Abstract
Future energy systems incorporating high shares of intermittent renewable energy sources are often designed using optimization-based, bottom-up energy system models. However, such models are generally limited to single years and hourly resolutions. This study quantifies the precision loss between hourly and sub-hourly-resolved data for the design and operation of a self-sufficient residential multi-energy system with respect to total costs, system design, and reliability using both averaging and sampling data methods. In this case study, the total annual cost is underestimated by 1.7% with the average hourly data relative to the fully-resolved minute resolution data, mainly due to the sizing of the photovoltaic inverter and battery. This is a result of the sub-hourly peaks in the supply and demand data that are evened out, significantly impacting the sub-electrical system. The results show up to 89 kWh of the annual lost load of the total electrical and thermal load, and a penalty cost of up to €894 (+24%) based on the value of the lost load. Another method, which employs regular sampling of the original time series, shows unpredictable behavior with respect to the tendency of either over- or underestimating system costs and components’ capacities depending on the selected samples. Both the sampling and averaging methods highlight that while hourly resolution may suffice for total system cost approximations, it falls short of sizing dynamically-operated components and meeting stringent reliability requirements. Future research may aim to enhance the temporal resolution of global intermittent renewable energy sources and reduce the computational expenses associated with minute-level resolutions.
Published Version
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