The　integration　of　renewable　energy　sources　in　hydrogen　production　through　water　electrolysis　is　pivotal　for　advancing　decarbonization　in　the　energy　and　chemical　industries.　However,　inappropriate　sizing　often　leads　to　poor　techno-economics　of　hydrogen　production　and　low　rates　of　renewable　energy　consumption.　This　paper　proposes　a　mixed　water　electrolysis　system　utilizing　both　alkaline　electrolyzers　(ALK)　and　proton　exchange　membrane　electrolyzers　(PEM),　coupled　with　battery　storage,　to　optimize　techno-economic　performance.　A　non-convex　mixed　integer　quadratic　constraint　programming　(MIQCP)　model　is　developed　to　minimize　the　levelized　cost　of　hydrogen　(LCOH)　while　addressing　the　complexities　of　system　configuration　and　scheduling.　The　model　is　transformed　into　a　mixed　integer　linear　programming　(MILP)　problem　using　segmented　linearization　and　the　Big-M　method.　A　K-means　clustering　algorithm　is　also　used　to　determine　the　typical　day　for　resolving　the　variable　explosion　problem　induced　by　the　sign　constraints.　A　case　based　on　a　hydrogen　production　park　proves　the　effectiveness　of　the　proposed　system.　Results　show　that　the　system　achieves　an　optimal　ALK/PEM　ratio　of　112.5:29,　yielding　an　LCOH　of　20.69　¥/kg,　which　is　5.78　%　and　10.66　%　lower　than　the　ALK-only　and　PEM-only　systems,　respectively.　The　internal　rate　of　return　for　the　mixed　system　is　5.02　%,　and　power　consumption　is　56.92　kWh/kg.　Sensitivity　analyses　highlight　the　impact　of　PEM　electrolyzer　cost　reductions　on　system　efficiency,　underscoring　the　economic　potential　of　hybrid　electrolyzer　configurations.　The　study　aims　at　providing　insights　into　the　optimization　of　renewable　energy-driven　hydrogen　production　systems,　facilitating　better　integration　and　cost-efficiency　in　green　hydrogen　projects.　©　2025　Elsevier　Ltd