Successful integration of intermittent renewable resources into the energy mix is instrumental to meet the growing global energy demand while reducing the carbon emissions. With this study, we propose a strategy of mixed-integer linear programming-based simultaneous design and operation to explore the techno-economic feasibility of novel energy system networks including solar photovoltaics, wind turbines, battery storage, and dense energy carriers. A multiscale energy system engineering approach is followed combining process synthesis, scheduling, and supply chain concepts to address the trade-offs between various technologies in renewable power generation and storage, as well as energy carrier production and transportation across different locations. We apply our strategy to analyze the integration of hydrogen- based dense energy carriers (DECs) produced in a high-potential region of renewable energy in Texas in tandem with local solar production and battery storage in a low-potential region in New York to minimize the levelized cost of renewable electricity. Case study results show that DECs can offer 30-50% cost reductions to local power generation and battery systems when used as clean backup fuels.