Chapter 11 - Portfolio Optimization and Utilities’ Investments in Liberalized Power Markets

Abstract

This chapter discusses simulation techniques and portfolio optimization to study private investors' diversification incentives in liberalized electricity markets. The main contribution on the methodological side is the introduction of a two-step simulation approach to assess the impact of both plant input (fuel) and output (electricity and CO2) price risks on the return of different base-load generation technologies. Monte Carlo simulations of gas, coal and nuclear plant investment returns are used as inputs of a mean-variance portfolio optimization to identify optimal base-load generation portfolios for large electricity generators in liberalized electricity markets. High degrees of correlation between gas and electricity prices, as observed in most European markets, reduce gas plant risks make portfolios dominated by gas plant more attractive. Long-term power purchase contracts and/or a lower cost of capital can rebalance optimal portfolios towards more diversified portfolios with larger shares of nuclear and coal plants. The chapter demonstrates the usefulness of this new theoretical approach by studying optimal portfolios in three case studies, using central parameter estimates derived from historical electricity, fuel, and carbon prices data from Britain over 2001–2005. These case studies give new insights into diversification incentives for power investors in liberalized markets. The dominance of CCGT in optimal generation portfolios can thus be traced back to the high degrees of correlation observed in many liberalized markets between electricity and gas prices, which reduce the risk of investment in this technology. Finding an instrument that corrects the potential market failure while not unduly distorting the market is a challenge.