The book describes both mathematical and computational tools for energy and power risk management, deriving from first principles stochastic models for simulating commodity risk and how to design robust C++ to implement these models. Coverage includes: An introduction to stochastic calculus, discussing Ito's lemma, Ito's Isometry, Ito product and quotient rules, Ito's lemma for multi-asset geometric Brownian motion, the Ornstein Uhlenbeck process, the Brownian Bridge, and the Ornstein Uhlenbeck Bridge. Single asset European option pricing using Girsanov's Theorem; the Weibull distribution, and the Johnson distribution (including parameter estimation); binomial, trinomial lattices and grids to value single and multi-asset European and American derivatives; Monte Carlo simulation; commodity spot and forward curve models; Merton's jump diffusion model; the Longstaff Schwartz regression method to evaluate American, Asian, swing and storage contracts. A chapter on Markowitz portfolio asset optimization which discusses transaction costs, and analytic derivatives. Examples are provided using a numerical optimization component, which allows the Objective Function and Constraint Functions to be written with Microsoft Excel VBA. Current research on modelling UK power contracts. This deals with: electricity power prices; fundamental power stack model, wind and solar generation; imbalance; system prices; swing contracts, battery storage; demand side response; and generators. A final chapter concerned with software engineering, illustrating how to create C++ vector and random number classes that facilitate the development of energy risk and derivative pricing software.