Abstract
Installation of new power generating units as backup black-start (BBS) sources is a vital issue to improve the acceleration of power network restoration, especially when a serious problem is occurred in main BS units (BSUs) and leads to fail in operation. Accordingly, this work address a new design for the optimal locating of the Gas-based Turbine (GT) as BBS to improve the smart grid performance during both restoration and normal conditions. To this end, there will be incompatible fitness functions to be minimized. Therefore, a multi-objective problem (MOP) including a mixed integer Nonlinear programming (MINLP), is formulated. The Pareto answers of the proposed MOP as the best solutions are modified and extracted by utilizing a meta-heuristic method, called crow search algorithm (CSA). A typical test system is employed for evaluation of the given plan. The extracted outcomes reveal that the network can desirably operate from this design not only to favorably enhance the capability of BSUs, but also to improve the power system performance in normal conditions. It also provides the better start-up program of non-black-start (NBS) power sources with the optimal paths during the restoration process.

Abstract
The deployment of the Internet of Things (IoT) in industry, called the Industrial IoT (IIoT), is supporting the introduction of very desirable improvements, such as increasing production flexibility, self-organization, and real-time and quick response to events. However, security and privacy challenges are still to be well addressed. The IIoT requires different properties to achieve secure and reliable systems and these requirements create extra challenges considering the limited processing and communication power available to IIoT field devices. In this research article, we present a key distribution protocol for IIoT that is computationally and communicationally lightweight (requires a single message exchange) and handles node addition and revocation, as well as fast rekeying. The scheme can also resist the consequences of node capture attacks (we assume that captured nodes can be detected by the gateway and previous works have shown this assumption to be acceptable in practice), server impersonation attacks and provides forward/backward secrecy. We show formally the correctness of our protocol and evaluate its energy consumption under realistic scenarios using a real embedded platform compared to previous state-of-theart key-exchange protocols, to show our protocol reliability for IIoT.

Abstract
Power transformer is the most important and expensive equipment used in the electric power industry. Fiber Bragg grating (FBG) sensors has stood out as a flexible and particularly suitable tool for power transformer monitoring being a passive and dielectric sensor element. In this work we evaluated the performance of FBG pressure sensors developed to monitor the static and dynamic pressure in high voltage winding transformers during events such as short-circuit and inrush current. Two types of sensors packaging materials were evaluated in laboratory: polyether ether ketone (PEEK) and transformerboard (TB). The sensors have been tested for high intensity and short duration impacts similar to those occurring in short circuits. In addition, we evaluated the time response of sensors using an interrogation system with a 5 kHz sweep in order to analyze the short circuit response time properly. The results pointed that FBG pressure sensors using PEEK and TB are suitable for transformer winding monitoring. The static sensitivity obtained to PEEK based sensors was 0.911 pm/N, in the range of 800 N to 1500 N. This sensitivity is 4.47 higher than TB based sensors sensitivity. Dynamical tests performance showed an excellent repeatability for both sensors, in agreement with static observation.

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This paper reports the development of a numerical module for the HiLight simulation platform dedicated to the propagation of light in nonlocal nonlinear optical media and the adaptions implemented for it to be used as a numerical test-bed to evaluate the impact of new extensions of the Theory of General Relativity in the dynamics of a N-body system. The phenomenology of light in nonlocal and nonlinear media is very rich and can be described by a multitude of effective models, with different levels of detail and approximations, which coincide with few or no differences with those found in many other fields of physics. In particular, nonlocal extensions of the Generalized Nonlinear Schrodinger equation (also known as the generalized Schrodinger-Newton system) constitute a wide class of physical models that can be found in both optics and in the studies of alternative theories for gravity. Therefore, numerical solvers developed for the former can be adapted to address the later. Indeed, this paper discusses the adaptation of a numerical solver of the generalized Schrodinger-Newton system based on GPGPU supercomputing, initially developed to investigate the properties of light in exotic nonlocal media, to tackle the dynamics of large distributions of matter whose interaction is governed by extensions of the Theory of General Relativity, namely those based on non-minimal coupling between curvature and matter. This paper analysis the structure of the resulting simulation module, its performance and validation tests.

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