Distributed generations (DGs) introduce significant uncertainties to restoration of active distribution networks, in addition to roughly estimated load demands. An adjustable robust restoration ...optimization model with a two-stage objective is proposed in this paper, involving the uncertain DG outputs and load demands. The first stage generates optimal strategies for recovery of outage power and the second stage seeks the worst-case fluctuation scenarios. The model is formulated as a mixed-integer linear programming problem and solved using the column-and-constraint generation method. The feasibility and reliability of the strategies obtained via this robust optimization model can be guaranteed for all cases in the predefined uncertainty sets with good performance. A technique known as the uncertainty budget is used to adjust the conservativeness of this model, providing a tradeoff between conservativeness and robustness. Numerical tests are carried out on the modified PG&E 69-bus system and a modified 246-bus system to compare the robust optimization model against a deterministic restoration model, which verifies the superiority of this proposed model.
This paper presents a fully distributed reactive power optimization algorithm that can obtain the global optimum solution of nonconvex problems for distribution networks (DNs) without requiring a ...central coordinator. Second-order conic relaxation is used to achieve exact convexification. A fully distributed second-order cone programming solver (D-SOCP) is formulated corresponding to the given division of areas based on the alternating direction method of multipliers (ADMM) algorithm, which is greatly simplified by exploiting the structure of active DNs. The problem is solved for each area with very little interchange of boundary information between neighboring areas. D-SOCP is extended by using a varying penalty parameter to improve convergence. A proof of its convergence is also given. The effectiveness of the method is demonstrated via numerical simulations using the IEEE 69-bus, 123-bus DNs, and a real 1066-bus distribution system.
To unlock the potential of flexible resources, a multi-time-scale economic scheduling strategy for the virtual power plant (VPP) to participate in the wholesale energy and reserve market considering ...large quantity of deferrable loads (DLs) aggregation and disaggregation is proposed in this paper. For the VPP multi-time-scale scheduling including day-ahead bidding and real-time operation, the following models are proposed, namely, DLs aggregation model based on clustering approach, economic scheduling model considering DLs aggregation, and DLs disaggregation model satisfying consumers' requirements, respectively. The proposed strategy can realize the efficient management of massive DLs to reduce the energy management complexity and increase the overall economics with high computation efficiency, which indicate its promising application in the VPP economic scheduling.
Fluctuations in wind power in geographically distributed areas are typically complementary, and therefore a coordinated multi-area dynamic economic dispatch may enable greater wind power penetration ...in interconnected power systems. Here we describe a decentralized approach based on a modified generalized Benders decomposition in which locally optimal cost function of each area is introduced. The technique exhibits rapid convergence and does not require parameter tuning. It is suitable for multi-area interconnected systems with a hierarchical control architecture. Comparative numerical simulations demonstrate that the performance of our method is favorable in terms of accuracy, convergence and computational efficiency. A case study on a real power system is also carried out to demonstrate the potential of this technique to increase wind power penetration.
Diffusion magnetic resonance imaging (MRI) is a standard imaging tool in clinical neurology, and is becoming increasingly important for neuroscience studies due to its ability to depict complex ...neuroanatomy (eg, white matter connectivity). Single‐shot echo‐planar imaging is currently the predominant formation method for diffusion MRI, but suffers from blurring, distortion, and low spatial resolution. A number of methods have been proposed to address these limitations and improve diffusion MRI acquisition. Here, the recent technical developments for image formation in diffusion MRI are reviewed. We discuss three areas of advance in diffusion MRI: improving image fidelity, accelerating acquisition, and increasing the signal‐to‐noise ratio.
Level of Evidence: 5
Technical Efficacy: Stage 1
J. MAGN. RESON. IMAGING 2017;46:646–662
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Large-scale wind farms are typically geographically separated from load centers and distributed in different control areas. Therefore, interregional energy dispatch is important for wind power ...generation via sharing spinning reserve capacity among interconnected systems. However, existing tie-line scheduling methods in China do not provide satisfactory performance in accommodating the recent large-scale integration of wind power. In this paper, we describe a coordination framework for tie-line scheduling and power dispatch to operate multi-area systems. Tie-line flows are updated hourly to hedge uncertainty in the near future, preserving the operational independence of areas. The coordinated tie-line scheduling problem is formulated using two-stage adaptive robust optimization to account for uncertainties in the available wind power and is solved using a column-and-constraint generation method in a coordinate-and-decentralize manner. Comparative simulations show that the method is effective in enabling further wind power penetration and can improve economic efficiency in multi-area systems. A case study using a large-scale power system demonstrates the benefits and scalability of the method in practice.
This paper proposes a new distance-based distributionally robust unit commitment (DB-DRUC) model via Kullback-Leibler (KL) divergence, considering volatile wind power generation. The objective ...function of the DB-DRUC model is to minimize the expected cost under the worst case wind distributions restricted in an ambiguity set. The ambiguity set is a family of distributions within a fixed distance from a nominal distribution. The distance between two distributions is measured by KL divergence. The DB-DRUC model is a "min-max-min" programming model; thus, it is intractable to solve. Applying reformulation methods and stochastic programming technologies, we reformulate this "min-max-min" DB-DRUC model into a one-level model, referred to as the reformulated DB-DRUC (RDB-DRUC) model. Using the generalized Benders decomposition, we then propose a two-level decomposition method and an iterative algorithm to address the RDB-DRUC model. The iterative algorithm for the RDB-DRUC model guarantees global convergence within finite iterations. Case studies are carried out to demonstrate the effectiveness, global optimality, and finite convergence of a proposed solution strategy.
This paper describes a fully distributed power dispatch method that can achieve fast frequency recovery and minimal generation cost for autonomous microgrids. The method is comprised of two stages. ...In the first stage, a subgradient-based consensus algorithm is used to recover frequency. The equal increment rate criteria is incorporated into this algorithm to achieve a minimal regulating cost, obtained by economically distributing power among distributed energy resources. Control signals updated with latest local measurements are executed in each iteration step to speed up the frequency recovery procedure. In the second stage, an average consensus algorithm is applied to resolve frequency oscillations caused by measurement errors. Numerical tests are described to demonstrate the validity of the proposed method and its applicability in the presence of communication time delay is discussed.
Gemcitabine (GEM)-based chemotherapy is commonly used to treat pancreatic cancer. However, acquired resistance to GEM remains a challenge in pancreatic cancer patients. Here we tested whether ...cancer-associated fibroblasts (CAFs) play vital roles in regulating drug resistance by transferring exosomal miRNA to cancer cells. CAFs were isolated from primary fibroblast of pancreatic cancer patients, and exosomes were collected and identified through transmission electron microscopy and western blotting analysis. The functions of CAFs-derived exosomal miRNA in regulating drug resistance were further investigated. We found that CAFs were innately resistant to GEM. The conditioned medium (CM) and the exosomes derived from CAFs contributed to GEM resistance, and GEM treatment further enhanced the effect of CAFs or CAFs-exosomes on pancreatic cancer cells proliferation. MiR-106b level was upregulated in CAFs and CAFs-exosomes following GEM treatment. MiR-106b was directly transferred from CAFs to pancreatic cancer cells through exosomes. Pretreatment of CAFs with miR-106b inhibitor suppressed miR-106b expression in CAFs-exosomes and resulted in a decreased resistance of cancer cells to GEM. MiR-106b promoted GEM resistance of cancer cells by directly targeting TP53INP1. Summarily, our data demonstrated that CAFs-derived exosomal miR-106b plays a vital role in causing GEM resistance of pancreatic cancer, thus offering a new target for sensitizing pancreatic cancer cells to GEM.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose
To develop a method for dynamic ∆B0$$ \Delta {B}_0 $$ mapping and distortion correction.
Methods
A blip‐rewound EPI trajectory was developed to acquire multiple 2D EPI images in a single ...readout with an interleaved order, which allows a short TE difference. A joint multi‐echo reconstruction was utilized to exploit the shared information between EPI images. The reconstructed images from each readout are combined to produce a final magnitude image. A ∆B0$$ \Delta {B}_0 $$ map is calculated from the phase of these images for distortion correction. The efficacy of the proposed method is assessed with phantom and in vivo experiments. The performance of the proposed method in the presence of subject motion is also investigated.
Results
Compared to conventional multi‐echo EPI, the proposed method allows dynamic ∆B0$$ \Delta {B}_0 $$ mapping at matched resolution with a much shorter TR. Phantom and in vivo results show that the proposed method can provide a comparable magnitude image as conventional single‐shot EPI. The ∆B0$$ \Delta {B}_0 $$ maps calculated from the proposed method are consistent with conventional multi‐echo EPI in the phantom experiment. For in vivo experiments, the proposed method provides a more accurate estimation of ∆B0$$ \Delta {B}_0 $$ than conventional multi‐echo EPI, which is prone to phase wrapping problems due to the long TE difference. In‐vivo scan with subject motion shows the proposed dynamic field mapping method can improve the temporal stability of EPI time series compared to gradient echo (GRE) based static field mapping.
Conclusion
The proposed method allows accurate dynamic ∆B0$$ \Delta {B}_0 $$ mapping for robust distortion correction without compromising spatial or temporal resolution.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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