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Previous studies investigating deep decarbonization of bulk electric power systems and wholesale electricity markets have not sufficiently explored how future grid pathways could affect the grid's vulnerability to hydrometeorological uncertainty on multiple timescales. Here, we employ a grid operations model and a large synthetic weather ensemble to "stress test" a range of future grid pathways for the U.S. West Coast developed by ReEDS, a well‐known capacity planning model. Our results show that gradual changes in the underlying capacity mix from 2020 to 2050 can cause significant "re‐ranking" of weather years in terms of annual wholesale electricity prices (with "good" years becoming bad, and vice versa). Nonetheless, we find the highest and lowest ranking price years in terms of average electricity price remain mostly tied to extremes in hydropower availability (streamflow) and load (summer temperatures), with the strongest sensitivities related to drought. Seasonal dynamics seen today involving spring snowmelt and hot, dry summers remain well‐defined out to 2050. In California, future supply shortfalls in our model are concentrated in the evening and occur mostly during periods of high temperature anomalies in late summer months and in late winter; in the Pacific Northwest, supply shortfalls are much more strongly tied to negative streamflow anomalies. Under our more robust sampling of stationary hydrometeorological uncertainty, we also find that the ratio of dis‐patchable thermal (i.e., natural gas) capacity to wind and solar required to ensure grid reliability can differ significantly from values reported by ReEDS. Plain Language Summary: In this study we model how increased adoption of wind power, solar power, batteries and electric vehicles could alter the U.S. West Coast grid's exposure to weather uncertainty. Our results show that as the mix of technologies used on the grid changes from 2020 to 2050, it will cause a "re‐ranking" of weather years (with "good" years capable of becoming "bad" and vice versa). For example, years with low wind speeds generally become more concerning (marked by comparatively high prices) as installed wind power increases. Nonetheless, the highest and lowest price years remain most strongly tied to extremes in hydropower availability (streamflow) and electricity demand (summer air temperatures) even out to 2050. In California, supply shortfalls are concentrated in the evening during periods of anomalously high temperatures in late summer and late winter; in the Pacific Northwest, supply shortfalls are most strongly tied to negative streamflow anomalies. By subjecting various decarbonization scenarios to weather uncertainty, we also find that the amount of "firm" (natural gas) capacity needed to ensure reliability can differ significantly from values reported in a widely used capacity expansion model. Key Points: Changing capacity mixes cause "re‐ranking" of weather years in terms of annual priceNonetheless, the highest and lowest price years remain tied to extremes in hydropower production and loadCapacity expansion models may misrepresent firm capacity needed under weather uncertainty [ABSTRACT FROM AUTHOR]

For large energy consumers transitioning to high shares of solar energy, irradiance variability causes volatility in power generation and energy expenditures. Volatility in an end user's cash flow is harmful to their financial health, especially in abnormally cloudy years. This paper explores the utility of an irradiance-based weather derivative in mitigating cloud weather risk and measures the effectiveness of the developed derivative by applying it to a case study of two Chilean copper mines. Weather derivatives are financial instruments tied to an underlying weather variable that act as an insurance for the contract holder, executing indemnity payments based on an index value. This research develops a contract with a combined index based on monthly sums of irradiance and cloudy day sequencing to mitigate a solar mine's weather risk. The design and evaluation of contracts are based on LEELO, a linear optimization model outputting optimal sizes of solar photovoltaic, battery storage, and power-to-gas systems, as well as the operation of these systems for a given mine's load, irradiance and technology costs. Results indicate contracts are effective in cloudier climates with increasing utility for mines installing solar energy systems until the year 2030. After 2030 batteries begin to become a more cost-effective risk-hedging mechanism as they become more affordable. Image 1 • Irradiance-based weather derivative is developed for risk hedging of solar systems. • Hybrid index based on monthly irradiance counts and cloudy days sequencing. • Application to Chilean mines with solar-battery systems stabilizes cash flows. • Weather derivative is very effective in cloudier regions after the year 2030. • After 2040, risk mitigation via batteries is more cost effective than derivatives. [ABSTRACT FROM AUTHOR]

• To date the most complete model for planning South America's power sector. • South America's transition relies on solar, wind, and gas as bridging technology. • Lithium batteries and pumped hydro are the main storage technologies. • Modeling 30 nodes is a good trade-off between complexity and quality of results. • Hydrogen exports aid the integration of renewable generation. Europe and North America have numerous studies on 100% renewable power systems. South America, however, lacks research on zero-carbon energy systems, especially understanding South America as an interconnected region, despite its great renewable energy sources, increasing population, and economic productivity. This work extends the cost-optimization energy planning model LEELO and applies it to South America. This results in the to-date most complete model for planning South America's power sector, with a high temporal (8760 time steps per year) and spatial (over 40 nodes) resolution, and 30 technologies involved. Besides the base case, we study how varying spatial resolution for South America impacted investment results (43, 30, 16, 1 node). Finally, we also evaluate green hydrogen export scenarios, from 0% to 20% on top of the electricity demand. Our study reveals that South America's energy transition will rely, in decreasing order, on solar photovoltaic, wind, gas as bridging technology, and also on some concentrated solar power. Storage technologies equal to about 10% of the total installed power capacity would be required, aided by the existing hydropower fleet. Not only is the transition to renewables technically possible, but it is also the most cost-efficient solution: electricity costs are expected to reach 32 €/MWh from the year 2035 onwards without the need for further fossil fuels. Varying the spatial resolution, the most-resolved model (43 nodes) reveals 11% and 6% more costs than the one-node and one-node-per-country (16) models, respectively, with large differences in investment recommendations, especially in concentrated solar and wind power. The difference between 43 and 30 nodes is negligible in terms of total costs, energy storage, and technology mix, indicating that 30 nodes are an adequate resolution for this region. We then use the 30-node model to analyze hydrogen export scenarios. The electricity costs drop, as hydrogen is not only a load but also a flexibility provider. Most green hydrogen is produced in Chile, Argentina, and northeast Brazil. For future work, we propose to do an integrated energy plan, including transport and heat, for the region, as well as modeling local hydrogen demands. This work aims to inform policymakers of sustainable transitions, and the energy community. [ABSTRACT FROM AUTHOR]

• We calculate the optimal electricity supply for large copper mines around the world. • From 2020 onwards, all mines should have solar shares above 25%. • In 2030, the first fully solar mines should be established. • In the long-term, Chile and Peru have the lowest electricity costs. • In most locations, low-cost solar energy makes up for costs from declining ore grades. Extracting copper is energy-intensive. At the same time, copper is a key material for building the energy systems of the future. Both facts call for clean copper production. The present work addresses the greenhouse gas emissions of this industry and focuses on designing the future electricity supply of the main copper mines around the world, from 2020 to 2050, using distributed solar photovoltaic energy, storage, and a grid connection. We also consider the increasing energy demand due to ore grade decline. For the design, we use an optimization model called LEELO. Its main inputs are an hourly annual demand profile, power-contract prices for each mine, cost projections for energy technologies, and an hourly annual solar irradiation profile for each mine. Our findings show that it is attractive for the mines to have today a solar generation of 25% to 50% of the yearly electricity demand. By 2030, the least-cost solution for mines in sunny regions will be almost fully renewable, while in other regions it will take until 2040. The expected electricity costs range from 60 to100 €/MWh for 2020 and from 30 to 55 €/MWh for 2050, with the lower bound in sunny regions such as Chile and Peru. In most locations assessed, the low cost of solar energy will compensate for the increased demand due to declining ore grades. For the next steps, we recommend representing the demand with further detail, including other vectors such as heat and fuels. In addition, we recommend to include the embodied emissions of the technologies to get a more complete picture of the environmental footprint of the energy supply for copper production. [ABSTRACT FROM AUTHOR]