34 research outputs found
An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data
This paper presents an independent component analysis (ICA) based
unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC)
load disaggregation using low-resolution (e.g., 15 minutes) smart meter data.
We first demonstrate that electricity consumption profiles on mild-temperature
days can be used to estimate the non-HVAC base load on hot days. A residual
load profile can then be calculated by subtracting the mild-day load profile
from the hot-day load profile. The residual load profiles are processed using
ICA for HVAC load extraction. An optimization-based algorithm is proposed for
post-adjustment of the ICA results, considering two bounding factors for
enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC
energy bounds computed based on the relationship between HVAC load and
temperature to remove unrealistic HVAC load spikes. Second, we exploit the
dependency between the daily nocturnal and diurnal loads extracted from
historical meter data to smooth the base load profile. Pecan Street data with
sub-metered HVAC data were used to test and validate the proposed
methods.Simulation results demonstrated that the proposed method is
computationally efficient and robust across multiple customers
A Load Switching Group based Feeder-level Microgrid Energy Management Algorithm for Service Restoration in Power Distribution System
This paper presents a load switching group based energy management system
(LSG-EMS) for operating microgrids on a distribution feeder powered by one or
multiple grid-forming distributed energy resources. Loads on a distribution
feeder are divided into load switching groups that can be remotely switched on
and off. The LSG-EMS algorithm, formulated as a mixed-integer linear
programming (MILP) problem, has an objective function of maximizing the served
loads while minimizing the total number of switching actions. A new set of
topology constraints are developed for allowing multiple microgrids to be
formed on the feeder and selecting the optimal supply path. Customer comfort is
accounted for by maximizing the supply duration in the customer preferred
service period and enforcing a minimum service duration. The proposed method is
demonstrated on a modified IEEE 33-bus system using actual customer data.
Simulation results show that the LSG-EMS successfully coordinates multiple
grid-forming sources by selecting an optimal supply topology that maximizes the
supply period of both the critical and noncritical loads while minimizing
customer service interruptions in the service restoration process.Comment: 5 pages, 7 figures, submitted to 2021 IEEE PES General Meetin
A Novel Feeder-level Microgrid Unit Commitment Algorithm Considering Cold-load Pickup, Phase Balancing, and Reconfiguration
This paper presents a novel 2-stage microgrid unit commitment (Microgrid-UC)
algorithm considering cold-load pickup (CLPU) effects, three-phase load
balancing requirements, and feasible reconfiguration options. Microgrid-UC
schedules the operation of switches, generators, battery energy storage
systems, and demand response resources to supply 3-phase unbalanced loads in an
islanded microgrid for multiple days. A performance-based CLPU model is
developed to estimate additional energy needs of CLPU so that CLPU can be
formulated into the traditional 2-stage UC scheduling process. A per-phase
demand response budget term is added to the 1st stage UC objective function to
meet 3-phase load unbalance limits. To reduce computational complexity in the
1st stage UC, we replace the spanning tree method with a feasible
reconfiguration topology list method. The proposed algorithm is developed on a
modified IEEE 123-bus system and tested on the real-time simulation testbed
using actual load and PV data. Simulation results show that Microgrid-UC
successfully accounts for CLPU, phase imbalance, and feeder reconfiguration
requirements.Comment: 10 pages, submitted to IEEE Transactions on Smart Gri
Challenges in QCD matter physics - The Compressed Baryonic Matter experiment at FAIR
Substantial experimental and theoretical efforts worldwide are devoted to
explore the phase diagram of strongly interacting matter. At LHC and top RHIC
energies, QCD matter is studied at very high temperatures and nearly vanishing
net-baryon densities. There is evidence that a Quark-Gluon-Plasma (QGP) was
created at experiments at RHIC and LHC. The transition from the QGP back to the
hadron gas is found to be a smooth cross over. For larger net-baryon densities
and lower temperatures, it is expected that the QCD phase diagram exhibits a
rich structure, such as a first-order phase transition between hadronic and
partonic matter which terminates in a critical point, or exotic phases like
quarkyonic matter. The discovery of these landmarks would be a breakthrough in
our understanding of the strong interaction and is therefore in the focus of
various high-energy heavy-ion research programs. The Compressed Baryonic Matter
(CBM) experiment at FAIR will play a unique role in the exploration of the QCD
phase diagram in the region of high net-baryon densities, because it is
designed to run at unprecedented interaction rates. High-rate operation is the
key prerequisite for high-precision measurements of multi-differential
observables and of rare diagnostic probes which are sensitive to the dense
phase of the nuclear fireball. The goal of the CBM experiment at SIS100
(sqrt(s_NN) = 2.7 - 4.9 GeV) is to discover fundamental properties of QCD
matter: the phase structure at large baryon-chemical potentials (mu_B > 500
MeV), effects of chiral symmetry, and the equation-of-state at high density as
it is expected to occur in the core of neutron stars. In this article, we
review the motivation for and the physics programme of CBM, including
activities before the start of data taking in 2022, in the context of the
worldwide efforts to explore high-density QCD matter.Comment: 15 pages, 11 figures. Published in European Physical Journal
Sizing optimization for island microgrid with pumped storage system considering demand response
Abstract Currently, small islands are facing an energy supply shortage, which has led to considerable concern. Establishing an island microgrid is a relatively good solution to the problem. However, high investment costs restrict its application. In this paper, micro pumped storage (MPS) is used as an energy storage system (ESS) for islands with good geographical conditions, and deferrable appliance is treated as the virtual power source which can be used in the planning and operational processes. Household acceptance of demand response (DR) is indicated by the demand response participation degree (DRPD), and a sizing optimization model for considering the demand response of household appliances in an island microgrid is proposed. The particle swarm optimization (PSO) is used to obtain the optimal sizing of all major devices. In addition, the battery storage (BS) scheme is used as the control group. The results of case studies demonstrate that the proposed method is effective, and the DR of deferrable appliances and the application of MPS can significantly reduce island microgrid investment. Sensitivity analysis on the total load of the island and the water head of the MPS are conducted
Tripsense : a trust-based vehicular platoon crowdsensing scheme with privacy preservation in VANETs
In this paper, we propose a trust-based vehicular platoon crowdsensing scheme, named TripSense, in VANET. The proposed TripSense scheme introduces a trust-based system to evaluate vehicles’ sensing abilities and then selects the more capable vehicles in order to improve sensing results accuracy. In addition, the sensing tasks are accomplished by platoon member vehicles and preprocessed by platoon head vehicles before the data are uploaded to server. Hence, it is less time-consuming and more efficient compared with the way where the data are submitted by individual platoon member vehicles. Hence it is more suitable in ephemeral networks like VANET. Moreover, our proposed TripSense scheme integrates unlinkable pseudo-ID techniques to achieve PM vehicle identity privacy, and employs a privacy-preserving sensing vehicle selection scheme without involving the PM vehicle’s trust score to keep its location privacy. Detailed security analysis shows that our proposed TripSense scheme not only achieves desirable privacy requirements but also resists against attacks launched by adversaries. In addition, extensive simulations are conducted to show the correctness and effectiveness of our proposed scheme.Published versio