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CN-122001027-A - Layered operation control method and system of integrated system for producing and storing biological natural gas

CN122001027ACN 122001027 ACN122001027 ACN 122001027ACN-122001027-A

Abstract

The invention discloses a layered operation control method and a layered operation control system of an integrated system for preparing and storing biological natural gas, wherein the method comprises the steps of obtaining the operation state of the system and the external environment information; the method comprises the steps of constructing a monthly level planning layer, optimizing a cross-season gas storage target based on long-term prediction, considering anaerobic fermentation slow process dynamics, constructing an hour level scheduling layer, adopting model prediction control to formulate a hydrogen production and power generation plan based on short-term prediction, introducing biosynthesized hydrogen injection rate change rate penalty, constructing a minute level real-time control layer, based on ultra-short-term prediction rolling tracking plan, designing a quick response loop to cope with sudden green electricity absorption, peak regulation and frequency modulation requirements, and feeding real-time operation data back to an upper layer to perform model parameter self-adaptive update. The method integrates multi-scale prediction information, coordinates the speed process, realizes efficient green electricity consumption and flexible power grid support, and can be widely applied to the optimal operation control of a biological natural gas production and storage system.

Inventors

  • ZENG WEI
  • SUN MIN
  • XIONG JIANHAO
  • WAN ZIJING

Assignees

  • 国网江西省电力有限公司电力科学研究院

Dates

Publication Date
20260508
Application Date
20260409

Claims (9)

  1. 1. The layered operation control method of the integrated system for producing and storing the biological natural gas is characterized by comprising the following steps of: acquiring running state information and external environment information of an integrated system for producing and storing the biological natural gas, wherein the external environment information comprises long-term prediction data of renewable energy power generation, short-term prediction data of renewable energy power generation, a power grid dispatching instruction and time-of-use electricity price information; The method comprises the steps of constructing a monthly planning layer, taking historical operation data and long-term prediction data of renewable energy power generation as input, taking the monthly time as a period, taking the maximum monthly income as a target, and optimizing a monthly gas production plan of a gas customization unit, a monthly gas storage plan of a gas storage unit and a monthly gas consumption plan of a gas consumption unit; Constructing an hour-level scheduling layer, transmitting the monthly gas production plan, the monthly gas storage plan and the monthly gas consumption plan to the hour-level scheduling layer by taking the monthly gas production plan, the monthly gas storage plan and the monthly gas consumption plan as constraint conditions, and recognizing a current operation mode of the integrated system for producing and storing the biological natural gas by taking the short-term prediction data, the power grid scheduling instruction and the time-of-use electricity price information as inputs, constructing a corresponding optimized scheduling model according to the recognized operation mode, solving the optimized scheduling model and generating an hour-level scheduling instruction; and constructing a minute-level real-time control layer, taking real-time operation state information of the integrated system for producing and storing the biological natural gas as feedback input, and carrying out real-time closed-loop control on the gas producing unit, the gas storing unit and the gas using unit by taking minutes as a period, so that real-time operation parameters track the scheduling instruction, and feeding real-time operation data back to the hour-level scheduling layer and the month-level planning layer for rolling optimization of the next period to form closed-loop control.
  2. 2. The method for controlling the layered operation of the integrated system for producing and storing the biological natural gas according to claim 1, wherein the identification of the operation mode is based on the comparison result of the short-term prediction value of renewable energy power generation and the preset consumption threshold value of the system, the type identification of a power grid dispatching instruction and the time period category of time-of-use electricity price; when the short-term predicted value of renewable energy power generation exceeds a preset digestion threshold value of the integrated system for biological natural gas production and storage, recognizing the short-term predicted value as a green electricity digestion mode; when the received power grid dispatching instruction is a peak clipping instruction or a valley filling instruction, identifying the power grid dispatching instruction as a power grid peak clipping mode; and when the received power grid dispatching instruction is a primary frequency modulation instruction or a secondary frequency modulation instruction, identifying the power grid dispatching instruction as a power grid frequency modulation mode.
  3. 3. The hierarchical operation control method of an integrated system for biogas production and storage according to claim 2, wherein the optimized scheduling model constructed in the green electricity consumption mode comprises: Taking the maximum surplus green electricity consumption or the minimum waste wind waste light quantity as an optimization target; taking the start-stop state and the load rate of the electrolytic hydrogen production equipment as decision variables; The optimal scheduling model constructed in the power grid peak shaving mode comprises the following steps: Taking maximum peak regulation compensation benefit or minimum system load peak-valley difference as an optimization target; Taking the charging and discharging power of the gas storage unit and the output force of the gas generator set as decision variables; The optimal scheduling model constructed in the grid frequency modulation mode comprises the following steps: Taking minimized frequency deviation or maximized frequency modulation mileage gain as an optimization target; the rapid gas charging and discharging rate of the gas storage unit and the adjusting rate of the gas generator set are taken as decision variables.
  4. 4. The hierarchical operation control method of an integrated system for biogas production and storage according to claim 1, wherein the optimal scheduling model of the monthly planning layer targets the maximum monthly benefit, and the expression is: , in the formula, In order to optimize the total number of months in the cycle, Is the first Expected power generation income of month is calculated by the total monthly power generation amount and the predicted electricity price, Is the first The expected hydrogen production cost of month is calculated by the total hydrogen production amount of month and the predicted electricity price, Is the first The gas storage cost of the month is high, For the slow process penalty factor to be good, Punishment coefficients for slow processes; Constraint conditions comprise monthly energy balance, gas storage capacity constraint and biosynthesis slow dynamic constraint, and the expression is: , , , in the formula, Is the first The energy state of the air storage tank at the end of the month, Is the first The energy state of the air storage tank at the end of the month, Is the first The month converts the total energy stored by hydrogen production, Is the first The total energy released by the monthly power generation, For the maximum energy capacity of the air storage tank, For the bioconversion efficiency of hydrogen to methane, Is the first The average maximum acceptable hydrogen injection rate for the microbial system, Is the first Total hours of month.
  5. 5. The hierarchical operation control method of an integrated system for biogas production and storage according to claim 1, wherein an optimized scheduling model of the hour-level scheduling layer is a model predictive control model, and an objective function of the model predictive control model is: , , , in the formula, For a period of time Is used for selling electricity price of the electric car, For a period of time The grid-connected power of the generator set, For a period of time Is used for purchasing electricity price of the electric car, For a period of time The hydrogen production power of the electrolytic cell, 、 、 Are all the weight coefficients of the two-dimensional space model, Electricity price for selling electricity 1.5 To 2 times of the total number of the components, The value of (2) is that the gas storage quantity deviation at the end of the day The temperature is controlled within +/-5 percent, Is typically 0.1 to 1.0, For a period of time The wind-solar prediction total output force of the system, For the limit power that the grid can accommodate, For the methane storage amount of the air storage tank at the end of the day, For the end-of-day target gas storage volume, For the time step size of the time step, For the target energy state of the lunar air storage tank, In order to discard wind and discard light penalty coefficients, Is the lower heat value of methane, For a period of time The proportion of hydrogen gas partitioning to the primary biosynthesis, For a period of time The ratio of hydrogen partitioning to primary biosynthesis; Constraint conditions of the model predictive control model comprise hydrogen material balance, natural gas material balance, power generation balance, equipment capacity constraint, hydrogen distribution constraint, biosynthesis hydrogen injection rate change rate constraint, hydrogen storage tank state boundary, gas storage tank state boundary and periodic boundary conditions; The hydrogen material balance expression is: , , , in the formula, For a period of time The hydrogen storage amount of the hydrogen storage tank, For a period of time The hydrogen storage amount of the hydrogen storage tank, For the hydrogen production efficiency of the electrolytic cell, For a period of time The flow rate of the hydrogen injected into the biosynthesis, For a period of time Injecting chemically synthesized hydrogen flow; The natural gas material balance expression is: , in the formula, For a period of time The methane storage amount of the gas storage tank, For a period of time The methane storage amount of the gas storage tank, The conversion efficiency of hydrogen to methane for the secondary chemical synthesis, For a period of time The natural gas flow rate used for power generation, For a period of time Natural gas flow for direct sales; the expression of the power generation balance is: , in the formula, The electric efficiency of the generator set is obtained; The expression for the device capacity constraint is: , , , in the formula, For the rated power of the electrolytic cell, Rated power of the generator; The expression of the hydrogen partitioning constraint is: , , in the formula, The proportion of hydrogen to be distributed to the chemical synthesis for period k; The expression of the biosynthetic hydrogen injection rate change rate constraint is: , in the formula, Maximum rate of change allowed for the microbial system; The expressions of the hydrogen storage tank state boundary and the gas storage tank state boundary are as follows: , , in the formula, For the period k hydrogen storage tank hydrogen inventory, For the maximum capacity of the hydrogen storage tank, For period k the natural gas storage tank stock, The maximum capacity of the air storage tank; the expression of the periodic boundary condition is: , , in the formula, For the hydrogen inventory at the initial time of day, For the storage of the hydrogen in the gas storage tank at the end of the day, Is the methane stock at the initial time of day.
  6. 6. The hierarchical operation control method of an integrated system for biogas production and storage according to claim 1, wherein the minute-scale real-time control layer adopts a model predictive control algorithm, takes the scheduling instruction as a reference track, takes current real-time operation state information as an initial condition, optimizes a control sequence in a future preset time domain in a rolling manner, and issues a first control action to execution mechanisms of a gas production unit, a gas storage unit and a gas utilization unit, and an objective function of the model predictive control algorithm is as follows: , in the formula, For the current time t to the future Predicted values of grid-connected power of the generator at the moment, For the future A reference trajectory of the generator power at the moment, For the current time t to the future Predicted value of hydrogen production power of the electrolytic cell at any time, For the future Reference track of hydrogen production power of the electrolytic cell at any time, In order to predict the number of time periods within the window, As a predicted value of the frequency deviation of the power grid, In order to obtain the real-time wind and light discarding punishment item based on ultra-short term wind and light prediction calculation, 、 Are weight coefficients.
  7. 7. A layered operation control system of an integrated system for producing and storing biogas, comprising: the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is configured to acquire operation state information and external environment information of an integrated system for producing and storing biological natural gas, and the external environment information comprises long-term prediction data of renewable energy power generation, short-term prediction data of renewable energy power generation, a power grid dispatching instruction and time-of-use electricity price information; The first construction module is configured to construct a monthly planning layer, takes historical operation data and long-term prediction data of renewable energy power generation as input, takes the monthly time as a period, and takes the maximum monthly benefit as a target to optimize and manufacture a monthly gas production plan of the gas customizing unit, a monthly gas storage plan of the gas storing unit and a monthly gas consumption plan of the gas consuming unit; The second construction module is configured to construct an hour-level scheduling layer, transmit the month gas production plan, the month gas storage plan and the month gas utilization plan to the hour-level scheduling layer by taking the month gas production plan, the month gas storage plan and the month gas utilization plan as constraint conditions, and recognize the current operation mode of the integrated system for producing and storing the biological natural gas by taking the short-term prediction data, the power grid scheduling instruction and the time-of-use electricity price information as inputs, and construct a corresponding optimized scheduling model and solve according to the recognized operation mode to generate an hour-level scheduling instruction; The third construction module is configured to construct a minute-level real-time control layer, takes real-time running state information of the integrated system for producing and storing the biological natural gas as feedback input, and carries out real-time closed-loop control on the gas producing unit, the gas storing unit and the gas consuming unit by taking minutes as a period, so that real-time running parameters track the scheduling instruction, and real-time running data are fed back to the hour-level scheduling layer and the month-level planning layer for rolling optimization of the next period to form closed-loop control.
  8. 8. An electronic device comprising at least one processor and a memory communicatively coupled to the at least one processor, wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.
  9. 9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method of any one of claims 1 to 6.

Description

Layered operation control method and system of integrated system for producing and storing biological natural gas Technical Field The invention belongs to the technical field of renewable energy system optimization operation control, and particularly relates to a layered operation control method and system of an integrated system for biological natural gas production and storage. Background The intermittent and fluctuating nature of renewable energy sources brings great challenges to safe and stable operation of a power grid, the problem of wind and light abandoning is increasingly prominent, and development of large-scale and long-period energy storage technologies is needed to realize space-time transfer of electric power. Under the background, the technology of converting electricity into biological natural gas has been developed, and the technology of converting surplus green electricity into hydrogen and then coupling the hydrogen with biomass to prepare the biological natural gas has solved the problem of green electricity consumption and can produce green fuel, and has become an important development direction in the field of renewable energy sources. The system adopts a two-stage hydrogenation synthesis route, which is different from the traditional single conversion route, and comprises the steps of firstly injecting green hydrogen prepared by electrolysis into an anaerobic fermentation system, carrying out first-stage biosynthesis under the action of hydrogen nutrition type methanogen to increase the methane concentration in methane, and carrying out second-stage catalytic methanation reaction on the residual hydrogen and methane-rich gas produced at one stage to generate the biological natural gas. The technical route has the advantages that green electricity, green hydrogen and biomass energy sources such as local methane are deeply coupled, so that the green electricity can be efficiently converted and stored, and the utilization value of the biomass energy can be improved. However, the optimal operation control of the system faces the challenges of complex multi-time scale coupling, multi-level prediction information, slow biosynthesis process constraint and the like, namely the electrolytic hydrogen production can be responded in a second level, the catalytic reaction needs minute-level temperature control, the anaerobic fermentation is performed into a month-level slow process, the gas storage can realize cross-season energy transfer, dynamic mutual coupling of different time scales, the wind-light output prediction has a plurality of time scales such as a long term, a short term, an ultra-short term and the like, the power grid demand also has intra-day, cross-day and seasonal differences, the anaerobic fermentation is used as a slow process, the gas production rate cannot be quickly adjusted, hysteresis exists due to the influence of hydrogen injection amount, and the slow dynamics must be considered by a control strategy, so that the impact on a biological system is avoided. At present, an integrated system optimization control method for producing and storing the biological natural gas, which can systematically fuse multi-scale prediction information and coordinate different process links, is not available. Disclosure of Invention The invention provides a layered operation control method and a layered operation control system of an integrated system for preparing and storing biological natural gas, which are used for solving the technical problems of difficult multi-time scale coupling, insufficient coordination of fast and slow processes and insufficient utilization of predictive information in the prior art. In a first aspect, the present invention provides a method for controlling the layered operation of an integrated system for biogas production and storage, comprising: acquiring running state information and external environment information of an integrated system for producing and storing the biological natural gas, wherein the external environment information comprises long-term prediction data of renewable energy power generation, short-term prediction data of renewable energy power generation, a power grid dispatching instruction and time-of-use electricity price information; The method comprises the steps of constructing a monthly planning layer, taking historical operation data and long-term prediction data of renewable energy power generation as input, taking the monthly time as a period, taking the maximum monthly income as a target, and optimizing a monthly gas production plan of a gas customization unit, a monthly gas storage plan of a gas storage unit and a monthly gas consumption plan of a gas consumption unit; Constructing an hour-level scheduling layer, transmitting the monthly gas production plan, the monthly gas storage plan and the monthly gas consumption plan to the hour-level scheduling layer by taking the monthly gas production plan, the monthly gas storage plan