This paper presents a Reinforcement Learning (RL) based energy market for a prosumer dominated microgrid. The proposed market model facilitates a real-time and demand-dependent dynamic pricing environment, which reduc...
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ISBN:
(纸本)9781728161273
This paper presents a Reinforcement Learning (RL) based energy market for a prosumer dominated microgrid. The proposed market model facilitates a real-time and demand-dependent dynamic pricing environment, which reduces grid costs and improves the economic benefits for prosumers. Furthermore, this market model enables the grid operator to leverage prosumers' storage capacity as a dispatchable asset for grid support applications. Simulation results based on the Deep Q-Network (DQN) framework demonstrate significant improvements of the 24-hour accumulative profit for both prosumers and the grid operator, as well as major reductions in grid reserve power utilization.
Mobile edge computing (MEC) can provide users with high-quality video services by placing computing and storage capacity close to the user. Transferring large size video files usually consumes more time and energy, an...
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Mobile edge computing (MEC) can provide users with high-quality video services by placing computing and storage capacity close to the user. Transferring large size video files usually consumes more time and energy, and the emergence of edge caching can effectively solve this problem. Current caching schemes generally consider the impact of only one or two factors among attributes such as ratings and reviews, without considering the impact of multiple factors together on the recommender system. In this paper, we propose a video caching strategy based on multi-factor recommendation (VCSMFR) to solve the above problem. First, the video file ratings and corresponding rankings are obtained by a recommendation algorithm that fuses multi-factor data (e.g., reviews, directors, and actors). Then, an optimized particle swarm algorithm is used to make caching decisions for files stored on the edge MEC server to solve the problem that traditional particle swarm algorithms are prone to local convergence. Simulation results show that the recommendation algorithm proposed in this paper can analyze user and video information more carefully by fusing multiple factors, and improve the cache hit rate by 11% over the traditional caching scheme. In addition, the greedy algorithm is introduced into the optimized particle swarm algorithm, which improves the local search ability as well as the convergence of the algorithm and achieves faster caching decisions.
The work implements the common DC bus electric vehicles (EVs) charging infrastructure based on hybrid renewable energy sources such as solar photovoltaic (PV) and fuel cell. The requisite to incorporate distributed en...
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ISBN:
(纸本)9781665447539
The work implements the common DC bus electric vehicles (EVs) charging infrastructure based on hybrid renewable energy sources such as solar photovoltaic (PV) and fuel cell. The requisite to incorporate distributed energy resources (DERs) is attributed to the escalating concern for decarbonisation with improved power quality requirements. Furthermore, the bidirectional flow of power enables the transition between modes of grid presence/absence. The utilization of an adaptive comb filter is achieved for satisfactory operation during mode with synchronization ability along with power transfer proficiency and improved power quality requirements. The utilization of common DC bus charging mechanism for EVs, facilitates fast charging capability at higher voltage levels. Thus, for validation and corroboration of the system behavior, its performance is authenticated during weak grid conditions in conjunction with grid connected/islanded modes of operation.
This paper proposes a preliminary microfluidic computing system design for Spiking Neural P systems designed to solve the computational hard problem of Boolean satisfiability SAT by implementing the model studied in o...
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This paper proposes a preliminary microfluidic computing system design for Spiking Neural P systems designed to solve the computational hard problem of Boolean satisfiability SAT by implementing the model studied in our previous work. We have also developed a simulation model for the proposed system and have been doing in silico experiments. An AC voltage applied to facilitated electrodes generates Dielectrophoretic force (DEP) and non-uniform electric field in the microfluidic channels. This DEP serves as the main functioning tool of the proposed biochip to control computation steps.
High Performance computing (HPC) and, in general, parallel and distributedcomputing (PDC) is ubiquitous. Every computing device, from a smartphone to a supercomputer, relies on parallel processing. Compute clusters o...
High Performance computing (HPC) and, in general, parallel and distributedcomputing (PDC) is ubiquitous. Every computing device, from a smartphone to a supercomputer, relies on parallel processing. Compute clusters of multicore and manycore processors (CPUs and GPUs) are routinely used in many subdomains of computer science, such as data science, parallel machine learning and high performance computing. Therefore, it is important for every computing professional (and especially every programmer) to understand how parallelism and distributedcomputing affect problem solving. It is essential for educators to impart a range of PDC and HPC skills and knowledge at multiple levels within the curriculum of Computer Science (CS), Computer Engineering (CE), and related disciplines such as computational data science. Software industry and research laboratories require people with these skills, more so now. Therefore, they now engage in extensive on-the-job training. Additionally, rapid changes in hardware platforms, languages, and programming environments increasingly challenge educators to decide what to teach and how to teach it, in order to prepare students for careers that are increasingly likely to involve PDC and HPC. EduHiPC aims to provide a forum that brings together academia, industry, government, and non-profit organizations – especially from India, its vicinity, and Asia – for exploring and exchanging experiences and ideas about the inclusion of high-performance, parallel, and distributedcomputing into undergraduate and graduate curriculum of Computer Science, Computer Engineering, Computational Science, Computational Engineering, and computational courses for STEM and business and other non-STEM disciplines.
In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically ind...
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In recent years, the GAA NS Si MOSFET has been explored as a leading technology. However, the intrinsic parameters of GAA NS Si MOSFETs are affected to varying degrees by various fluctuation sources, Statistically independent and identically distributed $(iid)$ assumptions on the aforementioned random variables overestimate the variability of high-frequency characteristics, compared with considering all fluctuation factors simultaneously. Notably, the random nanosized metal grains dominates the variations of voltage gain, cut-off frequency, and 3dB frequency because the random work functions strongly alter the channel surface potential.
In order to solve the problem of impersonation of the electronic identity of power maintenance personnel, this paper proposes an trusted identity authentication model based on Blockchain. This model uses plug-in authe...
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Transactional memory is designed for developing parallel programs and improving the efficiency of parallel pro-grams. PSTM (python software transactional memory) mainly supports multi-core parallel programs based on t...
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ISBN:
(数字)9781665488105
ISBN:
(纸本)9781665488112
Transactional memory is designed for developing parallel programs and improving the efficiency of parallel pro-grams. PSTM (python software transactional memory) mainly supports multi-core parallel programs based on the python language. In order to better adapt to the developing requirements of distributed concurrent programs and enhance the safety of the system, DPSTM (distributed python software transactional memory) was developed. Compared with PSTM, DPSTM has the advantages of higher operating efficiency and stronger fault tolerance. In this paper, we apply CSP (Communicating Sequential Processes) to formally analyze the components of DPSTM v2 architecture, the data exchange process between components, and two different transaction processing modes. We use the model checker PAT (Process Analysis Toolkit) to model the DPSTM v2 architecture and verify eight properties, including deadlock freedom, ACI (atomicity, isolation, and consistency), sequential consistency, data server availability, read tolerance, and crash tolerance. The verification results show that the DPSTM v2 archi-tecture can guarantee all of the above properties. In particular, the normal operation of the system can be maintained when some of the data servers are crashed, ensuring the safety of a distributed system.
Nowadays the advantages of heterogeneous acceleration technology are becoming more and more obvious. Edge computing center began to accelerate its distributed trading business based on FPGA technology, especially in t...
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The proceedings contain 12 papers. The topics discussed include: performance evaluation of distributed networks for Internet of things;connectivity pattern analysis for virtual simulation design, based on high-perform...
The proceedings contain 12 papers. The topics discussed include: performance evaluation of distributed networks for Internet of things;connectivity pattern analysis for virtual simulation design, based on high-performance game analysis;computational study for improvement of aerodynamic performance of airfoil by changing various aerodynamic properties;an experimental design approach to IoT enabled smart parallel irrigation system using embedded microcontrollers;to develop, test and record a 3 lead EMG electrode and flex sensor on a 3D prosthetic limb with different gait patterns using Arduino microcontroller;and low-cost system for the management of hospital services, applied to hospitalized patients through the use of IoT technology.
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