Optimization planning of distributed photovoltaic integration in distribution networks using combinatorial search algorithm.

The current scenario sees the potential emergence of challenges such as power imbalances and energy dissipation upon the incorporation of distributed photovoltaic (PV) systems into distribution networks, impacting power quality and economic viability. To address these identified risks, this study introduces an innovative combinatorial search algorithm designed to autonomously derive optimal planning strategies for distribution networks. The process begins by establishing distinct planning models for distributed PVs and distribution network systems, followed by the application of the search algorithm to align these models and generate relevant Pareto datasets and multi-objective positioning criteria. By strategically combining and optimizing existing solutions to bolster the distribution network's load-carrying capacity, the optimal strategy is progressively refined under the guidance of multiple objective constraints. Subsequent multiphase simulation experiments validate the efficacy of our approach in minimizing energy losses when compared to analogous methodologies. The distribution network integration planning strategies derived through our method showcase outstanding performance in reducing energy losses, conducting steady-state voltage safety assessments, optimizing installation capacity utilization rates, and enhancing economic returns, thus emphasizing the substantial potential of our approach in facilitating the seamless integration of distributed PVs into distribution networks. [ABSTRACT FROM AUTHOR]