Enhancing distribution grid planning with time series-based analysis: a case study from Germany

The transition to renewable energy sources is presenting significant challenges for the distribution grid, particularly with the integration of photovoltaic systems, heat pumps, and electric vehicles. These advancements are causing increasingly variable loads in low-voltage grids, thereby stressing the limits of current network expansion and planning methodologies. Ensuring grid stability while accommodating the evolving energy landscape is a critical challenge for grid operators. This paper presents a two-step methodology for improving power flow calculations using feeder line measurements. The approach first transitions from single worst-case calculations to time-series based power flow analysis incorporating detailed PV system modelling. Subsequently, a calibration approach using multiplicative scale factors aligns power flow calculations with actual measurements. The methodology is validated through two case studies of rural low-voltage networks dominated by PV systems. The results demonstrate that traditional worst-case calculations overestimate the grid utilization by 65-87%, while the time-series approach achieves significantly better accuracy with deviations of approximately 26%. While a simple calibration improves the overall agreement between calculations and measurements, the modelling of the utilization is not improved. These findings highlight the potential for more accurate grid planning through the integration of measurement data and time-series based calculations, supporting more efficient infrastructure investment decisions in the ongoing energy transition.