我国沿海地区经济发达,能源需求量大,探索海上风电制氢为其他行业供能具有现实意义。比较了海上风电输电上岸后的两种利用模式:1)风电售电模式;2)风电制氢模式。首先通过比较碱性(alkaline,ALK)电解槽和质子交换膜(proton exchange membrane,PEM)电解槽的工作特性,建立了制氢系统产氢量模型。其次,建立两种模式的经济分析模型;最后,结合净现值和平准化制氢成本比较了不同风能利用模式的经济性。结果表明在当前技术情景下,氢价取46.93元/kg、风电上网电价取0.531 8元/(kW·h)时,风电制氢模式比风电售电模式更具有经济性,氢价是影响制氢模式经济性的最大因素,而氢价取决于未来氢市场的供需关系,不确定性较大。

The coastal areas of China are economically developed and have a large energy demand. It is of practical significance to explore the production of hydrogen using offshore wind power to supply energy to other industries. This paper compares two utilization modes of offshore wind power after transmission on shore, i.e., direct sales and use for hydrogen production. Firstly, by comparing the power characteristics of alkaline (ALK) and proton exchange membrane (PEM) electrolyzers, the hydrogen production model is established. Secondly, the economic models of the two modes are established. Finally, the economy of different wind energy utilization modes are compared using net present value (NPV) and levelized cost of hydrogen production (LCOH). The results show that, under the current technical scenario, when the hydrogen price is 46.93 yuan/kg and the feed-in electricity price of wind power is 0.5318 yuan/(kW·h), the wind power used for hydrogen production is more economical than the wind power sales mode. The hydrogen price is the biggest factor affecting the economics of the hydrogen production model, where the hydrogen price depends on the supply and demand relationship in the future hydrogen market, and there is great uncertainty.

A semiempirical equation was used to represent the performance characteristics of a 20-cell proton exchange membrane electrolyzer stack. The coefficients of the equation are the exchange current densities and membrane conductivity. These coefficients were determined using experimental data and a nonlinear curve fitting method. The anode exchange current density was found to be 1.65×10−8Acm−2, the cathode exchange current density 0.09Acm−2, and the membrane conductivity 0.075Scm−1. External programmable power supplies were used to obtain the (I‐V) characteristic curve of a commercial proton exchange membrane electrolyzer. Stack current, voltage, and system temperature were monitored while 1A current steps were applied to the electrolyzer stack.

针对复杂工况对光伏制氢系统性能产生不确定性的影响,提出考虑多变量因素影响的光伏制氢系统模型,探索辐照度、温度、膜厚、压力等因素对光伏质子交换膜（PEM）制氢系统的影响。系统首先建立考虑辐照度、温度、膜厚、压力等因素影响的光伏-质子交换膜电解槽-氢储罐的光伏制氢模型,之后对系统进行定量计算和定性分析,并依据实际光伏数据进行实验验证。结果表明,在额定功率范围内,太阳电池输出电流和功率随辐照度的增加而增大,随温度的升高而降低。质子交换膜电解槽电压随辐照度、膜厚、压力的增加而增大,随温度的升高而减小。太阳电池输出功率、质子交换膜电解槽电压的变化趋势与辐照度变化趋势具有一致性。最终计算得到太阳电池系统、质子交换膜电解槽系统和总系统效率分别为16.8%、72.2%和12.1%。

For the uncertain influence of complicated working conditions on the photovoltaic hydrogen production system performance, this paper puts forward a photovoltaic hydrogen production system model that takes into account the influence of multivariable factors and explores the effects of the light intensity, temperature, film thickness, pressure and other factors on the photovoltaic-proton exchange membrane （PEM） hydrogen production system. The PV hydrogen production model of solar cell-proton exchange membrane electrolyzer, which considers the solar irradiance, temperature, film thickness and pressure and other factors, is first established in the system. Then, the system is quantitatively calculated and qualitatively analyzed and is also experimentally verified based on the actual PV data. The results show that within the rated power range, the solar cell output current and power increase with light intensity and decrease with the temperature increase. In addition, the PEM electrolyzer voltage increases with light intensity, film thickness and pressure, and decreases with temperature. The trend of the solar cell output power and PEM electrolyzer voltage are consistent with the trends of the light intensity. At last, the calculation show that there are 16.8%, 72.2% and 12.1% efficiencies for the solar cell system, the PEM electrolyzer system and the total system, respectively.

Proton exchange membrane fuel cells (PEMFC) are a type of the increasingly developed sustainable energy systems which have been turned into one of the most popular of them in the last decade. The performance of these types of fuel cells is the best among the others; however, they can be better by an authentic control to maintain in the maximum efficiency in the operative points during the current ripples. To do this and also to improve the value of the output voltage, the two-phase interleaved boost converter is utilized. Since boost converter has uncertain parameters and disturbances in their essence, using the ordinary methods for the control of them can ignore some of the principal parameters. In this study, a new technique is utilized for optimal control of the proton exchange membrane fuel cells with interval uncertain parameters. Here, we consider the uncertainties in the converter inherent. Because of considering the uncertainties in the system, controllability of the system is first testified based on interval arithmetic. Then, an extended version of the linear quadratic regulator strategy using interval analysis is employed for achieving a reliable and optimal solution. Chebyshev inclusion method is utilized for solving the Pontryagins problem of the LQR problem. Eventually, by solving the interval version of the Riccati equations, the robust range for optimal control of the PEMFC is obtained. The results of the proposed system are finally compared with Monte Carlo method for showing the efficiency of the presented technique.Copyright © 2019 ISA. Published by Elsevier Ltd. All rights reserved.

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.

高比例可再生能源的间歇性进一步加剧了电力系统安全稳定运行风险,使得灵活性资源配置愈发关键,因此有必要开展电力系统灵活性资源规划配置研究。文章提出了一种考虑蓄电池与电制氢设备特性的微网灵活性资源配置与运行协同优化双层模型。上层目标为系统年碳排放量最小与年化综合利润最大,下层目标为系统日运营利润最大,开展满足电-氢负荷下的容量规划案例分析,并设置不同灵活性技术成本下降情景,设计经济性、清洁性、灵活性指标对比评判不同情景下两种技术的竞争力。结果表明:所提优化配置方法能够以较小的经济代价实现系统环境效益的大幅提升,目前蓄电池相较电制氢技术更具综合性优势,但后者在未来具有更大的获益空间和市场潜力。

The intermittence of high proportion of renewable energy further aggravates the insecure operation of power system, which makes flexible resources configuration more critical. Therefore, it is necessary to conduct research on flexible resources planning and configuration of power system. For the multi-energy microgrid, a bi-level collaborative optimization method of configuration and operation of flexible resources is proposed in this paper, considering the characteristics of storage battery and power to hydrogen (P2H) equipment. Taking the minimum total annual carbon emissions and the maximum comprehensive annual profit as the objective functions for the outer layer model, and choosing maximum daily operating profit for the inner layer model, a case study under electricity-hydrogen load is carried out. Then cost reduction scenarios of these two flexibility technologies is depicted, and economic, cleanliness and flexibility indices are designed to compare and evaluate the competitiveness of the two technologies in different conditions. The results show that the proposed optimal configuration method can prominently improve the environmental benefits of the microgrid with less economic cost. At present, compared with P2H technology, storage battery technology has overwhelming advantages, but the former will have greater profit margins and market potential in the future.

电解水制氢(power-to-hydrogen,PtH)装置耦合海上风电运行,在促进风电消纳的同时可以制备绿色氢能,推进工业领域的无碳化进程,因而备受关注。文章开展海上风电制氢微网的实时能量管理策略研究。首先,构建海上风电制氢微网的实时能量管理模型,包含海上风电、电制氢装置以及储氢罐等元件。然后,提出基于近似动态规划(approximate dynamic programming,ADP)的微网实时能量管理策略,采用分段线性函数近似状态值函数以应对不确定性因素。最后,通过算例验证所提策略的有效性和优越性。在所提策略下,海上风电通过电制氢装置就地消纳,实现氢气的提前制备和存储。以具备精准预测技术的理想算例为基准,所提策略在满足正态分布的实时测试场景下,优化准确率平均值大于99%。

Introducing power-to-hydrogen (PtH) into offshore wind farms can assist the integration of wind power and produce green hydrogen, which accelerates decarbonization in industrial sectors and has attracted attention worldwide. In these circumstances, this paper studies the real-time energy management strategy of the offshore wind PtH microgrid. First, the real-time energy management model of the offshore wind PtH microgrid is proposed, including offshore wind farms, PtH devices and hydrogen storage tanks. Then, real-time energy management strategy based on approximate dynamic programming (ADP) is proposed. The value function is approximated by piece-wise linear functions (PLFs) to cope with uncertainties in the microgrid. Finally, the effectiveness and superiority of the proposed strategy is verified by case studies. Under the proposed strategy, offshore wind power can be consumed by PtH, achieving production and storage of hydrogen in advance. On the basis of the ideal case with perfect forecasting, the proposed strategy has an average optimization accuracy of more than 99% in real-time test scenarios with normal distribution.

光伏发电存在间歇性的缺点，需要一个可持续的储能系统来满足需求。介绍光伏-PEM(质子交换膜)储氢系统，将电能转化为氢气储存，后期再通过PEM 燃料电池将氢气转化为电能。该系统包含光伏发电系统、PEM制氢电解槽以及燃料电池等，通过电解水产生氢气，氢气在高压下储存在压缩储罐中以备后用，后期系统有需要时，氢气将通过PEM燃料电池重新转化为电能。光伏发电系统的输出电流由PI控制器控制，以稳定电解槽的输入电流。对于光伏-PEM储氢系统，主要问题是对天气条件的依赖。通过系统建模来模拟光伏-PEM储氢系统的运行过程，评估与太阳能光伏输出电流相关的光照强度对氢气生产、氢气储存以及后期氢气再电气化的影响，为后续有助于缓解与太阳能、风力发电和其他间歇性发电相关的储能问题奠定基础。