An optimization method for a multi-energy complementary system based on electric-thermal-hydrogen hybrid energy storage

Abstract

The present invention provides a method for optimizing a multi-energy complementary system based on electric-thermal-hydrogen hybrid energy storage, which adopts a hybrid energy storage form of electricity storage, hydrogen storage, and heat storage, and takes into account the mutual conversion between the three energy storage forms, so as to better achieve a balance between the cost of the energy storage system and the performance of the energy storage system. The present invention optimizes the system energy production, conversion, storage, and other aspects, considers different constraints such as energy storage capacity, energy storage system response speed, and energy storage system capacity, and adopts reliability, cost, stability, and other multi-objective optimization. It solves the problem of combined configuration of large-scale energy storage systems, absorbs the advantages of various energy storage technology routes through reasonable design and scheduling, solves the problems of high cost of large-scale electricity storage systems, difficulty in using hydrogen storage systems, difficulty in ensuring the temperature of molten salt heat storage systems, and coordination and matching of multi-energy storage systems, and finally realizes the low-cost and efficient operation of the combined energy storage system.

Description

Technical Field

[0001] The present invention belongs to the technical field of renewable energy power generation, and specifically relates to a method for optimizing a multi-energy complementary system based on electric, thermal and hydrogen hybrid energy storage. Background Art

[0002] At present, there are many studies based on multi-energy complementary systems. However, most of the related work only focuses on a single energy storage technology. The multi-energy complementary system architecture model based on a single energy storage has several limitations:

[0003] (1) Each energy storage technology has its own advantages and disadvantages. In the actual multi-energy complementary system, the energy storage requirements include power type, capacity type and other forms, and different energy storage forms correspond to different cost structures. A single energy storage technology is difficult to meet the actual needs of the system.

[0004] (2) Some single energy storage forms are suitable for rapid system response, while others are suitable for large-capacity storage. The requirements for storage and construction conditions are also different. However, a multi-energy complementary system with a single energy storage is not conducive to the development of this feature.

[0005] (3) At present, energy storage technology is still in its early stages of development. The configuration scheme of a single energy storage form is not conducive to improving the performance and cost of the system, but the design, operation and optimization methods of multi-hybrid energy storage systems are still immature.

[0006] (4) In a multi-energy complementary system that includes solar thermal, the temperature of the concentrating field at the front end of the solar thermal power station may fluctuate with the change of the sun, which will affect the power generation efficiency at the back end. Summary of the invention

[0007] The purpose of the present invention is to provide a multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage to overcome the above-mentioned technical problems existing in the prior art.

[0008] To this end, the technical solution provided by the present invention is as follows:

[0009] A multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage comprises the following steps:

[0010] Step 1) respectively establishing a photovoltaic power generation subsystem model, a wind power generation subsystem model and a solar thermal power generation subsystem model, and respectively establishing a storage subsystem model, a heat storage subsystem model and a hydrogen storage subsystem model;

[0011] Step 2) setting the system operation logic and determining the thresholds that need to be optimized in the operation logic to obtain the expected charge and discharge capacity of each link;

[0012] Step 3) setting the restriction conditions of each subsystem model, and verifying the expected charge and discharge capacity of each link obtained in step 2);

[0013] Step 4) setting system optimization parameters and target values, wherein the system optimization parameters include system conversion efficiency, system power shortage rate, system initial investment, and system life cycle energy cost;

[0014] Step 5) Use a single swarm intelligence algorithm or a combined algorithm to continuously iterate the optimization target until the set target value is reached, then jump out to obtain the optimization solution. If it is not reached, the number of cycles can be changed to restart the cycle or some of the restrictions set in step 2) can be adjusted;

[0015] Step 6) Obtain the multi-energy flow conversion combination optimization of electrical energy, thermal energy and hydrogen energy.

[0016] The photovoltaic power generation electronic system model in step 1) is as follows:

[0017]

[0018]

[0019]

[0020] Where I is the system current, V is the system voltage, and I SC is the short-circuit current, V oc is the open circuit voltage; I m is the output current at maximum power, V m is the output voltage at the maximum power point.

[0021] The wind power generation subsystem model is as follows:

[0022]

[0023] Among them, P wt is the system output power, V in is the system startup wind speed, V out is the system shutdown wind speed, V rs is the wind speed corresponding to the full load operation of the system, P WTd Full load operating power.

[0024] The photothermal electronic system model in step 1) is as follows:

[0025] P t th,SF-HTF+Ptth,TS-HTF =P t th,HTF-TS+Ptth,HTF-PB

[0026] Among them, P t th,SF-HTFP is the thermal power output by the heat collection module; t th,HTF-TS P is the heat absorption power of the heat storage system of the CSP power station that can absorb energy from the heat transfer medium; t th,TS-HTF P is the heat release power of the heat storage system of the CSP power station that can release energy from the heat transfer medium; t th,HTF-PB It is the thermal power absorbed from the heat transfer fluid in the power generation process.

[0027] Step 1) The model of the Zhongchu electronic system is as follows:

[0028] V bat =E b +R i I bat

[0029]

[0030] Among them, V bat ,I bat E are the external current and voltage of the battery respectively; b is the internal electromotive force of the battery; Ri is the resistance of the battery; SOC0 is the initial state of charge of the battery; P c (t) is the battery charging and discharging power, the charged state is positive; L c_0 is the rated capacity of the battery.

[0031] The heat storage subsystem model in step 1) is as follows:

[0032]

[0033] in, is the heat storage energy of the heat storage system at time t; γ is the heat dissipation coefficient; P t th,cha , P t th,dis are the charging / discharging power of the heat storage system at time t; Δt is the time interval; the heat storage capacity of the heat storage link is limited by the heat storage capacity, that is, The upper and lower limits of the heat storage energy of the heat storage system.

[0034] The hydrogen storage subsystem model in step 1) is the hydrogen storage capacity limitation and storage-use balance.

[0035] Step 2) The specific process is as follows:

[0036] Compare the power dispatched by the grid with the power available from wind power and photovoltaic power, two non-dispatchable power sources:

[0037] (1) When the amount of electricity delivered is less than the amount of electricity that can be generated by photovoltaic and wind power, the system enters the power surplus mode and the energy storage system enters the charging process;

[0038] In the charging process, the energy storage units are selected in order according to the overall energy conversion efficiency, that is, electrochemical energy storage is used first, and when the electrochemical energy storage is full, thermal energy storage is used, and finally hydrogen energy storage is used, and charging is carried out in sequence;

[0039] When there is a gap in heat supply within the past 24 hours, electric heating conversion is carried out, and heat storage is given priority. Other energy storage is carried out in the above order;

[0040] When there is a hydrogen energy gap within the past 24 hours, electricity-to-hydrogen conversion is carried out, hydrogen energy storage is given priority, and other energy storage forms are carried out in the above order;

[0041] (2) When the amount of electricity delivered is greater than the amount of electricity that can be generated by photovoltaic and wind power, the system enters the power shortage mode and the energy storage system enters the discharge process;

[0042] In the discharge process, the energy storage units are selected in order according to the overall energy conversion efficiency, that is, electrochemical energy storage is used first, and when the electrochemical energy storage is full, thermal energy storage is performed, and finally hydrogen energy storage is used for discharge in sequence;

[0043] When there is excess thermal energy storage in the past 24 hours, heat-to-electricity conversion is performed, with thermal energy storage being prioritized, and other energy storage is performed in the above order;

[0044] When there is excess hydrogen energy storage within the past 24 hours, hydrogen to electricity refueling conversion is carried out, hydrogen energy storage is given priority, and other forms of energy storage are carried out in the above order.

[0045] The specific process of step 3) is as follows:

[0046] First, a solution library is established based on the properties of the equipment to determine the limiting conditions, including system response climbing conditions, capacity limiting conditions, the hydrogen blending ratio allowed for the equipment and pipelines, and the maximum scale corresponding to the technical route;

[0047] The system response climbing conditions include the power climbing requirements of the equipment per minute and the response cycle of the energy storage link after receiving the charging and discharging requirements. The capacity limitation conditions include the battery capacity, the heat storage tank capacity, and the hydrogen storage tank capacity. The hydrogen blending ratio allowed by the pipeline includes the maximum hydrogen energy combustion ratio that can be received by natural gas and pipeline equipment without safety failure.

[0048] Secondly, the expected charge and discharge capacity of each link obtained in step 2) is verified:

[0049] When the operation logic of step 2) does not satisfy the above solution set library, the corresponding values ​​are upper limit values. Based on the upper limit values, the ideal operation logic scheme is re-formulated and iterated until the restriction conditions of the solution set library are met.

[0050] The single swarm intelligence algorithm in step 5) is a multi-objective genetic algorithm, a multi-objective particle swarm algorithm, a multi-objective ant colony algorithm, a multi-objective bee colony algorithm or a multi-objective fish swarm algorithm.

[0051] The beneficial effects of the present invention are:

[0052] The multi-energy complementary system optimization method based on electric-thermal-hydrogen hybrid energy storage provided by the present invention adopts a hybrid energy storage form of electricity storage, hydrogen storage, and heat storage, and takes into account the mutual conversion between the three energy storage forms, which can better achieve a balance between the cost of the energy storage system and the performance of the energy storage system.

[0053] The present invention optimizes various aspects of system energy production and storage, considers different constraints such as energy storage capacity, energy storage system response speed, and energy storage system capacity, and uses reliability, cost, stability, and other factors for multi-objective optimization. The present invention can optimize the triggering conditions for the mutual conversion between electricity, heat, and hydrogen in the multi-energy complementary system, and improve the efficiency of system operation. Using a variety of energy storage forms, electric energy storage can meet the needs of power-type users, and meet the energy storage needs of wind power and photovoltaics in seconds and minutes; thermal energy storage corresponds to the needs of energy-type users, and meets the energy needs of the system from ten minutes to hours; hydrogen storage corresponds to the wind power and photovoltaic consumption needs in the system, the supplementary combustion needs of solar thermal power stations, and possible long-distance wireless energy transmission needs. Through the complementary energy supply and advantages mentioned above, the overall efficient operation of the multi-energy complementary hybrid energy storage system is ultimately achieved.

[0054] The present invention uses abandoned electricity from wind power and photovoltaic power to electrolyze water to produce hydrogen, which is beneficial to the consumption of renewable energy. The generated hydrogen energy is used as fuel to supplement the molten salt system of the solar thermal power station, and at the same time solves the problem of difficulty in ensuring the outlet temperature of the concentrating and collecting system of the solar thermal power station.

[0055] Through reasonable design and scheduling, the present invention absorbs the advantages of various energy storage technology routes, solves the problems of high cost of large-scale electricity storage systems, difficulty in using hydrogen storage systems, and difficulty in ensuring the temperature of molten salt heat storage systems, and ultimately achieves low-cost and efficient operation of the combined energy storage system. It can meet functional requirements at different levels and can combine the advantages of various technical routes to ultimately obtain a hybrid energy storage configuration optimization solution that improves the economy and power quality of the multi-energy complementary system.

[0056] The following will provide a further detailed description with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1It is a logical schematic diagram of the optimization process of the present invention;

[0058] Figure 2 It is a schematic diagram of energy flow of the present invention. DETAILED DESCRIPTION

[0059] The following describes the implementation of the present invention through specific embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification.

[0060] The exemplary embodiments of the present invention are now described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0061] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0062] Embodiment 1:

[0063] This embodiment provides a multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage, such as Figure 1 As shown, the following steps are included:

[0064] Step 1) respectively establishing a photovoltaic power generation subsystem model, a wind power generation subsystem model and a solar thermal power generation subsystem model, and respectively establishing a storage subsystem model, a heat storage subsystem model and a hydrogen storage subsystem model;

[0065] Step 2) setting the system operation logic and determining the thresholds that need to be optimized in the operation logic to obtain the expected charge and discharge capacity of each link;

[0066] Step 3) setting the restriction conditions of each subsystem model, and verifying the expected charge and discharge capacity of each link obtained in step 2);

[0067] Step 4) setting system optimization parameters and target values, wherein the system optimization parameters include system conversion efficiency, system power shortage rate, system initial investment, and system life cycle energy cost;

[0068] Step 5) Use a single swarm intelligence algorithm or a combined algorithm to continuously iterate the optimization target until the set target value is reached, then jump out to obtain the optimization solution. If it is not reached, the number of cycles can be changed to restart the cycle or some of the restrictions set in step 2) can be adjusted;

[0069] Step 6) Obtain the multi-energy flow conversion combination optimization of electrical energy, thermal energy and hydrogen energy.

[0070] During the optimization process, when the solution set corresponding to the optimization target is not updated for a specific number of times, the individual is reset, but the optimal and better solutions are retained and the cycle is restarted. The specific number of triggers can be adjusted according to the specific situation.

[0071] When the number of cycles reaches the set value, the program will exit. If the expected effect is not achieved, the number of cycles can be changed and the cycle can be restarted from step 5), or the limiting conditions set in step 2) can be partially adjusted.

[0072] The multi-energy complementary system optimization method based on electric-thermal-hydrogen hybrid energy storage provided by the present invention adopts a hybrid energy storage form of electricity storage, hydrogen storage, and heat storage, and takes into account the mutual conversion between the three energy storage forms, which can better achieve the balance between the cost of the energy storage system and the performance of the energy storage system. Through reasonable design and scheduling, it absorbs the advantages of various energy storage technology routes, solves the problems of high cost of large-scale electricity storage systems, difficulty in using hydrogen storage systems, and difficulty in ensuring the temperature of molten salt heat storage systems, and finally realizes the low-cost and efficient operation of the combined energy storage system, which can meet the functional requirements of different levels, and can combine the advantages of various technical routes, and finally obtain a hybrid energy storage configuration optimization plan that improves the economy and power quality of the multi-energy complementary system.

[0073] Embodiment 2:

[0074] On the basis of Example 1, this embodiment provides a multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage, and the photovoltaic power generation subsystem model in step 1) is as follows:

[0075]

[0076]

[0077]

[0078] Where I is the system current, V is the system voltage, and I SC is the short-circuit current, V oc is the open circuit voltage; I m is the output current at maximum power, V m is the output voltage at the maximum power point.

[0079] Using solar radiation and temperature as input conditions and using it as an uncontrollable power source, the above model represents the relationship between the output current of the photovoltaic panel and the external conditions.

[0080] The wind power generation subsystem model is as follows:

[0081]

[0082] Among them, P wt is the system output power, V in is the system startup wind speed, V out is the system shutdown wind speed, V rs is the wind speed corresponding to the full load operation of the system, P WTd Full load operating power.

[0083] The output characteristics of the wind turbine system are described based on the wind speed-power curve and are described using the primary output model as above.

[0084] Solar thermal power generation is an important dispatchable link in this technology. DNI ,t The heat output P through the heat collection module t th,SF-HTF Considering that too much solar radiation may cause incomplete absorption, the thermal power rejection P is introduced. t th,cut The power generation stage absorbs thermal power P from HTF t th,HTF-PB , and converts thermal energy into electrical energy P t CSP To generate electricity.

[0085] Based on the above analysis, if the energy loss of the heat-conducting medium in the heat transfer fluid (HTF) is ignored, the power balance equation inside the CSP power station can be obtained, that is, the thermal power generation electronic system model:

[0086] P t th,SF-HTF +P t th,TS-HTF =P t th,HTF-TS +P t th,HTF-PB

[0087] Among them, P t th,SF-HTF P is the thermal power output by the heat collection module; t th,HTF-TS P is the heat absorption power of the heat storage system of the CSP power station that can absorb energy from the heat transfer medium; t th,TS-HTFP is the heat release power of the heat storage system of the CSP power station that can release energy from the heat transfer medium; t th,HTF-PB It is the thermal power absorbed from the heat transfer fluid in the power generation process.

[0088] The solar thermal system includes heat collection, heat storage and power generation.

[0089] 1) Solar Collection

[0090] The thermal power output of the heat collection module P t th,SF-HTF for:

[0091]

[0092]

[0093] Where η SF is the light-to-heat conversion efficiency of the light field; A SF is the area of ​​the mirror field; x DNI,t is the direct solar radiation at time t; is the thermal power abandoned by the solar collector at time t.

[0094] In order to conveniently describe the relationship between the scale of the solar field in the solar collection link and the installed capacity of the CSP power station, the concept of solar multiple (SM) is introduced here. The solar multiple refers to the ratio of the output power of the solar collection link to the rated power of the power generation link under the maximum direct solar radiation that the mirror field can receive. Since the solar radiation reaching the ground has a certain degree of intermittence and uncertainty, the direct solar radiation intensity of the mirror field generally does not reach the designed maximum value. Therefore, in order to ensure that the power generation link can operate in the rated working state, the solar multiple is usually greater than 1 during the design of the CSP power station.

[0095] Solar multiple S of the heat collection link SF It can be expressed as:

[0096]

[0097] Where η PB is the heat-to-electricity conversion efficiency of the power generation link; x DNI,max is the maximum direct solar radiation intensity that the light field can receive, is the rated output power of the power generation link.

[0098] 2) Heat storage

[0099] For a heat storage system, its own heat dissipation is usually not negligible, so the energy storage state balance equation of the heat storage link can be expressed as:

[0100]

[0101] In the formula, is the heat storage energy of the heat storage system at time t; γ is the heat dissipation coefficient; P t th,cha , P t th,dis are the charging / discharging power of the heat storage system at time t; Δt is the time interval.

[0102] Considering that the dissipation coefficient is relatively small, it can be linearized to simplify the calculation. After linearization, the heat storage subsystem model is as follows:

[0103]

[0104] The heat storage capacity of the heat storage link is limited by the heat storage capacity, that is,

[0105]

[0106] In the formula, The upper and lower limits of the heat storage energy of the heat storage system.

[0107] In order to quantify the size of the heat storage capacity of the heat storage link, the concept of heat storage time is introduced here. The heat storage time refers to the maximum number of hours that the heat storage link can maintain the rated power generation of the CSP station under the rated heat storage capacity.

[0108] Heat storage time H TES It can be expressed as:

[0109]

[0110] Where η dis is the heat release efficiency; η PB is the thermoelectric conversion efficiency.

[0111] The heat storage system will be accompanied by heat loss during the charging / discharging process. The charging / discharging efficiency can be introduced to describe this process, that is,

[0112] P t th,cha =η cha P t th,HTF-TS

[0113] P t th,dis =P t th,TS-HTF / η dis

[0114] Where η cha is the charging efficiency of the heat storage system; η dis For heat release efficiency.

[0115] During the energy exchange process of the heat storage system, the charging and discharging power should be continuously adjustable within the limited range, and the charging / discharging process cannot be carried out at the same time.

[0116]

[0117]

[0118]

[0119] In the formula, are the maximum charging / discharging power, is the state variable of the heat storage system charging / discharging at time t.

[0120] 3) Power generation

[0121] The energy conversion balance equation in the power generation link is:

[0122]

[0123] Where η PB The heat-to-electricity conversion efficiency of the power generation stage; The power required to start the power generation link, It is the start flag variable of the power generation link at time t.

[0124] Output power P of the power generation link t CSP The following relationship should be satisfied:

[0125]

[0126] In the formula, It is the maximum and minimum output of the units in the power generation link; is a 0-1 variable of the unit's operating status. and The relationship between them should satisfy:

[0127]

[0128] The units in the power generation stage should meet the climbing constraints:

[0129]

[0130] In the formula, They are the maximum up and down climbing capabilities of the unit respectively.

[0131] The power generation link should meet the minimum start / stop time constraints:

[0132]

[0133]

[0134] In the formula, It is the minimum start / stop time of the power generation link.

[0135] The power storage system mainly simulates the important parameters in charging and discharging according to the following formula:

[0136] V bat =E b +R i I bat

[0137]

[0138] Among them, V bat ,I bat are the external current and voltage of the battery (charging direction is positive); E b is the internal electromotive force of the battery; Ri is the resistance of the battery; SOC0 is the initial state of charge of the battery; Q0 ​​is the rated capacity of the battery, in A·h; Q u Unavailable capacity.

[0139] It can be seen that the change of the state of charge SOC of the energy storage system directly reflects the working condition of the battery. By converting the above formula, the electronic storage system model can be obtained as follows:

[0140] V bat =E b +R i L bat

[0141]

[0142] Where P c (t) is the battery charging and discharging power, the charged state is positive; L c_0 It is the rated capacity of the battery, in kwh.

[0143] The hydrogen storage subsystem model in step 1) is the hydrogen storage capacity limitation and storage-use balance. The electric-hydrogen conversion only considers the electric-hydrogen efficiency.

[0144] The multi-energy complementary system includes the following parts:

[0145] (1) Energy production part:

[0146] Including: wind power, photovoltaic and solar thermal. Among them, wind power and photovoltaic are non-adjustable power sources, and solar thermal is an adjustable power source.

[0147] (2) Energy storage link:

[0148] The main equipment includes: battery storage modules, molten salt / water heat storage tanks, hydrogen storage tanks and other links. The power storage link is mainly used to handle minute-level energy storage, and the heat storage link is mainly used to handle hour-level energy storage. The hydrogen storage link is mainly used to handle longer-term and longer-distance energy storage.

[0149] Among them, the storage battery is interconnected with the photovoltaic and wind power units, and is directly used to store energy changes caused by minute-level fluctuations in resources.

[0150] The heat storage system is divided into two parts: molten salt heat storage and water heat storage. The molten salt heat storage part is mainly used for heat storage in high temperature sections (above 300 degrees), and the water heat storage part is mainly used for large-scale energy storage below 100 degrees. According to the corresponding characteristics, molten salt heat storage tanks and water storage tanks are set up respectively.

[0151] The energy source of the molten salt thermal storage system is divided into two parts. One part is connected to the heliostat field to absorb the tower, trough and linear Fresnel collector units. The other part is connected to the power generation outlet of the wind power photovoltaic system to absorb the electric molten salt heater to realize the conversion of electrical energy into thermal energy.

[0152] As for the water heat storage part, it mainly supplements the molten salt heat storage and mainly configures a water pool to realize water heat storage. Under normal working conditions, the energy source of water heat storage is the waste heat after solar thermal power generation. When the hot molten salt storage tank is close to full, the water heat storage can be used as a backup for the molten salt heat storage after multi-stage heat exchange to achieve larger-scale heat storage.

[0153] (3) The present invention realizes the combined optimization of the system through the conversion and coupling of multiple energy flows of electric energy, thermal energy and hydrogen energy, such as Figure 2 As shown, the energy in and out and energy conversion links are as follows:

[0154] Electrical Energy:

[0155] Main energy sources: charged by photovoltaic and wind power generation. In a few cases, it can also be charged by electricity generated by solar thermal power stations.

[0156] Main energy consumption: used for power grid access, electric heating of molten salt or electrolysis of water to produce hydrogen.

[0157] Thermal Energy:

[0158] The main energy sources are: solar thermal power station, electric heating, natural gas supplementary combustion, natural gas mixed with hydrogen supplementary combustion. The electric heat conversion system only considers the electric heat efficiency and heat storage capacity limitations.

[0159] Main energy consumption: driving steam turbine to generate electricity.

[0160] Hydrogen energy:

[0161] The main energy source is: hydrogen production by water electrolysis.

[0162] The main energy consumption is: hydrogen energy delivery, hydrogen blending into natural gas pipelines, and supplementary combustion in the solar thermal system.

[0163] The hydrogen storage link is mainly used to store energy for longer periods of time and over longer distances.

[0164] The present invention uses abandoned electricity from wind power and photovoltaic power to electrolyze water to produce hydrogen, which is beneficial to the consumption of renewable energy. The generated hydrogen energy is used as fuel to supplement the molten salt system of the solar thermal power station, and at the same time solves the problem of difficulty in ensuring the outlet temperature of the concentrating and collecting system of the solar thermal power station.

[0165] Embodiment 3:

[0166] On the basis of Example 1, this embodiment provides a multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage, and the specific process of step 2) is as follows:

[0167] Compare the power dispatched by the grid with the power available from wind power and photovoltaic power, two non-dispatchable power sources:

[0168] (1) When the amount of electricity delivered is less than the amount of electricity that can be generated by photovoltaic and wind power, the system enters the power surplus mode and the energy storage system enters the charging process;

[0169] In the charging process, the energy storage units are selected in order according to the overall energy conversion efficiency, that is, electrochemical energy storage is used first, and when the electrochemical energy storage is full, thermal energy storage is used, and finally hydrogen energy storage is used, and charging is carried out in sequence;

[0170] When there is a gap in heat supply within the past 24 hours, electric heating conversion is carried out, and heat storage is given priority. Other energy storage is carried out in the above order;

[0171] When there is a hydrogen energy gap within the past 24 hours, electricity-to-hydrogen conversion is carried out, hydrogen energy storage is given priority, and other energy storage forms are carried out in the above order;

[0172] (2) When the amount of electricity delivered is greater than the amount of electricity that can be generated by photovoltaic and wind power, the system enters the power shortage mode and the energy storage system enters the discharge process;

[0173] In the discharge process, the energy storage units are selected in order according to the overall energy conversion efficiency, that is, electrochemical energy storage is used first, and when the electrochemical energy storage is full, thermal energy storage is performed, and finally hydrogen energy storage is used for discharge in sequence;

[0174] When there is excess thermal energy storage in the past 24 hours, heat-to-electricity conversion is performed, with thermal energy storage being prioritized, and other energy storage is performed in the above order;

[0175] When there is excess hydrogen energy storage within the past 24 hours, hydrogen to electricity refueling conversion is carried out, hydrogen energy storage is given priority, and other forms of energy storage are carried out in the above order.

[0176] After calculating the difference between the system's required power generation and actual power generation, add and subtract the power that the energy storage system can provide in the order of (1) and (2). If the required power generation can be equal to the sum of the actual power generation and the energy storage regulation power, the ideal operation plan at that time is obtained, and the guarantee rate variable at that moment is set to 1. If it still cannot be satisfied, the corresponding ideal operation plan is also output, and the guarantee rate variable at that moment is set to 0.

[0177] Embodiment 4:

[0178] On the basis of Example 3, this embodiment provides a multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage, and the specific process of step 3) is as follows:

[0179] First, a solution library is established based on the properties of the equipment to determine the limiting conditions, including system response climbing conditions, capacity limiting conditions, the hydrogen blending ratio allowed for the equipment and pipelines, and the maximum scale corresponding to the technical route;

[0180] The system response climbing conditions include the power climbing requirements of the equipment per minute and the response cycle of the energy storage link after receiving the charging and discharging requirements. The capacity limitation conditions include the battery capacity, the heat storage tank capacity, and the hydrogen storage tank capacity. The hydrogen blending ratio allowed by the pipeline includes the maximum hydrogen energy combustion ratio that can be received by natural gas and pipeline equipment without safety failure.

[0181] Secondly, the expected charge and discharge capacity of each link obtained in step 2) is verified:

[0182] When the operation logic of step 2) does not satisfy the above solution set library, the corresponding values ​​are upper limit values. Based on the upper limit values, the ideal operation logic scheme is re-formulated and iterated until the restriction conditions of the solution set library are met.

[0183] If the power balance requirement cannot be met, the ideal solution is output according to the operation method of step 2), and the guarantee rate variable at this moment is set to 0.

[0184] The present invention is applicable to various forms of multi-energy complementary and hybrid energy storage systems. When the project does not completely include all the above-mentioned energy production and storage forms, some systems can be selected according to the specific project so that the simulation system is consistent with the actual system energy type. The specific project needs to add optimization system parameters, including: wind power, photovoltaic, solar thermal scale; electricity storage, heat storage, hydrogen storage scale; trigger condition parameters for the mutual conversion of electricity, heat and hydrogen, and parameter thresholds determined in step 2).

[0185] Embodiment 5:

[0186] Based on Example 1, this embodiment provides a multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage, and the single swarm intelligence algorithm in step 5) is a multi-objective genetic algorithm, a multi-objective particle swarm algorithm, a multi-objective ant colony algorithm, a multi-objective bee colony algorithm or a multi-objective fish swarm algorithm.

[0187] This embodiment provides an optimization method based on a multi-objective genetic algorithm. When the above-mentioned other single swarm intelligence algorithms are used, it is only necessary to replace the parameter encoding process according to the standard algorithm flow.

[0188] Step 1: According to the system construction situation and the system process specified above, determine the variables that need to be optimized, including the scale and form of all the above subsystems, and the corresponding operation trigger variables.

[0189] The second step is to determine the length of the genetic algorithm chromosome according to the number of parameters to be optimized and the selectable range of the corresponding parameters. In the initial cycle, each parameter can be encoded by a 4-bit binary number. According to the chromosome length, the number of chromosome populations is determined. The initial population can be selected to be twice the chromosome length.

[0190] The third step is to determine the corresponding relationship between parameters and solutions. That is, when encoding, normalize first, and then determine each parameter that needs to be optimized as a region of 4 bits each, and perform binary encoding. When evaluating and selecting solutions and performing inverse encoding, convert each 4-bit binary code into a decimal number and then perform inverse normalization.

[0191] Step 4: After completing the denormalization, determine the corresponding system construction and operation plan based on the corresponding relationship between the parameters and the design and operation plan;

[0192] Step 5: For the multiple system optimization objectives in step 4), as the corresponding fitness function, optimize according to the Pareto frontier to obtain the solution set, and perform crossover and mutation according to the results;

[0193] If the fourth step falls into the local optimum, it will restart randomly and return to the second step;

[0194] The fifth step is to determine whether the exit condition is met and generate the final system operation plan based on the optimal chromosome encoding.

[0195] The above examples are merely illustrative of the present invention and do not constitute a limitation on the protection scope of the present invention. All designs that are the same or similar to the present invention fall within the protection scope of the present invention.

Claims

1. A multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage, characterized in that: The following steps are involved: Step 1) respectively establishing a photovoltaic power generation subsystem model, a wind power generation subsystem model and a solar thermal power generation subsystem model, and respectively establishing a storage subsystem model, a heat storage subsystem model and a hydrogen storage subsystem model; Step 2) setting the system operation logic and determining the thresholds that need to be optimized in the operation logic to obtain the expected charge and discharge capacity of each link; The specific process is as follows: Compare the power dispatched by the grid with the power available from wind power and photovoltaic power, two non-dispatchable power sources: (1) When the amount of electricity delivered is less than the amount of electricity that can be generated by photovoltaic and wind power, the system enters the power surplus mode and the energy storage system enters the charging process; In the charging process, the energy storage units are selected in order according to the overall energy conversion efficiency, that is, electrochemical energy storage is used first, and when the electrochemical energy storage is full, thermal energy storage is used, and finally hydrogen energy storage is used, and charging is carried out in sequence; When there is a gap in heat supply within the past 24 hours, electric heating conversion is carried out, thermal energy storage is prioritized, and other energy storage is carried out in the above order; When there is a hydrogen energy gap within the past 24 hours, electricity-to-hydrogen conversion is carried out, hydrogen energy storage is given priority, and other energy storage forms are carried out in the above order; (2) When the amount of electricity delivered is greater than the amount of electricity that can be generated by photovoltaic and wind power, the system enters the power shortage mode and the energy storage system enters the discharge process; In the discharge process, the energy storage units are selected in order according to the overall energy conversion efficiency, that is, electrochemical energy storage is used first, and when the electrochemical energy storage is full, thermal energy storage is performed, and finally hydrogen energy storage is used for discharge in sequence; When there is excess thermal energy storage in the past 24 hours, heat-to-electricity conversion is performed, with thermal energy storage being prioritized, and other energy storage is performed in the above order; When there is excess hydrogen energy storage within the past 24 hours, the hydrogen to electricity supplementary combustion conversion is carried out, and hydrogen energy storage is given priority. Other energy storage forms are carried out in the above order; Step 3) setting the restriction conditions of each subsystem model, and verifying the expected charge and discharge capacity of each link obtained in step 2); The specific process is as follows: First, a solution library is established based on the properties of the equipment to determine the limiting conditions, including system response climbing conditions, capacity limiting conditions, the hydrogen blending ratio allowed for the equipment and pipelines, and the maximum scale corresponding to the technical route; The system response climbing conditions include the power climbing requirements of the equipment per minute and the response cycle of the energy storage link after receiving the charging and discharging requirements. The capacity limitation conditions include the battery capacity, the heat storage tank capacity, and the hydrogen storage tank capacity. The hydrogen blending ratio allowed by the pipeline includes the maximum hydrogen energy combustion ratio that can be received by natural gas and pipeline equipment without safety failure. Secondly, the expected charge and discharge capacity of each link obtained in step 2) is verified: When the operation logic of step 2) does not satisfy the above solution set library, the corresponding values ​​are the upper limit values. Then, according to the upper limit values, the ideal operation logic scheme is re-formulated and iterated until the restriction conditions of the solution set library are met; Step 4) setting system optimization parameters and target values, wherein the system optimization parameters include system conversion efficiency, system power shortage rate, system initial investment, and system life cycle energy cost; Step 5) Use a single swarm intelligence algorithm or a combined algorithm to continuously iterate the optimization target until the set target value is reached, then jump out to obtain the optimization solution. If it is not reached, change the number of cycles and restart the cycle or adjust some of the restrictions set in step 2); Step 6) Obtain the multi-energy flow conversion combination optimization of electrical energy, thermal energy and hydrogen energy.

2. The multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage according to claim 1 is characterized by: The photovoltaic power generation electronic system model in step 1) is as follows: Where I is the system current, V is the system voltage, and I SC is the short-circuit current, V oc is the open circuit voltage; I m is the output current at maximum power, V m is the output voltage at the maximum power point; The wind power generation subsystem model is as follows: Among them, P wt is the system output power, V in is the system startup wind speed, V out is the system shutdown wind speed, V rs is the wind speed corresponding to the full load operation of the system, P WTd Full load operating power.

3. The multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage according to claim 1 is characterized by: The photothermal electronic system model in step 1) is as follows: Among them, P t th,SF-HTF P is the thermal power output by the heat collection module; t th ,HTF-TS P is the heat absorption power of the heat storage system of the CSP power station absorbing energy from the heat transfer medium; t th ,TS-HTF P is the heat release power of the heat storage system of the CSP power station to release energy from the heat transfer medium; t th ,HTF-PB It is the thermal power absorbed from the heat transfer fluid in the power generation process.

4. The multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage according to claim 1 is characterized by: Step 1) The model of the Zhongchu electronic system is as follows: Among them, V bat ,I bat E are the external current and voltage of the battery respectively; b is the internal electromotive force of the battery; R i is the resistance of the battery; SOC0 is the initial state of charge of the battery; P c (t) is the battery charging and discharging power, the charged state is positive; L c_0 is the rated capacity of the battery.

5. The multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage according to claim 1 is characterized by: The heat storage subsystem model in step 1) is as follows: in, E t th is the heat storage energy of the heat storage system at time t; γ is the heat dissipation coefficient; P t th ,cha , P t th ,dis are the charging / discharging power of the heat storage system at time t; Δt is the time interval; the heat storage capacity of the heat storage link is limited by the heat storage capacity, that is, , , are the upper and lower limits of the heat storage energy of the heat storage system respectively.

6. The multi-energy complementary system optimization method based on electric thermal hydrogen hybrid energy storage according to claim 1 is characterized by: The hydrogen storage subsystem model in step 1) is the hydrogen storage capacity limitation and storage-use balance.

7. The multi-energy complementary system optimization method based on electric-thermal-hydrogen hybrid energy storage according to claim 1 is characterized by: The single swarm intelligence algorithm in step 5) is a multi-objective genetic algorithm, a multi-objective particle swarm algorithm, a multi-objective ant colony algorithm, a multi-objective bee colony algorithm or a multi-objective fish swarm algorithm.

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