WO2022166114A1 - 一种考虑柔性氢需求的电氢能源系统调度方法 - Google Patents

一种考虑柔性氢需求的电氢能源系统调度方法 Download PDF

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WO2022166114A1
WO2022166114A1 PCT/CN2021/105807 CN2021105807W WO2022166114A1 WO 2022166114 A1 WO2022166114 A1 WO 2022166114A1 CN 2021105807 W CN2021105807 W CN 2021105807W WO 2022166114 A1 WO2022166114 A1 WO 2022166114A1
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hydrogen
electric
load
period
power
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French (fr)
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李强
韩华春
袁晓冬
李群
吴志
贾勇勇
吴晨雨
吕振华
周苏洋
唐伟佳
陆帅
汪成根
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国网江苏省电力有限公司电力科学研究院
国网江苏省电力有限公司
南京沃克森电力科技有限公司
江苏省电力试验研究院有限公司
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Priority to US17/773,601 priority Critical patent/US20230122201A1/en
Publication of WO2022166114A1 publication Critical patent/WO2022166114A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J15/00—Systems for storing electric energy
    • H02J15/008—Systems for storing electric energy using hydrogen as energy vector
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • Y02A30/60—Planning or developing urban green infrastructure
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/10—Photovoltaic [PV]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

Definitions

  • the invention relates to the technical field of multi-energy flow system scheduling, in particular to an electric hydrogen energy system scheduling method considering flexible hydrogen demand.
  • the electric hydrogen energy system is a new type of energy system based on the electricity-to-gas technology. Through the electricity-to-gas technology, excess electric energy is converted into hydrogen energy and stored, which solves the pain point that electric energy cannot be stored for a long time and on a large scale. These characteristics of the electric hydrogen energy system provide technical support for the large-scale integration of renewable energy into the power system with significant seasonality, outstanding intermittency, and strong uncertainty, so it has a bright prospect in engineering applications, and is getting more and more attention. much attention.
  • the economic operation of the electric hydrogen energy system depends on the co-optimization of electricity and hydrogen energy.
  • the electro-hydrogen coupling effect complicates the system operation problem.
  • the electricity and hydrogen loads in the system have a certain degree of flexibility, and the load can be transferred within a certain period of time, which brings additional flexibility to the system operation, and also makes the scheduling decision of the electric hydrogen energy system an extremely important factor. Challenging puzzles. If the electricity and hydrogen energy flow is not effectively coordinated, on the one hand, the scheduling plan may be physically infeasible, posing a threat to the safe and stable operation of the system, and on the other hand, it will affect the economy of the system operation.
  • the purpose of the present invention is to provide an electric hydrogen energy system scheduling method considering flexible hydrogen demand, which can effectively solve the problem of coordination of electricity and hydrogen energy flow, and consider the flexibility of electricity and hydrogen loads, so as to further provide additional flexibility for system operation.
  • an economical and feasible dispatching plan of the electric-hydrogen integrated energy system can be obtained to ensure the safe, efficient and economical operation of the system.
  • the present invention provides an electric hydrogen energy system scheduling method considering flexible hydrogen demand, including:
  • the above-mentioned electric load flexibility equation, electricity purchase and sale constraint equation, renewable energy output constraint equation, hydrogen load flexibility equation, and electric hydrogen production safety operation constraint equation are used as the objective function.
  • the electric power balance constraint equation is used as the constraint condition, and the electric hydrogen energy system dispatch model is established;
  • the operating parameters of the power system include network parameters, topology, electrical load data and renewable energy output data of the power system
  • the operating parameters of the electrical hydrogen production system include network parameters, topology, hydrogen Load data, equipment type and equipment capacity.
  • the expression of the objective function is:
  • t represents the scheduling period
  • T represents the scheduling period
  • P t grid+ represents the power purchased by the power system from the grid in the t period
  • Re represents the unit cost of the power system selling electricity to the grid in the t period
  • P t grid- represents the power that the power system sells to the grid in the t period
  • c shift represents the unit penalty cost that the power system needs to pay to the user for electrical load transfer
  • P t e,in represent the electrical loads transferred from other time periods in the power system in the t period.
  • the expression of the electrical load flexibility equation is:
  • P t e represents the total electrical load of the power system in the t period
  • P t e,fix represents the fixed electrical load of the power system in the t period
  • P t e,out represents the power system transferred out to other periods in the t period.
  • Electrical load, P t e,in,max represents the maximum value of the electrical load that the power system can transfer from other time periods in the t period
  • P t e,out,max represents the power system that can be transferred out to other time periods in the t period. maximum load.
  • the expression of the electricity purchase and sale constraint equation is:
  • the expression of the renewable energy output constraint equation is:
  • p t PV represents the photovoltaic output dispatch value of the power system in the t period
  • ⁇ t,fore represents the standard deviation of the predicted PV output value of the power system at time t
  • ⁇ represents the confidence level of the PV predicted value
  • the expression of the hydrogen load flexibility equation is:
  • T h represents the length of the supply and demand balance cycle required by the hydrogen load of the electric hydrogen production system
  • k represents the supply and demand balance cycle sequence of the hydrogen load of the electric hydrogen production system
  • P t h represents the hydrogen supply of the users of the electric hydrogen production system at time t. load
  • the expression of the safe operation constraint equation of the electric hydrogen production is:
  • ⁇ P2H represents the conversion efficiency of the electric hydrogen production equipment
  • P t P2H represents the electric power consumed by the electric hydrogen production equipment in the t period
  • ⁇ represents the minimum load level of the electric hydrogen production equipment
  • C P2H represents the capacity of the electric hydrogen production equipment.
  • the expression of the electric power balance constraint equation is:
  • Ptgrid + -Ptgrid- + PtPV - PtP2H Pte .
  • an optimized scheduling result is obtained, including:
  • the mixed integer linear programming method is used to solve the scheduling model of the electric hydrogen energy system, and the optimal scheduling result is obtained.
  • the invention establishes the electricity load flexibility equation, the electricity purchase and sale constraint equation, the renewable energy output constraint equation, the hydrogen load flexibility equation, the electric hydrogen production safety operation constraint equation and the electric power balance constraint equation.
  • the lowest operating cost is the objective function, and an electric-hydrogen energy system scheduling model is constructed.
  • the optimal dispatching results of the electric-hydrogen energy system can be obtained. Since the flexibility of the electric load and the hydrogen load is fully considered, it can be used for the electric-hydrogen integrated energy system. Operation provides additional flexibility to improve system operation economy. Compared with the existing technology, it can effectively solve the problem of synergy between electricity and hydrogen energy flow. At the same time, the flexibility of electricity and hydrogen load is considered, which further provides additional flexibility for system operation.
  • an economical and feasible dispatching plan of the electric-hydrogen integrated energy system can be obtained to ensure the safe, efficient and economical operation of the system.
  • FIG. 1 is a schematic flowchart of an electric hydrogen energy system scheduling method considering flexible hydrogen demand in an embodiment of the present invention
  • FIG. 2 is a schematic diagram of the electrical load and the unit photovoltaic output in a typical electric hydrogen energy system according to an embodiment of the present invention
  • FIG. 3 is a comparison diagram of system economy under different hydrogen load flexibility by adopting an electric hydrogen energy system scheduling method considering flexible hydrogen demand in an embodiment of the present invention
  • FIG. 4 is a schematic diagram of the input electric power of an electric hydrogen production device under different hydrogen load flexibility by adopting an electric hydrogen energy system scheduling method considering flexible hydrogen demand in an embodiment of the present invention
  • FIG. 5 is a schematic diagram of system electric load transfer under different hydrogen load flexibility by adopting an electric hydrogen energy system scheduling method considering flexible hydrogen demand in an embodiment of the present invention.
  • an embodiment of the present invention provides an electric hydrogen energy system scheduling method considering flexible hydrogen demand, including:
  • the electric load in the electric hydrogen energy system has a certain flexibility, and the electric load can be transferred within a certain period of time, and the electric load in the current period can be transferred out to other periods, or transferred into the electric load from other periods.
  • the electrical load flexibility equation can be established according to the operating parameters of the power system.
  • the electric hydrogen energy system can exchange electric power with the upper-level power grid to purchase or sell electricity to the upper-level power grid.
  • the constraint equation of power purchase and sale can also be established.
  • the electric hydrogen energy system can generate electricity through renewable energy sources such as wind power and photovoltaics, and the output constraint equation of renewable energy can also be established according to the operating parameters of the power system.
  • the operating parameters of the power system include network parameters, topology, electrical load data and renewable energy output data of the power system.
  • the hydrogen load in the electric hydrogen energy system also has a certain flexibility, and the hydrogen demand required by users at different time periods in the supply and demand balance cycle is different, and the hydrogen load can be established according to the operating parameters of the electric hydrogen production system.
  • Flexible Equation At the same time, the electric hydrogen production equipment is subject to the safety constraints of the electric hydrogen production system during operation, and the electric hydrogen production safety operation constraint equation can be established according to the operating parameters of the electric hydrogen production system.
  • the operating parameters of the electric hydrogen production system include network parameters, topology, hydrogen load data, equipment type and equipment capacity of the electric hydrogen production system.
  • the electric power of the electric power system in the electric hydrogen energy system and the electric power of the electric hydrogen production system have a certain balance relationship, and a corresponding electric power balance constraint equation can be established.
  • the lowest operating cost of the electric hydrogen energy system is taken as the optimization goal, and each constraint equation established in the above steps is used as the constraint condition to establish the electric hydrogen energy system scheduling model.
  • the established electric hydrogen energy system scheduling model may be a mixed integer linear programming model.
  • the objective function of the electric hydrogen energy system scheduling model is solved, and finally the optimal scheduling result of the electric hydrogen energy system can be obtained.
  • the electric hydrogen energy system scheduling method considering the flexible hydrogen demand provided by the embodiment of the present invention, by establishing the electric load flexibility equation, the electricity purchase and sale constraint equation, the renewable energy output constraint equation, the hydrogen load flexibility equation, the electric hydrogen production Safety operation constraint equation and electric power balance constraint equation, and take the lowest operating cost of the electric hydrogen energy system in the dispatch period as the objective function, construct the electric hydrogen energy system dispatching model, and finally solve the model to obtain the optimal dispatching result of the electric hydrogen energy system. Since the flexibility of electric load and hydrogen load is fully considered, additional flexibility can be provided for the operation of the electric-hydrogen integrated energy system, so as to improve the operating economy of the system.
  • the expression of the objective function is:
  • t represents the scheduling period
  • T represents the scheduling period
  • P t grid+ represents the power purchased by the power system from the grid in the t period
  • Re represents the unit cost of the power system selling electricity to the grid in the t period
  • P t grid- represents the power that the power system sells to the grid in the t period
  • c shift represents the unit penalty cost that the power system needs to pay to the user for electrical load transfer
  • P t e,in represent the electrical loads transferred from other time periods in the power system in the t period.
  • the optimization objective of the operation scheduling of the electric hydrogen energy system is the lowest operating cost in the scheduling period, and the optimization variable is the power P t grid+ that the system purchases from the grid in each time period, and the system sells electricity to the grid in each time period.
  • P t e represents the total electrical load of the power system in the t period
  • P t e,fix represents the fixed electrical load of the power system in the t period
  • P t e,out represents the power system transferred out to other periods in the t period.
  • Electrical load, P t e,in,max represents the maximum value of the electrical load that the power system can transfer from other time periods in the t period
  • P t e,out,max represents the power system that can be transferred out to other time periods in the t period. maximum load.
  • the electric load P t e,in transferred in from other time periods and the electric load P t e,out transferred out to other time periods are both affected by A certain limitation, that is, the flexibility of the electric load in the electric hydrogen energy system is constrained by the above-mentioned electric load flexibility equation.
  • the power P t grid+ and the power P t grid- of electricity purchased from the upper-level power grid within a certain period of time are subject to the exchange of electric power allowed by the system and the power grid.
  • the limit of the maximum value that is, the purchase and sale of electricity to the upper-level power grid in the electric hydrogen energy system is constrained by the above-mentioned constraint equation of electricity purchase and sale.
  • p t PV represents the photovoltaic output dispatch value of the power system in the t period
  • ⁇ t,fore represents the standard deviation of the predicted PV output value of the power system at time t
  • ⁇ represents the confidence level of the PV predicted value
  • the renewable energy in the electric hydrogen energy system is mainly photovoltaic, and the photovoltaic output dispatch value p t PV in a certain period of time is limited by the photovoltaic power generation itself, that is, the output of the renewable energy in the electric hydrogen energy system is subject to the above Constraints of the Renewable Energy Output Constraint Equation.
  • T h represents the length of the supply and demand balance cycle required by the hydrogen load of the electric hydrogen production system
  • k represents the supply and demand balance cycle sequence of the hydrogen load of the electric hydrogen production system
  • P t h represents the hydrogen supply of the users of the electric hydrogen production system at time t. load
  • the fluctuation of the user's hydrogen load P t h in the supply and demand balance cycle in a certain period of time in the electric hydrogen energy system is limited, that is, the flexibility of the hydrogen load in the electric hydrogen energy system is subject to the above-mentioned hydrogen load flexibility equation constraints.
  • ⁇ P2H represents the conversion efficiency of the electric hydrogen production equipment
  • P t P2H represents the electric power consumed by the electric hydrogen production equipment in the t period
  • ⁇ represents the minimum load level of the electric hydrogen production equipment
  • C P2H represents the capacity of the electric hydrogen production equipment.
  • the electric power P t P2H consumed by the electric hydrogen production equipment within a certain period of time by the electric hydrogen energy system is subject to the safety constraints of the electric hydrogen production system, that is, the safe operation of the electric hydrogen energy system is subject to the above-mentioned electric hydrogen production safety operation constraint equation constraint.
  • Ptgrid + -Ptgrid- + PtPV - PtP2H Pte .
  • the electric hydrogen energy system purchases power from the upper power grid P t grid+ , sells power to the upper power grid P t grid- , and the photovoltaic output dispatch value within a certain period of time.
  • step S150 includes:
  • the mixed integer linear programming method is used to solve the dispatching model of the electric hydrogen energy system, and the optimal dispatching results are obtained.
  • the methods for solving optimization problems are mainly divided into two categories: heuristic methods and mathematical optimization methods.
  • the established electric hydrogen energy system scheduling model is a mixed integer linear programming model, which belongs to a mixed integer linear programming problem, and can be solved by using solvers such as Cplex and Gurobi to obtain the optimal scheduling result of the electric hydrogen energy system.
  • the electric-hydrogen conversion efficiency of the electric hydrogen production equipment is set to be 0.613 (that is, 54.3kMh electricity is consumed per 1kg of hydrogen produced), the equipment capacity is 2MW, and the minimum load level is 0.1.
  • the hydrogen supply time scale of the flexible hydrogen load is set to 1h, 6h, 12h, 24h and 168h, respectively, and the corresponding hydrogen demands are 12.5kg/h, 75.0kg/6h, 150.0kg/12h, 300.0kg/24h and 2100.0kg, respectively. /168h, to study the impact of hydrogen demand on the electric hydrogen energy system from the hourly to the weekly scale.
  • Fig. 3 the comparison of system economics of different flexible hydrogen demands under the photovoltaic configuration capacity of 20MW is shown in Fig. 3 .
  • Fig. 4 shows the input electric power results of the flexible electric hydrogen production equipment under different hydrogen loads. It can be seen that in the 1h hydrogen demand constraint, the electric hydrogen production equipment needs to maintain constant power operation to meet the real-time hydrogen demand.
  • the hydrogen load balance period is increased to 6h, the operation flexibility of the electric hydrogen production equipment is rapidly improved, and the main work is 3:00-4:00, 11:00-12:00, 14:00-15 in the one-day scheduling period : 00 and 23: 00-24: 00 during the low electricity price and the peak photovoltaic output, so the system economy has improved, but the electric hydrogen production equipment starts and stops too frequently (starts and stops three times in a day).
  • the electric hydrogen production equipment is further concentrated on working at rated power at noon, and only starts and stops once in a typical day.
  • Fig. 5 shows the electrical load transfer results under different hydrogen load flexibilities.
  • the system mainly transfers the electrical load demand from other periods to the peak photovoltaic output period from 8:00 to 17:00, and it can be found from the demand side response curve that the hydrogen load balancing period is 1h.
  • the volatility is the largest, and then becomes smaller and smaller as the time scale increases. From the above results, it can be found that with the gradual increase of the hydrogen load balancing period (the terminal storage capacity is gradually enhanced), the system has significant effects in equipment operation, transaction with the upper-level power grid, and demand-side response.

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Abstract

一种考虑柔性氢需求的电氢能源系统调度方法，通过建立电负荷柔性方程、购电售电约束方程、可再生能源出力约束方程、氢负荷柔性方程、电制氢安全运行约束方程和电功率平衡约束方程，并以调度周期内电氢能源系统的运行成本最低为目标函数，构建电氢能源系统调度模型，最后求解该模型可以得到电氢能源系统的优化调度结果。与现有技术相比，能够有效解决电、氢能流协同问题，同时考虑了电、氢负荷的柔性，进一步为系统运行提供额外的灵活性，通过所提出的调度方法获得经济可行的电氢综合能源系统调度计划，保证系统安全、高效、经济的运行。

Description

一种考虑柔性氢需求的电氢能源系统调度方法 技术领域
本发明涉及多能流系统调度技术领域，尤其涉及一种考虑柔性氢需求的电氢能源系统调度方法。
背景技术
电氢能源系统是一种基于电转气技术的新型能源系统，通过电转气技术将多余的电能转化成氢能并进行储存，解决了电能不能长期、大规模存储的痛点。电氢能源系统的这些特点为季节性显著、间歇性突出、不确定性强的可再生能源大规模接入电力系统提供了技术支撑，因此在工程应用上具有光明的前景，正得到越来越多的关注。
电氢能源系统的经济运行取决于电、氢能量的协同优化。一方面，电-氢耦合影响使系统运行问题变得十分复杂。另一方面，系统中电、氢负荷具有一定的柔性，即可在一定时段内对负荷进行转移，为系统运行带来了额外灵活性的同时，也使得电氢能源系统的调度决策成为一个极具挑战的难题。如果不对电、氢能流进行有效的协同调度，一方面可能导致调度计划在物理上是不可行的，给系统的安全稳定运行造成威胁，另一方面将影响系统运行的经济性。
鉴于上述问题，本设计人基于从事此类产品工程应用多年丰富的实务经验及专业知识，并配合学理的运用，以期设计考虑柔性氢需求的电氢能源系统调度方法，保证系统安全、高效、经济的运行。
发明内容
本发明的目的是：提供一种考虑柔性氢需求的电氢能源系统调度方法，能够有 效解决电、氢能流协同问题，同时考虑了电、氢负荷的柔性，进一步为系统运行提供额外的灵活性，通过所提出的调度方法获得经济可行的电氢综合能源系统调度计划，保证系统安全、高效、经济的运行。
为了达到上述目的，本发明提供一种考虑柔性氢需求的电氢能源系统调度方法，包括：
根据电力系统的运行参数，建立电负荷柔性方程、购电售电约束方程和可再生能源出力约束方程；
根据电制氢系统的运行参数，建立氢负荷柔性方程和电制氢安全运行约束方程；
利用电力系统和电制氢系统的电功率平衡关系，建立电功率平衡约束方程；
以调度周期内电氢能源系统的运行成本最低为目标函数，以所述电负荷柔性方程、购电售电约束方程、可再生能源出力约束方程、氢负荷柔性方程、电制氢安全运行约束方程和电功率平衡约束方程为约束条件，建立电氢能源系统调度模型；
求解所述电氢能源系统调度模型，得到优化调度结果。
优选地，所述电力系统的运行参数包括电力系统的网络参数、拓扑、电负荷数据和可再生能源出力数据，所述电制氢系统的运行参数包括电制氢系统的网络参数、拓扑、氢负荷数据、设备类型和设备容量。
优选地，所述目标函数的表达式为：
Figure PCTCN2021105807-appb-000001
式中，t代表调度时段，T代表调度周期，
Figure PCTCN2021105807-appb-000002
代表电力系统在t时段向电网购电的单位成本，P t grid+代表电力系统在t时段向电网购电的功率，
Figure PCTCN2021105807-appb-000003
代表电力系统在t时段向电网售电的单位成本，P t grid-代表电力系统在t时段向电网售电的功率，c shift代表电力系统电负荷转移需要向用户支付的单位惩罚成本，P t e,in代表电力系统在t时段从其它时段转入的电负荷。
优选地，所述电负荷柔性方程的表达式为：
Figure PCTCN2021105807-appb-000004
式中，P t e代表电力系统在t时段的总电负荷，P t e,fix代表电力系统在t时段的固定电负荷，P t e,out代表电力系统在t时段转出到其他时段的电负荷，P t e,in,max代表电力系统在t时段从其它时段可转入的电负荷的最大值，P t e,out,max代表电力系统在t时段可转出到其他时段的电负荷的最大值。
优选地，所述购电售电约束方程的表达式为：
Figure PCTCN2021105807-appb-000005
式中，
Figure PCTCN2021105807-appb-000006
代表电力系统在t时段向电网购电时的变量，
Figure PCTCN2021105807-appb-000007
代表电力系统在t时段向电网售电时的变量，
Figure PCTCN2021105807-appb-000008
代表电力系统与电网所允许交换电功率的最大值。
优选地，所述可再生能源出力约束方程的表达式为：
Figure PCTCN2021105807-appb-000009
式中，p t PV代表电力系统在t时段的光伏出力调度值，
Figure PCTCN2021105807-appb-000010
代表电力系统在t时段的光伏出力预测值，σ t,fore代表电力系统在t时段的光伏出力预测值的标准差，
Figure PCTCN2021105807-appb-000011
代表标准正态分布N(0,1)的逆累计分布函数，η代表光伏预测值的置信水平。
优选地，所述氢负荷柔性方程的表达式为：
Figure PCTCN2021105807-appb-000012
式中，T h代表电制氢系统的氢负荷所需的供需平衡周期长度，k代表电制氢系统的氢负荷的供需平衡周期序列，P t h代表电制氢系统在t时段用户的氢负荷；
Figure PCTCN2021105807-appb-000013
代表电制氢系统在第k个供需平衡周期内用户所需的氢需求。
优选地，所述电制氢安全运行约束方程的表达式为：
Figure PCTCN2021105807-appb-000014
式中，η P2H代表电制氢设备的转化效率，P t P2H代表在t时段电制氢设备消耗的电功率，λ代表电制氢设备的最小负载水平，
Figure PCTCN2021105807-appb-000015
代表在t时段电制氢设备的运行状态，C P2H代表电制氢设备的容量。
优选地，所述电功率平衡约束方程的表达式为：
P t grid+-P t grid-+P t PV-P t P2H＝P t e。
优选地，所述求解所述电氢能源系统调度模型，得到优化调度结果，包括：
利用混合整数线性规划法求解所述电氢能源系统调度模型，得到优化调度结果。
本发明至少具有以下有益效果：
本发明通过建立电负荷柔性方程、购电售电约束方程、可再生能源出力约束方程、氢负荷柔性方程、电制氢安全运行约束方程和电功率平衡约束方程，并以调度周期内电氢能源系统的运行成本最低为目标函数，构建电氢能源系统调度模型，最后求解该模型可以得到电氢能源系统的优化调度结果，由于充分考虑了电负荷和氢负荷的柔性，可以为电氢综合能源系统运行提供额外的灵活性，以提高系统运行经济性，与现有技术相比，能够有效解决电、氢能流协同问题，同时考虑了电、氢负荷的柔性，进一步为系统运行提供额外的灵活性，通过所提出的调度方法获得经济 可行的电氢综合能源系统调度计划，保证系统安全、高效、经济的运行。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例中考虑柔性氢需求的电氢能源系统调度方法的流程示意图；
图2为本发明实施例中典型电氢能源系统中的电负荷和单位光伏出力的示意图；
图3为本发明实施例中采用考虑柔性氢需求的电氢能源系统调度方法在不同氢负荷柔性下系统经济性的对比图；
图4为本发明实施例中采用考虑柔性氢需求的电氢能源系统调度方法在不同氢负荷柔性下电制氢设备输入电功率的示意图；
图5为本发明实施例中采用考虑柔性氢需求的电氢能源系统调度方法在不同氢负荷柔性下系统电负荷转移的示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。
需要说明的是，当元件被称为“固定于”另一个元件，它可以直接在另一个元件上或者也可以存在居中的元件。当一个元件被认为是“连接”另一个元件，它可以是直接连接到另一个元件或者可能同时存在居中元件。本文所使用的术语“垂直的”、“水平的”、“左”、“右”以及类似的表述只是为了说明的目的，并不表示是唯 一的实施方式。
除非另有定义，本文所使用的所有的技术和科学术语与属于本发明的技术领域的技术人员通常理解的含义相同。在本发明的说明书中所使用的术语只是为了描述具体的实施例的目的，不是旨在于限制本发明。本文所使用的术语“及/或”包括一个或多个相关的所列项目的任意的和所有的组合。
请参阅图1，本发明实施例提供一种考虑柔性氢需求的电氢能源系统调度方法，包括：
S110、根据电力系统的运行参数，建立电负荷柔性方程、购电售电约束方程和可再生能源出力约束方程。
本发明实施例中，电氢能源系统中的电负荷具有一定的柔性，可以在一定时段内对电负荷进行转移，将当前时段的电负荷转出到其他时段，或者从其他时段转入电负荷到当前时段，根据电力系统的运行参数可以建立电负荷柔性方程。同时，电氢能源系统可以与上级电网进行电功率交换，向上级电网购电或售电，根据电力系统的运行参数还可以建立购电售电约束方程。另外，电氢能源系统可以通过风电和光伏等可再生能源进行发电，根据电力系统的运行参数还可以建立可再生能源出力约束方程。
具体实施时，电力系统的运行参数包括电力系统的网络参数、拓扑、电负荷数据和可再生能源出力数据。
S120、根据电制氢系统的运行参数，建立氢负荷柔性方程和电制氢安全运行约束方程。
本发明实施例中，电氢能源系统中的氢负荷同样具有一定的柔性，在供需平衡周期内用户在不同时段所需的氢需求有所不同，根据电制氢系统的运行参数可以建立氢负荷柔性方程。同时，电制氢设备在运行时受到电制氢系统的安全约束，根据电制氢系统的运行参数可以建立电制氢安全运行约束方程。
具体实施时，电制氢系统的运行参数包括电制氢系统的网络参数、拓扑、氢负 荷数据、设备类型和设备容量。
S130、利用电力系统和电制氢系统的电功率平衡关系，建立电功率平衡约束方程。
本发明实施例中，电氢能源系统中的电力系统和电制氢系统的电功率具有一定的平衡关系，可以建立相应的电功率平衡约束方程。
S140、以调度周期内电氢能源系统的运行成本最低为目标函数，以电负荷柔性方程、购电售电约束方程、可再生能源出力约束方程、氢负荷柔性方程、电制氢安全运行约束方程和电功率平衡约束方程为约束条件，建立电氢能源系统调度模型。
本发明实施例中，在调度周期内，以电氢能源系统的运行成本最低为优化目标，并将上述步骤中建立各个约束方程作为约束条件，建立电氢能源系统调度模型。具体实施时，所建立的电氢能源系统调度模型可以是混合整数线性规划模型。
S150、求解电氢能源系统调度模型，得到优化调度结果。
本发明实施例中，在满足上述步骤中建立的约束条件前提下，求解该电氢能源系统调度模型的目标函数，最终可以得到电氢能源系统的优化调度结果。
以上可知，本发明实施例提供的考虑柔性氢需求的电氢能源系统调度方法，通过建立电负荷柔性方程、购电售电约束方程、可再生能源出力约束方程、氢负荷柔性方程、电制氢安全运行约束方程和电功率平衡约束方程，并以调度周期内电氢能源系统的运行成本最低为目标函数，构建电氢能源系统调度模型，最后求解该模型可以得到电氢能源系统的优化调度结果，由于充分考虑了电负荷和氢负荷的柔性，可以为电氢综合能源系统运行提供额外的灵活性，以提高系统运行经济性，与现有技术相比，能够有效解决电、氢能流协同问题，同时考虑了电、氢负荷的柔性，进一步为系统运行提供额外的灵活性，通过所提出的调度方法获得经济可行的电氢综合能源系统调度计划，保证系统安全、高效、经济的运行。
具体的，上述实施例中，目标函数的表达式为：
Figure PCTCN2021105807-appb-000016
式中，t代表调度时段，T代表调度周期，
Figure PCTCN2021105807-appb-000017
代表电力系统在t时段向电网购电的单位成本，P t grid+代表电力系统在t时段向电网购电的功率，
Figure PCTCN2021105807-appb-000018
代表电力系统在t时段向电网售电的单位成本，P t grid-代表电力系统在t时段向电网售电的功率，c shift代表电力系统电负荷转移需要向用户支付的单位惩罚成本，P t e,in代表电力系统在t时段从其它时段转入的电负荷。
本发明实施例中，电氢能源系统运行调度的优化目标为调度周期内运行成本最低，优化变量为系统在每个时段向电网购电的功率P t grid+、系统在每个时段向电网售电的功率P t grid-和系统在每个时段从其它时段转入的电负荷P t e,in。
进一步地，上述实施例中，电负荷柔性方程的表达式为：
Figure PCTCN2021105807-appb-000019
式中，P t e代表电力系统在t时段的总电负荷，P t e,fix代表电力系统在t时段的固定电负荷，P t e,out代表电力系统在t时段转出到其他时段的电负荷，P t e,in,max代表电力系统在t时段从其它时段可转入的电负荷的最大值，P t e,out,max代表电力系统在t时段可转出到其他时段的电负荷的最大值。
本发明实施例中，电氢能源系统在一定时段内对电负荷进行转移时，从其它时段转入的电负荷P t e,in和转出到其他时段的电负荷P t e,out均受到一定的限制，即电氢能源系统中电负荷具有的柔性受到上述电负荷柔性方程的约束。
更进一步地，上述实施例中，购电售电约束方程的表达式为：
Figure PCTCN2021105807-appb-000020
式中，
Figure PCTCN2021105807-appb-000021
代表电力系统在t时段向电网购电时的变量，
Figure PCTCN2021105807-appb-000022
代表电力系统在t时段向电网售电时的变量，
Figure PCTCN2021105807-appb-000023
代表电力系统与电网所允许交换电功率的最大值。
本发明实施例中，电氢能源系统在与上级电网进行电功率交换时，在一定时段内向上级电网购电的功率P t grid+和售电的功率P t grid-受到系统与电网所允许交换电功率的最大值的限制，即电氢能源系统中向上级电网的购电售电受到上述购电售电约束方程的约束。
更进一步地，上述实施例中，可再生能源出力约束方程的表达式为：
Figure PCTCN2021105807-appb-000024
式中，p t PV代表电力系统在t时段的光伏出力调度值，
Figure PCTCN2021105807-appb-000025
代表电力系统在t时段的光伏出力预测值，σ t,fore代表电力系统在t时段的光伏出力预测值的标准差，
Figure PCTCN2021105807-appb-000026
代表标准正态分布N(0,1)的逆累计分布函数，η代表光伏预测值的置信水平。
本发明实施例中，电氢能源系统中的可再生能源主要为光伏，且光伏在一定时段内出力调度值p t PV受到光伏发电本身的限制，即电氢能源系统中可再生能源出力受到上述可再生能源出力约束方程的约束。
更进一步地，上述实施例中，氢负荷柔性方程的表达式为：
Figure PCTCN2021105807-appb-000027
式中，T h代表电制氢系统的氢负荷所需的供需平衡周期长度，k代表电制氢系统的氢负荷的供需平衡周期序列，P t h代表电制氢系统在t时段用户的氢负荷；
Figure PCTCN2021105807-appb-000028
代 表电制氢系统在第k个供需平衡周期内用户所需的氢需求。
本发明实施例中，电氢能源系统在一定时段内用户的氢负荷P t h在供需平衡周期内的波动受到一定的限制，即电氢能源系统中氢负荷具有的柔性受到上述氢负荷柔性方程的约束。
更进一步地，上述实施例中，电制氢安全运行约束方程的表达式为：
Figure PCTCN2021105807-appb-000029
式中，η P2H代表电制氢设备的转化效率，P t P2H代表在t时段电制氢设备消耗的电功率，λ代表电制氢设备的最小负载水平，
Figure PCTCN2021105807-appb-000030
代表在t时段电制氢设备的运行状态，C P2H代表电制氢设备的容量。
本发明实施例中，电氢能源系统在一定时段内电制氢设备消耗的电功率P t P2H受到电制氢系统的安全约束，即电氢能源系统安全运行受到上述电制氢安全运行约束方程的约束。
更进一步地，上述实施例中，电功率平衡约束方程的表达式为：
P t grid+-P t grid-+P t PV-P t P2H＝P t e。
本发明实施例中，电氢能源系统在一定时段内向上级电网购电的功率P t grid+、向上级电网售电的功率P t grid-、光伏出力调度值
Figure PCTCN2021105807-appb-000031
和电制氢设备消耗的电功率P t P2H与电氢能源系统的总电负荷P t e之间具有平衡关系，受到上述电功率平衡约束方程的约束。
作为本发明一种优选的实施例，步骤S150包括：
利用混合整数线性规划法求解电氢能源系统调度模型，得到优化调度结果。
需要说明的是，优化问题的求解方法主要分为两大类：即启发式方法和数学优 化方法。本发明实施例中，所建立的电氢能源系统调度模型为混合整数线性规划模型，属于混合整数线性规划问题，可以采用Cplex、Gurobi等求解器进行求解，得到电氢能源系统的优化调度结果。
下面，结合具体的案例对本发明实施例提供的考虑柔性氢需求的电氢能源系统调度方法在经济性方面的优点进行验证。
设置调度周期为1年，时间间隔为1h。为使仿真结果更具实用性，通过采集我国东部沿海某地区的小时级年电力负荷曲线作为电负荷数据，利用美国国家可再生能源实验室开发的PVWatts Calculator计算年小时级单位光伏发电数据。电负荷和单位光伏出力如图2所示。
此外，设电制氢设备的电氢转换效率为0.613(即每生产1kg氢需消耗54.3kMh电)，设备容量为2MW，最小负载水平为0.1。
将柔性氢负荷的供氢时间尺度分别设置为1h、6h、12h、24h和168h，对应的氢需求分别为12.5kg/h、75.0kg/6h、150.0kg/12h、300.0kg/24h和2100.0kg/168h，研究从小时级到周级尺度下氢需求对电氢能源系统的影响。为了验证本发明所提出的方法在经济性方面的优势，光伏配置容量为20MW下不同柔性氢需求的系统经济性对比情况如图3所示。
从图3中可以看出，不同光伏配置容量下，系统年运行成本均随着供氢时间尺度的增加而降低。具体地，随着时间尺度从1h到6h，系统的购电成本在不同光伏配置容量下均大幅降低，进而使系统总费用降低。随着时间尺度从6h到168h，系统的成本降低逐渐放缓，后期变化很小。以上结果说明，随着柔性氢需求供氢时间尺度的增加，系统购电费用、售电费用和补贴费用均逐渐降低，这有利于缓解对上级电网和需求侧响应的依赖作用，同时验证了本发明实施例所提出的调度方法在运行经济性方面的优势。
请参阅图4，图4展示了不同氢负荷柔性下电制氢设备的输入电功率结果。可以看出，在1h氢需求约束中，电制氢设备需保持恒功率运行来满足实时的用氢需求。当氢负荷平衡周期增加到6h时，电制氢设备运行灵活性迅速提升，在一天的调度周 期内主要工作于3：00-4：00,11：00-12：00，14：00-15：00和23：00-24:00电价低谷和光伏出力高峰时段，因此系统经济性有所提升，但电制氢设备启停过于频繁(一天内启停三次)。而随着氢负荷平衡周期的进一步增加，电制氢设备进一步集中于在中午时段以额定功率进行工作，且在一个典型日内只启停一次。
请参阅图5，图5展示了不同氢负荷柔性下的电负荷转移结果。可以看出，不同氢负荷平衡周期下系统主要将其他时段的电负荷需求转移到8：00-17:00时段光伏出力高峰时段，且通过需求侧响应曲线可以发现，氢负荷平衡周期为1h时波动最大，随后随着时间尺度增加波动越来越小。以上结果可以发现，随着氢负荷平衡周期逐渐增大(终端存储能力逐渐增强)，系统在设备运行、与上级电网交易和需求侧响应等方面效果显著。
本行业的技术人员应该了解，本发明不受上述实施例的限制，上述实施例和说明书中描述的只是说明本发明的原理，在不脱离本发明精神和范围的前提下，本发明还会有各种变化和改进，这些变化和改进都落入要求保护的本发明范围内。本发明要求保护范围由所附的权利要求书及其等效物界定。

Claims (10)

  1. 一种考虑柔性氢需求的电氢能源系统调度方法，其特征在于，包括：
    根据电力系统的运行参数，建立电负荷柔性方程、购电售电约束方程和可再生能源出力约束方程；
    根据电制氢系统的运行参数，建立氢负荷柔性方程和电制氢安全运行约束方程；
    利用电力系统和电制氢系统的电功率平衡关系，建立电功率平衡约束方程；
    以调度周期内电氢能源系统的运行成本最低为目标函数，以所述电负荷柔性方程、购电售电约束方程、可再生能源出力约束方程、氢负荷柔性方程、电制氢安全运行约束方程和电功率平衡约束方程为约束条件，建立电氢能源系统调度模型；
    求解所述电氢能源系统调度模型，得到优化调度结果。
  2. 根据权利要求1所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述电力系统的运行参数包括电力系统的网络参数、拓扑、电负荷数据和可再生能源出力数据，所述电制氢系统的运行参数包括电制氢系统的网络参数、拓扑、氢负荷数据、设备类型和设备容量。
  3. 根据权利要求1所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述目标函数的表达式为：
    Figure PCTCN2021105807-appb-100001
    式中，t代表调度时段，T代表调度周期，
    Figure PCTCN2021105807-appb-100002
    代表电力系统在t时段向电网购电的单位成本，P t grid+代表电力系统在t时段向电网购电的功率，
    Figure PCTCN2021105807-appb-100003
    代表电力系统在t时段向电网售电的单位成本，P t grid-代表电力系统在t时段向电网售电的功率，c shift代表电力系统电负荷转移需要向用户支付的单 位惩罚成本，P t e,in代表电力系统在t时段从其它时段转入的电负荷。
  4. 根据权利要求3所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述电负荷柔性方程的表达式为：
    Figure PCTCN2021105807-appb-100004
    式中，P t e代表电力系统在t时段的总电负荷，P t e,fix代表电力系统在t时段的固定电负荷，P t e,out代表电力系统在t时段转出到其他时段的电负荷，P t e,in,max代表电力系统在t时段从其它时段可转入的电负荷的最大值，P t e,out,max代表电力系统在t时段可转出到其他时段的电负荷的最大值。
  5. 根据权利要求4所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述购电售电约束方程的表达式为：
    Figure PCTCN2021105807-appb-100005
    式中，
    Figure PCTCN2021105807-appb-100006
    代表电力系统在t时段向电网购电时的变量，
    Figure PCTCN2021105807-appb-100007
    代表电力系统在t时段向电网售电时的变量，
    Figure PCTCN2021105807-appb-100008
    代表电力系统与电网所允许交换电功率的最大值。
  6. 根据权利要求5所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述可再生能源出力约束方程的表达式为：
    Figure PCTCN2021105807-appb-100009
    式中，
    Figure PCTCN2021105807-appb-100010
    代表电力系统在t时段的光伏出力调度值，
    Figure PCTCN2021105807-appb-100011
    代表电力系统在t时段的光伏出力预测值，σ t,fore代表电力系统在t时段的光伏出力预测值的标准差，
    Figure PCTCN2021105807-appb-100012
    代表标准正态分布N(0,1)的逆累计分布函数，η代表光伏预测值的置信水平。
  7. 根据权利要求6所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述氢负荷柔性方程的表达式为：
    Figure PCTCN2021105807-appb-100013
    式中，T h代表电制氢系统的氢负荷所需的供需平衡周期长度，k代表电制氢系统的氢负荷的供需平衡周期序列，P t h代表电制氢系统在t时段用户的氢负荷；
    Figure PCTCN2021105807-appb-100014
    代表电制氢系统在第k个供需平衡周期内用户所需的氢需求。
  8. 根据权利要求7所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述电制氢安全运行约束方程的表达式为：
    Figure PCTCN2021105807-appb-100015
    式中，η P2H代表电制氢设备的转化效率，P t P2H代表在t时段电制氢设备消耗的电功率，λ代表电制氢设备的最小负载水平，
    Figure PCTCN2021105807-appb-100016
    代表在t时段电制氢设备的运行状态，C P2H代表电制氢设备的容量。
  9. 根据权利要求8所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述电功率平衡约束方程的表达式为：
    P t grid+-P t grid-+P t PV-P t P2H＝P t e。
  10. 根据权利要求1所述的考虑柔性氢需求的电氢能源系统调度方法，其特征在于，所述求解所述电氢能源系统调度模型，得到优化调度结果，包括：
    利用混合整数线性规划法求解所述电氢能源系统调度模型，得到优化调度结果。
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115483694A (zh) * 2022-10-24 2022-12-16 珠海康晋电气股份有限公司 基于分布式电网数据的电力节能调度系统
CN115545579A (zh) * 2022-12-01 2022-12-30 国网浙江义乌市供电有限公司 一种用于用户柔性资源的聚合智控方法和系统
CN116579115A (zh) * 2023-07-11 2023-08-11 国网能源研究院有限公司 电、氢协同互动的系统规划方法及装置
CN116581742A (zh) * 2023-05-16 2023-08-11 淮阴工学院 一种基于变色龙算法调控智慧云平台柔性电负荷调度系统及方法
CN117408091A (zh) * 2023-12-14 2024-01-16 国网浙江省电力有限公司电力科学研究院 考虑安全性风险的电-氢储能系统优化设计方法及系统

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112952805A (zh) * 2021-02-08 2021-06-11 国网江苏省电力有限公司电力科学研究院 一种考虑柔性氢需求的电氢能源系统调度方法
CN114156868B (zh) * 2021-11-11 2023-09-26 华南理工大学 一种考虑电氢协调的微网调度方法
CN115079564B (zh) * 2022-07-21 2022-11-04 清华四川能源互联网研究院 区域电氢系统脱碳路径规划优化方法
CN115498664A (zh) * 2022-09-28 2022-12-20 国网浙江省电力有限公司杭州供电公司 一种结合柔性直流配电网络的氢电耦合综合能源系统
CN116646993B (zh) * 2023-07-27 2023-10-03 国网能源研究院有限公司 电氢耦合系统协同程度测算方法、系统、装置及存储介质
CN117639069A (zh) * 2023-11-28 2024-03-01 国网青海省电力公司清洁能源发展研究院 一种适用于偏远农牧区的光-氢-储综合能源系统

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140277599A1 (en) * 2013-03-13 2014-09-18 Oracle International Corporation Innovative Approach to Distributed Energy Resource Scheduling
CN110288152A (zh) * 2019-06-25 2019-09-27 河海大学 考虑电/热柔性负荷的区域综合能源系统储能配置方法
CN110889600A (zh) * 2019-11-13 2020-03-17 国家电网有限公司 一种考虑柔性热负荷的区域综合能源系统优化调度方法
CN111027846A (zh) * 2019-12-06 2020-04-17 东南大学 一种考虑热氢联产的电氢综合能源系统及其容量配置方法
CN111144620A (zh) * 2019-12-06 2020-05-12 东南大学 一种考虑季节储氢的电氢综合能源系统及其鲁棒规划方法
CN112952805A (zh) * 2021-02-08 2021-06-11 国网江苏省电力有限公司电力科学研究院 一种考虑柔性氢需求的电氢能源系统调度方法

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107196294A (zh) * 2017-06-16 2017-09-22 国网江苏省电力公司电力科学研究院 源网荷互动模式下微电网多时间尺度自适应能量调度方法
US20210027862A1 (en) * 2018-03-30 2021-01-28 Board Of Trustees Of Michigan State University Systems and methods for drug design and discovery comprising applications of machine learning with differential geometric modeling
CN108539784B (zh) * 2018-04-13 2020-01-14 华南理工大学 基于需求侧响应的微电网最优机组及分时电价的优化方法
CN109861290A (zh) * 2019-03-14 2019-06-07 国网上海市电力公司 一种考虑多种柔性负荷的综合能源系统优化调度方法
CN110009152B (zh) * 2019-04-03 2021-12-07 东南大学 一种考虑电转气和不确定性的区域综合能源系统运行鲁棒优化方法
EP4066367A4 (en) * 2019-11-27 2024-01-03 Robert F Cruickshank Iii OPTIMIZED LOAD SHAPING SYSTEM, METHOD AND APPARATUS FOR OPTIMIZING ENERGY PRODUCTION AND CONSUMPTION
CN111738502B (zh) * 2020-06-15 2022-07-22 上海交通大学 促进富余风电消纳的多能互补系统需求响应运行优化方法
CN112086960B (zh) * 2020-09-03 2021-10-01 东北电力大学 基于模型预测控制的电氢耦合系统灵活裕度计算方法
CN112290533A (zh) * 2020-09-17 2021-01-29 国家电网公司西南分部 一种氢能-天然气混合储能的综合能源微电网调度方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140277599A1 (en) * 2013-03-13 2014-09-18 Oracle International Corporation Innovative Approach to Distributed Energy Resource Scheduling
CN110288152A (zh) * 2019-06-25 2019-09-27 河海大学 考虑电/热柔性负荷的区域综合能源系统储能配置方法
CN110889600A (zh) * 2019-11-13 2020-03-17 国家电网有限公司 一种考虑柔性热负荷的区域综合能源系统优化调度方法
CN111027846A (zh) * 2019-12-06 2020-04-17 东南大学 一种考虑热氢联产的电氢综合能源系统及其容量配置方法
CN111144620A (zh) * 2019-12-06 2020-05-12 东南大学 一种考虑季节储氢的电氢综合能源系统及其鲁棒规划方法
CN112952805A (zh) * 2021-02-08 2021-06-11 国网江苏省电力有限公司电力科学研究院 一种考虑柔性氢需求的电氢能源系统调度方法

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115483694A (zh) * 2022-10-24 2022-12-16 珠海康晋电气股份有限公司 基于分布式电网数据的电力节能调度系统
CN115483694B (zh) * 2022-10-24 2023-07-04 珠海康晋电气股份有限公司 基于分布式电网数据的电力节能调度系统
CN115545579A (zh) * 2022-12-01 2022-12-30 国网浙江义乌市供电有限公司 一种用于用户柔性资源的聚合智控方法和系统
CN116581742A (zh) * 2023-05-16 2023-08-11 淮阴工学院 一种基于变色龙算法调控智慧云平台柔性电负荷调度系统及方法
CN116581742B (zh) * 2023-05-16 2024-02-23 淮阴工学院 一种基于变色龙算法调控智慧云平台柔性电负荷调度系统及方法
CN116579115A (zh) * 2023-07-11 2023-08-11 国网能源研究院有限公司 电、氢协同互动的系统规划方法及装置
CN116579115B (zh) * 2023-07-11 2023-09-26 国网能源研究院有限公司 电、氢协同互动的系统规划方法及装置
CN117408091A (zh) * 2023-12-14 2024-01-16 国网浙江省电力有限公司电力科学研究院 考虑安全性风险的电-氢储能系统优化设计方法及系统
CN117408091B (zh) * 2023-12-14 2024-03-26 国网浙江省电力有限公司电力科学研究院 考虑安全性风险的电-氢储能系统优化设计方法及系统

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