First industrial-scale Power-to-Methanol plants are starting to be deployed in various geographic locations to tackle the problem of high greenhouse gas emissions of the predominantly fossil-based production of methanol. With the aim to speed up the deployment by streamlining their engineering and construction, we explore the potential of reducing the complexity of designs to be distributed across locations with different renewable energy conditions. A multi-objective optimization-based method incorporating a broad process network for early-stage process synthesis is proposed, which by determining the installed capacities of technologies from the chemical production, utility and storage subsystems, identifies alternative designs with different levels of complexity along two dimensions: 1) the number of different technologies used, 2) standardization of designs across different locations. The method was applied to case studies, which paired together design locations with either wind- or solar-dominant renewable resource conditions in the US and Chile for standardization. As per the method, the increases of methanol production costs due to reduced design flexibility, inherently bound to complexity reduction, were quantified and Pareto fronts were constructed. These uncovered the possibility to significantly reduce the complexity of the designs with only small increases of the production costs. By comparing the results of the case studies under different cost and operation scenarios, we characterized general aspects, which need to be considered for such design simplification. One of the main outcomes were the quantified cost-increases due to standardization, which were around 7 and 15 % relative to the specifically designed plants for each location in the US and Chile case studies respectively. A subsequent analysis of the economies of numbers through learning rates reported in academic literature suggested that the proposed standardization, even across extremely different locations, could compensate these cost-increases and be economically beneficial. Yet, more specific data on achievable cost-reductions are needed, requiring more interaction with the industry and further research, for which we highlighted promising directions.

中文翻译：

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确定电力制甲醇工艺的标准和简单设计：降低复杂性的成本

第一个工业规模的电力制甲醇工厂开始在不同的地理位置部署，以解决主要基于化石的甲醇生产的高温室气体排放问题。为了通过简化工程和施工来加速部署，我们探索了降低设计复杂性的潜力，以分布在具有不同可再生能源条件的地点。提出了一种基于多目标优化的方法，结合了用于早期工艺合成的广泛工艺网络，该方法通过确定化学品生产、公用事业和存储子系统的技术装机容量，确定了沿两个方向具有不同复杂程度的替代设计。维度：1）使用的不同技术的数量，2）不同地点的设计标准化。该方法应用于案例研究，将设计地点与美国和智利以风能或太阳能为主的可再生资源条件配对，以实现标准化。根据该方法，对由于设计灵活性降低而导致的甲醇生产成本的增加（本质上与复杂性降低有关）进行了量化，并构建了帕累托前沿。这些揭示了显着降低设计复杂性而仅增加少量生产成本的可能性。通过比较不同成本和运营场景下的案例研究结果，我们描述了此类设计简化需要考虑的一般方面。主要成果之一是标准化导致的量化成本增加，相对于美国和智利案例研究中每个地点专门设计的工厂，成本分别增加了 7% 和 15% 左右。随后通过学术文献中报告的学习率对数字经济进行的分析表明，即使在极其不同的地点，所提出的标准化也可以补偿这些成本增加并在经济上有利。然而，需要关于可实现的成本降低的更具体的数据，需要与行业更多的互动和进一步的研究，为此我们强调了有希望的方向。