CN115374999A - Hydropower hydrogen production optimal configuration method suitable for starting and stopping characteristics of hydrogen production equipment - Google Patents
Hydropower hydrogen production optimal configuration method suitable for starting and stopping characteristics of hydrogen production equipment Download PDFInfo
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 50
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- 239000000446 fuel Substances 0.000 claims description 27
- 230000005611 electricity Effects 0.000 claims description 20
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- 230000003993 interaction Effects 0.000 claims description 8
- 239000007789 gas Substances 0.000 claims description 7
- 238000005312 nonlinear dynamic Methods 0.000 claims description 6
- 238000006356 dehydrogenation reaction Methods 0.000 claims description 5
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Abstract
The invention provides a hydropower hydrogen production optimal configuration method suitable for the starting and stopping characteristics of hydrogen production equipment, which comprises the following steps: s1, collecting and analyzing the total amount of available new energy resources of a microgrid building local area, and determining installation parameters of new energy equipment; s2, acquiring local power load data, hot water demand data and hydrogen demand conditions of a construction site, and determining installation conditions and equipment capacity upper limit; s3, determining a topological structure of the microgrid, energy flow relationships in various energy main body forms and an overall energy supply and operation mode of the microgrid; s4, establishing a double-layer configuration-operation optimization model which is in accordance with the micro-grid comprehensive constraint set and an objective function by taking the minimum comprehensive cost of the whole life cycle of the micro-grid and the wind-solar energy consumption rate and the energy efficiency factor as objective functions; and S5, solving the optimization model to obtain an optimization configuration scheme of the microgrid. The invention realizes the coupling by utilizing various energy forms and improves the consumption rate of renewable energy sources and the energy efficiency of a system.
Description
Technical Field
The invention relates to the technical field of planned optimal configuration of a microgrid, in particular to a hydropower hydrogen production optimal configuration method suitable for starting and stopping characteristics of hydrogen production equipment. A
Background
In recent years, with the gradual exhaustion of fossil energy and the increasing of climate problems, the rapid development of clean renewable energy sources to reduce carbon dioxide emission becomes an important development trend. However, the higher dependence of renewable energy sources such as photovoltaic and wind turbine on the environment leads to stronger uncertainty on the power generation side, and brings greater challenges to the stable operation and scheduling of the power grid. As a novel networking form, the micro-grid can be compatible with various new energy sources to be jointly accessed, has strong regional networking capability, is beneficial to on-site consumption and management of the new energy sources, and is widely concerned and developed. The optimal configuration and energy type selection of the microgrid are important problems in the construction and operation of the microgrid, wherein the configuration of energy storage is crucial, and the selection of the proper energy storage type and energy storage capacity can effectively improve the economical efficiency and reliability of the operation of the microgrid. At present, battery energy storage is widely used as a mature energy storage mode, however, the storage battery is more limited by operation constraint and capacity, large-scale storage battery configuration is needed for meeting the reliable operation of a micro-grid, and the safe and economic operation of the micro-grid is not facilitated. With the development of hydrogen preparation and fuel cell technology, hydrogen energy storage is rapidly developed as a novel energy storage, and the characteristic of zero carbon emission and no pollution meets the environmental-friendly and clean requirements of micro-grids nowadays. The hydrogen energy storage is not easy to be limited by the upper limit of the capacity because the gas has the characteristics of storage and transportation, and meanwhile, the hydrogen storage technology is greatly developed, and the high-pressure hydrogen storage technology can ensure the saving storage of the hydrogen safe space. However, in the current optimized configuration of the hydrogen-containing microgrid, the problem of low efficiency of hydrogen equipment is often ignored, so that a large amount of energy is wasted, and the operating cost of the microgrid is increased in a phase-changing manner. Meanwhile, the problem of short service life and high cost of the hydrogen equipment makes it difficult to configure the hydrogen equipment on a large scale, i.e. a larger scale power equipment can not be configured like a storage battery and the like. The proportion of hydrogen storage and electricity storage of the microgrid is reasonably distributed, and the reliability and the economy of the microgrid can be effectively improved by utilizing the respective capacity advantages and power response advantages of the microgrid.
The invention discloses a micro-grid scheduling method which is disclosed in Chinese patent literature and has the publication number CN105896610B, and discloses a micro-grid energy storage scheduling method, wherein a micro-grid energy management system acquires the load in a micro-grid and the power and capacity conditions of each power supply in real time, transmits the load and the power and capacity conditions to a main network management system, and receives the information and the instruction of the main network management system; if the internal output power of one of the micro-grids is not enough to bear the load of the micro-grid, the main network management system calculates the regulation parameter factor lambda of each of the other micro-grids according to the monitoring parameters of the other micro-grids, if the regulation parameter factor lambda of each of the other micro-grids is not larger than 1, the main network management system selects a plurality of micro-grids from the micro-grids and supplies power to the micro-grids with insufficient internal output power, and the sum of the regulation parameter factors lambda of the plurality of micro-grids is larger than 1. However, the invention is not coupled by various energy forms, and the renewable energy consumption rate and the system energy efficiency cannot be improved by combining the technologies of electric energy storage, hydrogen equipment cooperative scheduling and the like.
Disclosure of Invention
The invention provides a hydropower hydrogen production optimal configuration method suitable for the starting and stopping characteristics of hydrogen production equipment, aims to overcome the defects that coupling of multiple energy forms cannot be realized, and renewable energy consumption rate and system energy efficiency cannot be improved by combining technologies such as electric energy storage and hydrogen equipment cooperative scheduling.
In order to achieve the purpose, the invention adopts the following technical scheme:
a hydropower hydrogen production optimal configuration method suitable for the starting and stopping characteristics of hydrogen production equipment comprises the following steps:
s1, collecting and analyzing the total amount of available new energy resources of a microgrid building local area, and determining installation parameters of new energy equipment;
s2, acquiring local power load data, hot water demand data and hydrogen demand conditions of a construction site, and determining installation conditions and an upper limit of equipment capacity;
s3, determining a topological structure of the microgrid, energy flow relationships in various energy main body forms and an overall energy supply and operation mode of the microgrid;
s4, establishing a double-layer configuration-operation optimization model which is in accordance with the micro-grid comprehensive constraint set and an objective function by taking the minimum comprehensive cost of the whole life cycle of the micro-grid and the wind-solar energy consumption rate and the energy efficiency factor as objective functions;
and S5, solving the optimization model to obtain an optimization configuration scheme of the microgrid.
According to the method, the total quantity and the energy relation of the new energy resource structure of the micro-grid location are obtained, the equipment installation condition and the upper and lower limits are determined, the information is collected, the energy flow relation of the topological structure of the micro-grid and various energy main body forms is completed, the overall energy supply and operation mode of the micro-grid is further determined, the optimization configuration scheme of the micro-grid is obtained by constructing a function solution optimization model, and therefore multiple energy forms, high renewable energy consumption rate and system energy efficiency can be coupled.
Preferably, the step S1 further comprises:
s11, collecting main climate observation data of wind, light and water resources;
and S12, adjusting the installation parameters of the photovoltaic equipment, the fan and the radial flow type hydropower station according to the data of the S11.
The invention adjusts the installation parameters of the corresponding power generation equipment by collecting the observation data of various energy forms, and is beneficial to effectively utilizing the energy of various forms according to the location of the micro-grid.
Preferably, the step S2 further includes:
s21 collects power load data and hydrogen demand data: load characteristic data of governments, industries and residents on electricity utilization conditions, holidays, double-holidays and workdays, and hydrogen demand data of hydrogen fuel cell automobiles in construction areas, gas consumption parameters, hydrogen industries and hydrogen marketers;
s22, determining the maximum installation capacity and the number of various devices according to the arrangement area of the new energy devices in the construction area, the government-related place standard and the hydrogen safety distance.
The method collects the power load data and the hydrogen demand data, arranges the area of the new energy equipment according to the obtained data, determines the maximum installation capacity and the number of various equipment, and is favorable for reasonably planning the storage and release of various energy forms of the microgrid.
Preferably, the step S3 further includes:
s31, comprehensively judging the profit and loss of the integral energy supply of the microgrid according to the profit and loss of the energy flows in various energy main body forms;
s32, if the whole energy supply of the microgrid is sufficient, executing the step: the distributed power supply utilizes new energy to generate electric energy to supply the electric energy to an electric load, and redundant electric energy is stored in an electric storage device or is used for hydrogen production by an electrolytic hydrogen production device and is stored in the electric storage device or sold to a main network;
s33, if the integral energy supply of the microgrid is insufficient, the step is executed: power is purchased from the main network or a demand side load response is made.
The method comprehensively judges the profit and loss of the integral energy supply of the micro-grid according to the profit and loss of the energy flow of various energy main bodies, utilizes equipment to store energy or sell the energy and the main grid when the energy of the micro-grid is surplus, and purchases electricity from the main grid or performs demand side load response or purchases hydrogen when the energy of the micro-grid is lost.
Preferably, the step of constructing the objective function in S4 includes:
the S41 objective function is expressed as follows:
minF＝(F ty1 +F sup +F rep )×CRF+F ty2 +βF p
wherein, F ty1 For the first investment cost of the equipment, F sup Investment cost for auxiliary equipment F rep For the cost of replacement of equipment in the full life cycle, F ty2 For the operating costs of the plant, F p Beta is a penalty coefficient, and CRF is a capital recovery coefficient;
the cost expressions in the objective function are as follows:
wherein: k is a radical of i Cost per unit power, P, of distributed power for dehydrogenation of fuel cells i For the corresponding installed capacity, i denotes the dehydrogenation fuel cell toThe distributed power supply of (1); g j Cost per unit capacity of the energy storage device, C j J represents the energy storage device type and number for its capacity; k is a radical of m Cost per unit power, P, for hydrogen-related equipment m-rate Rated capacity of hydrogen-related equipment, n is life cycle of microgrid, LC m M represents the type and the number of hydrogen-related equipment, including an electrolytic hydrogen production device and a hydrogen fuel cell, for the life span of the hydrogen-related equipment; alpha is alpha 1 α 2 The auxiliary cost coefficient refers to the proportion of the auxiliary cost to the purchase cost;
is the real-time electricity rate at the time t,
the power is interacted between the micro-grid and the main grid; m is a unit of gas In order to be the price of the hydrogen gas,
the trading volume of hydrogen at the moment t; p is a radical of d In order to meet the cost of the demand-side response,
for the demand side response power at time t,
representing the electrical load demand at time t,
and
respectively representing the photovoltaic output, the wind power output and the hydroelectric output at the moment t General assembly To optimize the time.
The invention establishes the objective function and each cost expression in the objective function, establishes the function of the operation cost and provides the operation parameters for the step S5.
Preferably, the step of S4 constructing the constraint includes:
s42 the power storage device operation constraints are:
wherein SOC represents the charge-discharge state of the power storage device, SOC min For the allowable lower limit of the SOC of the electric storage device, SOC max Is an allowable upper limit of the SOC of the electric storage device, SOC t Indicating the state of the SOC at time t,
the output power of the electric storage device at the time t. t is t 0 To optimize the starting moment, λ s Is the initial SOC state quantity, C bat Indicating the rated capacity, eta, of the electricity storage device bat The charge-discharge efficiency of the electric storage device; s43, the hydrogen production-hydrogen fuel cell equipment has the operation constraints that:
wherein, ES t Representing the state of capacity of the hydrogen storage unit at time t, m pro ,m con Electric conversion coefficient, C, of electrolytic hydrogen production apparatus and hydrogen fuel cell, respectively hyd Is the hydrogen storage capacity, lambda e Is the initial hydrogen storage device capacity state;
respectively representing the electrolytic hydrogen production power and the hydrogen fuel cell output at the moment t; k is a radical of formula g Is a hydrogen related unit parameter;
indicating the on-state of the hydrogen plant for the period of time; x represents the hydrogen waste amount in the starting and stopping process of the hydrogen production equipment;
s44, the main network power interaction and demand side response constraint is as follows:
wherein P is pmin ,P pmax For the upper and lower limits of the interaction power, P, of the microgrid and the main network drmax Responding to the upper limit of power for the demand side;
the power is interacted between the micro-grid and the main grid;
demand side response power for time t;
s45, the upper and lower limits of the power of the equipment are constrained as follows:
in the formula, P batmax The maximum output/charging power of the electricity storage device, alpha is the overload operation coefficient of the electrolytic hydrogen production device, and P el-rate 、P fc-rate The rated power of the hydrogen fuel cell and the electrolytic hydrogen production device are respectively, the lowest operating point which is not 0 exists when the electrolytic hydrogen production device and the hydrogen fuel cell are started, and the lowest operating point is zero when the electrolytic hydrogen production device and the hydrogen fuel cell are in a shutdown state.
The method establishes an electricity storage device operation constraint function, a hydrogen production-hydrogen fuel cell equipment operation constraint function, a main network power interaction and demand side response constraint function and an equipment power upper and lower limit constraint function, and the functions are used for calculating parameters of stable operation of the micro-grid system.
Preferably, the step S5 further includes:
s51, reading new energy, various load data and electricity price information data;
s52, randomly initializing the position and the speed of each particle of a population in the particle swarm optimization, wherein the population comprises an upper layer configuration capacity variable serving as an upper limit constraint value and a lower limit constraint value of a lower layer operation constraint;
s53, solving a mixed integer programming problem formed by lower-layer operation constraints by using a solver based on upper-layer configuration variable values represented by the particle swarm algorithm population to obtain the optimal operation cost or no-solution information under the values;
s54, calculating a total objective function value, evaluating the fitness of each particle, and storing the position and the fitness value of each particle;
s55, updating the speed and the displacement of the particles;
s56, updating the algorithm weight by utilizing a nonlinear dynamic inertia weight coefficient formula:
wherein, ω is max ,ω min Is the maximum and minimum of the weight of the particle, F is the current objective function value of the particle, F avg ,F min Respectively representing the average target value and the minimum target value of all current particles;
s57, updating the position and the adaptive value of the current optimal individual;
and S58, if the preset operation precision or iteration times is met, stopping searching, and outputting an optimal capacity configuration result, otherwise, returning to the step S53.
The method comprises the steps of assigning values to the positions and the speeds of particles in a population in a random initialization particle swarm algorithm by reading new energy, various load data and electricity price information data, calculating a total objective function value by using a cyclic algorithm, evaluating the fitness of each particle, storing the positions and the fitness values of the current particles, updating the algorithm weight by using the updated speed and displacement of the particles in a nonlinear dynamic inertia weight coefficient formula, and finding an optimal solution or finding the optimal solution after multiple cycles.
The invention has the beneficial effects that:
the available types and the total amount of new energy resources at the location of the micro-grid are collected and analyzed, the installation parameters of new energy equipment are determined, coupling of multiple energy forms is facilitated, the topological structure of the micro-grid, the energy flow relation of various energy main body forms and the overall energy supply and operation mode of the micro-grid are determined according to the requirements of power load data, hydrogen requirements, hot water requirements and the like, various factors are fitted into a target function and various upper and lower limit functions, an optimization model is calculated by a nonlinear dynamic inertia weight coefficient formula and a cyclic algorithm, and the consumption rate of renewable energy and the energy efficiency of a system are improved.
Drawings
FIG. 1 is a diagram of an electro-hydrogen coupled complementary microgrid structure and power flow relationships comprising photovoltaic devices, wind turbines;
FIG. 2 is a block diagram of an optimization solution algorithm;
fig. 3 is a flow chart of the present invention.
Detailed Description
The invention will be further explained by combining the practical case of the optimized configuration and the attached drawings. An optimal configuration method of hydroelectric hydrogen production suitable for the start-stop characteristic of hydrogen production equipment is shown in figure 3 and comprises the following steps:
s1, collecting and analyzing the total amount of available new energy resources of a microgrid building local area, and determining installation parameters of new energy equipment;
s11, collecting main climate observation data of wind, light and water resources;
s12, adjusting the installation parameters of the photovoltaic equipment, the fan and the radial flow type hydropower station according to the data of the S11;
s2, acquiring local power load data, hot water demand data and hydrogen demand conditions of a construction site, and determining installation conditions and an upper limit of equipment capacity;
s21 collects power load data and hydrogen demand data: load characteristic data of governments, industries and residents on electricity utilization conditions, holidays, double-holidays and workdays, and hydrogen demand data of hydrogen fuel cell automobiles in construction areas, gas consumption parameters, hydrogen industries and hydrogen marketers;
s22, determining the maximum installation capacity and the maximum number of various devices according to the arrangement area of new energy devices in a construction area, government-related land use standards and hydrogen safety distances;
according to fig. 1:
s3, determining a topological structure of the microgrid, energy flow relations of various energy main body forms and an overall energy supply and operation mode of the microgrid;
s31, comprehensively judging the profit and loss of the integral energy supply of the microgrid according to the profit and loss of the energy flows in various energy main forms;
s32, if the integral energy supply of the microgrid is sufficient, executing the step: the distributed power supply utilizes new energy to generate electric energy to supply the electric energy to an electric load, and redundant electric energy is stored in an electric storage device or is used for hydrogen production by an electrolytic hydrogen production device and is stored in the electric storage device or sold to a main network;
s33, if the integral energy supply of the microgrid is insufficient, the step is executed: purchasing electricity or making demand side load responses or purchasing hydrogen from a main grid;
s4, establishing a double-layer configuration-operation optimization model which is in accordance with the micro-grid comprehensive constraint set and an objective function by taking the minimum comprehensive cost of the whole life cycle of the micro-grid and the wind-solar energy consumption rate and the energy efficiency factor as objective functions;
the S41 objective function is expressed as follows:
minF＝(F ty1 +F sup +F rep )×CRF+F ty2 +βF p
wherein, F ty1 For the first investment cost of the equipment, F sup Investment cost for auxiliary equipment F rep For the cost of replacement of equipment in the full life cycle, F ty2 For the operating costs of the plant, F p Penalty terms for the absorption rate and the energy efficiency, beta is a penalty coefficient, and CRF is a capital recovery coefficient;
the cost expressions in the S42 objective function are as follows:
wherein: k is a radical of formula i Cost per unit power, P, of distributed power for dehydrogenation of fuel cells i For the corresponding installed capacity, i represents a distributed power supply in which the hydrogen removal fuel cell is; g j Cost per unit capacity of the energy storage device, C j J represents the energy storage device type and number for its capacity; k is a radical of m Cost per unit power, P, for hydrogen-related equipment m-rate Rated capacity of hydrogen-related equipment, n is life cycle of microgrid, LC m M represents the type and number of hydrogen-related equipment, including electrolytic hydrogen production deviceAnd a hydrogen fuel cell; alpha is alpha 1 α 2 For an auxiliary cost coefficient, the proportion of auxiliary cost to purchase cost is referred to;
is the real-time electricity rate at the time t,
the power is interacted between the micro-grid and the main grid; m is gas In order to be the price of the hydrogen gas,
the trading volume of hydrogen at the moment t; p is a radical of d In order to meet the cost of the demand-side response,
for the demand side response power at time t,
representing the electrical load demand at time t,
and
respectively representing the photovoltaic output, the wind power output and the hydroelectric output at the moment t General (1) To optimize the time.
S43 the electric storage device operation constraints are:
wherein SOC represents the charging/discharging state of the accumulator, SOC min For the allowable lower limit of the SOC of the electric storage device, SOC max Is an allowable upper limit of the SOC of the electric storage device, SOC t Indicating the state of the SOC at time t,
the output power of the electric storage device at the time t. t is t 0 Is superior toChange the starting time of lambda s Is the initial SOC state quantity, C bat Indicating the rated capacity, eta, of the storage means bat The charge-discharge efficiency of the electric storage device;
s44, the hydrogen production-hydrogen fuel cell equipment has the operation constraints that:
wherein, ES t Representing the state of capacity of the hydrogen storage unit at time t, m pro ,m con Electric conversion coefficient, C, of electrolytic hydrogen production apparatus and hydrogen fuel cell, respectively hyd Is the hydrogen storage capacity, lambda e Is the initial hydrogen storage device capacity state;
respectively representing the electrolytic hydrogen production power and the hydrogen fuel cell output at the moment t; k is a radical of g Is a hydrogen related unit parameter;
indicating the on-state of the hydrogen plant for the period of time; x represents the hydrogen waste amount in the starting and stopping process of the hydrogen production equipment;
s45, main network power interaction and demand side response constraint is as follows:
wherein P is pmin ,P pmax For the upper and lower limits of the interaction power, P, of the microgrid and the main network drmax Responding to the upper power limit for the demand side;
power is interacted between the micro-grid and the main grid;
demand side response power at time t;
s46, the upper and lower limits of the power of the equipment are constrained as follows:
in the formula, P batmax Alpha is the maximum output/charging power of the electricity storage device, and alpha is the overload operation coefficient of the electrolytic hydrogen production device, P el-rate 、P fc-rate Rated power of the hydrogen fuel cell and the electrolytic hydrogen production device are respectively, the electrolytic hydrogen production device and the hydrogen fuel cell have a lowest operating point which is not 0 when starting up, and are zero when in a shutdown state;
according to FIG. 2:
s5, solving the optimization model to obtain an optimization configuration scheme of the microgrid;
s51, reading new energy, various load data and electricity price information data;
s52, randomly initializing the position and the speed of each particle of a population in the particle swarm optimization, wherein the population comprises an upper layer configuration capacity variable serving as an upper limit constraint value and a lower limit constraint value of a lower layer operation constraint;
s53, solving a mixed integer programming problem formed by lower-layer operation constraints by using a solver based on upper-layer configuration variable values represented by the particle swarm algorithm population to obtain the optimal operation cost or no-solution information under the values;
s54, calculating a total objective function value, evaluating the fitness of each particle, and storing the position and the fitness value of each particle;
s55, updating the speed and the displacement of the particles;
s56, updating the algorithm weight by utilizing a nonlinear dynamic inertia weight coefficient formula:
wherein, ω is max ,ω min The maximum and minimum of the weight of the particle, F is the current objective function value of the particle, F avg ,F min Respectively representing the average target value and the minimum target value of all current particles;
s57, updating the position and the adaptive value of the current optimal individual;
and S58, if the preset operation precision or iteration times are met, stopping searching, and outputting an optimal capacity configuration result, otherwise, returning to the step S53.
The embodiment of the invention comprises the following steps:
the method comprises the steps of firstly, analyzing the local new energy condition of the micro-grid construction, secondly, researching or acquiring the local or nearby power load data and hydrogen demand condition of the construction site, requirements such as installation conditions, equipment capacity upper limit and the like, thirdly, determining the topological structure of the micro-grid, energy flow relations of various energy main forms, determining the overall energy supply and operation mode of the micro-grid, and fourthly, establishing a comprehensive constraint set and an objective function to form a double-layer configuration-operation optimization model.
Table 1 optimal configuration capacity results
| Component type | Capacity parameter |
| photovoltaic/fan/KW | 400/3735.06 |
| accumulator/KWH | 5887.11 |
| Electrolysis cell/Fuel cell/KW | 389.15/167.15 |
| Hydrogen storage tank/KG | 200 |
According to the method, the total quantity and the energy relation of the new energy resource structure of the place where the micro-grid is located are obtained, the equipment installation condition and the upper limit and the lower limit are determined, the information is gathered, the energy flow relation of the topological structure of the micro-grid and various energy main body forms is completed, the overall energy supply and operation mode of the micro-grid is further determined, the optimization configuration scheme of the micro-grid is obtained by constructing a function solution optimization model, and therefore the multiple energy forms, the high renewable energy consumption rate and the system energy efficiency can be coupled.
The invention adjusts the installation parameters of the corresponding power generation equipment by collecting the observation data of various energy forms, and is beneficial to effectively utilizing the energy of various forms according to the location of the micro-grid.
The method collects the power load data and the hydrogen demand data, arranges the area of the new energy equipment according to the obtained data, determines the maximum installation capacity and the number of various equipment, and is favorable for reasonably planning the storage and release of various energy forms of the microgrid.
The method comprehensively judges the profit and loss of the integral energy supply of the micro-grid according to the profit and loss of the energy flow of various energy main bodies, utilizes equipment to store energy or sell the energy and the main grid when the energy of the micro-grid is surplus, and purchases electricity or carries out demand side load response or purchases hydrogen from the main grid when the energy of the micro-grid is lost.
The method establishes an objective function, cost expressions in the objective function, an electricity storage device operation constraint function, a hydrogen production-hydrogen fuel cell equipment operation constraint function, a main network power interaction and demand side response constraint function and an equipment power upper and lower limit constraint function, and the functions are used for calculating parameters of stable operation of the micro-grid system.
The method comprises the steps of assigning values to the positions and the speeds of particles in a population in a random initialization particle swarm algorithm by reading new energy, various load data and electricity price information data, calculating a total objective function value by using a cyclic algorithm, evaluating the fitness of each particle, storing the positions and the fitness values of the current particles, updating the algorithm weight by using the updated speed and displacement of the particles in a nonlinear dynamic inertia weight coefficient formula, and finding an optimal solution or finding the optimal solution after multiple cycles.
Claims (7)
1. A hydropower hydrogen production optimal configuration method suitable for the starting and stopping characteristics of hydrogen production equipment is characterized by comprising the following steps: the method comprises the following steps:
s1, collecting and analyzing the total amount of available new energy resources of a microgrid building local area, and determining installation parameters of new energy equipment;
s2, acquiring local power load data, hot water demand data and hydrogen demand conditions of a construction site, and determining installation conditions and equipment capacity upper limit;
s3, determining a topological structure of the microgrid, energy flow relations of various energy main body forms and an overall energy supply and operation mode of the microgrid;
s4, establishing a double-layer configuration-operation optimization model which is in accordance with the micro-grid comprehensive constraint set and an objective function by taking the minimum comprehensive cost of the whole life cycle of the micro-grid and the wind-solar energy consumption rate and the energy efficiency factor as objective functions;
and S5, solving the optimization model to obtain an optimization configuration scheme of the microgrid.
2. A hydropower hydrogen production optimization configuration method suitable for the start-stop characteristic of hydrogen production equipment according to claim 1, which is characterized in that: wherein the step S1 further comprises:
s11, collecting main climate observation data of wind, light and water resources;
and S12, adjusting the installation parameters of the photovoltaic equipment, the fan and the radial flow type hydropower station according to the data of the S11.
3. A hydropower hydrogen production optimization configuration method suitable for the start-stop characteristic of hydrogen production equipment according to claim 1, which is characterized in that: wherein the step S2 further comprises:
s21 collects power load data and hydrogen demand data: load characteristic data of governments, industries and residents on electricity utilization conditions, holidays, double-holidays and workdays, and hydrogen demand data of hydrogen fuel cell automobiles in construction areas, gas consumption parameters, hydrogen industries and hydrogen marketers;
s22, determining the maximum installation capacity and the number of various devices according to the arrangement area of the new energy devices in the construction area, the government relevant ground standard and the hydrogen safety distance.
4. A hydropower hydrogen production optimization configuration method suitable for the start-stop characteristic of hydrogen production equipment according to claim 1, which is characterized in that: wherein the step S3 further comprises:
s31, comprehensively judging the profit and loss of the integral energy supply of the microgrid according to the profit and loss of the energy flows in various energy main body forms;
s32, if the whole energy supply of the microgrid is sufficient, executing the step: the distributed power supply utilizes new energy to generate electric energy to supply the electric energy to an electric load, and redundant electric energy is stored in an electric storage device or is used for hydrogen production by an electrolytic hydrogen production device and is stored in the electric storage device or sold to a main network;
s33, if the integral energy supply of the microgrid is insufficient, the step is executed: power is purchased from a main grid or demand side load responses are made or hydrogen is purchased.
5. An optimal configuration method of hydroelectric hydrogen production suitable for the start-stop characteristics of hydrogen production equipment, according to claim 1, characterized in that: wherein the step of constructing the objective function in S4 comprises:
the S41 objective function is expressed as follows:
minF＝(F ty1 +F sup +F rep )×CRF+F ty2 +βF p
wherein, F ty1 For the first investment cost of the equipment, F sup Investment cost for auxiliary equipment F rep For the cost of replacement of equipment in the full life cycle, F ty2 For the operating costs of the plant, F p Beta is a penalty coefficient, and CRF is a capital recovery coefficient;
wherein: k is a radical of i Cost per unit power, P, of distributed power for dehydrogenation of fuel cells i I represents a distributed power source in which the dehydrogenation fuel cell is regarded as corresponding installed capacity; g j To storeCost per unit volume of energy installation, C j J represents the energy storage device type and number for its capacity; k is a radical of m Cost per unit power, P, for hydrogen-related equipment m-rate Rated capacity of hydrogen-related equipment, n is life cycle of microgrid, LC m M represents the type and the number of hydrogen-related equipment, including an electrolytic hydrogen production device and a hydrogen fuel cell, for the life span of the hydrogen-related equipment; alpha is alpha 1 α 2 For an auxiliary cost coefficient, the proportion of auxiliary cost to purchase cost is referred to;
is the real-time electricity rate at the time t,
the power is interacted between the micro-grid and the main grid; m is a unit of gas In order to be the price of the hydrogen gas,
the trading volume of hydrogen at the moment t; p is a radical of d In order to meet the cost of the demand-side response,
for the demand side response power at time t,
representing the electrical load demand at time t,
and
respectively representing the photovoltaic output, the wind power output and the hydroelectric output at the moment t General assembly To optimize the time.
6. A hydropower hydrogen production optimization configuration method suitable for the start-stop characteristic of hydrogen production equipment according to claim 1, which is characterized in that: wherein the step of constructing the construction constraint in S4 comprises:
s42, constructing operation constraints of the power storage device;
s43, constructing main network power interaction and demand side response constraint;
s44, constructing main network power interaction and demand side response constraint;
s45, constructing upper and lower limits of power of the equipment;
7. a hydropower hydrogen production optimization configuration method suitable for the start-stop characteristic of hydrogen production equipment according to claim 1, which is characterized in that: wherein the step S5 further comprises:
s51, reading new energy, various load data and electricity price information data;
s52, randomly initializing the position and the speed of each particle of a population in the particle swarm optimization, wherein the population comprises an upper layer configuration capacity variable serving as an upper limit constraint value and a lower limit constraint value of a lower layer operation constraint;
s53, solving a mixed integer programming problem formed by lower-layer operation constraints by using a solver based on upper-layer configuration variable values represented by the particle swarm algorithm population to obtain the optimal operation cost or no-solution information under the values;
s54, calculating a total objective function value, evaluating the fitness of each particle, and storing the position and the fitness value of each particle;
s55, updating the speed and the displacement of the particles;
s56, updating the algorithm weight by utilizing a nonlinear dynamic inertia weight coefficient formula:
wherein, ω is max ,ω min The maximum and minimum of the weight of the particle, F is the current objective function value of the particle, F avg ,F min Respectively representing the average target value and the minimum target value of all current particles;
s57, updating the position and the adaptive value of the current optimal individual;
and S58, if the preset operation precision or iteration times are met, stopping searching, and outputting an optimal capacity configuration result, otherwise, returning to the step S53.
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