Selecting　right　renewable　energy　resources　(RESs)　is　emerging　as　a　solution　to　alleviate　energy　crisis　and　environmental　pollution.　To　better　address　the　RESs　selection　problems,　this　paper　proposes　an　enhanced　Technique　for　Order　Preference　by　Similarity　to　Ideal　Solutions　(TOPSIS).　Specifically,　the　decision　information　is　characterized　by　linguistic　terms　and　then　encoded　by　interval　type-2　fuzzy　sets　(IT2FSs).　The　current　IT2FSs　preprocessing　models　recklessly　transform　IT2FSs　into　crisp　numbers,　which　may　discount　the　superiority　of　applying　fuzzy　sets.　Hence,　we　define　a　novel　interval　type-2　fuzzy　projection　model　to　measure　the　IT2FSs　and　some　related　theorems　about　the　projection　model　are　explored　mathematically.　Moreover,　based　on　this　new　interval　type-2　fuzzy　projection　model,　an　enhanced　TOPSIS　is　proposed　to　calculate　the　closeness　coefficients　of　alternatives.　Of　note,　to　keep　information　as　much　as　possible,　the　obtained　closeness　coefficients　are　still　IT2FSs.　Finally,　the　Karnik-Mendel　(KM)　algorithms　are　employed　to　compare　and　rank　those　closeness　coefficients.　The　effectiveness　of　the　proposed　method　is　demonstrated　by　a　RESs　selection　case.　Comparisons　are　also　conducted　to　illustrate　its　advantages.