This paper examines different types of optimization techniques and provides a spatial analysis of energy prices. The last decade has seen an increasing interest in deregulated energy markets. There are few papers, to the author's knowledge, that have considered portfolio optimization, however not in the Italian zonal energy market since deregulation. In deregulated energy markets with zonal pricing the market is partitioned into a number of zones, each of which is assigned a market price to which market participants react to at any given point in time. The paper investigates with emphasis on portfolio theory accounting for the initial capital requirement for the various zones in the Italian energy market and computes the optimal allocation weights needed in the various zones to mitigate the risk inherent in the market. The market risk subsequently affects the zonal prices since these prices combine to bring about the single national electricity price (prezzo unico d'acquisto, PUN). Implementing a modified version of the Mean–Variance portfolio theory, we draw policy implications based on the empirical evidence providing good risk management strategy for market participants.