<jats:p>In the fight against anthropogenic climate change, the benefit of the integration of fluctuating renewable energies (wind and photovoltaics) into the electricity grid is a widely proved concept. At the same time, a fluctuating and decentralised supply of energy, especially at lower voltage levels, leads to a local discrepancy in the power balance between generation and consumption. A possible solution in connection with demand side management is the grid-oriented flexibilisation of energy demand. The present study shows how the use of an innovative hybrid-redundant high-temperature heat system (combined heat and power (CHP), power-to-heat system (PtH), gas boiler) can contribute to a flexibilisation of the electrical energy demand of plastics processing companies. In this context, the flexibilisation potential of a company is to be understood as the grid-related change of the energy supply through a change of the energy sources within the framework of the process heat supply. For this purpose, an omniscient control algorithm is developed that specifies the schedule of the individual system components. A sensitivity analysis is used to test the functionality of the control algorithm. Determination of the electrical flexibilisation potential is carried out via a comprehensive simulation study using Monte Carlo methods. For this purpose, the residual load curves of four characteristic distribution grids with a high share of renewable energies as well as heat load profiles of injection moulding machines are taken into consideration. A frequency distribution provides information on the electrical flexibilisation potential to be expected depending on the various combinations. The evaluation is carried out using a specially introduced logic, which identifies grid-relevant changes in the company's power consumption as flexibilisation potential based on a reference load curve. The results show that a reliable energy supply for production is possible despite flexibilisation. Depending on the grid under consideration, there are differences in the exploitation of the potential, which essentially depends on the installed renewable capacity. Depending on the scenario under consideration, an average of up to 1486 kWhel can be shifted in a positive direction and 1199 kWhel in a negative direction.</jats:p>

Renewable energy and storage systems are widely discussed to minimise the impact of global warming. In addition to the temporal resolution of simulation tools, also the chosen input data might have a strong impact on the performance of renewable energy systems, and energy storage systems in particular. This study analyses the impact of probabilistic weather data on the design of renewable energy systems. The main objective is hereby the determination of the robustness of a recently state-of-the-art design process of a 100% renewable energy and storage system with varying probabilistic input data. The island of La Gomera, Canary Islands, is taken as a case study. Although all analysed systems show some variance in their results, the combination of vehicle-to-grid and power-to-hydrogen shows the best economic performance. Hereby, small island energy systems depending heavily on wind energy show higher variations than those with high shares of solar energy. This analysis illustrates clearly that the choice of one historical reference year is not suitable to determine the expected performance of an energy system. To learn about their sensitivity, synthetic probabilistic inputs as applied in this study are a good way to determine both the expected mean values and their variance.