Distributed Co-simulation for Smart Homes Energy Management in the Presence of Electrical Thermal Storage

Distributed generation and energy storage technologies have helped SmartGrid projects gain great momentum over the last decade. However, despite a large number of pilot and demonstration projects, low-level information is often unavailable. Therefore, tools for defining and building different operation scenarios are required. These tools can facilitate adopting novel approaches to multi-domain energy management. This paper proposes a distributed, flexible co-simulation framework to integrate simulators from separate domains and platforms. Particularly, the proposed scheme enables the development of hybrid thermal-electric systems for smart buildings. In this study, an object-oriented approach to modeling electrical thermal storage (ETS) units is also suggested. The evaluation process is carried out using real-world data. A case study is practiced by designing a residential agent that performs model predictive control (MPC) of residential heating load in the presence of ETS. The results show that proper integration of ETS into Home Energy Management Systems (HEMSs) can achieve economic savings of up to 45 %. The findings of this study demonstrate ETS's high potential for reducing customer bills while satisfying users' comfort. Furthermore, they recommend practical strategies for short-term planning of smart grids by increasing their flexibility based on ETS-integrated Demand Response (DR) programs. © 2022 IEEE

Techno-economic Feasibility of A Trust and Grid-aware Coordination Scheme

The massive penetration of active customers throughout Home Energy Management Systems (HEMS) may cause adverse effects on the power grid, including rebound peaks, instabilities, and power congestion. The concept of coordination has arisen in literature to mitigate these effects and relieve power grid stress. Their advantages have been discussed for different market types as well as at different grid scales. However, it is imperative to develop proofs-of-concept and test not only the economic feasibility of such programs but also the technical one. This paper presents a cosimulation-based framework that facilitates economic and technical studies for coordination programs. A case study is presented, with eighteen residential users and a local coordinator within a Stackelberg game. At the customer level, flexibility is achieved through electric thermal storage (ETS). The program exploits salient features of blockchain algorithms to increase security at the demand aggregation level. The technical feasibility was evaluated through the Peak-to-average (PAR) ratio, active power losses, and the voltage profile using power flow methods over the IEEE 33-node feeder. This study’s findings demonstrate the coordination programs’ ability to bring economic benefits and reduce the PAR. Furthermore, they suggest that although coordination programs can assist in flattening the power profile, they could create adverse effects on the power grid in critical scenarios

Rhodium single-atom catalyst design through oxide support modulation for selective gas-phase ethylene hydroformylation

A frontier challenge in single-atom (SA) catalysis is the design of fully inorganic sites capable of emulating the high reaction selectivity traditionally exclusive of organometallic counterparts in homogeneous catalysis. Modulating the direct coordination environment in SA sites, via the exploitation of the oxide support's surface chemistry, stands as a powerful albeit underexplored strategy. We report that isolated Rh atoms stabilized on oxygen-defective SnO2 uniquely unite excellent TOF with essentially full selectivity in the gas-phase hydroformylation of ethylene, inhibiting the thermodynamically favored olefin hydrogenation. Density Functional Theory calculations and surface characterization suggest that substantial depletion of the catalyst surface in lattice oxygen, energetically facile on SnO2, is key to unlock a high coordination pliability at the mononuclear Rh centers, leading to an exceptional performance which is on par with that of molecular catalysts in liquid media

Rhodium Single‐Atom Catalyst Design through Oxide Support Modulation for Selective Gas‐Phase Ethylene Hydroformylation

A frontier challenge in single-atom (SA) catalysis is the design of fully inorganic sites capable of emulating the high reaction selectivity traditionally exclusive of organometallic counterparts in homogeneous catalysis. Modulating the direct coordination environment in SA sites, via the exploitation of the oxide support\u27s surface chemistry, stands as a powerful albeit underexplored strategy. We report that isolated Rh atoms stabilized on oxygen-defective SnO$_2$ uniquely unite excellent TOF with essentially full selectivity in the gas-phase hydroformylation of ethylene, inhibiting the thermodynamically favored olefin hydrogenation. Density Functional Theory calculations and surface characterization suggest that substantial depletion of the catalyst surface in lattice oxygen, energetically facile on SnO$_2$, is key to unlock a high coordination pliability at the mononuclear Rh centers, leading to an exceptional performance which is on par with that of molecular catalysts in liquid media

Epidemiological trends and clinical outcomes of cryptococcosis in a medically insured population in the United States: a claims-based analysis from 2017 to 2019

Background: Emerging risk factors highlight the need for an updated understanding of cryptococcosis in the United States. Objective: Describe the epidemiological trends and clinical outcomes of cryptococcosis in three patient groups: people with HIV (PWH), non-HIV-infected and non-transplant (NHNT) patients, and patients with a history of solid organ transplantation. Methods: We utilized data from the Merative Medicaid Database to identify individuals aged 18 and above with cryptococcosis based on the International Classification of Diseases, Tenth Revision diagnosis codes from January 2017 to December 2019. Patients were stratified into PWH, NHNT patients, and transplant recipients according to Infectious Diseases Society of America guidelines. Baseline characteristics, types of cryptococcosis, hospitalization details, and in-hospital mortality rates were compared across groups. Results: Among 703 patients, 59.7% were PWH, 35.6% were NHNT, and 4.7% were transplant recipients. PWH were more likely to be younger, male, identify as Black, and have fewer comorbidities than patients in the NHNT and transplant groups. Notably, 24% of NHNT patients lacked comorbidities. Central nervous system, pulmonary, and disseminated cryptococcosis were most common overall (60%, 14%, and 11%, respectively). The incidence of cryptococcosis fluctuated throughout the study period. PWH accounted for over 50% of cases from June 2017 to June 2019, but this proportion decreased to 47% from July to December 2019. Among the 52% of patients requiring hospitalization, 61% were PWH and 35% were NHNT patients. PWH had longer hospital stays. In-hospital mortality at 90days was significantly higher in NHNT patients (22%) compared to PWH (7%) and transplant recipients (0%). One-year mortality remained lowest among PWH (8%) compared to NHNT patients (22%) and transplant recipients (13%). Conclusion: In this study, most cases of cryptococcosis were PWH. Interestingly, while the incidence remained relatively stable in PWH, it slightly increased in those without HIV by the end of the study period. Mortality was highest in NHNT patients

Local invertibility in Sobolev spaces with applications to nematic elastomers and magnetoelasticity

We define a class of deformations in W^1,p(\u3a9,R^n), p>n 121, with positive Jacobian that do not exhibit cavitation. We characterize that class in terms of the non-negativity of the topological degree and the equality between the distributional determinant and the pointwise determinant of the gradient. Maps in this class are shown to satisfy a property of weak monotonicity, and, as a consequence, they enjoy an extra degree of regularity. We also prove that these deformations are locally invertible; moreover, the neighbourhood of invertibility is stable along a weak convergent sequence in W^1,p, and the sequence of local inverses converges to the local inverse. We use those features to show weak lower semicontinuity of functionals defined in the deformed configuration and functionals involving composition of maps. We apply those results to prove existence of minimizers in some models for nematic elastomers and magnetoelasticity

Econometric analysis of the industrial growth determinants in Colombia

An econometric study is carried out using a panel data model with fixed effects to identify the industrial development determinants in Colombia during the term 2005–2015. The database used in the study corresponds to World Bank and the Colombian state. The determinants of industrial growth identified at the theoretical level that allow the enhancement of productive capacities to face foreign competition in Colombia are: innovation; networks of innovations and knowledge among companies and organizations; the interest rate; the capital-product ratio, the unit labor cost; and the exchange rate. The amount invested in scientific, technological and innovation activities by industrial group is the only variable that is not significant in the model

A practical approach to residential appliances on-line anomaly detection: A case study of standard and smart refrigerators

Anomaly detection is a significant application of residential appliances load monitoring systems. As an essential prerequisite of load diagnosis services, anomaly detection is critical to energy saving and occupant comfort actualization. Notwithstanding, the investigation into diagnosis of household anomalous appliances has not been decently taken into consideration. This paper presents an extensive study about operation-time anomaly detection of household devices particularly, refrigerators, in terms of appliances candidate, by utilizing their energy consumption data. Energy as a quantitative property of electrical loads, is a reliable information for a robust diagnosis. Additionally, it is very practical since it is low-priced to measure and definite to interpret. Subsequently, an on-line anomaly detection approach is proposed to effectively determine the anomalous operation of the household appliances candidate. The proposed approach is capable of continuously monitoring energy consumption and providing dynamic information for anomaly detection algorithms. A machine learning-based technique is employed to construct efficient models of appliances normal behavior with application to operation-time anomaly detection. The performance of the suggested approach is evaluated through a set of diagnostic tests, by utilizing normal and anomalous data of targeted devices, measured by an acquisition system. In addition, a comparison analysis is provided in order to further examine the effectiveness of the developed mechanism by exploiting a public database. Moreover, this study elaborates sensible remarks on an effective management of anomaly detection and diagnosis decision phases, pivotal to correctly recognition of a faulty/abnormal operation. Indeed, through experimental results of case studies, this work assists in the development of a load monitoring and anomaly detection system with practical implementation

Power estimation of multiple two-state loads using a probabilistic non-intrusive approach

This paper investigates a non-intrusive approach of retrieving electric space heater (ESH) power profiles from a residential aggregated signal. In cold-climate regions with heating appliances controlled by electronic thermostats, an accurate non-intrusive recognition of power profiles is a challenging task. Accordingly, a robust disaggregation approach based on the difference factorial hidden Markov model (DFHMM) and the Kronecker operation is contributed. The proposed method aims to uncover the underlying stochastic tow-state models of ESHs using their common prior knowledge. The major advantage of the developed load-monitoring architecture consists of modeling simplicity and inference as well as load-detection efficacy in the presence of perturbations from other unknown loads. The experimental results prove the effectiveness of the method in manipulating the challenging case of multiple two-state loads with a high event overlapping probability