  We consider simple stochastic games $\mathcal G$ with energy-parity
objectives, a combination of quantitative rewards with a qualitative parity
condition. The Maximizer tries to avoid running out of energy while
simultaneously satisfying a parity condition. We present an algorithm to
approximate the value of a given configuration in 2-NEXPTIME. Moreover,
$\varepsilon$-optimal strategies for either player require at most
$O(2EXP(|{\mathcal G}|)\cdot\log(\frac{1}{\varepsilon}))$ memory modes.
