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This paper proposes a new optimization model and solution method for determining optimal locations and sizing of renewable energy sources and hydrogen storage in a power network. We obtain these strategic decisions based on the multi-period alternating current optimal power (AC OPF) flow problem that considers the uncertainty of renewable output, electricity demand, and electricity prices. We develop a second-order cone programming approach within a Benders decomposition framework to provide globally optimal solutions. To the best of our knowledge, our paper is the first to propose a systematic optimization framework based on AC OPF that jointly analyzes power network, renewable, and hydrogen storage interactions in order to provide optimal locations and sizing decisions of renewables and hydrogen storage. In a test case, we show that the joint integration of renewable sources and hydrogen storage and consideration of the AC OPF model significantly reduces the operational cost of the power network. In turn, our findings can provide quantitative insights to decision-makers on how to integrate renewable sources and hydrogen storage under different settings of the hydrogen selling price, renewable curtailment costs, emission tax prices, and conversion efficiency.