Internal and external collaborative low-carbon economic optimization scheduling method for port integrated energy system

Abstract

The invention discloses an internal and external collaborative low-carbon economic optimization scheduling method for a port integrated energy system. The method comprises the following steps: S1, obtaining output prediction data, time-of-use electricity prices, capacities of various devices and output constraints of photovoltaic, wind power and cold and heat power loads; s2, building a green certificate-carbon transaction mechanism model and a comprehensive demand response model based on carbon flow characteristics; s3, constructing a port objective function and a port area objective function by taking the minimum operation cost after internal and external cooperation as an objective function; and S4, the port objective function solves a port external coordination optimization problem, the solved interaction power is transmitted to the basic energy supply unit, and the port area objective function solves a port area internal optimization problem. The method fully considers the carbon transaction mechanism of the harbor districts and the energy interaction among the multiple harbor districts, and can effectively improve the economic benefit and low-carbon characteristic of the comprehensive energy system of the harbor.

Description

Technical Field

[0001] The present invention relates to the field of optimized operation of integrated energy systems, and in particular to a low-carbon economic optimization scheduling method for an integrated energy system of a port with internal and external coordination. Background Art

[0002] As the carbon emission problem in the shipping industry becomes increasingly serious, ports, as shipping hubs, are in urgent need of green and low-carbon construction. The coordinated development of various energy systems is the current mainstream trend, so the integrated energy system of ports that can achieve the coupling and interconnection of multiple energy sources has gradually attracted attention from the energy industry.

[0003] In the existing research on the optimization of port integrated energy systems, most of them adopt the method of separate planning, separate design and independent operation, without considering the source-load economic regulation of the integrated energy system and the mutual assistance between various energy sources. Problems such as different load types and electricity consumption characteristics, large configuration redundancy of supply-side energy supply, and strong uncertainty in new energy output have not been effectively solved. At the same time, carbon emission constraints further reduce the effective ways to help each other among various energy sources. In order to achieve low-carbon economic operation of the port integrated energy system, on the one hand, it is necessary to interconnect, couple and complement each other among various energy sources; on the other hand, it is also necessary to adopt carbon trading and demand response mechanisms to improve energy use and increase the flexibility of the system. Therefore, it is of great research significance to take into account the economy and environmental protection of the system in the internal and external coordinated optimization scheduling of IPES. Summary of the invention

[0004] Purpose of the invention: The purpose of the present invention is to provide an internally and externally coordinated low-carbon economic optimization scheduling method for a port integrated energy system, which can effectively reduce the operating cost of the system and improve the low-carbon characteristics by fully considering the green-carbon trading mechanism of the port area and the energy interaction between multiple port areas.

[0005] Technical solution: A low-carbon economic optimization scheduling method for port integrated energy system with internal and external coordination, in which the port integrated energy system realizes transactions with the upper energy market through the port distribution network and natural gas network. The port is composed of multiple port areas, each of which is a basic energy supply unit. The ports exchange electric energy and thermal energy through interconnection lines. The equipment in the port area mainly includes photovoltaics, fans, gas boilers, electric refrigerators, combined heat and cold power generation, and power and heat storage devices; including the following steps:

[0006] S1, obtain output forecast data, time-of-use electricity prices, capacity of various equipment and output constraints of photovoltaic, wind power, and cooling and heating power loads;

[0007] S2, build a green certificate-carbon trading mechanism model and a comprehensive demand response model based on carbon flow characteristics;

[0008] S3, taking the minimum operating cost after internal and external coordination as the objective function, construct the port objective function and port area objective function;

[0009] S4, the port objective function solves the coordination optimization problem outside the port and transfers the obtained interactive power to the basic energy supply unit. The port area objective function solves the optimization problem inside the port area.

[0010] Furthermore, in step S2, based on the carbon flow characteristics of the port integrated energy system, a green certificate-carbon trading mechanism is established to calculate the carbon trading range and green certificate benefits;

[0011] The carbon flow model on the input side of the port integrated energy system is:

[0012] E e,t =P e,t ρ e,t

[0013] E g,t =P g,t ρ g,t

[0014] In the formula, E e,t 、E g,t are the carbon emissions caused by purchasing electricity and gas at time t; P e,t , P g,t are the power supplied by the power grid and gas grid at time t; ρ e,t , g,t are the carbon flow densities corresponding to the power supplied by the power grid and the gas grid respectively;

[0015] According to the conservation of carbon flow of equipment input and output, the carbon flow model of the energy hub is obtained as follows:

[0016]

[0017] In the formula, are the electrical, thermal and cooling power produced by CCHP at time t respectively; are the carbon flux densities of CCHP producing electricity, heat and cooling power respectively; are the power of thermal energy produced by GB at time t and the corresponding carbon flow density; are the electrical and cooling power produced by the EC at time t, respectively; are the carbon flux densities of the EC output electricity and cooling power, respectively;

[0018] The carbon emissions on the output side of the port's integrated energy system are:

[0019]

[0020] In the formula, E Le,t 、E Lh,t、E Lc,t are the carbon emissions of electricity, heating and cooling loads at time t; e PV,t 、e WT,t are the carbon potentials of photovoltaic and wind turbines respectively; e se,t 、e sh,t are the carbon potentials of the electrical and thermal energy storage devices when they release energy; P PV,t , P WT,t are the power of photovoltaic power and wind power at time t respectively; P se,t , P sh,t are the energy capacities of the electrical and thermal energy storage devices at time t respectively; is the thermal power of GB at time t;

[0021]

[0022] In the formula, is the carbon trading cost of load i at time t; They are the carbon trading ranges of marginal effects obtained by Shapley value method; is the carbon emission of load i at time t; is the carbon flow density of load i at time t; is the load of load i at time t; λ1, λ2 and λ3 are the three-tier carbon trading unit prices, in yuan / t;

[0023] The green certificate trading mechanism of the port integrated energy system is:

[0024]

[0025] In the formula, is the transaction cost of green certificates at time t; α GCT is the transaction price of green certificates; is the amount of green certificates bought / sold at time t; is the total power consumption at time t; is the amount of renewable energy consumed at time t; k is the quantitative coefficient, 1 green certificate corresponds to 1MW·h of renewable energy power; ω is the power consumption responsibility weight;

[0026] The comprehensive demand response model of the port is:

[0027]

[0028] Where P e,dr,t is the power load participating in the comprehensive demand response at time t, in MW; is the load reduction at time t; are the loads transferred from time t to other time periods and from other time periods to time t respectively;

[0029] Port power P after comprehensive demand responsee,port,t The requirements are:

[0030]

[0031] In the formula, is the port power demand without considering comprehensive demand response, in MW;

[0032] The controllable load constraints are:

[0033]

[0034] In the formula, The proportion of the port's electricity load that can be reduced in the total electricity load; are the proportion of power load transferred from period t to other periods and from other periods to period t to the total power load; They respectively represent whether to transfer the power load, 0 means no transfer, and 1 means transfer.

[0035] Further, in step S4, the objective function is established with the minimum cost of the whole day operation, and the cost function is composed of the energy interaction cost Energy storage costs The expression of the port objective function is:

[0036]

[0037] Where N is the total number of ports; C1 is the full-day operating cost, are the energy interaction cost and energy storage cost between the nth ports respectively; g e , g h The transaction costs for electricity and heat; is the transmitted electrical and thermal power of the ith EH equipment in the port area, They represent EH at time t respectively. i Xiang EH j , EH j Xiang EH i The delivered electric power, i and j represent the number of the EH equipment; They represent EH at time t respectively. i Xiang EH j , EH j Xiang EH i Whether to transmit power, 0 means no power is transmitted, 1 means power is transmitted; d i,j For EH i With EH j The distance between them; σ is the tie line loss rate, and energy cannot be transmitted in both directions on the same line at the same time; R ε is the operation and maintenance coefficient of the ε equipment, ε∈{ES,HS}; is the charge and discharge power corresponding to ES and HS devices;

[0038] Energy storage and equipment constraints are as follows:

[0039]

[0040] Interaction power constraints of tie lines:

[0041]

[0042] In the formula, is the upper and lower limits of energy storage of the ε device; is the upper and lower limits of the energy release of the ε device; P i,j,max is the maximum transmittable capacity in kW;

[0043] The objective function of the port area is to minimize the cost of full-day operation. The cost function is composed of the purchased energy cost C BUY,t , Equipment operating cost C OP,t , demand response cost C n,dr,t , Carbon trading costs and green certificate transaction cost C GCT,t The expression of the port area objective function is as follows:

[0044]

[0045] C BUY,t =P e,t g e,t +P g,t g g,t

[0046]

[0047] In the formula, C BUY,t , C OP,t , C dr,t , C co2,t , C GCT,t , are the port's energy purchase cost, equipment operation cost, demand response cost, carbon trading cost, and green certificate trading cost; g e,t , g g,t are time-of-use electricity and gas prices; ξ∈{CCHP,PV,WT,GB,ES,HS}; P ξ t is the operating capacity of each unit, in MW; R ξ is the operating cost coefficient of each equipment; are the load reduction and transfer costs, RMB / MWh respectively; T is the length of a dispatch cycle, Δt is the length of the time period considered;

[0048] The energy hub coupling constraints are as follows:

[0049]

[0050] Where: L e,t , L ship,t , L h,t , L c,t are the total demand of electrical load, ship shore power load, heating load and cooling load respectively; P PV,t , P WT,t are photovoltaic and wind power input respectively; H g is the calorific value of natural gas; and are the energy conversion efficiencies of CCHP electricity, heat, and cold, respectively; α, β, and γ are the distribution coefficients of CCHP electricity, heat, and cold energy, respectively; P ship,t is the total ship shore power load power at time t; m is the number of ships at the port at time t; is the shore power load power of the i-th ship at time t; is the state of the i-th ship connected to the port shore power at time t. When the ship is not connected to the port shore power

[0051] The power purchase and gas purchase and equipment power constraints are as follows:

[0052]

[0053] Where P e,max , P e,min are the upper and lower limits of electricity purchase respectively; P g,max , P g,min are the upper and lower limits of gas purchase volume respectively; P i is the power of each device; P i,min is the power lower limit of each device; P i,max The power limit for each device.

[0054] Furthermore, the obtained interaction power is the interaction power of electrical energy and thermal energy between ports.

[0055] Compared with the prior art, the present invention has the following significant effects:

[0056] 1. The present invention adopts a hierarchical optimization method based on target cascade analysis to solve the problem. The upper objective function solves the coordination optimization problem outside the port, and passes the obtained interactive power to the lower layer. The lower objective function solves the internal optimization problem of the port area, fully considering the carbon trading mechanism of the port area and the energy interaction between multiple port areas, which can effectively improve the economic benefits of the port comprehensive energy system;

[0057] 2. By considering the green-carbon trading mechanism and incentive-based comprehensive demand response, the present invention can achieve optimal scheduling of the port comprehensive energy system through energy interaction between port areas on the basis of coordinated operation of a single port area, thereby effectively reducing the operating cost of the system and improving the low-carbon characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a diagram of the operation model of the port integrated energy system in an embodiment of the present invention;

[0059] Figure 2 It is a flow chart of solving the low-carbon economic optimization method of the port integrated energy system in an embodiment of the present invention;

[0060] Figure 3 (a) is the carbon emission range of bulk carrier port area, (b) is the carbon emission range of cruise ship port area, and (c) is the carbon emission range of container ship port area;

[0061] Figure 4 (a) is the power dispatching strategy for bulk carrier port area, (b) is the power dispatching strategy for cruise ship port area, and (c) is the power dispatching strategy for container ship port area.

[0062] Figure 5 (a) is the thermal energy scheduling strategy for bulk cargo port area, (b) is the thermal energy scheduling strategy for cruise port area, and (c) is the thermal energy scheduling strategy for container port area. DETAILED DESCRIPTION

[0063] The present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0064] In this embodiment, the framework of the port integrated energy system is firstly constructed. Figure 1 As shown in the figure, the port integrated energy system realizes transactions with the upper energy market through the port distribution network and natural gas network. The port is composed of multiple port areas, each of which is a basic energy supply unit. The ports exchange electric energy and thermal energy through interconnection lines to meet the load demand on the user side. The equipment in the energy hub mainly includes photovoltaics, fans, gas boilers (GB), electric chillers (EC), combined cooling, heating and power (CCHP), and power and heat storage devices. Based on the carbon energy flow characteristics of the port integrated energy system (PIES), the green-carbon trading mechanism is introduced to calculate the carbon trading range and green certificate benefits; and according to the multi-energy characteristics of the port integrated energy system, an incentive-based comprehensive demand response model is established to guide the transformation of load energy use methods.

[0065] Figure 2 It is a flow chart of the low-carbon economic optimization method of the port integrated energy system in an embodiment of the present invention.

[0066] according to Figure 2 The hierarchical optimization method based on target cascade analysis shown in the figure performs system optimization scheduling, which specifically includes the following steps:

[0067] Step 1: Obtain output forecast data, time-of-use electricity prices, capacity sizes and output constraints of photovoltaic, wind power, and cooling and heating power loads.

[0068] Step 2: Build a green certificate-carbon trading mechanism model and a comprehensive demand response model;

[0069] (21) PIES Green-Carbon Trading Model

[0070] In this embodiment, based on the carbon flow characteristics of the port integrated energy system (PISE), a green certificate-carbon trading mechanism is introduced to calculate the carbon trading range and green certificate benefits.

[0071] The carbon flow model on the input side of PIES is:

[0072] E e,t =P e,t ρ e,t (1)

[0073] E g,t =P g,t ρ g,t (2)

[0074] In the formula, E e,t 、E g,t are the carbon emissions caused by purchasing electricity and gas at time t; P e,t , P g,t are the power supplied by the power grid and gas grid at time t; ρ e,t , g,t They are the carbon flow density corresponding to the power supplied by the power grid and the gas grid respectively.

[0075] According to the conservation of carbon flow of equipment input and output, the carbon flow model of the energy hub is obtained as follows:

[0076]

[0077] In the formula, are the electrical, thermal and cooling power produced by CCHP at time t respectively; are the carbon flux densities of CCHP producing electricity, heat and cooling power respectively; are the power of thermal energy produced by GB at time t and the corresponding carbon flow density; are the electrical and cooling power produced by the EC at time t, respectively; are the carbon flux densities of the EC output electricity and cooling power, respectively.

[0078] The carbon emissions on the output side of PIES are:

[0079]

[0080] In the formula, E Le,t 、E Lh,t 、E Lc,t are the carbon emissions of electricity, heating and cooling loads at time t; e PV,t 、e WT,t are the carbon potentials of photovoltaic and wind turbines respectively; e se,t 、e sh,t are the carbon potentials of the electrical and thermal energy storage devices when they release energy; P PV,t , P WT,t are the power of photovoltaic power and wind power at time t respectively; P se,t , P sh,t are the energy capacities of the electrical and thermal energy storage devices at time t respectively; is the thermal power of GB at time t.

[0081]

[0082] Where: is the carbon trading cost of load i at time t; They are the carbon trading ranges of marginal effects obtained by Shapley value method; is the carbon emission of load i at time t; is the carbon flow density of load i at time t; is the load amount of load i at time t; λ1, λ2 and λ3 are the three-level carbon trading unit prices, in yuan / t.

[0083] The green certificate trading mechanism of PIES is:

[0084]

[0085] In the formula, is the transaction cost of green certificates at time t; α GCT is the transaction price of green certificates; is the amount of green certificates bought / sold at time t; is the total power consumption at time t; is the renewable energy consumption at time t; k is the quantitative coefficient, 1 green certificate corresponds to 1MW·h of renewable energy electricity; ω is the power consumption responsibility weight.

[0086] (22) The port comprehensive demand response model is:

[0087]

[0088] Where P e,dr,t is the power load participating in the integrated demand response (IDR) at time t, in MW; is the load reduction at time t, in MW; They are the load transferred from time t to other time periods and the load transferred from other time periods to time t respectively.

[0089] Port power P after comprehensive demand response e,port,t The requirements are:

[0090]

[0091] Where: It is the port power demand without considering the comprehensive demand response, in MW.

[0092] The controllable load constraints are:

[0093]

[0094] Where: The proportion of the port's electricity load that can be reduced in the total electricity load; are the proportion of power load that can be transferred from period t to other periods and from other periods to period t to the total power load; They respectively represent whether to transfer the power load, 0 means no transfer, and 1 means transfer.

[0095] Step 3: Taking the minimum operating cost after internal and external coordination as the objective function, a two-layer optimization scheduling model of the port comprehensive energy system taking internal and external coordination into account is constructed;

[0096] In the two-layer optimization scheduling model of the port's integrated energy system taking into account internal and external coordination, the objective function of the port is established with the minimum operating cost throughout the day.

[0097] The port optimization goal is to minimize the cost of operation throughout the day, and the cost function is composed of energy interaction cost Energy storage costs The expression of the port objective function is:

[0098]

[0099] Where: N is the total number of ports, n represents the nth port; C1 is the full-day operation cost, is the energy interaction cost and energy storage cost between the nth port areas; g e , g h The transaction costs for electricity and heat; is the transmitted electrical and thermal power of the ith EH equipment in the port area, points means that at time t EH i Xiang EH j , EH j Xiang EH i The delivered electric power, i and j are the numbers of the EH equipment respectively; They represent EH at time t respectively. i Xiang EH j , EH j Xiang EH i Whether to transmit power, 0 means no power is transmitted, 1 means power is transmitted; d i,j For EH i With EH j The distance between them; σ is the tie line loss rate; in the same line at the same time, energy cannot be transmitted in both directions. ε is the operation and maintenance coefficient of the ε equipment, ε∈{ES,HS}; It is the charging and discharging power corresponding to ES (electricity storage) and HS (heat storage) equipment.

[0100] The constraints of the port objective function are: energy storage and equipment constraints and interconnection line interaction power constraints;

[0101] Energy storage and equipment constraints are as follows:

[0102]

[0103] Where: are the upper and lower limits of energy storage of the ε device, respectively; are the upper and lower limits of energy release of the ε device respectively.

[0104] The tie line interaction power constraints are as follows:

[0105]

[0106] Where: P i,j,max It is the maximum transmittable capacity in kW.

[0107] In the two-layer optimization scheduling model of the port integrated energy system taking into account internal and external coordination, the objective function established by the port area with the minimum full-day operation cost is:

[0108] The port area optimization goal is to minimize the full-day operating cost, and the cost function is composed of the purchased energy cost C BUY,t , Equipment operating cost C OP,t , demand response cost C n,dr,t , Carbon trading costs and green certificate transaction cost C GCT,tThe expression of the port area objective function is as follows:

[0109]

[0110] C BUY,t =P e,t g e,t +P g,t g g,t (twenty two)

[0111]

[0112] In the formula, C BUY,t , C OP,t , C dr,t , C GCT,t , are the port's energy purchase cost, equipment operation cost, demand response cost, carbon trading cost, and green certificate trading cost; g e,t , g g,t are time-of-use electricity and gas prices; ξ∈{CCHP,PV,WT,GB,ES,HS}; P ξ t is the operating capacity of each unit, in MW; R ξ is the operating cost coefficient of each equipment; are the load reduction and transfer costs, RMB / MWh respectively; T is the length of a scheduling cycle, and Δt is the length of the time period considered.

[0113] The constraints of the port area's objective function are: energy hub coupling constraints and power purchase and gas purchase and equipment power constraints;

[0114] The energy hub coupling constraints are as follows:

[0115]

[0116] Where: L e,t , L ship,t , L h,t , L c,t are the total demand of electrical load, ship shore power load, heating load and cooling load respectively; P PV,t , P WT,t are photovoltaic and wind power input respectively; H g is the calorific value of natural gas; and are the energy conversion efficiencies of CCHP electricity, heat and cold, respectively; α, β and γ are the corresponding distribution coefficients of CCHP electricity, heat and cold energy.

[0117]

[0118] Where: P ship,tis the total ship shore power load power at time t; m is the number of ships at the port at time t; is the shore power load power of the i-th ship at time t; is the state of the i-th ship connected to the port shore power at time t. When the ship is connected to the port shore power, When the ship is not connected to the port shore power

[0119] The power purchase and gas purchase and equipment power constraints are as follows:

[0120]

[0121] Where: P e,max , P e,min are the upper and lower limits of electricity purchase respectively; P g,max , P g,min are the upper and lower limits of gas purchase volume respectively; P i is the power of each device; P i,min is the power lower limit of each device; P i,max The power limit for each device.

[0122] Step 4: Solve the problem through a hierarchical optimization method based on target cascade analysis.

[0123] Formula (15) is used as the upper layer (i.e., port) objective function to solve the coordination optimization problem outside the port, and the obtained interaction power (i.e., the interaction power of electrical energy and thermal energy between ports) is transferred to the lower layer (i.e., port area). Formula (21) is used as the lower layer objective function to solve the optimization problem inside the port area.

[0124] In summary, by optimizing the port integrated energy system through the present invention, the carbon trading mechanism of the port area and the energy interaction between multiple port areas are fully considered, which can effectively improve the economic benefits and low-carbon characteristics of the port integrated energy system.

[0125] The simulation analysis is carried out by taking Suzhou inland port as an example to verify the effectiveness of the proposed method. The IPES consisting of bulk cargo port area, cruise port area and container port area is optimized and analyzed, and 6 scenarios are set as shown in Table 1.

[0126] Table 1 Scene settings

[0127] Scenario Carbon Trading Green Certificate Mechanism IDR EHs collaborative operation Ⅰ Ⅱ √ Ⅲ √ √ Ⅳ √ Ⅴ √ √ √ Ⅵ √ √ √ √

[0128] (1) Analysis of carbon trading results

[0129] The results of the tiered carbon trading of each port area are analyzed. Taking the carbon emission quota of the bulk carrier port area at t = 1h as an example, the interval is set, and the three carbon trading unit prices are 5, 10, and 20 yuan / t respectively, and the carbon quotas of three EHs (s = 1, 2, 3; respectively recorded as EH1, EH2, and EH3) in 24h are obtained as follows Figure 3 As shown in (a), (b) and (c).

[0130] It can be seen that the carbon emission quota of EH3 is larger than that of EH1 and EH2 because the container port has the highest load and the largest carbon emission. Since the port has a large demand for electricity and gas loads during the day, and the electricity and gas loads account for a large proportion, the carbon emission quota intervals of each EH from 9:00 to 20:00 are relatively high, belonging to the high-carbon period, while the intervals from 0:00 to 8:00 are relatively low, belonging to the low-carbon period. Compared with using a single interval to calculate the carbon emission responsibility cost of each period, it is more reasonable to use the IPES carbon trading model based on the Shapley value method.

[0131] (2) Scheduling results analysis

[0132] The optimization scheduling results under different scenarios are shown in Table 2.

[0133] Table 2 Optimization scheduling results under different scenarios

[0134]

[0135] Compared with scenarios Ⅰ, Ⅳ and Ⅱ, Ⅴ, when considering IPES hierarchical coordination optimization, the operating costs are reduced compared to the independent operation of each port area. Therefore, the internal and external coordination optimization of IPES makes energy use more reasonable by realizing the sharing of energy among various port areas. When low-carbon economic optimization is not considered, compared with scenarios Ⅰ and Ⅳ, the port's electricity purchase amount increases, and carbon emissions increase accordingly, thereby increasing the port's carbon emissions. Therefore, although the IPES internal and external coordination strategy has certain economic benefits, it will bring certain negative effects in terms of carbon emissions.

[0136] When only the carbon trading mechanism is considered without considering the green certificate mechanism, compared with scenarios Ⅰ and Ⅱ, the operating cost, carbon emissions and electricity purchase volume are all reduced, but the gas purchase volume increases by 10.9MW·h. This is because under the carbon trading mechanism, the port will be more inclined to use cleaner CCHP to supply electricity. When considering both the carbon trading mechanism and the green certificate mechanism, compared with scenarios Ⅳ and Ⅴ, the operating cost is reduced by 2,086 yuan, carbon emissions are reduced by 8.2 tons, electricity purchase volume is reduced by 8.3MW·h, and gas purchase volume increases by 16.3MW·h. Therefore, considering green certificate trading while considering carbon trading will reduce carbon benefits, but it can bring green certificate benefits to the system while reducing the carbon emissions of the system. Comparing scenarios Ⅱ and Ⅲ, it can be seen that after the introduction of the green certificate mechanism, carbon emissions were reduced by 1.1 tons, and the operating cost was reduced by 979 yuan. It shows that the green certificate mechanism further promotes the reduction of carbon emissions and helps to balance the economic benefits of the system. Comparing scenarios V and VI, when considering carbon trading at the same time, scenario VI takes demand response into account, and the total cost of the port energy system is reduced by 3,255 yuan, the amount of electricity purchased is reduced, the cost of purchasing natural gas is increased, and carbon emissions are reduced. This shows that the introduction of IDR has enabled IPES to increase the utilization of the gas grid, reduce the energy supply of the power grid, and thus reduce carbon emissions. Taking scenario VI as an example, the dispatch strategies of the three IPES ports are as follows: Figure 4 As shown in (a), (b), and (c), Figure 5 As shown in (a), (b) and (c).

[0137] The present invention provides a low-carbon economic optimization scheduling method for a port integrated energy system with internal and external coordination. By considering the carbon trading mechanism of green power certificates and the incentive-based comprehensive demand response, a two-layer optimization scheduling model for a port integrated energy system taking into account internal and external coordination is established; a hierarchical optimization method based on target cascade analysis is used for solving the problem to achieve low-carbon economic scheduling of the port. The optimization model fully considers the carbon trading mechanism of the port area and the energy interaction between multiple port areas, effectively improving the economic benefits and low-carbon characteristics of the port integrated energy system.

[0138] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A low-carbon economic optimization scheduling method for port integrated energy system with internal and external coordination, wherein: The port integrated energy system realizes transactions with the upper energy market through the port distribution network and natural gas network. The port is composed of multiple port areas, each of which is a basic energy supply unit. The ports exchange electric energy and thermal energy through interconnection lines. The equipment in the port area mainly includes photovoltaics, fans, gas boilers, electric refrigerators, combined heat and power generation, and power and heat storage devices. It is characterized by the following steps: S1, obtain output forecast data, time-of-use electricity prices, capacity of various equipment and output constraints of photovoltaic, wind power, and cooling and heating power loads; S2, build a green certificate-carbon trading mechanism model and a comprehensive demand response model based on carbon flow characteristics; S3, taking the minimum operating cost after internal and external coordination as the objective function, construct the port objective function and port area objective function; S4, the port objective function solves the coordination optimization problem outside the port and transfers the obtained interactive power to the basic energy supply unit. The port area objective function solves the optimization problem inside the port area.

2. The low-carbon economy optimization scheduling method for the port integrated energy system with internal and external coordination according to claim 1 is characterized in that: In step S2, based on the carbon flow characteristics of the port integrated energy system, a green certificate-carbon trading mechanism is established to calculate the carbon trading range and green certificate benefits; The carbon flow model on the input side of the port integrated energy system is: E e,t =P e,t r e,t E g,t =P g,t r g,t In the formula, E e,t 、E g,t are the carbon emissions caused by purchasing electricity and gas at time t; P e,t , P g,t are the power supplied by the power grid and gas grid at time t respectively; ρ e,t , g,t are the carbon flow densities corresponding to the power supplied by the power grid and the gas grid respectively; According to the conservation of carbon flow of equipment input and output, the carbon flow model of the energy hub is obtained as follows: In the formula, are the electrical, thermal and cooling power produced by CCHP at time t respectively; are the carbon flux densities of CCHP producing electricity, heat and cooling power respectively; are the power of thermal energy produced by GB at time t and the corresponding carbon flow density; are the electrical and cooling power produced by the EC at time t, respectively; are the carbon flux densities of the EC output electricity and cooling power, respectively; The carbon emissions on the output side of the port's integrated energy system are: In the formula, E Le,t 、E Lh,t 、E Lc,t are the carbon emissions of electricity, heating and cooling loads at time t; e PV,t 、e WT,t are the carbon potentials of photovoltaic and wind turbines respectively; e se,t 、e sh,t are the carbon potentials of the electrical and thermal energy storage devices when they release energy; P PV,t , P WT,t are the power of photovoltaic power and wind power at time t respectively; P se,t , P sh,t are the energy capacities of the electrical and thermal energy storage devices at time t respectively; is the thermal power of GB at time t; In the formula, is the carbon trading cost of load i at time t; They are the carbon trading ranges of marginal effects obtained by Shapley value method; is the carbon emission of load i at time t; is the carbon flow density of load i at time t; is the load of load i at time t; λ1, λ2 and λ3 are the three-tier carbon trading unit prices, in yuan / t; The green certificate trading mechanism of the port integrated energy system is: In the formula, is the transaction cost of green certificates at time t; α GCT is the transaction price of green certificates; is the amount of green certificates bought / sold at time t; is the total power consumption at time t; is the amount of renewable energy consumed at time t; k is the quantitative coefficient, 1 green certificate corresponds to 1MW·h of renewable energy power; ω is the power consumption responsibility weight; The comprehensive demand response model of the port is: Where P e,dr,t is the power load participating in the comprehensive demand response at time t, in MW; is the load reduction at time t; are the loads transferred from time t to other time periods and from other time periods to time t respectively; Port power P after comprehensive demand response e,port,t The requirements are: In the formula, is the port power demand without considering comprehensive demand response, in MW; The controllable load constraints are: In the formula, The proportion of the port's electricity load that can be reduced in the total electricity load; are the proportion of power load transferred from period t to other periods and from other periods to period t to the total power load; They respectively represent whether to transfer the power load, 0 means no transfer, and 1 means transfer.

3. The low-carbon economy optimization scheduling method for port integrated energy system with internal and external coordination according to claim 1 is characterized in that: In step S4, the objective function is established with the minimum cost of running all day, and the cost function is composed of the energy interaction cost Energy storage costs The expression of the port objective function is: Where N is the total number of ports; C1 is the full-day operating cost, are the energy interaction cost and energy storage cost between the nth ports respectively; g e , g h The transaction costs for electricity and heat; is the transmitted electrical and thermal power of the ith EH equipment in the port area, They represent EH at time t respectively. i Xiang EH j , EH j Xiang EH i The delivered electric power, i and j represent the number of the EH equipment; They represent EH at time t respectively. i Xiang EH j , EH j Xiang EH i Whether to transmit power, 0 means no power is transmitted, 1 means power is transmitted; d i,j For EH i With EH j The distance between them; σ is the tie line loss rate, and energy cannot be transmitted in both directions on the same line at the same time; R ε is the operation and maintenance coefficient of the ε equipment, ε∈{ES,HS}; is the charge and discharge power corresponding to ES and HS devices; Energy storage and equipment constraints are as follows: Interaction power constraints of tie lines: In the formula, is the upper and lower limits of energy storage of the ε device; is the upper and lower limits of the energy release of the ε device; P i,j,max is the maximum transmittable capacity in kW; The objective function of the port area is to minimize the cost of full-day operation. The cost function is composed of the purchased energy cost C BUY,t , Equipment operating cost C OP,t , demand response cost C n,dr,t , Carbon trading costs and green certificate transaction cost C GCT,t The expression of the port area objective function is as follows: C BUY,t =P e,t g e,t +P g,t g g,t In the formula, C BUY,t , C OP,t , C dr,t , C GCT,t , are the port's energy purchase cost, equipment operation cost, demand response cost, carbon trading cost, and green certificate trading cost; g e,t , g g,t are time-of-use electricity and gas prices; ξ∈{CCHP,PV,WT,GB,ES,HS}; P ξ t is the operating capacity of each unit, in MW; R ξ is the operating cost coefficient of each equipment; are the load reduction and transfer costs, RMB / MWh respectively; T is the length of a dispatch cycle, Δt is the length of the time period considered; The energy hub coupling constraints are as follows: Where: L e,t , L ship,t , L h,t , L c,t are the total demand of electrical load, ship shore power load, heating load and cooling load respectively; P PV,t , P WT,t are photovoltaic and wind power input respectively; H g is the calorific value of natural gas; and are the energy conversion efficiencies of CCHP electricity, heat, and cold, respectively; α, β, and γ are the distribution coefficients of CCHP electricity, heat, and cold energy, respectively; P ship,t is the total ship shore power load power at time t; m is the number of ships at the port at time t; is the shore power load power of the i-th ship at time t; is the state of the i-th ship connected to the port shore power at time t. When the ship is not connected to the port shore power The power purchase and gas purchase and equipment power constraints are as follows: Where P e,max , P e,min They are the upper and lower limits of electricity purchase respectively; P g,max , P g,min are the upper and lower limits of gas purchase volume respectively; P i is the power of each device; P i,min is the power lower limit of each device; P i,max The power limit for each device.

4. The low-carbon economy optimization scheduling method for port integrated energy system with internal and external coordination according to claim 1 is characterized in that: The obtained interaction power is the interaction power of electrical energy and thermal energy between ports.

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