In recent years, resilience-enhanced building buildings have been attracting increasing attention, in which photovoltaic (PV) power generation and storage batteries are installed in office buildings to continue operations even during a grid outage. PV power generation and storage batteries can be introduced to office buildings to continue commercial operations in the case of grid outages. When introducing PV power generation and storage batteries into a building, the total cost, which is the sum of the equipment installation cost and the damage cost in the event of a disaster, is crucial. When installing PV power generation and storage batteries in a building and calculating the total cost of using these facilities in the event of a disaster, it is necessary to consider the uncertainty of power demand and the amount of power generated by PV power generation. Monte Carlo Simulation is a method to consider uncertainty. However, it has a problem that the combination of conditions becomes enormous, and the calculation load is high when the total cost is calculated. Therefore, in this study, we propose convolution as a method to reduce the computational load generated when calculating the probability distribution of the total cost generated by strengthening the resilience of the building.

中文翻译：

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使用卷积的高速计算方法计算具有发电和存储设施的建筑物的正常成本和灾难成本

近年来，增强抗灾能力的建筑越来越受到人们的关注，其中在办公楼中安装光伏发电和蓄电池，即使在电网停电时也能继续运行。办公楼可以引入光伏发电和蓄电池，在电网停电的情况下继续商业运营。当将光伏发电和蓄电池引入建筑物时，总成本（设备安装成本和发生灾害时的损坏成本之和）至关重要。在建筑物中安装光伏发电和蓄电池并计算发生灾害时使用这些设施的总成本时，需要考虑电力需求和光伏发电发电量的不确定性。蒙特卡罗模拟是一种考虑不确定性的方法。然而，其存在条件组合变得庞大、计算总成本时的计算负荷高的问题。因此，在本研究中，我们提出卷积作为一种方法，以减少计算通过加强建筑物的弹性而产生的总成本的概率分布时产生的计算负荷。