67 research outputs found

    Continuous Multiagent Control using Collective Behavior Entropy for Large-Scale Home Energy Management

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    With the increasing popularity of electric vehicles, distributed energy generation and storage facilities in smart grid systems, an efficient Demand-Side Management (DSM) is urgent for energy savings and peak loads reduction. Traditional DSM works focusing on optimizing the energy activities for a single household can not scale up to large-scale home energy management problems. Multi-agent Deep Reinforcement Learning (MA-DRL) shows a potential way to solve the problem of scalability, where modern homes interact together to reduce energy consumers consumption while striking a balance between energy cost and peak loads reduction. However, it is difficult to solve such an environment with the non-stationarity, and existing MA-DRL approaches cannot effectively give incentives for expected group behavior. In this paper, we propose a collective MA-DRL algorithm with continuous action space to provide fine-grained control on a large scale microgrid. To mitigate the non-stationarity of the microgrid environment, a novel predictive model is proposed to measure the collective market behavior. Besides, a collective behavior entropy is introduced to reduce the high peak loads incurred by the collective behaviors of all householders in the smart grid. Empirical results show that our approach significantly outperforms the state-of-the-art methods regarding power cost reduction and daily peak loads optimization

    Aqua­bis(triphenyl­phosphine-κP)copper(I) tetra­fluoridoborate

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    In the title compound, [Cu(C18H15P)2(H2O)]BF4, the CuI atom is coordinated by two P atoms from triphenyl­phosphine ligands and one water mol­ecule in a distorted trigonal geometry. In the BF4 − anion, three F atoms are disordered over two sites around the B—F bond, the site-occupancy ratio being 0.67 (6):0.33 (6). The Cu⋯F distance of 2.602 (5) Å between the Cu atom and the ordered F atom may suggest a weak but genuine inter­action. O—H⋯F and weak C—H⋯F hydrogen bonding is present in the crystal structure


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    Valve as an important part of the gas distribution mechanism, is an crucial part of the engine. When the engine works, the valve is subjected to high temperature, high impact, frictional wear and corrosion and other harsh working conditions, and the reliable and durable valve has an important impact on the safety and reliability of the engine. In this paper, a model of four-stroke marine diesel engine valve is used as the research object, and the intake valve set and exhaust valve set models are established respectively. Heat transfer simulation and failure analysis of inlet and exhaust valves of different structures and materials under different operating conditions were carried out using finite element analysis. The results show that the different valve structures and manufacturing materials have different effects on the reliability of the valves; Changing the valve structures and choosing different valve manufacturing materials have a greater impact on the heat transfer and deformation, thus affecting the overall reliability of the valves

    Complex I deficiency in m.3243A>G fibroblasts is alleviated by reducing NADH accumulation

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    Introduction: Mitochondrial disease is a spectrum of debilitating disorders caused by mutations in the mitochondrial DNA (mtDNA) or nuclear DNA that compromises the respiratory chain. Mitochondrial 3243A>G (m.3243 A>G) is the most common mutation showing great heterogeneity in phenotype. Previous studies have indicated that NADH: ubiquinone oxidoreductase (complex I) deficiency accompanied by a decreased nicotinamide adenine dinucleotide (NAD+)/reduced NAD+ (NADH) ratio may play a pivotal role in the pathogenesis of m.3243A>G mutation.Methods: To evaluate the potential effects of strategies targeting the imbalanced NAD+/NADH ratio in m.3243A>G mutation, we treated fibroblasts derived from patients with the m.3243 A>G mutation using nicotinamide riboside (NR) or mitochondria-targeted H2O-forming NADH oxidase (mitoLbNOX).Results: M.3243 A>G fibroblasts showed a significant reduction in complex I core subunit 6, complex I enzymatic activity, complex I-dependent oxygen consumption rate (OCR), and adenosine triphosphate (ATP) production compared to the controls. The NAD+/NADH ratio was also significantly reduced in m.3243 A>G fibroblasts, and, using fluorescence lifetime imaging microscopy, we also found that the NADH level was elevated in m.3243 A>G fibroblasts. After NR treatment, the NAD+/NADH ratio, complex I-dependent OCR, and ATP levels increased, whereas NADH levels remained unchanged. More excitingly, after treatment with mitoLbNOX, the NAD+/NADH ratio, complex I-independent OCR, and ATP levels increased more pronouncedly compared with the NR treatment group, accompanied by significantly reduced NADH levels.Discussion: The present study suggests that compared with repletion of NAD+ alone, the combination of this therapeutic modality with alleviation of NADH overload may amplify the treatment effect of restoring NAD+/NADH balance in m.3243A>G fibroblasts

    Diagnostic de la batterie et gestion de l’énergie pour applications embarquées

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    In order to cope with environmental problems and climate change, electric vehicles (EVs) gain the ever booming development in recent years. From the point of view of energy storage, because of their high energy / power density and their extended lifespan, it is essentially the lithium-ion battery (LIB) technology which is the most used power unit for EVs. Doubtlessly, the reliability of LIBs is of vital importance for the development of EVs. To this end, this thesis is dedicated to the algorithmic development of battery state and parameter estimation as well as incipient short-circuit diagnosis. The battery state and parameter estimation, which can also be termed as battery monitoring, is a critical part in the so-called health conscious energy management strategy for electric or hybrid electric vehicle. Premature aging can be avoided through the accurate battery state estimation such as state of charge (SOC) and state of health (SOH). Furthermore, as the thermal runaway (TR) can be ultimately attributed to short-circuit (SC) electrical abuse, therefore, effective battery incipient SC detection can give an early warning of TR. The main contribution of this thesis lies in the theoretical and methodological aspects in the domain of battery monitoring and incipient SC diagnosis.Les véhicules électriques (VEs) connaissent un développement en plein essor ces dernières années pour faire face aux problèmes environnementaux et aux dérèglements climatiques. Du point de vue du stockage de l'énergie, c'est essentiellement la technologie des batteries lithium-ion (LIB) qui est la plus utilisée pour d'alimentation des véhicules électriques compte tenu de leur haute densité d'énergie / puissance et de leur longue durée de vie. La fiabilité des LIBs est sans aucun doute d'une importance fondamentale pour le développement des VE. Dans cet objectif, les travaux de thèse s'inscrivent dans le développement des algorithmes dédiés à l'estimations des états de la batterie ainsi qu'au diagnostic de court-circuit naissant. L'estimation des états de la batterie, qui peut également être qualifiée de surveillance de la batterie, est un élément indispensable de la stratégie de gestion de l'énergie d'un véhicule électrique ou hybride. Par ailleurs, le vieillissement prématuré peut être évité grâce à la surveillance des états de batterie telles que l'état de charge (SOC) et l'état de santé (SOH). De plus, étant donné que l'emballement thermique (TR) peut être la conséquence d'un défaut de court-circuit (SC) électrique, de ce fait, une détection efficace de SC naissant de la batterie peut donc donner une alerte protectrice de TR. La principale contribution de cette thèse réside dans les aspects théoriques et méthodologiques dans le domaine de la surveillance de la batterie et du diagnostic SC naissant

    Research on the application of digital twin in coal mine power grid

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    Based on the basic concepts and connotations of digital twin, this paper analyzes the application advantages of digital twin technology in coal mine power grid. The operation management of the coal mine power grid is assisted by two means of synchronous entity operation status and digital simulation operation. The technology has the characteristics of data-driven, real-time update and synchronous feedback. The basic framework of the digital twin system of the coal mine power grid is proposed. The framework is composed of physical entity layer, digital twin model layer, user service management layer and data exchange layer. The operation mode of the digital twin system of the coal mine power grid is explored from two aspects of the physical entity and the digital twin model. This paper introduces the key technologies for establishing the digital twin system of the coal mine power grid. The technologies include digital twin model construction of coal mine power grid, intelligent data acquisition, intelligent communication based on 5G, digital twin intelligent database, and digital twin equipment intelligent management platform. The application scenarios of digital twin technology in the coal mine power grid are proposed. The scenarios include the condition evaluation of underground electrical equipment, fault location and protection of the coal mine power grid, intelligent monitoring of the coal mine power grid and intelligent inspection of underground lines. The digital twin technology is applied to the coal mine power grid to carry out dynamic simulation modeling on the state and operation of the coal mine power grid. On the one hand, the higher operation requirement of the current large-scale coal mine power grid relative to the ground power grid can be met. The safety of coal mine production can be guaranteed. On the other hand, the intelligent process of the coal mine power grid can be promoted. The efficient and reasonable utilization of data resources can be realized

    Graphene aerogel supported crystalline ZnO@amorphous Zn2GeO4 core-shell hierarchical structure for lithium storage

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    Fabricating a combined amorphous and crystalline hierarchical structure is a promising strategy to further improve the electrochemical performance of electrode materials, because it will provide additional opportunities for altering and manipulating the electrolyte adsorption and ion migratory dynamics in the lithium storage process. In this work, a crystalline-amorphous core-shell ZnO/Zn2GeO4/graphene aerogel with a three-dimensional structure has been successfully fabricated and shows enhanced stability and electrochemical performances