Planning method of regional electricity-biogas energy microgrid considering mixed biomass energy flows

Abstract

The present invention discloses a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows, comprising the steps of establishing a regional electricity-biogas integrated energy microgrid planning model considering mixed biomass energy flows, and using as input parameters of the planning model a set of parameters of nodes to be planned for the biogas project, load demand parameters, a set of parameters of biomass raw material supply points, a set of parameters of pipelines to be planned, a transportation network, and a distribution network structure. The present invention proposes a regional electricity-biogas integrated energy microgrid planning model considering mixed biomass energy flows. The model focuses on the effects of mixed fermentation technology on the optimal mixing ratio requirements of different biomass energy flows and the corresponding anaerobic fermentation methods, biogas pipeline network structure, the investment and construction of distributed biogas gas units, and the number, scale, and site selection of anaerobic fermentation. The model optimizes the planning of biogas pipeline networks, biogas projects, and biomass raw material transportation routes while meeting regional electricity and gas load requirements.

Description

Technical Field

[0001] The present invention relates to the technical field of energy microgrid planning, and in particular to a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flow. Background Art

[0002] In remote rural areas, biogas is often used as an alternative to natural gas. The biogas produced by anaerobic fermentation can not only fuel gas generators within the distribution network but also meet local gas demand through regional biogas pipelines, ultimately forming a regional integrated energy microgrid based on biomass energy.

[0003] Due to the high transportation costs and low calorific value of biomass raw materials, rational planning of biogas project site selection is crucial for building a regional integrated energy microgrid based on biomass energy. At present, most of the research on biogas project site selection and planning focuses on the optimization of the biomass energy supply chain.

[0004] With the further improvement of fermentation technology, different from the past single fermentation technology that could only process one or the same type of biomass raw materials, mixed fermentation technology can simultaneously process and ferment different types of biomass raw materials, adjust the carbon-nitrogen ratio of the fermentation system, increase the buffering capacity and organic load of the fermentation system, reduce toxic inhibition, increase system stability, and thus improve fermentation efficiency.

[0005] The emergence of anaerobic co-digestion technology means that traditional biomass supply chain models need to further consider the impact of multiple biomass energy flows and the optimal mixing ratios between these flows on biogas project site selection, scale, fermentation methods, and other planning issues. However, there is currently a lack of technical solutions that can optimize the planning of biogas pipeline networks, biogas projects, and biomass feedstock transportation routes while meeting regional electricity and gas load requirements. Summary of the Invention

[0006] The main purpose of the present invention is to provide a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows, aiming to solve the current problem of lack of technical solutions that can optimize the planning of biogas pipeline networks, biogas projects and biomass raw material transportation routes while meeting the regional electricity load and gas load requirements.

[0007] The technical solution proposed by the present invention is:

[0008] A regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows includes:

[0009] Establish a regional electricity-biogas integrated energy microgrid planning model considering mixed biomass energy flows, and use as input parameters the set parameters of the biogas project nodes to be planned, load demand parameters, the set parameters of the biomass raw material supply points, the set parameters of the pipelines to be planned, the transportation network, and the distribution network structure;

[0010] Generate a start-end matrix and determine the shortest path between the node where the planned anaerobic fermentation plant is located and the biomass raw material supply node to build a biomass raw material supply transportation network;

[0011] A mathematical model is constructed with the total investment and operating cost of the regional integrated energy system as the objective function, and which satisfies the coupling of the regional biogas pipeline network, distribution network, and biomass raw material supply and transportation network.

[0012] Preferably, the generating of the start-end matrix and determining the shortest path between the node where the anaerobic fermentation plant to be planned is located and the biomass raw material supply node to construct the biomass raw material supply transportation network further includes:

[0013] Modeling the physical characteristics and network structure of the distribution network;

[0014] The Weymouth model of natural gas network is used to model the steady-state physical characteristics of the regional biogas network.

[0015] A mixed integer second-order cone programming model was constructed, and the final optimization results were obtained using the commercial solver Cplex.

[0016] Preferably, the set parameters of the nodes to be planned for the biogas project include fermentation type, site selection node and construction scale; fermentation type includes: organic waste fermentation, livestock and poultry manure fermentation and mixed fermentation; the set parameters of the biomass raw material supply point include the annual supply of organic waste and livestock and poultry manure in cities, farms and suburban / rural areas; the load demand parameters include electricity load demand parameters and gas load demand parameters; the set parameters of the pipelines to be planned include pipeline connection node information.

[0017] Preferably, generating a start-end matrix and determining the shortest path between the node where the anaerobic fermentation plant to be planned is located and the biomass raw material supply node to construct a biomass raw material supply transportation network includes:

[0018] Get the number K of anaerobic fermentation plants planned in the regional plan;

[0019] Based on the regional plan, the number of anaerobic fermentation plants K is obtained to obtain the decision variable X representing the construction status of the anaerobic fermentation plant. ncs , and X ncs Satisfy the following constraints:

[0020]

[0021]

[0022]

[0023] If and only if the nth anaerobic fermentation plant is located at node i, any type of biomass transport flow from node j to node i may exist, so the following conditions are met:

[0024]

[0025] Where, BS wcaij is the transportation volume of biomass raw material type a from node i to node j for an anaerobic fermentation plant of construction scale c in scenario w; M is a sufficiently large positive number; CB is the set of candidate nodes for planning anaerobic fermentation plants, and satisfies CB∈NI; Ω j is the set of all candidate equipment located at node j, including distributed gas-fired unit plants, anaerobic fermentation plants, and substations; a is the type of biomass raw materials including livestock and poultry manure and organic waste;

[0026] Among them, the sum of the transport volume of biomass raw material type a from node i where the anaerobic fermentation plant is located to node j is not greater than the corresponding node biomass utilization rate:

[0027]

[0028] Where, BD wai is the maximum supply of biomass feedstock type a at node i in scenario w;

[0029] Calculate the total amount of biomass raw materials collected from node i to node j by the nth anaerobic fermentation plant:

[0030]

[0031] VS typically indicates the amount of biodegradable organic matter that determines methane potential (methane is the primary compound in biogas). While standardized values better represent the actual methane yield from a feedstock, the methane potential expressed for a single feedstock often varies significantly across different humidity levels. In contrast, when expressed on a VS scale, the methane potential of various organic wastes or livestock manures is comparable and unaffected by the relative humidity. Based on the above analysis, the biomass supply is based on the VS standard rather than standardization.

[0032] Where, VS a is the average VS mass fraction of biomass feedstock type a; BF wcna The total mass of VS of biomass raw material type a collected by the nth anaerobic fermentation plant with a construction scale of c in scenario w.

[0033] Preferably, the calculation of the total amount of biomass raw materials collected from the nth anaerobic fermentation plant from node i to node j further includes:

[0034] Introducing the Matrix represents the stable efficiency of the anaerobic fermentation plant, where The vectors assumed in the equation are the stable efficiencies of mixed fermentation, livestock and poultry manure single fermentation, and organic waste single fermentation plants, respectively. The total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is:

[0035]

[0036] Where, is the degradation efficiency matrix of the s-th digestion-type anaerobic fermentation device; η a is the average methane potential per ton of biomass feedstock type a;

[0037] The amount of livestock and poultry manure and organic waste collected in the nth anaerobic fermentation plant is limited by the required mixing ratio, and the mixing ratio satisfies the first condition constraint, wherein the first condition constraint is:

[0038]

[0039]

[0040]

[0041] Where, s1 is the digestion type of mixed fermentation, s2 is the digestion type of single fermentation of livestock and poultry manure, and s3 is the digestion type of single fermentation of organic waste; is the lower limit of the optimal mixing ratio of organic waste and livestock manure, It is the upper limit of the optimal mixing ratio of organic waste and livestock manure.

[0042] Preferably, the amount of livestock and poultry manure and organic waste collected in the nth anaerobic fermentation plant is limited by a required mixing ratio, and the mixing ratio satisfies the following conditional constraints, and then further includes:

[0043] Introducing auxiliary variables To process the variable x ncs With BF wcna The non-convexity caused by the product of is used to reconstruct the calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario. The reconstructed result is:

[0044]

[0045]

[0046]

[0047] Replace the first constraint equivalently with:

[0048]

[0049]

[0050]

[0051]

[0052]

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] Where, DT b is the load partition, b is the subscript of the load partition; f wcns , f2 and f3 are auxiliary variables;

[0059] The calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is subject to the maximum production capacity of the nth anaerobic fermentation plant, and the limiting formula is:

[0060]

[0061] Where λ c Selection of production capacity level for anaerobic fermentation plants;

[0062] Among them, the total biogas production per hour of all preferred anaerobic digestion plants in the region meets the following conditions:

[0063]

[0064] Where PG wbg GD is the gas consumption rate of the distributed gas generator set in scenario w and load partition b; wbi Gas load demand of node i for load partition b in scenario w.

[0065] Preferably, the calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is reconstructed, and then further includes:

[0066] Calculate the transportation cost of any anaerobic fermentation plant in the preset scenario w. The calculation formula is:

[0067]

[0068]

[0069] Where C fix is the fixed cost unit price, C var is the unit price of variable cost; RL ij is the shortest distance between any two points obtained by traversing the road network through the Dijkstra algorithm; FC wcaij is the fixed transportation cost of transporting biomass feedstock type a between any two points in scenario w;

[0070] Based on geographic information, the planning problem is solved by Dijkstra algorithm to generate a start-end matrix, and then determine the shortest distance between the planned anaerobic fermentation plant and the existing biomass raw material supply nodes.

[0071] Preferably, the modeling of the physical characteristics and network structure of the distribution network includes:

[0072] The node active and reactive power flow balance is modeled in the equations:

[0073]

[0074]

[0075] Where PF wbik is the active power flow from node i to node k in scenario w load partition b, QF wbik is the reactive power flow from node i to node k in scenario w load partition b; PE wbg is the active power of the g-th distributed gas generator set in scenario w with load partition b, QE wbg is the reactive power of the g-th distributed gas generator set in load partition b of scenario w; QD wbk is the reactive power of load node k in scenario w load partition b; QS wbm is the reactive power output by substation m in load partition b in scenario w;

[0076] Calculate line network loss:

[0077]

[0078] Where V wbi is the square value of the voltage at node i in scenario w load partition b; X ij is the inductance of the power line between node i and node j, Z ij are the inductance and reactance of the power line between node i and node j; l represents the index of the line, and NL represents the set of lines;

[0079] The relaxation equations related to active flow, reactive flow, voltage amplitude at the sending end, and current amplitude along the straight line are as follows:

[0080]

[0081] Where, I is the voltage amplitude at the sending end;

[0082] Upper and lower limits are set for node voltage, node current, output power of existing and candidate biogas generators and substations respectively. The constraint formula is:

[0083]

[0084]

[0085]

[0086]

[0087] Where V max is the upper limit of the voltage square value, V min is the lower limit of the voltage square value; I min is the lower limit of the current square value, I max is the upper limit of the square value of the current; is the maximum capacity of the substation, is the maximum capacity of the biogas generator.

[0088] Preferably, the Weymouth model of the natural gas network is used to model the steady-state physical characteristics of the regional biogas network, including:

[0089] The power distribution system is coupled to the regional biogas network through a biogas-based generator, and the expression is:

[0090]

[0091] Where, γ is the energy conversion efficiency of the biogas generator;

[0092] Maintain the balance of biogas flow at the node. The expression for maintaining the balance of biogas flow at the node is:

[0093]

[0094] Calculate the square of the pressure level at each node:

[0095]

[0096] Where PG wbg is the biogas consumed by the biogas generator g, GP wbi is the node pressure, GF wbijis the biogas flow rate, GP max is the upper limit of the node pressure, GP min is the lower limit of the node pressure;

[0097] The Weymouth model of the natural gas network is used to model the steady-state physics of the regional biogas network and is marked as the first model. The expression of the first model is:

[0098]

[0099]

[0100] Introduce two auxiliary variables To obtain the equivalent expression of the first model expression:

[0101]

[0102] Preferably, the construction of the mixed integer second-order cone programming model and obtaining the final optimization result through the commercial solver Cplex includes:

[0103] The non-convexity of the equivalent expression of the expression of the first model is further converted into a two-dimensional cone form, wherein the two-dimensional cone form uses the McCormick envelope method as the constraint equation, and the expression of the two-dimensional cone form is:

[0104]

[0105]

[0106]

[0107]

[0108]

[0109] Where A ij It is a characteristic parameter of the pipeline, which is related to temperature, pressure, pipeline diameter, friction coefficient and biogas compressibility coefficient;

[0110] In order to maintain the tree-like structure of the regional biogas pipeline network, the number of pipelines should meet the following conditions:

[0111]

[0112]

[0113]

[0114]

[0115]

[0116] Among them, z ij is the virtual airflow between the pipelines to be planned.

[0117] The above technical solution can achieve the following beneficial effects:

[0118] This paper proposes a regional electricity-biogas integrated energy microgrid planning model that considers mixed biomass energy flows. This model focuses on the optimal mixing ratio requirements of different biomass energy flows due to mixed fermentation technologies, as well as the corresponding impacts on anaerobic fermentation methods, biogas pipeline network structure, the investment and construction of distributed biogas gas generators, and the number, scale, and location of anaerobic fermentation units. This model optimizes the planning of biogas pipeline networks, biogas projects, and biomass feedstock transportation routes while meeting regional electricity and gas load requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0119] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0120] Figure 1 This is a flow chart of the first embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flow proposed by the present invention. DETAILED DESCRIPTION

[0121] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0122] The present invention proposes a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flow.

[0123] As attached Figure 1 As shown, in a first embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flow proposed by the present invention, this embodiment includes the following steps:

[0124] Step S110: Establish a regional electricity-biogas integrated energy microgrid planning model considering mixed biomass energy flow, and use the set parameters of the nodes to be planned for the biogas project, the load demand parameters, the set parameters of the biomass raw material supply points, the set parameters of the pipelines to be planned, the transportation network and the distribution network structure as input parameters of the planning model.

[0125] Step S120: Generate a start-end matrix and determine the shortest path between the node where the anaerobic fermentation plant to be planned is located and the biomass raw material supply node to construct a biomass raw material supply transportation network.

[0126] Step S130: Construct a mathematical model that takes the total investment and operating cost of the regional integrated energy system as the objective function and satisfies the coupling of the regional biogas pipeline network, the distribution network, and the biomass raw material supply and transportation network.

[0127] This paper proposes a regional electricity-biogas integrated energy microgrid planning model that considers mixed biomass energy flows. This model focuses on the optimal mixing ratio requirements of different biomass energy flows due to mixed fermentation technologies, as well as the corresponding impacts on anaerobic fermentation methods, biogas pipeline network structure, the investment and construction of distributed biogas gas generators, and the number, scale, and location of anaerobic fermentation units. This model optimizes the planning of biogas pipeline networks, biogas projects, and biomass feedstock transportation routes while meeting regional electricity and gas load requirements.

[0128] In a second embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the first embodiment, step S120 further includes the following steps:

[0129] Step S140: Modeling the physical characteristics and network structure of the distribution network.

[0130] Step S150: using the Weymouth model of the natural gas network to model the steady-state physical characteristics of the regional biogas pipeline network.

[0131] Specifically, the Weymouth model here is the Weymouth equation.

[0132] Step S160: construct a mixed integer second-order cone programming model and obtain the final optimization result through the solver Cplex.

[0133] In addition, the biomass-based regional integrated energy system planning model proposed in the present invention takes into account the available biomass energy supply at different nodes, the energy demand of each node, the candidate locations and technical characteristics of the power generation system, and the layout of the existing power grid. While meeting the regional electricity load and gas load demands, it can minimize the total investment and operating costs of the regional integrated energy system and improve economic benefits by optimizing the planning of regional biogas networks, facilities and biomass transportation routes.

[0134] In a third embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed in the present invention, based on the first embodiment, the set parameters of the nodes to be planned for the biogas project include fermentation type, site selection node and construction scale; the fermentation types include: organic waste fermentation, livestock manure fermentation and mixed fermentation; the set parameters of the biomass raw material supply point include each network node, that is, the biomass collection area, specifically including the annual supply of organic waste and livestock manure in cities, farms and suburban / rural areas; the load demand parameters include electricity load demand parameters and gas load demand parameters, specifically including each network node, that is, the hourly electricity and gas load demand information of cities, farms and suburban / rural areas where residents have basic energy needs for biogas load and electricity load; the set parameters of the pipeline to be planned include pipeline connection node information.

[0135] In a fourth embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flow proposed by the present invention, based on the second embodiment, in step S130, the calculation formula of the mathematical model is:

[0136]

[0137] Where α is the annualized investment cost weight; IC is the total investment cost; p w is the probability distribution of random scene w; OC w is the operating cost in scenario w; TC w is the transportation cost in scenario w; w is the scenario index;

[0138] Specifically, the annualized investment cost refers to the installation of biogas generator sets, pipelines, and anaerobic digestion power plants. The total investment cost IC is calculated as follows:

[0139]

[0140] Where x ncs is the construction status of the nth anaerobic fermentation plant with a construction scale of c and the sth fermentation type being anaerobic fermentation. If x ncs =1, indicating investment and construction, if x ncs =0, it means that it has not been built; x g is the construction status of biogas generator g, if x g =1, indicating investment and construction, if x g =0, it means no construction has been completed; x p is the construction status of biogas pipeline p, if x p =1, indicating investment and construction, if x p =0, it means no construction has been started; is the investment price for building an anaerobic fermentation plant of scale c; The investment cost of biogas generator g, is the investment cost of the biogas pipeline p; s∈NS is the index and alternative set of anaerobic fermentation types, n∈NN is the subscript and set of alternative anaerobic fermentation plants; c∈NC is the subscript and set of construction scale of alternative anaerobic fermentation plants; g∈NG is the subscript and set of alternative biogas generators; p∈NP is the subscript and set of alternative biogas pipelines;

[0141] Among them, operating costs OC w The calculation formula is:

[0142]

[0143] Where BG wbn is the gas production of the nth anaerobic fermentation plant in scenario w when in load partition b in scenario w; is the unit price of operating cost per cubic kilometer of biogas produced by an anaerobic fermentation plant of scale c; sub The price of electricity purchased from the main grid, OC loss is the network loss price, I wbij is the square value of the current from node i to node j; PS wbm is the active power capacity purchased by substation m in load partition b from the main grid in scenario w; R ij is the resistance value of the electric load line from node i to node j; i and j are node indexes; NI is the node set; m∈NM is the index and set of substations, DT b Represents the load partition, and b is the subscript of the load partition.

[0144] Specifically, due to different economies of scale, investment and operating prices will vary with the capacity level of the anaerobic digestion plant. Since this target already takes into account the supply costs of electricity and gas loads, the fuel costs of biogas-based generators are implicitly included in the operating costs of the anaerobic digestion plant.

[0145] Among them, the transportation cost TC in scenario w w The calculation formula is:

[0146]

[0147] Where, BTC wn is the raw material transportation cost of the nth anaerobic fermentation unit under scenario w.

[0148] Specifically, the total transportation cost in each scenario is the sum of the transportation costs of each anaerobic fermentation plant.

[0149] The mathematical model must satisfy the following requirements:

[0150]

[0151] The above formula represents the maximum total capacity of generators and substations that can supply the predicted regional peak load demand and system reserves, where: is the maximum active output of the substation, is the maximum active output of the generator; PD wbi Predict active power for node i; RE bw is the system spinning reserve capacity; b is the load partition index.

[0152] In a fifth embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the third embodiment, step S120 includes the following steps:

[0153] Step S410: Obtain the number K of anaerobic fermentation plants planned in the region.

[0154] Specifically, biomass raw materials are spatially dispersed and have low calorific value density, resulting in high transportation costs. Proper planning of the site selection for anaerobic fermentation plants is key to maintaining their sustainable and stable operation.

[0155] Step S420: Based on the regional plan, the number of anaerobic fermentation plants K is planned to obtain the decision variable X representing the construction status of the anaerobic fermentation plants. ncs , and X ncs Satisfy the following constraints:

[0156]

[0157] In the above formula, K represents the total number of anaerobic fermentation plants to be built. If K=1, it means that only one anaerobic fermentation plant is to be built in the area.

[0158]

[0159] Specifically, the above formula restricts any node from being able to have more than one anaerobic digestion plant. This also restricts an anaerobic digestion plant to only one capacity and one digestion type, which is constrained by the following formula:

[0160]

[0161] Once the indicator x is determined ncs The installation location and capacity of the associated anaerobic fermentation plant, and the transportation route of biomass raw materials vary with the location and scale of the anaerobic fermentation plant; when x ncs =0, in any case, biomass raw materials cannot be transported from any other node to the nth anaerobic fermentation plant; that is, if and only if the nth anaerobic fermentation plant is located at node i, any type of biomass transport flow from node j to node i may exist, so it satisfies:

[0162]

[0163] In the formula, the above formula is marked as the first formula; BS wcaij is the transportation volume of biomass raw material type a from node i to node j for an anaerobic fermentation plant of construction scale c in scenario w; M is a sufficiently large positive number; CB is the set of candidate nodes for planning anaerobic fermentation plants, and satisfies CB∈NI; Ω j is the set of all alternative equipment located at node j, including distributed gas unit plants, anaerobic fermentation plants and substations, etc.; a is the type of biomass raw materials including livestock and poultry manure and organic waste.

[0164] Among them, due to the limitation of the maximum biomass utilization rate, the sum of the transportation volume of biomass raw material type a from node i where the anaerobic fermentation plant is located to node j is not greater than the corresponding node biomass utilization rate:

[0165]

[0166] Where, BD wai is the maximum supply of biomass feedstock type a at node i in scenario w.

[0167] Step S430: Calculate the total amount of biomass raw materials collected by the nth anaerobic fermentation plant from node i to node j:

[0168]

[0169] Specifically, VS typically indicates the amount of biodegradable organic matter that determines the methane potential (methane is the primary compound in biogas). While standardized values better represent the actual methane yield from a feedstock, the methane potential expressed for a single feedstock often varies significantly across different humidity levels. In contrast, when expressed using the VS standard, the methane potential of various organic wastes or livestock manures is comparable and unaffected by the relative humidity. Based on the above analysis, the biomass supply is based on the VS standard rather than standardization.

[0170] Where, VS a is the average VS mass fraction of biomass feedstock type a; BF wcna The total mass of VS of biomass raw material type a collected by the nth anaerobic fermentation plant with a construction scale of c in scenario w.

[0171] In a sixth embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the fifth embodiment, step S430 further includes the following steps:

[0172] Step S510: Introducing the matrix represents the stable efficiency of the anaerobic fermentation plant, where The vectors assumed in the equation are the stable efficiencies of mixed fermentation (AcoD), livestock and poultry manure single fermentation (AmoD-AM), and organic waste single fermentation (AmoD-FW) plants, respectively. The total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is:

[0173]

[0174] Specifically, since organic matter has better stabilization efficiency in mixed fermentation systems than in single fermentation systems in terms of process stability, nutrient balance, toxicity dilution, microbial flora, and ecological sustainability, the stabilization efficiency must vary with the fermentation type of the anaerobic fermentation plant.

[0175] Where, is the degradation efficiency matrix of the s-th digestion-type anaerobic fermentation device; η a is the average methane potential per ton of biomass feedstock type a;

[0176] Step S520: The amount of livestock and poultry manure and organic waste collected from the nth anaerobic fermentation plant is limited by the required mixing ratio, and the mixing ratio satisfies a first condition constraint, wherein the first condition constraint is:

[0177]

[0178]

[0179]

[0180] Specifically, anaerobic digestion is a time-consuming process compared to energy scheduling. However, most commercial anaerobic digestion plants are equipped with feedstock warehouses to store excess feedstock as a backup, so the uncertainty of biomass availability can be estimated annually. Furthermore, the amount of biomass feedstock collected at the nth anaerobic digestion plant does not necessarily have to exactly match the biogas produced hourly.

[0181] Where s1 is the digestion type of mixed fermentation (AcoD), s2 is the digestion type of livestock and poultry manure single fermentation (AmoD-AM), and s3 is the digestion type of organic waste single fermentation (AmoD-FW). ncs = 0 is included in the first formula; θminAM·FW is the lower limit of the optimal mixing ratio (VS quality) of organic waste and livestock manure, It is the upper limit of the optimal mixing ratio of organic waste and livestock manure.

[0182] In a seventh embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the sixth embodiment, step S520 further includes the following steps:

[0183] Step S610: Since the first constraint condition cannot be solved directly by a commercial solver, an auxiliary variable is introduced To process the variable x ncs With BF wcna The non-convexity caused by the product of is used to reconstruct the calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario. The reconstructed result is:

[0184]

[0185]

[0186]

[0187] Replace the first constraint equivalently with:

[0188]

[0189]

[0190]

[0191]

[0192] Specifically, the non-convexity inequality in the above formula is relaxed in the following formula:

[0193]

[0194]

[0195]

[0196]

[0197]

[0198]

[0199] Where, DT b is the load partition, b is the subscript of the load partition; f wcns , f2 and f3 are auxiliary variables;

[0200] The calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is subject to the maximum production capacity of the nth anaerobic fermentation plant, and the limiting formula is:

[0201]

[0202] Where λ c Selection of production capacity level for anaerobic fermentation plants;

[0203] Among them, based on energy loss, the total biogas production per hour of all preferred anaerobic fermentation plants in the region meets the following conditions:

[0204]

[0205] Specifically, the total biogas production per hour of all preferred anaerobic digestion plants in the area should be equal to the total biogas consumption in the above formula.

[0206] Where PG wbg GD is the gas consumption rate of the distributed gas generator set in scenario w and load partition b; wbi Gas load demand of node i for load partition b in scenario w.

[0207] In an eighth embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the seventh embodiment, step S610 further includes the following steps:

[0208] Step S710: Calculate the transportation cost of any anaerobic fermentation plant in the preset scenario w. The calculation formula is:

[0209]

[0210] Specifically, the above formula is marked as the second formula.

[0211]

[0212] Specifically, the total transportation cost includes: 1. a variable cost of distance that is proportional to the amount of biomass raw materials transported; 2. a fixed cost that is independent of the transportation distance and is usually related to the loading and uploading of raw materials, as shown in the second formula; once a biomass transportation route exists between two nodes, the cost remains fixed.

[0213] Where C fix is the fixed cost unit price, C var is the unit price of variable cost; RL ij is the shortest distance between any two points obtained by traversing the road network through the Dijkstra algorithm; FC wcaij is the fixed transportation cost of transporting biomass feedstock type a between any two points in scenario w.

[0214] Step S720: Based on the geographic information, the planning problem is solved by using the Dijkstra algorithm to generate a start-end matrix, thereby determining the shortest distance between the anaerobic fermentation plant to be planned and the existing biomass raw material supply nodes.

[0215] In a ninth embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the eighth embodiment, step S140 includes the following steps:

[0216] Step S710: Model the node active and reactive power flow balance in the equation:

[0217]

[0218]

[0219] Specifically, the above two formulas adopt a convex branch flow model.

[0220] Where PF wbik is the active power flow from node i to node k in scenario w load partition b, QF wbik is the reactive power flow from node i to node k in scenario w load partition b; PE wbg is the active power of the g-th distributed gas generator set in scenario w with load partition b, QE wbg is the reactive power of the g-th distributed gas generator set in load partition b of scenario w; QD wbk is the reactive power of load node k in scenario w load partition b; QS wbm is the reactive power output by substation m in load partition b in scenario w;

[0221] Step S720: Calculate line network loss:

[0222]

[0223] Where V wbi is the square value of the voltage at node i in scenario w load partition b; X ij is the inductance of the power line between node i and node j, Z ij are the inductance and reactance of the power line between node i and node j; l represents the index of the line, and NL represents the set of lines;

[0224] The relaxation equations related to active flow, reactive flow, voltage amplitude at the sending end, and current amplitude along the straight line are as follows:

[0225]

[0226] Where, I is the voltage amplitude at the sending end;

[0227] Step S730: Set upper and lower limit constraints on the node voltage, node current, output power of existing and candidate biogas generators and substations respectively. The constraint formula is:

[0228]

[0229]

[0230]

[0231]

[0232] Where V max is the upper limit of the voltage square value, V min is the lower limit of the voltage square value; I min is the lower limit of the current square value, I max is the upper limit of the square value of the current; is the maximum capacity of the substation, is the maximum capacity of the biogas generator.

[0233] In a tenth embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the ninth embodiment, step S150 includes the following steps:

[0234] Step S910: Coupling the power distribution system with the regional biogas network through a biogas-based generator, as expressed by:

[0235]

[0236] Where, γ is the energy conversion efficiency of the biogas generator.

[0237] Step S920: Maintaining node biogas flow balance, wherein the biogas inflow from the adjacent sending node i to the node k is equal to the sum of the biogas outflow from the node k to the receiving node j.

[0238]

[0239] Specifically, the above formula indicates whether there is biogas flowing along the candidate pipeline, which depends on the installation status of the pipeline.

[0240] Among them, the expression for maintaining the balance of node biogas flow is:

[0241]

[0242] Step S930: Calculate the square of the pressure level of each node:

[0243]

[0244] Where PG wbg is the biogas consumed by the biogas generator g, GP wbi is the node pressure, GF wbij is the biogas flow rate, GP max is the upper limit of the node pressure, GP min is the lower limit of the node pressure.

[0245] Step S940: Since biogas and natural gas share common physical properties, the Weymouth model of the natural gas network is used to model the steady-state physics of the regional biogas network, and is marked as the first model. Since the flow direction of the biogas is not pre-specified before the candidate pipeline is installed, the Weymouth model is used as a steady-state abstraction of the differential equation together with a set of nonlinear functions of the biogas flow rate and node pressure. The expression of the first model is:

[0246]

[0247]

[0248] Step S950: The sign function representing the flow direction is nonlinear, making the model difficult to solve. Therefore, two auxiliary variables are introduced To obtain the equivalent expression of the first model expression:

[0249]

[0250] In an eleventh embodiment of a regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows proposed by the present invention, based on the tenth embodiment, step S160 includes the following steps:

[0251] Step S1010: The non-convexity of the equivalent expression of the expression of the first model is further converted into a two-dimensional cone form, wherein the two-dimensional cone form uses the McCormick envelope method as a constraint equation, and the expression of the two-dimensional cone form is:

[0252]

[0253]

[0254]

[0255]

[0256]

[0257] Where A ijIt is a characteristic parameter of the pipeline, which is related to temperature, pressure, pipeline diameter, friction coefficient and biogas compressibility coefficient;

[0258] Specifically, compared to traditional natural gas pipelines, the transmission distance is shorter and the energy demand is lower. The topology of the regional biogas pipeline network is tree-like. To maintain the tree-like structure of the regional biogas pipeline network, the number of pipelines should meet the following conditions:

[0259]

[0260]

[0261] Specifically, when node i is a candidate node for installing an anaerobic digestion power plant, y i In the above formula, it is equal to 1, thereby ensuring that the total amount of biogas outflow is not equal to the total amount of biogas inflow, so as to ensure that the node where the candidate anaerobic fermentation plant is located will not be isolated from other nodes.

[0262]

[0263]

[0264]

[0265] Specifically, since the anaerobic digestion plant can independently meet the node demand without any inflow or outflow of biogas, the above formula is used to prevent the preferred anaerobic digestion plant from being isolated from the rest of the regional biogas network.

[0266] Among them, z ij is the virtual airflow between the pipelines to be planned.

[0267] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0268] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0269] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A regional electricity-biogas integrated energy microgrid planning method considering mixed biomass energy flows, characterized by: include: Establish a regional electricity-biogas integrated energy microgrid planning model considering mixed biomass energy flows, and use as input parameters the set parameters of the biogas project nodes to be planned, load demand parameters, the set parameters of the biomass raw material supply points, the set parameters of the pipelines to be planned, the transportation network, and the distribution network structure; Generate a start-end matrix and determine the shortest path between the node where the planned anaerobic fermentation plant is located and the biomass raw material supply node to build a biomass raw material supply transportation network; Construct a mathematical model that takes the total investment and operating costs of the regional integrated energy system as the objective function and satisfies the coupling of the regional biogas pipeline network, distribution network, and biomass raw material supply and transportation network; The process of generating a start-end matrix and determining the shortest path between the node where the anaerobic fermentation plant to be planned is located and the biomass raw material supply node to construct a biomass raw material supply transportation network further includes: Modeling the physical characteristics and network structure of the distribution network; The Weymouth model of natural gas network is used to model the steady-state physical characteristics of the regional biogas network. A mixed integer second-order cone programming model was constructed, and the final optimization results of the regional biogas pipeline network, distribution network, and biomass raw material supply network were obtained through the Cplex solver. The set of parameters for the nodes to be planned for the biogas project include fermentation type, site selection node, and construction scale; fermentation types include: organic waste fermentation, livestock manure fermentation, and mixed fermentation; the set of parameters for biomass raw material supply points includes the annual supply of organic waste and livestock manure in cities, farms, and suburban / rural areas; the load demand parameters include the electricity load demand parameters and the gas load demand parameters; the set of parameters for the pipelines to be planned includes pipeline connection node information; The generating of the start-end matrix and determining the shortest path between the node where the anaerobic fermentation plant to be planned is located and the biomass raw material supply node to construct the biomass raw material supply transportation network includes: Get the number K of anaerobic fermentation plants planned in the regional plan; Based on the regional plan, the number of anaerobic fermentation plants K is obtained to obtain the decision variable X representing the construction status of the anaerobic fermentation plant. ncs , and X ncs Satisfy the following constraints: ， ， ， If and only if the nth anaerobic fermentation plant is located at node i, any type of biomass transport flow from node j to node i may exist, so the following conditions are met: ， Where, BS wcaij is the transportation volume of biomass raw material type a from node i to node j for an anaerobic fermentation plant of construction scale c in scenario w; M is a sufficiently large positive number; CB is the set of candidate nodes for planning anaerobic fermentation plants, and CB∈NI; is the set of all candidate equipment located at node j, including distributed gas-fired unit plants, anaerobic fermentation plants, and substations; a is the type of biomass raw materials including livestock and poultry manure and organic waste; Among them, the sum of the transport volume of biomass raw material type a from node i where the anaerobic fermentation plant is located to node j is not greater than the corresponding node biomass utilization rate: Where, BD wai is the maximum supply of biomass feedstock type a at node i in scenario w; Calculate the total amount of biomass raw materials collected from node i to node j by the nth anaerobic fermentation plant: ， Where, VS a is the average VS mass fraction of biomass feedstock type a; BF wcna is the total mass of VS of biomass feedstock type a collected by the nth anaerobic fermentation plant with a construction scale of c in scenario w; The calculation of the total amount of biomass raw materials collected by the nth anaerobic fermentation plant from node i to node j further includes: Introducing the Matrix represents the stable efficiency of anaerobic fermentation plants, where The vectors assumed in the equation are the stable efficiencies of mixed fermentation, livestock and poultry manure single fermentation, and organic waste single fermentation plants, respectively. The total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is: ， Where, is the degradation efficiency matrix of the sth digestion type anaerobic fermentation device; ηa is the average methane potential per ton of biomass raw material type a; The amount of livestock and poultry manure and organic waste collected at the nth anaerobic fermentation plant is limited by the required mixing ratio, and the mixing ratio satisfies the first condition constraint, wherein the first condition constraint is: ， ， ， Where, s1 is the digestion type of mixed fermentation, s2 is the digestion type of single fermentation of livestock and poultry manure, and s3 is the digestion type of single fermentation of organic waste; is the lower limit of the optimal mixing ratio of organic waste and livestock manure, It is the upper limit of the optimal mixing ratio of organic waste and livestock manure.

2. A method for planning a regional electricity-biogas integrated energy microgrid considering mixed biomass energy flow according to claim 1, characterized in that: The amount of livestock and poultry manure and organic waste collected in the nth anaerobic fermentation plant is limited by the required mixing ratio, and the mixing ratio satisfies the first condition constraint, and then further includes: Introducing auxiliary variables To process variables and The non-convexity caused by the product of is used to reconstruct the calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario. The reconstructed result is: ， ， ， Replace the first constraint equivalently with: ， ， ， ， ， ， ， ， ， ， Where DT b is the load partition, b is the subscript of the load partition; 、 and All are auxiliary variables; The calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is subject to the maximum production capacity of the nth anaerobic fermentation plant, and the limiting formula is: ， Where, Selection of production capacity level for anaerobic fermentation plants; Among them, the total biogas production per hour of all preferred anaerobic digestion plants in the region meets the following conditions: ， Where PG wbg GD is the gas consumption rate of the distributed gas generator set in scenario w and load partition b; wbi Gas load demand of node i for load partition b in scenario w.

3. A method for planning a regional electricity-biogas integrated energy microgrid considering mixed biomass energy flows according to claim 2, characterized in that: The calculation formula for the total amount of biogas produced annually by the nth anaerobic fermentation plant under each scenario is reconstructed, and then further includes: Calculate the transportation cost of any anaerobic fermentation plant in the preset scenario w. The calculation formula is: ， ， Where C fix is the fixed cost unit price, C var is the unit price of variable cost; RL ij is the shortest distance between any two points obtained by traversing the road network through the Dijkstra algorithm; FC wcaij is the fixed transportation cost of transporting biomass feedstock type a between any two points in scenario w; Based on geographic information, the planning problem is solved by Dijkstra algorithm to generate a start-end matrix, and then determine the shortest distance between the planned anaerobic fermentation plant and the existing biomass raw material supply nodes.

4. A method for planning a regional electricity-biogas integrated energy microgrid considering mixed biomass energy flows according to claim 3, characterized in that: The modeling of the physical characteristics and network structure of the distribution network includes: The node active and reactive power flow balance is modeled in the equations: ， ， Where PF wbik is the active power flow from node i to node k in scenario w load partition b, QF wbik is the reactive power flow from node i to node k in scenario w load partition b; PE wbg is the active power of the g-th distributed gas generator set in scenario w with load partition b, QE wbg is the reactive power of the g-th distributed gas generator set in load partition b of scenario w; QD wbk is the reactive power of load node k in scenario w load partition b; QS wbm is the reactive power output by substation m in load partition b in scenario w; Calculate line network loss: ， Where V wbi is the square value of the voltage at node i in scenario w load partition b; X ij is the inductance of the power line between node i and node j, Z ij are the inductance and reactance of the power line between node i and node j; l represents the index of the line, and NL represents the set of lines; The relaxation equations related to active flow, reactive flow, voltage amplitude at the sending end, and current amplitude along the straight line are as follows: ， Where, I is the voltage amplitude at the sending end; Upper and lower limits are set for node voltage, node current, output power of existing and candidate biogas generators and substations respectively. The constraint formula is: ， ， ， ， Where V max is the upper limit of the voltage square value, V min is the lower limit of the voltage square value; I min is the lower limit of the current square value, I max is the upper limit of the square value of the current; is the maximum capacity of the substation, is the maximum capacity of the biogas generator.

5. A method for planning a regional electricity-biogas integrated energy microgrid considering mixed biomass energy flow according to claim 4, characterized in that: The Weymouth model of the natural gas network is used to model the steady-state physical characteristics of the regional biogas network, including: The power distribution system is coupled to the regional biogas network through a biogas-based generator, and the expression is: ， Where, The energy conversion efficiency of the biogas generator; Maintain the balance of biogas flow at the node. The expression for maintaining the balance of biogas flow at the node is: ， Calculate the square of the pressure level at each node: ， Where, is the biogas consumed by the biogas generator g, is the node pressure, is the biogas flow rate, is the upper limit of the node pressure, is the lower limit of the node pressure; The Weymouth model of the natural gas network is used to model the steady-state physics of the regional biogas network and is marked as the first model. The expression of the first model is: ， ， Introduce two auxiliary variables , , to obtain the equivalent expression of the expression of the first model: ， ， 。 6. A method for planning a regional electricity-biogas integrated energy microgrid considering mixed biomass energy flows according to claim 5, characterized in that: The mixed integer second-order cone programming model is constructed and the final optimization results are obtained using the commercial solver Cplex, including: The non-convexity of the equivalent expression of the expression of the first model is further converted into a two-dimensional cone form, wherein the two-dimensional cone form uses the McCormick envelope method as the constraint equation, and the expression of the two-dimensional cone form is: ， ， ， ， ， Where A ij It is a characteristic parameter of the pipeline, which is related to temperature, pressure, pipeline diameter, friction coefficient and biogas compressibility coefficient; In order to maintain the tree-like structure of the regional biogas pipeline network, the number of pipelines should meet the following conditions: ， ， ， ， ， Among them, z ij is the virtual airflow between the pipelines to be planned.

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