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Extreme outside temperatures resulting from heat waves, winter storms, and similar weather-related events trigger the Heating Ventilation and Air Conditioning (HVAC) systems, resulting in challenging, and potentially catastrophic, peak loads. As a consequence, such extreme outside temperatures put a strain on power grids and may thus lead to blackouts. To avoid the financial and personal repercussions of peak loads, demand response and power conservation represent promising solutions. Despite numerous efforts, it has been shown that the current state-of-the-art fails to consider (1) the complexity of human behavior when interacting with power conservation systems and (2) realistic home-level power dynamics. As a consequence, this leads to approaches that are (1) ineffective due to poor long-term user engagement and (2) too abstract to be used in real-world settings. In this article, we propose an auction theory-based power conservation framework for HVAC designed to address such individual human component through a three-fold approach:personalized preferencesof power conservation,models of realistic user behavior, andrealistic home-level power dynamics. In our framework, the System Operator sends Load Serving Entities (LSEs) the required power saving to tackle peak loads at the residential distribution feeder. Each LSE then prompts its users to providebids, i.e.,personalized preferencesof thermostat temperature adjustments, along with corresponding financial compensations. We employmodels of realistic user behaviorby means of online surveys to gather user bids and evaluate user interaction with such system.Realistic home-level power dynamicsare implemented by our machine learning-based Power Saving Predictions (PSP) algorithm, calculating the individual power savings in each user’s home resulting from such bids. A machine learning-based PSPs algorithm is executed by the users’ Smart Energy Management System (SEMS). PSP translates temperature adjustments into the corresponding power savings. Then, the SEMS sends bids back to the LSE, which selects the auction winners through an optimization problem called POwer Conservation Optimization (POCO). We prove that POCO is NP-hard, and thus provide two approaches to solve this problem. One approach is an optimal pseudo-polynomial algorithm called DYnamic programming Power Saving (DYPS), while the second is a heuristic polynomial time algorithm called Greedy Ranking AllocatioN (GRAN). EnergyPlus, the high-fidelity and gold-standard energy simulator funded by the U.S. Department of Energy, was used to validate our experiments, as well as to collect data to train PSP. We further evaluate the results of the auctions across several scenarios, showing that, as expected, DYPS finds the optimal solution, while GRAN outperforms recent state-of-the-art approaches. 

Abstract Electrons in Earth's outer radiation belt are highly dynamic, with fluxes changing by up to orders of magnitude. The penetration of electrons from the outer belt to the inner belt is one such change observed during geomagnetic storms and was previously observed in electrons up to 1 MeV for some strong storms observed by the Van Allen Probes. We analyze pulse height analysis data from the Relativistic Electric and Proton Telescope (REPT) on the Van Allen Probes to produce electron flux measurements with lower minimum energy and significantly improved resolution compared to the standard REPT data and show that electron penetrations into the inner belt (L ≤ 2) extend to at least 1.3 MeV and penetrations into the slot region (2 < L < 2.8) extend to at least 1.5 MeV during certain geomagnetic storms. We also demonstrate that these penetrations are associated with butterfly pitch angle distributions from 1 to 1.3 MeV. 

Abstract Recent multi-point measurements, in particular from the Magnetospheric Multiscale (MMS) spacecraft, have advanced the understanding of micro-scale aspects of magnetic reconnection. In addition, the MMS mission, as part of the Heliospheric System Observatory, combined with recent advances in global magnetospheric modeling, have furthered the understanding of meso- and global-scale structure and consequences of reconnection. Magnetic reconnection at the dayside magnetopause and in the magnetotail are the drivers of the global Dungey cycle, a classical picture of global magnetospheric circulation. Some recent advances in the global structure and consequences of reconnection that are addressed here include a detailed understanding of the location and steadiness of reconnection at the dayside magnetopause, the importance of multiple plasma sources in the global circulation, and reconnection consequences in the magnetotail. These advances notwithstanding, there are important questions about global reconnection that remain. These questions focus on how multiple reconnection and reconnection variability fit into and complicate the Dungey Cycle picture of global magnetospheric circulation. 

Abstract The Van Allen Probes Electric Fields and Waves (EFW) instrument provided measurements of electric fields and spacecraft floating potentials over a wide dynamic range from DC to 6.5 kHz near the equatorial plane of the inner magnetosphere between 600 km altitude and 5.8 Re geocentric distance from October 2012 to November 2019. The two identical instruments provided data to investigate the quasi-static and low frequency fields that drive large-scale convection, waves induced by interplanetary shock impacts that result in rapid relativistic particle energization, ultra-low frequency (ULF) MHD waves which can drive radial diffusion, and higher frequency wave fields and time domain structures that provide particle pitch angle scattering and energization. In addition, measurements of the spacecraft potential provided a density estimate in cold plasmas ( $$<20~\text{eV}$$ < 20 eV ) from 10 to $$3000~\text{cm}^{-3}$$ 3000 cm − 3 . The EFW instrument provided analog electric field signals to EMFISIS for wave analysis, and it received 3d analog signals from the EMFISIS search coil sensors for inclusion in high time resolution waveform data. The electric fields and potentials were measured by current-biased spherical sensors deployed at the end of four 50 m booms in the spacecraft spin plane (spin period $$\sim11~\text{sec}$$ ∼ 11 sec ) and a pair of stacer booms with a total tip-tip separation of 15 m along the spin axis. Survey waveform measurements at 16 and/or 32 S/sec (with a nominal uncertainty of 0.3 mV/m over the prime mission) were available continuously while burst waveform captures at up to 16,384 S/sec provided high frequency waveforms. This post-mission paper provides the reader with information useful for accessing, understanding and using EFW data. Selected science results are discussed and used to highlight instrument capabilities. Science quantities, data quality and error sources, and analysis routines are documented.