2020 47th IEEE Photovoltaic Specialists Conference (PVSC) 2020
DOI: 10.1109/pvsc45281.2020.9300653
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Method for Quantifying Value of Storage Toward Reaching 100% Renewable Electricity

Abstract: Optimization models can be quite powerful in identifying a pathway to lowest cost zero-carbon energy systems. However, it is less obvious how to invert the models to calculate the target cost and duration of storage needed for that storage to be a significant solution. Storage is a dispatchable and flexible resource with the ability to perform many functions of grid support, further complicating the analysis. This paper complements existing papers by presenting an academic study of a simplified energy system, … Show more

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Cited by 7 publications
(3 citation statements)
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“…More commonly, solar electricity contributes more than half of the total electricity with some daytime electricity stored for nighttime use. For a more in-depth exploration of understanding the value of storage, see our companion paper in these proceedings [7].…”
Section: Resultsmentioning
confidence: 99%
“…More commonly, solar electricity contributes more than half of the total electricity with some daytime electricity stored for nighttime use. For a more in-depth exploration of understanding the value of storage, see our companion paper in these proceedings [7].…”
Section: Resultsmentioning
confidence: 99%
“…Second, challenges have begun to arise to the potential for diffusion-based strategies to continue to accelerate solar development enough to decarbonize energy systems by 2050. These include: technical hurdles in the integration of renewables into grid-based electricity systems [31], especially when combined with social patterns of energy demand that poorly match solar generation patterns [32]; shifts in costs from solar panels to installation and balance-of-system costs that are not as easily reduced through technology innovation [33]; snarls in global supply chains that limit availability of key materials or technologies and slow or even reverse price declines [34]; social and industrial opposition to renewable energy projects, e.g., due to concerns about land use or impacts on utility business models [35]; and rising costs of land and transmission lines to connect rural projects to urban centers [36]. Growing doubts also question whether markets can accelerate fast enough, even with substantial policy incentives, to meet ambitious decarbonization targets and address other critical challenges for global energy systems, including to enhance energy access worldwide, to promote energy justice, and to decrease energy vulnerabilities facing many communities in an era of rising climate risks [37].…”
Section: The Limits Of Diffusion-based Approachesmentioning
confidence: 99%
“…The model is spatially resolved in seven (7) balancing zones with five (5) zones capturing California balancing authorities and two zones that represent regional aggregations of outof-state balancing authorities [4] as shown in Fig 1 . The model performs load balancing, provides planning reserve and applies operational constraints. Input files define 171 electricity generating resources, each with associated cost, starting capacity, guidance about increasing or retiring that capacity, ability to provide ancillary services, zone location, constraints on rate of ramping output, etc.…”
Section: General Assumptions Of Resolvementioning
confidence: 99%