This paper studies the real-time dynamic energy management (DEM) of multi microgrids (MMGs) considering active and reactive power flow constraints, voltage battery operational characters, uncertainties in renewable generation load. A stochastic spatiotemporal decomposition decision-making framework is proposed based on approximate programming (ADP) to make decentralized decisions both spatial temporal dimensions. The tie-line state charge (SOC) are coordinated real time deal with upcoming...

In this paper, we propose a parallel dual dynamic programming (PDDP)-based decentralized algorithm for the multi-area optimal power flow (MAOPF), which can preserve information privacy and operational independence of each area. The MAOPF problem is decomposed into series subproblems individual areas by (DDP) algorithm, Benders cut-based value functions are used to reflect impacts one area's decisions subsequent areas. solution be obtained in fashion, requiring only limited amount exchange...

Bridge-type micro-displacement mechanism based on flexible hinge is a classical displacement magnifying mechanism. A branched chain model was established to analyze the characteristics of according its symmetrical structure, thus formulas for calculating output and amplification ratio were derived. Finite element simulation carried by software ANSYS11.0, then compared with theoretical model. Finally, an experiment sample piece designed processed verify The results showed that: bridge-type...

The energy management (EM) of active distribution network (ADN) under uncertainties is a stochastic, nonconvex and nonlinear problem, which cannot be solved by traditional algorithms in acceptable time. In this paper, we decouple computationally intractable problem into series subproblems are easier to handle, then solve them successively according an improved approximate dynamic programming (IADP) algorithm. Different from the existing (ADP) algorithms, need update value functions...

Intervertebral discs (IVDs), as small joints lying between adjacent vertebrae, have played an important role in pressure buffering and tissue protection. The fully-automatic localization segmentation of IVDs been discussed the literature for many years since they are crucial to spine disease diagnosis provide quantitative parameters treatment. Traditionally hand-crafted features derived based on image intensities shape priors localize segment IVDs. With advance deep learning, various neural...

In this paper, we propose a bi-level, real-time economic dispatch method of virtual power plant (VPP), including various distributed energy resources (DERs). Considering the different interests VPPs and system operator, is described as bi-level programming problem, where operator dispatches based on price incentive mechanism upper level, provide response according to optimal control their DERs lower level. uncertainties loads, decision risks level are further dealt with by fuzzy chance...

This study focuses on the real‐time operation of a microgrid (MG). A novel approximate dynamic programming based spatiotemporal decomposition approach is developed to incorporate efficient management distributed energy storage systems into MG while considering uncertainties in renewable generation. The original problem decomposed single‐period and single‐unit sub‐problems, value functions are used describe interaction among sub‐problems. two‐stage procedure further designed for decisions...

The compliant double parallel four-bar mechanism is a classical guiding mechanism. Two mathematic models of were built based on pseudo-rigid-body model and elastic beam theory. theory was used to analysis the effect axial deformation displacement moving plate at large displacement. Effect geometric parameters accurate two discussed. Results showed that proportional force. Meanwhile, its width/thickness ratio rectangular cross section have significant plate. increases rapidly with decrease...

Hysteresis and nonlinearity of piezo actuator are the major factors affecting motion accuracy in controlling a micro system. The prediction classical Preisach model could be improved only by mass experiments for measuring hysteresis. A based on BP neural networks was proposed to improve accuracy. stoke has relation current exciting voltage historical extrema according dasiawiping-outpsila property model. established. input is voltage, at nearest turning point its corresponding stroke output...

Phase mask optimization is one of the critical steps in designing a wavefront coding system to extend depth field (DoF). As classical phase mask, cubic was taken as an example. An improved particle swarm (PSO) algorithm applied calculate parameters by introducing modulation transfer function criterion and threshold constraint. The quality subsequent image restoration guaranteed on premise extended DoF. Finally, PSO proved be faster, more efficient, accurate compared simulated annealing...

This study presents a fully decentralised robust optimisation (RO) approach for multi‐area economic dispatch (MA‐ED) in the presence of wind power uncertainty. Unlike traditional algorithms, authors formulate this MA‐ED problem as dynamic programming problem, and decompose centralised into series sub‐problems based on approximate algorithm. The value functions are proposed each area to iteratively estimate impacts its dispatches other areas which make decisions subsequently. algorithm does...

Shearer height adjusting is a key technology for coalmine unmanned working face. On the basis of establishing face mathematical models, this paper determined related parameters influencing adjusting, then analyzed traditional memory cutting strategy and pointed out its shortcomings. Aiming at changing technical limitations currently, proposed new based on GRNN(General Regression Neural Network). According to data acquired from face, we use MATLAB analyze algorithm, results shows GRNN network...

We propose EMS®, a cloud-enabled massive computational experiment management system supporting high-throughput robotics research. Compared to existing systems, EMS® features sky-based pipeline orchestrator which allows us exploit heterogeneous computing environments painlessly (e.g., on-premise clusters, public clouds, edge devices) optimally deploy large-scale jobs with more than millions of hours) in an integrated fashion. Cornerstoned on this orchestrator, paper introduces three...

The decarbonization of power and energy systems faces a bottleneck: enormous number user-side resources cannot be properly managed operated by centralized system operators, who used to send dispatch instructions only few large plants. To break through, we need not new devices algorithms, but structural reforms our systems. Taking the Internet as paradigm, practicable design Energy is presented based on principle standardization. A combination stylized data delivery, referred Block Exchange...

Managing and unlocking the flexibility hidden in electric vehicles (EVs) has emerged as a critical yet challenging task towards low-carbon power energy systems. This paper focuses on online bidding dispatch strategies for an EV aggregator (EVA) joint energy-regulation market, considering EVs' contributions compensations. A method quantifying tradable commodity is proposed, allowing EVA to set prices based bid-in supply curves. An model market incorporate procurement formulated. The...

This study proposes a decentralised methodology to deal with the optimal energy flow (OEF) problem of electricity–natural gas system (EGS). The OEF EGS is formulated as multi‐stage dynamic programming (DP) process, and approximate DP algorithm used decompose it into subproblems. independent decision each subproblem can be made by solving Bellman's equation, requiring just moderate interchange information among different Such that privacy dispatch independency subsystems (including...

The development of microgrids has put forward new requirements for the transmission cost allocation method. First, this paper develops framework allocating costs in grid with connected. Second, we consider two typical operating states and propose relevant indicators to describe microgrids, which effectively reflect different types power generation. Third, formulate a usage-based Finally, numerical experiments are used verify effectiveness approach.

This paper proposes a renewable energy prediction method adapted to the climate characteristics of plateau mountains and oceans in southern region. The proposed approach contains four parts: data clearing, time-period clustering, modeling for forecasts, feature-prediction accuracy correlation matrix calculation. Therein, forecast algorithm is improved mainly from two aspects: 1) Time-period clustering implemented before training models. Different models are trained with clustered sets...