Enhancing Business Resilience under Power Shortage : Effective Allocation of Scarce Electricity Based on Power System Failure and CGE Models

Enhancing Business Resilience under Power Shortage : Effective Allocation of Scarce Electricity Based on Power System Failure and CGE Models
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增强电力短缺情况下的业务弹性:基于电力系统故障和 CGE 模型的稀缺电力的有效分配

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发表时间:
2014
期刊:
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影响因子:
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通讯作者:
A. Yuyama
A. Yuyama
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作者:
Y. Kajitani;K. Nakano;A. Yuyama

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该研究旨在提出一种方法,以捕捉能源短缺的风险,由于意外事故发电厂在高能源需求条件下。在电力需求每年不断增加的许多发展中国家以及在毁灭性灾害后可能对多个发电厂造成损害的灾害易发国家,这种风险变得特别大。基本上,能源短缺风险应该从供应能力和需求响应的角度来捕捉。从供电侧的角度出发,我们的研究重点之一是捕捉电力系统的脆弱性,并建立一个合适的供电系统功能故障模型。另一方面,有必要了解社会如何通过有效减少电力需求来吸收短缺的影响。为此,本研究探讨了CGE模型作为最优功率分配工具的潜力。通过对日本最近的电力短缺的案例研究,计算了电力短缺恶化的可能性以及吸收损失的前景,并与基于发电厂事故、企业用电量和生产产量等各种统计数据集的结果进行了比较。
The study aims at presenting a methodology to capture the risk of energy shortages due to unscheduled accidents on power plants under high energy demand conditions. This type of risk becomes especially large in many of developing countries where the power demand constantly increases every year as well as disaster-prone countries where the damages to multiple power plants could occur after devastating disasters. Basically, energy shortage risk should be captured from the viewpoints of supply capacity and demand response. From the aspect of supply side, one of the focuses in our research is to capture the vulnerability of power system and develop an appropriate functional failure model for power supply systems. On the other hand, it would be necessary to understand how the society absorbs the impacts of shortage by effectively reducing power demand. For this purpose, this study investigates the potential of CGE model as an optimal power allocation tool. Through the case study of the recent Japanese power shortages, the possibility of worse power shortage as well as the prospect to absorb the losses is calculated and compared with the achieved based on the various statistical data sets such as accidents of power plants, business power consumption, and production outputs.
DOI: 10.1111/j.0022-4146.2005.00365.x
发表时间: 2005-02-01
影响因子: 3
作者:
Rose, A;Liao, SY
通讯作者: Liao, SY