The majority of remote locations not connected to the main electricity grid rely on diesel generators to provide electrical power. High fuel transportation costs and significant carbon emissions have motivated the development and installation of hybrid power systems using renewable energy such these locations. Because wind and solar energy is intermittent, such sources are usually combined with energy storage for a more stable power supply. This paper presents a modelling and sizing framework for off-grid hybrid power systems using airborne wind energy, solar PV, batteries and diesel generators. The framework is based on hourly time-series data of wind resources from the ERA5 reanalysis dataset and solar resources from the National Solar Radiation Database maintained by NREL. The load data also include hourly time series generated using a combination of modelled and real-life data from the ENTSO-E platform maintained by the European Network of Transmission System Operators for Electricity. The backbone of the framework is a strategy for the sizing of hybrid power system components, which aims to minimise the levelised cost of electricity. A soft-wing ground-generation-based AWE system was modelled based on the specifications provided by Kitepower B.V. The power curve was computed by optimising the operation of the system using a quasi-steady model. The solar PV modules, battery systems and diesel generator models were based on the specifications from publicly available off-the-shelf solutions. The source code of the framework in the MATLAB environment was made available through a GitHub repository. For the representation of results, a hypothetical case study of an off-grid military training camp located in Marseille, France, was described. The results show that significant reductions in the cost of electricity were possible by shifting from purely diesel-based electricity generation to an hybrid power system comprising airborne wind energy, solar PV, batteries and diesel.@en

Currently, in remote off-grid locations, electricity is primarily generated using diesel generators, which is expensive and has significant carbon emissions. Alternatively, these remote locations have a huge potential for utilizing renewable energy sources. In such locations, airborne wind energy (AWE) systems could have an advantage over conventional wind turbines. Since, the AWE systems operate at higher altitudes, stronger and more consistent wind energy can be harnessed. Moreover, they are more compact and have higher mobility, which can reduce installation, operation, and maintenance costs. The centralized controller of the HPP optimizes the energy sources’ dispatch based on the resource and demand forecasts. Due to the anti-correlation between the wind and solar resources, electricity can be generated more constantly on a daily and seasonal scale. The batteries can be smaller, and diesel generators rarely need to be used. The stronger the anti-correlation between the wind and solar resources, the better the HPP performs. The model of the HPP uses wind, solar, and load data as inputs. The hourly energy production is calculated, and combined with the load data, the battery capacity is determined. To find the optimal number of kites, modules, battery capacity, different combinations of kites and modules are put in the model. The levelized cost of electricity (LCoE) is evaluated for each configuration. The model’s output is the minimal LCoE with the corresponding capacity of the different components. The model is used to evaluate multiple case studies, which resulted in the following key findings. HPPs have a stronger case in off-grid markets than utility-scale grid-connected markets. The cost reduction by sharing the infrastructure is minimal. The security of the power supply is better maximized at lower costs than standalone installations. The LCoE has become so competitive that the use of diesel can almost wholly be replaced in suitable locations, which results in a significant reduction in carbon emissions.