Managing renewable energy resources using equity-market risk tools - the efficient frontiers

Abstract

Most past analyses on distributed energy sources have employed large-scale stochastic optimization while taking into account the physics of the network, its control, its dimension and sometimes its investment costs. One may call it the physical/control aspect of the network. What is missing is a higher level and a broader view of the distribution of the network resources - a business-like policy toward resource distribution that provides for clear criteria on the relationship between risk (uncertainty, or volatility) and gain-over-costs. The dynamics of the energy market, and specifically, the renewable sector carry volatility and risks with similarities to the financial market. Here, we leverage a well-established, return-risk approach, commonly used by equity portfolio managers and introduce it to energy resources: solar, wind, and biodiesel. We visualize the relationship between the resources' costs and their risks in terms of efficient frontiers. We apply this analysis to publically available data for various US regions: Central, Eastern and Western coasts. Since risk management is contingent on costs, this approach sheds useful light on assessing dynamic pricing in modern electrical power grids. By integrating geographical and temporal dimensions into our research, we aim at more nuanced and context-specific recommendations for energy resource allocation. As an example, the lowest risk of 0.124 (in terms of standard deviation) for an expected return of 1.93% in Newark, New Jersey, USA has energy portfolio distribution of: 50.54%, 18.62%, and 30.84% for solar, wind, and biodiesel, respectively. Decision-makers may benefit from this approach, making informed and transparent selections to curate their energy supply.