• Energy Research
• 2021-2025close
• National Science Foundation close

Solar and wind power are now cheaper than fossil fuels but are intermittent. The extra supply-side variability implies growing benefits of using real-time retail pricing (RTP). We evaluate the potential gains of RTP using a model that jointly solves investment, supply, storage, and demand to obtain a chronologically detailed dynamic equilibrium for the island of Oahu, Hawai'i. We find that RTP reduces costs in high-renewable systems by roughly 6 to 12 times as much as in fossil systems holding demand assumptions fixed, markedly lowering the cost of clean energy integration.

AbstractBillions of years ago, the Earth's waters were dominated by cyanobacteria. These microbes amassed to such formidable numbers, they ushered in a new era—starting with the Great Oxidation Event—fuelled by oxygenic photosynthesis. Throughout the following eon, cyanobacteria ceded portions of their global aerobic power to new photoautotrophs with the rise of eukaryotes (i.e. algae and higher plants), which co‐existed with cyanobacteria in aquatic ecosystems. Yet while cyanobacteria's ecological success story is one of the most notorious within our planet's biogeochemical history, scientists to this day still seek to unlock the secrets of their triumph. Now, the Anthropocene has ushered in a new era fuelled by excessive nutrient inputs and greenhouse gas emissions, which are again reshaping the Earth's biomes. In response, we are experiencing an increase in global cyanobacterial bloom distribution, duration, and frequency, leading to unbalanced, and in many instances degraded, ecosystems. A critical component of the cyanobacterial resurgence is the freshwater‐marine continuum: which serves to transport blooms, and the toxins they produce, on the premise that “water flows downhill”. Here, we identify drivers contributing to the cyanobacterial comeback and discuss future implications in the context of environmental and human health along the aquatic continuum. This Minireview addresses the overlooked problem of the freshwater to marine continuum and the effects of nutrients and toxic cyanobacterial blooms moving along these waters. Marine and freshwater research have historically been conducted in isolation and independently of one another. Yet, this approach fails to account for the interchangeable transit of nutrients and biology through and between these freshwater and marine systems, a phenomenon that is becoming a major problem around the globe. This Minireview highlights what we know and the challenges that lie ahead.

As residential photovoltaic (PV) system installations continue to increase rapidly, utilities need to identify the locations of these new components to manage the unconventional two-way power flow and maintain sustainable management of distribution grids. But historical records are unreliable and constant re-assessment of active residential PV locations is resource intensive. To resolve these issues, we propose to model the solar detection problem in a machine learning set up based on labeled data, e.g., supervised learning. However, the challenge for most utilities is limited labels or labels on only one type of users. Therefore, we design new semi-supervised learning and one-class classification methods based on autoencoders, which greatly improve the nonlinear data representation of human behavior and solar behavior. The proposed methods have been tested and validated not only on synthetic data based on a publicly available dataset, but also on real-world data from utility partners. The numerical results show robust detection accuracy, laying down the foundation for managing distributed energy resources in distribution grids.

This work introduces statistical models for the energy harvested from the in-home hybrid power line-wireless channel in the frequency band from 0 to 100 MHz. Based on numerical analyses carried out over the data set obtained from a measurement campaign together with the use of the maximum likelihood value criterion and the adoption of five distinct power masks for power allocation, it is shown that the log-normal distribution yields the best model for the energies harvested from the free-of-noise received signal and from the additive noise in this setting. Additionally, the total harvested energy can be modeled as the sum of these two statistically independent random variables. Thus, it is shown that the energies harvested from this kind of hybrid channel is an easy-to-simulate phenomenon when carrying out research related to energy-efficient and self-sustainable networks.

Family and caregiving leave are increasingly important dimensions for careers in academic science, and for vital, sustainable institutional structures. These forms of leave are intended to support equity, and particularly gender equity. A key question is how the actual use of leave affects critical milestones of advancement for women—compared to men—in (1) time to tenure and (2) the odds of promotion to full professor. We address this question with descriptive statistics and event history analyses, based on responses to a survey of 3688 US faculty members in 4 scientific fields within a range of Carnegie institutional types. We find that leave that stops the tenure clock extends time to tenure for both men and women—the effect is gender neutral. Promotion to full professor is another matter. Being a woman has a strong negative effect on the likelihood of promotion to full professor, and women are especially disadvantaged in promotion when they used tenure leave years earlier. These findings have implications for a life-course perspective on gender and advancement in academic science, the roles of caretaking and leave, and the intended and unintended consequences of leave policies for equitable and sustainable university systems.

For fast timescales or long prediction horizons, the AC optimal power flow (OPF) problem becomes a computational challenge for large-scale, realistic AC networks. To overcome this challenge, this paper presents a novel network reduction methodology that leverages an efficient mixed-integer linear programming (MILP) formulation of a Kron-based reduction that is optimal in the sense that it balances the degree of the reduction with resulting modeling errors in the reduced network. The method takes as inputs the full AC network and a pre-computed library of AC load flow data and uses the graph Laplacian to constraint nodal reductions to only be feasible for neighbors of non-reduced nodes. This results in a highly effective MILP formulation which is embedded within an iterative scheme to successively improve the Kron-based network reduction until convergence. The resulting optimal network reduction is, thus, grounded in the physics of the full network. The accuracy of the network reduction methodology is then explored for a 100+ node medium-voltage radial distribution feeder example across a wide range of operating conditions. It is finally shown that a network reduction of 25-85% can be achieved within seconds and with worst-case voltage magnitude deviation errors within any super node cluster of less than 0.01pu. These results illustrate that the proposed optimization-based approach to Kron reduction of networks is viable for larger networks and suitable for use within various power system applications.

AbstractOver the last two decades, anomalous warming events have been observed in coastal Antarctic regions. While these events have been documented in the Ross Sea sector, the Antarctic interior is believed to have been buffered from warming. In this work, we present data from lakes located near Mt. Heekin and Thanksgiving Valley (~85° S) along the Shackleton Glacier, which are believed to be the southern-most Antarctic dry valley lakes. In 2018, the lakes were characterized, repeat satellite images were examined, and lake water chemistry was measured. Our analysis shows that lake areas recently increased, and the water-soluble ion chemistry indicates a flushing of salts from periglacial soils, likely from increased glacial melt as illustrated by water isotope data. Our results show that high southern latitude ice-free areas have likely been affected by warm pulses over the past 60 years and these pulses may be quasi-synchronous throughout the Transantarctic Mountains.