Transparent and flexible energy system analysis: The method of the point cloud

Abstract:
This paper introduces a novel method for the rapid and transparent analysis of costs and benefits of hybrid renewable energy systems. At its core, the method relies on the pre-calculation of numerous configurations of various system com-ponents and their visualization in the dimensions of system costs and degree of self-sufficiency. By representing these configurations as a point cloud, the method enables flexible, fast, and interactive analysis across a wide range of system dimensions. Using the standard load profile of a household with 3 MWh of electricity demand and 17 MWh of heat demand as an example, energy systems achieving up to 100 % self-sufficiency are analyzed under simplified cost assumptions to demonstrate the method. The influence of different storage technologies and adjusted cost assumptions on the system component sizing and overall costs is highlighted. The energy systems include, on the electrical side, PV systems and wind turbines as well as battery and fuel-based long-term storage options, which either store hydrogen or e-fuels. For reconversion, a combined heat and power (CHP) system is used (Pel 2,5 kW, Ptherm 1,68 kW). The thermal section consists of a heat pump (Ptherm 10 kW, COP 3), a heating rod (25 kW), and a thermal storage system. The heat pump, heating rod, and CHP are kept constant across all scenarios. The analysis shows that a combination of a 6 kW wind turbine and a 250 kWh thermal storage system achieves a self-sufficiency degree of 96,2 % with investment costs of 20.900 €. By purchasing biogas or natural gas, the gap to 100 % self-sufficiency can be closed at cumulative total costs over 25 years of 26.000 €. Alternatively, a fully self-sufficient hydrogen system with a pressure tank storage is feasible at investment costs of approximately 30.000 €, allowing various scenarios regarding PV share, battery size, long-term storage size, and electrolyzer capacity. Another variant is an e-fuel-based system, which achieves 100 % self-sufficiency at investment costs of 25.700 €. Despite the significantly higher costs of e-fuel production, the long-term storage is much cheaper, and the required thermal storage size can be signifi-cantly reduced. These results are part of a broad spectrum of different system configurations that, represented as a point cloud, create a framework in the self-sufficiency-cost space. By applying spline interpolation between the points of the framework, the results can be further refined, and component size changes can be analyzed in detail through sensitivity analyses.