A Long-Term Dispatch Method for Power Systems Integrating Flexible Hydroelectric Hydrogen Chains

Abstract

This invention belongs to the technical field of coordinated scheduling of riverine hydrogen chains and their basin power systems, and specifically relates to a medium- and long-term scheduling method for power systems integrating flexible riverine hydrogen chains. It includes: establishing THPE (Theoretical, Practical, and Efficient) operational constraints considering the influence of upstream river water levels; constructing HV (Hydrogen-Vehicle) spatiotemporal energy transfer constraints considering the impact of seasonal river water levels on HV navigation conditions; proposing a medium- and long-term scheduling model for the riverine hydrogen chain basin power system with the objective function of minimizing the operating cost of the riverine hydrogen chain and its basin power system; designing an accuracy-adaptive piecewise linearization method to improve solution efficiency, considering the impact of hydrogen load on the real-time hydrogen charging and discharging rate of hydrogen-carrying vessels; processing the nonlinear constraints of the model using a linearization method to solve the scheduling model and obtain an optimization strategy; and guiding the medium- and long-term coordinated operation of the riverine hydrogen chain and its basin power system based on the optimization strategy. This method can significantly improve the coordinated scheduling capability and economy of hydrogen-electric systems.

Description

Technical Field

[0001] This invention belongs to the technical field of river waterway hydrogen chains and their basin power system coordinated scheduling, and particularly relates to a long-term scheduling method for power systems that integrates flexible waterway hydrogen chains, and especially to a long-term coordinated scheduling strategy for waterway hydrogen chains and their power systems that considers flexible hydrogen production, transportation and sales. Background Technology

[0002] Producing hydrogen through clean-energy electrolysis achieves zero carbon dioxide emissions, making it an ideal way to meet hydrogen energy demand and a necessary choice for facilitating the local consumption of surplus energy. However, this dynamic energy conversion can easily lead to an imbalance between the supply and demand of electricity and hydrogen in the same time and space. Therefore, it is necessary to coordinate the relationship between the power system and the hydroelectric hydrogen chain and formulate a reasonable coordinated dispatch strategy.

[0003] Large-scale, long-distance hydrogen storage and transportation faces the following challenges under current hydrogen transport methods: gaseous hydrogen trailers have limited capacity, liquid hydrogen tankers consume a lot of energy, dedicated hydrogen pipelines are expensive and difficult to popularize, and while blending hydrogen into natural gas pipelines is flexible, it is subject to proportional restrictions and poses safety hazards. Furthermore, the lack of connection between natural gas pipelines and renewable energy bases makes it even more difficult to integrate green hydrogen. Current mainstream storage and transportation solutions struggle to balance safety and economic efficiency, and cannot effectively support large-scale, cross-regional transportation of green hydrogen. Summary of the Invention

[0004] The purpose of this invention is to provide a long-term dispatching method for power systems that integrates flexible hydroelectric hydrogen chains. Since traditional HPEs are limited by fixed locations, they are not conducive to flexible hydrogen energy transportation and grid coordinated regulation. This invention aims to solve the limitations of traditional stationary hydrogen production devices (HPEs) in terms of hydrogen energy transportation and grid support.

[0005] To address the aforementioned technical problems, this invention provides a long-term dispatching method for power systems integrating flexible hydroelectric hydrogen chains, comprising the following steps:

[0006] Step S1: By analyzing the limitations of traditional stationary hydrogen production units, establish operational constraints for the mobile hydrogen production unit THPE that take into account the influence of upstream river water levels.

[0007] Step S2: Considering the impact of seasonal river water levels on the HV navigation conditions of hydrogen transport vessels, construct spatiotemporal energy transfer constraints for HV;

[0008] Step S3: Taking the minimum operating cost of the hydroelectric hydrogen chain and its basin power system as the objective function, a medium- and long-term scheduling model for the hydroelectric hydrogen chain basin power system is proposed.

[0009] Step S4: Considering the impact of the hydrogen load of the hydrogen-carrying vessel on the real-time hydrogen charging and discharging rate, a piecewise linearization method with adaptive accuracy is designed to improve the solution efficiency.

[0010] Step S5: Use linearization methods to process the nonlinear constraints of the model and solve the scheduling model to obtain the optimization strategy;

[0011] Step S6: Guide the long-term coordinated operation of the hydroelectric hydrogen chain and its basin power system based on the optimization strategy.

[0012] Preferably, in step S1, the THPE operating constraints are set as follows:

[0013]

[0014]

[0015] in, The mobile hydrogen production vessel k is located at station i in scenario s; The minimum navigation depth for the mobile hydrogen production vessel k; Let 's' be the water depth in river channel ij under scenario 's'. For hydrogen production vessel k, a passage marker is placed in river channel ij in scenario s; For the transfer flag in adjacent scenarios of hydrogen production vessels; For use as a working symbol for hydrogen production vessels; This represents THPE's real-time hydrogen production capacity. The rated hydrogen production capacity and minimum hydrogen production capacity of the hydrogen production unit; The amount of hydrogen produced for THPE; η h denoted as THPE's hydrogen production efficiency; M is an infinite positive number.

[0016] The hydrogen storage constraints of the HPS are set as follows:

[0017]

[0018] in, Let i be the amount of hydrogen produced by hydrogen production station i at time t in scenario s. Let be the amount of hydrogen charged at node i for the nth HV; The amount of hydrogen stored in the i-node HPS; The maximum charge / discharge rate of the i-node HPS hydrogen storage tank; The amount of hydrogen stored in the hydrogen storage tank at time t on day s; T / S / 0 represent the last day, the last moment, and the initial moment of the scheduling cycle, respectively; The rated capacity of the HPS hydrogen storage tank at node i.

[0019] Preferably, in step S2, the HV spatiotemporal energy transfer constraint is set as follows:

[0020]

[0021] in, The flag of the hydrogen transport vessel k at time t in scenario s is located at station i. Let HV be the travel time between stations i and j; This is a flag indicating whether a vessel can pass through the waterway ij; T is the scheduling period; M is an infinite positive number.

[0022] Also includes:

[0023] The relationship between compression power and high-pressure hydrogen storage pressure is expressed in the following formula (19);

[0024]

[0025] The equation of state for a gas is expressed in the following formula (20);

[0026] p hv V hv =n hv RT hv (20)

[0027] The relationship between the number of hydrogen moles and the amount of hydrogen stored in the high-pressure hydrogen storage system is expressed in the following formula (21);

[0028] n hv =E hv / M h (twenty one)

[0029] The maximum available hydrogen charging rate related to the initial hydrogen storage capacity is calculated, as expressed in the following formula (22);

[0030]

[0031] In the formula, To do work to compress hydrogen, V represents the initial and final pressures during hydrogen charging. hv For hydrogen storage capacity, T hv Where R is the compressor operating temperature, n is the gas constant, and n is the gas temperature. hv M is the amount of hydrogen gas. h is the molar mass of hydrogen gas; This represents the initial hydrogen storage capacity.

[0032] The hydrogen storage constraint settings for the HV are as follows:

[0033]

[0034] in, Indicates the real-time hydrogen charge / discharge rate of HV; This represents the maximum hydrogen charging rate for HV. This refers to the real-time hydrogen storage capacity of HV. This represents the initial hydrogen storage capacity of HV. The hydrogen storage capacity at the end of the HV scheduling cycle, d s The number of days included in a typical scenario; The rated hydrogen storage capacity of the ship.

[0035] According to the Bertrand model, the hydroelectric hydrogen energy chain can compete for market share in hydrogen sales by adjusting hydrogen prices. Therefore, the operating constraints of the hydrogen refueling station HRS considering market response are set as follows:

[0036]

[0037] in, This represents the amount of hydrogen sold by hydrogen refueling station i at time t in scenario s. This is the standard hydrogen supply from a hydrogen source. For the hydrogen load at hydrogen refueling station i at time t in scenario s, Let be the hydrogen release rate at station i at time t in scenario k of the ship. The price of hydrogen sold at site i in scenario s. The initial hydrogen price at the hydrogen refueling station. This is the hydrogen price coefficient.

[0038] Preferably, in step S3, the formula for the objective function is set as follows:

[0039] min f g +f thpe +f hv -f h (33)

[0040]

[0041] Among them, f g The total cost of the thermal power unit. For the unit operating cost of thermal power units, Let i be the operating power of thermal power unit i at time t in scenario s. The start-up and shutdown costs of thermal power units, For the start / stop indication of thermal power units, d s The number of days included in each typical scenario; f thpe p represents the total transfer cost of a mobile hydrogen production vessel. thpe,k For the cost of a single transfer of hydrogen production vessels, For the transfer marking of mobile hydrogen production vessels; f hv p is the sum of the transfer cost of HV and the driver cost. hv,k For the unit operating cost of a ship, For the station marker position of the ship, plab p is the daily labor cost for one ship. hv,k For HV, the hourly transfer cost; f h For the revenue from hydrogen sales at hydrogen refueling stations, For the hydrogen price in scenario i of hydrogen refueling stations, The amount of hydrogen sold at a hydrogen refueling station at time t in scenario i.

[0042] The grid constraints of the hydroelectric power system in the waterway hydrogen chain basin are set as follows:

[0043]

[0044] Where, θ i,t x is the phase angle of the voltage at node i; ij Let ij be the impedance of the transmission line; Let be the power flowing through the ij transmission line; To provide power to thermal power units, For wind power output at node i; For node i load; For hydrogen production capacity; Rated power of thermal power units; The ramp rate of the thermal power unit; This refers to the rated power of the wind turbine.

[0045] Preferably, in step S4, the adaptive piecewise linearization approximation method specifically includes: an accuracy-aware adaptive piecewise stage and a linearization approximation stage;

[0046] Assuming that the above formula (25) is processed, the following formula is used for calculation:

[0047]

[0048]

[0049] f(x) represents the actual hydrogen charging rate function related to the initial hydrogen storage capacity (HV) of the hydrogen transport vessel; g(x) represents the linearized approximation function; Equation (44) represents the actual hydrogen charging power function of the hydrogen transport vessel, which varies with the initial hydrogen storage capacity; Equation (45) represents the first derivative of the actual hydrogen charging rate function of the hydrogen transport vessel; Equation (46) represents the linearized approximation hydrogen charging rate function of the hydrogen transport vessel; Equation (47) represents the linear slope; Equation (48) defines the maximum linearized approximation error; Equation (49) gives the endpoints of all segmented intervals; where, To do work in compressing hydrogen, T hv R is the compressor operating temperature, R is the gas constant, and M is the gas constant. h is the molar mass of hydrogen gas; Adjacent points and The x-coordinate of the point of tangency that satisfies the error value Δe; Let x be the first and last points on the x-axis; x is the x-axis obtained sequentially to satisfy the error value.

[0050] Preferably, in step S5, the rated hydrogen storage capacity of the hydrogen transport vessel (HV) is divided into multiple intervals using V breakpoints. The maximum available hydrogen charging power of the HV at any given time is approximated as a linear combination of the hydrogen energy storage at the breakpoints. This scheduling model is expressed as follows:

[0051]

[0052]

[0053] Equation (50) restricts the real-time hydrogen storage capacity of the hydrogen transport vessel (HV) to fall within one of the V-1 intervals; Equation (51) indicates that the sum of the hydrogen storage weights corresponding to all breakpoints equals 1; Equation (52) indicates that the weight of a breakpoint is non-zero only when an interval is selected; Equation (53) gives the relationship between the real-time hydrogen storage capacity and the hydrogen storage capacity at breakpoints; Equation (54) calculates the maximum available hydrogen charging power of the hydrogen transport vessel (HV) based on the hydrogen energy storage at breakpoints; V-1 is the number of linearized segments; The selected segment; As weight; This represents the hydrogen storage capacity at the corresponding breakpoint. This is the rated hydrogen charging rate.

[0054] Preferably, step S5 specifically includes the following steps:

[0055] Step S51: Use linearization techniques to transform the nonlinear constraints and scheduling model into a classic mixed-integer linear programming problem;

[0056] Step S52: Call the preset solver to solve the linearized mixed-integer linear programming problem and obtain the optimization result;

[0057] Step S53: Output the long-term coordinated operation power of the hydrogen chain in the waterway and its basin power system from the optimization results.

[0058] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a long-term dispatching method for a power system integrating a flexible waterway hydrogen chain as described above.

[0059] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a long-term scheduling method for a power system integrating a flexible hydroelectric hydrogen chain as described above.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] This invention proposes a long-term scheduling strategy for power systems integrating a flexible waterway hydrogen chain. Specifically, it includes: First, establishing a spatiotemporal transfer characteristic model of a shipborne transferable hydrogen production device (THPE) and a hydrogen transport vessel (HV) considering the influence of river water levels, and quantifying the dynamic coupling relationship between HV hydrogen storage capacity and real-time hydrogen refueling rate; Second, introducing a Bertrand game theory model to guide the hydrogen sales strategy of hydrogen refueling stations (HRS), taking into account the market response behavior of other hydrogen sources; Based on this, constructing a medium-term scheduling optimization model for power systems integrating the waterway hydrogen chain, and using an accuracy-adaptive piecewise linearization method to transform it into a mixed integer linear programming (MILP) problem to improve solution efficiency. Finally, simulation verification through an improved IEEE 30-node power system and river network demonstrates that this strategy can significantly improve the coordinated scheduling capability and economy of the hydrogen-electricity system, addressing the problem of insufficient coordination between existing waterway hydrogen chains and basin power systems, leading to an imbalance between electricity and hydrogen supply and demand in the same time and space. This invention can coordinate power balance, improve renewable energy utilization, and reduce system operating costs. Attached Figure Description

[0062] Figure 1 A flowchart illustrating the long-term scheduling steps in a hydroelectric hydrogen chain and its power system, considering flexible hydrogen production, transportation, and sales, is provided for embodiments of the present invention.

[0063] Figure 2 A navigation chart of a mobile hydrogen production vessel (THPE) considering the influence of water level, provided for embodiments of the present invention.

[0064] Figure 3 A graph showing the relationship between the rated hydrogen charging rate of a ship and the real-time hydrogen load, provided for embodiments of the present invention.

[0065] Figure 4 The modified waterway hydrogen chain and its basin power system IEEE 30-node wiring diagram provided for embodiments of the present invention.

[0066] Figure 5 A graph showing the rated hydrogen production capacity of a hydrogen production station provided in an embodiment of the present invention.

[0067] Figure 6 The power balance data diagram provided for an embodiment of the present invention.

[0068] Figure 7 A diagram showing the spatiotemporal location of a hydrogen transport ship and its hydrogen charging / discharging relationship, provided for embodiments of the present invention.

[0069] Figure 8 The chart shows the hydrogen load supply ratio and market bidding data provided for embodiments of the present invention.

[0070] Figure 9 The graph shows a comparison of the solution time and accuracy between the proposed algorithm and the traditional solution provided in the embodiments of the present invention. Detailed Implementation

[0071] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer from the following description. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0072] like Figure 1 As shown, this embodiment of the invention specifically discloses a method for long-term scheduling of a hydroelectric hydrogen chain and its power system, considering flexible hydrogen production, transportation, and sales, including the following steps:

[0073] S1. By analyzing the limitations of traditional stationary hydrogen production units, operational constraints for transferable hydrogen production equipment (THPE) are established, taking into account the influence of upstream river water levels.

[0074] S2. Considering the impact of seasonal river water levels on the navigation conditions of hydrogen vessels (HV), construct spatiotemporal energy transfer constraints for HV.

[0075] S3. Taking the minimum operating cost of the hydroelectric hydrogen chain and its basin power system as the objective function, a medium- and long-term scheduling model for the hydroelectric hydrogen chain basin power system is proposed.

[0076] S4. Considering the impact of the hydrogen load of hydrogen-carrying ships on the real-time hydrogen charging and discharging rate, a piecewise linearization method with adaptive accuracy is designed to improve the solution efficiency.

[0077] S5. Linearization method is used to process the nonlinear constraints of the model, and the scheduling model is solved to obtain the optimization strategy;

[0078] S6. Guide the long-term coordinated operation of the hydroelectric hydrogen chain and its basin power system based on the optimization strategy.

[0079] In step S1, renewable energy bases often experience power curtailment, while power load centers may face insufficient power supply due to transmission line capacity limitations. If mobile hydrogen production vessels are used to produce hydrogen at renewable energy bases, and then hydrogen transport vessels are used to transport the hydrogen to downstream receiving-end power grids, where it is converted into electricity using hydrogen generators to meet power demand, this method not only flexibly utilizes renewable energy and improves the utilization rate of renewable energy sources, but also provides energy replenishment for downstream applications. In this process, due to the limitations of traditional stationary hydrogen production units, mobile hydrogen production vessels (THPEs) can leverage their unique advantages to improve hydrogen production efficiency. THPE operational constraints:

[0080]

[0081]

[0082] In the formula, The mobile hydrogen production vessel k is located at station i in scenario s; The minimum navigation depth for the mobile hydrogen production vessel k; Let 's' be the water depth in river channel ij under scenario 's'. For hydrogen production vessel k, a passage marker is placed in river channel ij in scenario s; For the transfer flag in adjacent scenarios of hydrogen production vessels; For use as a working symbol for hydrogen production vessels; This represents THPE's real-time hydrogen production capacity. The rated hydrogen production capacity and minimum hydrogen production capacity of the hydrogen production unit; The amount of hydrogen produced for THPE; η h This represents the hydrogen production efficiency of THPE.

[0083] Hydrogen storage constraints of HPS:

[0084]

[0085] In the formula, Let be the amount of hydrogen charged at node i for the nth HV; The amount of hydrogen stored in the i-node HPS; The maximum charge / discharge rate of the i-node HPS hydrogen storage tank; The amount of hydrogen stored in the hydrogen storage tank at time t on day s; T / S / 0 represent the last day, the last moment, and the initial moment of the scheduling cycle, respectively; The rated capacity of the HPS hydrogen storage tank at node i.

[0086] During the dry winter, river levels may not meet the navigation requirements of HV (High-Vehicle Navigation Vehicle). The spatiotemporal transition constraints considering the impact of seasonal water levels on HV navigation are as follows:

[0087]

[0088] In the formula, The flag of the hydrogen transport vessel k at time t in scenario s is located at station i. Let HV be the travel time between stations i and j; This is a marker indicating whether a vessel can pass through the waterway.

[0089] Unlike the case where the hydrogen release rate limitation (from high pressure to low pressure) is usually ignored, the hydrogen charging rate (from low pressure to high pressure) is determined by the compression capacity and the hydrogen storage capacity of the high-pressure hydrogen storage system. The relationship between compression power and high-pressure hydrogen storage pressure is expressed in Equation (19). The gas equation of state is given in Equation (20). The relationship between the number of hydrogen moles and the amount of hydrogen stored in the high-pressure hydrogen storage system is expressed in Equation (21). The maximum available hydrogen charging rate related to the initial hydrogen storage capacity is calculated according to Equation (22). It can be seen that the high-pressure hydrogen charging power gradually decreases as the initial hydrogen storage capacity increases.

[0090]

[0091] p hv V hv =n hv RT hv (20)

[0092] n hv =E hv / M h (twenty one)

[0093]

[0094] In the formula, To do work to compress hydrogen, V represents the initial and final pressures during hydrogen charging. hv For hydrogen storage capacity, T hv This refers to the compressor's operating temperature.

[0095] HV's hydrogen storage constraints:

[0096]

[0097] In the formula, Indicates the real-time hydrogen charge / discharge rate of HV; This represents the maximum hydrogen charging rate for HV. This refers to the real-time hydrogen storage capacity of HV. This represents the initial hydrogen storage capacity of HV. The hydrogen storage capacity at the end of the HV scheduling cycle, d s This represents the number of days included in a typical scenario.

[0098] As a commodity, the price of hydrogen is determined by all hydrogen sources in the market. According to the Bertrand model, the hydroelectric hydrogen energy chain can compete for market share in hydrogen sales by adjusting hydrogen prices. The operational constraints of a hydrogen refueling station (HRS) considering market response are as follows:

[0099]

[0100] In the formula, This represents the amount of hydrogen sold by hydrogen refueling station i at time t in scenario s. This is the standard hydrogen supply from a hydrogen source. For the hydrogen load at hydrogen refueling station i at time t in scenario s, The price of hydrogen sold at site i in scenario s. The initial hydrogen price at the hydrogen refueling station. This is the hydrogen price coefficient.

[0101] With the objective function of minimizing the short-term operating cost of the hydroelectric hydrogen chain and its basin power system, a medium- and long-term scheduling model for the hydroelectric hydrogen chain basin power system is constructed.

[0102] The objective function formula is:

[0103] min f g +f thpe +f hv -f h (33)

[0104]

[0105] In the formula, f g The total cost of the thermal power unit is, of which, For the unit operating cost of thermal power units, Let i be the operating power of thermal power unit i at time t in scenario s. The start-up and shutdown costs of thermal power units, For the start / stop indication of thermal power units; f thpe p represents the total transfer cost of a mobile hydrogen production vessel. thpe,k For the cost of a single transfer of hydrogen production vessels, For the transfer marking of mobile hydrogen production vessels; f hv p is the sum of the transfer cost of HV and the driver cost. lab p is the daily labor cost for one ship. hv,k For HV, the hourly transfer cost; f h Revenue from hydrogen sales at hydrogen refueling stations.

[0106] Basin power system grid constraints:

[0107]

[0108]

[0109] In the formula, θ i,t x is the phase angle of the voltage at node i; ij Let ij be the impedance of the transmission line; Let be the power flowing through the ij transmission line; For wind power output at node i; For node i load; This refers to the hydrogen production capacity.

[0110] Considering the impact of hydrogen load on the real-time hydrogen charging and discharging rate of hydrogen-carrying vessels, an accuracy-adaptive piecewise linearization method is designed to improve solution efficiency.

[0111] To address scheduling models with nonlinear constraints and a large number of binary variables, a precision-aware adaptive piecewise linearization approximation method is developed. This method includes a precision-aware adaptive piecewise stage and a linearization approximation stage. Taking equation (25) as an example, a precision-aware adaptive piecewise method is introduced. f(x) represents the actual hydrogen charging rate function related to the initial energy storage of the hydrogen transport vessel (HV). g(x) represents the linearization approximation function. When translated to be tangent to each other, the difference between their function values ​​at the corresponding tangency points reaches its maximum. Therefore, given the maximum error and the initial endpoint, the second endpoint can be calculated according to equations (44)-(49), and so on.

[0112]

[0113] Equation (44) represents the actual hydrogen charging power function of the hydrogen transport vessel, which varies with the initial hydrogen storage. Equation (45) represents the first derivative of the actual hydrogen charging rate function of the hydrogen transport vessel. Equation (46) represents the linearized approximate hydrogen charging rate function of the hydrogen transport vessel. Equation (47) represents the linear slope. Equation (48) defines the maximum linearization approximation error. Equation (49) gives the endpoints of all segmented intervals.

[0114] A linearization method is used to process the nonlinear constraints of the model, and the optimal scheduling strategy is obtained by solving the scheduling model.

[0115] The rated hydrogen storage capacity of a hydrogen transport vessel (HV) is divided into multiple intervals using V discontinuities. The maximum available hydrogen charging power of the HV at any given time is approximated as a linear combination of the hydrogen energy storage at the discontinuities. This model is expressed as follows:

[0116]

[0117] Equation (50) restricts the real-time hydrogen storage capacity of hydrogen transport vessels (HVs) to fall within one of the V-1 intervals. Equation (51) indicates that the sum of the hydrogen storage weights corresponding to all breakpoints equals 1. Equation (52) means that the weight of a breakpoint is non-zero only when an interval is selected. Equation (53) gives the relationship between real-time hydrogen storage capacity and breakpoint hydrogen storage capacity. Equation (54) calculates the maximum available hydrogen charging power of hydrogen transport vessels based on the hydrogen energy storage at the breakpoints.

[0118] Step 5 above specifically includes:

[0119] Step 51: The nonlinear constraints and scheduling model are transformed into a classic mixed-integer linear programming problem using linearization techniques.

[0120] Step 52: Call the preset solver to solve the linearized mixed-integer linear programming problem and obtain the optimization result;

[0121] Step 53: Output the long-term coordinated operating power of the hydroelectric hydrogen chain and its basin power system from the optimization results.

[0122] This invention also discloses a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps described above regarding the long-term scheduling strategy of the hydroelectric hydrogen chain and its power system, which takes into account flexible hydrogen production, transportation, and sales.

[0123] This invention also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described above regarding the long-term scheduling strategy of the hydroelectric hydrogen chain and its power system, taking into account flexible hydrogen production, transportation, and sales.

[0124] To enable those skilled in the art to better understand the present invention and its advantages, the following explanation is provided in conjunction with specific embodiments of the present invention:

[0125] The simulation platform was set up as follows: an Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz desktop computer. It utilized the yalmip toolbox and gurobi optimization software based on the Matlab R2022a platform. Figure 2 The navigation conditions for THPE provided in this embodiment of the invention describe the correlation between THPE and seasonally varying river levels. As can be seen from the figure, THPE can only be transferred when the seasonal river level is greater than the minimum navigation depth of THPE. The rated hydrogen refueling rate of the hydrogen transport vessel at the station is as follows: Figure 3 As shown. Figure 4The basic data provided for the embodiments of the invention are used to obtain the hydroelectric hydrogen chain and the power balance of the basin power system and the spatiotemporal transfer of HV from the optimization results during specific implementation. Then, the operation can be guided according to the optimized scheduling strategy.

[0126] Figure 5 It can be seen that THPE's flexible transfer in different scenarios results in varying rated hydrogen production capacity for hydrogen production stations. The proposed scheduling model's power system operating power is as follows: Figure 6 As shown, thermal power plants, renewable energy power plants, and hydrogen production stations coordinate with each other to maintain power balance. THPE's flexible transfer between hydrogen production stations improves the operational flexibility of the power system. In particular, renewable energy power plants exhibit less wind and solar curtailment under different scenarios, resulting in higher renewable energy utilization rates, with a total wind and solar curtailment of 905.4 MWh during the dispatch cycle.

[0127] Figure 7 This describes the HV's travel route, rated hydrogen exchange power, and real-time power. The renewable energy sources for hydrogen production stations vary across different scenarios. THPE (hydrogen generation equipment) travels to different stations for hydrogen production, ensuring the reasonable utilization of renewable energy. HVs travel to different stations for hydrogen refueling and are then transported to hydrogen load centers. The transport routes for HV1 and HV2 are as follows: Figure 7 As shown in the figure. The results indicate that by optimizing hydrogen production, transportation, and consumption, the hydrogen demand of hydrogen load centers can be reasonably met. Figure 8 The ratio of hydrogen supply from conventional hydrogen sources and hydrogen refueling stations at the load center.

[0128] Scheme 2 uses a traditional scheduling model with a fixed rated power for the hydrogen production station. Comparative analysis further demonstrates the superiority of the scheduling strategy proposed in this invention.

[0129] As shown in Table 1 below, frequent operation results in a higher HV cost for Scheme 1 compared to Scheme 2, while a flexible scheduling strategy significantly reduces the cost of thermal power units. Within the scheduling cycle, compared to Scheme 2, the total operating cost of Scheme 1 is reduced by RMB 16.23 million (10.1%).

[0130] Table 1

[0131]

[0132]

[0133] like Figure 9 As shown, compared with algorithms that directly solve the problem, the proposed algorithm achieves an accuracy of 8% under the premise of similar solution time, while traditional methods can only reach a maximum of about 60%. The results verify the superiority of the proposed algorithm. The strategy proposed in this invention can further reduce system operating costs and improve the utilization rate of renewable energy while taking into account the energy balance of the hydroelectric hydrogen chain and its basin power system.

[0134] The above description is merely a description of preferred embodiments of the present invention and is not intended to limit the scope of the present invention in any way. Any changes or modifications made by those skilled in the art based on the above disclosure shall fall within the protection scope of the claims.

Claims

1. A long-term dispatching method for power systems integrating flexible hydroelectric hydrogen chains, characterized in that, Includes the following steps: Step S1: By analyzing the limitations of traditional stationary hydrogen production units, establish operational constraints for the mobile hydrogen production unit THPE that take into account the influence of upstream river water levels. Step S2: Considering the impact of seasonal river water levels on the HV navigation conditions of hydrogen transport vessels, construct spatiotemporal energy transfer constraints for HV; Step S3: Taking the minimum operating cost of the hydroelectric hydrogen chain and its basin power system as the objective function, a medium- and long-term scheduling model for the hydroelectric hydrogen chain basin power system is proposed. Step S4: Considering the impact of the hydrogen load of the hydrogen-carrying vessel on the real-time hydrogen charging and discharging rate, a piecewise linearization method with adaptive accuracy is designed to improve the solution efficiency. Step S5: Use linearization methods to process the nonlinear constraints of the model and solve the scheduling model to obtain the optimization strategy; Step S6: Guide the long-term coordinated operation of the hydroelectric hydrogen chain and its basin power system based on the optimization strategy.

2. The long-term dispatching method for a power system integrating a flexible hydroelectric hydrogen chain as described in claim 1, characterized in that, In step S1, the THPE operating constraints are set as follows: in, The mobile hydrogen production vessel k is located at station i in scenario s; The minimum navigation depth for the mobile hydrogen production vessel k; Let 's' be the water depth in river channel ij under scenario 's'. For hydrogen production vessel k, a passage marker is placed in river channel ij in scenario s; For the transfer flag in adjacent scenarios of hydrogen production vessels; For use as a working symbol for hydrogen production vessels; This represents THPE's real-time hydrogen production capacity. The rated hydrogen production capacity and minimum hydrogen production capacity of the hydrogen production unit; The amount of hydrogen produced for THPE; η h denoted as THPE's hydrogen production efficiency; M is an infinitely large positive number. The hydrogen storage constraints of the HPS are set as follows: in, Let i be the amount of hydrogen produced by hydrogen production station i at time t in scenario s. Let be the amount of hydrogen charged at node i for the nth HV; Hydrogen charge / discharge rates for the i-node HPS; The maximum hydrogen charging rate for the i-node HPS hydrogen storage tank; The amount of hydrogen stored in the hydrogen storage tank at time t on day s; T / S / 0 represent the last day, the last moment, and the initial moment of the scheduling cycle, respectively; The rated capacity of the HPS hydrogen storage tank at node i.

3. The long-term dispatching method for a power system integrating a flexible hydroelectric hydrogen chain as described in claim 2, characterized in that, In step S2, the HV spatiotemporal energy transfer constraint is set as follows: in, The flag of the hydrogen transport vessel k at time t in scenario s is located at station i. Let HV be the travel time between stations i and j; This is a flag indicating whether a vessel can pass through the waterway ij; T is the scheduling period; M is an infinite positive number. Also includes: The relationship between compression power and high-pressure hydrogen storage pressure is expressed in the following formula (19); The equation of state for a gas is expressed in the following formula (20); p hv V hv =n hv RT hv (20) The relationship between the number of hydrogen moles and the amount of hydrogen stored in the high-pressure hydrogen storage system is expressed in the following formula (21); n hv =E hv / M h (21) The maximum available hydrogen charging rate related to the initial hydrogen storage capacity is calculated, as expressed in the following formula (22); In the formula, To do work to compress hydrogen, V represents the initial and final pressures during hydrogen charging. hv For hydrogen storage capacity, T hv Where R is the compressor operating temperature, n is the gas constant, and n is the gas temperature. hv M is the amount of hydrogen gas. h Here is the molar mass of hydrogen. This represents the initial hydrogen storage capacity. The hydrogen storage constraint settings for the HV are as follows: in, Indicates the real-time hydrogen charge / discharge rate of HV; This represents the maximum hydrogen charging rate for HV. This refers to the real-time hydrogen storage capacity of HV. This represents the initial hydrogen storage capacity (HV). The hydrogen storage capacity at the end of the HV scheduling cycle, d s The number of days included in a typical scenario; The rated hydrogen storage capacity of the ship; According to the Bertrand model, the hydroelectric hydrogen energy chain can compete for market share in hydrogen sales by adjusting hydrogen prices. Therefore, the operating constraints of the hydrogen refueling station HRS considering market response are set as follows: in, This represents the amount of hydrogen sold by hydrogen refueling station i at time t in scenario s. This is the standard hydrogen supply from a hydrogen source. For the hydrogen load at hydrogen refueling station i at time t in scenario s, Let be the hydrogen release rate at station i at time t in scenario k of the ship. The price of hydrogen sold at site i in scenario s. The initial hydrogen price at the hydrogen refueling station. This is the hydrogen price coefficient.

4. A long-term dispatching method for a power system integrating a flexible hydroelectric hydrogen chain as described in claim 3, characterized in that, In step S3, the formula for the objective function is set as follows: min f g +f thpe +f hv -f h (33) Among them, f g The total cost of the thermal power unit. For the unit operating cost of thermal power units, Let i be the operating power of thermal power unit i at time t in scenario s. The start-up and shutdown costs of thermal power units, For the start / stop indication of thermal power units, d s The number of days included in each typical scenario; f thpe p represents the total transfer cost of a mobile hydrogen production vessel. thpe,k For the cost of a single transfer of hydrogen production vessels, For the transfer marking of mobile hydrogen production vessels; f hv p is the sum of the transfer cost of HV and the driver cost. hv,k For the unit operating cost of a ship, For the station marker position of the ship, p lab p is the daily labor cost for one ship. hv,k For HV, the hourly transfer cost; f h For the revenue from hydrogen sales at hydrogen refueling stations, For the hydrogen price in scenario i of hydrogen refueling stations, For hydrogen refueling station scenario i, the amount of hydrogen sold at time t; The grid constraints of the hydroelectric power system in the waterway hydrogen chain basin are set as follows: Where, θ i,t x is the phase angle of the voltage at node i; ij Let ij be the impedance of the transmission line; Let be the power flowing through the ij transmission line; To provide power to thermal power units; For wind power output at node i; For node i load; For hydrogen production capacity; Rated power of thermal power unit; The ramp rate of the thermal power unit; This refers to the rated power of the wind turbine.

5. A long-term dispatching method for a power system integrating a flexible hydroelectric hydrogen chain as described in claim 4, characterized in that, In step S4, the adaptive piecewise linearization approximation method specifically includes: an accuracy-aware adaptive piecewise stage and a linearization approximation stage; Assuming that the above formula (25) is processed, the following formula is used for calculation: f(x) represents the actual hydrogen charging rate function related to the initial hydrogen storage capacity (HV) of the hydrogen transport vessel; g(x) represents the linearized approximation function; Equation (44) represents the actual hydrogen charging power function of the hydrogen transport vessel, which varies with the initial hydrogen storage capacity; Equation (45) represents the first derivative of the actual hydrogen charging rate function of the hydrogen transport vessel; Equation (46) represents the linearized approximation hydrogen charging rate function of the hydrogen transport vessel; Equation (47) represents the linear slope; Equation (48) defines the maximum linearized approximation error; Equation (49) gives the endpoints of all segmented intervals; where, To do work in compressing hydrogen, T hv R is the compressor operating temperature, R is the gas constant, and M is the gas constant. h is the molar mass of hydrogen gas; adjacent points and The x-coordinate of the point of tangency that satisfies the error value Δe; Let x be the first and last points on the x-axis; x is the x-axis obtained sequentially to satisfy the error value.

6. A long-term dispatching method for a power system integrating a flexible hydroelectric hydrogen chain as described in claim 5, characterized in that, In step S5, the rated hydrogen storage capacity of the hydrogen transport vessel (HV) is divided into multiple intervals using V breakpoints. The maximum available hydrogen charging power of the HV at any given time is approximated as a linear combination of the hydrogen energy storage at the breakpoints. This scheduling model is expressed as follows: Equation (50) restricts the real-time hydrogen storage capacity of the hydrogen transport vessel (HV) to fall within one of the V-1 intervals; Equation (51) indicates that the sum of the hydrogen storage weights corresponding to all breakpoints equals 1; Equation (52) indicates that the weight of a breakpoint is non-zero only when an interval is selected; Equation (53) gives the relationship between the real-time hydrogen storage capacity and the hydrogen storage capacity at breakpoints; Equation (54) calculates the maximum available hydrogen charging power of the hydrogen transport vessel (HV) based on the hydrogen energy storage at breakpoints; V-1 is the number of linearized segments; The selected segment; As weight; This represents the hydrogen storage capacity at the corresponding breakpoint. This is the rated hydrogen charging rate.

7. A long-term dispatching method for a power system integrating a flexible hydroelectric hydrogen chain as described in claim 6, characterized in that, Step S5 specifically includes the following steps: Step S51: Use linearization techniques to transform the nonlinear constraints and scheduling model into a classic mixed-integer linear programming problem; Step S52: Call the preset solver to solve the linearized mixed-integer linear programming problem and obtain the optimization result; Step S53: Output the long-term coordinated operation power of the hydrogen chain in the waterway and its basin power system from the optimization results.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements a long-term scheduling method for a power system integrating a flexible waterway hydrogen chain as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a long-term scheduling method for a power system integrating a flexible waterway hydrogen chain as described in any one of claims 1 to 7.

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