Optimal Sizing of Photovoltaic Systems With Flexible Curtailment Strategy

As part of many national energy transition strategies, solar photovoltaic (PV) capacity is expected to increase significantly because PV deployment represents a key pathway for decarbonizing the energy sector. Alongside utility-scale installations, distributed PV systems connected to near-end users are becoming increasingly common in distribution networks. However, integrating intermittent sources without demand-matching capabilities introduces challenges related to operational network constraints. Consequently, distribution system operators (DSOs) limit PV integration to an acceptable level, referred to as hosting capacity (HC). Moreover, with increasing PV penetration, the curtailment of production becomes necessary during certain periods. Although curtailment has traditionally been avoided owing to the associated loss of clean energy, techno-economic studies show that shifting toward curtailment management can increase both HC and profitability. Curtailment management can be achieved through flexible PV power control, energy-storage integration, demand-side management, and flexible network regulation devices. This study specifically focuses on the techno-economic performance of flexible PV power control and compares it with the conventional approach without curtailment management, energy storage-based solutions, and their combination. The analysis was conducted on a modified IEEE 33-node test network, and key network constraints were incorporated. Using sequential Monte Carlo simulations with correlated stochastic time-series data for PV production, load profiles, and electricity prices over the years, the optimal PV and/or energy storage capacities were determined for various configurations. The results demonstrate that flexible curtailment management can increase both PV HC and expected profit, providing DSOs with boundary HC values while offering investors insight into the profitability of further PV integration.