Recently,　many　renewable　energy　(RE)　initiatives　around　the　world　are　based　on　general　frameworks　that　accommodate　the　regional　assessment　taking　into　account　the　mismatch　of　supply　and　demand　with　pre-set　goals　to　reduce　energy　costs　and　harmful　emissions.　Hence,　relying　entirely　on　individual　assessment　and　RE　deployment　scenarios　may　not　be　effective.　Instead,　developing　a　multi-faceted　RE　assessment　framework　is　vital　to　achieving　these　goals.　In　this　study,　a　regional　RE　assessment　approach　is　presented　taking　into　account　the　mismatch　of　supply　and　demand　with　an　emphasis　on　Photovoltaic　(PV)　and　wind　turbine　systems.　The　study　incorporates　mapping　of　renewable　resources　optimized　capacities　for　different　configurations　of　PV　and　wind　systems　for　multiple　sites　via　test　case.　This　approach　not　only　optimizes　system　size　but　also　provides　the　appropriate　size　at　which　the　maximum　renewable　energy　fraction　in　the　regional　power　generation　mix　is　maximized　while　reducing　energy　costs　using　MATLAB＇s　ParetoSearch　algorithm.　The　performance　of　the　proposed　approach　is　tested　in　a　realistic　test　site,　and　the　results　demonstrate　the　potential　for　maximizing　the　RE　share　compared　to　the　achievable　previously　reported　fractions.　The　results　indicate　the　importance　of　resource　mapping　based　on　energy-demand　matching　rather　than　a　quantitative　assessment　of　anchorage　sites.　In　the　examined　case　study,　the　new　assessment　approach　led　to　the　identification　of　the　best　location　for　installing　a　hybrid　PV　/　wind　system　with　a　storage　system　capable　of　achieving　a　nearly　100%　autonomous　RE　system　with　Levelized　cost　of　electricity　of　0.05　USD/kWh.