Universal modeling and optimizing method and system for multi-energy micro-grid energy management-oriented LNG cold energy gradient utilization

Abstract

The invention discloses an LNG cold energy gradient utilization general modeling and optimizing method and system for multi-energy micro-grid energy management, and the method comprises the steps: considering the transfer coupling and loss of cold energy based on the gradient utilization purpose and equipment parameters, and building a utilization general model for each stage of the cold energy gradient utilization process; the method comprises the following steps: establishing a multi-energy micro-grid energy optimization model containing cold energy gradient utilization, and carrying out energy management cooperation on a cold energy gradient utilization link and a multi-energy micro-grid based on a multi-energy micro-grid architecture and distributed energy characteristics by taking system economic carbon reduction operation as an optimization target; and converting the energy optimization model into a two-stage stochastic optimization model based on multiple scenes and solving the two-stage stochastic optimization model according to the uncertainty of the source load and the operation characteristics of the multi-energy micro-grid equipment to obtain a multi-energy micro-grid energy management decision of cold energy gradient utilization. According to the invention, integration and collaboration are carried out on a universal model for gradient utilization of cold energy and energy consumption management of the multi-energy micro-grid, and an energy management decision with economic low-carbon property and high energy efficiency property is obtained through optimization.

Description

Technical Field

[0001] The present invention relates to a multi-energy system energy optimization method, in particular to a general modeling and optimization method and system for liquefied natural gas (LNG) cold energy cascade utilization for multi-energy microgrid energy management. Background Art

[0002] Natural gas can be stored and transported in the form of liquefied natural gas (LNG). When it arrives at the LNG receiving station, it is gasified and then delivered to users. During the LNG gasification process, a large amount of high-quality cold energy is released. If this cold energy is not fully utilized, it will not only cause a huge waste of energy, but also may cause cold pollution to nearby sea areas. Efficient use of LNG cold energy can save energy and reduce consumption, reduce carbon emissions, and bring significant social, economic and environmental benefits.

[0003] Due to the wide temperature variation range of the LNG gasification process, a single method cannot fully utilize cold energy of different grades. Cold energy cascade utilization technology can fully utilize the cold energy of each temperature zone according to the needs of different temperature ranges, thereby reducing waste. In addition, fully coordinating the cold energy cascade utilization with the multi-energy microgrid system of the LNG receiving station can effectively improve energy utilization efficiency and enhance the economy and low carbon nature of the multi-energy microgrid system.

[0004] Although there has been great progress in the research on LNG cold energy cascade utilization, there are still limitations. At present, LNG cold energy utilization is mostly modeled and simulated from the perspective of chemical thermodynamics, and is rarely used in energy management. In addition, a relatively universal LNG cold energy cascade utilization model has not been proposed, and simulation is limited to the equipment level. Therefore, it is urgent to propose a universal modeling and optimization method for liquefied natural gas (LNG) cold energy cascade utilization for multi-energy microgrid energy management to improve the above-mentioned series of problems existing in the current LNG cold energy cascade utilization. Summary of the invention

[0005] Purpose of the invention: In view of the problems existing in the prior art, the purpose of the present invention is to provide a general modeling and optimization method and system for the cascade utilization of liquefied natural gas (LNG) cold energy for energy management of multi-energy microgrids. By coupling the universal model of cascade utilization of cold energy with the energy demand of the multi-energy microgrid, the energy management decision with both economical, low-carbon and high energy efficiency is optimized, providing a new solution for the research on cascade utilization of LNG cold energy and the operation optimization of the multi-energy microgrid system.

[0006] Technical solution: The general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management described in the present invention comprises the following steps:

[0007] (1) According to the purpose and equipment parameters of LNG cold energy cascade utilization, a general model for LNG cold energy utilization at each stage is established, including: dividing the LNG cold energy utilization stages and determining the purpose of cold energy utilization at each stage; according to the equipment parameters of cold energy utilization at each stage, determining the upper and lower limits of the input cold energy required for equipment operation, and establishing the equipment operation constraint model for cold energy utilization at each stage; according to the on / off time limit of the cold energy utilization equipment, establishing the time constraint model for cold energy utilization at each stage; according to the cold energy loss caused by heat transfer during the cold energy utilization process and the power consumption of the cold energy utilization equipment, establishing the loss model for cold energy utilization at each stage; according to the actual cold energy power and the cold energy heat transfer loss power, establishing the coupling model of cold energy utilization at each stage and the output of the corresponding purpose;

[0008] (2) establishing a transfer coupling model for LNG cold energy cascade utilization based on the LNG gasification model, wherein the LNG gasification model includes power constraints of the LNG gasification station and on / off time constraints of the LNG gasification station, and the transfer coupling model for LNG cold energy cascade utilization includes: the cold energy power that can be recovered and utilized in the LNG gasification process is greater than or equal to the sum of the actual cold energy power of each stage, and the total power consumption in the cold energy utilization process is the sum of the power consumption of the cold energy utilization equipment in each stage;

[0009] (3) Based on the multi-energy microgrid architecture and the distributed energy contained therein, a multi-energy microgrid energy optimization model with cascade utilization is established. The multi-energy microgrid energy optimization model takes minimizing the operating cost and carbon emissions of the multi-energy microgrid system in a specified period of time as the optimization objective function, and includes the distributed energy operation and multi-energy conversion constraints, energy balance constraints, and power purchase and sale constraints between the multi-energy microgrid system and the power market in the multi-energy microgrid system. The operating cost of the multi-energy microgrid system in the objective function includes the transaction cost in the power market, the operating cost and startup cost of the cold energy utilization equipment, and the operating cost is determined by the output of the cold energy utilization stage and the unit cost of the equipment operation;

[0010] (4) According to the uncertainty of source and load and the operating characteristics of the multi-energy microgrid equipment, the multi-energy microgrid energy optimization model is transformed into a two-stage stochastic optimization model based on multiple scenarios and solved to obtain the energy management decision of the multi-energy microgrid with cascaded utilization of LNG cold energy.

[0011] Furthermore, in the step (1), the equipment operation constraint model for the cold energy utilization in each stage is specifically as follows: the cold energy power actually used in the m stage in the t period does not exceed the upper limit of the cold energy input power of the stage and is not lower than the lower limit of the cold energy input power of the stage;

[0012] The time constraint model of cold energy utilization in each stage is as follows: the startup time and shutdown time of the cold energy utilization equipment meet the specified startup and shutdown time limits;

[0013] The loss model of cold energy utilization at each stage is established based on the relationship between cold energy loss and utilized cold energy, and the relationship between the power consumption of cold energy utilization equipment and utilized cold energy;

[0014] The coupling model of the cold energy used in each stage and the corresponding output is expressed as: In the formula, Represents the output of stage m during period t; η m is the utilization rate; It represents the cooling power actually used in stage m during period t; It represents the heat transfer power loss during the period t.

[0015] Furthermore, in the LNG gasification model, the power limit of the LNG gasification station is specifically as follows: the gasification power of the LNG gasification station in period t does not exceed the upper limit of the gasification power of the LNG gasification station and does not fall below the lower limit of the gasification power of the LNG gasification station;

[0016] The startup and shutdown time constraints of the LNG gasification station are as follows: the startup and shutdown time of the LNG gasification station must comply with the specified startup and shutdown time constraints;

[0017] In the transfer coupling model of LNG cold energy cascade utilization, the recoverable cold energy power is expressed as: In the formula, represents the cold energy power that can be recovered and utilized during the LNG gasification process during period t; η lng represents the efficiency coefficient of LNG cold energy recovery and utilization; q ng is the calorific value of natural gas.

[0018] Furthermore, in step (3), the distributed energy operation and multi-energy conversion constraints in the multi-energy microgrid system include the operation, multi-energy conversion and carbon emission constraints of the micro gas turbine, the electric refrigerator, the normal temperature and high pressure gas storage tank, and the battery energy storage device, as well as the renewable energy power generation constraints;

[0019] Energy balance constraints include electricity, cooling, gas and carbon energy balance constraints;

[0020] The power purchase and sale constraints of the multi-energy microgrid system in the power market include the electricity price set according to the power purchase and sale transaction history and forecast data of the power market on the day before and within the day, as well as the corresponding upper and lower limits of power purchase and sale transmission.

[0021] Furthermore, in step (3), the transaction cost in the electricity market is calculated as follows: In the formula, is the transaction cost in period t, They represent the electricity purchase and sales prices in the electricity market during period t the day before, They represent the power purchase and power sales in the day-ahead power market during period t, They represent the purchase and sale prices of electricity in the electricity market during the t period of the day, They represent the power purchase and sales in the intraday power market during period t, respectively, and τ is the length of the trading period;

[0022] The operating cost of cold energy utilization equipment is calculated as follows: In the formula, is the operating cost of the cooling energy utilization equipment during period t, c lng_m represents the unit cost of operating the cold energy utilization equipment in stage m, is the output of stage m usage in period t;

[0023] The startup cost of cold energy utilization equipment is calculated as follows: In the formula, is the equipment startup cost during period t, represents the startup cost of LNG gasification equipment; represents the microturbine startup cost; represents the startup cost of the cold energy utilization equipment in stage m; It is a 0-1 variable used to indicate the start-up indication of LNG gasification, micro gas turbine and m-stage cold energy utilization.

[0024] Furthermore, the step (4) comprises:

[0025] (4.1) Based on the predicted expected values ​​of renewable energy output and load and the probability distribution of uncertainty, multiple sets of scenarios are randomly generated to simulate the possible actual conditions of source and load;

[0026] (4.2) According to the operation characteristics of the equipment in the multi-energy microgrid, the model in step (3) is transformed into a two-stage stochastic optimization model based on multiple scenarios. The corresponding mathematical matrix expression is:

[0027]

[0028] Where: n is the probability of the uncertainty scenario, n represents the uncertainty scenario, u n represents uncertain variables, including renewable energy output and electrical cooling load power; x represents the day-ahead phase variables, including binary variables for controlling the start and stop of cooling energy utilization equipment, the start and stop of LNG gasification, the start and stop of micro gas turbines, and the power purchased and sold in the day-ahead power market, which should be maintained as a one-dimensional variable related to the dispatch period; y nrepresents the optimization variables in the intraday stage, mainly including the operation of cold energy utilization equipment, LNG gasification, micro gas turbine operation, electric refrigeration machine refrigeration, normal temperature and high pressure gas storage tank storage and intraday power market transaction related variables, which should be converted into two-dimensional variables related to scenarios and time; C is the coefficient matrix of the objective function of the day-ahead stage, mainly the day-ahead transaction electricity price and equipment startup cost; E is the coefficient matrix of the objective function of the intraday stage, mainly the day-ahead transaction electricity price, carbon tax price and unit cost of cold energy utilization equipment; g(x,y n ,u n ) represents all the equality constraints contained in the above model, h(x,y n ) represents all inequality constraints;

[0029] (4.3) Based on the above two-stage stochastic optimization model, the mathematical programming solver is called to optimize and solve the model to obtain the optimal values ​​of the energy management decision variables of the multi-energy microgrid with cascaded utilization of LNG cold energy.

[0030] Furthermore, the step (4) further comprises:

[0031] (4.4) Based on the more accurate forecast values ​​of the source and load during the day, the multi-energy microgrid energy optimization model with cascade utilization in step (3) is used to fix the optimal value of the day-ahead variable obtained by optimization (4.3), and the operating variables of each scheduling period during the day are re-optimized to obtain the optimal value of the microgrid operation decision during the day.

[0032] A general modeling and optimization system for LNG cold energy cascade utilization for multi-energy microgrid energy management, including:

[0033] The general model construction module for cold energy utilization is used to establish a general model for the utilization of LNG cold energy at each stage according to the purpose and equipment parameters of the cascade utilization of LNG cold energy, including: dividing the LNG cold energy utilization stages and determining the purpose of cold energy utilization at each stage; determining the upper and lower limits of the input cold energy required for equipment operation according to the equipment parameters of cold energy utilization at each stage, and establishing the equipment operation constraint model for cold energy utilization at each stage; establishing the time constraint model for cold energy utilization at each stage according to the on / off time limit of the cold energy utilization equipment; establishing the loss model for cold energy utilization at each stage according to the cold energy loss caused by heat transfer during the cold energy utilization process and the power consumption of the cold energy utilization equipment; establishing the coupling model of cold energy utilization at each stage and the output of the corresponding purpose according to the actual cold energy power and the cold energy heat transfer loss power;

[0034] A cold energy cascade utilization transfer coupling model building module is used to establish a transfer coupling model for LNG cold energy cascade utilization according to an LNG gasification model, wherein the LNG gasification model includes power limits of an LNG gasification station and on / off time constraints of an LNG gasification station, and the transfer coupling model for LNG cold energy cascade utilization includes: the cold energy power that can be recovered and utilized during the LNG gasification process is greater than or equal to the sum of the actual cold energy powers at each stage, and the total power consumption in the cold energy utilization process is the sum of the power consumption of the cold energy utilization equipment at each stage;

[0035] A multi-energy microgrid energy optimization model construction module including cascade utilization is used to establish a multi-energy microgrid energy optimization model including cascade utilization according to the multi-energy microgrid architecture and the distributed energy contained therein. The multi-energy microgrid energy optimization model takes minimizing the operating cost and carbon emissions of the multi-energy microgrid system in a specified period of time as the optimization objective function, and includes distributed energy operation and multi-energy conversion constraints, energy balance constraints, and power purchase and sale constraints between the multi-energy microgrid system and the power market in the multi-energy microgrid system. The operating cost of the multi-energy microgrid system in the objective function includes the transaction cost in the power market, the operating cost and startup cost of the cold energy utilization equipment, and the operating cost is determined by the output of the cold energy utilization stage and the unit cost of the equipment operation;

[0036] The optimization model conversion and solution module is used to convert the multi-energy microgrid energy optimization model into a two-stage stochastic optimization model based on multiple scenarios and solve it according to the uncertainty of source and load and the operating characteristics of the multi-energy microgrid equipment, so as to obtain the energy management decision of the multi-energy microgrid with cascaded utilization of LNG cold energy.

[0037] The present invention also provides a computer device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management as described above are implemented.

[0038] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management as described above.

[0039] Beneficial effects: The present invention proposes a universal model for the utilization of LNG cold energy at each stage, which simplifies the modeling process of the cascade utilization of cold energy; when considering the coupling relationship of cold energy utilization at each stage, it does not strictly limit the proportion of cold energy at each stage, making the coupling relationship more flexible and tight; the cascade utilization of LNG cold energy is introduced into the multi-energy microgrid for optimization, which improves the energy utilization rate of the system, reduces the overall operating cost of the system, and reduces carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0041] Figure 2 is a typical daily power curve of renewable energy and load;

[0042] Figure 3 This is a schematic diagram of energy flow in an embodiment of the present invention;

[0043] Figure 4 The gas load supply and demand results after optimization of the present invention;

[0044] Figure 5 The carbon load supply and demand results after optimization of the present invention;

[0045] Figure 6 The power load supply and demand results after optimization of the present invention;

[0046] Figure 7 The trading conditions of the day-ahead and intraday electricity markets after optimization by the present invention;

[0047] Figure 8 This is the cooling load supply and demand result after optimization of the present invention. DETAILED DESCRIPTION

[0048] The technical solution of the present invention is explained and illustrated in detail below in conjunction with the accompanying drawings, specific drawings and specific embodiments.

[0049] The general modeling and optimization method for liquefied natural gas (LNG) cold energy cascade utilization for multi-energy microgrid energy management of the present invention comprises the following steps:

[0050] Step 1: According to the purpose and equipment parameters of LNG cold energy cascade utilization, a general model for the utilization of LNG cold energy at each stage is established.

[0051] The cold energy released during LNG gasification can be divided into multiple stages, and the uses of LNG cold energy in different temperature zones can be summarized as follows: deep cold section, which can be used for air separation (applicable to large receiving stations), low-temperature carbon capture, and low-temperature crushing (requirements for site selection); medium cold section, which can be used for cold energy power generation; shallow cold section, which can be used for low-temperature cold storage, air conditioning system, data center cooling, etc. The present invention first determines the uses of LNG cold energy in the system, divides the LNG cold energy utilization stages according to the different temperature zones corresponding to the uses, and uses m to represent each stage; and uses M to represent the output of each stage.

[0052] In order to make the specific implementation methods described in this article detailed and easy to understand, the multi-energy microgrid system of LNG cold energy cascade utilization of low-temperature carbon capture (deep cooling) - cold energy power generation (intermediate cooling) - direct cooling (shallow cooling) is taken as an example. The low-temperature carbon capture stage is represented by c, and its output is the carbon flow obtained by carbon capture, represented by C; the cold energy power generation stage is represented by p, and the output is the power generation power, represented by P; the direct cooling stage is represented by co, and the output is the direct cooling power, represented by CO.

[0053] According to the equipment parameters of cold energy utilization at each stage, the upper and lower limits of the input cold energy required for equipment operation are determined, and the equipment operation constraint model of cold energy utilization at each stage of LNG is established, namely:

[0054]

[0055] In the formula, m represents the stage of cold energy utilization, They represent the lower and upper limits of the cooling energy input power in this stage respectively; It is a 0-1 variable, used to indicate whether the cold energy utilization process is started or stopped at this stage;

[0056] Cold energy utilization equipment cannot be started or stopped at any time, and its minimum start-up time is The lower limit of shutdown time is The mathematical expression of the constraint is:

[0057]

[0058] In the process of cold energy utilization, heat transfer will cause the loss of cold energy. At the same time, the cold energy utilization equipment has power consumption. The cold energy loss and the utilized cold energy can be regarded as a linear relationship, and the power consumption and the utilized cold energy can be regarded as a linear relationship. The loss model of cold energy utilization in each stage is established, and the corresponding mathematical expression is:

[0059]

[0060] Where: represents the heat transfer power loss during the period t, v m is the loss coefficient, It represents the cooling power actually used in stage m during period t; Indicates the power consumption of the equipment during period t; k m is the power consumption coefficient; it is worth noting that other functions can also be used to express the relationship between cooling loss and cooling used, and between power consumption and cooling used.

[0061] A coupling model between the cold energy used in each stage and the output of the corresponding purpose is established, and its corresponding mathematical expression is:

[0062]

[0063] Where: It represents the output of the cold energy utilization phase during the period t; η m is the utilization rate;

[0064] It is worth noting that the general cold energy utilization model in step 1 is applicable to common cold energy utilization scenarios and tiered divisions.

[0065] Step 2: Establish a transfer coupling model for cascade utilization of LNG cold energy.

[0066] The transfer coupling model of LNG cold energy cascade utilization includes:

[0067] (1) LNG gasification model:

[0068] The power limit of the LNG gasification station corresponds to the mathematical expression:

[0069]

[0070] In the formula, It represents the gasification power of the LNG gasification station during period t; It is a 0-1 variable, used to indicate the switch of the LNG gasification device; Indicates the upper and lower limits of the gasification power of the LNG gasification station.

[0071] LNG gasification stations cannot be flexibly started and stopped, and their lower limit of start-up time is The lower limit of shutdown time is The mathematical expression of its operating time limit is similar to the time constraint (2) of the cold energy utilization equipment and will not be repeated here.

[0072] (2) Transfer coupling model of cold energy cascade utilization:

[0073] During the LNG gasification process, the relationship between the recyclable cold energy and the gasification power is:

[0074]

[0075] In the formula, It represents the cold energy power that can be recovered and utilized during the LNG gasification process during period t, in kW; η lng represents the efficiency coefficient of LNG cold energy recovery and utilization; q ng is the calorific value of natural gas.

[0076] The mathematical expression corresponding to the transfer coupling of the released cold energy through each stage is:

[0077]

[0078] The mathematical expression of the total power consumption of the cold energy cascade utilization equipment at each stage is:

[0079]

[0080] In the formula, It represents the total power consumption of equipment in all stages of the cold energy utilization process.

[0081] Step 3: Based on the multi-energy microgrid architecture and the distributed energy contained, establish a multi-energy microgrid energy optimization model with cascade utilization.

[0082] The energy optimization model of multi-energy microgrid with cascade utilization includes:

[0083] (1) Distributed energy operation and multi-energy conversion constraints: Based on the multi-energy microgrid architecture, the operation constraints and energy conversion constraints of distributed energy, energy-consuming equipment, load and cold energy cascade utilization equipment in the system are established, including:

[0084] Operating constraints of micro gas turbines:

[0085]

[0086] Where: represents the electric power and gas power of the micro gas turbine during period t, η gt_p is electrical efficiency; Indicates the upper and lower limits of electric power; is a 0-1 variable, used to indicate the micro gas turbine switch; represents the carbon emissions generated by the micro gas turbine during period t, kg / h; λ g_co2 is the carbon emission coefficient per unit gas power, h ng is the calorific value of natural gas per unit volume.

[0087] Gas turbine equipment cannot be started or stopped at any time, and its minimum start-up time is The lower limit of shutdown time is The mathematical expression of the constraint is shown in formula (2), which will not be repeated here.

[0088] Operating constraints of the electric refrigerator in the system:

[0089]

[0090]

[0091] Where: represents the cooling power of the electric refrigerator during period t; represents the power consumption of the electric refrigerator during period t; η ec Indicates the refrigeration efficiency of the electric refrigerator; Indicates the upper limit of cooling power of the electric refrigerator.

[0092] The multi-energy system adds a high-pressure gas storage tank to meet the supply and demand balance of gas load by storing and releasing natural gas. The power consumption and gas storage capacity of the gas storage tank are considered to be in a linear relationship, and its operation constraints are:

[0093]

[0094] Where: Indicates the natural gas storage SOC state of the gas tank during period t; V gs is the capacity of the gas tank; η gs is the natural gas compression rate; Δt is the scheduling step length; They represent the lower and upper limits of the SOC of the natural gas storage tank respectively; It is a 0-1 variable, used to indicate the filling and degassing status of the gas tank; Respectively represent the storage and release power of the gas storage tank; k gs_p The linear coefficient representing the power consumption, Indicates the power consumption of the gas tank at normal temperature.

[0095] The operating constraints for renewable energy generation are:

[0096]

[0097] Where: represents the renewable energy power generation during period t, Represents the upper limit of renewable energy power generation.

[0098] (2) Establish a trading model for multi-energy microgrid systems in the power market:

[0099] The electricity price and the corresponding upper and lower limits of electricity purchase and sale transmission are set based on the history and forecast data of electricity purchase and sale transactions in the electricity market on the previous day and within the day.

[0100] The constraints for day-ahead market transactions are:

[0101]

[0102] Where: They represent the power purchased / sold by the port MEMG in the power market during the day-ahead period t respectively; is a 0-1 variable used to indicate the state of electricity purchase / sale in the day-ahead electricity market; Indicates the upper limit of power purchased / sold in the day-ahead power market.

[0103] The constraints for intraday market trading are:

[0104]

[0105] Where: They represent the power purchased / sold by the port MEMG in the power market during period t within the day; It is a 0-1 variable, used to indicate the state of buying / selling electricity in the intraday electricity market; Indicates the upper limit of power purchased / sold in the intraday electricity market.

[0106] (3) Establish energy balance constraints. The overall energy balance constraints include electricity, cooling, gas and carbon energy balance constraints:

[0107]

[0108] Where: represents the power of cold energy generation, Indicates the electrical load power; Indicates gas load power; Indicates the direct cooling power of cold energy. represents the direct cooling loss, Indicates cooling load power; Indicates carbon emissions during period t, kg / h; Indicates the carbon flow obtained from carbon capture, kg / h.

[0109] (4) Establishing an optimization objective function for economic low carbon:

[0110] The economic and low-carbon optimization objective function is to minimize the daily operating cost and carbon emissions of the multi-energy microgrid system:

[0111]

[0112] The total cost of the system in period t

[0113]

[0114] The transaction cost of the system in the electricity market during period t for:

[0115]

[0116] Where: They represent the electricity purchase and sales prices in the electricity market during period t the day before, They represent the purchase and sale prices of electricity in the intraday power market during period t, in units of yuan / kWh; τ is the length of the trading period, such as 15 minutes, 1 hour, etc.;

[0117] Carbon emission cost of the system in period t for:

[0118]

[0119] Where: c co2 represents the carbon tax price, in yuan / kg; C outIndicates carbon emissions in kg / h;

[0120] Operating cost of cooling energy utilization equipment in the system during period t for:

[0121]

[0122] Where: c lng_m is the unit cost of operating the cold energy utilization equipment in stage m, is the output of the cold energy utilization phase in period m expressed by equation (5);

[0123] Running costs It can be specifically expressed as:

[0124]

[0125] Where: c lng_c 、c lng_p 、c lng_co They represent the unit costs of carbon capture, cold energy power generation, and direct cooling equipment operation, respectively, and the units are RMB / (kg / h), RMB / kW, and RMB / kW, respectively. In the above formula, the actual output cold energy in the third stage of direct cooling of LNG cold energy cascade utilization is the input cold energy of the third stage. Minus cooling energy loss

[0126] The startup cost of the equipment in the system during period t for:

[0127]

[0128] Where: It represents the unit startup cost of LNG gasification equipment, in yuan / h; It represents the unit startup cost of micro gas turbine, in Yuan / h; It represents the unit startup cost of cold energy utilization equipment at each stage, in Yuan / h.

[0129] Start-up indicator variables of LNG gasification, micro gas turbine and cold energy utilization equipment in the system during period t for:

[0130]

[0131] Step 4: Convert the above model into a two-stage stochastic optimization model based on multiple scenarios and solve it to obtain the energy management decision of the multi-energy microgrid with cascaded utilization of LNG cold energy.

[0132] (4.1) Generate uncertainty scenarios of renewable energy and load based on stochastic optimization concept:

[0133] Firstly, according to the predicted expected value of renewable energy output and load and the probability distribution of uncertainty, multiple groups of scenarios are randomly generated to simulate the possible actual situation of source and load;

[0134] (4.2) According to the operation characteristics of the equipment in the multi-energy microgrid, the model described in step 3 is transformed into a two-stage stochastic optimization model based on multiple scenarios. The corresponding mathematical matrix expression is:

[0135]

[0136] Where: n is the probability of the uncertainty scenario, n represents the uncertainty scenario, u n represents uncertain variables, including renewable energy output and electrical cooling load power in this system; x represents the day-ahead stage variables, including binary variables for controlling the start and stop of cooling energy utilization equipment, the start and stop of LNG gasification, the start and stop of micro gas turbines, and the power purchased and sold in the day-ahead power market, which should be kept as a one-dimensional variable related to the scheduling period; y n represents the optimization variables in the intraday stage, mainly including the operation of cold energy utilization equipment, LNG gasification, micro gas turbine operation, electric refrigeration machine refrigeration, normal temperature high pressure gas storage tank storage and intraday electricity market transactions and other related variables, which should be converted into two-dimensional variables related to the scene and time; C is the coefficient matrix of the objective function of the day-ahead stage, mainly the day-ahead transaction electricity price and equipment startup cost, etc.; E is the coefficient matrix of the objective function of the intraday stage, mainly the day-ahead transaction electricity price, carbon tax price and unit cost of cold energy utilization equipment, etc.; g(x,y n ,u n ) represents all the equality constraints contained in the above model, h(x,y n ) represents all inequality constraints.

[0137] (4.3) Solution of stochastic optimization model:

[0138] According to the above two-stage stochastic optimization method, the model is optimized and solved by calling Gurobi or Cplex solvers to obtain the optimal values ​​of the energy management decision variables of the multi-energy microgrid with cascaded utilization of LNG cold energy.

[0139] (4.4) Intraday mulligan:

[0140] According to the more accurate forecast value of source and load during the day, the multi-energy microgrid energy optimization model with cascade utilization in step 3 is used to fix the optimal value of the day-ahead variable obtained by optimization (4.3), and the operating variables of each scheduling period during the day are re-optimized to obtain the optimal value of the microgrid operation decision during the day.

[0141] The annual operation data of a port multi-energy microgrid system with an LNG gasification station in East China and the operation data of the LNG cold energy utilization equipment that has been put into operation are selected for analysis. The basic parameters include: (1) the typical daily output curve combining renewable energy and load, such as Figure 2 As shown in Figure 1, the average output of renewable energy and the average load of electric cooling are obtained in each hour. The fluctuation of renewable energy is set to ±20%, the load fluctuation is set to ±10%, and the upper limit of renewable energy power generation is limited to 1000kW; (2) The operating parameters of the cooling energy cascade utilization equipment and microgrid energy consumption equipment are shown in Table 1; (3) The day-ahead power market transaction power limit is 5000kW, and the intraday power market transaction power limit is 2000kW. The reference value of the electricity price is: the peak purchase / sale price is 0.76 yuan / kWh, the normal purchase / sale price is 0.56 yuan / kWh, and the valley purchase / sale price is 0.38 yuan / kWh. The day-ahead market is 1.1 and 0.9 times the reference value, and the intraday market is 1.3 and 0.7 times the reference value; (4) The unit operating cost of cold energy utilization equipment is 0.3 yuan / (kg / h) for carbon capture equipment, 0.1 yuan / kW for cold energy power generation equipment, and 0.2 yuan / kW for direct cooling equipment; (5) The unit startup cost of system equipment is 2 yuan / h for LNG gasification equipment, 5 yuan / h for micro gas turbines, 5 yuan / h for carbon capture equipment, 10 yuan / h for cold energy power generation equipment, and 2 yuan / h for direct cooling equipment. The parameters of cold energy cascade utilization equipment and microgrid energy consumption equipment are shown in Table 1.

[0142] Table 1 Parameters of cold energy cascade utilization equipment and microgrid energy equipment

[0143]

[0144] Depend on Figure 3 It can be seen that according to the multi-energy microgrid architecture and the LNG cold energy utilization equipment in the system, a simple energy flow analysis is carried out on the multi-energy microgrid system containing the cascade utilization of cold energy, mainly considering the four major energy flows of electricity, cold, gas and carbon, reflecting the coupling relationship between distributed energy, multi-energy conversion equipment and cold energy utilization equipment in the system.

[0145] Using the above two-stage stochastic optimization model based on multiple scenarios, 50 groups of uncertainty scenarios are generated here, and it is assumed that they are uniformly distributed, and the probability of each group of scenarios is ρ n That is

[0146] The Yalmip platform is used to build and Gurobi solver is used to solve the problem. The optimization of LNG cold energy cascade utilization for multi-energy microgrid energy management is realized, and the optimal values ​​of multi-energy microgrid energy management decision variables for LNG cold energy cascade utilization are obtained. The optimization results are as follows: Figure 4-Figure 8 shown.

[0147] Depend on Figure 4 It can be seen that the gas load fluctuates within a day, and the demand is higher during the day, which may be due to the increase in cold energy demand or for the supply of gas to micro gas turbines. LNG gasification can basically meet the system's gas load demand. At the same time, the gas storage equipment stores gas during the low gas load period and releases gas during the peak period, which plays a role in balancing the system's natural gas supply.

[0148] Depend on Figure 5 It can be seen that the carbon load supply and demand of the system after optimization are as follows: (1) At 1-6 o'clock, the carbon load is significantly reduced. This is due to the sharp drop in nighttime load. The system increases renewable energy generation and cold energy generation, reducing the use of micro gas turbines. This reflects the strategy of the system to prioritize low-carbon energy during low-load periods. At the same time, due to the role of carbon capture, carbon emissions are effectively reduced, showing the system's emission reduction potential during low-load periods; (2) At 7-24 o'clock, the carbon load is always maintained at a high level. This is due to the increase in electricity demand during the daytime. The system needs to mobilize micro gas turbines and other power generation methods to meet the load demand, resulting in an increase in carbon emissions. This reflects that although a certain amount of low-carbon energy participates in power supply under high load conditions, the system still faces certain carbon emission pressures, so emission reduction measures can be further optimized. (3) Overall, during the 1-24 period, the cumulative total carbon capture accounts for about 50% of the total carbon emissions of the system's micro gas turbines, which greatly reduces the system's carbon emissions, reflecting a significant green carbon reduction optimization effect.

[0149] Depend on Figure 6-Figure 7 It can be seen that the power load supply and demand situation after system optimization is as follows: (1) At 6-10, 12-16, 18-20 and 23-24, due to the synergistic effect of micro gas turbines, renewable energy and cold energy power generation, not only can the power load demand be fully met, but also revenue can be obtained by selling electricity to the power market, which reduces the system operating costs and improves economic efficiency; (2) In the 1-2 and 4-5 periods, the system reduces the power generation of micro gas turbines during the night low-load period and relies more on low-carbon renewable energy power generation and cold energy power generation, which reduces the carbon emissions generated by operation; (3) Overall, the effect of LNG cold energy power generation is significant. Most of the time, the cold energy power generation capacity can reach 1600kW, which exceeds 50% of the rated operating power generation capacity of the gas turbine, greatly alleviating the power consumption pressure of the system and reducing the carbon emissions of the system.

[0150] Depend on Figure 8It can be seen that the LNG direct cooling link supplements the cooling load demand that cannot be supplied by the electric refrigeration machine. When the LNG direct cooling amount is small, the direct cooling power is about 200kW, which can meet about 10% of the cooling load demand at this time; when the LNG direct cooling amount is large, the cooling power can reach 1100kW, which is more than 30% of the cooling load demand at this time. It can be seen that the LNG direct cooling link has the effect of supplementing the supply of cooling demand. At the same time, through the reasonable distribution of cooling energy in the system, the supply of LNG cooling energy is increased during the peak of cooling load, which reduces the demand for electric cooling, that is, additional electricity consumption, and further optimizes energy utilization.

[0151] Based on the same technical concept as the method embodiment, the present invention also provides a general modeling and optimization system for LNG cold energy cascade utilization for multi-energy microgrid energy management, including:

[0152] The general model construction module for cold energy utilization is used to establish a general model for the utilization of LNG cold energy at each stage according to the purpose and equipment parameters of the cascade utilization of LNG cold energy, including: dividing the LNG cold energy utilization stages and determining the purpose of cold energy utilization at each stage; determining the upper and lower limits of the input cold energy required for equipment operation according to the equipment parameters of cold energy utilization at each stage, and establishing the equipment operation constraint model for cold energy utilization at each stage; establishing the time constraint model for cold energy utilization at each stage according to the on / off time limit of the cold energy utilization equipment; establishing the loss model for cold energy utilization at each stage according to the cold energy loss caused by heat transfer during the cold energy utilization process and the power consumption of the cold energy utilization equipment; establishing the coupling model of cold energy utilization at each stage and the output of the corresponding purpose according to the actual cold energy power and the cold energy heat transfer loss power;

[0153] A cold energy cascade utilization transfer coupling model building module is used to establish a transfer coupling model for LNG cold energy cascade utilization according to an LNG gasification model, wherein the LNG gasification model includes power limits of an LNG gasification station and on / off time constraints of an LNG gasification station, and the transfer coupling model for LNG cold energy cascade utilization includes: the cold energy power that can be recovered and utilized during the LNG gasification process is greater than or equal to the sum of the actual cold energy powers at each stage, and the total power consumption in the cold energy utilization process is the sum of the power consumption of the cold energy utilization equipment at each stage;

[0154] A multi-energy microgrid energy optimization model construction module including cascade utilization is used to establish a multi-energy microgrid energy optimization model including cascade utilization according to the multi-energy microgrid architecture and the distributed energy contained therein. The multi-energy microgrid energy optimization model takes minimizing the operating cost and carbon emissions of the multi-energy microgrid system in a specified period of time as the optimization objective function, and includes distributed energy operation and multi-energy conversion constraints, energy balance constraints, and power purchase and sale constraints between the multi-energy microgrid system and the power market in the multi-energy microgrid system. The operating cost of the multi-energy microgrid system in the objective function includes the transaction cost in the power market, the operating cost and startup cost of the cold energy utilization equipment, and the operating cost is determined by the output of the cold energy utilization stage and the unit cost of the equipment operation;

[0155] The optimization model conversion and solution module is used to convert the multi-energy microgrid energy optimization model into a two-stage stochastic optimization model based on multiple scenarios and solve it according to the uncertainty of source and load and the operating characteristics of the multi-energy microgrid equipment, so as to obtain the energy management decision of the multi-energy microgrid with cascaded utilization of LNG cold energy.

[0156] The present invention also provides a computer device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management are implemented.

[0157] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management.

[0158] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices (systems), computer equipment or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0159] The present invention is described with reference to a flowchart of a method according to an embodiment of the present invention. It should be understood that each process in the flowchart and a combination of processes in the flowchart can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the process in the flowchart. Figure 1 A device that specifies functions in a process or multiple processes.

[0160] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple processes.

[0161] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 The steps of a specified function in a process or multiple processes.

Claims

1. A general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management, characterized in that: The following steps are involved: (1) According to the purpose and equipment parameters of LNG cold energy cascade utilization, a general model for LNG cold energy utilization at each stage is established, including: dividing the LNG cold energy utilization stages and determining the purpose of cold energy utilization at each stage; according to the equipment parameters of cold energy utilization at each stage, determining the upper and lower limits of the input cold energy required for equipment operation, and establishing the equipment operation constraint model for cold energy utilization at each stage; according to the on / off time limit of the cold energy utilization equipment, establishing the time constraint model for cold energy utilization at each stage; according to the cold energy loss caused by heat transfer during the cold energy utilization process and the power consumption of the cold energy utilization equipment, establishing the loss model for cold energy utilization at each stage; according to the actual cold energy power and the cold energy heat transfer loss power, establishing the coupling model of cold energy utilization at each stage and the output of the corresponding purpose; (2) establishing a transfer coupling model for LNG cold energy cascade utilization based on the LNG gasification model, wherein the LNG gasification model includes power constraints of the LNG gasification station and on / off time constraints of the LNG gasification station, and the transfer coupling model for LNG cold energy cascade utilization includes: the cold energy power that can be recovered and utilized in the LNG gasification process is greater than or equal to the sum of the actual cold energy power of each stage, and the total power consumption in the cold energy utilization process is the sum of the power consumption of the cold energy utilization equipment in each stage; (3) Based on the multi-energy microgrid architecture and the distributed energy contained therein, a multi-energy microgrid energy optimization model with cascade utilization is established. The multi-energy microgrid energy optimization model takes minimizing the operating cost and carbon emissions of the multi-energy microgrid system in a specified period of time as the optimization objective function, and includes the distributed energy operation and multi-energy conversion constraints, energy balance constraints, and power purchase and sale constraints between the multi-energy microgrid system and the power market in the multi-energy microgrid system. The operating cost of the multi-energy microgrid system in the objective function includes the transaction cost in the power market, the operating cost and startup cost of the cold energy utilization equipment, and the operating cost is determined by the output of the cold energy utilization stage and the unit cost of the equipment operation; (4) According to the uncertainty of source and load and the operating characteristics of the multi-energy microgrid equipment, the multi-energy microgrid energy optimization model is transformed into a two-stage stochastic optimization model based on multiple scenarios and solved to obtain the energy management decision of the multi-energy microgrid with cascaded utilization of LNG cold energy.

2. The method according to claim 1, characterized in that In the step (1), the equipment operation constraint model for the cold energy utilization in each stage is specifically: the cold energy power actually used in the m stage in the t period does not exceed the upper limit of the cold energy input power of the stage and is not lower than the lower limit of the cold energy input power of the stage; The time constraint model of cold energy utilization in each stage is as follows: the startup time and shutdown time of the cold energy utilization equipment meet the specified startup and shutdown time limits; The loss model of cold energy utilization at each stage is established based on the relationship between cold energy loss and utilized cold energy, and the relationship between the power consumption of cold energy utilization equipment and utilized cold energy; The coupling model of the cold energy used in each stage and the corresponding output is expressed as: In the formula, It represents the output quantity of the purpose of stage m in period t; η m is the utilization rate; It represents the cooling power actually used in stage m during period t; It represents the heat transfer power loss during the period t.

3. The method according to claim 1, characterized in that In the LNG gasification model, the power limit of the LNG gasification station is specifically as follows: the gasification power of the LNG gasification station in period t does not exceed the upper limit of the gasification power of the LNG gasification station and does not fall below the lower limit of the gasification power of the LNG gasification station; The startup and shutdown time constraints of the LNG gasification station are as follows: the startup and shutdown time of the LNG gasification station must comply with the specified startup and shutdown time constraints; In the transfer coupling model of LNG cold energy cascade utilization, the recoverable cold energy power is expressed as: In the formula, represents the cold energy power that can be recovered and utilized during the LNG gasification process during period t; η lng represents the efficiency coefficient of LNG cold energy recovery and utilization; q ng is the calorific value of natural gas.

4. The method according to claim 1, characterized in that: In the step (3), the distributed energy operation and multi-energy conversion constraints in the multi-energy microgrid system include the operation, multi-energy conversion and carbon emission constraints of the micro gas turbine, the electric refrigerator, the normal temperature and high pressure gas storage tank, and the battery energy storage device, as well as the renewable energy power generation constraints; Energy balance constraints include electricity, cooling, gas and carbon energy balance constraints; The power purchase and sale constraints of the multi-energy microgrid system in the power market include the electricity price set according to the power purchase and sale transaction history and forecast data of the power market on the day before and within the day, as well as the corresponding upper and lower limits of power purchase and sale transmission.

5. The method according to claim 1, characterized in that In step (3), the transaction cost in the electricity market is calculated as follows: In the formula, is the transaction cost in period t, They represent the electricity purchase and sales prices in the electricity market during period t the day before, They represent the power purchase and power sales in the day-ahead power market during period t, They represent the purchase and sale prices of electricity in the electricity market during the t period of the day, They represent the power purchase and sales in the intraday power market during period t, respectively, and τ is the length of the trading period; The operating cost of cold energy utilization equipment is calculated as follows: In the formula, is the operating cost of the cooling energy utilization equipment during period t, c lng_m represents the unit cost of operating the cold energy utilization equipment in stage m, is the output of stage m usage in period t; The startup cost of cold energy utilization equipment is calculated as follows: In the formula, is the equipment startup cost during period t, represents the startup cost of LNG gasification equipment; represents the microturbine startup cost; represents the startup cost of the cold energy utilization equipment in stage m; It is a 0-1 variable used to indicate the start-up indication of LNG gasification, micro gas turbine and m-stage cold energy utilization.

6. The method according to claim 1, characterized in that The step (4) comprises: (4.1) Based on the predicted expected values ​​of renewable energy output and load and the probability distribution of uncertainty, multiple sets of scenarios are randomly generated to simulate the possible actual conditions of source and load; (4.2) According to the operation characteristics of the equipment in the multi-energy microgrid, the model in step (3) is transformed into a two-stage stochastic optimization model based on multiple scenarios. The corresponding mathematical matrix expression is: Where: n is the probability of the uncertainty scenario, n represents the uncertainty scenario, u n represents uncertain variables, including renewable energy output and electrical cooling load power; x represents the day-ahead phase variables, including binary variables for controlling the start and stop of cooling energy utilization equipment, the start and stop of LNG gasification, the start and stop of micro gas turbines, and the power purchased and sold in the day-ahead power market, which should be maintained as a one-dimensional variable related to the dispatch period; y n represents the optimization variables in the intraday stage, mainly including the operation of cold energy utilization equipment, LNG gasification, micro gas turbine operation, electric refrigeration machine refrigeration, normal temperature and high pressure gas storage tank storage and intraday power market transaction related variables, which should be converted into two-dimensional variables related to scenarios and time; C is the coefficient matrix of the objective function of the day-ahead stage, mainly the day-ahead transaction electricity price and equipment startup cost; E is the coefficient matrix of the objective function of the intraday stage, mainly the day-ahead transaction electricity price, carbon tax price and unit cost of cold energy utilization equipment; g(x,y n ,u n ) represents all the equality constraints contained in the above model, h(x,y n ) represents all inequality constraints; (4.3) Based on the above two-stage stochastic optimization model, the mathematical programming solver is called to optimize and solve the model to obtain the optimal values ​​of the energy management decision variables of the multi-energy microgrid with cascaded utilization of LNG cold energy.

7. The method according to claim 6, characterized in that The step (4) further comprises: (4.4) Based on the more accurate forecast values ​​of the source and load during the day, the multi-energy microgrid energy optimization model with cascade utilization in step (3) is used to fix the optimal value of the day-ahead variable obtained by optimization (4.3), and the operating variables of each scheduling period during the day are re-optimized to obtain the optimal value of the microgrid operation decision during the day.

8. A general modeling and optimization system for LNG cold energy cascade utilization for multi-energy microgrid energy management, characterized in that: include: The general model construction module for cold energy utilization is used to establish a general model for the utilization of LNG cold energy at each stage according to the purpose and equipment parameters of the cascade utilization of LNG cold energy, including: dividing the LNG cold energy utilization stages and determining the purpose of cold energy utilization at each stage; determining the upper and lower limits of the input cold energy required for equipment operation according to the equipment parameters of cold energy utilization at each stage, and establishing the equipment operation constraint model for cold energy utilization at each stage; establishing the time constraint model for cold energy utilization at each stage according to the on / off time limit of the cold energy utilization equipment; establishing the loss model for cold energy utilization at each stage according to the cold energy loss caused by heat transfer during the cold energy utilization process and the power consumption of the cold energy utilization equipment; establishing the coupling model of cold energy utilization at each stage and the output of the corresponding purpose according to the actual cold energy power and the cold energy heat transfer loss power; A cold energy cascade utilization transfer coupling model building module is used to establish a transfer coupling model for LNG cold energy cascade utilization according to an LNG gasification model, wherein the LNG gasification model includes power limits of an LNG gasification station and on / off time constraints of an LNG gasification station, and the transfer coupling model for LNG cold energy cascade utilization includes: the cold energy power that can be recovered and utilized during the LNG gasification process is greater than or equal to the sum of the actual cold energy powers at each stage, and the total power consumption in the cold energy utilization process is the sum of the power consumption of the cold energy utilization equipment at each stage; A multi-energy microgrid energy optimization model construction module including cascade utilization is used to establish a multi-energy microgrid energy optimization model including cascade utilization according to the multi-energy microgrid architecture and the distributed energy contained therein. The multi-energy microgrid energy optimization model takes minimizing the operating cost and carbon emissions of the multi-energy microgrid system in a specified period of time as the optimization objective function, and includes distributed energy operation and multi-energy conversion constraints, energy balance constraints, and power purchase and sale constraints between the multi-energy microgrid system and the power market in the multi-energy microgrid system. The operating cost of the multi-energy microgrid system in the objective function includes the transaction cost in the power market, the operating cost and startup cost of the cold energy utilization equipment, and the operating cost is determined by the output of the cold energy utilization stage and the unit cost of the equipment operation; The optimization model conversion and solution module is used to convert the multi-energy microgrid energy optimization model into a two-stage stochastic optimization model based on multiple scenarios and solve it according to the uncertainty of source and load and the operating characteristics of the multi-energy microgrid equipment, so as to obtain the energy management decision of the multi-energy microgrid with cascaded utilization of LNG cold energy.

9. A computer device, characterized in that: include: one or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and when the programs are executed by the processors, the steps of the general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management are implemented as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the general modeling and optimization method for LNG cold energy cascade utilization for multi-energy microgrid energy management as described in any one of claims 1 to 7 are implemented.

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