摘要：作为一种清洁、高效、可持续的无碳能源，氢储能受到了世界各国的广泛关注，被视为现今解决能源危机及可再生能源消纳的关键方法之一。该文针对波动性可再生能源接入的氢储能系统，分析了波动性电源对不同类型的电解制氢设备的影响，并结合不同类型的功率波动特点，从氢储能设备及制氢效果2方面对可再生能源接入氢储能系统产生的影响进行了详细的分析研究。结合理论分析，提出了一种能够降低这种影响的模块化自适应控制策略，并通过仿真建模验证了该策略的有效性。 

&nbsp;ABSTRACT： &nbsp; As a clean, efficient and sustainable carbon-free energy, hydrogen storage has attracted worldwide attention, which has been regarded as one of the key methods to solve the energy crisis and renewable energy consumption problems. This paper analyzes the influence of wave power supply on different types of hydrogen production equipment for the hydrogen energy storage system which is connected by the fluctuating renewable energy. Combined with the characteristics of different types of power fluctuations, the impact of renewable energy access to hydrogen energy storage system is analyzed in detail from two aspects of hydrogen energy storage equipment and hydrogen production effect. Based on the theoretical analysis, a modularized adaptive control strategy is proposed to reduce the influence, whose effectiveness is verified by simulation modeling.<div>&nbsp;</div>

目前高比例风光接入的输电网存在弃风弃光率普遍较高的问题,配置储能设备作为一种具有潜在效用的手段在当前的研究中备受青睐。针对输电网储能配置问题,为达到综合成本减小和弃风弃光率降低的目的,提出了一种基于双层规划模型的输电网氢-电混合储能系统配置方法。首先,对氢-电混合储能系统的特性进行建模,在此基础上建立输电网氢-电混合储能系统功率与容量配置双层规划模型。上层模型以配置储能后年综合成本最小为目标;下层模型以弃风弃光率最小为目标。其后基于蓄电池和氢储能的不同特性,提出一种氢-电混合储能系统配合策略。最后,针对该模型非线性多目标的特点,采用双层迭代粒子群算法与潮流计算相结合进行模型求解。在算例仿真部分,以某含有高比例风光接入地区输电网为例,进行氢-电混合储能系统容量和选址的优化配置,验证了所建模型和所提求解算法的可行性和有效性。提高了风电光伏出力在时序上的转移能力,减少了高碳化石能源的消耗量,降低了弃风弃光率。

At present, the transmission grid with a high proportion of photovoltaic and wind power has a generally high rate of curtailment of wind and solar power. As a potential utility, the configuration of energy storage equipment is favored in current research. Aiming at the problem of energy storage configuration in the transmission network, this paper proposes a configuration method based on a two-layer programming model for the hydrogen-electric hybrid energy storage system in order to reduce the comprehensive cost and the curtailment rate of wind and solar energy. Firstly, the characteristics of the hydrogen-electricity hybrid energy storage system are modeled, and on this basis, a two-layer planning model for the power and capacity allocation of the hydrogen-electricity hybrid energy storage system in the transmission network is established. The upper-layer model aims to minimize the annual comprehensive cost after the energy storage is configured; the lower-layer model aims to minimize the curtailment rate of wind and solar energy. Then, according to the different characteristics of batteries and hydrogen energy storage, a hydrogen-electricity hybrid energy storage system coordination strategy is proposed. Finally, according to the nonlinear multi-objective characteristics of the model, the two-layer iterative particle swarm optimization algorithm is combined with power flow calculation to solve the model. In the simulation part, taking a transmission network with a high proportion of wind and solar power access as an example, the capacity and location of hydrogen-electricity hybrid energy storage system are optimized to verify the feasibility and effectiveness of the model and the proposed solution algorithm. Ultimately, the transfer ability of photovoltaic and wind power output in time series is improved, the consumption of high-carbon fossil energy is reduced, and the curtailment rate of wind and solar energy is reduced.

通过分析电解制氢效率与制氢功率的关系,提出一种基于分段模糊控制电解槽阵列效率提升的策略,基于大规模风-氢耦合系统应用场景,建立考虑风电制氢效率的风电制氢系统优化调度模型,并采用人工蜂群算法求解最优制氢功率。仿真结果表明,所提出的控制策略不仅可保证电解槽的安全运行,同时能提高电解槽的制氢效率,为电解制氢系统在电力系统中的大规模应用提供理论依据。最后,在此基础上,加入电解槽阵列的模块化优化策略,使建立的分段模糊控制器能够统筹安全性、经济性、能效性,以期为氢能在电力系统中的大规模应用提供理论依据。

By analyzing the relationship between the efficiency of electrolyzer and hydrogen production power, this paper proposes a strategy to improve the efficiency of electrolyzer array based on subsection fuzzy control. Based on the scenario of large-scale wind power to hydrogen system, an optimal adjustment model of wind power to hydrogen system considering the efficiency of electrolyzer is established, and the optimal power of hydrogen production is calculated by an artificial bee colony algorithm. The simulation results show that the control strategy proposed in this paper can not only ensure the operation safety of the electrolyzer, but also improve the efficiency of the electrolyzer, providing a theoretical basis for the large-scale electrolyzer of application in the power system. Finally, based on the previous research results, a modular optimization strategy is added to the electrolyzer, enabling the established subsection fuzzy controller to coordinate the safety, economy and energy efficiency, and providing a theoretical basis for the large-scale application of hydrogen energy in the power system.

为解决因风电随机性带来的&#x0201c;弃风&#x0201d;问题,实现宽功率波动下的高效制氢,提出基于最小二乘支持向量机（LSSVM）的超短期组合预测模型,提高风电功率预测鲁棒性。通过变分模态分解（VMD）预处理将风电功率分解为不同带宽的子模态,以降低随机噪声及模态混叠的影响;引入蜻蜓算法（DA）优化LSSVM,建立超短期组合预测模型,以满足电解槽控制的时间分辨率及精度要求。以河北省某风电制氢示范项目为例,验证该算法对于高波动性数据具备更高的预测精度,为风电制氢系统的优化控制提供依据。

针对电化学储能和氢储能的互补特性,提出了一种包含电化学和氢储能的混合储能系统配置和运行的综合优化模型,并提出了智能算法进行求解。该模型基于双层决策优化问题,将混合储能系统配置及运行2个不同时间维度的问题分上下层进行综合求解,并考虑了两者间的相互影响,采用强化学习近端策略优化(proximal policy optimization,PPO)算法求解该双层优化模型。以甘肃省某地区的风光数据,通过对比应用多种传统算法求解结果,验证了所用算法在复杂环境下适应度最高且收敛速度最快。研究结果表明,应用该模型最大可降低24%的弃风、弃光率,有效提升系统综合效益。氢储能作为容量型储能配置不受地形因素限制,适用于多样的应用场景,从而为氢储能这一新型储能形态在全国的广泛配置提供了应用示范。

According to the complementary characteristics of electrochemical energy storage and hydrogen storage, an integrated optimization model for the configuration and operation of a hybrid energy storage system is given, including electrochemical energy storage, hydrogen storage proposed and an intelligent algorithm. The model is based on a two-layer decision optimization problem, in which two different time dimensions of the hybrid energy storage system configuration and operation are solved in upper and lower layers, and the interaction between them is considered. A reinforcement learning proximal policy optimization (PPO) algorithm is used to solve the two-layer optimization model. By comparing the results of applying various traditional algorithms to solve the scenery data of a region in Gansu Province, it is verified that the used algorithm has the highest adaptability and the fastest convergence speed in a complex environment. The results show that the application of this model can reduce the abandoning rate of wind and solar power by 24% and effectively improve the comprehensive benefit of the system, and that hydrogen storage as a capacity-based energy storage configuration is not limited by topographical factors and is suitable for diverse application scenarios, thus providing an application demonstration for the widespread deployment of hydrogen storage, a new form of energy storage, in the whole country.