System modeling and stability analysis is one of the most important issues of inverter-dominated microgrids. It is useful to determine the system stability and optimize the control parameters. The complete small signal models for the inverterdominated microgrids have been developed which are very accurate and could be found in literature. However, the modeling procedure will become very complex when the number of inverters in microgrid is large. One possible solution is to use the reduced-order small signal models for the inverterdominated microgrids. Unfortunately, the reduced-order small signal models fail to predict the system instabilities. In order to solve the problem, a new modeling approach for inverterdominated microgrids by using dynamic phasors is presented in this paper. Our findings indicate that the proposed dynamic phasor model is able to predict accurately the stability margins of the system, while the conventional reduced-order small signal model fails. In addition, the virtual ω-E frame power control method, which deals with the power coupling caused by the line impedance X/R characteristic, has also been chosen as an application example of the proposed modeling technique.Index Terms-microgrid, droop control, inverter, small signal mode, dynamic phasor, stability analysis, I.

Abstract:In recent years the unconstrained binary quadratic program (UBQP) has grown in importance in the field of combinatorial optimization due to its application potential and its computational challenge. Research on UBQP has generated a wide range of solution techniques for this basic model that encompasses a rich collection of problem types. In this paper we survey the literature on this important model, providing an overview of the applications and solution methods.

This study aimed to determine whether aging negatively affects MSC replication and osteogenesis and whether these features could be altered by exposure to an extracellular matrix (ECM) generated by marrow cells from young or old mice. A cell-free ECM was prepared from cultured femoral marrow cells from either 3- or 18-mo-old C57BL/6 mice (young-ECM or old-ECM, respectively). The replication and osteogenesis of young or old MSCs maintained on young-ECM vs. old-ECM as well as plastic were examined in vitro and in vivo. We found that the frequency of MSCs in marrow from old mice, measured by colony-forming cells, was only marginally lower than that of young mice. In contrast, defects in the self-renewal and bone formation capacity of old MSCs were remarkable. These defects were corrected by provision of a young-ECM but not old-ECM. In parallel cultures maintained on a young-ECM, the intracellular levels of reactive oxygen species from both old and young mice were reduced 30-50% compared to those maintained on old-ECM or plastic. We concluded that aging negatively affects the formation of an ECM that normally preserves MSC function, and aged MSCs can be rejuvenated by culture on a young-ECM.

Given an undirected graph G = (V, E) with a set V of vertices and a set E of edges, the graph coloring problem consists of partitioning all vertices into k independent sets and the number of used colors k is minimized. This paper presents a memetic algorithm (denoted by MACOL) for solving the problem of graph coloring. The proposed MACOL algorithm integrates several distinguished features such as an adaptive multi-parent crossover (AMPaX) operator and a distance-and-quality based replacement criterion for pool updating. The proposed algorithm is evaluated on the DIMACS challenge benchmarks and computational results show that the proposed MACOL algorithm achieves highly competitive results, compared with 11 state-of-the-art algorithms. The influence of some ingredients of MACOL on its performance is also analyzed.

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This paper presents an Adaptive Tabu Search algorithm (denoted by ATS) for solving the problem of curriculum-based course timetabling. The proposed algorithm follows a general framework composed of three phases: initialization, intensification and diversification. The initialization phase is primarily aimed to construct a feasible initial timetable using a fast greedy heuristic. When a feasible initial assignment is reached, an adaptively combined intensification (Tabu Search) and diversification (Perturbation Operator from Iterated Local Search) phase is used in order to reduce the number of soft constraint violations without breaking hard constraints any more. The proposed ATS algorithm integrated several distinguished features including an original double Kempe chains neighborhood structure, a penalty-guided perturbation approach and a mechanism for dynamically integrating tabu search with perturbation. Computational results indicate that better solutions can be found compared with Tabu Search and Iterated Local Search alone, as well as another reference algorithm. This paper also shows an analysis to explain which are the essential ingredients of the proposed ATS algorithm.

This paper presents a hybrid metaheuristic approach (HMA) for solving the Unconstrained Binary Quadratic Programming (UBQP) problem. By incorporating a tabu search procedure into the framework of evolutionary algorithms, the proposed approach exhibits several distinguishing features, including a diversification-based combination operator and a distance-and-quality based replacement criterion for pool updating. The proposed algorithm is able to easily obtain the best-known solutions for 31 large random instances up to 7000 variables (which no previous algorithm has done) and find new best solutions for 3 of 9 instances derived from the set partitioning problem, demonstrating the efficacy of our proposed algorithm in terms of both solution quality and computational efficiency. Furthermore, some key elements and properties of the HMA algorithm are also analyzed.