In this work, we propose a two-step methodology for designing and sizing a data center solely powered by local renewable energy. The first step consists in determining the necessary IT equipment for processing a given IT workload composed of batch and service tasks. We propose an adapted binary search algorithm and prove its optimality to find the minimum number of servers to handle the IT workload. When the IT sizing is computed, the second step consists in defining the supplying electrical infrastructure using wind turbines and photovoltaic panels as primary sources. Batteries and a hydrogen system are added as secondary sources for short- and long-term energy storage, respectively. In this electrical sizing step, first a set of primary source configurations is determined using a binary search algorithm, then the secondary sources are calibrated so that levels of charge are constant during one day and one year, respectively. Experiments using real IT workload traces and actual meteorological data are conducted to illustrate the provided methodology to decision makers for choosing the best configuration for their data center.