CN116187664A - Photovoltaic power station and hydrogen production and hydrogen adding station system planning method considering traffic flow prediction - Google Patents

Photovoltaic power station and hydrogen production and hydrogen adding station system planning method considering traffic flow prediction Download PDF

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CN116187664A
CN116187664A CN202211640037.1A CN202211640037A CN116187664A CN 116187664 A CN116187664 A CN 116187664A CN 202211640037 A CN202211640037 A CN 202211640037A CN 116187664 A CN116187664 A CN 116187664A
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梁凌
王辉
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China Three Gorges University CTGU
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Abstract

A photovoltaic power station and hydrogen production hydrogen station system planning method considering traffic flow prediction comprises the following steps: introducing a traffic flow prediction method, and obtaining a hydrogen adding station hydrogen adding demand according to traffic flow data and expected vehicle hydrogen adding probability, so as to ensure that the hydrogen fuel cell automobile is timely hydrogenated; determining specific parameters of main equipment of a photovoltaic power station and a hydrogen production and hydrogenation station to obtain data of a power network and a traffic network; taking the minimized system cost as an objective function, and taking traffic network constraint, electric power network constraint and hydrogen production and hydrogenation station main equipment operation constraint into consideration to construct a system planning model of a photovoltaic power station and a hydrogen production and hydrogenation station taking traffic flow prediction into consideration; and solving the model by means of a CPLEX solver in a YALMIP toolbox according to the established photovoltaic power station and hydrogen production and hydrogenation station system planning model, and obtaining the optimal deployment of the positions and capacities of the photovoltaic power station and the hydrogen production and hydrogenation station through simulation verification.

Description

Photovoltaic power station and hydrogen production and hydrogen adding station system planning method considering traffic flow prediction
Technical Field
The invention belongs to the technical field of new energy utilization, and particularly relates to a photovoltaic power station and hydrogen production station system planning method considering traffic flow prediction.
Background
The hydrogen production hydrogenation stations (hydrogen producing and refueling station, HPRS) are used as carriers of hydrogen fuel cell automobiles (Fuel cell vehicle, FCV) in a traffic network and hubs for coupling an electric power network with the traffic network, and are important for scientific planning and layout of the hydrogen production hydrogenation stations. The scholars at home and abroad conduct a great deal of research on the planning problem of HPRS, consider the full life cycle of the hydrogen addition station in the aspect of the optimal operation of the hydrogen addition station, conduct system analysis modeling on the cost benefit of the hydrogen addition station and establish a hydrogen addition station cost benefit assessment model based on full life cycle economy analysis; energy analysis and economic analysis are carried out on different hydrogen station architectures; the research well evaluates and analyzes the optimized operation of the hydrogen station, and provides an integrated optimization model consisting of a generalized Bass diffusion model and a flow capturing position model for exploring the interaction relation between the sales of the hydrogen fuel cell automobiles and the number of the gas stations, and the result shows that the long-term site selection planning of the hydrogen station network can meet the increasing fuel requirements; an optimization method for minimizing installation investment and operation cost is provided, and the optimal capacity of the electrolytic tank and the hydrogen storage equipment is obtained; comprehensively considering the problems of network planning and operation of a hydrogen supply chain, a hydrogen supply chain optimization model based on an off-grid wind hydrogen coupling system, which is favorable for realizing scientific planning of hydrogen infrastructure, is provided. However, the above proposed model does not consider the coupling constraint of the electric power-traffic network, and most of them are off-grid modes, and the cooperative operation between the HPRS and the power grid is not sufficiently described.
For a hydrogen adding station for hydrogen production by utilizing photovoltaic power generation and power grid power supply, an electrolysis system based on a proton exchange membrane electrolysis cell and a design of the hydrogen adding station for photovoltaic power generation are provided; the multi-objective planning method of the electric-thermal hydrogen comprehensive energy system taking the wind-solar uncertainty into consideration is provided to solve the equipment capacity configuration scheme by taking the minimum economic cost, the maximum wind-solar energy absorption rate and the minimum energy supply deficiency as optimization targets. These studies do not mention collaborative planning of electric power-traffic, and at present, the collaborative planning research of electric power-traffic is mainly focused on locating and sizing of electric vehicle charging piles. Meanwhile, traffic network constraint and electric power network constraint are considered, and a wind-hydrogen-electric coupling network planning model is constructed; modeling the hydrogen demand by adopting a section-based method, and establishing an HPRS planning model based on robust remorse by considering the combination of a traffic network and a power distribution network. The above documents do not consider predicting FCV hydrogen demand when considering HPRS planning studies and are rarely combined with renewable energy sources.
Thus, two issues should be considered when considering hydrogen production hydrogen plant system planning issues:
1. the photovoltaic power station is required to be connected with the hydrogen production and hydrogenation station, so that greater economic and environmental benefits are obtained.
2. The uncertainty problem of the hydrogen demand of hydrogen fuel cell automobiles needs to be considered when solving the modeled model.
Disclosure of Invention
In view of the technical problems in the background art, the photovoltaic power station and hydrogen production and hydrogen addition station system planning method considering traffic flow prediction provided by the invention introduces a traffic flow prediction method, and meanwhile, the hydrogen production and hydrogen addition station is combined with the photovoltaic power station, and the connection between the power network and the traffic network is established through the hydrogen production and hydrogen addition station junction, so that the optimal deployment scheme of the positions and the capacities of the photovoltaic power station and the hydrogen production and hydrogen addition station is more practically provided.
In order to solve the technical problems, the invention adopts the following technical scheme:
a photovoltaic power station and hydrogen production hydrogen station system planning method considering traffic flow prediction comprises the following steps:
step 1: introducing a traffic flow prediction method, and obtaining a hydrogen adding station hydrogen adding demand according to traffic flow data and expected vehicle hydrogen adding probability, so as to ensure that the hydrogen fuel cell automobile is timely hydrogenated;
step 2: determining specific parameters of main equipment of a photovoltaic power station and a hydrogen production and hydrogenation station to obtain data of a power network and a traffic network;
step 3: taking the minimized system cost as an objective function, and taking traffic network constraint, electric power network constraint and hydrogen production and hydrogenation station main equipment operation constraint into consideration to construct a system planning model of a photovoltaic power station and a hydrogen production and hydrogenation station taking traffic flow prediction into consideration;
step 4: and solving the model by means of a CPLEX solver in a YALMIP toolbox according to the established photovoltaic power station and hydrogen production and hydrogenation station system planning model, and obtaining the optimal deployment of the positions and capacities of the photovoltaic power station and the hydrogen production and hydrogenation station through simulation verification.
Preferably, in step 1, the traffic flow data is from a database in a country or a region, and considering that there is a significant difference between the traffic flow on weekdays and on weekends, the traffic flow prediction is performed on the data on weekdays and on weekends by using a support vector machine, a K nearest neighbor and an artificial neural network, respectively.
Preferably, the decomposition step of step 3 is as follows:
step 3.1: the equal annual investment cost of the hydrogen production hydrogenation station and the photovoltaic power station is calculated;
Figure BDA0004008511070000021
wherein: s is S 1 For investment cost, xi 0 As the capital recovery coefficient of the HPRS,
Figure BDA0004008511070000022
wherein τ, T 0 Respectively controlling the discount rate and the HPRS operation planning period; c (C) n,ele 、C n,comp 、C n,tank Investment costs of the nth HPRS electrolytic tank, the compressor and the hydrogen storage tank are respectively set; c ele 、c comp 、c tank The cost of the unit rated power of the electrolytic tank, the compressor and the hydrogen storage tank is respectively; />
Figure BDA0004008511070000031
And->
Figure BDA0004008511070000032
Respectively nthRated power of HPRS electrolytic tank and compressor; m is M n,tank For the capacity of the selected hydrogen storage tank; zeta type toy 1 For capital recovery coefficient of photovoltaic power station, its value calculation method is identical to xi 0 ；c pv Investment cost for unit power of the photovoltaic power station; />
Figure BDA0004008511070000033
Rated power for the first photovoltaic power station;
step 3.2: calculating the operation cost of the hydrogen production and hydrogenation station within one year;
Figure BDA0004008511070000034
/>
wherein: s is S 2 For the operation cost, C n,el 、C n,w Respectively the nth HPRS power consumption and the water purification cost; c st Cost per kilogram of hydrogen stored in the hydrogen storage tank;
Figure BDA0004008511070000035
hydrogen demand for nth HPRS at time t d; p is p c The power consumption rate of the cooling system; />
Figure BDA0004008511070000036
Electricity price at time t of day d; />
Figure BDA0004008511070000037
The water purifying amounts consumed by the electrolytic tank and the compressor at the moment t are respectively; j (J) w Selling prices for local clean water; />
Figure BDA0004008511070000038
The electrolysis efficiency of the electrolytic tank and the compressor are respectively;
step 3.3: and constructing a system planning model of the photovoltaic power station and the hydrogen production and hydrogen adding station considering traffic flow prediction, wherein the system planning model comprises an objective function and related constraints for minimizing the system cost.
Preferably, the cost-minimized objective function is expressed as:
F＝min(S 1 +S 2 ) (3)
where F is the objective function value that minimizes the cost.
Preferably, the relevant constraints include power network constraints, traffic network constraints, power-traffic network constraints, photovoltaic plant constraints, and hydrogen production hydrogen plant constraints.
Preferably, the power network constraint is:
upper active power limit constraint:
P ij ≤P ijmax (4)
wherein: p (P) ij And P ijmax Respectively is line l ij Active power and active power upper limit of (2);
unit climbing rate constraint:
-P x ≤P x (t)-P x (t-1)≤P x (5)
wherein: p (P) x and-P x Respectively refers to the upper limit and the lower limit of the change of the active output unit time of the unit x; p (P) x (t) and P x (t-1) is the active power of the unit x at the time t and the time t-1;
node voltage constraint:
U t,imin ≤U t,i ≤U t,imax (6)
in U t,i The node voltage deviation of the node i at the time t is obtained; u (U) t,min The node voltage deviation minimum value of the node i at the time t is obtained; u (U) t,max The maximum value of the node voltage deviation of the node i at the time t.
Preferably, the traffic network constraint is:
FCV hydrogenation number and total demand constraint:
N n,FCV ≤N n,H (7)
Figure BDA0004008511070000041
wherein:N m,FCV ，N m,H the number of hydrogen filling and the number of hydrogen filling permission of the automobile in the mth HPRS; m is M e,HCV The e-th hydrogen fuel cell car capacity;
HPRS number constraint:
n u,H ＝1 (9)
wherein: n is n u,H In the planning process, each road network node can only build one HPRS for the number of HPRSs at the road network node u.
Preferably, the electric power-traffic network constraint is:
Figure BDA0004008511070000042
wherein:
Figure BDA0004008511070000043
active power consumed by HPRS at node u in the traffic network at d-th day t; />
Figure BDA0004008511070000044
Active power consumed by HPRS at node i in the power network at d-th day t; />
Figure BDA0004008511070000045
Active power and reactive power of the load at the node i at the time t of the d day are respectively; />
Figure BDA0004008511070000046
The actual output of the photovoltaic power station at the node i at the time of the d day t is obtained; />
Figure BDA0004008511070000051
Active and reactive power of the initial load of the i node in the power network are respectively.
Preferably, the photovoltaic power station is constrained as follows:
Figure BDA0004008511070000052
wherein:
Figure BDA0004008511070000053
the power is predicted for the photovoltaic power station at the node i at the d-th day t moment; />
Figure BDA0004008511070000054
Predicting the per unit value of the output of the photovoltaic power station at the d-th day t time of the area; />
Figure BDA0004008511070000055
And->
Figure BDA0004008511070000056
The lower limit and the upper limit of the installed capacity of the photovoltaic power station at the node are respectively set; />
Figure BDA0004008511070000057
And the sum of the installed capacities of the photovoltaic power stations in the whole power distribution network is obtained.
10. The photovoltaic power plant and hydrogen generation system planning method considering traffic flow prediction as claimed in claim 5, wherein: the hydrogen production and hydrogen adding station constraint is as follows:
Figure BDA0004008511070000058
wherein: h h Is the heating value of hydrogen;
Figure BDA0004008511070000059
hydrogen production rate of the electrolyzer at time t on day d for the nth HPRS; η (eta) ele Energy efficiency for the electrolyzer; Γ -shaped structure n,ele Maximum hydrogen production capacity per hour for the nth HPRS; Γ -shaped structure n,ele And->
Figure BDA00040085110700000510
The lower limit and the upper limit of the maximum hydrogen production capacity of the nth HPRS in unit hour are respectively set;
Figure BDA00040085110700000511
wherein:
Figure BDA00040085110700000512
the hydrogen amount flowing into the compressor at the time t of d days is the nth HPRS; />
Figure BDA00040085110700000513
Power consumption at a reference pressure for the compressor; f (F) ini Is the standard atmospheric pressure; gamma ray comp Hydrogen dissipation ratio for electrolyzer to compressor; />
Figure BDA00040085110700000514
Figure BDA00040085110700000515
Figure BDA0004008511070000061
Wherein:
Figure BDA0004008511070000062
and->
Figure BDA0004008511070000063
The hydrogen capacity of the hydrogen storage tank at the time t of d days and the time t+1 of the nth HPRS; />
Figure BDA0004008511070000064
The amount of hydrogen flowing into the hydrogen storage tank at time t of d days for the nth HPRS; />
Figure BDA0004008511070000065
And->
Figure BDA0004008511070000066
The hydrogen storage amounts of the hydrogen storage tanks of the nth HPRS at the time 1 and the time 24 are respectively shown; alpha is expressed as the ratio of the hydrogen storage quantity of the hydrogen storage tank of the nth HPRS at the moment 1 or 24 to the rated hydrogen storage capacity value corresponding to the hydrogen storage quantity; m is M n,tank And->
Figure BDA0004008511070000067
The lower limit and the upper limit of the rated hydrogen storage capacity of the hydrogen storage tank of the nth HPRS are respectively; gamma ray tank The hydrogen dissipation ratio from the compressor to the hydrogen storage tank.
The following beneficial effects can be achieved in this patent:
1. the invention considers traffic flow and simultaneously considers traffic network constraint, electric power network constraint and hydrogen production station system equipment model constraint; combining HPRS, a photovoltaic power station and power grid planning by the model, and coordinating and optimizing the capacity, the quantity and the positions of all the devices in the system; the obtained optimization result is more fit with reality, and the combination of the optimization result and the photovoltaic power station can effectively reduce the system cost, the hydrogen production patch can increase the construction quantity of the hydrogen production and hydrogenation stations, an effective calculation tool is provided for planning analysis of the hydrogen production and hydrogenation stations under the background of rapid development of hydrogen energy, and the optimization method has a certain reference value.
2. Firstly, predicting traffic flow on a certain section of path by comparing and selecting a proper method; secondly, taking traffic network constraint, electric power network constraint and HPRS system equipment model constraint into consideration, and establishing a system planning model of the hydrogen production and hydrogen station combined photovoltaic power station taking traffic flow prediction into consideration; and finally, solving by calling a CPLEX solver in the YALMIP toolbox to obtain an optimal deployment scheme of the positions and the capacities of the photovoltaic power station and the hydrogen production and hydrogenation station.
Drawings
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
FIG. 1 is a schematic diagram of the main equipment of the hydrogen production and hydrogenation station by on-site water electrolysis;
FIG. 2 is a graph of predicted weekday and weekend traffic flow data according to the present invention;
FIG. 3 is a schematic diagram of an electric power-traffic network coupling framework of the present invention;
FIG. 4 is a graph of typical predicted force per unit values for a photovoltaic cell 24h of the present invention;
FIG. 5 shows the hydrogen demand of the hydrogen production and hydrogenation station, the total hydrogen production of the electrolytic tank, the total hydrogen storage of the hydrogen storage tank and the time-of-use electricity price of the region.
Detailed Description
Example 1:
the optimal scheme is as shown in fig. 1 to 5, and the planning method of the photovoltaic power station and hydrogen production and hydrogen adding station system taking traffic flow prediction into consideration comprises the following steps:
step 1: introducing a traffic flow prediction method, and obtaining a hydrogenation demand of a hydrogenation station according to traffic flow data and expected vehicle hydrogenation probability, so as to ensure that a hydrogen fuel cell automobile is timely hydrogenated;
step 2: determining parameters of main equipment of a photovoltaic power station and a hydrogen production and hydrogenation station to obtain data of an electric power network and a traffic network;
step 3: taking the minimized system cost as an objective function, and taking traffic network constraint, electric power network constraint and hydrogen production and hydrogenation station main equipment operation constraint into consideration to construct a system planning model of a photovoltaic power station and a hydrogen production and hydrogenation station taking traffic flow prediction into consideration;
step 4: and solving the model by means of a CPLEX solver in a YALMIP toolbox according to the established photovoltaic power station and hydrogen production and hydrogenation station system planning model, and obtaining the optimal deployment of the positions and capacities of the photovoltaic power station and the hydrogen production and hydrogenation station through simulation verification.
In this example, the hydrogen production hydrogen adding station and the photovoltaic power station are addressed and fixed in volume as shown in fig. 3, and the hydrogen production hydrogen adding station is scheduled as shown in fig. 5. It should be noted that the planner can obtain the planning scheme by only calling the CPLEX solver in the yalminip tool box to solve the established model.
In this embodiment, the step 1 specifically includes the following steps:
step 1.1: traffic flow data used in the present invention comes from the Ireland national highway administration (Ireland National Road Authority). The data comprises M1 traffic flow data between southern connecting sections of Brinell, ireland, for 5 months;
step 1.2: considering that the traffic flow of the weekdays and the weekends have significant difference, respectively using a support vector machine (Support Vector Machine, SVM), K nearest neighbor (K Nearest Neighbor, KNN) and an artificial neural network (Artificial Neural Network, ANN) to predict the traffic flow of the data of the weekdays and the weekends;
step 1.3: evaluation index analysis of three prediction methods
TABLE 1 predictive evaluation of traffic flow
Figure BDA0004008511070000071
Figure BDA0004008511070000081
In this embodiment, the step 3 specifically includes the following steps:
step 3.1: the equal annual investment cost of the hydrogen production hydrogenation station and the photovoltaic power station is calculated;
Figure BDA0004008511070000082
wherein: s is S 1 For investment cost, xi 0 As the capital recovery coefficient of the HPRS,
Figure BDA0004008511070000083
wherein τ, T 0 Respectively controlling the discount rate and the HPRS operation planning period; c (C) n,ele 、C n,comp 、C n,tank Investment costs of the nth HPRS electrolytic tank, the compressor and the hydrogen storage tank are respectively set; c ele 、c comp 、c tank The unit rated power cost of the electrolytic tank, the compressor and the hydrogen storage tank; />
Figure BDA0004008511070000084
And->
Figure BDA0004008511070000085
Rated power of the nth HPRS electrolytic tank and the rated power of the compressor respectively; m is M n,tank For the capacity of the selected hydrogen storage tank; zeta type toy 1 For capital recovery coefficient of photovoltaic power station, its value calculation method is identical to xi 0 ；c pv Investment cost for unit power of the photovoltaic power station; />
Figure BDA0004008511070000086
Rated power for the first photovoltaic power station;
step 3.2: calculating the operation cost of the hydrogen production and hydrogenation station within one year;
Figure BDA0004008511070000087
wherein: s is S 2 For the operation cost, C n,el 、C n,w Respectively the nth HPRS power consumption and the water purification cost; c st Cost per kilogram of hydrogen stored in the hydrogen storage tank;
Figure BDA0004008511070000088
hydrogen demand for nth HPRS at time t d; p is p c The power consumption rate of the cooling system; />
Figure BDA0004008511070000089
Electricity price at time t of day d; />
Figure BDA00040085110700000810
The water purifying amounts consumed by the electrolytic tank and the compressor at the moment t are respectively; j (J) w Selling prices for local clean water; />
Figure BDA00040085110700000811
The electrolysis efficiency of the electrolytic tank and the compressor are respectively;
step 3.3: and constructing a system planning model of the photovoltaic power station and the hydrogen production and hydrogen adding station considering traffic flow prediction, wherein the system planning model comprises an objective function and related constraints for minimizing the system cost.
In this embodiment, the cost-minimized objective function is expressed as:
F＝min(S 1 +S 2 ) (3)
where F is an objective function value that minimizes cost;
in this embodiment, the relevant constraints include power network constraints, traffic network constraints, power-traffic network constraints, photovoltaic plant constraints, hydrogen production hydrogen station constraints;
in this embodiment, the power network constraint is:
upper active power limit constraint:
P ij ≤P ijmax (4)
wherein: p (P) ij And P ijmax Respectively is line l ij Active power and active power upper limit of (2);
unit climbing rate constraint:
-P x ≤P x (t)-P x (t-1)≤P x (5)
wherein: p (P) x and-P x Respectively refers to the upper limit and the lower limit of the change of the active output unit time of the unit x; p (P) x (t) and P x (t-1) is the active power of the unit x at the time t and the time t-1;
node voltage constraint:
U t,imin ≤U t,i ≤U t,imax (6)
in U t,i The node voltage deviation of the node i at the time t is obtained; u (U) t,imin The node voltage deviation minimum value of the node i at the time t is obtained; u (U) t,imax The node voltage deviation maximum value of the node i at the time t is obtained;
in this embodiment, the traffic network constraint is:
FCV hydrogenation number and total demand constraint:
N n,FCV ≤N n,H (7)
Figure BDA0004008511070000091
wherein: n (N) m,FCV ，N m,H The number of hydrogen filling and the number of hydrogen filling permission of the automobile in the mth HPRS; m is M e,HCV The e-th hydrogen fuel cell car capacity;
HPRS number constraint:
n u,H ＝1 (9)
wherein: n is n u,H In the planning process, each road network node can only build one HPRS for the number of HPRSs at the road network node u;
in this embodiment, the electric power-traffic network constraint is:
Figure BDA0004008511070000101
wherein:
Figure BDA0004008511070000102
active power consumed by HPRS at node u in the traffic network at d-th day t; />
Figure BDA0004008511070000103
Active power consumed by HPRS at node i in the power network at d-th day t; />
Figure BDA0004008511070000104
Active power and reactive power of the load at the node i at the time t of the d day are respectively; />
Figure BDA0004008511070000105
The actual output of the photovoltaic power station at the node i at the time of the d day t is obtained; />
Figure BDA0004008511070000106
Active power and reactive power of the initial load of the i node in the power network are respectively;
in this embodiment, the photovoltaic power station constraint is:
Figure BDA0004008511070000107
wherein:
Figure BDA0004008511070000108
the power is predicted for the photovoltaic power station at the node i at the d-th day t moment; />
Figure BDA0004008511070000109
Predicting the per unit value of the output of the photovoltaic power station at the d-th day t time of the area; />
Figure BDA00040085110700001010
And->
Figure BDA00040085110700001011
The lower limit and the upper limit of the installed capacity of the photovoltaic power station at the node are respectively set; />
Figure BDA00040085110700001012
The sum of the installed capacities of the photovoltaic power stations in the whole power distribution network is calculated;
in this embodiment, the hydrogen production hydrogen station constraints are:
Figure BDA00040085110700001013
wherein: h h Is the heating value of hydrogen;
Figure BDA00040085110700001014
hydrogen production rate of the electrolyzer at time t on day d for the nth HPRS; η (eta) ele Energy efficiency for the electrolyzer; Γ -shaped structure n,ele Maximum hydrogen production capacity per hour for the nth HPRS; Γ -shaped structure n,ele And->
Figure BDA0004008511070000111
The lower limit and the upper limit of the maximum hydrogen production capacity of the nth HPRS in unit hour are respectively set; />
Figure BDA0004008511070000112
Wherein:
Figure BDA0004008511070000113
the hydrogen amount flowing into the compressor at the time t of d days is the nth HPRS; />
Figure BDA0004008511070000114
Power consumption at a reference pressure for the compressor; f (F) ini Is the standard atmospheric pressure; gamma ray comp Hydrogen dissipation ratio for electrolyzer to compressor;
Figure BDA0004008511070000115
Figure BDA0004008511070000116
Figure BDA0004008511070000117
wherein:
Figure BDA0004008511070000118
and->
Figure BDA0004008511070000119
The hydrogen capacity of the hydrogen storage tank at the time t of d days and the time t+1 of the nth HPRS;
Figure BDA00040085110700001110
the amount of hydrogen flowing into the hydrogen storage tank at time t of d days for the nth HPRS; />
Figure BDA00040085110700001111
And->
Figure BDA00040085110700001112
The hydrogen storage amounts of the hydrogen storage tanks of the nth HPRS at the time 1 and the time 24 are respectively shown; alpha is expressed as the ratio of the hydrogen storage quantity of the hydrogen storage tank of the nth HPRS at the moment 1 or 24 to the rated hydrogen storage capacity value corresponding to the hydrogen storage quantity; m is M n,tank And->
Figure BDA00040085110700001113
The lower limit and the upper limit of the rated hydrogen storage capacity of the hydrogen storage tank of the nth HPRS are respectively; gamma ray tank The hydrogen dissipation ratio from the compressor to the hydrogen storage tank.
The coupling system of the IEEE30 standard node power grid and the 30 node road network in the embodiment of the invention is shown in fig. 3, wherein the unit distance is 1KM, and the node connected by a dotted line in the figure is the coupling position of the electric power-traffic network. The specific parameters of the hydrogen production and hydrogenation station equipment are shown in table 2. In this example, the photovoltaic power station may be directly connected to the corresponding power distribution network node. The specific parameters of the photovoltaic power station are shown in an annex A table A2. In addition, the photovoltaic typical predicted force per unit value of the photovoltaic power station 24h
Figure BDA00040085110700001114
See fig. 4. In order to promote the development of hydrogen energy automobiles and the popularization of hydrogen energy automobiles, various national governments have given great efforts to subsidize the infrastructure of hydrogen production and hydrogen stations, and the specific contents (for example, japan) are shown in table 4. To alleviate peak-to-valley differences in the load curves, the region implements a time-of-use electricity price mechanism, and the electricity price of 24 hours in a day is shown in Table 5.
The optimization results of this example are shown in Table 6. The total hydrogen demand in this area was 13110kg per day as determined by traffic flow predictions, and as can be seen from table 6, 8 HPRS's were needed to power hydrogen fuel cell cars in a 30 node traffic network. Fig. 3 shows the deployment of HPRS in a traffic network. The 2 numbers in brackets indicate the hydrogen production capacity of each HPRS electrolyzer and the hydrogen storage capacity of the hydrogen storage tank. The equipment specifications of each HPRS are different and are distributed and deployed in the whole traffic network.
Fig. 5 shows the total hydrogen demand of HPRS, the total hydrogen production of the electrolyzer, the total hydrogen storage of the hydrogen storage tank, and the electricity price change 24 hours per day. As can be seen from the hydrogen demand distribution of fig. 5, the hydrogen demand of HPRS is small in the early morning and at night, mainly focusing on 08:00-21:00, and at 10:00 and 19:00 reaches the highest peak. Meanwhile, the HPRS hydrogen production amount can rapidly respond to the change of the peak-valley time-of-use electricity price, and when the electricity price is 01:00-8: when 00 reaches the minimum, the electrolyzer prepares hydrogen with rated power, and when the electricity price is 09:00-12: when 00 reaches the maximum, the hydrogen production amount of the electrolytic tank is reduced. Since 08: the hydrogen production amount of HPRS before 00 is more, so the hydrogen storage amount of the hydrogen storage tank is 08:00, then the hydrogen storage capacity of the hydrogen storage tank drops sharply due to the increase in hydrogen demand and the decrease in hydrogen production, 22:00 is minimized. However, as the electricity price decreases, the electrolyzer returns to producing hydrogen with rated hydrogen production capacity and the hydrogen demand is less at night, so the hydrogen storage capacity increases rapidly to the initial value.
The site location of each photovoltaic power plant is shown in the distribution network of fig. 3. Wherein the installed capacity of each photovoltaic power plant is shown in red font in fig. 3. It can be seen from the figure that there are a large number of photovoltaic power stations at the end of the distribution network line, since the photovoltaic power stations can increase their voltage level when the distribution network line is terminated, in order to avoid that the termination voltage level is below the prescribed limit.
TABLE 2 investment and operating parameters for Hydrogen production and hydrogenation plant facilities
Figure BDA0004008511070000121
Table 3 photovoltaic power plant parameters
Figure BDA0004008511070000122
Figure BDA0004008511070000131
TABLE 4 hydrogenation apparatus patch details
Figure BDA0004008511070000132
Table 5 peak-valley time-of-use electricity prices of the grid
Figure BDA0004008511070000133
TABLE 6 optimization results for this example
Figure BDA0004008511070000134
The above embodiments are only preferred embodiments of the present invention, and should not be construed as limiting the present invention, and the scope of the present invention should be defined by the claims, including the equivalents of the technical features in the claims. I.e., equivalent replacement modifications within the scope of this invention are also within the scope of the invention.

Claims (10)

1. A photovoltaic power station and hydrogen production and hydrogen adding station system planning method considering traffic flow prediction is characterized by comprising the following steps:
step 1: introducing a traffic flow prediction method, and obtaining a hydrogen adding station hydrogen adding demand according to traffic flow data and expected vehicle hydrogen adding probability, so as to ensure that the hydrogen fuel cell automobile is timely hydrogenated;
step 2: determining specific parameters of main equipment of a photovoltaic power station and a hydrogen production and hydrogenation station to obtain data of a power network and a traffic network;
step 3: taking the minimized system cost as an objective function, and taking traffic network constraint, electric power network constraint and hydrogen production and hydrogenation station main equipment operation constraint into consideration to construct a system planning model of a photovoltaic power station and a hydrogen production and hydrogenation station taking traffic flow prediction into consideration;
step 4: and solving the model by means of a CPLEX solver in a YALMIP toolbox according to the established photovoltaic power station and hydrogen production and hydrogenation station system planning model, and obtaining the optimal deployment of the positions and capacities of the photovoltaic power station and the hydrogen production and hydrogenation station through simulation verification.
2. The photovoltaic power plant and hydrogen generation system planning method taking into account traffic flow prediction as claimed in claim 1, wherein: in step 1, traffic flow data come from a database of a country or a region, and considering that the traffic flow of the weekdays and the weekends have significant differences, the traffic flow prediction is carried out on the data of the weekdays and the weekends by using a support vector machine, a K nearest neighbor and an artificial neural network respectively.
3. The photovoltaic power plant and hydrogen generation system planning method taking into account traffic flow prediction as claimed in claim 1, wherein: the decomposition step of step 3 is as follows:
step 3.1: the equal annual investment cost of the hydrogen production hydrogenation station and the photovoltaic power station is calculated;
Figure FDA0004008511060000011
wherein: s is S 1 For investment cost, xi 0 As the capital recovery coefficient of the HPRS,
Figure FDA0004008511060000012
wherein τ, T 0 Respectively controlling the discount rate and the HPRS operation planning period; c (C) n,ele 、C n,comp 、C n,tank Investment costs of the nth HPRS electrolytic tank, the compressor and the hydrogen storage tank are respectively set; c ele 、c comp 、c tank The cost of the unit rated power of the electrolytic tank, the compressor and the hydrogen storage tank is respectively; />
Figure FDA0004008511060000021
And->
Figure FDA0004008511060000022
Rated power of the nth HPRS electrolytic tank and the rated power of the compressor respectively; m is M n,tank For the capacity of the selected hydrogen storage tank; zeta type toy 1 Capital recovery for photovoltaic power plantsCoefficient, its value calculation method is same as xi 0 ；c pv Investment cost for unit power of the photovoltaic power station; />
Figure FDA0004008511060000023
Rated power for the first photovoltaic power station;
step 3.2: calculating the operation cost of the hydrogen production and hydrogenation station within one year;
Figure FDA0004008511060000024
wherein: s is S 2 For the operation cost, C n,el 、C n,w Respectively the nth HPRS power consumption and the water purification cost; c st Cost per kilogram of hydrogen stored in the hydrogen storage tank;
Figure FDA0004008511060000025
hydrogen demand for nth HPRS at time t d; p is p c The power consumption rate of the cooling system; />
Figure FDA0004008511060000026
Electricity price at time t of day d; />
Figure FDA0004008511060000027
The water purifying amounts consumed by the electrolytic tank and the compressor at the moment t are respectively; j (J) w Selling prices for local clean water; />
Figure FDA0004008511060000028
The electrolysis efficiency of the electrolytic tank and the compressor are respectively;
step 3.3: and constructing a system planning model of the photovoltaic power station and the hydrogen production and hydrogen adding station considering traffic flow prediction, wherein the system planning model comprises an objective function and related constraints for minimizing the system cost.
4. A photovoltaic power plant and hydrogen generation system planning method taking into account traffic flow prediction as defined in claim 3, wherein: the cost-minimized objective function is expressed as:
F＝min(S 1 +S 2 ) (3)
where F is the objective function value that minimizes the cost.
5. A photovoltaic power plant and hydrogen generation system planning method taking into account traffic flow prediction as defined in claim 3, wherein: the related constraints include power network constraints, traffic network constraints, power-traffic network constraints, photovoltaic power plant constraints, and hydrogen production hydrogen generation hydrogen station constraints.
6. The photovoltaic power plant and hydrogen generation system planning method considering traffic flow prediction as claimed in claim 5, wherein: the power network constraint is as follows:
upper active power limit constraint:
P ij ≤P ijmax (4)
wherein: p (P) ij And P ijmax Respectively is line l ij Active power and active power upper limit of (2);
unit climbing rate constraint:
-P x ≤P x (t)-P x (t-1)≤P x (5)
wherein: p (P) x and-P x Respectively refers to the upper limit and the lower limit of the change of the active output unit time of the unit x; p (P) x (t) and P x (t-1) is the active power of the unit x at the time t and the time t-1;
node voltage constraint:
U t,imin ≤U t,i ≤U t,imax (6)
in U t,i The node voltage deviation of the node i at the time t is obtained; u (U) t,min The node voltage deviation minimum value of the node i at the time t is obtained; u (U) t,max The maximum value of the node voltage deviation of the node i at the time t.
7. The photovoltaic power plant and hydrogen generation system planning method considering traffic flow prediction as claimed in claim 5, wherein: the traffic network constraint is as follows:
FCV hydrogenation number and total demand constraint:
N n,FCV ≤N n,H (7)
Figure FDA0004008511060000031
wherein: n (N) m,FCV ，N m,H The number of hydrogen filling and the number of hydrogen filling permission of the automobile in the mth HPRS; m is M e,HCV The e-th hydrogen fuel cell car capacity;
HPRS number constraint:
n u,H ＝1 (9)
wherein: n is n u,H In the planning process, each road network node can only build one HPRS for the number of HPRSs at the road network node u.
8. The photovoltaic power plant and hydrogen generation system planning method considering traffic flow prediction as claimed in claim 5, wherein: the electric power-traffic network constraint is as follows:
Figure FDA0004008511060000032
wherein:
Figure FDA0004008511060000033
active power consumed by HPRS at node u in the traffic network at d-th day t; />
Figure FDA0004008511060000034
Active power consumed by HPRS at node i in the power network at d-th day t; p (P) i t,d 、/>
Figure FDA0004008511060000041
Active power and reactive power of the load at the node i at the time t of the d day are respectively; />
Figure FDA0004008511060000042
The actual output of the photovoltaic power station at the node i at the time of the d day t is obtained; />
Figure FDA0004008511060000043
Active and reactive power of the initial load of the i node in the power network are respectively.
9. The photovoltaic power plant and hydrogen generation system planning method considering traffic flow prediction as claimed in claim 5, wherein: the photovoltaic power station is constrained as follows:
Figure FDA0004008511060000044
wherein:
Figure FDA0004008511060000045
the power is predicted for the photovoltaic power station at the node i at the d-th day t moment; />
Figure FDA0004008511060000046
Predicting the per unit value of the output of the photovoltaic power station at the d-th day t time of the area; />
Figure FDA0004008511060000047
And->
Figure FDA0004008511060000048
The lower limit and the upper limit of the installed capacity of the photovoltaic power station at the node are respectively set;
Figure FDA0004008511060000049
installation capacity for photovoltaic power station in whole distribution networkSum up.
10. The photovoltaic power plant and hydrogen generation system planning method considering traffic flow prediction as claimed in claim 5, wherein: the hydrogen production and hydrogen adding station constraint is as follows:
Figure FDA00040085110600000410
wherein: h h Is the heating value of hydrogen;
Figure FDA00040085110600000411
hydrogen production rate of the electrolyzer at time t on day d for the nth HPRS; η (eta) ele Energy efficiency for the electrolyzer; Γ -shaped structure n,ele Maximum hydrogen production capacity per hour for the nth HPRS; Γ -shaped structure n,ele And->
Figure FDA00040085110600000412
The lower limit and the upper limit of the maximum hydrogen production capacity of the nth HPRS in unit hour are respectively set;
Figure FDA00040085110600000413
wherein:
Figure FDA00040085110600000414
the hydrogen amount flowing into the compressor at the time t of d days is the nth HPRS; />
Figure FDA00040085110600000415
Power consumption at a reference pressure for the compressor; f (F) ini Is the standard atmospheric pressure; gamma ray comp Hydrogen dissipation ratio for electrolyzer to compressor;
Figure FDA0004008511060000051
Figure FDA0004008511060000052
Figure FDA0004008511060000053
wherein:
Figure FDA0004008511060000054
and->
Figure FDA0004008511060000055
The hydrogen capacity of the hydrogen storage tank at the time t of d days and the time t+1 of the nth HPRS; />
Figure FDA0004008511060000056
The amount of hydrogen flowing into the hydrogen storage tank at time t of d days for the nth HPRS; />
Figure FDA0004008511060000057
And->
Figure FDA0004008511060000058
The hydrogen storage amounts of the hydrogen storage tanks of the nth HPRS at the time 1 and the time 24 are respectively shown; alpha is expressed as the ratio of the hydrogen storage quantity of the hydrogen storage tank of the nth HPRS at the moment 1 or 24 to the rated hydrogen storage capacity value corresponding to the hydrogen storage quantity; m is M n,tank And->
Figure FDA0004008511060000059
The lower limit and the upper limit of the rated hydrogen storage capacity of the hydrogen storage tank of the nth HPRS are respectively; gamma ray tank The hydrogen dissipation ratio from the compressor to the hydrogen storage tank. />
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CN116611673A (en) * 2023-07-20 2023-08-18 国网湖北省电力有限公司经济技术研究院 Electric traffic coupling network-oriented optical storage charging station planning method and system
CN116611673B (en) * 2023-07-20 2023-10-03 国网湖北省电力有限公司经济技术研究院 Electric traffic coupling network-oriented optical storage charging station planning method and system

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