A data-driven approach to support voltage profiles & loss reduction in wind generator integrated active distribution network considering solid-state transformers with twofold reactive power compensation

The paper proposes an optimal planning strategy for an active distribution network (ADN) with wind energy-based distributed generation (WDG) by considering the twofold reactive power compensation (TRPC) feature of a three-stage type solid-state transformer (SST). A model for wind speed and load demand estimation for each hour of the day is formulated by using the partition around medoids (PAM) technique over an annual database of load demand and wind speed. A multi-objective mixed-integer non-linear programming (MINLP) approach for optimally locating and sizing the SST installations in the radial distribution network (RDN) is presented to address the dual objectives of voltage profile improvement (VPI) and energy loss reduction (ELR). Along with the SST parameters, the locations and number of wind turbine (WT) units to be integrated into the system are treated as optimization variables. Furthermore, the distribution power flow accounts for the distribution transformer's (DT) operating losses as well as the approximate losses of the SST. The presented approach is tested on a 33-bus RDN and the results are reported for multiple case studies. The programming was developed in the MATLAB R2020a environment and the paretosearch algorithm (PSA) is used to address the MINLP problem. Other standard multi-objective optimization algorithms, including multi-objective multi-verse optimization (MOMVO), non-dominated sorting genetic algorithm (NSGA-II), and multi-objective salp swarm algorithm (MSSA) are used to compare the performance of the proposed method. The outcomes of the peak hour evaluation, with a 20% over-rating, show the active and reactive power demand on the MV side of the substation to have decreased by 56.3% and 30.1% respectively. The active line loss has been lowered by 76.95% and the reactive line loss has decreased by 76.14%. The absolute minimum voltage has increased by 7.314%. Furthermore, according to the annual technical evaluation, there was a 29.42% reduction in active energy served by the DTs and SSTs.

Automated summary

This study proposes an optimal planning strategy for an active distribution network with wind energy-based distributed generation, considering the twofold reactive power compensation feature of a three-stage solid-state transformer. Models for wind speed and load demand estimation are formulated using the PAM technique, and a multi-objective MINLP approach is presented for locating and sizing the SST installations to improve voltage profile and reduce energy losses. The approach is tested on a 33-bus RDN and results show significant improvements in active and reactive power demand, line losses, and voltage quality.