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A life cycle assessment-based multi-objective optimization of the purchased, solar, and wind energy for the grocery, perishables, and general merchandise multi-facility distribution center network

机译:基于生命周期评估的多目标优化,用于杂货店,易腐物品和普通商品多设施配送中心网络的已购买,太阳能和风能

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Walmart Inc., the U.S. and world's largest grocery retailer, owns a perishables, grocery, and general merchandise distribution center network, which stores and distributes refrigerated and non-refrigerated food. Finding cost-effective strategies to implement solar and wind-powered electricity in their distribution centers was the central objective of this research. The study analyzed the tradeoffs and effects on costs and climate change impact related to the increase of renewable energy use in the distribution centers. The research combined the life cycle assessment and quantitative methods including the Monte Carlo uncertainty analysis and the multi-objective optimization. A life cycle assessment-based multi-objective optimization model was built to find cost-effective strategies to minimize fossil energy use and mitigate the impact of the Walmart Inc. distribution center network on climate change. The bi-objective and the triple-objective optimization included a number of combinations of minimal costs, non-renewable fossil energy use, and climate change impact criteria. The results of the multi objective optimizations were Pareto-optimal solutions obtained by weighing the importance of chosen criteria from the baseline to the zero energy scenarios. A selection of the Pareto-optimal solutions included the good, the better, and the zero energy building scenarios. A better building was a Pareto-optimal set of buildings, which demonstrated superiority from the life cycle assessment perspective. The superiority of Pareto-optimal solutions was evaluated using the Monte Carlo pairwise comparison. The good distribution centers were characterized by the Pareto-optimal solutions between the baseline and the better distribution centers. Finally, the zero energy general merchandise distribution centers were mostly the Pareto-optimal solutions with a 100% share of solar energy. For the zero energy grocery and perishables distribution centers the solutions were a combination of solar and supplemental wind energy because refrigerated warehouses are more energy intensive. The study provided the benchmark results that may improve distribution centers and other buildings and a framework to test environmental and renewable energy policies in buildings.
机译:美国和世界最大的食品杂货零售商沃尔玛(Walmart Inc.)拥有易腐食品,食品杂货和一般商品分销中心网络,该网络存储和分发冷藏和非冷藏食品。寻找经济有效的策略在其配电中心实施太阳能和风能发电是本研究的中心目标。该研究分析了权衡,对成本的影响以及与配送中心可再生能源使用增加有关的气候变化影响。该研究结合了生命周期评估和定量方法,包括蒙特卡洛不确定性分析和多目标优化。建立了基于生命周期评估的多目标优化模型,以找到具有成本效益的策略,以最大程度地减少化石能源的使用并减轻沃尔玛公司配送中心网络对气候变化的影响。双目标和三目标优化包括最低成本,不可再生的化石能源使用以及气候变化影响标准的多种组合。多目标优化的结果是帕累托最优解,是通过权衡从基线到零能耗方案的所选标准的重要性而获得的。帕累托最优解决方案的选择包括良好,更好和零能耗构建方案。更好的建筑物是帕累托最优的建筑物,从生命周期评估的角度来看,它们表现出优越性。使用蒙特卡罗成对比较评估帕累托最优解的优越性。良好的配送中心的特征是基线和更好的配送中心之间的帕累托最优解。最后,零能耗的一般商品配送中心主要是帕累托最优解决方案,其中太阳能占100%。对于零能耗食品杂货和易腐物品配送中心,解决方案是太阳能和风能的补充,因为冷藏仓库的能源消耗更高。该研究提供了可改善配送中心和其他建筑物的基准结果,并提供了测试建筑物环境和可再生能源政策的框架。

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