A method for collaborative optimization configuration of electrical heat network and energy hub

Abstract

The present invention relates to a method for coordinated optimization configuration of an electrical heat network and an energy hub, the method comprising: step 1: planning an energy hub model that couples a distribution network, a natural gas network and a heating network; step 2: determining energy demand data, supply-side energy prices, renewable energy output data and basic operating parameters of cogeneration, electric heat pumps, electric refrigeration, absorption chillers and electric, heat and cold energy storage equipment in the energy hub; step 3: establishing an objective function, and completing the modeling of an optimized operation model of a comprehensive energy system according to energy balance constraints of distribution networks, natural gas networks and heating networks and operating constraints of energy hubs; step 4: solving to obtain the multi-energy system structure and the configuration capacity in the energy hub. Compared with the prior art, the present invention solves the problem that current research is limited to a single planning structure or configuration capacity, reduces the cost problem caused by a single planning, and gives full play to the high energy utilization rate advantage of the multi-energy system.

Description

Technical Field

[0001] The present invention relates to multi-energy system technology, and in particular to a method for collaboratively optimizing the configuration of an electrical heat network and an energy hub. Background Art

[0002] With the continuous optimization and opening of the electricity market, resource integration and coordinated optimization of multiple energy systems are of great significance for promoting renewable energy consumption, improving energy efficiency and reducing carbon dioxide emissions from energy systems. Traditional energy network planning focuses on a single network and lacks overall coordination between networks.

[0003] The power grid itself has the characteristics of real-time balancing and is difficult to store on a large scale. Therefore, the cross-regional transmission capacity of the power grid still needs to be improved. The transmission loss of the heat network is large. The gas pipeline network can store on a large scale, but the utilization efficiency is low. The power system can improve its flexibility through multi-energy interconnection with natural gas and heating systems. In order to analyze and model multi-energy networks, energy hubs (EHs) provide suitable tools for the planning and operation of multiple energy carrier systems, realizing flexible conversion and unified management between different energy sources. Components in EHs, such as cogeneration units, electric heat pumps, electric refrigeration equipment, absorption chillers, and energy storage are coupling components between electricity, heat, and gas networks. This interconnection method can be applied to complex buildings such as airports, hospitals, shopping malls, industrial plants, and power plants.

[0004] At present, existing technologies have studied EH planning models based on simultaneous consideration of renewable energy and demand response. However, most of the existing studies consider the introduction of components in EH or capacity planning, and fewer studies include pipelines and pipeline planning for power grids and natural gas pipelines. Research on electrical and thermal networks coupled to energy hubs is even more limited. This field urgently needs a method for simultaneous planning of comprehensive and coordinated multi-energy system structures and energy hubs. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a method for coordinated optimization configuration of electrical thermal network and energy hub.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A method for collaboratively optimizing configuration of an electrical heat network and an energy hub, the method comprising:

[0008] Step 1: Plan an energy hub model that couples the distribution network, natural gas network, and heating network;

[0009] Step 2: Determine energy demand data, supply-side energy prices, renewable energy output data, and basic operating parameters of cogeneration, electric heat pumps, electric refrigeration, absorption chillers, and electric, heat, and cold energy storage equipment in the energy hub;

[0010] Step 3: Establish the objective function and complete the modeling of the integrated energy system optimization operation model based on the energy balance constraints of the distribution network, natural gas network, heating network and the operation constraints of the energy hub;

[0011] Step 4: Solve to obtain the multi-energy system structure and the configuration capacity within the energy hub.

[0012] Preferably, the energy hub model includes models of key equipment inside the energy hub, which are divided into: energy consumption model of cogeneration, energy consumption model of electric heat pump, energy consumption model of electric refrigerator, energy consumption model of absorption refrigerator, electricity storage, heat storage, cold storage model and wind turbine output model; multiple energy sources are converted, distributed and stored within the network.

[0013] Preferably, the energy consumption model of cogeneration is expressed as:

[0014]

[0015]

[0016] in, and are the electricity and heat output of cogeneration, respectively. The amount of gas consumed by combined heat and power generation, and are the electrical efficiency and thermal efficiency of cogeneration, respectively;

[0017] The energy consumption model of the electric heat pump is expressed as:

[0018]

[0019] in, and are the heat output and power consumption of the electric heat pump, respectively, ehp is the heating efficiency of the electric heat pump;

[0020] The energy consumption model of the electric refrigerator is expressed as:

[0021]

[0022] in, and are the cooling capacity and power consumption of the electric refrigerator, respectively, ere is the cooling efficiency of the electric refrigerator;

[0023] The energy consumption model of the absorption refrigerator is expressed as:

[0024]

[0025] in, and are the cooling capacity and heat consumption of the absorption chiller, respectively, ac is the refrigeration efficiency of the absorption chiller;

[0026] The mathematical model of electricity storage is expressed as:

[0027]

[0028] in, are the remaining power of the energy storage device in time period t and time period t-1, and are the charging power and discharging power of the energy storage device, respectively. and They represent the charging and discharging efficiency of the energy storage device, Δt is the time span within a single time period, and E es is the storage capacity of the electrical energy storage device;

[0029] The heat storage mathematical model is expressed as:

[0030]

[0031] in, are the remaining heat storage capacity of the thermal energy storage equipment in time period t and time period t-1, and are the heat absorption power and heat release power of the thermal energy storage equipment, and They represent the heat absorption and heat release efficiency of the thermal energy storage device, Δt is the time span in a single time period, and E hs The storage capacity of the thermal energy storage device;

[0032] The mathematical model of cold storage is expressed as:

[0033]

[0034] in, are the remaining cold storage capacity of the cold energy storage equipment in time period t and time period t-1, and are the charging power and discharging power of the cold energy storage equipment respectively. and They represent the charging and discharging efficiency of the cold energy storage device, Δt is the time span in a single time period, and E cs The storage capacity of the cold energy storage device;

[0035] The wind turbine output model is expressed as Indicates the fan output.

[0036] Preferably, the objective function is:

[0037] min COST=M o +M gen +M IDR +M L

[0038] Where COST is the operator’s annual investment cost for the multi-energy system, M o is the configuration cost of the energy hub, M IDR is the demand response cost, M gen is the annual investment cost of purchasing electrical heat, M L The investment cost for planning lines and pipelines.

[0039] Preferably, the configuration cost of the energy hub is:

[0040]

[0041] Where BUS is a set of multiple energy hubs, o is any energy hub in the set BUS, x is the candidate device in energy hub o, on is the total number of candidate devices in energy hub o, yy o,x is the unit capacity investment cost of alternative equipment x in energy hub o, M o,x is the configuration capacity of the candidate device x in the energy hub o, t o,x is the life of the alternative equipment x in the energy hub o, r is the discount rate, and R is the residual value rate of fixed assets.

[0042] Preferably, the annual investment cost for purchasing electrical heat is:

[0043]

[0044] Ω EG is the set of power grid generator nodes, Ω GG is the gas source node set of the gas network, Ω HG is the set of heat source nodes in the heat network, q1, q2, q3 correspond to the set Ω EG Any generator node in the set Ω GG Any gas source node, set Ω HG Any heat source node in C e,t is the price of electricity purchased by the energy hub from the grid unit during period t, C g,t is the price of gas purchased by the energy hub from the gas grid, C h,t is the price of heat purchased by the energy hub from the heat network unit during period t, is the amount of electricity purchased by the energy hub from node q1 during period t, is the gas purchase volume of the energy hub from node q2 during period t, is the amount of heat purchased by the energy hub from node q3 during period t, Day is the number of days in a year, and th is the number of periods divided into a day.

[0045] Preferably, the investment cost of planning lines and pipelines is:

[0046]

[0047] Ω LP is the set of transmission lines and natural gas pipelines to be built, L is the set Ω LP Any transmission line or natural gas pipeline in L A 0-1 variable indicating whether L is constructed or not. If so, y L is 1, otherwise y L is 0, M L represents the construction cost of building L, t L L is the operating life, r is the discount rate, and R is the residual value rate of fixed assets.

[0048] Preferably, the demand response cost is expressed as:

[0049]

[0050] P shift,t , P cut,t They represent the load that can be shifted and the load that can be reduced during period t, M shift 、M cut They represent the unit load compensation costs of shiftable load and curtailable load respectively. α and β are 0-1 variables indicating whether demand response occurs. If demand response occurs, it is 1, and if demand response does not occur, it is 0.

[0051] Preferably, the energy balance constraints of the distribution network, natural gas network and heating network are expressed as:

[0052]

[0053]

[0054]

[0055]

[0056] in, The amount of electricity purchased from the grid for the energy hub, The power output of cogeneration, To show the fan output, and are the charging power and discharging power of the energy storage device, respectively. The electric load at the user end;

[0057] Purchase heat from the grid for the energy hub, The heat output of the combined heat and power generation is the heat output of the electric heat pump. and are the heat absorption power and heat release power of the thermal energy storage equipment, is the heat consumed by the absorption chiller, is the heat load at the user end;

[0058] is the cooling capacity output by the electric refrigerator, is the cooling capacity output by the absorption chiller, and are the charging power and discharging power of the cold energy storage equipment respectively. is the cooling load at the user end;

[0059] The amount of gas purchased from the gas grid for the energy hub, The amount of gas consumed for combined heat and power generation.

[0060] Preferably, the operation constraints of the energy hub include:

[0061] Constraints on combined heat and power generation:

[0062]

[0063] The amount of gas consumed by combined heat and power generation, are the lower and upper limits of the gas consumption in cogeneration, respectively;

[0064] Energy consumption constraints of electric heat pumps:

[0065]

[0066] is the amount of electricity consumed by the electric heat pump, are the lower and upper limits of the amount of electricity consumed by the electric heat pump, respectively;

[0067] Energy consumption constraints of electric refrigeration machines:

[0068]

[0069] is the amount of electricity consumed by the electric refrigerator, are the lower and upper limits of the amount of electricity consumed by the electric refrigerator, respectively;

[0070] Energy consumption constraints of absorption chillers:

[0071]

[0072] is the power consumed by the absorption chiller, are the lower and upper limits of the heat consumed by the absorption chiller, respectively;

[0073] Charge constraints of electric energy storage equipment:

[0074]

[0075]

[0076] is the state of charge of the energy storage device, They are the lower and upper limits of the state of charge of the electric energy storage device respectively;

[0077] Thermal energy storage equipment load constraints:

[0078]

[0079]

[0080] is the heat load state of the thermal energy storage device, They are the lower and upper limits of the thermal load state of the thermal energy storage equipment respectively;

[0081] Cold storage equipment load constraints:

[0082]

[0083]

[0084] is the load-cooling state of the cold energy storage equipment. They are the lower and upper limits of the load cooling state of the cold energy storage equipment respectively;

[0085] Wind turbine output constraints:

[0086]

[0087] Indicates the fan output. Respectively represent the minimum and maximum values ​​of the fan output.

[0088] Compared with the prior art, the present invention has the following advantages:

[0089] (1) The present invention simultaneously plans the multi-energy system structure and the equipment capacity within the energy hub, solving the problem that current research is limited to a single planning structure or configuration capacity, and reduces the cost problem caused by a single planning.

[0090] (2) The present invention plans a general model of a multi-energy system by minimizing system costs, thereby giving full play to the high energy utilization advantage of the multi-energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 To illustrate an implementation flow chart of the method according to the present invention;

[0092] Figure 2 It shows a diagram of an electricity-gas-heat network structure taking into account an energy hub according to the present invention;

[0093] Figure 3 It shows a schematic diagram of the purchase price of electricity, heat and gas in a multi-energy system;

[0094] Figure 4 A schematic diagram of the electricity / heat / cooling load demand under the energy hub system is shown;

[0095] Figure 5 The diagram shows the results of power network node voltage optimization;

[0096] Figure 6 The result diagram of natural gas network node pressure optimization is shown;

[0097] Figure 7 The graph shows the temperature optimization results of the heating network nodes. DETAILED DESCRIPTION

[0098] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. Note that the following embodiments are merely illustrative in nature, and the present invention is not intended to limit its applicable objects or uses, and the present invention is not limited to the following embodiments.

[0099] Example

[0100] like Figure 1 As shown, this embodiment provides a method for coordinated optimization configuration of an electrical heat network and an energy hub, the method comprising:

[0101] Step 1: Plan an energy hub model that couples the distribution network, natural gas network, and heating network;

[0102] Step 2: Determine energy demand data, supply-side energy prices, renewable energy output data, and basic operating parameters of cogeneration, electric heat pumps, electric refrigeration, absorption chillers, and electric, heat, and cold energy storage equipment in the energy hub;

[0103] Step 3: Establish the objective function and complete the modeling of the integrated energy system optimization operation model based on the energy balance constraints of the distribution network, natural gas network, heating network and the operation constraints of the energy hub;

[0104] Step 4: Solve to obtain the multi-energy system structure and the configuration capacity within the energy hub.

[0105] The energy hub model includes models of key equipment within the energy hub, which are divided into: energy consumption model of cogeneration, energy consumption model of electric heat pump, energy consumption model of electric refrigerator, energy consumption model of absorption refrigerator, electricity storage, heat storage, cold storage model and wind turbine output model; multiple energy sources are converted, distributed and stored within the network.

[0106] The following is a detailed description of the models of key equipment:

[0107] (1) The energy consumption model of cogeneration is expressed as:

[0108]

[0109]

[0110] in, and are the electricity and heat output of cogeneration, respectively. The amount of gas consumed by combined heat and power generation, and They are the electrical efficiency and thermal efficiency of cogeneration, respectively.

[0111] (2) The energy consumption model of the electric heat pump is expressed as:

[0112]

[0113] in, and are the heat output and power consumption of the electric heat pump, respectively, ehp is the heating efficiency of the electric heat pump.

[0114] (3) The energy consumption model of the electric refrigerator is expressed as:

[0115]

[0116] in, and are the cooling capacity and power consumption of the electric refrigerator, respectively, ere is the cooling efficiency of the electric refrigerator.

[0117] (4) The energy consumption model of the absorption chiller is expressed as:

[0118]

[0119] in, and are the cooling capacity and heat consumption of the absorption chiller, respectively, ac is the refrigeration efficiency of the absorption chiller.

[0120] (5) The mathematical model of power storage is expressed as:

[0121]

[0122] in, are the remaining power of the energy storage device in time period t and time period t-1, and are the charging power and discharging power of the energy storage device, respectively. and They represent the charging and discharging efficiency of the energy storage device, Δt is the time span within a single time period, and E es It is the storage capacity of the electrical energy storage device.

[0123] (6) The heat storage mathematical model is expressed as:

[0124]

[0125] in, are the remaining heat storage capacity of the thermal energy storage equipment in time period t and time period t-1, and are the heat absorption power and heat release power of the thermal energy storage equipment, and They represent the heat absorption and heat release efficiency of the thermal energy storage device, Δt is the time span in a single time period, and E hs is the storage capacity of the thermal energy storage device.

[0126] (7) The mathematical model of cold storage is expressed as:

[0127]

[0128] in, are the remaining cold storage capacity of the cold energy storage equipment in time period t and time period t-1, and are the charging power and discharging power of the cold energy storage equipment respectively. and They represent the charging and discharging efficiency of the cold energy storage device, Δt is the time span in a single time period, and E cs The storage capacity of the cold energy storage device.

[0129] (8) The wind turbine output model is expressed as Indicates the fan output.

[0130] On this basis, the energy supply network flow models of power grid, natural gas grid and heating grid are studied, specifically:

[0131] (1) The power grid is mainly represented by a DC power flow model, which follows the electromagnetic law and is expressed as:

[0132]

[0133]

[0134] -π≤θ≤π

[0135]

[0136] Where: represents the power of the transmission line; θ i and θ j They represent the phases of the starting point and the end point of the transmission line respectively; xl represents the line susceptance; y l A 0-1 variable representing whether the transmission line is built on behalf of others; and Represent the lower and upper power limits of the transmission line respectively.

[0137] (2) The natural gas system consists of natural gas sources, compressors, natural gas pipelines and natural gas loads. The natural gas system model is expressed as:

[0138]

[0139]

[0140]

[0141] ψ i ≤ξ·ψ j

[0142]

[0143] Where: represents the natural gas pipeline flow; ψ i , j represents the air pressure at nodes i and j; C p represents the natural gas pipeline coefficient; y p A 0-1 variable representing whether the natural gas pipeline is built on behalf of others; ψ and They represent the lower and upper limits of pipeline gas pressure respectively; ξ is the compression coefficient of the compressor; and Represent the lower and upper limits of the pipeline flow respectively.

[0144] (3) The hydraulic model of the hot water network is expressed as:

[0145] A h m=m o

[0146] B h (ΔH b -H p )=0

[0147] Where: A h is the node-branch association matrix; m is the thermal pipeline flow vector; m o is the net heat load flow of the thermal network node; B h is the thermal network loop matrix; ΔH b is the pressure drop vector of the thermal pipeline; H p Thermal pipeline circulation pump vector;

[0148] Thermal model of the hot water network:

[0149]

[0150]

[0151]

[0152]

[0153] Where: φ l ,φ s They are the thermal power required by the heat load and the thermal power supplied by the heat source; are the hot water flow rates flowing through the heat load and heat source respectively; They are the supply water temperature flowing into the heat load and the return water temperature flowing out of the heat load respectively; are the supply water temperature and return water temperature of the heat source: C p Specific heat capacity parameter of hot water in thermal network; m out 、m in are the hot water flows out of and into the nodes, respectively; are the hot water temperatures at the head and end of the thermal pipeline: T te is the ambient temperature of the thermal pipe; p is the heat transfer coefficient of the thermal pipeline; L p is the length of the thermal pipeline; m p is the hot water flow rate in the thermal pipe.

[0154] In addition, the load of the present invention includes: basic load, time-shiftable load and reducible load.

[0155] Basic load: In terms of electrical load, this type of load mainly includes electricity consumption of basic lighting equipment, electricity consumption of entertainment equipment, etc.; in terms of cold / heat load, this type of load mainly includes water load for washing, cleaning, etc.

[0156] Translable load: This type of load only needs to meet certain load requirements within a specified time interval. It generally has a fixed load duration and customary usage time. The model is as follows:

[0157]

[0158] Reducible load: It is allowed to be cut off and reduced in a limited time within a certain period of time. The model is as follows:

[0159] P cut,min ≤P cut,t ≤P cut,max

[0160] Based on the following, the objective function is established:

[0161] min COST=M o +M gen +M IDR +M L

[0162] Where COST is the operator’s annual investment cost for the multi-energy system, M o is the configuration cost of the energy hub, M IDR is the demand response cost, M gen is the annual investment cost of purchasing electrical heat, M L The investment cost for planning lines and pipelines.

[0163] The configuration cost of the energy hub is:

[0164]

[0165] Where BUS is a set of multiple energy hubs, o is any energy hub in the set BUS, x is the candidate device in energy hub o, on is the total number of candidate devices in energy hub o, yy o,x is the unit capacity investment cost of alternative equipment x in energy hub o, M o,x is the configuration capacity of the candidate device x in the energy hub o, t o,x is the life of the alternative equipment x in the energy hub o, r is the discount rate, and R is the residual value rate of fixed assets.

[0166] The annual investment cost for purchasing electrical heat is:

[0167]

[0168] ΩEG is the set of power grid generator nodes, Ω GG is the gas source node set of the gas network, Ω HG is the set of heat source nodes in the heat network, q1, q2, q3 correspond to the set Ω EG Any generator node in the set Ω GG Any gas source node, set Ω HG Any heat source node in C e,t is the price of electricity purchased by the energy hub from the grid unit during period t, C g,t is the price of gas purchased by the energy hub from the gas grid, C h,t is the price of heat purchased by the energy hub from the heat network unit during period t, is the amount of electricity purchased by the energy hub from node q1 during period t, is the gas purchase volume of the energy hub from node q2 during period t, is the amount of heat purchased by the energy hub from node q3 during period t, Day is the number of days in a year, and th is the number of periods divided into a day.

[0169] The investment cost of planning lines and pipelines is:

[0170]

[0171] Ω LP is the set of transmission lines and natural gas pipelines to be built, L is the set Ω LP Any transmission line or natural gas pipeline in L A 0-1 variable indicating whether L is constructed or not. If so, y L is 1, otherwise y L is 0, M L represents the construction cost of building L, t L L is the operating life, r is the discount rate, and R is the residual value rate of fixed assets.

[0172] The demand response cost is expressed as:

[0173]

[0174] P shift,t , P cut,t They represent the load that can be shifted and the load that can be reduced during period t, M shift 、M cut They represent the unit load compensation costs of shiftable load and curtailable load respectively. α and β are 0-1 variables indicating whether demand response occurs. If demand response occurs, it is 1, and if demand response does not occur, it is 0.

[0175] The energy balance constraints of the distribution network, natural gas network, and heating network are expressed as:

[0176]

[0177]

[0178]

[0179]

[0180] in, The amount of electricity purchased from the grid for the energy hub, The power output of cogeneration, To show the fan output, and are the charging power and discharging power of the energy storage device, respectively. The electric load at the user end;

[0181] Purchase heat from the grid for the energy hub, The heat output of the combined heat and power generation is the heat output of the electric heat pump. and are the heat absorption power and heat release power of the thermal energy storage equipment, is the heat consumed by the absorption chiller, is the heat load at the user end;

[0182] is the cooling capacity output by the electric refrigerator, is the cooling capacity output by the absorption chiller, and are the charging power and discharging power of the cold energy storage equipment respectively. is the cooling load at the user end;

[0183] The amount of gas purchased from the gas grid for the energy hub, The amount of gas consumed for combined heat and power generation.

[0184] Preferably, the operation constraints of the energy hub include:

[0185] Constraints on combined heat and power generation:

[0186]

[0187] The amount of gas consumed by combined heat and power generation, are the lower and upper limits of the gas consumption in cogeneration, respectively;

[0188] Energy consumption constraints of electric heat pumps:

[0189]

[0190] is the amount of electricity consumed by the electric heat pump, are the lower and upper limits of the amount of electricity consumed by the electric heat pump; the energy consumption constraint of the electric refrigerator is:

[0191]

[0192] is the amount of electricity consumed by the electric refrigerator, are the lower and upper limits of the amount of electricity consumed by the electric refrigerator, respectively;

[0193] Energy consumption constraints of absorption chillers:

[0194]

[0195] is the power consumed by the absorption chiller, are the lower and upper limits of the heat consumed by the absorption chiller, respectively;

[0196] Charge constraints of electric energy storage equipment:

[0197]

[0198]

[0199] is the state of charge of the energy storage device, They are the lower and upper limits of the state of charge of the electric energy storage device respectively;

[0200] Thermal energy storage equipment load constraints:

[0201]

[0202]

[0203] is the heat load state of the thermal energy storage device, They are the lower and upper limits of the thermal load state of the thermal energy storage equipment respectively;

[0204] Cold storage equipment load constraints:

[0205]

[0206]

[0207] is the load-cooling state of the cold energy storage equipment. They are the lower and upper limits of the load cooling state of the cold energy storage equipment respectively;

[0208] Wind turbine output constraints:

[0209]

[0210] Indicates the fan output. Respectively represent the minimum and maximum values ​​of the fan output.

[0211] Specifically:

[0212] The specific implementation process of the present invention is:

[0213] Step (1) Data collection: The data include the electricity, heat, cooling loads, wind power output, incentive prices of various demand response resources, unit electricity, heat and gas purchase prices, parameters of energy conversion equipment and energy storage equipment, and installation investment costs of transmission lines, gas pipelines and heating pipelines in different seasons of the planned year.

[0214] Step (2) classifies various loads: according to the energy consumption characteristics of cooling / heating / electricity loads, the loads described in step (1) are classified into rigid loads, time-shiftable loads and curtailable loads, and various demand response models are established.

[0215] Step (3) Modeling: Based on the coupling transformation relationship of each energy source in the energy hub, an energy hub model is planned that can couple the distribution network, natural gas network and heating network.

[0216] Step (4) completes the modeling of the optimized operation model of the integrated energy system with the goal of optimizing the total cost and based on the energy balance of the distribution network, natural gas network, heating network and the operation constraints of the energy hub.

[0217] Step (5) solves the model through optimization tools: judge whether the optimization result after using demand response technology is better by the total construction and dispatching cost of the energy hub, the amount of electrical resource savings, and the equipment utilization rate, and output the optimal result. Select the total cost within the planning period as the objective function to minimize, and obtain the simultaneous planning for realizing the configuration capacity of the electrical and thermal energy system structure and the energy hub.

[0218] A source hub consists of three basic elements: a renewable component, an energy conversion component, and a storage device.

[0219] The constraints include: one or more of configuration capacity constraints, pricing constraints, safety constraints, and equipment operation characteristic constraints.

[0220] Figure 2 The following is a diagram showing an electric-gas-heat network structure taking into account the energy hub of the present invention. Figure 2As shown, the multi-energy system includes: a 13-node distribution network system, a 7-node gas system, a 9-node heating system and 4 energy hub systems. The energy hub is composed of energy conversion elements (cogeneration, electric heat pump, electric refrigeration, absorption chiller), renewable energy elements (fan system) and energy storage equipment (electricity storage equipment, heat storage equipment, cold storage equipment).

[0221] This embodiment relates to a system for realizing simultaneous planning of multi-energy system and energy hub configuration, including: an equipment parameter input unit, a configuration equipment planning unit, a connection relationship planning unit for lines and pipelines in a multi-energy system, and a planning result output unit. In order to compare the similarities and differences between the planning results of a conventional model and a model with added energy storage and demand response, the following two scenarios are constructed for analysis:

[0222] Scenario 1: No energy storage and demand response model included;

[0223] Scenario 2: Including energy storage and demand response model.

[0224] The invention introduces the basic information of the case, including load demand, construction area, energy price and candidate system component parameters as follows. Four energy centers provide electric cooling and heating loads in this system, and users use centralized cooling and heating loads without considering transmission losses. As a case study, Figure 2 As shown in the figure, the model shows the optimal design of 4 interconnected energy centers, 13-node power grid system, 7-node natural gas system and 9-node thermal system. The EH1 store EH1 has an area of ​​45,000 square meters; the hotel EH2 has an area of ​​38,400 square meters; the office building EH3 has an area of ​​50,000 square meters; and the hospital EH4 has an area of ​​42,000 square meters. The method was verified by CPLEX in the MATLAB optimization toolbox.

[0225] The loads in the complementary optimization configuration of the multi-energy system include electricity, heat and cooling. The parameters of the given candidate equipment are:

[0226] Table 1: List of main equipment in the energy hub.

[0227]

[0228] according to Figure 4 The typical summer daily load curve of CLP power heating and cooling power, the maximum energy consumption and unit price are input, and the specific equipment selection and connection mode of each energy center are obtained in turn. The alternative components of each energy center are wind power, transformer, power generation, heat storage, water pump and battery. The optimal system configuration results of the two modes are shown in Table 2.

[0229] Table 2: Energy hub optimization configuration results table.

[0230]

[0231] Table 3: Multi-energy network planning results table.

[0232] Scenario 1 Scenario 2 Power System Line:1-4,4-9 Lines: 1–4 Gas system Pipeline: 3-2; 6-7 Pipes: 6–7 Heating system Pipeline: 0 Pipeline: 0

[0233] The optimal trading strategies are shown in Tables 2 and 3. Energy output equipment includes centralized wind power equipment, not only CHP, electric heat pumps, absorption chillers and electric refrigeration, but also flexible load response and energy storage equipment. Demand response makes decisions based on market prices. Energy storage equipment is used to smooth the peak and fill the valley of load demand. There are two purposes for purchasing electricity, heat and natural gas. One is to use energy directly, and the other is to directly supply energy to the equipment in the energy hub. Due to the existence of CHP and distributed renewable energy, the demand for electricity at the input end of the energy hub has been transferred (transferred to natural gas demand) and reduced (distributed wind power output offset). Due to the role of electric heat pumps, the existing heat network structure can be temporarily not expanded, saving certain costs and resources. The planning results show that in order to meet the demand for electricity, heat and cold loads, expanding the natural gas network, the transmission network and building local CHP and renewable energy are more cost-effective than expanding the heat network, and it is necessary to plan energy storage to cooperate with CHP operation and smooth the output fluctuations of renewable energy.

[0234] In scenario 1, natural gas is mainly used to supply electricity for CHP during peak electricity prices, and the fans are operated in real time (1-24 hours). Electricity is purchased from the power grid to supplement the shortage of CHP and fans, reducing power supply costs. CHP mainly provides heat energy utilization during peak heat load periods. Due to the high heating efficiency of electric heat pumps, heat is only generated by electric heat pumps after 18:00 in the afternoon, which is a period of low energy consumption. The cooling load is only generated by electric refrigeration and absorption chillers. Although affected by electricity prices, electric refrigeration equipment is widely used due to its high efficiency.

[0235] After considering demand response and integrated energy storage system in scenario 2, the overall transmission capacity of the power grid decreases due to the lower waste heat recovery efficiency of CHP than that of electric heat pumps, and the local increase in power grid purchases is mainly due to the increase in energy storage equipment. In other periods, demand response varies with the peak and trough of electricity prices. Energy hubs should transfer part of the load during the peak electricity price period to this period. Make full use of the complementary characteristics of various energy conversion equipment. In order to achieve economy, compared with scenario 1, the capacity of CHP is significantly reduced and the capacity of EHP is relatively increased. Electricity storage improves the flexibility of EHP and ER, and heat storage improves the flexibility of CHP, combining EHP with the heat network to reduce heating costs. Cold storage equipment and AC, ER, meet the cold load, increase the flexibility of the system, and reduce refrigeration costs.

[0236] Comprehensively comparing the scenarios, controllable power loads and controllable heat and cooling loads can both reduce annual operating costs, but from the perspective of equipment capacity allocation and specific cost items, their impacts on annual operating costs are different. Controlled power loads have a significant impact on energy consumption costs. Controlled cooling / heat loads can significantly reduce the installed capacity of equipment, thereby reducing the installation cost of configurable energy storage. As a balancing regulating device, the total cost of the energy hub is reduced, while in the absence of IDR and energy storage, the total cost is the highest. It can be seen that the method proposed in the present invention realizes the simultaneous planning of the multi-energy system structure and the configured capacity within the energy hub, and meets the minimum planning cost, which can be applied to actual projects.

[0237] The above embodiments are merely examples and do not limit the scope of the present invention. These embodiments can also be implemented in various other ways, and various omissions, substitutions, and changes can be made without departing from the technical concept of the present invention.

Claims

1. A method for collaborative optimization configuration of electrical heat network and energy hub, characterized in that: The method includes: Step 1: Plan an energy hub model that couples the distribution network, natural gas network, and heating network; Step 2: Determine energy demand data, supply-side energy prices, renewable energy output data, and basic operating parameters of cogeneration, electric heat pumps, electric refrigeration, absorption chillers, and electric, heat, and cold energy storage equipment in the energy hub; Step 3: Establish the objective function and complete the modeling of the integrated energy system optimization operation model based on the energy balance constraints of the distribution network, natural gas network, heating network and the operation constraints of the energy hub; Step 4: Solve to obtain the multi-energy system structure and the configuration capacity within the energy hub; The energy hub model includes models of key equipment inside the energy hub, which are divided into: energy consumption model of cogeneration, energy consumption model of electric heat pump, energy consumption model of electric refrigerator, energy consumption model of absorption refrigerator, electricity storage, heat storage, cold storage model and wind turbine output model; multiple energy sources are converted, distributed and stored inside the network; The energy consumption model of cogeneration is expressed as: in, and are the electricity and heat output of cogeneration, respectively. The amount of gas consumed by combined heat and power generation, and are the electrical efficiency and thermal efficiency of cogeneration, respectively; The energy consumption model of the electric heat pump is expressed as: in, and are the heat output and power consumption of the electric heat pump, respectively, ehp is the heating efficiency of the electric heat pump; The energy consumption model of the electric refrigerator is expressed as: in, and are the cooling capacity and power consumption of the electric refrigerator, respectively, ere is the cooling efficiency of the electric refrigerator; The energy consumption model of the absorption refrigerator is expressed as: in, and are the cooling capacity and heat consumption of the absorption chiller, respectively, ac is the refrigeration efficiency of the absorption chiller; The mathematical model of electricity storage is expressed as: in, are the remaining power of the energy storage device in time period t and time period t-1, and are the charging power and discharging power of the energy storage device, respectively. and They represent the charging and discharging efficiency of the energy storage device, Δt is the time span within a single time period, and E es is the storage capacity of the electrical energy storage device; The heat storage mathematical model is expressed as: in, are the remaining heat storage capacity of the thermal energy storage equipment in time period t and time period t-1, and are the heat absorption power and heat release power of the thermal energy storage equipment, and They represent the heat absorption and heat release efficiency of the thermal energy storage device, Δt is the time span in a single time period, and E hs The storage capacity of the thermal energy storage device; The mathematical model of cold storage is expressed as: in, are the remaining cold storage capacity of the cold energy storage equipment in time period t and time period t-1, and are the charging power and discharging power of the cold energy storage equipment respectively. and They represent the charging and discharging efficiency of the cold energy storage device, Δt is the time span in a single time period, and E cs The storage capacity of the cold energy storage device; The wind turbine output model is expressed as Indicates the fan output.

2. A method for coordinated optimization configuration of electrical heat network and energy hub according to claim 1, characterized in that: The objective function is: min COST=M o +M gen +M IDR +M L Where COST is the operator’s annual investment cost for the multi-energy system, M o is the configuration cost of the energy hub, M IDR is the demand response cost, M gen is the annual investment cost of purchasing electrical heat, M L The investment cost for planning lines and pipelines.

3. A method for coordinated optimization configuration of electrical heat network and energy hub according to claim 2, characterized in that: The configuration cost of the energy hub is: Where BUS is a set of multiple energy hubs, o is any energy hub in the set BUS, x is the candidate device in energy hub o, on is the total number of candidate devices in energy hub o, yy o,x is the unit capacity investment cost of the alternative equipment x in the energy hub o, M o,x is the configuration capacity of the candidate device x in the energy hub o, t o,x is the life of the alternative equipment x in the energy hub o, r is the discount rate, and R is the residual value rate of fixed assets.

4. A method for coordinated optimization configuration of electrical heat network and energy hub according to claim 2, characterized in that: The annual investment cost for purchasing electrical heat is: Ω EG is the set of power grid generator nodes, Ω GG is the gas source node set of the gas network, Ω HG is the set of heat source nodes in the heat network, q1, q2, q3 correspond to the set Ω EG Any generator node in the set Ω GG Any gas source node, set Ω HG Any heat source node in C e,t is the price of electricity purchased by the energy hub from the grid unit during period t, C g,t is the price of gas purchased by the energy hub from the gas grid, C h,t is the price of heat purchased by the energy hub from the heat network unit during period t, is the amount of electricity purchased by the energy hub from node q1 during period t, is the gas purchase volume of the energy hub from node q2 during period t, is the amount of heat purchased by the energy hub from node q3 during period t, Day is the number of days in a year, and th is the number of periods divided into a day.

5. The method for coordinated optimization configuration of electrical heat network and energy hub according to claim 2, characterized in that: The investment cost of planning lines and pipelines is: Ω LP is the set of transmission lines and natural gas pipelines to be built, L is the set Ω LP Any transmission line or natural gas pipeline in L A 0-1 variable indicating whether L is constructed or not. If so, y L is 1, otherwise y L is 0, M L represents the construction cost of building L, t L L is the operating life, r is the discount rate, and R is the residual value rate of fixed assets.

6. A method for coordinated optimization configuration of electrical heat network and energy hub according to claim 2, characterized in that: The demand response cost is expressed as: P shift,t , P cut,t They represent the load that can be shifted and the load that can be reduced during period t, M shift 、M cut They represent the unit load compensation costs of shiftable load and curtailable load respectively. α and β are 0-1 variables indicating whether demand response occurs. If demand response occurs, it is 1, and if demand response does not occur, it is 0.

7. A method for coordinated optimization configuration of electrical heat network and energy hub according to claim 1, characterized in that: The energy balance constraints of the distribution network, natural gas network and heating network are expressed as: in, The amount of electricity purchased from the grid for the energy hub, The power output of cogeneration, To show the fan output, and are the charging power and discharging power of the energy storage device, respectively. The electric load at the user end; Purchase heat from the grid for the energy hub, The heat output of the combined heat and power generation is the heat output of the electric heat pump. and are the heat absorption power and heat release power of the thermal energy storage equipment, is the heat consumed by the absorption chiller, is the heat load at the user end; is the cooling capacity output by the electric refrigerator, is the cooling capacity output by the absorption chiller, and are the charging power and discharging power of the cold energy storage equipment respectively. is the cooling load at the user end; The amount of gas purchased from the gas grid for the energy hub, The amount of gas consumed for combined heat and power generation.

8. The method for coordinated optimization configuration of electrical heat network and energy hub according to claim 1, characterized in that: The operational constraints of the energy hub include: Constraints on combined heat and power generation: The amount of gas consumed by combined heat and power generation, are the lower and upper limits of the gas consumption in cogeneration, respectively; Energy consumption constraints of electric heat pumps: is the amount of electricity consumed by the electric heat pump, are the lower and upper limits of the amount of electricity consumed by the electric heat pump, respectively; Energy consumption constraints of electric refrigeration machines: is the amount of electricity consumed by the electric refrigerator, are the lower and upper limits of the amount of electricity consumed by the electric refrigerator, respectively; Energy consumption constraints of absorption chillers: is the power consumed by the absorption chiller, are the lower and upper limits of the heat consumed by the absorption chiller, respectively; Charge constraints of electric energy storage equipment: is the state of charge of the energy storage device, They are the lower and upper limits of the state of charge of the electric energy storage device respectively; Thermal energy storage equipment load constraints: is the heat load state of the thermal energy storage device, They are the lower and upper limits of the thermal load state of the thermal energy storage equipment respectively; Cold storage equipment load constraints: is the load-cooling state of the cold energy storage equipment. They are the lower and upper limits of the load cooling state of the cold energy storage equipment respectively; Wind turbine output constraints: Indicates the fan output. Respectively represent the minimum and maximum values ​​of the fan output.

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