Hosting capacity in smart distribution systems using OpenDSS tool and Monte Carlo-based methodology

The increased installation of distributed generators in the electrical network presents significant challenges for system planners and operators, demanding strategic adaptations to accommodate diverse energy sources while ensuring grid stability and operational efficiency. HC analysis has recently been proposed as an essential tool capable of guiding investments into the areas of the network, most likely to offer optimal benefits. This paper presents a method for the estimation of photovoltaic HC of the distribution network. For this purpose, the OpenDSS program, employing the Monte Carlo-based method, is utilised to quantify the HC of the electrical distribution network. The simulation is conducted using a real electrical MV network and then verified against the IEEE Test System for validation. The paper reports HC of 166.5%, which is higher in comparison with similar methods and models, investigates the influence of constant generation in daily simulation and proves that voltage constraint is violated before line loading. A considerable increase of the circuit losses is recorded if the optimal penetration of PV is exceeded. The main contribution of this work is the development, testing and implementation of the HC estimation method in complex power systems using open-source tools and integrating them in an innovative fashion. The results of this research will contribute to collective endeavours of energy transition and a sustainable future.