In most studies, the lowest temporal resolution data used in addressing the problem of matching local generation and demand is hourly. There are very few attempts that use minute level temporal resolution capturing the highly stochastic nature. This study utilizes high-resolution household load modelling platform called Suricatta to assess the potential for matching in real-time. In this study, 1-minute and 1-hour resolutions data is used to evaluate load matching index of PVs and wind turbines along with storage battery and demand response solutions. The results demonstrate the relatively high relevance of 1-minute data resolution in case of demand response planning and also for wind turbine generations. Besides, the diurnal nature of weather variables together with their negative correlation to the typical Finnish household seasonal consumption emphasizes the need for storage systems and/or demand response plans to enhance matching of distribution system level wind turbine and PV generations.