A comprehensive energy optimization method for all aspects of low-carbon farms

Abstract

The present invention relates to a comprehensive energy optimization method for all aspects of a low-carbon farm, comprising the following steps: step S1: constructing a low-carbon farm comprehensive energy system structure, including a farm energy conversion center, a comprehensive energy distribution network, and a farm multi-energy load; step S2: constructing a low-carbon farm comprehensive energy system model based on the low-carbon farm comprehensive energy system structure; step S3: based on the low-carbon farm comprehensive energy system model, obtaining an optimized scheduling plan with the goal of minimizing the farm operation energy consumption. The present invention saves heating energy loss to the maximum extent, achieves the low-carbon goal of a low-carbon farm, and further improves the utilization efficiency of farm energy.

Description

Technical Field

[0001] The present invention relates to the field of optimization and scheduling of integrated energy systems, and in particular to a method for optimizing the overall energy supply of a low-carbon farm. Background Art

[0002] Under the background of dual carbon goals, my country's energy system is at a critical juncture of green and low-carbon transformation. The integrated energy system can achieve complementary advantages among different energy sources, thereby improving energy utilization efficiency. In-depth research has been conducted on the optimal scheduling of urban integrated energy systems. However, there is little research on the optimal scheduling of low-carbon farm integrated energy systems. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a comprehensive energy optimization method for all aspects of a low-carbon farm, to save heating energy loss to the maximum extent, to achieve the low-carbon goal of the low-carbon farm, and thus to improve the energy utilization efficiency of the farm.

[0004] To achieve the above object, the present invention adopts the following technical solution:

[0005] A comprehensive energy optimization method for all aspects of a low-carbon farm comprises the following steps:

[0006] Step S1: construct a low-carbon farm integrated energy system structure, including a farm energy conversion center, an integrated energy distribution network, and a farm multi-energy load;

[0007] Step S2: constructing a low-carbon farm comprehensive energy system model based on the low-carbon farm comprehensive energy system structure;

[0008] Step S3: Based on the low-carbon farm integrated energy system model, with the goal of minimizing the farm operation energy consumption, obtain an optimized scheduling plan.

[0009] Furthermore, the energy conversion center of the farm mainly includes a transformer, CHP, a heat pump and a biogas treatment unit; the electrical energy and thermal energy produced by the energy conversion center of the farm are transmitted to the livestock houses of the farm through an integrated energy distribution network.

[0010] Furthermore, the step S2 is specifically as follows:

[0011] Step S21: Establishing a mathematical model of energy production and conversion unit of a low-carbon farm;

[0012] Step S22: mathematically modeling the power distribution system of the low-carbon farm;

[0013] Step S23: Based on the principle of piecewise linearization, a low-carbon farm heat network model is constructed.

[0014] Furthermore, the step S21 specifically includes: mathematically describing the power consumption associated with the biogas treatment process and the power output of other energy conversion units.

[0015] The electricity consumption associated with the biogas treatment process is expressed as:

[0016] P t biogas =η b P t g (1)

[0017] Where P t g is the biogas power produced by the biogas treatment unit during period t; P t biogas The electric power consumed in the biogas treatment process; η b is the electricity consumption coefficient during biogas treatment.

[0018] The power output constraints of other energy conversion units are:

[0019] P t chp =η e P t g (2)

[0020]

[0021]

[0022] 0≤P t e ≤P e,max (5)

[0023] 0≤P t g ≤P g,max (6)

[0024] 0≤P t hp ≤P hp,max (7)

[0025] Where η e is the gas-to-electricity efficiency of CHP; η h is the gas-to-heat efficiency of CHP; P t hp The electrical power consumed by the heat pump; is the thermal power output of the heat pump; η hp P is the heat pump's electricity-to-heat efficiency; t e P is the electric power purchased by the farm from the upper distribution network; e,maxP is the upper limit of the electric power purchased by the farm from the upper distribution network; g,max P is the upper limit of the gas power input from the biogas processing unit to the CHP (i.e. the upper limit of the maximum gas power output of the biogas processing unit); hp,max This is the upper limit of the heat pump output.

[0026] Furthermore, the step S22 is specifically as follows: modeling the power distribution system based on the Distflow model, and linearizing the square terms in the power flow constraints of the distribution network.

[0027] as follows Fig. 9 As shown, j is the sending end and j+1 is the receiving end. j +iQ j is the complex power of node j; is the complex power of the load carried by node (j+1); r f +ix f is the complex impedance of the line from node j to node j+1. V j is the voltage at node j, and the power flow at each node is expressed as follows:

[0028]

[0029]

[0030]

[0031] 1-ε≤V j ≤1+ε (11)

[0032] The square term in the power flow constraint of the distribution network is linearized, and the linearized power flow constraint is as follows:

[0033]

[0034]

[0035]

[0036] Furthermore, the step S23 uses a piecewise linearization method to linearize the node pressure equation, converting the nonlinear constraints of the heat network into linear constraints;

[0037]

[0038]

[0039]

[0040] In the formula, p n,t is the pressure of node n at time t; represents the pipeline characteristics, κ l , L l and dl are the friction coefficient, length and inner diameter of the pipe l respectively; ρ is the density of water; Equal to in numerical terms Is a 0-1 variable, used to represent Whether the value of is in the qth segment.

[0041] Furthermore, the construction of the low-carbon farm heat network model is as follows:

[0042] The thermal resistance-heat capacity network model is used to mathematically model the wall thermal dynamic model and indoor thermal dynamic model of the pig house, and a low-carbon farm thermal network model is based on the constant water supply temperature of each livestock house;

[0043]

[0044]

[0045] In the formula, r 1,2 、r 1,3 、r 1,4 、r 1,5 The value is 1 when the wall is exposed to sunlight, otherwise it is 0; α 1,2 , α 1,3 , α 1,4 , α 1,5 and Aw 1,2 , Aw 1,3 , Aw 1,4 , Aw 1,5 Respectively represent the heat absorption rate and surface area of ​​the four walls; Cr 1 is the equivalent heat capacity of the indoor air in the pig house; Indicates the heat dissipation of the radiator in the pig house; represents the internal heat generated by livestock activities and metabolism in the pig house; there is a window on the wall between the pig house and node i, and the outdoor light intensity obtained through the window is A win is the window area, τ win is the window transmittance.

[0046] Furthermore, step S3 is specifically as follows: taking the lowest energy consumption of the farm as the optimization scheduling target, considering the operation constraints of each link of source-grid-load in the comprehensive energy system of the farm, and solving the low-carbon farm heat network model through the CPLEX solver based on the MATLAB-YALMIP platform.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] The present invention can save heating energy loss to the maximum extent, achieve the low-carbon goal of the low-carbon farm, and further improve the energy utilization efficiency of the farm. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The structure of the integrated energy system of a farm according to an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of solar radiation intensity and outdoor temperature according to an embodiment of the present invention;

[0051] Figure 3 A schematic diagram of electricity prices according to an embodiment of the present invention;

[0052] Figure 4 A schematic diagram of the electrical load and indoor heat gain of each pig house in an embodiment of the present invention;

[0053] Figure 5 This is a schematic diagram of the amount of electricity purchased and the amount of biogas used by a farm after optimized scheduling according to an embodiment of the present invention;

[0054] Figure 6 It is an energy optimization scheduling scheme for the integrated energy system of a farm according to an embodiment of the present invention;

[0055] Figure 7 This is a schematic diagram of the temperature in the pig house and the radiator flow rate of the comparison group of the embodiment of the present invention;

[0056] Figure 8 Schematic diagram of the temperature inside a pig house in two scenarios of an embodiment of the present invention;

[0057] Fig. 9 Schematic diagram of a linearization circuit in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0059] Please refer to Figure 1 The present invention provides a comprehensive energy optimization method for the "source-grid-load" of a low-carbon farm, comprising the following steps:

[0060] Step S1: constructing a low-carbon farm integrated energy system structure;

[0061] Step S2: constructing a low-carbon farm comprehensive energy system model; including constructing a mathematical model of the energy production and conversion unit of the low-carbon farm, a mathematical model of the power distribution system, a mathematical model of the heat network, and a mathematical model of the livestock house;

[0062] Step S3: With the goal of minimizing the energy consumption of farm operations, a low-carbon farm integrated energy system optimization scheduling model is constructed.

[0063] In this embodiment, the low-carbon farm integrated energy system structure mainly includes the farm energy conversion center, the integrated energy distribution network and the farm multi-energy load. The farm energy conversion center mainly includes a transformer, CHP, a heat pump and a biogas treatment unit. The electricity and heat energy produced by the energy conversion center are transmitted to the livestock house of the farm through the integrated energy distribution network to meet the electricity and heat load requirements of the livestock.

[0064] In this embodiment, step S2 is specifically:

[0065] Step S21: Establishing a mathematical model of energy production and conversion unit of a low-carbon farm;

[0066] Preferably, the specific description is a mathematical description of the power consumption accompanying the biogas treatment process and the power output of other energy conversion units;

[0067] The electricity consumption associated with the biogas treatment process can be expressed as:

[0068] P t biogas =η b P t g (1)

[0069] Where P t g is the biogas power produced by the biogas treatment unit during period t; P t biogas The electric power consumed in the biogas treatment process; η b is the electricity consumption coefficient during biogas treatment.

[0070] The power output constraints of other energy conversion units are:

[0071] P t chp =η e P t g (2)

[0072]

[0073]

[0074] 0≤P t e ≤P e,max (5)

[0075] 0≤P t g ≤P g,max (6)

[0076] 0≤Pt hp ≤P hp,max (7)

[0077] Where η e is the gas-to-electricity efficiency of CHP; η h is the gas-to-heat efficiency of CHP; P t hp The electrical power consumed by the heat pump; is the thermal power output of the heat pump; η hp P is the heat pump's electricity-to-heat efficiency; t e P is the electric power purchased by the farm from the upper distribution network; e,max P is the upper limit of the electric power purchased by the farm from the upper distribution network; g,max P is the upper limit of the gas power input from the biogas processing unit to the CHP (i.e. the upper limit of the maximum gas power output of the biogas processing unit); hp,max This is the upper limit of the heat pump output.

[0078] Step S22: mathematically modeling the power distribution system of the low-carbon farm;

[0079] Preferably, in this embodiment, the distribution system is modeled based on the Distflow model, and in order to improve the solution efficiency, the square terms in the power flow constraints of the distribution network are linearized in this paper.

[0080] as follows Fig. 9 As shown, j is the sending end and j+1 is the receiving end. j +iQ j is the complex power of node j; is the complex power of the load carried by node (j+1); r f +ix f is the complex impedance of the line from node j to node j+1. V j is the voltage at node j, and the power flow at each node is expressed as follows:

[0081]

[0082]

[0083]

[0084] 1-ε≤V j ≤1+ε (11)

[0085] The square term in the power flow constraint of the distribution network is linearized, and the linearized power flow constraint is as follows:

[0086]

[0087]

[0088]

[0089] Step S23: Based on the principle of piecewise linearization, a low-carbon farm heat network model is constructed.

[0090] Since the secondary heating network in low-carbon farms is small in scale and short in distance, only the hydraulic model of the secondary heating network needs to be considered. This paper chooses to use the piecewise linearization method to linearize the node pressure equation and convert the nonlinear constraints of the heating network into linear constraints.

[0091]

[0092]

[0093]

[0094] In the formula, p n,t is the pressure of node n at time t; represents the pipeline characteristics, κ l , L l and dl are the friction coefficient, length and inner diameter of the pipe l respectively; ρ is the density of water; Equal to in numerical terms Is a 0-1 variable, used to represent Whether the value of is in the qth segment.

[0095] The resistance-capacitance (RC) network model was used to mathematically model the wall thermal dynamic model and indoor thermal dynamic model of the pig house, and the mathematical model of the livestock house radiator was constructed based on the assumption that the water supply temperature of each livestock house is constant.

[0096]

[0097]

[0098] In the formula, r 1,2 、r 1,3 、r 1,4 、r 1,5 The value is 1 when the wall is exposed to sunlight, otherwise it is 0; α 1,2 , α 1,3 , α 1,4 , α 1,5 and Aw 1,2 , Aw 1,3 , Aw 1,4 , Aw 1,5 Respectively represent the heat absorption rate and surface area of ​​the four walls; Cr 1is the equivalent heat capacity of the indoor air in the pig house; Indicates the heat dissipation of the radiator in the pig house; represents the internal heat generated by livestock activities and metabolism in the pig house; there is a window on the wall between the pig house and node 5, so the outdoor light intensity obtained through the window is A win is the window area, τ win is the window transmittance.

[0099] Preferably, in this embodiment, step S3 is specifically as follows: taking the lowest energy consumption of the farm as the optimization scheduling target, considering the operation constraints of each link of "source-grid-load" in the comprehensive energy system of the farm, and solving the above linear programming model through the CPLEX solver based on the MATLAB-YALMIP platform.

[0100] Embodiment 1:

[0101] This embodiment models and optimizes the scheduling of the IEEE 33 power distribution system and the individual piggery, and provides a comprehensive energy optimization method for the "source-grid-load" of a low-carbon farm, including the following steps:

[0102] Step 1: Construct the integrated energy system structure of a low-carbon farm. In the implementation case, the IEEE 33 power distribution system and 20 separate pig houses were selected, and a typical day in winter in northern my country was selected to construct the integrated energy system structure of a low-carbon farm.

[0103] Step 2: Construct a comprehensive energy system model for low-carbon farms; including the construction of mathematical models of energy production and conversion units of low-carbon farms, mathematical models of power distribution systems, mathematical models of heat networks, and mathematical models of livestock houses.

[0104] Step 3: With the goal of minimizing farm operation costs, construct an optimization scheduling model for the integrated energy system of a low-carbon farm.

[0105] The farm gives priority to using biogas for comprehensive energy supply based on the maximum biogas production power of the biogas treatment unit, and the shortfall is met by purchasing electricity from the external power grid. This is because biogas is obtained through the treatment of livestock manure, and giving priority to using biogas can minimize the energy costs of the farm.

[0106] CHP makes the most of biogas to produce electricity and heat, and maintains a constant power output of electricity and heat throughout the day. When the heat output of CHP cannot meet the heat load of the farm, the farm dispatches a heat pump to generate heat by consuming electricity.

[0107] Based on the heat storage characteristics of the pig house enclosure structure, the farm can dynamically adjust the water flow of the radiator in the pig house within the temperature comfort range of the growing pig house and the nursery piglet house, thereby saving the heating cost of the pig house and reducing the operating cost of the farm.

[0108] The operation cost of the farm without biogas is compared, as shown in Table 1. It can be seen that through the use of biogas, the farm can reduce the operation cost by about 10.3%, and reduce the purchase of electricity from the external power grid by about 11%, thereby further reducing the dependence on the external power grid. Therefore, through the effective use of biogas, while solving the pollution of farm manure, the energy cost of the farm can be reduced, and the dependence on the external power grid can be further reduced, thereby slowing down the construction of potential rural power grid backup capacity.

[0109] Table 1 Comparison results

[0110] Table 3 Comparative results

[0111]

[0112] Comparing the two scenarios, the heat load and operating cost of the farm under the two scenarios are shown in Table 2, considering the heat storage characteristics of the pig house enclosure structure and the resulting flexibility of the heat load, and not considering the heat storage characteristics of the pig house enclosure structure and the resulting flexibility of the heat load. It can be seen that since scenario 2 does not adjust the water flow of the radiator and cannot utilize the flexibility of the heat load, its total heat load and operating cost are higher than scenario 1. In addition, the flow rate of the pig house radiator in scenario 2 is set manually, rather than determined by optimized scheduling. Therefore, the temperature in the pig house may be too high or too low, and the temperature comfort level in the house cannot be guaranteed, and heat energy may be wasted.

[0113] Table 2 Comparison results of two scenarios

[0114] Table 4 Comparative results in two scenarios

[0115]

[0116] The above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A comprehensive energy optimization method for all aspects of a low-carbon farm, characterized in that: The following steps are involved: Step S1: construct a low-carbon farm integrated energy system structure, including a farm energy conversion center, an integrated energy distribution network, and a farm multi-energy load; Step S2: constructing a low-carbon farm comprehensive energy system model based on the low-carbon farm comprehensive energy system structure; Step S3: Based on the low-carbon farm comprehensive energy system model, with the goal of minimizing the farm operation energy consumption, an optimal scheduling plan is obtained; The energy conversion center of the farm mainly includes a transformer, CHP, a heat pump and a biogas processing unit; the electric energy and thermal energy produced by the energy conversion center of the farm are transmitted to the livestock house of the farm through the integrated energy distribution network; The step S2 is specifically as follows: Step S21: Establishing a mathematical model of energy production and conversion unit of a low-carbon farm; Step S22: mathematically modeling the power distribution system of the low-carbon farm; Step S23: constructing a low-carbon farm heat network model based on the principle of piecewise linearization; The step S21 specifically includes: mathematically describing the power consumption associated with the biogas treatment process and the power output of other energy conversion units, The electricity consumption associated with the biogas treatment process is expressed as: In the formula, is the biogas power produced by the biogas treatment unit during period t; The electric power consumed in the biogas treatment process; η b is the electricity consumption coefficient during biogas treatment; The power output constraints of other energy conversion units are: Where η e is the gas-to-power efficiency of CHP; η h is the gas-to-heat efficiency of CHP; The electrical power consumed by the heat pump; is the thermal power output of the heat pump; η hp is the electricity-to-heat efficiency of the heat pump; P is the electric power purchased by the farm from the upper distribution network; e,max P is the upper limit of the electric power purchased by the farm from the upper distribution network; g,max P is the upper limit of the gas power input from the biogas processing unit to the CHP, that is, the upper limit of the maximum gas power output of the biogas processing unit; hp,max The upper limit of the heat pump output; The step S22 specifically includes: modeling the power distribution system based on the Distflow model, and linearizing the square terms in the power flow constraints of the distribution network Assume j is the sender, j+1 is the receiver, P j +iQ j is the complex power of node j; is the complex power of the load carried by node (j+1); r f +ix f is the complex impedance of the line from node j to node j+1; V j is the voltage at node j, and the power flow at each node is expressed as follows: 1-ε≤V j ≤1+ε (11) The square term in the power flow constraint of the distribution network is linearized, and the linearized power flow constraint is as follows: The step S23 uses a piecewise linearization method to linearize the node pressure equation, converting the nonlinear constraints of the heat network into linear constraints; In the formula, p n,t is the pressure of node n at time t; represents the pipeline characteristics, κ l , L l and dl are the friction coefficient, length and inner diameter of the pipe l respectively; ρ is the density of water; Equal to in numerical terms Is a 0-1 variable, used to represent Whether the value of is in the qth segment; The construction of the low-carbon farm heat network model is as follows: The thermal resistance-heat capacity network model is used to mathematically model the wall thermal dynamic model and indoor thermal dynamic model of the pig house, and a low-carbon farm thermal network model is based on the constant water supply temperature of each livestock house; In the formula, r 1,2 、r 1,3 、r 1,4 、r 1,5 The value is 1 when the wall is exposed to sunlight, otherwise it is 0; α 1,2 , α 1,3 , α 1,4 , α 1,5 and Aw 1,2 , Aw 1,3 , Aw 1,4 , Aw 1,5 Respectively represent the heat absorption rate and surface area of ​​the four walls; Cr 1 is the equivalent heat capacity of the indoor air in the pig house; Indicates the heat dissipation of the radiator in the pig house; represents the internal heat generated by livestock activities and metabolism in the pig house; there is a window on the wall between the pig house and node i, and the outdoor light intensity obtained through the window is A win is the window area, τ win is the window transmittance.

2. A method for comprehensive energy optimization of all aspects of a low-carbon farm according to claim 1, characterized in that: The step S3 is specifically as follows: taking the lowest energy consumption of the farm as the optimization scheduling target, considering the operation constraints of each link of source-grid-load in the comprehensive energy system of the farm, and solving the low-carbon farm heat network model through the CPLEX solver based on the MATLAB-YALMIP platform.

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