Stochastic Techno-Economic Assessment of TSC Sizing in Distribution Networks

This paper introduces a novel stochastic optimization framework for the optimal sizing of thyristor-switched capacitors (TSCs) in medium-voltage distribution networks. Unlike conventional deterministic approaches, the proposed model explicitly incorporates load demand variability through multiple probabilistic scenarios, thereby enhancing the robustness and reliability of reactive power compensation. The methodology employs advanced nonlinear programming techniques, i.e., the IPOPT solver within a scenario-based framework, in order to determine the TSC sizes that minimize the expected total system costs, including those associated with energy losses and investments. According to extensive simulations on a standard 33-bus distribution system, our stochastic approach yields cost savings of approximately 12.3–12.4% while significantly improving voltage stability and operational efficiency under various load conditions. Assessments regarding voltage profile performance and average processing times, as well as a comparative analysis considering deterministic results, were also conducted in order to validate the effectiveness and computational efficiency of the approach. This study underscores the importance of probabilistic modeling for a smarter, more resilient grid operation, laying a solid foundation for integrating adaptive reactive power devices to support sustainable and reliable power distribution in evolving smart grid environments.