On the Optimal Energy Controls for Large Scale Residential Communities Including Smart Homes

Residences with smart home energy management (HEM) systems and solar generation are modifying domestic load profiles. Moreover, the growing penetration of solar photovoltaic (PV) energy brings the total net power demand further down as houses become local generators. High PV penetration introduces technical challenges for the power system including the duck curve . This paper proposes a co-simulation framework for high PV penetration smart energy communities which allows the simultaneous simulation of home energy consumption along with control algorithms for each house, as well as system power flow. Models are developed and presented for one of the largest rural field demonstrators for smart energy technologies comprising industrial, business, and 5,000+ residences, located in Glasgow, KY, US. The objectives of the HEM system are to reduce the total energy consumption and peak demand by controlling the heating ventilation and air-conditioning (HVAC) systems, water heaters, and batteries, so as to benefit both consumers and the utility. The advantages to the residential consumers include reduced electricity bills and the utility benefits from lower peak demand. Case studies are conducted for typical winter and summer days and simulation and experimental results are presented. The paper also includes long term load prediction for the utility considering different percentages of smart homes

Peak Reduction and Long Term Load Forecasting for Large Residential Communities Including Smart Homes with Energy Storage

Domestic load profiles in the residential sectors are being modified with the adoption of smart home management systems and solar generation. In addition, houses with rooftop PV behave like local generators, contributing to the growth of the penetration of PV energy. Hence, the demand for power is declining day by day. However, the increasing PV penetration causes technical challenges for the power system, such as the “duck curve”. This can be addressed through home energy management (HEM) techniques including peak shaving, load shifting with smart home devices. In this regard, electric water heaters (EWH), with high thermal mass and being ubiquitous, are attractive and low-cost energy storage systems. In this article, a case study for one of the largest rural field smart energy technology demonstrators involving business, industries, and more than 5,000 residences, located in Glasgow, KY, US, is presented. Furthermore, a HEM system, which aims to minimize the total energy usage and peak demand by regulating the heating, ventilation, and air-conditioning (HVAC) systems, water heaters, and batteries, thereby benefiting both the utility and the consumer is proposed. This work also demonstrates the ability of EWH to provide ancillary services while maintaining customer comfort. The minimum participation rates for EWH and batteries are calculated and compared with respect to different peak reduction targets. Long term load prediction by considering different fractions of smart homes for the utility is also provided

Competition between normal and intruder states inside the "Island of Inversion"

The beta decay of the exotic 30Ne (N=20) is reported. For the first time, the low-energy level structure of the N=19, 30Na (Tz = 4), is obtained from beta-delayed gamma spectroscopy using fragment-beta-gamma-gamma coincidences. The level structure clearly displays "inversion", i.e., intruder states with mainly 2p2h configurations displacing the normal states to higher excitation energies. The good agreement in excitation energies and the weak and electromagnetic decay patterns with Monte Carlo Shell Model calculations with the SDPF-M interaction in the sdpf valence space illustrates the small d3/2 - f7/2 shell gap. The relative position of the "normal dominant" and "intruder dominant" excited states provides valuable information to understand better the N=20 shell gap.Comment: 4 pages, 5 figure

The Local Cluster Survey II: Disk-Dominated Cluster Galaxies with Suppressed Star Formation

We investigate the role of dense environments in suppressing star formation by studying $\rm \log_{10}(M_\star/M_\odot) > 9.7$ star-forming galaxies in nine clusters from the Local Cluster Survey ($0.0137 < z < 0.0433$) and a large comparison field sample drawn from the Sloan Digital Sky Survey. We compare the star-formation rate (SFR) versus stellar mass relation as a function of environment and morphology. After carefully controlling for mass, we find that in all environments, the degree of SFR suppression increases with increasing bulge-to-total (B/T) ratio. In addition, the SFRs of cluster and infall galaxies at a fixed mass are more suppressed than their field counterparts at all values of B/T. These results suggest a quenching mechanism that is linked to bulge growth that operates in all environments and an additional mechanism that further reduces the SFRs of galaxies in dense environments. We limit the sample to $B/T < 0.3$ galaxies to control for the trends with morphology and find that the excess population of cluster galaxies with suppressed SFRs persists. We model the timescale associated with the decline of SFRs in dense environments and find that the observed SFRs of the cluster core galaxies are consistent with a range of models including: a mechanism that acts slowly and continuously over a long (2-5 Gyr) timescale, and a more rapid ($<1$ Gyr) quenching event that occurs after a delay period of 1-6 Gyr. Quenching may therefore start immediately after galaxies enter clusters.Comment: 17 pages, 12 figure