In the near future, it is expected the widespread use of electric vehicles (EVs). And a lot of retail stores will have EV quick chargers. This might cause a problem that is a rise in electricity costs of the stores because of an increase in maximum load power. The stores want to reduce electricity cost especially related with load peak for low cost operation. Installation of photovoltaic (PV) and storage battery system are one of the solutions for peak cutting. So it is important to decide the reasonable system scale to install. On the other hand, the stores also want to make battery lifetime longer for low cost operation. Thus, an optimization method of system installation and operation for a retail store is discussed in this paper. In the first step, the system scale is optimized, whose purpose is maximizing the effect of peak cut with minimum installation cost. In the optimization, a genetic algorithm (GA) is employed to solve the multi-objective trade-off problem. In the next step, system operation is optimized to make battery lifetime longer. In order to extend the battery lifetime, start timing control of the EV quick charge is effective. However, start timing control delays the beginning of charging, which makes it unattractive for customers. The relationship between delay time and battery lifetime improvement is investigated. And a design method to achieve long system lifetime is shown.