CN-122022221-A - Green electricity-hydrogen-methanol integrated comprehensive energy system and optimal scheduling method thereof

Abstract

The invention relates to a green electricity-hydrogen-methanol integrated comprehensive energy system and an optimal scheduling method thereof, belonging to the technical field of comprehensive energy system optimization. The invention takes wind power/photovoltaic as primary energy, realizes green electricity-green hydrogen bidirectional conversion through a hydrogen energy storage unit (comprising an electrolytic tank, a compressor, a hydrogen storage tank and a hydrogen fuel cell), forms a carbon closed loop path in cooperation with an electricity-methanol unit (coupling a carbon trapping device and a methanol synthesis reactor), designs a day-ahead dispatching optimization model based on multi-market interaction, aims at minimizing running total cost, integrates equipment running constraint, multi-energy flow balance and a market transaction mechanism, and further provides a day-ahead dispatching decision for minimizing running cost by the optimizing and dispatching method of the green electricity-hydrogen-methanol integrated comprehensive energy system, thereby realizing the cooperative optimization of electricity-hydrogen-methanol multi-energy flow and the efficient cyclic utilization of carbon resources.

Inventors

• WANG YUWEI
• ZHANG ZHILUN
• LI MEI
• WANG YURU
• Zhai chang
• CHEN BO
• SUN XIAOTONG
• Li Nianduo
• CAI YUNLONG
• LI BINGKANG
• SONG MINGHAO
• SHI LIN
• WANG YIWEI
• WANG YUCHEN
• CAO ZEBIN
• HU JIAN

Assignees

• 华北电力大学（保定）

Dates

Publication Date

20260512

Application Date

20251017

Claims (4)

1. 1. The green electricity-hydrogen-methanol integrated comprehensive energy system is characterized by comprising a renewable energy power generation unit, a hydrogen energy storage unit and an electric methanol production unit, and realizing multi-dimensional energy interaction through an external power grid, an electric load, a hydrogen energy market and a methanol market; After green power generated by the renewable energy power generation unit is converged into a power hub, multipath distribution is performed, and the method specifically comprises the following steps: The part of green electricity drives an electrolytic tank in the hydrogen energy storage unit to electrolyze water to prepare hydrogen, the generated hydrogen is stored in a hydrogen storage tank with charging and discharging capabilities after being compressed, and the stored hydrogen provides raw material for a hydrogen fuel cell to generate electricity and feed back to a power grid on one hand and is directly transmitted to a hydrogen energy market on the other hand; the other part of green power is supplied to an electric methanol unit, and is combined with a carbon source obtained by a carbon dioxide capturing device to be catalytically converted into methanol in a methanol synthesis reactor, and the product is stored in a methanol storage tank which also supports bidirectional flow and then is output to a methanol market, so that the power load requirement in the system is ensured.
2. 2. The green electricity-hydrogen-methanol integrated comprehensive energy system according to claim 1, wherein a green electricity-hydrogen-methanol integrated optimization scheduling model is constructed based on the system, and a function of the model is expressed as: Wherein C total represents total daily operation cost of the green electricity-hydrogen-methanol integrated comprehensive energy system, C 0 represents sum of various costs of system operation, R 0 represents sum of various benefits of system operation, C EL and C Respectively representing the unit power operation and maintenance cost of the electrolytic cell and the electric power of the electrolytic cell at the moment, c HC and Respectively representing the unit output operation cost and the electric power of the hydrogen compressor at the t time, c HFC and C HS 、c MS represents the unit hydrogen charging and discharging/methanol operation and maintenance cost of the hydrogen storage tank/methanol storage tank respectively; respectively representing the hydrogen charging/methanol power of the hydrogen storage tank/methanol storage tank at the t moment; Respectively representing the hydrogen release/methanol power of the hydrogen storage tank/methanol storage tank at the t time, c cut , C M 、c c 、c W 、c P respectively represents the unit output operation and maintenance cost of the methanol reactor, carbon capture, wind power generation and photovoltaic power generation; Respectively representing carbon capture, methanol production, wind power generation and photovoltaic power generation power at the t-th moment; And The price of selling/purchasing electricity of the system at the time t is respectively represented by the selling electricity quantity and the purchasing electricity quantity of the system, and the price of selling hydrogen and selling methanol is respectively represented by ρ H 、ρ M ; And The hydrogen sales and the methanol sales at time t are respectively shown, and R C shows the carbon market benefit.
3. 3. The green electricity-hydrogen-methanol integrated comprehensive energy system according to claim 2, wherein the constraint conditions of the green electricity-hydrogen-methanol integrated optimization scheduling model include the following: 1) Hydrogen storage body restraint 1.1 Electrolysis cell) In the formula, Represents hydrogen production; Represents the electric power input of the electrolytic cell, P EL,max represents the rated power of the electrolytic cell, eta EL represents the hydrogen production coefficient of the electrolytic cell; 1.2 Hydrogen compressor In the formula, Represents the hydrogen compression electric power input, P HC,max represents the planned capacity of the hydrogen compressor, eta HC represents the hydrogen compression coefficient of the hydrogen compressor; 1.3 Hydrogen fuel cell In the formula, P t HFC represents the amount of generated electricity; eta HFC represents the power generation efficiency of the oxyhydrogen fuel cell; represents the rated electric power of the hydrogen fuel cell; And Respectively representing the downward and upward climbing coefficients; 1.4 Hydrogen storage tank Ψ 0 ＝Ψ T (15) Wherein, ψ t represents the hydrogen storage amount, and ψ 0 represents the initial hydrogen storage amount; represents the hydrogen charge; indicating the hydrogen release amount; Psi T represents the hydrogen storage amount at the end of the period T, psi max represents the planned capacity of the hydrogen storage tank; 2) Renewable energy power generation main body constraint In the formula, Indicating the amount of waste; Indicating the air discarding quantity; representing a photovoltaic output; representing the output of the wind turbine generator; 3) Main body restraint for electric methanol production 3.1 Carbon capture In the formula, Represents carbon capture power; Lambda C 、μ C represents the capture efficiency and conversion coefficient, respectively; representing the rated power of the carbon capture device; 3.2 Methanol reactor In the formula, Representing the power of methanol preparation equipment; represents the amount of reactant hydrogen, mu M represents the conversion coefficient, lambda M represents And Feed ratio; indicating the rated power of the methanol production equipment; 3.3 Methanol storage tank Φ 0 ＝Φ T (28) Wherein Φ t represents the amount of stored methanol; indicating the methanol feed amount; The amount of methanol is shown; Represents the rated power of methanol entering and exiting, phi T represents the methanol storage quantity at the end of the period T, phi 0 represents the initial methanol storage quantity, and phi max represents the planned capacity of the methanol storage tank; 4) Market constraints In the formula, Representing the sales power; representing the electricity purchasing quantity; Representing maximum transmission electric power; indicating the amount of hydrogen sold by the hydrogen market; Representing the amount of methanol sold by the methanol market; And Respectively represent the maximum hydrogen selling/methanol amount; representing the carbon trade market carbon quota, R C , k, Lambda t 、λ s The conversion coefficients of carbon market income, carbon credit and carbon dioxide emission reduction, the methanol amount produced by the system, the emission factor of the traditional process, the emission factor of the system and the maximum trade carbon credit of the carbon market are respectively expressed; 5) Load shedding constraint In the formula, A range constraint representing the cut load; predicted electrical load; 6) System node balancing constraints Wherein equation (40) represents an electrical node balance constraint, equation (41) represents a methanol node balance constraint, and equation (42) represents a hydrogen node balance constraint.
4. 4. The optimal scheduling method for the green electricity-hydrogen-methanol integrated comprehensive energy system according to any one of claims 1 to 3, comprising the following steps: S1, multi-source data acquisition and pretreatment: Collecting time sequence data of historical wind power, photovoltaic output, system electric load and electric market price, constructing a standardized training data set through data cleaning and normalization processing, and generating 24-hour predicted values before the day by adopting an LSTM neural network time sequence prediction algorithm, wherein the time sequence data comprises wind power/photovoltaic predicted output System internal electrical load prediction value Time-of-use electricity price S2, loading system constant parameters: Initializing physical limit parameters of equipment, wherein the physical limit parameters comprise rated power, storage tank capacity, energy efficiency coefficient and market constraint, and the rated power comprises P EL,max 、P HC,max , The tank capacity includes ψ max 、Φ max , the energy efficiency coefficient includes μ EL 、λ M , and the market constraints include: S3, building a mixed integer linear programming model: A nonlinear model is built, the nonlinear model is converted into an MILP form, and integer variables are defined: hydrogen storage tank mode of operation (Hydrogen charge=1, hydrogen discharge=0); power trade status v t e {0,1} (purchase = 1, sell = 0); linear reconstruction mutex constraint: Preserving the mathematical form of the objective functions (1) - (3) and the linear constraints (4) - (15), (17) - (42); s4, solving an optimization model and performing convergence control: Invoking a CPLEX configuration parameter of a mathematical programming solver, selecting a branch-and-bound method, wherein an objective function is (1), a convergence condition is that a relative gap is less than 1% or a calculation time is less than 300 seconds, and outputting a 24-period optimal solution vector X * ; s5, checking feasibility of a scheduling scheme: performing posterior analysis on the solution vector obtained in the step S4, verifying the balance of the multi-energy flow, checking that the power of the equipment is not out of limit, and confirming that the state of the storage tank is closed circularly; S6, issuing and executing a real-time control instruction: The energy management system converts the optimization scheme into equipment control signals, and system operation data is returned in real time to form closed-loop optimization.

Description

Green electricity-hydrogen-methanol integrated comprehensive energy system and optimal scheduling method thereof Technical Field The invention belongs to the technical field of comprehensive energy system optimization, and particularly relates to a green electricity-to-methanol comprehensive energy system integrating wind power, photovoltaic, hydrogen energy storage and carbon capture and a day-ahead dispatching optimization method for minimizing operation cost of the system. Background Under global energy transformation, the large-scale application of renewable energy sources such as wind power, photovoltaic and the like has become a key path. However, the inherent intermittence and fluctuation of the solar energy system results in a large amount of waste wind and light, which severely restricts the energy utilization efficiency and economy. In order to stabilize fluctuation and improve the digestion capability, the academic community proposes a green electricity-green hydrogen conversion path, namely, surplus electric power is converted into hydrogen through electrolysis of water, and energy cross-space-time transfer is realized. Although the hydrogen energy has zero carbon characteristic, the problems of high storage and transportation cost, insufficient infrastructure and the like limit the direct application of the hydrogen energy. Therefore, the downstream extension to green liquid fuel synthesis is an important direction to break through the bottleneck, where green electricity to methanol is of great interest for its technical feasibility and commercial potential. Methanol is used as a basic chemical raw material and a potential clean fuel with a global demand of more than one hundred million tons, and the traditional production of the methanol is severely dependent on fossil energy. The green electricity methanol can realize closed loop circulation of carbon-hydrogen-oxygen elements by coupling renewable energy sources, electrolytic hydrogen production and carbon dioxide trapping, wherein the trapped industrial carbon dioxide is used as a synthetic raw material to recycle greenhouse gases, and the green hydrogen replaces fossil synthetic gas to eliminate process carbon emission from the source. The path not only helps deep decarburization in the chemical industry, but also can produce high added value green methanol, and meets the requirements of multiple scenes such as traffic fuel, hydrogen carrier, chemical raw materials and the like. However, existing research on multiple focused single links (such as hydrogen production efficiency or methanol synthesis catalyst development) lacks global optimization of the "electro-hydro-alcohol" full chain dynamic coupling mechanism. In the system cooperative operation level, key equipment such as an electrolytic tank, a hydrogen storage tank, a methanol reactor and the like need to dynamically respond to fluctuation of wind power and photovoltaic output, time-of-use electricity price signals and multi-element market demands. The traditional rigid scheduling strategy of 'hydrogen determination by electricity' or 'alcohol determination by hydrogen' is difficult to meet the requirement of the system on flexibility in multiple time scales, the system is required to be integrated with operation and maintenance cost, market benefit (electric power/hydrogen/methanol/carbon transaction) and punishment cost (wind abandon light abandon and load cut), the prior strategy is insufficient to excavate the multi-directional conversion capability of hydrogen energy storage to improve the economical efficiency, and the dynamic matching mechanism of carbon dioxide capture and methanol synthesis is not clear in the carbon circulation level, and the carbon utilization efficiency is easily influenced by wind and light fluctuation. Therefore, a collaborative scheduling framework for a green electricity-to-methanol comprehensive energy system needs to be constructed, and a marketization interaction mechanism is deeply integrated through precise modeling of a multi-energy flow coupling constraint so as to collaborative optimize the system operation cost minimization and the efficient utilization target of carbon resources. Disclosure of Invention The invention aims to provide a green electricity-hydrogen-methanol integrated comprehensive energy system and an optimal scheduling method thereof, which are used for solving the problems that in the prior art, stroke-light-hydrogen-methanol multi-energy flow collaborative optimization is insufficient, carbon circulation efficiency is to be improved, running economy is poor and the like. In order to achieve the above purpose, the invention adopts the following technical scheme: The green electricity-hydrogen-methanol integrated comprehensive energy system comprises a renewable energy power generation unit, a hydrogen energy storage unit and an electric methanol production unit, and realizes multi-dimensional energy interaction through an ex