As reliance on wind and solar power for electricity generation increases, so does the importance of understanding how variability in these resources affects the feasible, cost-effective ways of supplying energy services. We use hourly weather data over multiple decades and historical electricity demand data to analyze the gaps between wind and solar supply and electricity demand for California (CA) and the Western Interconnect (WECC). We quantify the occurrence of resource droughts when the daily power from each resource was less than half of the 39-year daily mean for that day of the year. Averaged over 39 years, CA experienced 6.6 days of solar and 48 days of wind drought per year, compared to 0.41 and 19 for WECC. Using a macro-scale electricity model, we evaluate the potential for both long-term storage and more geographically diverse generation resources to minimize system costs. For wind-solar-battery electricity systems, meeting California demand with WECC generation resources reduces the cost by 9% compared to constraining resources entirely to California. Adding long-duration storage lowers system costs by 21% when treating California as an island. This data-driven analysis quantifies rare weather-related events and provides an understanding that can be used to inform stakeholders in future electricity systems.

Electric sector capacity expansion models are widely used by academic, government, and industry researchers for policy analysis and planning. Many models overlap in their capabilities, spatial and temporal resolutions, and research purposes, but yield diverse results due to both parametric and structural differences. Previous work has attempted to identify some differences among commonly used capacity expansion models but has been unable to disentangle parametric from structural uncertainty. Here, we present a model benchmarking effort using highly simplified scenarios applied to four open-source models of the U.S. electric sector. We eliminate all parametric uncertainty through using a common dataset and leave only structural differences. We demonstrate how a systematic model comparison process allows us to pinpoint specific and important structural differences among our models, including specification of technologies as baseload or load following generation, battery state-ofcharge at the beginning and end of a modeled period, application of battery roundtrip efficiency, treatment of discount rates, formulation of model end effects, and digit precision of input parameters. Our results show that such a process can be effective for improving consistency across models and building model confidence, substantiating specific modeling choices, reporting uncertainties, and identifying areas for further research and development. We also introduce an open-source test dataset that the modeling community can use for unit testing and build on for benchmarking exercises of more complex models. A community benchmarking effort can increase collaboration among energy modelers and provide transparency regarding the energy transition and energy challenges, for other stakeholders such as policymakers.

Electricity systems worldwide are transforming from relying almost exclusively on firm, predictable generation (e.g., fossil, nuclear, and large hydropower) towards incorporating more variable generation (e.g., wind and solar PV). In these systems, the electric load minus generation from variable resources is known as the "residual load."The peak residual load provides an estimate of the dispatchable power capacity required to supply electric load during all hours. We analyze a decade of concurrent historical electric load and weather data from four electricity systems. For each system, we construct hypothetical, plausible residual load profiles to study the peak residual load values and their spread from year to year, the "inter-annual variability,"as a function of wind and solar generation. The inter-annual variability in the peak residual load can be equated with the spread in dispatchable power capacity required to supply all load from year to year in electricity systems. In each system, adding variable generation changed the inter-annual variability in the peak residual load values. The introduction of variable renewable power is often thought to increase the variability of most electricity systems characteristics. In contrast, using our simple approach, we show the inter-annual variability in peak residual load may decrease with added solar generation in systems where peak load occurs in the summer months. We attribute these reductions to correlations between the availability of solar generation and the hours of peak electric load, which occurred during the hottest days each year, when electric cooling (air conditioning) was likely used. Also, we show the inter-annual variability in peak residual load decreased in certain circumstances when adding wind generation to the system with a winter peaking load. An understanding of how and why this spread in peak dispatchable power capacity changes with increasing wind and solar deployment could inform long-term planning and resource adequacy targets for electricity systems.

We performed spectral analyses on the ages of 89 well-dated major geological events of the last 260 Myr from the recent geologic literature. These events include times of marine and non-marine extinctions, major ocean-anoxic events, continental flood-basalt eruptions, sea-level fluctuations, global pulses of intraplate magmatism, and times of changes in seafloor-spreading rates and plate reorganizations. The aggregate of all 89 events shows ten clusters in the last 260 Myr, spaced at an average interval of similar to 26.9 Myr, and Fourier analysis of the data yields a spectral peak at 27.5 Myr at the >= 96% confidence level. A shorter period of similar to 8.9 Myr may also be significant in modulating the timing of geologic events. Our results suggest that global geologic events are generally correlated, and seem to come in pulses with an underlying similar to 27.5-Myr cycle. These cyclic pulses of tectonics and climate change may be the result of geophysical processes related to the dynamics of plate tectonics and mantle plumes, or might alternatively be paced by astronomical cycles associated with the Earth's motions in the Solar System and the Galaxy. (C) 2021 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.

Solar and wind resources are dependent on geophysical constraints. Here the authors find that solar and wind power resources can satisfy countries' electricity demand of between 72-91% of hours, but hundreds of hours of unmet demand may occur annually.

Variability of wind and solar generation and electricity demand poses substantial challenges to the affordable supply of reliable electricity. In a modeling study published in Energy & Environmental Science, Guerra and colleagues find that a portfolio of energy storage technologies provides the least-cost path to reliable electricity supply.

Non-marine tetrapods (amphibians, reptiles, birds and mammals) have apparently experienced at least 10 distinct episodes of intensified extinctions over the past 300 My. Eight of these ten non-marine extinction events are concurrent with known marine-extinction episodes, which previously yielded evidence for an underlying period of similar to 26.4 to 27.3 My. We performed circular spectral analysis and Fourier transform analysis of the ages of the ten recognised tetrapod-extinction events, and detected a statistically significant (99% confidence) underlying periodicity of similar to 27.5 My. We also find that the eight coeval non-marine/marine-extinction pulses all occurred at the times of eruptions of Large Igneous Provinces (LIPs) (continental flood-basalts and oceanic plateaus), with potentially severe environmental effects. Three of these co-extinction episodes are further correlated with the ages of the three largest (>= 100-km diameter) impact craters of the last 260 My, which are also apparently capable of causing extinction events. These findings suggest that global cataclysmal events with an underlying periodicity of similar to 27.5 My were the cause of the coordinated periodic extinction episodes of non-marine tetrapods and marine organisms.

When wind turbines are arranged in clusters, their performance is mutually affected, and their energy generation is reduced relative to what it would be if they were widely separated. Land-area power densities of small wind farms can exceed 10 W/m2, and wakes are several rotor diameters in length. In contrast, large-scale wind farms have an upper-limit power density in the order of 1 W/m2 and wakes that can extend several tens of kilometers. Here, we address two important questions: 1) How large can a wind farm be before its generation reaches energy replenishment limits and 2) How far apart must large wind farms be spaced to avoid inter-wind-farm interference? We characterize controls on these spatial and temporal scales by running a set of idealized atmospheric simulations using the Weather and Research Forecasting model. Power generation and wind speed within and over the wind farm show that a timescale inversely proportional to the Coriolis parameter governs such transition, and the corresponding length scale is obtained by multiplying the timescale by the geostrophic wind speed. A geostrophic wind of 8 m/s and a Coriolis parameter of 1.05 x 10-4 rad/s (latitude of similar to 46 degrees) would give a transitional scale of about 30 km. Wind farms smaller than this result in greater power densities and shorter wakes. Larger wind farms result instead in power densities that asymptotically reach their minimum and wakes that reach their maximum extent.

As reliance on wind and solar power for electricity generation increases, so does the importance of understanding how variability in these resources affects the feasible, cost-effective ways of supplying energy services. We use hourly weather data over multiple decades and historical electricity demand data to analyze the gaps between wind and solar supply and electricity demand for California (CA) and the Western Interconnect (WECC). We quantify the occurrence of resource droughts when the daily power from each resource was less than half of the 39-year daily mean for that day of the year. Averaged over 39 years, CA experienced 6.6 days of solar and 48 days of wind drought per year, compared to 0.41 and 19 for WECC. Using a macro-scale electricity model, we evaluate the potential for both long-term storage and more geographically diverse generation resources to minimize system costs. For wind-solar-battery electricity systems, meeting California demand with WECC generation resources reduces the cost by 9% compared to constraining resources entirely to California. Adding long-duration storage lowers system costs by 21% when treating California as an island. This data-driven analysis quantifies rare weather-related events and provides an understanding that can be used to inform stakeholders in future electricity systems.