As　one　of　the　most　effective　ways　to　alleviate　energy　crisis　and　environmental　pollution,　the　renewable　energy　sources　(RESs)　have　received　increasing　attention.　Different　RESs　enjoy　different　characteristics　and　are　suitable　for　different　scenarios,　thus　it　is　essential　to　evaluate　them　before　installation.　Due　to　the　increasing　complexity　of　reality,　the　RESs　evaluation　usually　involves　various　risks　and　large-scale　group　decision　makers.　To　manage　these　risks　and　decision　makers,　this　paper　proposes　an　interval　type-2　fuzzy　large-scale　group　risk　evaluation　method.　First,　the　interval　type-2　fuzzy　sets　(IT2FSs)　are　employed　to　encode　the　qualitative　information　provided　by　the　decision　makers.　Then,　a　new　clustering　approach　integrating　consensus　reaching　model　and　risk　measurement　model　is　developed　to　manage　the　decision　makers　and　enhance　the　evaluation　efficiency.　After　the　clustering　process,　the　selection　procedure　is　activated　and　an　interval　type-2　fuzzy　centroid-based　ranking　method　is　presented　to　rank　the　candidate　RESs.　Finally,　a　case　study　in　China　is　provided　to　illustrate　the　effectiveness　of　the　proposed　method　and　comparisons　are　also　made　to　verify　the　advantages.　©　2021　Elsevier　B.V.