Thermocline thermal energy storage is one of the most promising solutions for recovering waste heat in industrial plants. This paper aims to optimise the shape of a thermal energy storage to minimise its environmental impacts and maximise its exergy efficiency. The reference storage is an existing industrial high-temperature air/ceramic packed-bed heat storage called EcoStock®. The physical model used to determine the performances of the tank is a one dimensional model with two equations: one for the heat transfer fluid and one for the filler material. The environmental impacts are analysed using a life cycle assessment through four selected indicators: cumulative energy demand, global warming potential, abiotic depletion potential and particulate matter. To solve this multi-criteria problem, a particle swarm optimisation algorithm was applied with several exergy and environmental weighting factors. A Pareto set is obtained, bounded by the single exergy or environmental optimisations. Favouring exergy efficiency reduces the volume of the tank. However, environmental footprint of the tank is increased: the indicators of cumulative energy demand and abiotic depletion potential are considerably higher. The shape of the tank evolves with the exergy weight, from a square shape (environmental optimisation) to a tapered shape (exergy optimisation).

温跃层热能储存是回收工业工厂废热的最有前途的解决方案之一。本文旨在优化热能储存的形状，以最大限度地减少其对环境的影响并最大限度地提高其火用效率。参考存储是现有的工业高温空气/陶瓷填充床蓄热器，称为 EcoStock®。用于确定储罐性能的物理模型是具有两个方程的一维模型：一个用于传热流体，另一个用于填充材料。使用生命周期评估通过四个选定的指标来分析环境影响：累积能源需求、全球变暖潜力、非生物耗竭潜力和颗粒物。为了解决这个多标准问题，粒子群优化算法被应用于几个火用和环境加权因子。获得帕累托集，以单个火用或环境优化为界。有利于火用效率减少了坦克的体积。然而，坦克的环境足迹增加了：累积能源需求和非生物耗竭潜力的指标要高得多。坦克的形状随着火用重量的变化而演变，从方形（环境优化）到锥形（火用优化）。累积能源需求和非生物耗竭潜力的指标要高得多。坦克的形状随着火用重量的变化而演变，从方形（环境优化）到锥形（火用优化）。累积能源需求和非生物耗竭潜力的指标要高得多。坦克的形状随着火用重量的变化而演变，从方形（环境优化）到锥形（火用优化）。