Medium-and-long-term scheduling method for electric power system fused with flexible waterway hydrogen chain

Abstract

The invention belongs to the technical field of co-scheduling of a river water path hydrogen chain and a watershed power system thereof, and particularly relates to a medium and long-term scheduling method of a power system fused with a flexible water path hydrogen chain. Comprising the following steps: establishing THPE operation constraints considering upstream river water level influence; the influence of the seasonal water level of the river channel on HV navigation conditions is considered, and HV space-time energy transfer constraints are constructed; taking the lowest operating cost of the waterway hydrogen chain and the watershed power system thereof as an objective function, and proposing a medium-and-long-term scheduling model of the waterway hydrogen chain watershed power system; the influence of the hydrogen carrying capacity of the hydrogen transport ship on the real-time hydrogen charging and discharging rate is considered, and a precision self-adaptive piecewise linearization method is designed to improve the solving efficiency; processing the nonlinear constraint of the model by adopting a linearization method, and solving the scheduling model to obtain an optimization strategy; according to the optimization strategy, medium-and-long-term cooperative operation of the waterway hydrogen chain and the watershed power system thereof is guided. According to the method, the cooperative scheduling capability and economical efficiency of the hydrogen-electricity system can be remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of coordinated dispatching of river waterway hydrogen chains and their basin power systems, and particularly relates to a medium- and long-term dispatching method for a power system integrating a flexible waterway hydrogen chain, and more particularly to a medium- and long-term coordinated dispatching strategy for a waterway hydrogen chain and its power system considering flexible hydrogen production, transportation, and sales. Background Art

[0002] Using clean electricity for electrolytic hydrogen production can achieve zero carbon dioxide emissions, which is not only an ideal form to meet hydrogen energy demand but also an inevitable choice to promote the local consumption of surplus energy. However, this dynamic energy conversion easily leads to imbalances in the supply and demand of electric energy and hydrogen energy in the same time and space. Therefore, it is necessary to coordinate the relationship between the power system and the waterway hydrogen chain and formulate a reasonable coordinated dispatching strategy.

[0003] Large-scale long-distance hydrogen energy storage and transportation face the following problems under the existing hydrogen transportation methods: the capacity of gaseous hydrogen trailers is limited, liquid hydrogen tank trucks consume high energy, the cost of dedicated hydrogen pipelines is high and popularization is difficult, and although natural gas pipelines can be blended with hydrogen flexibly, they are limited by the ratio and have safety hazards. At the same time, there is a lack of connection between natural gas pipelines and renewable energy bases, making it more difficult for green hydrogen to be incorporated. The current mainstream storage and transportation solutions are difficult to balance safety and economy and cannot effectively support the large-scale cross-regional transportation of green hydrogen. Summary of the Invention

[0004] The purpose of the invention is to provide a medium- and long-term dispatching method for a power system integrating a flexible waterway hydrogen chain. Since traditional HPE is limited by fixed siting, which is not conducive to flexible hydrogen transportation and grid coordinated regulation, the invention aims to solve the limitations of traditional fixed hydrogen production devices (HPE) in hydrogen transportation and grid support.

[0005] To solve the above technical problems, the invention provides a medium- and long-term dispatching method for a power system integrating a flexible waterway hydrogen chain, including the following steps:

[0006] Step S1: By analyzing the limitations of traditional fixed hydrogen production devices, establish the operation constraints of a mobile hydrogen production device THPE considering the influence of upstream river water levels.

[0007] Step S2: Considering the influence of seasonal river water levels on the navigation conditions of hydrogen transportation ships HV, construct the spatio-temporal energy transfer constraints of HV.

[0008] Step S3: Taking the lowest operation cost of the waterway hydrogen chain and its basin power system as the objective function, propose a medium- and long-term dispatching model for the waterway hydrogen chain basin power system.

[0009] Step S4: Considering the influence of the hydrogen-carrying capacity of hydrogen transportation ships on the real-time hydrogen charging and discharging rate, design a piecewise linearization method with adaptive accuracy to improve the solution efficiency.

[0010] Step S5: Process the non - linear constraints of the model using a linearization method, and solve the scheduling model to obtain an optimization strategy;

[0011] Step S6: Guide the medium - and long - term coordinated operation of the waterway hydrogen chain and its basin power system according to the optimization strategy.

[0012] Preferably, in the said Step S1, the THPE operation constraints are set as follows:

[0013]

[0014]

[0015] Among them, is the flag bit of the mobile hydrogen - production ship k at site i under scenario s; is the minimum navigation water depth of the mobile hydrogen - production ship k; is the water depth of the river channel ij under scenario s; is the passing flag of the hydrogen - production ship k in the river channel ij under scenario s; is the transfer flag bit of the hydrogen - production ship in the adjacent scenario; is the working flag of the hydrogen - production ship; is the real - time hydrogen - production power of THPE; is the rated hydrogen - production power and the minimum hydrogen - production power of the hydrogen - production device; is the hydrogen amount produced by THPE; η h is the hydrogen - production efficiency of THPE; M is a positive number approaching infinity.

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

[0017]

[0018] Among them, is the hydrogen - production amount of the hydrogen - production station i at time t under scenario s, is the hydrogen - filling amount of the nth HV at node i; is the hydrogen storage amount of the HPS at node i; is the maximum hydrogen - charging / discharging rate of the hydrogen storage tank of the HPS at node i; is the hydrogen storage amount of the hydrogen storage tank at time t on the s - th day; T / S / 0 respectively represent the last day, the last moment, and the initial moment of the scheduling period; is the rated capacity of the hydrogen storage tank of the HPS at node i.

[0019] Preferably, in the said Step S2, the HV spatio - temporal energy transfer constraints are set as follows:

[0020]

[0021] Among them, is the flag bit of the hydrogen-carrying ship k at the site i at time t in the scenario s; is the passing time of the HV between the sites i and j; is the flag bit indicating whether the ship can pass through the river ij; T is the scheduling period; M is a positive number approaching infinity;

[0022] It also includes:

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

[0024]

[0025] The gas state equation, which is expressed in the following formula (20);

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

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

[0028] n hv = E hv / M h (21)

[0029] Calculating the maximum available hydrogen charging rate related to the initial hydrogen storage amount, which is expressed in the following formula (22);

[0030]

[0031] In the formula, is the work done by compressing hydrogen, are the initial and final hydrogen charging pressures, V hv is the hydrogen storage capacity, T hv is the operating temperature of the compressor, R is the gas constant, n hv is the amount of hydrogen substance, M h is the molar mass of hydrogen; is the initial hydrogen storage capacity.

[0032] The hydrogen storage constraint of the HV is set as follows:

[0033]

[0034] Among them, represents the real-time hydrogen charging / discharging rate of the HV; is the maximum hydrogen charging rate of the HV; is the real-time hydrogen storage capacity of HV, is the initial hydrogen storage capacity of HV, is the hydrogen storage capacity at the end of the HV scheduling period, d s is the number of days included in the typical scenario; is the rated hydrogen storage capacity of the ship.

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

[0036]

[0037] Among them, is the hydrogen sales volume of hydrogen refueling station i at time t in scenario s, is the hydrogen supply of conventional hydrogen sources, is the hydrogen load of hydrogen refueling station i at time t in scenario s, is the hydrogen release rate of ship k at time t in scenario s at station i, is the hydrogen sales price of station i in scenario s, is the initial hydrogen price of the hydrogen refueling station, is the hydrogen price coefficient.

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

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

[0040]

[0041] Among them, f g is the total cost of the thermal power unit, is the unit operating cost of the thermal power unit, is the operating power of thermal power unit i at time t in scenario s, is the start-stop cost of the thermal power unit, is the start-stop flag of the thermal power unit, d s is the number of days included in each typical scenario; f thpe is the total transfer cost of the mobile hydrogen production ship, p thpe,k is the single transfer cost of the mobile hydrogen production ship, is the transfer flag of the mobile hydrogen production ship; f hv is the sum of the transfer cost and the driver cost of HV, p hv,k is the unit driving cost of the ship, is the station flag bit of the ship, plab is the labor cost of a ship per day, p hv,k is the transfer cost of HV per hour; f h is the hydrogen sales revenue of the hydrogen refueling station, is the hydrogen price in scenario s of hydrogen refueling station i, is the hydrogen quantity sold at time t in scenario s of hydrogen refueling station i.

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

[0043]

[0044] Among them, θ i,t is the voltage phase angle of node i; x ij is the impedance of the ij transmission line; is the power flowing through the ij transmission line; is the output of the thermal power unit, is the wind power output of node i; is the load of node i; is the hydrogen production power; is the rated power of the thermal power unit; is the ramp rate of the thermal power unit; is the rated power of the wind turbine.

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

[0046] Assume that the above formula (25) is processed and calculated using the following formula:

[0047]

[0048]

[0049] f(x) represents the actual hydrogen filling rate function related to the initial energy storage of the hydrogen transport ship HV; g(x) represents the linear approximation function; formula (44) represents the actual hydrogen filling power function of the hydrogen transport ship, which changes with the initial hydrogen storage; formula (45) represents the first derivative of the actual hydrogen filling rate function of the hydrogen transport ship; formula (46) represents the linearized approximate hydrogen filling rate function of the hydrogen transport ship; formula (47) represents the linear slope; formula (48) defines the maximum linear approximation error; formula (49) gives the endpoints of all segmented intervals; among them, is the work done by compressing hydrogen, T hv is the working temperature of the compressor, R is the gas constant, M h is the molar mass of hydrogen; is the adjacent point and The abscissa of the tangent point that satisfies the error value Δe; Are the first and last points on the abscissa; x is the abscissa that successively satisfies the error value.

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

[0051]

[0052]

[0053] Equation (50) restricts that the real-time hydrogen storage of the hydrogen transport ship HV can only fall into one of the V - 1 intervals; Equation (51) indicates that the sum of the hydrogen storage weights corresponding to all breakpoints is equal to 1; Equation (52) indicates that only when a certain interval is selected, the weight of the breakpoint takes a non-zero value; Equation (53) gives the relationship between the real-time hydrogen storage and the hydrogen storage at the breakpoint; Equation (54) calculates the maximum available hydrogen filling power of the hydrogen transport ship HV according to the hydrogen energy storage at the breakpoint; V - 1 is the number of linearization segments; Is the selected segment; Is the weight; Is the hydrogen storage corresponding to the corresponding breakpoint; Is the rated hydrogen filling rate.

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

[0055] Step S51: Adopt linearization technology to transform the non-linear constraints and scheduling model into a classical mixed-integer linear programming problem;

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

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

[0058] The present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a medium- and long-term scheduling 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, on which a computer program is stored. When the computer program is executed by a processor, it implements a medium- and long-term scheduling method for a power system integrating a flexible waterway hydrogen chain as described above.

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

[0061] The present invention proposes a medium- and long-term scheduling strategy for a power system integrating a flexible waterway hydrogen chain, which specifically includes: First, establish a spatio-temporal transfer characteristic model of a shipborne transferable hydrogen production device (THPE) and a hydrogen transport ship (HV) considering the influence of river water level, and quantify the dynamic coupling relationship between the hydrogen storage capacity of the HV and the real-time hydrogen filling rate; Second, introduce the Bertrand game model to guide the hydrogen energy sales strategy of the hydrogen refueling station (HRS), taking into account the market response behavior of other hydrogen sources; On this basis, construct a medium-term scheduling optimization model for the power system integrating the waterway hydrogen chain, and use a piecewise linearization method with adaptive precision to transform it into a mixed-integer linear programming (MILP) problem to improve the solution efficiency. Finally, through the verification of the improved IEEE 30-node power system and river network simulation, it is shown that this strategy can significantly improve the coordinated scheduling ability and economy of the hydrogen-electric system, and is used to solve the problem of insufficient coordination ability between the existing waterway hydrogen chain and the basin power system, resulting in the imbalance between the supply and demand of electric energy and hydrogen energy in the same space and time. The present invention can coordinate the power and electricity balance, improve the utilization rate of renewable energy, and at the same time reduce the system operation cost. Brief Description of the Drawings

[0062] Figure 1 It is a flow chart of the medium- and long-term scheduling steps of a waterway hydrogen chain and its power system considering flexible hydrogen production, transportation and sales provided by an embodiment of the present invention.

[0063] Figure 2 It is a navigation chart of a mobile hydrogen production ship (THPE) considering the influence of water level provided by an embodiment of the present invention.

[0064] Figure 3 It is a relationship diagram of the rated hydrogen filling rate of a ship considering the real-time hydrogen load provided by an embodiment of the present invention.

[0065] Figure 4 It is a modified wiring diagram of the waterway hydrogen chain and its basin power system IEEE 30-node provided by an embodiment of the present invention.

[0066] Figure 5 It is a data diagram of the rated hydrogen production power of a hydrogen production station provided by an embodiment of the present invention.

[0067] Figure 6 It is a data diagram of the electric power balance provided by an embodiment of the present invention.

[0068] Figure 7 It is a relationship diagram of the spatio-temporal position of a hydrogen transport ship and the hydrogen charging / discharging of the hydrogen transport ship provided by an embodiment of the present invention.

[0069] Figure 8 It is a data diagram of the hydrogen load supply ratio and market bidding price provided by an embodiment of the present invention.

[0070] Figure 9 This is a data graph comparing the solution time and accuracy of the proposed algorithm and the traditional scheme provided by the embodiments of the present invention. Detailed implementation manners

[0071] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. According to the following description, the advantages and features of the present invention will be clearer. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise scales, only for the purpose of facilitating and clearly assisting in explaining the purpose of the embodiments of the present invention.

[0072] As Figure 1 shown, the embodiments of the present invention specifically disclose a waterway hydrogen chain considering flexible hydrogen production, transportation and sales and a medium- and long-term scheduling method for its power system, including the following steps:

[0073] S1. By analyzing the limitations of traditional fixed hydrogen production devices, establish the operation constraints of transferable hydrogen production equipment (THPE) considering the influence of upstream river water levels.

[0074] S2. Considering the influence of seasonal river water levels on the navigation conditions of hydrogen vessels (HV), construct the spatio-temporal energy transfer constraints of HV.

[0075] S3. Taking the lowest operation cost of the waterway hydrogen chain and its basin power system as the objective function, propose a medium- and long-term scheduling model for the waterway hydrogen chain basin power system.

[0076] S4. Considering the influence of the hydrogen-carrying capacity of hydrogen vessels on the real-time hydrogen charging and discharging rate, design a piecewise linearization method with adaptive accuracy to improve the solution efficiency.

[0077] S5. Use the linearization method to process the non-linear constraints of the model, and solve the scheduling model to obtain the optimization strategy.

[0078] S6. Guide the medium- and long-term coordinated operation of the waterway hydrogen chain and its basin power system according to the optimization strategy.

[0079] In step S1, renewable energy bases often generate curtailment of electricity, and due to the influence of the capacity of transmission lines, power load centers may have problems of insufficient power supply. If mobile hydrogen production ships are used to produce hydrogen at renewable energy bases, and then hydrogen transportation ships are used to transport hydrogen to the downstream receiving power grid, and the electro-hydrogen conversion is achieved through hydrogen energy generators to meet the power demand. This method can not only flexibly absorb renewable energy and improve the utilization rate of renewable energy of the former, but also provide energy supply for the latter. In this process, due to the limitations of traditional fixed hydrogen production devices, mobile hydrogen production ships (THPE) can play their unique advantages and improve the hydrogen production efficiency. THPE operation constraints:

[0080]

[0081]

[0082] Wherein, is the flag bit of mobile hydrogen production ship k located at site i under scenario s; is the minimum navigation water depth of mobile hydrogen production ship k; is the water depth of river channel ij under scenario s; is the passage flag of hydrogen production ship k located in river channel ij under scenario s; is the transfer flag bit of the hydrogen production ship in the adjacent scenario; is the working flag of the hydrogen production ship; is the real-time hydrogen production power of THPE; are the rated hydrogen production power and the minimum hydrogen production power of the hydrogen production device; is the amount of hydrogen produced by THPE; η h is the hydrogen production efficiency of THPE.

[0083] Hydrogen storage constraints of HPS:

[0084]

[0085] Wherein, is the hydrogen filling amount of the nth HV at node i; is the hydrogen storage amount of HPS at node i; is the maximum hydrogen charging / discharging rate of the hydrogen storage tank of HPS at node i; is the hydrogen storage amount of the hydrogen storage tank at the t-th moment of the s-th day; T / S / 0 respectively represent the last day, the last moment, and the initial moment of the scheduling period; is the rated capacity of the hydrogen storage tank of HPS at node i.

[0086] In the dry winter, the water level of the river may not meet the navigation requirements of HV. Considering the spatio-temporal transfer constraints of seasonal water level affecting HV navigation are as follows:

[0087]

[0088] wherein, is the flag bit of the hydrogen transport ship k at the station i at the moment t in the scenario s; is the passing time of the HV between the stations i and j; is the flag bit indicating whether the ship can pass through the river course ij.

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

[0090]

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

[0092] n hv = E hv / M h (21)

[0093]

[0094] wherein, is the work done by compressing hydrogen, are the initial pressure and the final pressure of hydrogen filling, V hv is the hydrogen storage capacity, T hv is the working temperature of the compressor.

[0095] Hydrogen storage constraint of HV:

[0096]

[0097] wherein, represents the real-time hydrogen charging / discharging rate of the HV; is the maximum hydrogen filling rate of the HV; is the real-time hydrogen storage capacity of the HV, is the initial hydrogen storage capacity of the HV, is the hydrogen storage capacity at the end of the HV scheduling period, d s is the number of days included in the typical scenario.

[0098] As a commodity, the price of hydrogen is jointly determined by all hydrogen sources in the market. According to the Bertrand model, the waterway hydrogen energy chain can compete for the market share of hydrogen energy sales by adjusting the price of hydrogen. The operating constraints of hydrogen refueling stations (HRS) considering market reactions are described as follows:

[0099]

[0100] In the formula, is the hydrogen sales volume of hydrogen refueling station i at time t in scenario s, is the hydrogen supply of conventional hydrogen sources, is the hydrogen load of hydrogen refueling station i at time t in scenario s, is the hydrogen sales price of station i in scenario s, is the initial hydrogen price of the hydrogen refueling station, is the hydrogen price coefficient.

[0101] Taking the minimum short-term operating cost of the waterway hydrogen chain and its basin power system as the objective function, a medium- and long-term scheduling model of the waterway 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 is the total cost of thermal power units, where, is the unit operating cost of thermal power units, is the operating power of thermal power unit i at time t in scenario s, is the start-stop cost of thermal power units, is the start-stop flag of thermal power units; f thpe is the total transfer cost of mobile hydrogen production ships, p thpe,k is the single transfer cost of mobile hydrogen production ships, is the transfer flag of mobile hydrogen production ships; f hv is the sum of the transfer cost and driver cost of HV, p lab is the labor cost of one ship per day, p hv,k is the transfer cost of HV per hour; f h is the hydrogen sales revenue of hydrogen refueling stations.

[0106] Constraints of the basin power system grid:

[0107]

[0108]

[0109] where θ i,t is the voltage phase angle of node i; x ij is the impedance of the transmission line ij; is the power flowing through the transmission line ij; is the wind power output of node i; is the load of node i; is the hydrogen production power.

[0110] Considering the influence of the hydrogen storage capacity of the hydrogen transport ship on the real-time hydrogen charging and discharging rate, a piecewise linearization method with adaptive precision is designed to improve the solution efficiency.

[0111] To solve the scheduling model with non-linear 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 ship HV. g(x) represents the linearization approximation function. When translated to be tangent, the difference in their function values at the corresponding tangent points reaches the maximum. Therefore, given the maximum error and the initial endpoints, 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 ship, which changes with the initial hydrogen storage capacity. Equation (45) represents the first derivative of the actual hydrogen charging rate function of the hydrogen transport ship. Equation (46) represents the linearized approximate hydrogen charging rate function of the hydrogen transport ship. Equation (47) represents the linear slope of. Equation (48) defines the maximum linearization approximation error. Equation (49) gives the endpoints of all piecewise intervals.

[0114] The linearization method is used to handle the non-linear constraints of the model, and the scheduling model is solved to obtain the optimal scheduling strategy.

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

[0116]

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

[0118] The above-mentioned step 5 specifically includes:

[0119] Step 51, using linearization techniques to transform the non-linear constraints and scheduling model into a classical mixed-integer linear programming problem;

[0120] Step 52, calling a preset solver to solve the linearized mixed-integer linear programming problem to obtain the optimization result;

[0121] Step 53, outputting the medium- and long-term collaborative operation power of the waterway hydrogen chain and its basin power system from the optimization result.

[0122] An embodiment of the present invention also discloses a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the above-mentioned medium- and long-term scheduling strategy of the waterway hydrogen chain and its power system considering flexible hydrogen production, transportation, and sales.

[0123] An embodiment of the present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of the above-mentioned medium- and long-term scheduling strategy of the waterway hydrogen chain and its power system considering flexible hydrogen production, transportation, and sales.

[0124] To enable those skilled in the art to better understand the present invention and the advantages of the present invention's technology, the following explanations are made in combination with specific embodiments of the present invention:

[0125] The simulation platform is set as follows: an Intel(R) Core(TM) i5-10210U CPU@1.60GHz desktop computer. Call the Yalmip toolbox and Gurobi optimization software based on the Matlab R2022a platform. Figure 2 The THPE navigation conditions provided for the embodiments of the present invention describe the correlation between THPE and the river water level that changes with seasons. It can be seen from the figure that THPE can only transfer when the seasonal water level of the river is greater than the minimum navigation depth of THPE. The rated hydrogen charging rate of the hydrogen-carrying vessel when charging at the station is as Figure 3 shown. Figure 4The basic data provided for the invention embodiments. During specific implementation, the waterway hydrogen chain, the power balance of the power system in its basin, and the HV spatio-temporal transfer situation are obtained from the optimization results, and then the operation can be guided according to this optimized scheduling strategy.

[0126] Figure 5 It can be seen that flexible transfer is carried out under different THPE scenarios, resulting in different rated hydrogen production powers of hydrogen production stations under different scenarios. The operating power of the power system of the proposed scheduling model is as Figure 6 shown. The thermal power plant, the renewable energy power station, and the hydrogen production station coordinate with each other to maintain power balance. The flexible transfer of THPE between hydrogen production stations improves the operating flexibility of the power system. In particular, under different scenarios, the curtailment of wind and light in new energy power stations is less, and the utilization rate of renewable energy is higher. The total curtailment of wind and light during the scheduling period is 905.4 megawatt-hours.

[0127] Figure 7 For the HV navigation route, the rated hydrogen exchange power and the real-time power. The renewable energy of hydrogen production stations is different under different scenarios. THPE goes to different stations for hydrogen production, and the renewable energy is reasonably consumed. HV goes to different stations for hydrogen filling and is transported to the hydrogen load center. The transfer routes of HV1 and HV2 are as Figure 7 shown. The results show that by optimizing hydrogen energy production, transportation, and consumption, the hydrogen demand of the hydrogen load center can be reasonably met. Figure 8 For the hydrogen supply ratio of the conventional hydrogen source and the hydrogen refueling station at the load center.

[0128] Set the traditional scheduling model as Scheme 2, and this model sets a fixed rated power of the hydrogen production station. Through comparative analysis, the superiority of the scheduling strategy proposed in the present invention is further reflected.

[0129] As can be seen from Table 1 below, frequent operation makes the HV cost of Scheme 1 higher than that of Scheme 2, while the flexible scheduling strategy significantly reduces the cost of thermal power units. During the scheduling period, compared with Scheme 2, the total operating cost of Scheme 1 is reduced by 16.23 million yuan (10.1%).

[0130] Table 1

[0131]

[0132]

[0133] As Figure 9 shown, compared with the algorithm for directly solving the problem, under the premise of approximate solution time, the accuracy of the proposed algorithm can reach 8%, while the traditional method can only reach about 60% at most. The results verify the superiority of this algorithm. The strategy proposed in the present invention can further reduce the system operating cost and improve the utilization rate of renewable energy while taking into account the energy balance of the waterway hydrogen chain and its basin power system.

[0134] The above description is only a description of the preferred embodiments of the present invention and does not limit the scope of the present invention in any way. Any changes and modifications made by those of ordinary skill in the art of the present invention based on the above disclosure fall within the scope of protection of the claims.

Claims

1. A method for medium- and long-term dispatching of power systems integrating a flexible waterway hydrogen chain, characterized in that: The steps include: Step S1: By analyzing the limitations of the traditional fixed hydrogen production device, the operation constraints of the mobile hydrogen production device THPE considering the influence of the upstream river water level are established; Step S2: Considering the impact of seasonal water levels of the river on the navigation conditions of hydrogen transport vessels HV, the HV spatiotemporal energy transfer constraints are constructed; Step S3: Taking the lowest operating cost of the water-road-hydrogen chain and its basin power system as the objective function, a medium- and long-term dispatch model for the water-road-hydrogen chain basin power system is proposed; Step S4: Considering the influence of the hydrogen carrying capacity of the hydrogen transport ship on the real-time hydrogen charging and discharging rate, a precision-adaptive piecewise linearization method is designed to improve the solution efficiency; Step S5: using a linearization method to process the nonlinear constraints of the model, solving the scheduling model to obtain an optimization strategy; Step S6: Guiding the medium- and long-term coordinated operation of the waterway hydrogen chain and its basin power system according to the optimization strategy.

2. A method for medium- and long-term dispatching of a power system integrating a flexible waterway hydrogen chain as claimed in claim 1, characterized in that: In step S1, the THPE operation constraints are set as follows: in, is the mark position of mobile hydrogen production ship k at site i in scenario s; is the minimum navigation depth of the mobile hydrogen production ship k; is the water depth of the river ij under scenario s; is the passage sign of hydrogen production ship k located in river channel ij under scenario s; It is the transfer mark position in the adjacent scenario of hydrogen production ships; It is the working mark of hydrogen-producing ship; is the real-time hydrogen production power of THPE; The rated hydrogen production power and minimum hydrogen production power of the hydrogen production device; is the amount of hydrogen produced by THPE; η h is the hydrogen production efficiency of THPE; M is an infinite positive number; The hydrogen storage constraints of the HPS are set as follows: in, is the hydrogen production of hydrogen production station i at time t in scenario s, is the hydrogen filling amount of the nth HV at the i-th node; is the hydrogen charging and discharging rate of HPS at node i; is the maximum hydrogen filling rate of the HPS hydrogen storage tank at node i; is the hydrogen storage capacity of the hydrogen storage tank at time t on the sth day; T / S / 0 represents the last day, the last time and the initial time of the scheduling period respectively; is the rated capacity of the HPS hydrogen storage tank at node i.

3. A method for medium- and long-term dispatching of a power system integrating a flexible waterway hydrogen chain as claimed in claim 2, characterized in that: In step S2, the HV spatiotemporal energy transfer constraints are set as follows: in, is the flag position of hydrogen transport ship k at site i at time t in scenario s; is the travel time of HV between stations i and j; is the flag indicating whether the ship can pass through the river ij; T is the scheduling cycle; 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 gas state equation 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, which is expressed in the following formula (22): In the formula, To compress the hydrogen, is the initial and final pressure of hydrogen filling, V hv is the hydrogen storage capacity, T hv is the compressor operating temperature, R is the gas constant, n hv is the amount of hydrogen substance, M h is the molar mass of hydrogen, is the initial hydrogen storage capacity; The hydrogen storage constraints of the HV are set as follows: in, Indicates the real-time hydrogen charging / discharging rate of HV; is the maximum hydrogen charging rate of HV; is the real-time hydrogen storage capacity of HV, is the initial hydrogen storage capacity of HV, is the hydrogen storage capacity at the end of the HV dispatch period, d s is the number of days included in the typical scenario; is the rated hydrogen storage capacity of the ship; According to the Bertrand model, the waterway hydrogen energy chain can compete for the market share of hydrogen energy sales by adjusting the price of hydrogen. Therefore, the operating constraints of the hydrogen refueling station HRS considering the market response are set as follows: in, is the hydrogen sales volume of hydrogen refueling station i at time t in scenario s, is the hydrogen supply of conventional hydrogen source, is the hydrogen load of hydrogen station i at time t in scenario s, is the hydrogen discharge rate of ship k at site i at time t in scenario s, is the hydrogen selling price at site i in scenario s, is the initial hydrogen price at the hydrogen refueling station, is the hydrogen price coefficient.

4. A method for medium- and long-term dispatching of a power system integrating a flexible waterway hydrogen chain as claimed in claim 3, characterized in that: In step S3, the formula of the objective function is set as follows: min f g +f thpe +f hv -f h (33) Among them, f g is the total cost of the thermal power unit, is the unit operating cost of thermal power units, is the operating power of thermal power unit i at time t in scenario s, is the start-up and shutdown cost of thermal power units, It is the start and stop sign of the thermal power unit, d s is the number of days included in each typical scenario; f thpe is the total transfer cost of the mobile hydrogen production vessel, p thpe,k is the single transfer cost of the mobile hydrogen production vessel, It is the transfer mark of mobile hydrogen production ship; hv is the sum of the HV transfer cost and the driver cost, p hv,k is the unit travel cost of the ship, is the ship's station mark, p lab is the labor cost of one boat per day, p hv,k is the HV transfer cost per hour; f h The revenue from selling hydrogen at hydrogen refueling stations, is the hydrogen price in scenario s at hydrogen refueling station i, The amount of hydrogen sold at hydrogen station i at time t in scenario s; The grid constraints of the waterway hydrogen chain basin power system are set as follows: Among them, θ i,t is the voltage phase angle of node i; x ij is the ij transmission line impedance; is the power flowing through the ij transmission line; Provide power for thermal power units; The wind power output of node i; is the i-node load; is the hydrogen production power; is the rated power of the thermal power unit; is the climbing rate of the thermal power unit; is the rated power of the wind turbine.

5. A method for medium- and long-term dispatching of a power system integrating a flexible waterway hydrogen chain as claimed in claim 4, characterized in that: In the step S4, the adaptive piecewise linearization approximation method specifically includes: an accuracy-aware adaptive piecewise phase and a linearization approximation phase; Assume that the above formula (25) is processed and calculated using the following formula: f(x) represents the actual hydrogen charging rate function related to the initial energy storage of the hydrogen transport ship HV; g(x) represents the linearized approximate function; Equation (44) represents the actual hydrogen charging power function of the hydrogen transport ship, which changes with the change of the initial hydrogen storage; Equation (45) represents the first-order derivative of the actual hydrogen charging rate function of the hydrogen transport ship; Equation (46) represents the linearized approximate hydrogen charging rate function of the hydrogen transport ship; Equation (47) represents the linear slope; Equation (48) defines the maximum linearized approximate error; Equation (49) gives the endpoints of all segmented intervals; where, To compress hydrogen, T hv is the compressor operating temperature, R is the gas constant, M h is the molar mass of hydrogen; For adjacent points and The horizontal coordinate of the tangent point that satisfies the error value Δe; are the first and last points on the horizontal axis; x is the horizontal coordinate that satisfies the error value obtained in sequence.

6. A method for medium- and long-term dispatching of a power system integrating a flexible waterway hydrogen chain as claimed in claim 5, characterized in that: In step S5, the rated hydrogen storage capacity of the hydrogen transport ship HV is divided into multiple intervals using V breakpoints, and the maximum available hydrogen charging power of the hydrogen transport ship HV at any time is approximated as a linear combination of the breakpoint hydrogen energy storage. The scheduling model is expressed as follows: Formula (50) limits the real-time hydrogen storage capacity of the hydrogen transport ship HV to only fall into one of the V-1 intervals; Formula (51) indicates that the sum of the hydrogen storage weights corresponding to all breakpoints is equal to 1; Formula (52) indicates that only when a certain interval is selected, the weight of the breakpoint takes a non-zero value; Formula (53) gives the relationship between the real-time hydrogen storage capacity and the breakpoint hydrogen storage capacity; Formula (54) calculates the maximum available hydrogen charging power of the hydrogen transport ship HV based on the breakpoint hydrogen energy storage; V-1 is the number of linearization segments; is the selected segment; is the weight; is the hydrogen storage capacity corresponding to the breakpoint; is the rated hydrogen charging rate.

7. A method for medium- and long-term dispatching of a power system integrating a flexible waterway hydrogen chain as claimed in claim 6, characterized in that: The step S5 specifically includes the following steps: Step S51: using linearization technology to transform the nonlinear constraints and scheduling model into a classic mixed integer linear programming problem; Step S52: calling a preset solver to solve the linearized mixed integer linear programming problem to obtain an optimization result; Step S53: Output the medium- and long-term coordinated operation power of the waterway hydrogen chain 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, wherein: When the processor executes the computer program, a medium- and long-term scheduling method for a power system integrating a flexible waterway hydrogen chain is implemented 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 a processor, a medium- and long-term scheduling method for a power system integrating a flexible waterway hydrogen chain is implemented as described in any one of claims 1 to 7.

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