<p>在碳达峰与碳中和目标背景下，电制氢技术有望解决我国新型电力系统中可再生能源消纳的瓶颈，不过，纯氢运输成本高，因此常将氢气直接掺入燃气管道运输以降低运输成本。这种情况下，电制氢系统往往需要多台电解槽组合运行才能够满足容量要求，现有研究在电氢耦合网络容量配置和优化过程中通常将电解槽看作整体，忽略了电解槽单体运行特性，这会导致优化结果出现偏差。因此，论文围绕绿电-氢能-混氢天然气耦合网络容量优化问题，开展了下述研究。</p> <p>首先，基于电制氢技术和混氢天然气技术，构建绿电-氢能-混氢天然气耦合网络结构。根据燃气管道压强不同将燃气管道掺氢细分为中、低压管道掺氢和高压管道掺氢，进一步阐述了耦合网络中各组成部分的原理及数学模型，包括发电系统、氢能系统和混氢天然气网络等，为容量优化配置的研究奠定了基础。</p> <p>其次，基于碱性电解槽单体运行特性分析了多电解槽组合运行特性，提出了多电解槽组合运行的双层轮值策略。利用电解槽过载特性进行容量配置，有效减少了配置容量；同时为避免某一台电解槽长期运行在过载状态，将电解槽分为内外两层进行轮值。算例结果表明，提出的双层轮值策略。</p> <p>最后，建立了绿电-氢能-混氢天然气耦合网络容量优化配置模型。以年化总成本最小为目标函数，计及功率、氢气和天然气平衡约束、各设备容量约束及各设备运行约束等，构建了考虑不同压强管道掺氢比约束的优化模型，得到对应的混合整数线性规划问题，并提出经济性、年碳排放量、弃电率以及供气需求下降比指标来评价耦合网络性能。以实际算例数据为例，利用MATLAB平台调用Gurobi求解器求解，验证了所建模型能有效降低系统年化总成本，提高氢能应用的灵活性。</p>

<p>Under the background of carbon peaking and carbon neutrality goals, the electric hydrogen technology is expected to solve the bottleneck of renewable energy consumption in China&#39;s new power system. However, pure hydrogen is expensive to transport, so hydrogen is often blended directly into gas pipelines to reduce transport costs. In this case, multiple electrolyzers are often required to operate in combination to meet the capacity requirements. Existing studies usually consider the electrolyzers as a whole in the capacity configuration and optimisation of the electro-hydrogen coupling network, ignoring the individual operating characteristics of the electrolyzers, which can lead to biased optimisation results. Therefore, the following research has been carried out on the capacity optimisation of the coupled green power-hydrogen-hydrogen hybrid gas network.</p> <p>Firstly, a green electricity-hydrogen energy-hydrogen blending gas coupling network structure is constructed based on the electricity-to-hydrogen technology and hydrogen blending gas technology. According to the different pressure of gas pipelines, the gas pipeline hydrogen doping is subdivided into medium and low pressure pipeline hydrogen doping and high pressure pipeline hydrogen doping. The principles and mathematical models of each component in the coupling network are further elaborated, including the power generation system, the hydrogen energy system and the hydrogen-blended natural gas network, etc., laying the foundation for the research of capacity optimization allocation.</p> <p>Secondly, the combined operation characteristics of multiple electrolysers are analysed based on the single unit operation characteristics of alkaline electrolysers, and a double layer shift strategy is proposed for the combined operation of multiple electrolysers. The capacity allocation is made by using the overload characteristics of the electrolyser, which effectively reduces the allocated capacity; at the same time, in order to avoid a single electrolyser operating in an overload condition for a long period of time, the electrolyser is divided into two layers for rotation. The results show that the proposed double-layer rotation strategy can effectively balance the operating time and fluctuating power of a single electrolyser, thus extending the service life of the electrolyser array.</p> <p>Finally, a capacity optimisation model for the coupled green power-hydrogen energy-hydrogen blending gas network is developed. With the minimum annualised total cost as the objective function and taking into account the power, hydrogen and natural gas balance constraints, capacity constraints of each equipment and operating constraints of each equipment, the optimisation model is constructed considering different pressure pipeline hydrogen blending ratio constraints to obtain the corresponding mixed integer linear programming problem, and the economics, annual carbon emission, abandonment rate and demand reduction ratio of gas supply are proposed to evaluate the performance of the coupled network. Using the actual arithmetic data as an example, the Gurobi solver is invoked using the MATLAB platform to solve the problem, and it is verified that the proposed model can effectively reduce the total annualised system cost and improve the flexibility of hydrogen energy applications.</p>