. However, problems such as low biomass utilization efficiency and single utilization form are still prominent and need to be further optimized. Summary of the invention

[0006] In order to solve the above problems, the present invention proposes a planning method for an electric heating and cooling fertilizer multi-generation integrated energy system. The present invention is aimed at rural areas. On the basis of the overall planning framework of the "biomass + photovoltaic" integrated energy system, it is optimized to achieve a friendly and high-quality supply of comprehensive energy needs of rural users.

[0007] According to some embodiments, the present invention adopts the following technical solutions:

[0008] A method for planning an electric cooling, heating and fertilizer multi-generation integrated energy system comprises the following steps:

[0009] Build a framework for an integrated energy system based on biomass and photovoltaic power supply;

[0010] According to the framework of the integrated energy system, a distributed photovoltaic grid-connected capacity assessment model and a biomass supply capacity assessment model were established;

[0011] According to the established evaluation model, the distributed photovoltaic grid-connected capacity and biomass supply capacity are estimated respectively. Based on the estimated results, an operation benefit optimization model of the integrated energy system is established, and the operation constraints are constructed;

[0012] The optimization model is iteratively solved using a genetic algorithm to obtain a calculation result. The calculation result is used as an iterative starting point, and a secondary optimization search is performed using an interior point method to determine the optimal solution of the optimization model. The optimal solution is used as the final planning scheme for the electrical heating, cooling and fertilizer multi-generation integrated energy system.

[0013] As an optional implementation method, the integrated energy system framework also includes grid energy and gas energy. The energy supply principle of the integrated energy system framework is to consume local solar energy and biomass resources in a limited way, realize the combined supply of electricity and fertilizer, and supplement it with grid energy and gas energy.

[0014] As an optional implementation method, the specific process of establishing a distributed photovoltaic grid-connected capacity assessment model includes: the photovoltaic access capacity of the distribution network where the integrated energy system is located is the ratio of the maximum photovoltaic injection power in the node to the actual output of the rated photovoltaic when the node voltage per unit value in the network reaches the set value.

[0015] As an optional implementation method, the specific process of establishing a biomass supply capacity assessment model includes: establishing a theoretical biogas production calculation model for biomass raw material input, a theoretical power supply calculation model for biomass direct combustion power generation, and a by-product compound fertilizer production calculation model.

[0016] As an optional implementation, the operating revenue optimization model maximizes the revenue obtained by adding the revenue from selling comprehensive energy to other revenues and deducting the real-time operating costs.

[0017] As a further limitation, the real-time operating costs include real-time energy purchase costs, real-time equipment maintenance costs, and real-time pollution emission costs;

[0018] The real-time energy purchase cost includes the cost of purchasing electricity from the power grid company, the cost of purchasing gas from the natural gas company, the cost of purchasing biomass resources, and the cost of purchasing supplementary fertilizers.

[0019] As an optional implementation, the operation constraints include constraints on source-load supply-demand balance, energy conversion equipment output, photovoltaic output, and biomass supply capacity.

[0020] An electric cooling, heating and fertilizer multi-generation integrated energy system planning system, comprising:

[0021] A framework building module configured to construct a comprehensive energy system framework based on biomass and photovoltaic power supply;

[0022] An evaluation model building module is configured to establish a distributed photovoltaic grid-connected capacity evaluation model and a biomass supply capacity evaluation model according to an integrated energy system framework;

[0023] The optimization model building module is configured to estimate the distributed photovoltaic grid-connected capacity and biomass supply capacity respectively according to the established evaluation model, and on the basis of the estimated results, establish an operation benefit optimization model of the integrated energy system and construct operation constraint conditions;

[0024] The optimization calculation module is configured to use a genetic algorithm to iteratively solve the optimization model to obtain a calculation result, use the calculation result as an iterative starting point, perform secondary optimization using an interior point method, determine the optimal solution of the optimization model, and use the optimal solution as the final electrical cooling, heating, and fertilizer multi-generation integrated energy system planning scheme.

[0025] An electronic device includes a memory and a processor, and computer instructions stored in the memory and running on the processor. When the computer instructions are run by the processor, the steps in the above-mentioned electric heating, cooling and fertilizer multi-generation integrated energy system planning method are completed.

[0026] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the steps in the above-mentioned method for planning an electric heating, cooling and fertilizer multi-generation integrated energy system are completed.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] This invention focuses on the planning of comprehensive energy systems in rural areas. Taking into account that the energy resource endowment in rural areas is more diversified than that in urban areas, a "biomass + photovoltaic" regional comprehensive energy system planning framework suitable for rural areas is proposed. The principle of giving priority to the consumption of regional energy resources and supplementing the energy supply of large power grids and gas pipelines is proposed, and a real-time operation profit optimization model of the system is established to effectively improve the economy, comprehensiveness and energy saving of the rural energy system, and realize the friendly and high-quality supply of the comprehensive energy needs of rural users.

[0029] The comprehensive energy system planning framework of the present invention rationally considers the local energy supply potential of regional resources and the complementary effects of power grid electricity and gas pipeline network, as well as the complementary effects between different types of renewable resources, to ensure good economy of the system and improve the comprehensive performance of the energy system.

[0030] The present invention provides a hybrid algorithm based on "genetic algorithm + interior point method" for optimization and solution, which can effectively improve the computing performance and obtain more accurate calculation results when the model complexity is high.

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0033] Figure 1 It is a schematic diagram of the integrated energy system planning framework;

[0034] Figure 2 It is a schematic diagram of the hybrid algorithm optimization solution process;

[0035] Figure 3 is the comprehensive energy load of each typical day in a rural area in this embodiment;

[0036] Figure 4 is a comparison chart of the benefits of each planning result on each typical day in this embodiment;

[0037] Figure 5 is a comparison chart of initial investment and payback period of each planning result in this embodiment;

[0038] Figure 6 2 is a schematic diagram comparing the solving effects of different algorithms in this embodiment. DETAILED DESCRIPTION

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

[0040] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0041] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0042] The present invention proposes a "biomass + photovoltaic" integrated energy system planning framework suitable for rural areas, and establishes a rural biomass comprehensive utilization system model and a distributed photovoltaic grid-connected capacity evaluation model based on the framework, and then establishes a real-time operation benefit optimization model for the rural electrical heating and cooling fertilizer integrated energy system. The optimization model is solved by a hybrid algorithm of genetic algorithm and interior point method to realize the integrated energy system planning for rural areas.

[0043] Specifically, the overall planning framework of the "biomass + photovoltaic" integrated energy system applicable to rural areas, such as Figure 1 As shown, the overall architecture includes biomass energy supply and photovoltaic energy supply, limited consumption of local solar energy and biomass resources, realization of electricity and fertilizer co-supply, and supplemented by large power grid electricity and gas pipeline network natural gas, to achieve friendly and high-quality supply of comprehensive energy needs of rural users.

[0044] At the planning level, a distributed photovoltaic grid-connected capacity assessment model is first established as the basis for considering photovoltaic power supply in the integrated energy system, as shown in formula (1).

[0045]

[0046] In the formula, S pv is the photovoltaic access capacity of the distribution network where the integrated energy system is located, n pv is the total number of nodes connected to photovoltaic power generation, P v,d is the photovoltaic injection power of node d. 1kW It is the actual output of 1kW photovoltaic. It means that there are nodes in the network whose voltage per unit value reaches 1.07.

[0047] According to the empirical data of theoretical biogas production rate of various types of biomass in actual projects and the parameters of various types of biomass raw materials, a theoretical biogas production calculation model for a certain amount of biomass raw material input can be established, as shown in formula (2).

[0048]

[0049] In the formula, G IES Indicates quality B AF The amount of biomass natural gas that can be produced by anaerobic fermentation of biomass raw materials, unit Nm3 , B AF R is the amount of raw materials consumed, in kg. DM R is the dry matter weight of the raw material. VM is the percentage of volatile components contained in dry matter. γ is the gas production rate per unit mass of raw materials, in units of L / (kg·VS), η G is the volume ratio of biogas before and after purification. θ G =35.588MJ / Nm 3 is the standard calorific value of natural gas. 1 =3.6 means 1kWh corresponds to 3.6MJ of energy.

[0050] The theoretical power supply of a certain mass of biomass direct combustion power generation is shown in formula (3):

[0051]

[0052] In the formula, E DCPG For quality B DCPG The theoretical external power supply of biomass raw materials directly burned, unit kWh. DCPG R is the amount of raw materials consumed by the direct-fired unit, in kg. S is the self-consumption rate of biomass power plant, m L The standard amount of straw consumed by the direct-fired unit to produce 1kWh of electricity, unit: kg / kWh. L is the calorific value of standard straw, θ 2 It is the actual calorific value of the raw material, in MJ / kg.

[0053] The two by-products of biomass anaerobic fermentation sludge and biomass direct combustion power generation ash can be used to prepare compound fertilizers required for agricultural production. The yield is shown in formula (4) and the effective ingredients are shown in formula (5).

[0054]

[0055]

[0056] In the formula, F z is the total output of fertilizer sources from biomass anaerobic fermentation and direct combustion for power generation, F z1 , F z2 and F z3 They are N element, K 2 O.P 2 O 5 The content of three active ingredients. 1 and η 2 are the fertilizer utilization rates of BBP biogas residue and BPP ash residue respectively. 0≤α g ≤1 indicates the percentage of gas g in biogas. gIndicates the molar mass of gas g, in g / mol. 2 =22.4 is the standard gas molar mass, unit L / mol. k includes CH 4 , CO 2 , CO, H 2 S et al. x is the proportion of biogas residue to the remaining dry matter, τ x1 Indicates the nitrogen content in biomass. τ x2 and τ x3 Respectively represent the potassium and phosphorus content in biomass, unit is g / kg·DM. η H2O Indicates the moisture content of biogas residue after aerobic composting. τ y2 and τ y3 Respectively represent the potassium and phosphorus content in biomass, unit is g / kg DM. η y2 and η y3 The ratio of potassium and phosphorus in fly ash and bottom ash, η y It is the proportion of the components in the ash with a particle size less than 1 mm.

[0057] Next, a real-time operating profit optimization model of the “biomass + photovoltaic” integrated energy system is established, as shown in formula (6).

[0058] max C Q =C SELL +C ADD -C OPE (6)

[0059] The instructions are as follows:

[0060] (1) Profit from sale of comprehensive energy C SELL :

[0061] C SELL =∑c j L j (7)

[0062] Where, L j is the energy demand of regional load, in kWh, c j The selling price of energy j, in CNY / kWh. j can be electricity, gas, cooling or heating.

[0063] (2) Other income C ADD :Including the feed-in tariff subsidy for biomass direct combustion power generation and photovoltaic power generation C SUB , the comprehensive income of producing and selling triple compound fertilizer C FER , and the revenue from selling excess energy to the grid and natural gas company C SALE .

[0064]

[0065] In the formula, c DPV,E and c DCPG,E They are the unit grid-connected electricity price subsidies for distributed photovoltaic and biomass direct combustion power generation, in yuan / kWh. SALE,F is the selling price of 1kg of triple compound fertilizer, c COS,F F is the comprehensive cost of producing 1kg of triple compound fertilizer, in yuan / kg. F is the output, in kg. c SALE,E and c SALE,G The unit prices of electricity and gas sold to the power grid and gas grid, respectively, in RMB / kwh. SALE G is the electricity sold to the grid company. SALE Natural gas for sale

[0066] (3) Real-time operating cost of the “biomass + photovoltaic” integrated energy system C OPE :

[0067] C OPE =C PUR +C MTN +C POL (9)

[0068] 1) Real-time energy purchase cost C PUR : Including the cost of purchasing electricity from the power grid company C GRID , the cost of purchasing gas from the natural gas company C PIPE , Cost of acquiring biomass resources C BMS and the cost of purchasing additional fertilizer C SUP .

[0069]

[0070] In the formula, c GRID and c PIPE They are the unit prices of electricity and gas, in yuan / kWh. GRID is the electricity purchased from the power grid company, G PIPE The unit is kWh. AF and c DCPG The unit price of biomass purchased for anaerobic fermentation and direct combustion power generation, in yuan / kg. b and F b They respectively represent the unit price and purchase quantity of fertilizer b.

[0071] 2) Equipment real-time maintenance cost C MTN :The maintenance cost of a certain amount of energy produced by a certain equipment is calculated by the maintenance price coefficient of the equipment producing 1kWh of energy.

[0072] CMTN =∑X i c M,i (∑P i,j ) (11)

[0073] In the formula, c M,i It represents the maintenance cost of equipment i producing 1 kWh of energy, in RMB / kWh. i,j The amount of energy j produced by equipment i, in kWh. j can be E, H, C, G, representing the four energies of electric heating and cooling, respectively. X i A 0-1 variable indicating whether device i is put into use, and the same applies to the following.

[0074] 3) Real-time pollution emission cost C POL : Includes the cost of controlling emissions of carbon monoxide (CO) and nitrogen oxide compounds (NOx).

[0075]

[0076] In the formula, c CO and c NOx are the treatment costs per unit mass of CO and NOx, in RMB / kg. i,CO and V i,NOx are the CO and NOx emissions of equipment i, in kg. i is the load rate of device i.

[0077] The model constraints are as follows:

[0078] (1) Equality constraint, i.e., source-load supply-demand balance constraint. Equation (13) is the electricity balance equation, Equation (14) is the gas balance equation, and Equation (15) is the heat and cold energy balance equation.

[0079] E IES +E GRID =L E +∑E i X i (13-a)

[0080] E IES =L E +∑E i X i (13-b)

[0081] E SALE =E IES -(L E +∑E i X i ) (413-c)

[0082]

[0083] GIES +G PIPE =L G +∑G i X i (14-a)

[0084] G IES =L G +∑G i X i (14-b)

[0085] G SALE =G IES -(L G +∑G i X i ) (14-c)

[0086]

[0087] Where, L E , L G , L H , L C are the regional electricity, electricity, heating and cooling loads, E i and G i They represent the electricity and natural gas consumed by device i, both in kWh. pv is the electricity supplied by photovoltaics. δ represents the conversion efficiency of each type of unit. The subscript corresponds to the unit type, and the superscript corresponds to the target energy type. E, G, H, and C represent the four types of energy, electrical, thermal, and cold, respectively. It represents the "gas-to-heat" conversion efficiency of CCHP units. Sub-formulas a, b, and c represent the three scenarios of the integrated energy system where local energy supply is less than demand, supply and demand are balanced, and supply exceeds demand.

[0088] (2) Inequality constraints.

[0089] 1) Output constraints of energy conversion equipment.

[0090] min P i,j ≤P i,j ≤max P i,j (16)

[0091] 2) Photovoltaic output constraints.

[0092] 0≤E pv ≤S pv P 1kW (17)

[0093] 3) Constraints on biomass supply capacity.

[0094]

[0095] In the formula, B a Represents the regional maximum supply capacity of biomass a.

[0096] According to the production of "biomass-electricity" and "biomass-natural gas" in the system, the fertilizer source output can be obtained according to equations (4) and (5), and then by purchasing conventional fertilizers, ternary compound fertilizer can be prepared. The optimization model is shown in equations (19) to (21).

[0097]

[0098]

[0099] F F =F z +∑F b (twenty one)

[0100] In the formula, C F is the sales revenue of the produced ternary compound fertilizer, unit yuan, c F is the unit price of ternary compound fertilizer, unit: yuan / kg, F F is the output of triple compound fertilizer, unit: kg. c b and F b They represent the unit price and purchase amount of fertilizer b, respectively, and b represents the type of fertilizer. 1 、r 2 and r 3 They are N, K in the ternary compound fertilizer 2 O and P 2 O 5 The percentage of b,z1 , b,z2 , and b,z3 are N and K in fertilizer b respectively. 2 O and P 2 O 5 percentage.

[0101] Solve the optimization model, such as Figure 2 As shown, the solution method is: set the initial parameters of the genetic algorithm, use the genetic algorithm to iteratively solve the optimization model to obtain the calculation result, use the calculation result as the iteration starting point, use the interior point method to perform secondary optimization, determine the optimal solution of the optimization model, and use the optimal solution as the final electrical heating and cooling fertilizer multi-generation integrated energy system planning scheme.

[0102] As a typical embodiment, taking a rural area in the north as an example, four typical days in spring, summer, autumn and winter are selected respectively. Figure 3 From top to bottom are the regional electricity, gas, heat, cooling loads and unit capacity photovoltaic output. The benchmark values ​​of the four loads are 12, 6.5, 8.5 and 15MW respectively.

[0103] Under the voltage deviation constraint of the distribution network in this area, it has been evaluated that the allowed installation capacity of distributed photovoltaics in the distribution network in this area is 4.5MW.

[0104] Regarding the forms of biomass utilization, the present invention is divided into three categories when applied, namely, anaerobic fermentation only, direct combustion power generation only, and "anaerobic fermentation + direct combustion power generation". The relevant parameters are shown in Tables 1 to 5.

[0105] Table 1 Price Parameters (Yuan)

[0106]

[0107] Table 2 Equipment parameters

[0108]

[0109]

[0110] Table 3 Biomass parameters

[0111]

[0112] Table 4 Ash parameters

[0113]

[0114] Table 5 Supplementary fertilizer parameters

[0115]

[0116]

[0117] Various types of parameters are introduced into the rural "biomass + photovoltaic" integrated energy system optimization model. After iterative optimization by the hybrid algorithm, the planning results of the electric cooling, heating and fertilizer integrated energy system for the rural area are obtained, as shown in Table 6.

[0118] It should be pointed out that A1 represents the planning result of the traditional integrated energy system, A2 represents the planning result considering the regional distributed photovoltaic power supply potential, A3 represents the planning result considering only the biomass natural gas potential, A4 represents the planning result considering only the biomass power supply potential, A5 represents the planning result considering the combined supply of biomass electricity and fertilizer, and A6 represents the "biomass + photovoltaic" system.

[0119] Table 6 Results of comprehensive energy system planning in rural areas

[0120]

[0121]

[0122] First, compare the benefits of each planning result, such as Figure 4 shown.

[0123] From the seasonal perspective, affected by seasonal radiation intensity and atmospheric temperature, biomass natural gas and photovoltaic power generation show higher efficiency and benefits in summer than in winter. From the perspective of system energy input types: 1) The economic efficiency of traditional integrated energy system planning is the lowest; 2) Limited by the capacity of photovoltaic grid connection, photovoltaic cannot support regional energy demand on a large scale, and the system economic optimization effect is limited; 3) When only considering the biomass energy supply potential, the planning result based on the biomass comprehensive utilization system is the most economical, and only considering the anaerobic fermentation of biomass is the worst economical, and it is not recommended to be used alone in the rural integrated energy system; 4) The system economic efficiency of only considering a single type of energy resource for on-site energy supply still has room for optimization. Based on the complementary effect between energy sources, the "biomass + photovoltaic" rural integrated energy system has better system economics than the "biomass +" and "photovoltaic +" solutions.

[0124] From the perspective of initial investment and payback period, Figure 5 As shown in the figure, the initial investment and payback period of the "PV+" integrated energy system are optimal, but it cannot fully utilize the local resources in the region. The "biomass+" integrated energy system, especially the integrated energy system that only considers biomass natural gas, has a large initial investment and a payback period of more than 8 years. Although the "biomass+PV" integrated energy system has a large initial investment, due to the complementary effects of distributed photovoltaic and biomass comprehensive utilization systems, its payback period can even be close to that of the "PV+" system.

[0125] Therefore, from the perspective of system operation income and initial investment and recovery period, the "biomass comprehensive utilization system + distributed photovoltaic" rural comprehensive energy system proposed in the present invention is the optimal planning scheme for the rural area.

[0126] Finally, the advantages of the hybrid algorithm based on "genetic algorithm + interior point method" proposed in this invention are verified. Taking the real-time operation cost of the system at a certain moment as an example, the iteration results are as follows: Figure 6 As shown, the horizontal axis is the number of iterations, and the vertical axis is the real-time running cost of the system, in units of yuan.

[0127] As can be seen from the figure, the hybrid algorithm proposed in the present invention has better solution performance than the genetic algorithm or the interior point method alone, especially when the complexity of the solution model is high (A5, A6), the solution result based on the hybrid algorithm is better. Compared with the use of the genetic algorithm and the interior point method alone, the optimization amount of the optimization result based on the hybrid algorithm in this embodiment on the real-time operation cost of the rural integrated energy system is shown in Table 7.

[0128] Table 7 Reduction in real-time operating cost of the system based on the hybrid algorithm (%)

[0129]

[0130] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0134] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0135] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A planning method for an integrated energy system of electric cooling, heating and fertilizer multi-generation. Its characteristics are: The following steps are involved: Build a framework for an integrated energy system based on biomass and photovoltaic power supply; According to the framework of the integrated energy system, a distributed photovoltaic grid-connected capacity assessment model and a biomass supply capacity assessment model were established; According to the established evaluation model, the distributed photovoltaic grid-connected capacity and biomass supply capacity are estimated respectively. Based on the estimated results, an operation benefit optimization model of the integrated energy system is established, and the operation constraints are constructed; The optimization model is iteratively solved by using a genetic algorithm to obtain a calculation result, and the calculation result is used as an iterative starting point to perform a secondary optimization search by using an interior point method to determine the optimal solution of the optimization model, and the optimal solution is used as the final planning scheme for the electric heating and cooling fertilizer multi-generation integrated energy system; The specific process of establishing a distributed photovoltaic grid-connected capacity assessment model includes: the photovoltaic access capacity of the distribution network where the integrated energy system is located is the ratio of the maximum photovoltaic injection power in the node to the actual output of the rated photovoltaic when the voltage per unit value of the node in the network reaches the set value; The specific process of establishing the biomass supply capacity evaluation model includes: establishing a theoretical biogas production calculation model for biomass raw material input, a theoretical power supply calculation model for biomass direct combustion power generation, and a by-product compound fertilizer production calculation model; The forms of biomass utilization are divided into three categories, including anaerobic fermentation only, direct combustion power generation only, and "anaerobic fermentation + direct combustion power generation"; A theoretical biogas production calculation model for a certain amount of biomass raw material input is established, as shown in formula (2); In the formula, G IES Indicates quality B AF The amount of biomass natural gas that can be produced by anaerobic fermentation of biomass raw materials, unit Nm 3 , B AF is the amount of raw materials consumed, in kg; R DM R is the dry matter weight of the raw material; VM is the percentage of volatile components contained in dry matter; γ is the gas production rate per unit mass of raw materials, unit L / (kg·VS), η G is the volume ratio of biogas before and after purification; θ G =35.588MJ / Nm 3 is the standard natural gas calorific value; ω 1 =3.6 means 1kWh corresponds to 3.6MJ of energy; The theoretical power supply of a certain mass of biomass direct combustion power generation is shown in formula (3); In the formula, E DCPG For quality B DCPG The theoretical external power supply of biomass raw materials directly burned, unit kWh; B DCPG is the amount of raw materials consumed by the direct-fired unit, in kg; R S is the self-consumption rate of biomass power plant, m L The standard amount of straw consumed by the direct-fired unit to produce 1 kWh of electricity, unit: kg / kWh; θ L is the calorific value of standard straw, θ 2 is the actual calorific value of the raw material, in MJ / kg; The model constraints are as follows: (1) Equality constraint, i.e., source-load supply-demand balance constraint, is as follows: Electric balance equation: AND IES +E GRID =L E +∑E i X i (13-a) E IES =L E +∑E i X i (13-b) AND SALE =And IES -(THE E +∑E i X i ) (13-c) Gas balance equation: G IES +G PIPE =L G +∑G i X i (14-a) G IES =L G +∑G i X i (14-b) G SALE =G IES -(L G +∑G i X i ) (14-c) Heat and cold energy balance equation: Where, L E , L G , L H , L C are the regional electricity, gas, heating and cooling loads, E i and G i They represent the electricity and natural gas consumed by equipment i, both in kWh; E pv is the electricity supplied by photovoltaics; δ represents the conversion efficiency of each type of unit, the subscript corresponds to the unit type, the superscript corresponds to the target energy type, E, G, H, and C represent the four types of energy, electrical, thermal, and cold, respectively. It represents the "gas-to-heat" conversion efficiency of CCHP units; sub-formulas a, b, and c represent the three scenarios of local energy supply less than demand, supply and demand balance, and supply greater than demand in the integrated energy system respectively; (2) Inequality constraints: 1) Output constraints of energy conversion equipment: my P i,j ≤P i,j ≤max P i,j (16) 2) Photovoltaic output constraints: 0 ≤E pv ≤S pv P 1kW (17) 3) Biomass supply capacity constraints: In the formula, B a Represents the regional maximum supply capacity of biomass a.

2. A method for planning an electric heating and cooling combined energy system as claimed in claim 1, Its characteristics are: The integrated energy system framework also includes grid energy and gas energy. The energy supply principle of the integrated energy system framework is to consume local solar energy and biomass resources in a limited way, realize the combined supply of electricity and fertilizer, and supplement it with grid energy and gas energy.

3. A method for planning an integrated energy system for electric heating, cooling and fertilizer multi-generation as claimed in claim 1, Its characteristics are: The operating profit optimization model is to maximize the profit obtained by adding the profit from selling comprehensive energy and other profits, minus the real-time operating costs.

4. A method for planning an integrated energy system for electric heating, cooling and fertilizer multi-generation as claimed in claim 3, Its characteristics are: The real-time operating costs include real-time energy purchase costs, real-time equipment maintenance costs and real-time pollution emission costs; The real-time energy purchase cost includes the cost of purchasing electricity from the power grid company, the cost of purchasing gas from the natural gas company, the cost of purchasing biomass resources, and the cost of purchasing supplementary fertilizers.

5. A planning system for an electric cooling, heating and fertilizer combined energy system, based on a planning method for an electric cooling, heating and fertilizer combined energy system as claimed in any one of claims 1 to 4, Its characteristics are: include: A framework building module configured to construct a comprehensive energy system framework based on biomass and photovoltaic power supply; An evaluation model building module is configured to establish a distributed photovoltaic grid-connected capacity evaluation model and a biomass supply capacity evaluation model according to an integrated energy system framework; The optimization model building module is configured to estimate the distributed photovoltaic grid-connected capacity and biomass supply capacity respectively according to the established evaluation model, and on the basis of the estimated results, establish an operation benefit optimization model of the integrated energy system and construct operation constraint conditions; The optimization calculation module is configured to use a genetic algorithm to iteratively solve the optimization model to obtain a calculation result, use the calculation result as an iterative starting point, perform secondary optimization using an interior point method, determine the optimal solution of the optimization model, and use the optimal solution as the final electrical cooling, heating, and fertilizer multi-generation integrated energy system planning scheme.

6. An electronic device, Its characteristics are: The invention comprises a memory and a processor and computer instructions stored in the memory and executed on the processor. When the computer instructions are executed by the processor, the steps in the planning method of an electric heating, cooling and fertilizer multi-energy supply integrated energy system described in any one of claims 1 to 4 are completed.

7. A computer-readable storage medium, Its characteristics are: Used to store computer instructions, which, when executed by a processor, complete the steps of a method for planning an electric heating, cooling and fertilizer multi-generation integrated energy system according to any one of claims 1 to 4.

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