Why we must move beyond LCOE for renewable energy design

Abstract

• Wind and solar generation devaluation occurs for grids with high renewable shares • This effect, due to intermittency, dramatically reduces the value of generated energy • Cost of Valued Energy can be used to account for this intermittency penalty • Minimizing COVE can improve VRE system design to better meet demand The inherent intermittency of wind and solar energy challenges the relevance of Levelized Cost of Energy (LCOE) for their future design which neglects the time-varying price of electricity. The Cost of Valued Energy (COVE) is an improved valuation metric that takes into account time-dependent electricity prices. In particular, it integrates short-term (e.g., hourly) wind and solar energy “generation devaluation”, whereby high wind and/or solar energy generation can lead to low, and even negative, energy prices for grids with high renewable penetration. These aspects are demonstrated and quantified using examples of two large grids with high renewable shares with three approaches to model hourly price: 1) residual demand, 2) wind and solar generation, and 3) statistical price-generation correlation. All three approaches indicate significant generation devaluation. The residual demand approach provides the most accurate price information while statistical correlations show that generation devaluation is most pronounced for the Variable Renewable Energy (VRE) that dominates market share (e.g., solar for California and wind for Germany). In some cases, the cost of valued energy relative to levelized cost can be 43% higher for solar (CAISO) and 129% higher for wind (ERCOT). This indicates that COVE is a much more relevant metric than LCOE in such markets. In particular, COVE is based on the annualized system costs relative to the annualized spot market revenue, and thus considers economic effects of costs vs. revenue as well as those of supply vs. demand. As such, COVE (instead of LCOE) is recommended to design and value next-generation renewable energy systems, including storage integration tradeoffs. However, more work is needed to develop generation devaluation models for projected grids and markets and to better classify grid characteristics as we head to a carbon-neutral energy future.