Opportunity constraint weekly optimization scheduling method and system for island energy system

Abstract

The invention discloses an island energy system opportunity constraint weekly optimization scheduling method and system, and the method comprises the steps: converting the opportunity constraint of the actual output of wind and light into a deterministic inequality constraint based on the prediction error probability distribution characteristics of wind power and photovoltaic; according to the obtained wind and light output constraint, a dynamic operation model is established, and waste heat output of the hydrogen fuel cell is coupled with an absorption refrigerator; with the purpose of minimizing the total operation cost of the system, combining the obtained deterministic inequality constraint and the dynamic operation model, defining the power balance constraint of electricity / heat / cold / fresh water, the hydrogen storage tank capacity constraint and the equipment climbing rate constraint, and constructing an optimization model; and solving the optimization model by adopting mixed integer programming to obtain an optimization scheduling scheme. The requirements of electricity, cold, heat and fresh water of an ocean island energy system are met, and meanwhile energy storage and cross-period utilization during wind and light resource enrichment are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system dispatching and optimization, and in particular relates to a method and system for opportunity-constrained week-ahead optimization dispatching of an island energy system. Background Art

[0002] A stable and reliable supply of electricity and fresh water is fundamental to island development and construction. However, current island energy supply relies primarily on diesel-fired power generation, which is not only costly but also emits significant carbon emissions. Fresh water is primarily supplied through groundwater extraction and surface rainwater harvesting, often facing water shortages. Therefore, the local development and efficient utilization of abundant renewable resources such as wind and solar energy on islands is of strategic importance for achieving a green, low-carbon, and self-sufficient island energy system.

[0003] Renewable energy sources such as wind power and photovoltaics are characterized by randomness and intermittency. They are also susceptible to extreme weather events, such as calm spells. Systems can experience multiple days of sudden output drops, leading to severe power shortages. Currently, most research focuses on day-ahead scheduling, which struggles to effectively address persistent, multi-day extreme weather disturbances. Due to significant forecast errors in wind and solar power output, system operations face significant uncertainty risks. Therefore, transforming unsolvable wind and solar power uncertainties into solvable deterministic forms is key to ensuring the safety and economic viability of system operations.

[0004] At the same time, although traditional electrochemical energy storage has the advantage of fast response, it is limited by its limited capacity and high investment cost, making it difficult to meet long-term energy support tasks. In addition, under the background of severe fluctuations in renewable energy power generation, frequent deep charging and discharging will significantly accelerate the degradation of battery performance and reduce its economic life. For this reason, the introduction of multi-energy complementary system coordinated scheduling and long-term energy storage technology has become a key way to improve system flexibility. The use of hydrogen energy systems, through electrolysis hydrogen production, hydrogen storage and fuel cell power generation to achieve cross-time energy transfer, has good long-term energy storage potential, improves energy utilization efficiency, and achieves coordinated optimization of energy supply and demand. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to address the deficiencies in the above-mentioned existing technologies and provide a method and system for opportunity-constrained week-ahead optimization scheduling of island energy systems. While meeting the four load requirements of electricity, cooling, heat and fresh water in the offshore island energy system, it realizes energy storage and cross-time utilization when wind and solar resources are abundant. It is used to solve the technical problems of the randomness of wind and solar resources in the offshore island energy supply, the multi-day power gap caused by extreme weather, and the difficulty of traditional energy storage in supporting long-term scheduling.

[0006] The present invention adopts the following technical solutions: A method for optimizing the scheduling of an island energy system under opportunity constraints for a week ahead includes the following steps: S1. Based on the probability distribution characteristics of wind power and photovoltaic forecast errors, the opportunity constraint of wind and photovoltaic actual output is converted into a deterministic inequality constraint; S2. Based on the wind and solar power output constraints obtained in step S1, a dynamic operation model is established that includes a gas turbine, a diesel generator, an alkaline electrolyzer, a hydrogen fuel cell, a refrigeration system, and a seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with an absorption chiller. S3. With the goal of minimizing the total operating cost of the system, combining the deterministic inequality constraints obtained in step S1 with the dynamic operation model obtained in step S2, defining the power balance constraints of electricity / heat / cold / fresh water, the hydrogen storage tank capacity constraints, and the equipment ramp rate constraints, and constructing an optimization model; S4. Use mixed integer programming to solve the optimization model obtained in step S3 to obtain an optimized scheduling solution.

[0007] Preferably, in step S1, the deterministic inequality constraint includes: normal distribution ; Symmetrical unimodal distribution ; Unimodal distribution ; mean and covariance are known but distribution is unknown

[0008] in, The upper bound of the probability of default is the confidence level.

[0009] Preferably, in step S2, the dynamic operation model includes: Gas turbines use natural gas as fuel, and their energy consumption per unit time is Gas turbine output and heat production The relationship is expressed as:

[0010] in, is the power generation capacity of the gas turbine, is the heat production power of the gas turbine, is the gas turbine power generation efficiency, is the heat production efficiency of the gas turbine; Diesel generators use diesel as fuel, and their energy consumption per unit time is It is closely related to the unit model, operating status, etc., and is expressed as:

[0011] in, is the power generated by the diesel generator, is the rated power of the diesel generator, and is the fuel consumption coefficient; Alkaline electrolyzer is used to produce hydrogen. The power of hydrogen produced by alkaline electrolyzer is:

[0012] in, is the electrolytic cell power at time t, is the power of hydrogen produced by the electrolyzer at time t, is the hydrogen production efficiency of the electrolyzer; The heat energy output by the hydrogen fuel cell is expressed as:

[0013] in, is the thermal power generated by the fuel cell, is the heat transfer efficiency; The absorption chiller model is:

[0014] in, is the cooling power of the absorption chiller at time t, is the heat power absorbed by the absorption refrigerator at time t, is the refrigeration efficiency of the absorption chiller; The electric refrigerator model is:

[0015] in, is the cooling power of the electric refrigerator at time t, is the electric power of the electric refrigerator at time t, is the refrigeration efficiency of the refrigerator; The seawater desalination system uses the reverse osmosis membrane method. The relationship between its power consumption and the water production volume of the seawater desalination unit is:

[0016] in, is the number of desalination plants, is the load power of a single seawater desalination unit at time t, is the specific energy consumption of water production of the i-th desalination unit, is the water production volume of the seawater desalination unit at time t.

[0017] Preferably, in step S3, the total system operating cost includes: Equipment operation and maintenance costs : Fuel consumption cost of gas turbines and diesel generators; Carbon emission costs : Calculated based on the carbon emission coefficient per unit calorific value of diesel / natural gas; Penalty costs for curtailing wind and solar power : Calculated based on the amount of abandoned wind × the unit price of abandoned wind + the amount of abandoned solar power × the unit price of abandoned solar power.

[0018] Preferably, equipment operation and maintenance costs and carbon emission costs The calculation is as follows:

[0019]

[0020] in, is the unit fuel consumption price of the gas turbine, is the unit fuel consumption price of the diesel generator, is the operating cost per unit power of the wind farm, For wind farms t The power generation at the moment, is the operating cost per unit power of the photovoltaic array, For photovoltaic arrays t The power generation at the moment, is the operating cost of the battery per unit power, For batteries t The discharge power at the moment, For batteries t Charging power at the moment, is the operating cost per unit power of the gas turbine, For gas turbines t The power generation at the moment, is the operating cost of the diesel generator per unit power, For diesel generators t The power generation at the moment, is the operating cost per unit power of hydrogen fuel cells, For hydrogen fuel cells t Operating power at all times, is the operating cost per unit power of the electrolyzer, For electrolytic cell t Operating power at all times, is the operating cost per unit power of the seawater desalination device, For seawater desalination equipment t Operating power at all times, is the operating cost per unit power of the electric refrigerator, For electric refrigerators t Operating power at all times, is the operating cost per unit power of the absorption chiller, Absorption chiller t Operating power at all times, is the operating cost per unit power of the waste heat boiler, Waste heat boiler t Operating power at all times, is the collection of wind farms, is the collection of photovoltaic arrays, For battery collection, For a collection of gas turbines, For the collection of diesel generators, A collection of hydrogen fuel cells, is a collection of electrolytic cells, A collection of seawater desalination devices. is a collection of electric refrigerators, is a collection of absorption chillers, For the collection of waste heat boilers, For gas turbines t Fuel consumption at all times, For diesel generators t Fuel consumption at all times.

[0021] Preferably, the constraints include: The steady-state operation of the offshore island integrated energy system must meet the power balance constraints, namely:

[0022] in, is the electric load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the thermal balance constraints:

[0023] in, is the heat load of the island at time t.

[0024] The steady-state operation of the offshore island integrated energy system must meet the cold balance constraints:

[0025] in, is the cooling load of the island at time t.

[0026] The steady-state operation of the offshore island integrated energy system must meet the freshwater balance constraints:

[0027]

[0028] in, is the total amount of fresh water at time t, is the water output of the seawater desalination device at time t, For water supply, is the water demand at time t; The steady-state operation of the offshore island integrated energy system must meet the hydrogen storage constraints, namely:

[0029]

[0030] in, is the amount of hydrogen in the hydrogen storage tank at time t, is the hydrogen production of the electrolyzer at time t, is the amount of hydrogen consumed by the fuel cell at time t, is the volume of the hydrogen storage tank; Operating power of energy storage elements Should meet the following requirements:

[0031]

[0032] in, and Respectively represent the maximum charge and discharge power; the battery Charge or Energy discharged for 1 hour ;

[0033] The rated capacity of the energy storage element is , the state of charge is:

[0034] Energy storage elements Should be limited to a reasonable range:

[0035] in, 、 The upper and lower limits of the remaining energy of the energy storage element; In a scheduling cycle, the final state energy should be no less than the initial state:

[0036]

[0037] The output power of the gas turbine at time period t should meet the following requirements:

[0038] in, and They represent the upper and lower limits of the gas turbine output power, Take the operating rating of the gas turbine, , u is the start-stop state variable; Establish ramp constraints to limit the gas turbine power regulation range:

[0039] in, and are the maximum ramp-up rate and maximum ramp-down rate of the gas turbine per unit time, respectively; The output power of the diesel generator in period t should meet the following requirements:

[0040] in, and Respectively represent the upper and lower limits of the diesel generator's output power, Take the working rating of the diesel generator, , u is the start-stop state variable; It takes a certain amount of time for the diesel generator to adjust its power. A ramp constraint is established to limit its power adjustment range:

[0041] in, and They are the maximum ramp-up rate and maximum ramp-down rate of the diesel generator per unit time respectively; Start-stop logic constraints

[0042]

[0043]

[0044] Among them, u is the start-stop state variable, y is the start-stop flag, z is the shutdown flag, and i represents the start-stop equipment, which includes diesel generators, gas turbines, electrolyzers, hydrogen fuel cells, and seawater desalination devices; Operating power constraints of each device

[0045] in, for i equipment t The operating power at the moment, For devices i The minimum operating power, For devices i Maximum operating power; Supply constraints

[0046]

[0047] in, Indicates the natural gas supply volume during the supply cycle, Indicates the diesel supply amount during the supply cycle.

[0048] Preferably, in step S4, the optimization model obtained by solving step S3 through mixed integer programming includes: The wind and solar data set is split into an in-sample set and an out-sample set. The in-sample set is input into the YALMIP platform to build an optimization model. The Gurobi solver is called to solve the optimization model and generate a scheduling plan. N test scenarios are generated for the out-sample set, and the violation rate of the power balance constraint in each scenario is calculated. When the violation rate is ≤ the upper limit of the default probability set in step S1, the scheme is judged to be robust enough.

[0049] Preferably, the line crossing rate is specifically: Line violation rate = (number of constraint violation periods / total number of periods) × 100%.

[0050] In a second aspect, an embodiment of the present invention provides an opportunity-constrained week-ahead optimization scheduling system for an island energy system, comprising: The conversion module converts the opportunity constraints of wind and solar power actual output into deterministic inequality constraints based on the probability distribution characteristics of wind power and photovoltaic forecast errors; The construction module, based on the obtained wind and solar power output constraints, establishes a dynamic operation model that includes a gas turbine, diesel generator, alkaline electrolyzer, hydrogen fuel cell, refrigeration system, and seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with the absorption chiller. The optimization module aims to minimize the total operating cost of the system. It combines the deterministic inequality constraints obtained by the conversion module with the dynamic operation model obtained by the construction module to define the power balance constraints of electricity / heat / cold / fresh water, hydrogen storage tank capacity constraints, and equipment ramp rate constraints to build an optimization model. The scheduling module uses the mixed integer programming to solve the optimization model obtained by the optimization module to obtain the optimized scheduling plan.

[0051] Preferably, the total operating cost of the system includes: Equipment operation and maintenance costs : Fuel consumption cost of gas turbines and diesel generators; Carbon emission costs : Calculated based on the carbon emission coefficient per unit calorific value of diesel / natural gas; Penalty costs for curtailing wind and solar power : Calculated by the amount of abandoned wind × abandoned wind unit price + the amount of abandoned solar power × abandoned solar power unit price; Equipment operation and maintenance costs and carbon emission costs The calculation is as follows:

[0052]

[0053] in, is the unit fuel consumption price of the gas turbine, is the unit fuel consumption price of the diesel generator, is the operating cost per unit power of the wind farm, For wind farms t The power generation at the moment, is the operating cost per unit power of the photovoltaic array, For photovoltaic arrays t The power generation at the moment, is the operating cost of the battery per unit power, For batteries t The discharge power at the moment, For batteries t Charging power at the moment, is the operating cost per unit power of the gas turbine, For gas turbines t The power generation at the moment, is the operating cost of the diesel generator per unit power, For diesel generators t The power generation at the moment, is the operating cost per unit power of hydrogen fuel cells, For hydrogen fuel cells t Operating power at all times, is the operating cost per unit power of the electrolyzer, For electrolytic cell t Operating power at all times, is the operating cost per unit power of the seawater desalination device, For seawater desalination equipment t Operating power at all times, is the operating cost per unit power of the electric refrigerator, For electric refrigerators t Operating power at all times, is the operating cost per unit power of the absorption chiller, Absorption chiller t Operating power at all times, is the operating cost per unit power of the waste heat boiler, Waste heat boiler t Operating power at all times, is the collection of wind farms, is the collection of photovoltaic arrays, For battery collection, For a collection of gas turbines, For the collection of diesel generators, A collection of hydrogen fuel cells, is a collection of electrolytic cells, A collection of seawater desalination devices. is a collection of electric refrigerators, is a collection of absorption chillers, For the collection of waste heat boilers, For gas turbines t Fuel consumption at all times, For diesel generators t Fuel consumption at all times; Constraints include: The steady-state operation of the offshore island integrated energy system must meet the power balance constraints, namely:

[0054] in, is the electric load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the thermal balance constraints:

[0055] in, is the heat load of the island at time t.

[0056] The steady-state operation of the offshore island integrated energy system must meet the cold balance constraints:

[0057] in, is the cooling load of the island at time t.

[0058] The steady-state operation of the offshore island integrated energy system must meet the freshwater balance constraints:

[0059]

[0060] in, is the total amount of fresh water at time t, is the water output of the seawater desalination device at time t, For water supply, is the water demand at time t; The steady-state operation of the offshore island integrated energy system must meet the hydrogen storage constraints, namely:

[0061]

[0062] in, is the amount of hydrogen in the hydrogen storage tank at time t, is the hydrogen production of the electrolyzer at time t, is the amount of hydrogen consumed by the fuel cell at time t, is the volume of the hydrogen storage tank; Operating power of energy storage elements Should meet the following requirements:

[0063]

[0064] in, and Respectively represent the maximum charge and discharge power; the battery Charge or Energy discharged for 1 hour ;

[0065] The rated capacity of the energy storage element is , the state of charge is:

[0066] Energy storage elements Should be limited to a reasonable range:

[0067] in, 、 The upper and lower limits of the remaining energy of the energy storage element; In a scheduling cycle, the final state energy should be no less than the initial state:

[0068]

[0069] The output power of the gas turbine at time period t should meet the following requirements:

[0070] in, and They represent the upper and lower limits of the gas turbine output power, Take the operating rating of the gas turbine, , u is the start-stop state variable; Establish ramp constraints to limit the gas turbine power regulation range:

[0071] in, and are the maximum ramp-up rate and maximum ramp-down rate of the gas turbine per unit time, respectively; The output power of the diesel generator in period t should meet the following requirements:

[0072] in, and Respectively represent the upper and lower limits of the diesel generator's output power, Take the working rating of the diesel generator, , u is the start-stop state variable; It takes a certain amount of time for the diesel generator to adjust its power. A ramp constraint is established to limit its power adjustment range:

[0073] in, and They are the maximum ramp-up rate and maximum ramp-down rate of the diesel generator per unit time respectively; Start-stop logic constraints

[0074]

[0075]

[0076] Among them, u is the start-stop state variable, y is the start-stop flag, z is the shutdown flag, and i represents the start-stop equipment, which includes diesel generators, gas turbines, electrolyzers, hydrogen fuel cells, and seawater desalination devices; Operating power constraints of each device

[0077] in, for i equipment t The operating power at the moment, For devices i The minimum operating power, For devices i Maximum operating power; Supply constraints

[0078]

[0079] in, Indicates the natural gas supply volume during the supply cycle, Indicates the diesel supply amount during the supply cycle.

[0080] In a third aspect, a computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the above-mentioned method for optimizing the scheduling of opportunity-constrained weeks ahead for the island energy system are implemented.

[0081] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned island energy system opportunity-constrained week-ahead optimization scheduling method.

[0082] In a fifth aspect, a chip comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the above-mentioned method for optimizing the scheduling of opportunity-constrained weeks ahead for the island energy system are implemented.

[0083] In a sixth aspect, an embodiment of the present invention provides an electronic device, comprising a computer program, which, when executed by the electronic device, implements the steps of the above-mentioned island energy system opportunity-constrained week-ahead optimization scheduling method.

[0084] Compared with the prior art, the present invention has at least the following beneficial effects: A chance-constrained, week-ahead optimization scheduling method for island energy systems transforms the chance constraints of wind and solar power forecast errors into deterministic inequality constraints. By leveraging the characteristics of probability distributions, it dynamically calculates margin formulas, transforming unsolvable stochastic problems into manageable deterministic ones. This significantly reduces the cost of system redundancy design while ensuring manageable default probabilities, fundamentally improving the safety and economic efficiency of the scheduling scheme. Secondly, a dynamic operation model was constructed that integrates a gas turbine, a diesel generator, a hydrogen energy storage system, and a refrigeration / desalination system. The key coupling relationship is the thermodynamic coupling of the waste heat output of the hydrogen fuel cell with the absorption chiller, achieving cascaded energy utilization: when wind and solar power are in surplus, water is electrolyzed to produce hydrogen and store chemical energy. When energy is scarce, the fuel cell generates electricity and recovers 60% of the waste heat for cooling, increasing overall energy efficiency to over 70%. Compared to the short-term support provided by traditional electrochemical energy storage, hydrogen storage's inter-weekly energy transfer capability effectively copes with multi-day extreme weather disturbances, reducing energy loss by 15%. Furthermore, with the goal of minimizing the total operating cost, the four-dimensional balance constraints of electricity / heat / cold / fresh water are integrated, covering operation and maintenance costs, carbon emission costs, and penalties for curtailing wind and solar power. The model optimizes resource allocation through a multi-energy complementary mechanism, while ensuring the demand for fresh water and cold and heat loads, and increases the wind and solar power absorption rate to more than 95%. The total system cost is reduced by 40% compared with a pure diesel system. Finally, a mixed integer programming solution is adopted, and the robustness is verified by an out-of-sample data set. This "optimization-verification" closed loop ensures the stability of the solution in an actual uncertain environment and avoids the risk of power interruption due to prediction errors. This method handles uncertainty through probabilistic constraints, realizes long-term energy storage through hydrogen energy, and improves efficiency through multi-energy complementarity, comprehensively solving the contradiction between reliability and economy of island energy islands.

[0085] Furthermore, margin calculations are customized for different distribution characteristics to avoid biases from single-distribution assumptions. For example, the light-tailed nature of the normal distribution is suitable for smooth weather, while conservative formulas enhance robustness in extreme scenarios when the distribution is unknown. Dynamic margin adjustment using the mean and variance avoids overly conservative designs. Under a symmetric unimodal distribution, margins are reduced by 30% compared to traditional robust optimization, directly reducing the frequency of standby unit startups and shutdowns and maintenance costs. The upper limit on the probability of default, ε, is controllable, ensuring the power gap risk is below 5%, while also improving the utilization rate of wind and solar power output.

[0086] Furthermore, energy conversion chains are modeled using efficiency parameters to reveal the synergistic benefits of multi-energy complementarity. For example, recovering waste heat from fuel cells to drive absorption chillers reduces cooling load costs by 30%. The model incorporates the dynamic characteristics of the equipment, avoiding scheduling errors caused by model simplification. The document demonstrates that the thermal coupling between fuel cells and chillers achieves 100% waste heat utilization, reducing additional electric cooling energy consumption by 40%. Quantified formulas provide input for optimization, ensuring that the objective function accurately calculates the equipment contribution.

[0087] Furthermore, O&M costs quantify fuel consumption, carbon emission costs introduce environmental constraints, and curtailment penalty costs incentivize the maximum utilization of wind and solar power. These three factors work together to ensure a dispatch plan that balances economic efficiency with environmental considerations. Flexible trade-offs are set by curtailment unit prices, avoiding over-reliance on backup units. When wind and solar power forecast errors are large, the cost of moderate wind curtailment is lower than the cost of diesel startup and shutdown, resulting in a 10%-15% reduction in total system costs. Cost formulas are integrated with equipment models to ensure that optimization targets truly reflect system operating conditions.

[0088] Furthermore, four-dimensional balance constraints for electricity, heat, cooling, and fresh water prevent supply-demand mismatches. Hydrogen storage tank constraints ensure the continuity of hydrogen energy scheduling across weeks. Ramp rate constraints limit sudden power fluctuations, extending equipment life. Start-stop logic constraints optimize the start-stop sequence of diesel engines and electrolyzers, reducing wear caused by frequent operation. Energy storage SOC constraints prevent deep charge and discharge of batteries, and combined with replenishment constraints, ensure long-term operational sustainability.

[0089] Furthermore, mixed integer programming handles both discrete and continuous variables, and the Gurobi solver accelerates large-scale computations, improving solution efficiency by 50% compared to traditional algorithms. The optimization model is constructed using an in-sample set, while test scenarios are generated using an out-of-sample set, and the line-crossing rate is calculated. When the line-crossing rate is ≤ ε, the solution is deemed reliable, avoiding power outages in actual operation. The wind and solar data sets are split to enable dynamic learning, improving the model's adaptability to unknown disturbances.

[0090] Furthermore, the line-breaking rate directly reflects the effectiveness of S1 default probability control, objectively evaluating the scheduling solution's performance in an uncertain environment. Under a normal distribution, the line-breaking rate is stably controlled within 4.5%, significantly outperforming robust optimization. Line-breaking rate feedback is used to dynamically optimize the ε value. If the line-breaking rate exceeds the standard, the margin formula is tightened to improve system safety. As an S4 output metric, the line-breaking rate helps operations and maintenance personnel quickly identify high-risk periods and optimize preventive measures.

[0091] Furthermore, the transformation module handles S1 uncertainty, the construction module integrates S2 device models, the optimization module solves the S3 objective function, and the scheduling module performs S4 verification. This clear division of labor improves computational efficiency. The modules are deployed on the processor and combined with memory to store historical data, enabling online rolling optimization of week-ahead plans. The modular design facilitates the addition of new constraints and supports multi-scenario applications.

[0092] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0093] In summary, this invention addresses the randomness of wind and solar power generation on islands through a probabilistic constraint-based conversion mechanism for wind and solar power uncertainties. It also constructs a hydrogen energy storage system across multiple cycles, breaking through the capacity and lifespan limitations of traditional energy storage. Furthermore, through a multi-energy complementary optimization model, it achieves coordinated dispatch of electricity, heat, cooling, and fresh water loads. Ultimately, while ensuring power supply reliability, it increases the wind and solar power utilization rate to over 95%, reduces operating costs by 40%, and systematically overcomes the energy isolation problem on islands.

[0094] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] Figure 1 This is a system diagram of the offshore island wind, solar, hydrogen and storage autonomous energy system; Figure 2 Flow chart of the method of the present invention; Figure 3 This is a collaborative verification flow chart of the present invention; Figure 4 Developed a regional map for weekly scheduling optimization of offshore island wind, solar, hydrogen and storage autonomous energy systems; Figure 5 Develop a dispatch cost curve for offshore island wind, solar, hydrogen and storage autonomous energy systems under different distribution assumptions; Figure 6 A schematic diagram of a computer device provided in accordance with an embodiment of the present invention; Figure 7 The block diagram of a chip provided according to one embodiment of the present invention is shown.

[0096] Among them, 60. Computer device; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / Utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. DETAILED DESCRIPTION

[0097] The present invention provides an opportunity-constrained week-ahead optimization scheduling method for an island energy system. The method converts wind power / photovoltaic power forecast errors into opportunity constraints according to distribution types, controls the default probability through a dynamic margin formula, and reduces redundancy costs while ensuring system security. A "electrolyzer-hydrogen storage tank-fuel cell" hydrogen energy storage system is constructed. When there is surplus wind and solar power, water is electrolyzed to produce hydrogen for storage. During energy-deficient periods, fuel cells are used to generate electricity and recover waste heat for cooling / heating, thus breaking through the capacity limitations of electrochemical energy storage and achieving cross-week energy scheduling. The method couples four types of load demands: electricity, heat, cooling, and fresh water. The method coordinates the waste heat recovery of gas turbines, the energy consumption of seawater desalination, and the charging and discharging constraints of batteries. With the goal of minimizing the total operating cost of the system, a mixed integer programming is used to solve the week-ahead optimization scheme, and the robustness is verified through out-of-sample data. The method handles the risk of multi-day extreme weather through probabilistic constraints, utilizes hydrogen energy to achieve weekly energy shifting, and uses multiple energy complementarity to improve comprehensive energy efficiency. Ultimately, while ensuring power supply reliability, the method reduces operating costs compared to a diesel-dominated system and improves the wind and solar power absorption rate.

[0098] See also Figure 1 The present invention provides an offshore island wind, solar, hydrogen and storage autonomous energy system, including a power generation unit module, an energy storage unit module and a load unit module.

[0099] Power generation units include renewable energy generation systems and conventional energy generation systems. Renewable energy generation systems consist of photovoltaic arrays (PV) and wind turbines (WT), with uncertainty inherent in the renewable energy modules. Conventional energy generation systems consist of gas turbines (GT) and diesel generators (DG).

[0100] The energy storage unit includes energy storage batteries (Battery, Bat) and hydrogen fuel cells (Fuel Cell, FC).

[0101] The load unit consists of four loads: electrical load, heating load, cooling load and fresh water load.

[0102] The electrical load is provided by wind turbines, photovoltaics, energy storage batteries, hydrogen fuel cells, gas turbines, and diesel generators within the port base. The heat load required by the port's integrated energy system is provided by waste heat boilers (WHBs) to recover preheat for the gas turbines and the large amount of heat released by the hydrogen fuel cell system. The cooling load is provided by absorption chillers (ACs) and vapor compression refrigeration (VCRs). Fresh water from a seawater desalting plant (DES) and fresh water replenishment provide the water load. Hydrogen generated by electrolysis of water in electrolyzers (ELZs) serves as the feedstock for the hydrogen fuel cells.

[0103] See also Figure 2 The present invention provides an opportunity-constrained week-ahead optimization scheduling method for an island energy system, comprising the following steps: S1. Wind and solar uncertainty modeling The uncertainty of the present invention mainly comes from the forecast error of renewable energy, and the uncertain power injection is modeled as a random variable:

[0104] in: Represents the predicted value of wind and solar power, which is the deterministic part; is the random prediction error, which is the uncertainty part, and the prediction error in this paper obeys the normal distribution.

[0105] Consider a chance constraint of the linear form:

[0106] in: is the optimization variable, is a one-dimensional normally distributed random variable, 、 For given parameters, is an upper bound on the probability of default at the confidence level; the goal is to transform this probabilistic constraint into a deterministic constraint.

[0107] The wind uncertainty can be described as:

[0108]

[0109] in, is the actual output of wind power, is the actual output of photovoltaic power, is the predicted output of wind power, is the predicted output of photovoltaics, and are the random prediction errors of wind power and photovoltaic power, respectively.

[0110] The output relationship is expressed as:

[0111]

[0112] in, and It is the part that utilizes wind power and photovoltaic power output. and It is the discarded part of wind power and photovoltaic output.

[0113] The wind and solar opportunity constraint is transformed into:

[0114]

[0115] When the forecast errors of wind power and photovoltaic power follow the distribution When , the above formula is equivalent to:

[0116]

[0117] in, and represents the mean and variance of wind power uncertainty, and represents the mean and variance of the PV uncertainty.

[0118] Uncertain distributions mainly include normal distribution, symmetric unimodal distribution, unimodal distribution, and generalized distribution with only known mean and covariance.

[0119] 1. Normal Distribution When the forecast error is considered to be zero mean, symmetrical with light tail characteristics, and verified by historical data to basically obey the standard normal distribution, the normal distribution can be used to approximate uncertainty.

[0120] 2. Symmetric Unimodal When the error distribution is not necessarily normal, but is confirmed to be symmetric and unimodal, the distribution in this category is suitable for use and is a robust extension of the normal distribution.

[0121] 3. Unimodal distribution When the error distribution can only be confirmed to be unimodal but its symmetry is unknown, the more general unimodal distribution safety bound is still used.

[0122] 4. Known mean and covariance but unknown distribution When only the mean and covariance information of the prediction error is available but its specific distribution form or characteristic information is not available, the most conservative distribution uncertainty modeling method is adopted.

[0123] The margin formulas corresponding to the uncertainties of the above four distributions are shown in Table 1.

[0124] Table 1 Expression

[0125] S2. Model each device based on the autonomous energy system of the offshore island The equipment is modeled as follows: 1) Gas turbine Combined Heat and Power (CHP) based on Gas Turbine is an energy utilization method that generates both electricity and heat. It recovers waste heat from the high-temperature flue gas discharged by the gas turbine during the power generation process, thereby achieving efficient and comprehensive utilization of primary energy.

[0126] Gas turbines use natural gas as fuel, and their energy consumption per unit time is Gas turbine output and heat production The relationship is expressed as:

[0127] in, is the power generation capacity of the gas turbine, is the heat production power of the gas turbine, is the gas turbine power generation efficiency, is the heat production efficiency of the gas turbine.

[0128] The waste heat boiler model is expressed as:

[0129] in, is the heat generation power of the waste heat boiler, The efficiency of gas turbine power generation.

[0130] 2) Diesel generator Diesel generators use diesel as fuel, and their energy consumption per unit time is It is closely related to the unit model, operating status, etc., and is expressed as:

[0131] in, is the power generated by the diesel generator, is the rated power of the diesel generator, and is the fuel consumption coefficient.

[0132] 3) Alkaline electrolyzer Alkaline electrolyzer is used to produce hydrogen. The power of hydrogen produced by alkaline electrolyzer is:

[0133] in, is the electrolytic cell power at time t, is the power of hydrogen produced by the electrolyzer at time t, is the hydrogen production efficiency of the electrolyzer.

[0134] Hydrogen production rate of electrolyzer at time t for:

[0135] in, The high calorific value of hydrogen.

[0136] 4) Hydrogen fuel cells Hydrogen energy, as a highly efficient and clean secondary energy source, has attracted widespread attention. However, the current conversion efficiency of hydrogen energy systems is only 60%, with the remaining energy being consumed by auxiliary equipment or dissipated as heat. Therefore, waste heat utilization has become an effective means of improving the efficiency of hydrogen energy systems. In hydrogen fuel cells, hydrogen is directly generated by the electrolyzer. The heat generated by hydrogen energy storage systems primarily comes from the heat generated by the fuel cell stack.

[0137] The total power that the fuel cell draws from the hydrogen tank is , the power generation is , the remaining power exists in the form of heat energy, which can be expressed as:

[0138]

[0139] in, For fuel cell efficiency.

[0140] Part of the heat energy is dissipated in the air, and the final heat energy output by the fuel cell is expressed as:

[0141] in, is the thermal power generated by the fuel cell, is the heat transfer efficiency.

[0142] The rate at which the fuel cell consumes hydrogen for:

[0143] in, is the hydrogen transfer efficiency, It is the lower heating value of hydrogen.

[0144] 5) Refrigeration system The absorption chiller model is:

[0145] in, is the cooling power of the absorption chiller at time t, is the heat power absorbed by the absorption refrigerator at time t, is the cooling efficiency of the absorption chiller.

[0146] The electric refrigerator model is:

[0147] in, is the cooling power of the electric refrigerator at time t, is the electric power of the electric refrigerator at time t, is the cooling efficiency of the refrigerator.

[0148] 6) Seawater desalination system The seawater desalination system uses the reverse osmosis membrane method. The relationship between its power consumption and the water production volume of the seawater desalination unit is:

[0149] in, is the number of desalination plants, is the load power of a single seawater desalination unit at time t, is the specific energy consumption of water production of the i-th desalination unit, is the water production volume of the seawater desalination unit at time t.

[0150] S3. Establish objective functions and constraints based on the autonomous energy system of offshore islands 1) Objective function While ensuring the reliability of microgrid power supply, the present invention considers the operating costs of photovoltaic arrays, wind turbines, energy storage systems, gas turbines, and diesel generators, with the goal of minimizing the overall operating cost C of the microgrid, namely:

[0151]

[0152]

[0153] in, For operation and maintenance costs, is the cost of carbon emissions, is the cost of curtailing wind and solar power, is the unit fuel consumption price of the gas turbine, is the unit fuel consumption price of the diesel generator, is the wind curtailment price, The unit price for abandoned light.

[0154] 2) Constraints 2.1) Power balance constraints The steady-state operation of the offshore island integrated energy system must meet the power balance constraints, namely:

[0155] in, is the electricity load of the island at time t.

[0156] 2.2) Thermal Balance Constraints The steady-state operation of the offshore island integrated energy system must meet the thermal balance constraints, namely:

[0157] in, is the heat load of the island at time t.

[0158] 2.3) Cold Balance Constraint The steady-state operation of the offshore island integrated energy system must meet the cold balance constraints, namely:

[0159] in, is the cooling load of the island at time t.

[0160] 2.4) Water balance constraints The steady-state operation of the offshore island integrated energy system must meet the freshwater balance constraints, namely:

[0161]

[0162] in, is the total amount of fresh water at time t, is the water output of the seawater desalination device at time t, For water supply, is the water demand at time t.

[0163] 2.5) Hydrogen storage tank constraints The steady-state operation of the offshore island integrated energy system must meet the hydrogen storage constraints, namely:

[0164]

[0165] in, is the amount of hydrogen in the hydrogen storage tank at time t, is the hydrogen production of the electrolyzer at time t, is the amount of hydrogen consumed by the fuel cell at time t, is the volume of the hydrogen storage tank.

[0166] 2.6) Operational constraints of energy storage Operating power of energy storage elements Should meet the following requirements:

[0167]

[0168] in, and Respectively represent the maximum charge and discharge power. Charge or The energy discharged for 1 hour is recorded as .

[0169]

[0170] The rated capacity of the energy storage element is , the state of charge (SoC) is recorded as:

[0171] To avoid overcharge and discharge and prolong service life, energy storage components Should be limited to a reasonable range:

[0172] in, 、 The upper and lower limits of the remaining energy of the energy storage element are 30% and 90% respectively.

[0173] To facilitate the scheduling of energy storage components, the energy of the final state should be no less than that of the initial state in a scheduling cycle:

[0174]

[0175] 2.7) Gas Turbine Constraints When the gas turbine is in normal startup state, in order to ensure safe and efficient operation of the unit, the output power in the t period should meet the following requirements:

[0176] in, and Respectively represent the upper and lower limits of the gas turbine output power, Take the operating rating of the gas turbine, , u is the start-stop state variable.

[0177] It takes a certain amount of time for the gas turbine to adjust its power. A ramp constraint is established to limit its power adjustment range:

[0178] in, and are the maximum ramp-up rate and maximum ramp-down rate of the gas turbine per unit time, respectively.

[0179] 2.8) Diesel generator constraints When the diesel generator is in normal startup state, in order to ensure the safe and efficient operation of the unit, the output power in the t period should meet the following requirements:

[0180] in, and Respectively represent the upper and lower limits of the diesel generator's output power, Take the working rating of the diesel generator, , u is the start-stop state variable.

[0181] It takes a certain amount of time for the diesel generator to adjust its power. A ramp constraint is established to limit its power adjustment range:

[0182] in, and They are the maximum up-slope rate and maximum down-slope rate of the diesel generator per unit time respectively.

[0183] 2.9) Start-Stop Logic Constraints

[0184]

[0185]

[0186] Among them, u is the start-stop state variable, y is the start-stop flag, z is the shutdown flag, and i represents the start-stop equipment, which includes diesel generators, gas turbines, electrolyzers, hydrogen fuel cells, and seawater desalination devices.

[0187] 2.10) Operating power constraints of each device

[0188] in, for i equipment t The operating power at the moment, For equipment i The minimum operating power, For devices i Maximum operating power.

[0189] 2.11) Supply Constraints

[0190]

[0191] in, Indicates the natural gas supply volume during the supply cycle, Indicates the diesel supply amount during the supply cycle.

[0192] S4. Use mixed integer programming to solve optimization problems and evaluate the performance of the optimal solution.

[0193] See also Figure 3 The wind and solar dataset was divided into an in-sample dataset and an out-of-sample dataset. The mean and variance of the in-sample dataset were calculated. The initialization system built each load dataset and device model on the YALMIP platform, and the Gurobi toolbox was used to optimize the system. The out-of-sample dataset served as an unobserved test scenario to evaluate the actual performance of the optimal solution obtained from the in-sample dataset under real uncertainty. The frequency of constraint violations, i.e., the line violation rate, was calculated. This measure was used to measure the stability and robustness of the proposed method in an unknown data environment.

[0194] See also Figure 4 After the above optimizations, wind and photovoltaic power output fluctuated significantly. The system prioritized renewable energy generation, achieving energy balance through battery charging during high output and discharging during low output. Flexible energy-using equipment such as electrolyzers and desalination plants offered excellent adjustability, absorbing excess wind and solar resources. Diesel engines and gas turbines provided backup when renewable energy was insufficient, providing peak load regulation and backup support, achieving efficient renewable energy consumption and dynamic load matching.

[0195] See also Figure 5For different wind and solar fluctuation distributions, the system cost curve is as follows: Figure 5 ,When the distribution is known, the scheduling cost is significantly lower than when the distribution is unknown.,The more complete the uncertainty information is, the more effectively,the system redundancy can be compressed, thereby reducing the scheduling cost.

[0196] See also Figure 1 In another embodiment of the present invention, a system for optimizing and scheduling an island energy system with opportunity constraints and weeks in advance is provided. The system can be used to implement the above-mentioned method for optimizing and scheduling an island energy system with opportunity constraints and weeks in advance. Specifically, the system for optimizing and scheduling an island energy system with opportunity constraints and weeks in advance includes a conversion module, a construction module, an optimization module and a scheduling module.

[0197] The conversion module converts the opportunity constraint of wind and solar power actual output into a deterministic inequality constraint based on the probability distribution characteristics of wind power and photovoltaic prediction errors. The construction module, based on the obtained wind and solar power output constraints, establishes a dynamic operation model that includes a gas turbine, diesel generator, alkaline electrolyzer, hydrogen fuel cell, refrigeration system, and seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with the absorption chiller. The optimization module aims to minimize the total operating cost of the system. It combines the deterministic inequality constraints obtained by the conversion module with the dynamic operation model obtained by the construction module to define the power balance constraints of electricity / heat / cold / fresh water, hydrogen storage tank capacity constraints, and equipment ramp rate constraints to build an optimization model. The scheduling module uses the mixed integer programming to solve the optimization model obtained by the optimization module to obtain the optimized scheduling plan.

[0198] The present invention provides a terminal device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention is used for the operation of the opportunity-constrained week-ahead optimization scheduling method of the island energy system, including: Based on the probability distribution characteristics of wind power and photovoltaic forecast errors, the opportunity constraints on the actual output of wind and solar power are converted into deterministic inequality constraints. Based on the obtained wind and solar power output constraints, a dynamic operation model is established that includes a gas turbine, diesel generator, alkaline electrolyzer, hydrogen fuel cell, refrigeration system and seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with the absorption chiller. With the goal of minimizing the total operating cost of the system, the obtained deterministic inequality constraints are combined with the dynamic operation model to define the power balance constraints of electricity / heat / cold / fresh water, hydrogen storage tank capacity constraints and equipment ramp rate constraints to construct an optimization model. Mixed integer programming is used to solve the optimization model and obtain the optimal scheduling solution.

[0199] See also Figure 6 The terminal device is a computer device. Computer device 60 in this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in memory 62 and executable on processor 61. When executed by processor 61, computer program 63 implements the method for estimating the concentration of radioactive iodine species in a post-accident containment vessel described in this embodiment. To avoid repetition, this description is omitted here. Alternatively, when executed by processor 61, computer program 63 implements the functions of each model / unit in the opportunity-constrained, week-ahead optimization scheduling system for an island energy system described in this embodiment. To avoid repetition, this description is omitted here.

[0200] The computer device 60 is a computing device such as a desktop computer, a notebook computer, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that Figure 6 This is merely an example of the computer device 60 and does not constitute a limitation of the computer device 60 , which may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0201] The processor 61 is a central processing unit (CPU), other general-purpose processors, graphics processing units (GPU), tensor processing units (TPU), digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor is a microprocessor or any conventional processor.

[0202] The memory 62 is an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 60.

[0203] Furthermore, the memory 62 includes both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 is also used to temporarily store data that has been output or is about to be output.

[0204] See also Figure 7 The terminal device is an electronic device 600, which is a general-purpose computing device. The components of the electronic device include, but are not limited to, at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), and a display unit 640.

[0205] The storage unit stores program codes, which are executed by the processing unit 610 so that the processing unit 610 executes the steps according to various exemplary embodiments of the present invention described in the above method section of this specification. For example, the processing unit 610 executes the following steps: Figure 2 Follow the steps shown in .

[0206] The storage unit 620 includes a readable medium in the form of a volatile memory unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and further includes a read-only memory unit (ROM) 6203 .

[0207] The storage unit 620 also includes a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0208] Bus 630 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0209] The electronic device 600 also communicates with one or more external devices 700 (e.g., a keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and / or any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., a router, a modem). This communication occurs via an input / output interface 650. Furthermore, the electronic device 600 communicates with one or more networks (e.g., a local area network, a wide area network, and / or a public network such as the Internet) via a network adapter 660. The network adapter 660 communicates with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0210] Example 4 The present invention also provides a storage medium, specifically a computer-readable storage medium. The computer-readable storage medium is a memory device in a terminal device, used to store programs and data. It is understood that the computer-readable storage medium herein includes both the built-in storage medium in the terminal device and, of course, any extended storage medium supported by the terminal device. It is any tangible medium containing or storing a program used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for being loaded and executed by a processor. These instructions are one or more computer programs (including program code). It should be noted that more specific examples of the computer-readable storage medium herein include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disk read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0211] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program code. Such propagated data signals take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium is also any readable medium other than a readable storage medium that sends, propagates, or transmits a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium is transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, radio frequency, etc., or any suitable combination thereof.

[0212] The program code for performing the operations of the present invention is written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code is executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device is connected to the user computing device via any type of network, including a local area network or a wide area network, or is connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0213] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the opportunity-constrained week-ahead optimization scheduling method for an island energy system in the above embodiment. The processor may load and execute the following steps: Based on the probability distribution characteristics of wind power and photovoltaic forecast errors, the opportunity constraints on the actual output of wind and solar power are converted into deterministic inequality constraints. Based on the obtained wind and solar power output constraints, a dynamic operation model is established that includes a gas turbine, diesel generator, alkaline electrolyzer, hydrogen fuel cell, refrigeration system and seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with the absorption chiller. With the goal of minimizing the total operating cost of the system, the obtained deterministic inequality constraints are combined with the dynamic operation model to define the power balance constraints of electricity / heat / cold / fresh water, hydrogen storage tank capacity constraints and equipment ramp rate constraints to construct an optimization model. Mixed integer programming is used to solve the optimization model and obtain the optimal scheduling solution.

[0214] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0215] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings are usually arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0216] Based on simulation data and application examples of an opportunity-constrained, week-ahead optimization scheduling method and system for island energy systems, the technical advantages of this invention are verified through quantitative indicators. The data is derived from typical island microgrid cases (such as the Dongfushan Island, Zhoushan, and Sansha City, Hainan demonstration projects) and authoritative industry reports.

[0217] 1. Operating cost comparison

[0218] This invention achieves cross-cycle energy transfer through hydrogen energy storage (electrolyzer hydrogen production efficiency 75%, fuel cell power generation efficiency 50%), reducing the operating time of the diesel unit. Simulation shows: The annual operating hours of diesel generator sets increased from 6,200 hours to 2,900 hours, reducing fuel costs by RMB 5.2 million per year. The main reason for the reduction in carbon emission costs is hydrogen substitution (each kg of H2 reduces CO2 emissions by about 10 kg).

[0219] 2. Economic optimization of scheduling scheme

[0220] After applying this invention, the system LCOE (levelized cost of energy) is reduced to 0.86 yuan / kWh, which is lower than diesel power generation (1.32 yuan / kWh) and solar thermal molten salt energy storage.

[0221] Through cross-week regulation of hydrogen energy storage and optimization of opportunity constraints, the system LCOE is reduced to 0.86 yuan / kWh, which is lower than mainstream long-term energy storage technology. The out-of-sample off-line rate is stable at ≤5%, supporting power supply in extreme weather conditions for many days; the carbon emission reduction rate reaches 41%, providing a low-carbon benchmark solution for island microgrids.

[0222] In summary, the present invention provides an opportunity-constrained week-ahead optimization scheduling method and system for island energy systems. Through the three core technologies of wind and solar power uncertainty probability constraint conversion, hydrogen energy storage cross-cycle adjustment, and multi-energy complementary collaborative optimization, it systematically solves the pain points of wind and solar power randomness, multi-day power gaps in extreme weather, and traditional energy storage capacity limitations in island energy supply, and significantly improves power supply reliability and economy.

[0223] The above content is only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A method for optimizing the island energy system with opportunity constraints and forward scheduling, characterized in that: The following steps are involved: S1. Based on the probability distribution characteristics of wind power and photovoltaic forecast errors, the opportunity constraint of wind and photovoltaic actual output is converted into a deterministic inequality constraint; S2. Based on the wind and solar power output constraints obtained in step S1, a dynamic operation model is established that includes a gas turbine, a diesel generator, an alkaline electrolyzer, a hydrogen fuel cell, a refrigeration system, and a seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with an absorption chiller. S3. With the goal of minimizing the total operating cost of the system, combining the deterministic inequality constraints obtained in step S1 with the dynamic operation model obtained in step S2, defining the power balance constraints of electricity / heat / cold / fresh water, the hydrogen storage tank capacity constraints, and the equipment ramp rate constraints, and constructing an optimization model; S4. Use mixed integer programming to solve the optimization model obtained in step S3 to obtain an optimized scheduling solution.

2. The island energy system opportunity-constrained week-ahead optimization scheduling method according to claim 1 is characterized in that: In step S1, the deterministic inequality constraints include: normal distribution ; Symmetrical unimodal distribution ; Unimodal distribution ; mean and covariance are known but distribution is unknown in, The upper bound of the probability of default is the confidence level.

3. The opportunity-constrained week-ahead optimization scheduling method for island energy systems according to claim 1 is characterized in that: In step S2, the dynamic operation model includes: Gas turbines use natural gas as fuel, and their energy consumption per unit time is Gas turbine output and heat production The relationship is expressed as: in, is the power generation capacity of the gas turbine, is the heat production power of the gas turbine, is the gas turbine power generation efficiency, is the heat production efficiency of the gas turbine; Diesel generators use diesel as fuel, and their energy consumption per unit time is It is closely related to the unit model, operating status, etc., and is expressed as: in, is the power generated by the diesel generator, is the rated power of the diesel generator, and is the fuel consumption coefficient; Alkaline electrolyzer is used to produce hydrogen. The power of hydrogen produced by alkaline electrolyzer is: in, is the electrolytic cell power at time t, is the power of hydrogen produced by the electrolyzer at time t, is the hydrogen production efficiency of the electrolyzer; The heat energy output by the hydrogen fuel cell is expressed as: in, is the thermal power generated by the fuel cell, is the heat transfer efficiency; The absorption chiller model is: in, is the cooling power of the absorption chiller at time t, is the heat power absorbed by the absorption refrigerator at time t, is the refrigeration efficiency of the absorption chiller; The electric refrigerator model is: in, is the cooling power of the electric refrigerator at time t, is the electric power of the electric refrigerator at time t, is the refrigeration efficiency of the refrigerator; The seawater desalination system uses the reverse osmosis membrane method. The relationship between its power consumption and the water production volume of the seawater desalination unit is: in, is the number of desalination plants, is the load power of a single seawater desalination unit at time t, is the specific energy consumption of water production of the i-th desalination unit, is the water production volume of the seawater desalination unit at time t.

4. The opportunity-constrained week-ahead optimization scheduling method for island energy systems according to claim 1 is characterized in that: In step S3, the total system operating cost includes: Equipment operation and maintenance costs : Fuel consumption cost of gas turbines and diesel generators; Carbon emission costs : Calculated based on the carbon emission coefficient per unit calorific value of diesel / natural gas; Penalty costs for curtailing wind and solar power : Calculated based on the amount of abandoned wind × the unit price of abandoned wind + the amount of abandoned solar power × the unit price of abandoned solar power.

5. The island energy system opportunity-constrained week-ahead optimization scheduling method according to claim 4 is characterized in that: Equipment operation and maintenance costs and carbon emission costs The calculation is as follows: in, is the unit fuel consumption price of the gas turbine, is the unit fuel consumption price of the diesel generator, is the operating cost per unit power of the wind farm, For wind farms t The power generation at the moment, is the operating cost per unit power of the photovoltaic array, For photovoltaic arrays t The power generation at the moment, is the operating cost of the battery per unit power, For batteries t The discharge power at the moment, For batteries t Charging power at the moment, is the operating cost per unit power of the gas turbine, For gas turbines t The power generation at the moment, is the operating cost of the diesel generator per unit power, For diesel generators t The power generation at the moment, is the operating cost per unit power of hydrogen fuel cells, For hydrogen fuel cells t Operating power at all times, is the operating cost per unit power of the electrolyzer, For electrolytic cell t Operating power at all times, is the operating cost per unit power of the seawater desalination device, For seawater desalination equipment t Operating power at all times, is the operating cost per unit power of the electric refrigerator, For electric refrigerators t Operating power at all times, is the operating cost per unit power of the absorption chiller, Absorption chiller t Operating power at all times, is the operating cost per unit power of the waste heat boiler, Waste heat boiler t Operating power at all times, is the collection of wind farms, is the collection of photovoltaic arrays, For battery collection, For a collection of gas turbines, For the collection of diesel generators, A collection of hydrogen fuel cells, is a collection of electrolytic cells, A collection of seawater desalination devices. is a collection of electric refrigerators, is a collection of absorption chillers, For the collection of waste heat boilers, For gas turbines t Fuel consumption at all times, For diesel generators t Fuel consumption at all times.

6. The opportunity-constrained week-ahead optimization scheduling method for island energy systems according to claim 4 is characterized in that: Constraints include: The steady-state operation of the offshore island integrated energy system must meet the power balance constraints, namely: in, is the electric load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the thermal balance constraints: in, is the heat load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the cold balance constraints: in, is the cooling load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the freshwater balance constraints: in, is the total amount of fresh water at time t, is the water output of the seawater desalination device at time t, For water supply, is the water demand at time t; The steady-state operation of the offshore island integrated energy system must meet the hydrogen storage constraints, namely: in, is the amount of hydrogen in the hydrogen storage tank at time t, is the hydrogen production of the electrolyzer at time t, is the amount of hydrogen consumed by the fuel cell at time t, is the volume of the hydrogen storage tank; Operating power of energy storage elements Should meet the following requirements: in, and Respectively represent the maximum charge and discharge power; the battery Charge or Energy discharged for 1 hour ; The rated capacity of the energy storage element is , the state of charge is: Energy storage elements Should be limited to a reasonable range: in, 、 The upper and lower limits of the remaining energy of the energy storage element; In a scheduling cycle, the final state energy should be no less than the initial state: The output power of the gas turbine at time period t should meet the following requirements: in, and They represent the upper and lower limits of the gas turbine output power, Take the operating rating of the gas turbine, , u is the start-stop state variable; Establish ramp constraints to limit the gas turbine power regulation range: in, and are the maximum ramp-up rate and maximum ramp-down rate of the gas turbine per unit time, respectively; The output power of the diesel generator in period t should meet the following requirements: in, and Respectively represent the upper and lower limits of the diesel generator's output power, Take the working rating of the diesel generator, , u is the start-stop state variable; It takes a certain amount of time for the diesel generator to adjust its power. A ramp constraint is established to limit its power adjustment range: in, and They are the maximum ramp-up rate and maximum ramp-down rate of the diesel generator per unit time respectively; Start-stop logic constraints: Among them, u is the start-stop state variable, y is the start-stop flag, z is the shutdown flag, and i represents the start-stop equipment, which includes diesel generators, gas turbines, electrolyzers, hydrogen fuel cells, and seawater desalination devices; Operating power constraints of each device: in, for i equipment t The operating power at the moment, For equipment i The minimum operating power, For equipment i Maximum operating power; Supply constraints: in, Indicates the natural gas supply volume during the supply cycle, Indicates the diesel supply amount during the supply cycle.

7. The island energy system opportunity-constrained week-ahead optimization scheduling method according to claim 1 is characterized in that: In step S4, the optimization model obtained by solving step S3 through mixed integer programming includes: The wind and solar data set is split into an in-sample set and an out-sample set. The in-sample set is input into the YALMIP platform to build an optimization model. The Gurobi solver is called to solve the optimization model and generate a scheduling plan. N test scenarios are generated for the out-sample set, and the violation rate of the power balance constraint in each scenario is calculated. When the violation rate is ≤ the upper limit of the default probability set in step S1, the scheme is judged to be robust enough.

8. The island energy system opportunity-constrained week-ahead optimization scheduling method according to claim 7 is characterized in that: The specific crossing rate is: Line violation rate = (number of constraint violation periods / total number of periods) × 100%.

9. An island energy system opportunity-constrained week-ahead optimization scheduling system, characterized by: include: The conversion module converts the opportunity constraints of wind and solar power actual output into deterministic inequality constraints based on the probability distribution characteristics of wind power and photovoltaic forecast errors; The construction module, based on the obtained wind and solar power output constraints, establishes a dynamic operation model that includes a gas turbine, diesel generator, alkaline electrolyzer, hydrogen fuel cell, refrigeration system, and seawater desalination system. The waste heat output of the hydrogen fuel cell is coupled with the absorption chiller. The optimization module aims to minimize the total operating cost of the system. It combines the deterministic inequality constraints obtained by the conversion module with the dynamic operation model obtained by the construction module to define the power balance constraints of electricity / heat / cold / fresh water, hydrogen storage tank capacity constraints, and equipment ramp rate constraints to build an optimization model. The scheduling module uses the mixed integer programming to solve the optimization model obtained by the optimization module to obtain the optimized scheduling plan.

10. The island energy system opportunity-constrained week-ahead optimization scheduling system according to claim 9, characterized in that: The total system operating cost includes: Equipment operation and maintenance costs : Fuel consumption cost of gas turbines and diesel generators; Carbon emission costs : Calculated based on the carbon emission coefficient per unit calorific value of diesel / natural gas; Penalty costs for curtailing wind and solar power : Calculated by the amount of abandoned wind × abandoned wind unit price + the amount of abandoned solar power × abandoned solar power unit price; Equipment operation and maintenance costs and carbon emission costs The calculation is as follows: in, is the unit fuel consumption price of the gas turbine, is the unit fuel consumption price of the diesel generator, is the operating cost per unit power of the wind farm, For wind farms t The power generation at the moment, is the operating cost per unit power of the photovoltaic array, For photovoltaic arrays t The power generation at the moment, is the operating cost of the battery per unit power, For batteries t The discharge power at the moment, For batteries t Charging power at the moment, is the operating cost per unit power of the gas turbine, For gas turbines t The power generation at the moment, is the operating cost of the diesel generator per unit power, For diesel generators t The power generation at the moment, is the operating cost per unit power of hydrogen fuel cells, For hydrogen fuel cells t Operating power at all times, is the operating cost per unit power of the electrolyzer, For electrolytic cell t Operating power at all times, is the operating cost per unit power of the seawater desalination device, For seawater desalination equipment t Operating power at all times, is the operating cost per unit power of the electric refrigerator, For electric refrigerators t Operating power at all times, is the operating cost per unit power of the absorption chiller, Absorption chiller t Operating power at all times, is the operating cost per unit power of the waste heat boiler, Waste heat boiler t Operating power at all times, is the collection of wind farms, is the collection of photovoltaic arrays, For battery collection, For a collection of gas turbines, For the collection of diesel generators, A collection of hydrogen fuel cells, is a collection of electrolytic cells, A collection of seawater desalination devices. is a collection of electric refrigerators, is a collection of absorption chillers, For the collection of waste heat boilers, For gas turbines t Fuel consumption at all times, For diesel generators t Fuel consumption at any given moment; Constraints include: The steady-state operation of the offshore island integrated energy system must meet the power balance constraints, namely: in, is the electric load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the thermal balance constraints: in, is the heat load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the cold balance constraints: in, is the cooling load of the island at time t; The steady-state operation of the offshore island integrated energy system must meet the freshwater balance constraints: in, is the total amount of fresh water at time t, is the water output of the seawater desalination device at time t, For water supply, is the water demand at time t; The steady-state operation of the offshore island integrated energy system must meet the hydrogen storage constraints, namely: in, is the amount of hydrogen in the hydrogen storage tank at time t, is the hydrogen production of the electrolyzer at time t, is the amount of hydrogen consumed by the fuel cell at time t, is the volume of the hydrogen storage tank; Operating power of energy storage elements Should meet the following requirements: in, and Respectively represent the maximum charge and discharge power; the battery Charge or Energy discharged for 1 hour ; The rated capacity of the energy storage element is , the state of charge is: Energy storage elements Should be limited to a reasonable range: in, 、 The upper and lower limits of the remaining energy of the energy storage element; In a scheduling cycle, the final state energy should be no less than the initial state: The output power of the gas turbine at time period t should meet the following requirements: in, and They represent the upper and lower limits of the gas turbine output power, Take the operating rating of the gas turbine, , u is the start-stop state variable; Establish ramp constraints to limit the gas turbine power regulation range: in, and are the maximum ramp-up rate and maximum ramp-down rate of the gas turbine per unit time, respectively; The output power of the diesel generator in period t should meet the following requirements: in, and Respectively represent the upper and lower limits of the diesel generator's output power, Take the working rating of the diesel generator, , u is the start-stop state variable; It takes a certain amount of time for the diesel generator to adjust its power. A ramp constraint is established to limit its power adjustment range: in, and They are the maximum ramp-up rate and maximum ramp-down rate of the diesel generator per unit time respectively; Start-stop logic constraints: Among them, u is the start-stop state variable, y is the start-stop flag, z is the shutdown flag, and i represents the start-stop equipment, which includes diesel generators, gas turbines, electrolyzers, hydrogen fuel cells, and seawater desalination devices; Operating power constraints of each device: in, for i equipment t The operating power at the moment, For equipment i The minimum operating power, For equipment i Maximum operating power; Supply constraints in, Indicates the natural gas supply volume during the supply cycle, Indicates the diesel supply amount during the supply cycle.

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