Due　to　the　accelerated　pace　of　urbanization,　some　substations　are　increasingly　positioned　near　residential　zones　and　public　spaces.　The　noise　generated　by　these　substations　has　significantly　impaired　the　work　and　living　conditions　of　nearby　residents,　becoming　a　major　source　of　complaints.　Compared　to　traditional　passive　noise　control　technology,　active　noise　control　(ANC)　technology　exhibits　significant　advantages　such　as　greater　controllability,　ease　of　deployment,　and　enhanced　performance　in　low-frequency　noise　reduction.　The　effectiveness　of　an　ANC　system　primarily　depends　on　the　control　algorithm.　However,　traditional　least　mean　square　(LMS)　algorithms　face　challenges　such　as　slow　convergence　and　susceptibility　to　divergence　when　applied　to　time-varying　systems.　Based　on　the　time-domain　and　frequency-domain　characteristics　of　transformer　noise,　this　paper　proposes　a　control　technology　utilizing　the　time　series　forecasting　algorithm　and　designs　an　active　noise　control　system　for　power　transformers　by　integrating　both　software　and　hardware　parts.　The　experimental　results　demonstrate　that　the　system　can　achieve　a　maximum　overall　noise　reduction　of　approximately　8　dB　at　the　error　sensor,　with　the　noise　reduction　for　the　100　Hz　low-frequency　component　reaching　up　to　around　25　dB.　These　results　validate　the　effectiveness　of　the　time　series　forecasting　algorithm　and　the　reliability　of　the　active　noise　control　system　for　power　transformers　designed　in　this　study.　©　2025　IEEE.