Two-stage optimization method for island micro-energy network considering gradient utilization of hydrogen energy

Abstract

The invention relates to an island micro-energy network two-stage optimization method considering hydrogen energy gradient utilization, which belongs to the field of comprehensive energy and comprises the following steps: constructing an island micro-energy network integrated with a hydrogen energy gradient utilization device; based on historical data of wind power, photovoltaic and photo-thermal power stations and output of energy supply equipment, storage equipment, a gas turbine and a hydrogen fuel cell of an island micro energy grid, a day-ahead stage objective function with the day-ahead market net profit maximization as an objective is constructed; solving the day-ahead objective function based on day-ahead supply and demand balance constraint, unit constraint and demand response constraint to obtain day-ahead market electricity, heat and gas transaction volume; constructing a real-time stage objective function with the minimum real-time market deviation adjustment cost of the island micro-energy grid as an objective; and solving the real-time objective function based on the real-time supply and demand balance constraint, the unit constraint, the demand response constraint, the uncertainty of supply and demand cooperation and the current electricity, heat and gas transaction volume of the market to obtain the optimal solution of the output of each unit and the reduction volume of the demand side capable of reducing the load.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy technology, and in particular to a two-stage optimization method for an island micro-energy network taking into account the cascade utilization of hydrogen energy. Background Art

[0002] As a large country with vast sea areas, my country has a large amount of exploitable energy resources in the ocean that cannot be ignored. However, due to the geographical location of most islands far away from the mainland and the imbalance between energy types and demand loads on the islands, the traditional energy supply on the islands relies on ship transportation, which is difficult to meet the growing demand for multiple types of energy on the islands. With the continuous deepening of island development and the increasing demand for electricity, heat and gas loads by residents on the islands, the self-sufficient energy supply model on the islands cannot meet the growing demand for multiple loads, so the construction of a large-scale island multi-energy microgrid cluster energy supply network is an inevitable requirement for the sustainable development of the islands.

[0003] Island areas have abundant renewable energy sources such as wind and solar energy, but these energy sources are intermittent and unstable. At present, the structure of micro-energy networks is mainly concentrated in rural areas, cities, industrial parks and other micro-energy network utilization scenarios. The devices involved mainly include wind power, photovoltaics, energy storage and demand response (a phenomenon on the user side, such as increasing electricity prices will reduce load demand, or lowering electricity prices will increase load demand, and participate in grid regulation in this way). Since islands are rich in seawater resources and sufficient light resources, the optimization of existing island micro-energy networks is the key to improving energy utilization efficiency.

[0004] At the same time, the uncertainty of the internal devices of the island micro-energy network will affect the final dispatching results. How to characterize this fluctuation factor is an important prerequisite for ensuring the safe and stable operation of the system. At present, most studies only focus on the impact of the output uncertainty of supply-side resources such as wind and solar or the uncertainty of demand-side resource load on the dispatching results of the micro-energy network, and do not maximize the mobilization of internal supply and demand resources to form an interconnected cooperation mode between the supply and demand sides to improve the energy supply reliability of the island micro-energy network. Therefore, it is urgent to propose a supply and demand cooperation operation optimization strategy.

[0005] The existing island micro-energy network does not take into account the hydrogen load demand and abundant seawater resources of the micro-energy network, and does not realize the recycling of carbon elements to reduce carbon dioxide emissions. It also fails to maximize the mobilization of internal supply and demand resources to form a supply and demand interconnection and collaboration model to improve the energy supply reliability of the island micro-energy network and meet the growing demands of various loads. Summary of the invention

[0006] In view of the above analysis, an embodiment of the present invention aims to provide a two-stage optimization method for an island micro-energy network that takes into account the cascade utilization of hydrogen energy, so as to solve the technical problems that the existing methods do not take into account the cascade utilization of island hydrogen energy and the abundance of seawater resources, and fail to maximize the mobilization of internal supply and demand resources to form an effective supply and demand interconnection and cooperation model, so as to improve the energy supply reliability of the island micro-energy network and meet the needs of various loads.

[0007] The present invention provides a two-stage optimization method for an island micro-energy network considering the cascade utilization of hydrogen energy, comprising the following steps:

[0008] Construct an island micro-energy network integrating new hydrogen energy cascade utilization devices;

[0009] Based on the historical data of wind power, photovoltaic and solar thermal power stations, as well as the output of energy supply equipment, energy storage equipment, gas turbine output and hydrogen fuel cell output of the island micro-energy network, a day-ahead objective function with the goal of maximizing the day-ahead market net profit is constructed;

[0010] Solving the objective function of the day-ahead phase based on the day-ahead supply and demand balance constraint, the day-ahead unit constraint and the demand response constraint, and obtaining the electricity, heat and gas transaction volumes in the day-ahead market;

[0011] Construct a real-time objective function with the goal of minimizing the real-time market deviation adjustment cost of the island micro-energy network;

[0012] Based on the real-time supply and demand balance constraints, real-time unit constraints, real-time demand response constraints, the uncertainty of supply and demand cooperation, and the electricity, heat and gas trading volume in the day-ahead market, the real-time stage objective function is solved to obtain the optimal solution for the output of each unit on the supply side of the island micro-energy network and the amount of load reduction on the user demand side.

[0013] Furthermore, the novel hydrogen energy cascade utilization device comprises an electrolyzer, a hydrogen storage device, a hydrogen fuel cell and a methane reactor;

[0014] The electrolyzer is used to use the surplus clean energy generated by the wind energy and photovoltaic energy units in the island micro-energy network to electrolyze seawater to obtain hydrogen and oxygen, and convert electrical energy into hydrogen energy;

[0015] The hydrogen storage device is used to store the hydrogen converted by the electrolyzer;

[0016] The hydrogen fuel cell is used to directly obtain the hydrogen converted by the electrolyzer or the hydrogen stored in the hydrogen storage device when the electricity demand on the island increases, and convert the hydrogen into electrical energy and thermal energy by reacting with oxygen;

[0017] The methane generator is used to react the hydrogen converted by the electrolyzer, or the hydrogen stored in the hydrogen storage device, with the carbon dioxide produced by the gas turbine in the cogeneration unit in the island micro-energy network to generate methane natural gas that is easy to store and transport, thereby realizing carbon circulation;

[0018] The heat energy generated by the hydrogen fuel cell is collected by the waste heat recovery device in the cogeneration unit for heat energy utilization.

[0019] Furthermore, the output of the energy supply equipment includes wind power, photovoltaic, solar thermal power station, cogeneration unit and ground source heat pump output;

[0020] The output of the energy storage equipment includes the output of electricity storage, heat storage and hydrogen storage devices.

[0021] Furthermore, the objective function of the day-ahead phase is as follows:

[0022]

[0023] Among them, F r is the net income of the island micro-energy network in the day-ahead market, α1 is the probability of exceeding the expected income, It represents the net benefit F on the supply side r Greater than expected net income The probability is greater than or equal to α1; and are the electricity, heat and gas transaction volumes in period t, respectively; and are the prices of electricity, heat and gas in period t respectively; are the operation and maintenance cost and depreciation cost of unit n at time t; T is the scheduling period; N is the number of units, The power output of device n in the island micro-energy grid during time period t; is the unit operation and maintenance cost of device n; are the outputs of wind power, photovoltaic power, solar thermal power station, cogeneration unit, ground source heat pump, power storage device, heat storage device, hydrogen storage device, gas turbine and hydrogen fuel cell unit in time period t;

[0024] The unit n is wind power, photovoltaic, new hydrogen energy cascade utilization device, cogeneration unit, power storage device, ground source heat pump, and solar thermal power station unit in the island micro-energy network;

[0025] When the net income of the island micro-energy is the largest, the utilization rates of electricity, heat and gas loads are the largest.

[0026] Furthermore, the day-ahead supply-demand balance constraint is as follows:

[0027]

[0028]

[0029] Among them, β1, β2 and β3 are the confidence levels of the balance of supply and demand of electricity, heat and gas respectively. and They are respectively the electricity, heat and gas demands of the users of the island micro-energy network at time t; and are the outputs of wind power, photovoltaic power, gas turbine, solar thermal power station and hydrogen fuel cell at time t respectively; and They are the heat output of the hydrogen storage device, hydrogen fuel cell and power heat pump respectively; are the gas load demands satisfied by the methane reactor and the external natural gas network at time t, respectively;

[0030] The day-ahead unit constraints include output constraints for wind power, photovoltaic, solar thermal power stations, power storage devices and new hydrogen energy cascade utilization devices.

[0031] Furthermore, the real-time stage objective function is as follows:

[0032]

[0033] Among them, F c is the deviation adjustment cost of the island micro-energy network in the real-time market, α2 is the probability of exceeding the expected deviation adjustment cost, Indicates that the deviation adjustment cost of the island micro-energy network is less than the expected deviation adjustment cost The probability is greater than or equal to α2, is the incentive demand response cost of the k-th load at time t; is the unit reduction penalty cost of the k-th load at time t; is the load shedding type at time t, are the types of electricity, heat and gas load shedding at time t, is the compensation price for the interruption or transfer of the kth type of load during period t, are the load transfer amounts of electricity, heat and gas in the real-time stage, l is the step scale of the k-th load, and v is the step price of the k-th load;

[0034] The k-type loads include electricity, heat and gas.

[0035] Furthermore, the real-time supply and demand balance constraint is as follows:

[0036]

[0037] Among them, β6, β7 and β8 are the confidence levels of the supply and demand balance of electricity, heat and gas in the real-time stage, which are preset values. and are the real-time electricity, heat and gas loads at time t respectively; and are the real-time electricity, heat and gas transfer loads at time t respectively; and are the uncertainty factors for electricity, heat and gas loads, respectively; They are the electricity loads satisfied by wind power, photovoltaic power, gas turbine, solar thermal power station and hydrogen fuel cell in the real-time market at time t; are the heat loads satisfied by the real-time market electricity storage device, hydrogen storage device, hydrogen fuel cell and power heat pump at time t; It is the gas load satisfied by the real-time market methane reactor at time t.

[0038] Furthermore, the real-time demand response constraints are as follows:

[0039]

[0040] in, and They are the upper and lower limits of the amount of electricity load interruption and transfer of users participating in demand response at time t, respectively; and They are the upper and lower limits of the thermal load interruption and transfer amount of users participating in demand response at time t, respectively; and are the upper and lower limits of the gas load interruption and transfer amount of users participating in demand response at time t; β9, β 10 and β 11 They are the confidence levels of electricity, heat and gas demand response in the real-time stage respectively.

[0041] Furthermore, the real-time unit constraints include real-time wind turbine unit constraints, photovoltaic unit constraints, new hydrogen energy cascade utilization device unit constraints, solar thermal power station unit constraints, gas turbine unit constraints, hydrogen fuel cell unit constraints, power storage device unit constraints, hydrogen storage device unit constraints and ground source heat pump unit constraints.

[0042] Furthermore, in addition to integrating the novel hydrogen energy cascade utilization device, the island micro-energy network also includes wind power, photovoltaic, cogeneration units, solar thermal power stations, power storage devices, ground source heat pumps, external gas networks and loads;

[0043] The cogeneration unit includes a gas turbine, a waste heat recovery device and a heat exchange device;

[0044] The solar thermal power station includes a generator, a heat collection field and a heat storage device;

[0045] The loads include electricity, heat and gas loads;

[0046] Among them, wind power, photovoltaic, solar thermal power stations, cogeneration units, and ground source heat pumps are energy supply equipment; electricity storage devices, heat storage devices, and hydrogen storage devices are energy storage equipment.

[0047] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0048] 1. The present invention constructs an island micro-energy grid structure that integrates a new type of hydrogen energy cascade utilization device, considers the uncertainty on both sides of supply and demand and the cooperation strategy on both sides of supply and demand, adds a step-type demand response price mechanism, and constructs a two-stage stochastic optimization model for supply and demand cooperation, in which the day-ahead stage takes the maximum system net profit as the objective function to obtain the planned total output; the real-time stage constructs the goal of minimizing operating costs for optimization, calls on the incremental output of the unit and the user demand response to smooth out the deviation, and finally obtains the intraday real-time optimal output plan to meet the planned total output in the day-ahead stage. The present invention aggregates the use of distributed resources, better considers the multi-type energy load demands of the micro-energy grid, better promotes the absorption of wind power and photovoltaics, and promotes the transformation of my country's power system;

[0049] 2. The present invention enhances the energy self-sufficiency of island areas by constructing a large-scale island multi-energy microgrid cluster energy supply network, reducing dependence on external energy supplies, especially for islands far from the mainland. By utilizing the abundant wind power and photovoltaic renewable energy on the islands, through the hydrogen energy cascade utilization device, the effective conversion and cascade utilization between electricity, heat and gas energy is achieved, and the comprehensive utilization efficiency of energy is improved;

[0050] 3. The present invention achieves accurate matching and interconnected collaboration between supply and demand through the two-stage optimization method of the day-ahead market and the real-time market, improves the energy supply reliability of the island micro-energy network, and meets the growing demand for multiple loads. Through the objective functions of maximizing the net profit of the day-ahead market and minimizing the deviation adjustment cost of the real-time market, the operating cost of the island micro-energy network is reduced;

[0051] 4. The present invention takes into account the uncertainty of both supply and demand, effectively copes with the volatility and uncertainty of wind power and photovoltaic new energy output, and enhances the flexibility and reliability of the system. And through the methane reactor, hydrogen and carbon dioxide react to generate methane natural gas, realizing the recycling of carbon elements, reducing carbon dioxide emissions and reducing environmental pollution. By maximizing the mobilization of internal supply and demand resources, an effective supply and demand interconnection and cooperation model is formed, which improves the energy supply security of the island micro-energy network in the face of emergencies and extreme weather;

[0052] 5. The present invention maximizes the use of wind energy and photovoltaic energy through the hydrogen energy cascade utilization device, reduces the problem of wind and photovoltaic abandonment, and promotes the consumption of renewable energy. By stably and reliably meeting the electricity, heat and gas load needs of island residents, the quality of life and comfort of island residents are improved.

[0053] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The drawings are only for the purpose of illustrating specific embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0055] Figure 1 This is a flow chart of an optimization method for island micro-energy network considering the cascade utilization of hydrogen energy;

[0056] Figure 2 This is a schematic diagram of the island micro-energy network structure;

[0057] Figure 3 This is a schematic diagram of the structure of a hydrogen energy cascade utilization device;

[0058] Figure 4 This is a schematic diagram of the ladder cost of incentive-based demand response;

[0059] Figure 5 This is a schematic diagram of an extreme scenario;

[0060] Figure 6 Schematic diagram of demand-side uncertainty. DETAILED DESCRIPTION

[0061] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0062] The present invention aims to propose a two-stage optimization method for an island micro-energy network that takes into account the cascade utilization of hydrogen energy. A new type of hydrogen energy cascade utilization device is integrated on the basis of the traditional island micro-energy network, and a new type of hydrogen energy cascade utilization device is introduced to form a new island micro-energy network system structure.

[0063] Taking the maximization of the profit in the day-ahead stage and the minimization of the cost in the intraday implementation stage as the objective function, a two-stage operation optimization model of the supply and demand cooperation of the island micro-energy network considering uncertainty was constructed, so as to maximize the mobilization of resources on both the supply and demand sides, improve the energy supply reliability of the island micro-energy network and meet various load demands.

[0064] On the basis of the traditional island micro-energy grid structure, hydrogen energy and thermal energy are rationally converted and utilized through devices such as electric hydrogen production and solar thermal power stations to achieve electric energy conversion and meet the electricity, heat and gas load demands on the demand side of island users.

[0065] like Figure 1 As shown, a specific embodiment of the present invention discloses a two-stage (day-ahead stage and real-time stage) optimization method for an island micro-energy network considering the cascade utilization of hydrogen energy, comprising the following steps:

[0066] Step S1, constructing an island micro-energy network integrating a novel hydrogen energy cascade utilization device;

[0067] Step S2: constructing a day-ahead objective function with the goal of maximizing the day-ahead market net profit based on the acquired historical data of wind power, photovoltaic and solar thermal power stations, as well as the output of energy supply equipment, energy storage equipment, gas turbine output and hydrogen fuel cell output of the island micro-energy network;

[0068] Step S3, solving the objective function of the day-ahead stage based on the day-ahead supply and demand balance constraint, the day-ahead unit constraint and the demand response constraint to obtain the electricity, heat and gas transaction volumes in the day-ahead market;

[0069] Step S4, constructing a real-time phase objective function with the goal of minimizing the real-time market deviation adjustment cost of the island micro-energy network;

[0070] Step S5, based on the real-time supply and demand balance constraints, real-time unit constraints, real-time demand response constraints, the uncertainty of supply and demand cooperation, and the electricity, heat and gas trading volume in the day-ahead market as constraints, the real-time stage objective function is solved to obtain the optimal solution for the output of each unit on the supply side of the island micro-energy network, as well as the amount of load reduction on the user demand side.

[0071] Step S1 includes steps S11-S12.

[0072] S11. Construct an island micro-energy network integrating new hydrogen energy cascade utilization devices.

[0073] Based on the traditional micro-energy network, the island micro-energy network breaks the barriers of the original devices, considers the integration of new hydrogen energy cascade utilization devices, and proposes an island micro-energy network that integrates electricity, natural gas and hydrogen energy.

[0074] In order to effectively solve the energy demand of various energy categories in island scenarios, such as Figure 2As shown, the present invention integrates an electrolysis cell EC (Electrolysis Cell), a methane reactor MR (Methanation Reactor), a hydrogen storage device HSD (Hydrogen Storage Device), and a hydrogen fuel cell HFC (Hydrogen Fuel Cell) to form a new type of hydrogen energy cascade utilization device CHUD (Cascade Hydrogen Utilization Device);

[0075] In addition to integrating the novel hydrogen energy cascade utilization device, the island micro-energy network also includes a wind power plant (WPP), a photovoltaic power plant (PV), a coupled-heating-power unit (CHP), a solar thermal power plant (STPP), a power storage device (PSD), a ground source heat pump (GSHP), an external gas network (Gas Network) and loads;

[0076] The cogeneration unit includes a gas turbine GT (Gas Turbine), a waste heat recovery device WHD (Waste Heat Recovery Device) and a heat exchange device CH (Change Heat);

[0077] The solar thermal power station includes a generator PG (Power Generator), a collector field HCF (Heating Central Field) and a heat storage device HSS (Heating Storage System);

[0078] The loads include electricity, heat and gas loads;

[0079] Among them, wind power, photovoltaic, solar thermal power stations, cogeneration units, and ground source heat pumps are energy supply equipment; electricity storage devices, heat storage devices, and hydrogen storage devices are energy storage equipment.

[0080] The load includes electricity load EL (Electricity Load), hydrogen load HL (Hydrogen Load), and gas load GL (Gas Load).

[0081] When the island micro-energy grid system is in operation, wind power, photovoltaic and solar thermal power stations meet the system's electrical and thermal load requirements. The heat is collected by the collector field, and the generator directly generates electricity to meet the electrical load EL requirements. The heat storage device is used to charge and release heat to meet the thermal and electrical load requirements, thus achieving multi-energy synergy.

[0082] By utilizing the natural gas resources on the island and using the cogeneration unit to adopt the "electricity-to-heat" approach, the gas turbine will give priority to meeting the user's electricity load demand, and the waste heat recovery device will absorb the waste heat through the waste heat boiler to meet the heat load demand; considering the incomplete matching characteristics of wind and solar power and user loads, through power storage devices, ground source heat pumps and hydrogen energy cascade utilization devices, electric energy conversion is realized to meet the electricity, heat and gas load demands.

[0083] S12. Construct a new type of hydrogen energy cascade utilization device structure.

[0084] The novel hydrogen energy cascade utilization device comprises an electrolyzer, a hydrogen storage device, a hydrogen fuel cell and a methane reactor; the energy flow relationship thereof is as follows: Figure 3 shown.

[0085] The electrolyzer is used to use the surplus clean energy generated by the wind energy and photovoltaic energy units in the island micro-energy network to electrolyze seawater to obtain hydrogen and oxygen, and convert electrical energy into hydrogen energy;

[0086] The hydrogen storage device is used to store the hydrogen converted by the electrolyzer;

[0087] The hydrogen fuel cell is used to directly obtain the hydrogen converted by the electrolyzer or the hydrogen stored in the hydrogen storage device when the electricity demand on the island increases, and convert the hydrogen into electrical energy and thermal energy by reacting with oxygen;

[0088] The methane generator is used to react the hydrogen converted by the electrolyzer, or the hydrogen stored in the hydrogen storage device, with the carbon dioxide produced by the gas turbine in the cogeneration unit in the island micro-energy network to generate methane natural gas that is easy to store and transport, thereby realizing carbon circulation;

[0089] The heat energy generated by the hydrogen fuel cell is collected by the waste heat recovery device in the cogeneration unit for heat energy utilization.

[0090] When wind power and photovoltaic clean energy units are in full swing, the electrolyzer absorbs the remaining clean energy and uses the electricity from photovoltaic and wind power to electrolyze seawater H2O to generate hydrogen H2 and oxygen O2. The hydrogen is stored in the hydrogen storage device. In order to reduce the energy loss caused by hydrogen methanation, a hydrogen fuel cell is configured to store part of the hydrogen energy. When there is a shortage of electricity, the hydrogen fuel cell is used to convert the hydrogen energy into electricity to meet the electricity load demand. Part of the hydrogen energy is generated by the methane reactor and injected into the external gas grid natural gas system to meet the gas load demand. The waste heat recovery device in the cogeneration unit is used to recover the heat generated by the methane chemical reaction to meet the heat load demand.

[0091] The electrolyzer is the starting point of the hydrogen energy cascade utilization device.

[0092] The hydrogen H2 stored in the hydrogen storage device is stored in the form of compressed hydrogen or liquefied hydrogen;

[0093] Hydrogen fuel cells, which convert the chemical energy in hydrogen back into electricity while also generating heat;

[0094] Methane reactor: Hydrogen obtained by electrolysis of water in electrolyzer EC is used for power generation. In addition, part of the hydrogen reacts with carbon dioxide CO2 in the methane reactor to generate methane CH4. This process is called methanation, which converts hydrogen into a natural gas form that is easy to store and transport.

[0095] By utilizing the waste heat recovery device in the cogeneration unit, the heat energy generated in the hydrogen fuel cell HFC and the methane reactor MR is collected by the waste heat recovery device, and the heat energy is used for heating, hot water or industry to meet the heat demand on the island demand side and improve energy utilization efficiency.

[0096] Design objectives of the new hydrogen energy cascade utilization device:

[0097] (1) Maximize the utilization efficiency of clean energy (photovoltaic and wind power) and reduce the waste of wind and solar power;

[0098] (2) Providing flexible energy supply and utilization to cope with the intermittency and instability of renewable energy;

[0099] (3) Through the methanation process, hydrogen is converted into a natural gas energy form that is easier to store and transport;

[0100] (4) Through the waste heat recovery device, the comprehensive utilization efficiency of energy can be improved and the overall energy consumption of the system can be reduced.

[0101] The hydrogen production link, hydrogen-to-electricity-heat link and hydrogen-to-methane link of the hydrogen energy cascade utilization device are introduced respectively, as follows:

[0102] (1) Hydrogen production

[0103] The electrolyzer is the first link in the new hydrogen energy cascade utilization device. It converts electrical energy (electricity provided by photovoltaic and wind power) into hydrogen energy to achieve electricity-hydrogen conversion. Its input-output model is as follows:

[0104]

[0105] in, and are the hydrogen power output from the electrolyzer and the electrical power input to the electrolyzer, respectively, EC , b EC and c EC They are the quadratic term coefficient, linear term coefficient and constant term coefficient of the electrolysis efficiency function, which affect the electrolysis efficiency and energy conversion process; is the rated power of the electrolytic cell, η EC is the water electrolysis efficiency of the electrolyzer.

[0106] The input of the electrolyzer is electricity provided by photovoltaic and wind power, as well as seawater, and the output of electrolysis is hydrogen and oxygen.

[0107] The hydrogen produced by the electrolysis cell is transported to a hydrogen storage device for storage, and is also transported to a methane reactor for methanation.

[0108] The hydrogen production process realizes efficient and reliable hydrogen production and storage, as well as methanation to generate methane, providing a basis for subsequent hydrogen energy utilization links (such as hydrogen-to-electricity-heat and hydrogen-to-methane).

[0109] (2) Hydrogen-to-Electrical-Heat Link

[0110] When the island's electricity demand increases, the hydrogen in the hydrogen storage device is sent to the hydrogen fuel cell HFC, which reacts the hydrogen with oxygen to convert it into electrical energy and heat energy.

[0111] Hydrogen fuel cells realize the conversion between hydrogen energy and electrical energy and thermal energy, and realize the conversion between hydrogen-electricity and hydrogen-thermal energy. The conversion efficiency is approximately regarded as a constant, and its input-output model is as follows:

[0112]

[0113] Among them, P t HFC is the total power of the hydrogen fuel cell at time t, is the hydrogen power input to the hydrogen fuel cell by the hydrogen storage device HSD at time t, and are the electrical and thermal power output by the hydrogen fuel cell HFC at time t respectively; and They are the electrical and thermal power conversion efficiencies of hydrogen fuel cells HFC; is the maximum value of the total thermoelectric efficiency; aHFC , b HFC 、c HFC ,d HFC 、e HFC and f HFC are the first, second, third, fourth and fifth electric power efficiency function coefficients respectively; Rated electrical output power of hydrogen fuel cell HFC.

[0114] (3) Hydrogen to methane

[0115] The methane reactor uses part of the hydrogen converted by the electrolyzer EC to react with CO2 to achieve hydrogen methanation and hydrogen-natural gas conversion. Its input-output model is as follows:

[0116]

[0117] in, is the methane gas power output by the methane reactor MR at time t, is the hydrogen power input to the methane reactor at time t, η MR is the methanation efficiency of the methane reactor MR.

[0118] Step S2 includes steps S21-S24.

[0119] S21. Obtain historical data of wind power, photovoltaic and solar thermal power stations, and model the output of energy functional equipment and energy storage equipment of the island micro-energy network.

[0120] The output of the energy supply equipment includes wind power, photovoltaic, solar thermal power stations, cogeneration units and ground source heat pump output.

[0121] Energy supply equipment mainly consists of wind turbines, photovoltaic units, solar thermal power station units, and cogeneration units. The output modeling is as follows:

[0122] (1) Wind turbine output model

[0123] Wind speed affects the output of wind turbines. Since wind speed is affected by natural conditions and fluctuates, the output of wind turbines is uncertain. The linkage relationship between wind turbine output and wind speed is shown in formula (4):

[0124]

[0125] in, represents the power of wind power generation at time t; v t represents the wind speed at time t, in m / s; v in and v out Indicates the cut-in wind speed and cut-out wind speed of the fan; v cis the rated wind speed. When the rated wind speed is reached and the wind turbine is operating safely, the wind turbine is c Perform rated output.

[0126] The wind speed is represented by the Weibull distribution function, as shown in formula (5):

[0127]

[0128] Among them, v t is the wind speed at time t; c and k are the scale parameter and state parameter of Weibull distribution respectively.

[0129] (2) Photovoltaic unit output model

[0130] The intensity of solar radiation affects the output of photovoltaic units. Since the intensity of solar radiation is affected by natural conditions and is volatile, the output of photovoltaic units is uncertain.

[0131] The linkage relationship between the output of photovoltaic units and the solar radiation intensity is shown in formula (6):

[0132]

[0133] in, is the output of the photovoltaic unit at time t; η PV Power conversion efficiency for photovoltaic units; S PV is the solar radiation area; θ t is the solar radiation intensity at moment t.

[0134] The solar radiation intensity is described by the beta distribution function, as shown in formula (7):

[0135]

[0136] Among them, θ t is the solar radiation intensity at time t, r and r max are the solar irradiance and maximum irradiance at moment t respectively; α and β are the first and second shape parameters of Beta distribution respectively, which are estimated based on historical data or weather forecasts.

[0137] (3) CSP power station output model

[0138] CSP power stations absorb solar radiation energy through a solar collector field (HCF) and convert it into heat energy, which is then used for power generation or storage.

[0139] This part of thermal energy can be used to generate electricity through a generator or stored in a heat storage device; when needed, it can be released to generate electricity.

[0140] The power supply of a solar thermal power station is similar to that of a photovoltaic unit. Both are affected by the randomness of solar radiation, and the output is also uncertain. The solar radiation beta distribution model refers to formula (7), and the collector power model of the collector field is further obtained, as shown in formula (8):

[0141]

[0142] in, is the heat collection capacity of the CSP power station STPP at time t; η STPP is the light-to-heat conversion efficiency of the solar thermal field HCF; S STPP is the area of ​​the solar thermal field.

[0143] Based on the collected heat, the power supply and heat storage model of the solar thermal power station is obtained.

[0144] The power supply model of the generator set is shown in formula (9):

[0145]

[0146] in, is the power supply of the CSP power station STPP at time t; The power generation efficiency of the STPP generator set of the CSP power station; It is the heat used for power generation by the CSP power station STPP at time t.

[0147] Provided by solar thermal field, or by heat storage device;

[0148] The heat storage model of the heat storage device is shown in formula (10):

[0149]

[0150] in, and are the heat storage capacity of the energy storage device HSS at time t and t-1 respectively; is the heat storage loss rate; ζ is the state variable, when it is equal to 1, it is in the heat release state; and are the charging and discharging powers of the heat storage equipment at time t respectively; and are the charging and discharging efficiencies of the heat storage equipment respectively.

[0151] (4) CHP output model of cogeneration unit

[0152] The combined heat and power unit includes a gas turbine, a waste heat recovery device, and a heat exchange device. Its output model is shown in formula (11):

[0153]

[0154] in, is the power supply of the CHP unit at the tth moment; V t CHP,g is the amount of natural gas consumed at time t; η CHP is the power generation efficiency of the combined heat and power unit CHP; is the waste heat power of CHP power generation of the cogeneration unit at the tth moment; γ GT is the thermoelectric ratio; is the waste heat entering the heat exchange device CH; η WHB,t is the percentage of the heat entering the heat exchange device CH from the waste heat recovery device WHD at the tth moment to the total heat of WHD at the tth moment; η h is the heat transfer efficiency of the heat exchange device CH.

[0155] (5) Ground source heat pump output model

[0156] A ground-source heat pump uses the earth as a source of heat and cold, driven by high-quality energy. In winter, it extracts heat from the ground or water and transfers it to the interior of a building for heating. In summer, it releases heat from the interior of a building into the ground or surface water for cooling.

[0157] Among them, high-quality energy is a form of energy with high energy quality, high conversion efficiency, and easy control and utilization. Electricity is a typical high-quality energy.

[0158] Air source heat pumps for cooling refer to using the heat in the air as a low-temperature heat source, driven by high-quality energy (electricity), exchanging heat through the air conditioner condenser or evaporator, and then extracting or releasing heat energy through the circulation system to meet the user's heat load requirements; ground source heat pumps refer to using water bodies (groundwater, rivers, lakes and oceans on the surface) as cold and heat sources, driven by high-quality energy (electricity), to achieve the transfer of low-temperature heat energy to high-temperature heat energy, and achieve winter heating and summer heating. The output model of ground source heat pumps is shown in formula (12):

[0159]

[0160] in, is the energy supply power of the ground source heat pump unit at time t; COP HP is the electricity-heat and electricity-cold conversion efficiency of the ground source heat pump unit; g GSHP,t It is the amount of high-quality energy entering the ground source heat pump unit at time t.

[0161] The output of the energy storage equipment includes the output of electricity storage, heat storage and hydrogen storage devices.

[0162] Energy storage equipment stores the energy during the peak output period of the unit and releases the stored energy during the peak energy consumption period, thereby reducing the wasted energy during the peak output period and increasing the energy demand on the load side during the peak energy consumption period.

[0163] Energy storage equipment, including electricity storage devices, heat storage devices, and hydrogen storage devices, has a general output model as shown in formula (13):

[0164]

[0165] in, and are the energy storage capacity of the energy storage device at time t and time t-1 respectively; P t esc and P t esd are the charging and discharging power of the energy storage device at time t; η esc and η esd are the charging and discharging efficiencies of energy storage devices, respectively; is the energy storage loss rate of the energy storage device; ζ is the state variable of the energy storage device at the tth moment, which takes 0 or 1. When ζ=1, it is the energy storage state, and when ζ=0, it is the energy release state.

[0166] The constraints of the general model of energy storage device output are shown in formulas (14)-(16):

[0167]

[0168] in, is the maximum storage capacity of the energy storage device; and are the maximum storage and release powers of the energy storage device respectively.

[0169] The island micro-energy grid with integrated hydrogen energy cascade utilization device uses new energy to generate electricity (wind power and photovoltaic power) and electrolyzers to electrolyze seawater resources during peak hours to produce hydrogen, which reacts with the carbon dioxide produced by the gas turbine GT to generate methane, realizing carbon recycling, reducing carbon dioxide emissions, improving energy utilization, and reducing wind and solar power abandonment.

[0170] For the island micro-energy grid, it is internally coupled with wind power, photovoltaic and other clean energy units with strong uncertainty, and lacks the backup of the main grid, which poses a strong energy supply risk. How to maximize the mobilization of internal supply and demand resources and form a supply and demand interconnection and collaboration model to improve the reliability of the island micro-energy grid's energy supply.

[0171] The present invention designs a supply-demand interconnection collaboration model based on the demand-side response method, which is as follows:

[0172] (1) In the market today, based on the electricity load data on the demand side, the energy supply side predicts the energy supply capacity of its own new energy generators, takes into account the user load demand elasticity coefficient, introduces price-based demand response, guides users to reasonably transfer their energy demand, determines the total energy supply with the demand side, arranges the generator scheduling plan with maximum profit, and meets the energy demand of the demand side the next day.

[0173] Among them, the day-ahead market price energy demand response model is shown in formula (17):

[0174]

[0175] in, is the load transfer amount of the kth type affected by price-based demand response in the tth period, is the original load of the kth category in the tth period, is the elasticity coefficient of the k-th load at the i-th moment to the electricity price at the j-th moment, which is used to measure the sensitivity of the load to the change of electricity price. is the price after demand response of type k load price type in period t, is the original selling price of type k load in period t.

[0176] For the island micro-energy grid structure, the K-type loads include electricity, heat and gas.

[0177] (2) In the real-time market, the energy supply side, based on the total demand on the demand side and the real-time prediction of the energy supply capacity of its own new energy generators, takes the minimum load shedding cost as the goal, considers the maximum and minimum load reduction on the demand side, and introduces incentive energy demand response to guide the demand side to make load interruption strategies. The real-time market incentive energy demand response model is shown in formula (18):

[0178]

[0179] in, is the total amount of load reduction of the kth type affected by the incentive-based demand response in the tth period, is the amount of load reduction that can be achieved for the kth type of load in the tth period.

[0180] The "target of minimizing load shedding costs" mentioned in the real-time market means that the energy supply side strives to minimize the costs of load shedding measures required to cope with power shortages or excess demand while meeting the supply and demand balance.

[0181] Load reduction costs: When electricity supply cannot meet demand, the supply side needs to take measures to reduce some of the demand, such as reducing the power consumption of a certain type of load on the demand side through demand response. This load reduction may incur costs, especially when a quick response is required during peak demand periods.

[0182] Optimization goal: The goal of the energy supply side is to minimize the energy supply cost while ensuring the stable and reliable operation of the island micro-energy grid.

[0183] Supply and demand balance: The energy supply side needs to monitor the supply and demand situation in real time and take measures when necessary, such as adjusting power generation, starting backup power sources, or implementing demand response, to maintain the supply and demand balance.

[0184] Incentive demand response: The supply side can introduce incentives to encourage the demand side to voluntarily reduce electricity consumption when electricity supply is tight. This incentive can reduce the cost of load shedding.

[0185] System stability: The ultimate goal is to minimize costs without sacrificing stability and reliability, ensuring that all users on the island micro-energy demand side have access to the electricity they need.

[0186] Demand response is classified into the day-ahead stage and the real-time stage. In the day-ahead stage, the transferable load of price-based demand response is considered, and in the real-time stage, the interruptible load of incentive-based demand response is considered, so as to fully tap the adjustable potential of demand response and ensure flexible, safe and stable operation of the power system.

[0187] Step S22: construct a day-ahead objective function with the goal of maximizing the day-ahead market net profit.

[0188] The two-stage optimization of supply and demand cooperation is divided into the day-ahead supply and demand cooperation pre-scheduling stage and the real-time supply and demand cooperation emergency balance stage. According to the operation optimization strategy, the supply and demand parties match supply and demand in the day-ahead market to form a supply and demand curve.

[0189] The present invention starts from the supply side, optimizes the output of internal resources of the island micro-energy network, takes the maximization of its revenue in the day-ahead market as the day-ahead stage objective function, and aims to maximize the net revenue of the island micro-energy network.

[0190] The objective function of the day-ahead phase is as shown in formula (19):

[0191]

[0192] Among them, F r is the net income of the island micro-energy network in the day-ahead market, α1 is the probability of exceeding the expected income, It represents the net benefit F on the supply side r Greater than expected net income The probability is greater than or equal to α1; and are the electricity, heat and gas transaction volumes in period t, respectively; and are the prices of electricity, heat and gas in period t respectively; are the operation and maintenance cost and depreciation cost of unit n at time t; T is the scheduling period; N is the number of units, The power output of device n in the island micro-energy grid during time period t; is the unit operation and maintenance cost of device n; are the outputs of wind power, photovoltaic power, solar thermal power station, cogeneration unit, ground source heat pump, power storage device, heat storage device, hydrogen storage device, gas turbine and hydrogen fuel cell unit in time period t;

[0193] The unit n is wind power, photovoltaic, new hydrogen energy cascade utilization device, cogeneration unit, power storage device, ground source heat pump, and solar thermal power station equipment in the island micro-energy network;

[0194] When the net income of the island micro-energy is the largest, the utilization rates of electricity, heat and gas loads are the largest.

[0195] T is the scheduling period. If one day is the scheduling period and 1 hour is the scheduling interval, then T=24.

[0196] Among them, the depreciation cost of unit n at time t is shown in formula (20):

[0197]

[0198] Among them, C ii-n , C re-n and D n are the investment cost, residual value and service life of equipment n respectively.

[0199] The operation and maintenance cost of unit n at time t is shown in formula (21):

[0200]

[0201] Among them, P t n is the unit output of unit n at time t; is the unit operation and maintenance cost of unit n.

[0202] Step S3 includes steps S31-S32.

[0203] Step S31, constructing the day-ahead supply-demand balance constraint, the day-ahead unit constraint and the day-ahead demand response constraint.

[0204] (1) Establish a day-ahead supply-demand balance constraint.

[0205] The day-ahead supply-demand balance constraint is as shown in formulas (22)-(24):

[0206]

[0207] Among them, β1, β2 and β3 are the confidence levels of the balance of supply and demand of electricity, heat and gas respectively. and They are respectively the electricity, heat and gas demands of the users of the island micro-energy network at time t; and are the outputs of wind power, photovoltaic power, gas turbine, solar thermal power station and hydrogen fuel cell at time t respectively; and They are the heat output of the hydrogen storage device, hydrogen fuel cell and power heat pump respectively; are the gas load demands satisfied by the methane reactor and the external natural gas network at time t respectively.

[0208] (2) Construct the day-ahead unit constraints.

[0209] The day-ahead unit constraints include output constraints for wind power, photovoltaic, solar thermal power stations, power storage devices and new hydrogen energy cascade utilization devices.

[0210] Wind and solar power output constraints: Based on the modeling of wind turbines and photovoltaic units, the constraints are shown in formulas (25)-(26):

[0211]

[0212] in, and are the maximum operating powers of wind power WPP and photovoltaic PV, respectively; β4 and β5 represent the confidence levels of formula (25) and formula (26), respectively.

[0213] STPP constraints of CSP plants: This invention assumes that the heat energy collected by STPP can only be provided by the collector field HCF, and the heat storage equipment model is as shown in formula (27):

[0214]

[0215] in, and are the heat storage at time t and time t-1 respectively; is the heat storage loss rate; ζ is the state variable, when it is equal to 1, it is in the heat release state; and are the charging and discharging powers of the heat storage equipment at time t respectively; and are the charging and discharging efficiencies of the heat storage equipment respectively.

[0216] Based on the STPP model of CSP power station, the unit constraint conditions are obtained as shown in formula (28):

[0217]

[0218] in, and Represent the maximum charge / discharge power of STPP, GT, HFC, PSD, HSD and GSHP respectively.

[0219] The constraints of the electrolytic cell unit are shown in formula (29):

[0220]

[0221] in, and The upper and lower limits of the input power of the electrolytic cell.

[0222] The maximum storage capacity, maximum charging power and discharge power constraints of the CSP power station STPP are shown in formula (30):

[0223]

[0224] Where β8 is the confidence level of formula (30); and They are respectively the maximum storage capacity, maximum charging power and discharge power of the CSP station.

[0225] In addition, the output and constraints of the energy storage unit refer to models (27) and (30) respectively.

[0226] Constraints of hydrogen energy cascade utilization device units: Based on the modeling of hydrogen energy cascade utilization devices, the constraints are shown in formula (31):

[0227]

[0228] in, is the amount of hydrogen input into the hydrogen fuel cell HFC at time t; is the amount of hydrogen input into the methane reactor MR at time t; It represents the amount of hydrogen input into the electrolyzer EC at time t; and The upper and lower limits of the input power of the electrolytic cell EC, and The upper and lower limits of hydrogen gas input to the hydrogen fuel cell HFC, and These are the upper and lower limits of hydrogen input into the methane reactor MR.

[0229] (3) Construct day-ahead market demand response constraints.

[0230]

[0231] in, and They are respectively the energy consumption costs of users before and after the implementation of price-based demand response in the day-ahead market at time t.

[0232] The peak-valley electricity price inversion constraint is shown in formula (34):

[0233]

[0234] in, and They are respectively the peak energy selling price and valley energy selling price of the kth type of load after the implementation of price-based demand response in the day-ahead market.

[0235] Step S32, solving the objective function of the day-ahead phase.

[0236] Based on the day-ahead supply and demand balance constraint, the day-ahead unit constraint and the demand response constraint, the day-ahead phase objective function is solved using the solver CPLEX to obtain the electricity, heat and gas transaction volumes in the day-ahead market;

[0237] Based on the historical data of wind power, photovoltaic and solar thermal power stations, the scenario generation method is used to generate typical daily scenarios for the island micro-energy network. The typical daily scenarios and the parameter data of each unit are input as original data to solve the objective function of the day-ahead stage.

[0238] Step S4, specifically.

[0239] Since there are certain uncertainties on both the supply and demand sides, in order to reduce the impact of the deviations on the scheduling strategy during the implementation phase, a real-time objective function is constructed in the real-time market with the goal of minimizing the deviation adjustment cost.

[0240] The real-time objective function is shown in formula (35):

[0241]

[0242] Among them, F c is the deviation adjustment cost of the island micro-energy network in the real-time market, α2 is the probability of exceeding the expected deviation adjustment cost, Indicates that the deviation adjustment cost of the island micro-energy network is less than the expected deviation adjustment cost The probability is greater than or equal to α2, is the incentive demand response cost of the k-th load at time t; is the unit reduction penalty cost of the k-th load at time t; is the load shedding type at time t, are the types of electricity, heat and gas load shedding at time t, is the compensation price for the interruption or transfer of the kth type of load during period t, are the load transfer amounts of electricity, heat and gas in the real-time stage, l is the step scale of the k-th load, and v is the step price of the k-th load;

[0243] Among them, the k-type loads are electricity, heat and gas loads.

[0244] like Figure 4 As shown, the ladder price is expressed as a ladder-type charge according to the interval, which shows the relationship between the load reduction amount and the incentive price. In the [0, l] segment, the incentive price at this time is The incentive price in the interval [l,2l] is The larger the load involved in the response, the higher the unit cost.

[0245]

[0246] in, The electricity load demand of the user after the supply and demand cooperation in the real-time market at time t; is the market contract volume before time t; The amount of electrical load that can be reduced in real time at time t; is the uncertainty factor; is the real-time load shedding at time t; the superscript r is the real-time load satisfied by the market at time t; They are the actual outputs of wind power WPP, photovoltaic PV and solar thermal power station STPP in the real-time stage; They are the real-time electrical output of the gas turbine GT and the hydrogen fuel cell HFC at time t.

[0247] Step S5 includes steps S51-S53.

[0248] Step S51: construct real-time supply and demand balance constraints, real-time unit constraints, and real-time demand response constraints.

[0249] (1) Establish real-time supply and demand balance constraints.

[0250] The real-time supply and demand balance constraint is shown in formulas (37)-(39):

[0251]

[0252] Among them, β6, β7 and β8 are the confidence levels of the supply and demand balance of electricity, heat and gas in the real-time stage, which are preset values. and are the real-time electricity, heat and gas loads at time t respectively; and are the real-time electricity, heat and gas transfer loads at time t respectively; and are the uncertainty factors for electricity, heat and gas loads, respectively; They are the electricity loads satisfied by wind power, photovoltaic power, gas turbine, solar thermal power station and hydrogen fuel cell in the real-time market at time t; are the heat loads satisfied by the real-time market electricity storage device, hydrogen storage device, hydrogen fuel cell and power heat pump at time t; It is the gas load satisfied by the real-time market methane reactor at time t.

[0253] (2) Construct real-time demand response constraints.

[0254] The real-time demand response constraint is shown in formula (40):

[0255]

[0256] in, and They are the upper and lower limits of the amount of electricity load interruption and transfer of users participating in demand response at time t, respectively; and They are the upper and lower limits of the thermal load interruption and transfer amount of users participating in demand response at time t, respectively; and are the upper and lower limits of the gas load interruption and transfer amount of users participating in demand response at time t; β9, β 10 and β 11 They are the confidence levels of electricity, heat and gas demand response in the real-time stage respectively.

[0257] (3) Building real-time unit constraints

[0258] The real-time unit constraints include real-time wind turbine unit constraints, photovoltaic unit constraints, new hydrogen energy cascade utilization device unit constraints, solar thermal power station unit constraints, gas turbine unit constraints, hydrogen fuel cell unit constraints, power storage device unit constraints, hydrogen storage device unit constraints and ground source heat pump unit constraints.

[0259] Wind and solar power output constraints: Based on the modeling of wind turbines and photovoltaic units, the constraints are shown in formulas (41)-(42):

[0260]

[0261] where β 12 and β 13 They represent the confidence of formula (41) and formula (42) respectively.

[0262] In addition, the output of the remaining units in the island micro-energy grid should be less than their maximum output constraints, as shown in formula (42):

[0263]

[0264] in, and These are the maximum output limits of STPP, GT, HFC, PSD, HSD and GSHP respectively.

[0265] The output constraint of the electrolyzer of the hydrogen energy cascade utilization device is as shown in formula (43):

[0266]

[0267] Step S52: uncertainty modeling of both supply and demand sides.

[0268] The uncertainty in the present invention comes from the supply side and the demand side. The uncertainty on the supply side and the demand side are modeled below respectively.

[0269] (1) Supply-side uncertainty modeling.

[0270] Wind power, photovoltaic and solar thermal power stations are affected by the natural environment, and their output has a certain degree of uncertainty, which can be expressed by extreme scenarios, such as Figure 5 shown.

[0271] Extreme scenarios refer to the maximum or minimum output scenarios of wind power, photovoltaic, and solar thermal power stations, which can be calculated from historical data. The predicted outputs of wind power, photovoltaic, and solar thermal power stations need to be between their respective maximum output scenarios and minimum output scenarios. Therefore, the uncertainty of the power output of wind power, photovoltaic, and solar thermal power stations is modeled as shown in formulas (44)-(46):

[0272]

[0273] in, and are the actual outputs of wind power, photovoltaic and solar thermal power stations at time t respectively; and They represent the minimum and maximum output of wind power at time t respectively; and They represent the minimum and maximum output of photovoltaic power at time t respectively; and They represent the minimum output and maximum output of the CSP station at time t respectively.

[0274] Then, the uncertain set of output scenarios is converted into the following form, as shown in formulas (47)-(49):

[0275]

[0276] in, and They are the output fluctuation rates of wind power, photovoltaic power and solar thermal power stations respectively; and They are the output forecast values ​​of wind power, photovoltaic power and solar thermal power stations respectively; and They are the output errors of wind power, photovoltaic and solar thermal power stations respectively, and the output errors can be obtained through extreme scenarios.

[0277] Extreme scenarios refer to the uncertainty of the output of clean energy units such as wind power, photovoltaic and solar thermal power stations on the supply side, which may be affected by the natural environment. Extreme scenarios are used to represent the possible maximum or minimum output scenarios of these energy units, which can be calculated through historical data. Specifically, the predicted output of wind power, photovoltaic and solar thermal power stations needs to be between their respective maximum output scenarios and minimum output scenarios.

[0278] (2) Demand-side uncertainty modeling.

[0279] The demand side is affected by many factors such as the natural environment. When the supply side cooperates in the energy transfer response, there are two scenarios: over-response and under-response. Its essence is to use price signals or incentives to make users increase or reduce their electricity load, thereby playing a regulatory role. However, in the actual operation of the power grid, only a basic prediction of the adjustable load can be made. The specific adjustable load also needs to be determined by many factors such as the natural environment and the user's willingness to use energy. Therefore, the present invention adds uncertainty modeling on the demand side. and like Figure 6 as shown in order to quantify demand-side uncertainty.

[0280] Demand side uncertainty, as shown in formulas (50)-(51):

[0281]

[0282] in, and are the load demands of the kth type of load demand response after implementation time t in the day-ahead market and the real-time market respectively; and are the original load amounts of the k-th load demand response at time t in the day-ahead market and the real-time market respectively; is the deviation of price-based demand response at time t; is the deviation of the incentive demand response at time t.

[0283] The purpose of this step is to model the uncertainty of wind power, photovoltaic, and solar thermal power stations on the supply side and the demand response on the demand side, so that in the subsequent stochastic optimization model, the impact of uncertainty on both sides of supply and demand on the two-stage scheduling strategy of supply and demand cooperation can be reduced.

[0284] Step S53, solving the real-time stage objective function to obtain the optimal solution for the output of each unit on the supply side of the island micro-energy network and the amount of load reduction that can be reduced on the user demand side.

[0285] Based on the real-time supply and demand balance constraints, real-time unit constraints, real-time demand response constraints, the uncertainty of supply and demand cooperation, and the electricity, heat and gas trading volumes in the day-ahead market, the CPLEX solver is used to solve the real-time stage objective function.

[0286] The typical daily scenario with the largest fluctuation value is selected as the uncertainty factor to deal with the uncertainty of opportunity constraints. Based on extreme scenarios, an uncertainty set is constructed, and the real-time wind power, photovoltaic and solar thermal power station data, as well as the demand-side load data are determined to solve the real-time objective function.

[0287] Finally, the optimal operation strategy of the island micro-energy network in the real-time stage and the amount of load that can be reduced in the real-time stage are solved.

[0288] In summary, the two-stage optimization method of the island micro-energy network considering the cascade utilization of hydrogen energy according to the embodiment of the present invention has the following beneficial effects:

[0289] 1. The present invention constructs an island micro-energy grid structure that integrates a new type of hydrogen energy cascade utilization device, considers the uncertainty on both sides of supply and demand and the cooperation strategy on both sides of supply and demand, adds a step-type demand response price mechanism, and constructs a two-stage stochastic optimization model for supply and demand cooperation, in which the day-ahead stage takes the maximum system net profit as the objective function to obtain the planned total output; the real-time stage constructs the goal of minimizing operating costs for optimization, calls on the incremental output of the unit and the user demand response to smooth out the deviation, and finally obtains the intraday real-time optimal output plan to meet the planned total output in the day-ahead stage. The present invention aggregates the use of distributed resources, better considers the multi-type energy load demands of the micro-energy grid, better promotes the absorption of wind power and photovoltaics, and promotes the transformation of my country's power system;

[0290] 2. The present invention enhances the energy self-sufficiency of island areas by constructing a large-scale island multi-energy microgrid cluster energy supply network, reducing dependence on external energy supplies, especially for islands far from the mainland. By utilizing the abundant wind power and photovoltaic renewable energy on the islands, through the hydrogen energy cascade utilization device, the effective conversion and cascade utilization between electricity, heat and gas energy is achieved, and the comprehensive utilization efficiency of energy is improved;

[0291] 3. The present invention achieves accurate matching and interconnected collaboration between supply and demand through the two-stage optimization method of the day-ahead market and the real-time market, improves the energy supply reliability of the island micro-energy network, and meets the growing demand for multiple loads. Through the objective functions of maximizing the net profit of the day-ahead market and minimizing the deviation adjustment cost of the real-time market, the operating cost of the island micro-energy network is reduced;

[0292] 4. The present invention takes into account the uncertainty of both supply and demand, effectively copes with the volatility and uncertainty of wind power and photovoltaic new energy output, and enhances the flexibility and reliability of the system. And through the methane reactor, hydrogen and carbon dioxide react to generate methane natural gas, realizing the recycling of carbon elements, reducing carbon dioxide emissions and reducing environmental pollution. By maximizing the mobilization of internal supply and demand resources, an effective supply and demand interconnection and cooperation model is formed, which improves the energy supply security of the island micro-energy network in the face of emergencies and extreme weather;

[0293] 5. The present invention maximizes the use of wind energy and photovoltaic energy through the hydrogen energy cascade utilization device, reduces the problem of wind and photovoltaic abandonment, and promotes the consumption of renewable energy. By stably and reliably meeting the electricity, heat and gas load requirements of island residents, the quality of life and comfort of island residents are improved.

[0294] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A two-stage optimization method for island micro-energy network considering the cascade utilization of hydrogen energy, characterized in that: The steps include: Construct an island micro-energy network integrating new hydrogen energy cascade utilization devices; Based on the historical data of wind power, photovoltaic and solar thermal power stations, as well as the output of energy supply equipment, energy storage equipment, gas turbine output and hydrogen fuel cell output of the island micro-energy network, a day-ahead objective function with the goal of maximizing the day-ahead market net profit is constructed; Solving the objective function of the day-ahead phase based on the day-ahead supply and demand balance constraint, the day-ahead unit constraint and the demand response constraint, and obtaining the electricity, heat and gas transaction volumes in the day-ahead market; Construct a real-time objective function with the goal of minimizing the real-time market deviation adjustment cost of the island micro-energy network; Based on the real-time supply and demand balance constraints, real-time unit constraints, real-time demand response constraints, the uncertainty of supply and demand cooperation, and the electricity, heat and gas trading volume in the day-ahead market, the real-time stage objective function is solved to obtain the optimal solution for the output of each unit on the supply side of the island micro-energy network and the amount of load reduction on the user demand side.

2. The method according to claim 1, characterized in that: The novel hydrogen energy cascade utilization device comprises an electrolyzer, a hydrogen storage device, a hydrogen fuel cell and a methane reactor; The electrolyzer is used to use the surplus clean energy generated by the wind energy and photovoltaic energy units in the island micro-energy network to electrolyze seawater to obtain hydrogen and oxygen, and convert electrical energy into hydrogen energy; The hydrogen storage device is used to store the hydrogen converted by the electrolyzer; The hydrogen fuel cell is used to directly obtain the hydrogen converted by the electrolyzer or the hydrogen stored in the hydrogen storage device when the electricity demand on the island increases, and convert the hydrogen into electrical energy and thermal energy by reacting with oxygen; The methane generator is used to react the hydrogen converted by the electrolyzer, or the hydrogen stored in the hydrogen storage device, with the carbon dioxide produced by the gas turbine in the cogeneration unit in the island micro-energy network to generate methane natural gas that is easy to store and transport, thereby realizing carbon circulation; The heat energy generated by the hydrogen fuel cell is collected by the waste heat recovery device in the cogeneration unit for heat energy utilization.

3. The method according to claim 1, characterized in that: The output of the energy supply equipment includes wind power, photovoltaic, solar thermal power stations, cogeneration units and ground source heat pump output; The output of the energy storage equipment includes the output of electricity storage, heat storage and hydrogen storage devices.

4. The method according to claim 3, characterized in that: The objective function of the day-ahead phase is as follows: Among them, F r is the net income of the island micro-energy network in the day-ahead market, α1 is the probability of exceeding the expected income, It represents the net benefit F on the supply side r Greater than expected net income The probability is greater than or equal to α1; and are the electricity, heat and gas transaction volumes in period t, respectively; and are the prices of electricity, heat and gas in period t respectively; are the operation and maintenance cost and depreciation cost of unit n at time t; T is the scheduling period; N is the number of units, The power output of device n in the island micro-energy grid during time period t; is the unit operation and maintenance cost of device n; are the outputs of wind power, photovoltaic power, solar thermal power station, cogeneration unit, ground source heat pump, power storage device, heat storage device, hydrogen storage device, gas turbine and hydrogen fuel cell unit in time period t; The unit n is wind power, photovoltaic, new hydrogen energy cascade utilization device, cogeneration unit, power storage device, ground source heat pump, and solar thermal power station unit in the island micro-energy network; When the net income of the island micro-energy is the largest, the utilization rates of electricity, heat and gas loads are the largest.

5. The method according to claim 3, characterized in that: The day-ahead supply and demand balance constraint is as follows: Among them, β1, β2 and β3 are the confidence levels of the balance of supply and demand of electricity, heat and gas respectively. and They are respectively the electricity, heat and gas demands of the users of the island micro-energy network at time t; and are the outputs of wind power, photovoltaic power, gas turbine, solar thermal power station and hydrogen fuel cell at time t respectively; and They are the heat output of the hydrogen storage device, hydrogen fuel cell and power heat pump respectively; are the gas load demands satisfied by the methane reactor and the external natural gas network at time t, respectively; The day-ahead unit constraints include output constraints for wind power, photovoltaic, solar thermal power stations, power storage devices and new hydrogen energy cascade utilization devices.

6. The method according to claim 1, characterized in that: The real-time stage objective function is as follows: Among them, F c is the deviation adjustment cost of the island micro-energy network in the real-time market, α2 is the probability of exceeding the expected deviation adjustment cost, Indicates that the deviation adjustment cost of the island micro-energy network is less than the expected deviation adjustment cost The probability is greater than or equal to α2, is the incentive demand response cost of the k-th load at time t; is the unit reduction penalty cost of the k-th load at time t; is the load shedding type at time t, are the types of electricity, heat and gas load shedding at time t, is the compensation price for the interruption or transfer of the kth type of load during period t, are the load transfer amounts of electricity, heat and gas in the real-time stage, l is the step scale of the k-th load, and v is the step price of the k-th load; Among them, the k-type loads are electricity, heat and gas loads.

7. The method according to claim 6, characterized in that: The real-time supply and demand balance constraints are as follows: Among them, β6, β7 and β8 are the confidence levels of the supply and demand balance of electricity, heat and gas in the real-time stage, which are preset values. and are the real-time electricity, heat and gas loads at time t respectively; and are the real-time electricity, heat and gas transfer loads at time t respectively; and are the uncertainty factors for electricity, heat and gas loads, respectively; They are the electricity loads satisfied by wind power, photovoltaic power, gas turbine, solar thermal power station and hydrogen fuel cell in the real-time market at time t; are the heat loads satisfied by the real-time market electricity storage device, hydrogen storage device, hydrogen fuel cell and power heat pump at time t; It is the gas load satisfied by the real-time market methane reactor at time t.

8. The method according to claim 7, characterized in that: The real-time demand response constraints are as follows: in, and They are the upper and lower limits of the amount of electricity load interruption and transfer of users participating in demand response at time t, respectively; and They are the upper and lower limits of the thermal load interruption and transfer amount of users participating in demand response at time t, respectively; and are the upper and lower limits of the gas load interruption and transfer amount of users participating in demand response at time t; β9, β 10 and β 11 They are the confidence levels of electricity, heat and gas demand response in the real-time stage respectively.

9. The method according to claim 8, characterized in that: The real-time unit constraints include real-time wind turbine unit constraints, photovoltaic unit constraints, new hydrogen energy cascade utilization device unit constraints, solar thermal power station unit constraints, gas turbine unit constraints, hydrogen fuel cell unit constraints, power storage device unit constraints, hydrogen storage device unit constraints and ground source heat pump unit constraints.

10. The method according to any one of claims 1 to 9, characterized in that: In addition to integrating the novel hydrogen energy cascade utilization device, the island micro-energy network also includes wind power, photovoltaic, cogeneration units, solar thermal power stations, power storage devices, ground source heat pumps, external gas networks and loads; The cogeneration unit includes a gas turbine, a waste heat recovery device and a heat exchange device; The solar thermal power station includes a generator, a heat collection field and a heat storage device; The loads include electricity, heat and gas loads; Among them, wind power, photovoltaic, solar thermal power stations, cogeneration units, and ground source heat pumps are energy supply equipment; electricity storage devices, heat storage devices, and hydrogen storage devices are energy storage equipment.

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