A chain store is a group of stores that share central management, have standardized business operation, and spread nationwide or worldwide. Each store has a little different size and equipment, and located in various climate. Therefore, in order to compare and evaluate the power consumption of stores for energy saving, it is needed to reveal a standard and factors affecting power consumption. We conducted a large-scale monitoring experiment using wireless sensor nodes in 1987 convenience stores located in the Tohoku and the Chubu district. First, we show the distribution of average daily power consumption of stores in all area and in selected 10 cities which located in different climate. Next, multivariate regression analysis is applied to the average daily power consumption of refrigerators and air-conditioning systems of stores in the 10 cities. It is shown that a second-order outdoor temperature model can explain for both equipment, and shown that adding humidity term for refrigerators and adding hours of sunshine term to a second-order temperature model improve the accuracy. Finally, evaluation and energy saving methods using the model parameters are proposed.

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After the 2011 Great East Japan Earthquake, a business continuity planning, i.e., BCP, in a disaster case is attracting attentions in Japan. However, when a customer, i.e. a building owner actually would like to introduce energy generation devices such as a cogeneration equipment, there is no guideline to decide suitable device capacity based on the evaluation of economic efficiency and BCP as well as energy saving performance. This study proposes a method to optimize a plan for installing cogeneration equipment considering BCP under disaster risks simultaneously. We develop a simulation tool to decide an optimized planning of energy-generation equipment configuration. With this simulation tool, we performed case studies for different business cases such as a hospital and a hotel. The simulation results showed that the optimized installing plan can be an over-specification of equipment configuration under the assumption of disaster risks, which is never chosen under conventional definition. Then, we examined the economic performance of an energy generation equipment configuration by calculating a net present value from the viewpoint of BCP. This examination can give judgments of investment-return possibility and suitable subsidy price.

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