Nestor A. Sepulveda’s research while affiliated with Massachusetts Institute of Technology and other places

• Download : Download high-res image (263KB) • Download : Download full-size image Jesse D. Jenkins is an assistant professor at Princeton University in the department of mechanical and aerospace engineering and the Andlinger Center for Energy and the Environment. He is a macro-scale energy systems engineer with a focus on the rapidly evolving electricity sector and leads the Princeton ZERO Lab, which focuses on improving and applying optimization-based energy systems models to evaluate low-carbon energy technologies and generate insights to guide policy and planning decisions. Jesse earned a PhD and SM from the Massachusetts Institute of Technology and was previously a postdoctoral environmental fellow at Harvard University. • Download : Download high-res image (303KB) • Download : Download full-size image Nestor A. Sepulveda is a management consultant working in corporate strategy, technology development, decarbonization, sustainable investing, and advanced analytics. Nestor earned a PhD from the Massachusetts Institute of Technology developing methodologies that combine operations research and analytics to guide the energy transition and cleantech development. He received a SM in technology and policy working on energy policy and economics and a SM in nuclear science and engineering, both from MIT. Nestor is a former Naval Officer who served for more than 10 years in the Chilean Navy.

Long-duration energy storage (LDES) is a potential solution to intermittency in renewable energy generation. In this study we have evaluated the role of LDES in decarbonized electricity systems and identified the cost and efficiency performance necessary for LDES to substantially reduce electricity costs and displace firm low-carbon generation. Our findings show that energy storage capacity cost and discharge efficiency are the most important performance parameters. Charge/discharge capacity cost and charge efficiency play secondary roles. Energy capacity costs must be ≤US$20 kWh–1 to reduce electricity costs by ≥10$1 kWh–1 to fully displace all modelled firm low-carbon generation technologies. Electrification of end uses in a northern latitude context makes full displacement of firm generation more challenging and requires performance combinations unlikely to be feasible with known LDES technologies. Finally, LDES systems with the greatest impact on electricity cost and firm generation have storage durations exceeding 100 h. Wind and solar energy must be complemented by a combination of energy storage and firm generating capacity. Here, Sepulveda et al. assess the economic value and system impact of a wide range of possible long-duration energy storage technologies, providing insights to guide innovation and policy.

With declining costs of battery storage, there is growing interest to deploy them in power systems to provide multiple grid services that directly support integration of variable renewable energy (VRE) generation. Here, we assess the holistic system value of energy storage in future grids with increasing wind and solar generation. We also identify the major sources of storage value and their dynamics under different system settings and at increasing storage and wind and solar penetration levels. We use a high temporal resolution capacity expansion model to study least-cost integration of storage in two variants of an abstract power system that is populated with load and VRE profiles consistent with the U.S. Northeast (North) and Texas (South) regions. For both systems, storage value originates primarily from deferring investments in generation capacity (VRE, natural gas) and transmission, and generally declines with increasing storage penetration. Increasing VRE penetration from 40% to 60% increases the value of storage, but only enough to make storage capacity up to 4% of peak demand cost-effective at current Lithium-ion capital costs. With future capital costs of $150/kWh for 4 h duration storage, the cost-effective storage penetration ranges between 4% and 16% of peak demand across the system scenarios studied here. Storage substitution of natural gas capacity is dependent on the VRE resource mix and penetration level, but is less than 1 GW per GW of storage added for the durations (2, 4 or 8 h) considered here. Increasing storage duration increases storage value in some cases, but this increase in value may be insufficient to compensate for the increase in capital cost per kW even under the future cost scenario.

We investigate the role of firm low-carbon resources in decarbonizing power generation in combination with variable renewable resources, battery energy storage, demand flexibility, and long-distance transmission. We evaluate nearly 1,000 cases covering varying CO2 limits, technological uncertainties, and geographic differences in demand and renewable resource potential. Availability of firm low-carbon technologies, including nuclear, natural gas with carbon capture and sequestration, and bioenergy, reduces electricity costs by 10%–62% across fully decarbonized cases. Below 50 gCO2/kWh, these resources lower costs in the vast majority of cases. Additionally, as emissions limits decrease, installed capacity of several resources changes non-monotonically. This underscores the need to evaluate near-term policy and investment decisions based on contributions to long-term decarbonization rather than interim goals. Installed capacity for all resources is also strongly affected by uncertain technology parameters. This emphasizes the importance of a broad research portfolio and flexible policy support that expands rather than constrains future options.

We develop three novel enhanced mixed integer-linear representations of the power limit of the battery and its efficiency as a function of the charge and discharge power and the state of charge of the battery, which can be directly implemented in large-scale power systems models and solved with commercial optimization solvers. Using these battery representations, we conduct a techno-economic analysis of the performance of a 10 MWh lithium-ion battery system testing the effect of a 5-min vs. a 60-min price signal on profits using real time prices from a selected node in the MISO electricity market. Results show that models of lithium-ion batteries where the power limits and efficiency are held constant overestimate profits by 10% compared to those obtained from an enhanced representation that more closely matches the real behavior of the battery. When the battery system is exposed to a 5-min price signal, the energy arbitrage profitability improves by 60% compared to that from hourly price exposure. These results indicate that a more accurate representation of li-ion batteries as well as the market rules that govern the frequency of electricity prices can play a major role on the estimation of the value of battery technologies for power grid applications.