Publications

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In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (∼C/30). In this batch cell system, the effect of ions’ crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people’s access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users’ side.

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Reliable engineering quality, safety, and performance are essential for a successful energy-storage project. The commercial energy-storage industry is entering its most formative period, which will impact the arc of the industry's development for years to come. Project announcements are increasing in both frequency and scale. Energy-storage systems (ESSs) are establishing themselves as a viable option for deployment across the entire electricity infrastructure as grid-connected energy-storage assets or in combination with other grid assets, such as hybrid generators. In conclusion, how the industry will evolve-in direction and degree-will depend largely on building a firm foundation of sound engineering requirements into project expectations.

The role of power electronics in the utility grid is continually expanding. As converter design processes mature and new advanced materials become available, the pace of industry adoption is poised to accelerate. Looking forward, we can envision a future in which power electronics are as integral to grid functionality as the transformer is today. The Enabling Advanced Power Electronics Technologies for the Next Generation Electric Utility Grid Workshop was organized by Sandia National Laboratories and held in Albuquerque, New Mexico, July 17 - 18, 2018 . The workshop helped attendees to gain a broader understanding of power electronics R&D needs—from materials to systems—for the next generation electric utility grid. This report summarizes discussions and presentations from the workshop and identifies opportunities for future efforts.

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Energy storage is a unique grid asset in that it is capable of providing a number of grid services. In market areas, these grid services are only as valuable as the market prices for the services provided. This paper formulates the optimization problem for maximizing energy storage revenue from arbitrage (day-ahead and real-time markets) in the California Independent System Operator (CAISO) market. The optimization algorithm was then applied to three years of historical market data (2014-2016) at 2200 nodes to quantify the locational and time-varying nature of potential revenue. The optimization assumed perfect foresight, so it provides an upper bound on the maximum expected revenue. Since California is starting to experience negative locational marginal prices (LMPs) because of increased renewable generation, the optimization includes a duty cycle constraint to handle negative LMPs. Two additional trading algorithms were tested that do not require perfect foresight. The first sets a buy price threshold and a sell price threshold (e.g., limit orders) for participation in the real time market, subject to the constraints of the energy storage system. The second uses the day-ahead prices as an estimate for the real time prices and performs an optimization on a rolling time horizon. The simple threshold algorithm performed the best, but both fell well short of the potential revenue identified by the optimization with perfect foresight.

Techno-economic analyses of energy storage currently use constant-efficiency energy flow models. In practice, charge/discharge efficiency of energy storage varies as a function of state-of-charge, temperature, charge/discharge power. Therefore, using the constant-efficiency energy flow models will cause suboptimal results. This work focuses on incorporating nonlinear energy flow models based on nonlinear efficiency models in the revenue maximization problem of energy storage. Dynamic programming is used to solve the optimization problem. A case studies is conducted to maximize the revenue of a Vanadium Redox Flow Battery (VRFB) system in PJM's energy and frequency regulation market.

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