Effect of Wind Intermittency on the Electric Grid: Mitigating the Risk of Energy Deficits

Successful implementation of California’s Renewable Portfolio Standard (RPS) mandating 33 percent renewable energy generation by 2020 requires inclusion of a robust strategy to mitigate increased risk of energy deficits (blackouts) due to short time-scale (sub 1 hour) intermittencies in renewable energy sources. Of these RPS sources, wind energy has the fastest growth rate–over 25% year-over-year. If these growth trends continue, wind energy could make up 15 percent of California’s energy portfolio by 2016 (wRPS15). However, the hour-to-hour variations in wind energy (speed) will create large hourly energy deficits that require installation of other, more predictable, compensation generation capacity and infrastructure. Compensating for the energy deficits of wRPS15 could potentially cost tens of billions in additional dollar-expenditure for fossil and / or nuclear generation capacity. There is a real possibility that carbon dioxide and other greenhouse gas (GHG) emission reductions will miss the California Assembly Bill 32 (CA AB 32) target by a wide margin once the wRPS15 compensation system is in place. This work presents a set of analytics tools that show the impact of short-term intermittencies to help policy makers understand and plan for wRPS15 integration. What are the right policy choices for RPS that include wind energy?

💡 Research Summary

The paper addresses a critical challenge facing California’s Renewable Portfolio Standard (RPS), which mandates that 33 % of the state’s electricity come from renewable sources by 2020. While wind power is the fastest‑growing renewable technology—exhibiting more than 25 % annual growth—the authors warn that its rapid expansion could introduce substantial short‑term (sub‑hour) intermittency risks that jeopardize grid reliability. Assuming current growth trends continue, wind could represent 15 % of California’s generation mix by 2016 (the “wRPS15” scenario). The study quantifies how hourly fluctuations in wind speed translate into hourly energy deficits, and evaluates the additional conventional generation capacity required to compensate for those deficits.

Methodologically, the authors construct a probabilistic model of wind output based on historical wind‑speed and generation data. The model simulates hourly generation profiles under the wRPS15 scenario, then compares these profiles to projected hourly demand. The difference—when wind output falls short of demand—is defined as an “energy deficit.” To fill these deficits, the authors calculate the required capacity of fossil‑fuel or nuclear plants, estimate capital and operating costs, and compute the associated increase in CO₂ emissions. Their analysis suggests that, under wRPS15, hourly deficits of 2–3 GW could occur during low‑wind periods, necessitating tens of billions of dollars in additional conventional capacity. This extra capacity would erode the anticipated greenhouse‑gas (GHG) reductions, potentially causing California to miss the targets set by Assembly Bill 32 (AB 32).

The paper’s policy discussion highlights two broad mitigation pathways. First, large‑scale energy storage (e.g., lithium‑ion batteries, compressed‑air energy storage, or hydrogen) could absorb excess wind generation during high‑wind periods and release it during deficits, reducing reliance on fossil backup. Second, enhanced demand‑response programs and stronger inter‑regional transmission links could smooth out variability by shifting load or importing power from neighboring grids. However, the authors acknowledge that their analysis does not incorporate these alternatives in the cost‑benefit calculations; the baseline scenario assumes only conventional generation as a backup.

Critically, the study’s assumptions raise several concerns. The wind‑output model treats hourly fluctuations as statistically independent and does not fully capture extreme events such as prolonged wind lulls, which could underestimate the magnitude of deficits. By excluding storage and demand‑side flexibility, the cost estimates for backup generation are likely overstated, and the projected CO₂ penalty may be exaggerated. Moreover, the paper provides limited sensitivity analysis on key parameters (e.g., wind capacity factor, demand growth, storage cost trajectories), which hampers the robustness of its conclusions.

In summary, the paper convincingly demonstrates that wind‑energy intermittency, if left unmanaged, can impose substantial reliability and economic burdens on California’s grid. It underscores the necessity of pairing wind expansion with complementary technologies—energy storage, demand response, and transmission upgrades—to achieve the RPS goals without compromising emissions targets. Policymakers are urged to adopt an integrated planning framework that quantifies the trade‑offs among additional conventional capacity, storage investment, and GHG outcomes, thereby ensuring that the transition to a high‑penetration wind portfolio remains both reliable and environmentally sustainable.