Abstract
The Gemini Infrared Multi-Object Spectrograph (GIRMOS) instrument proposes to carry out Multi-Object Adaptive Optics (MOAO) correction on the residual of the Gemini Mutlti-Conjugate AO System (GeMS)corrected wavefronts in either Ground Layer (GLAO) or Multi-Conjugate (MCAO) mode. This work has been undertaken to determine the extent to which the ensquared energy delivered to a GIRMOS IFU can be improved over typical GeMS operation by adding MOAO correction. One of the key advantages of using the MOAO-fed IFUs is the improvement in performance toward the edge of the field, making the full 2’ field of GeMS more available for simultaneous observing. Using the Object Oriented Matlab Adaptive Optics (OOMAO) library1 to simulate the full system under a wide range of configurations and error conditions, we have established the baseline error budget and used the simulation to enable ongoing investigation into the particular control schemes and system errors that arise from using GeMS LGS and NGS WFSs to divide atmospheric correction between up to 3 DMs at different altitude conjugations and optimization directions.

Abstract
Power and energy systems lack decision-support systems that enable studying big problems as a whole. The interoperability between multi-agent systems that address specific parts of the global problem is essential. Ontologies ease interoperability between heterogeneous systems providing semantic meaning to the information exchanged between the various parties. This paper presents the practical application of a society of multi agent systems, which uses ontologies to enable the interoperability between different types of agent-based simulators, directed to the simulation and operation of electricity markets, smart grids and residential energy management. Real data-based demonstration shows the proposed approach advantages in enabling comprehensive, autonomous and intelligent power system simulation studies.

Abstract
Index Modulation (IM) is a technique that activate k out of n subcarriers of an OFDM symbol to transmit p(1) = right perpendicularlog(2) (n k)left perpendicular bits in symbol's indexes. Since both the symbol's spectrum width and transmission air-time duration remain the same, OFDM-IM outperforms OFDM's Spectral Efficiency (SE) for larger values of (n k). However, OFDM-IM requires an extra step called Index Selector (IxS) which takes T-alpha time units to map a given p(1)-bit input to its corresponding pattern of active subcarriers. This extra overhead virtually enlarges the symbol duration, which is not captured by the classic SE definition. To fulfill this gap, in this work we present the Spectro-Computational Efficiency (SCE) metric. SCE parameterizes either the absolute runtime of T-alpha on a reference hardware or its computational complexity T-alpha(n; k) as function of n and k. Based on SCE, we present theoretical case studies to identify the asymptotic bounds for T-alpha(n, k) across different choices of k. if T-alpha(n, n=2) is at most linear on n the resulting overhead is asymptotically negligible and IxS can handle an arbitrarily large OFDM symbol. Otherwise, OFDM-IM's SCE tends to zero regardless of the hardware processor speed. Also, we situate the inflection-point values for OFDM-IM's SCE between (6 3) and (14 7) in some practical case studies.

Abstract

Abstract
In power system static security analysis, it often requires to calculate continuous power flow from a certain load condition to a bifurcation point along a given direction, which is referred to as the maximum loadability problem. This paper proposes a convex optimization method for maximum loadability problem over meshed power grids based on the semidefinite relaxation approach. Because the objective is to maximize the load increasing distance, convex relaxation model is generally inexact, unlike the situation in cost-minimum optimal power flow problem. Inspired by the rank penalty method, this paper proposes an iterative procedure to retrieve the maximum loadability. The convex quadratic term representing the penalty on the rank of matrix variable is updated in each iteration based on the latest solution. In order to expedite convergence, generator reactive power is also included in the objective function, which has been reported in literature. Numeric tests on some small-scale systems validate its effectiveness. Any sparsity-exploration and acceleration techniques for semidefinite programming can improve the efficiency of the proposed approach. © 2019 IEEE.

Abstract
The charging behavior of electric vehicles (EVs) is a key concern to system operators and retailers given a massive adoption these resources. System operators and retailers may profit from the handling of EVs as flexible loads. The former has interest to move their charging into periods without congestion and voltage problems. Similarly, the latter wants them to only charge at periods when energy is cheaper. This paper addresses the problem by modelling a real-time tariff to encourage flexible EVs charging behavior. More precisely, different tariffs are modelled based on the relation between wind power generation, load consumption and spot price, while assuming Denmark as showcase. The EVs behavior entails three different patterns and a socioeconomic term that defines the anxiety of EVs users' to be responsive to the tariffs. An important conclusion is that a proper real-time tariff design can reduce the energy costs for the retailer and EVs.