Abstract
The operation of remote and isolated or islanded power systems is often very challenging because of their small system inertia. Moreover, economic and environmental pressure has led to an increasing renewable power penetration, particularly in wind generation and solar photovoltaics (PV). Simultaneously, significant technological progress has been made in terms of control capability of grid assets [generators, controllable loads such as electric vehicles (EVs), and energy storage systems], mostly exploiting the capabilities of power ?electronics. In this context, several advanced control solutions can be implemented, supporting and improving the robustness of the operation in terms of fast frequency and voltage control responses. In this article, the Portuguese islands are taken as a case study. Within the Madeira archipelago (Porto Santo and Madeira islands), two approaches were envisioned. For Porto Santo Island, the main goal is the sizing of a flywheel energy storage system (FESS) to avoid frequency stability problems. For Madeira Island, the objective relies on the exploitation of hydro resources through the quantification of the technical benefits resulting from variable speed hydro pumping stations that are able to provide primary frequency regulation services in the pump operation mode. In addition, this article also addresses the benefits of introducing EVs in Flores Island in the Azores Archipelago. Finally, to support the development of innovative technological solutions for this type of power system, a laboratory setup based on scaled test systems was also set up and is described. A set of applications was specifically developed for such autonomous power systems. The laboratorial infrastructure allowed the testing of ?solutions and prototypes for hardware and software modules related to those applications. © 2013 IEEE.

Abstract
The secure integration of renewable generation into modern power systems requires an appropriate assessment of the security of the system in real-time. The uncertainty associated with renewable power makes it impossible to tackle this problem via a brute-force approach, i.e. it is not possible to run detailed online static or dynamic simulations for all possible security problems and realizations of load and renewable power. Intelligent approaches for online security assessment with forecast uncertainty modeling are being sought to better handle contingency events. This paper reports the platform developed within the iTesla project for online static and dynamic security assessment. This innovative and open-source computational platform is composed of several modules such as detailed static and dynamic simulation, machine learning, forecast uncertainty representation and optimization tools to not only filter contingencies but also to provide the best control actions to avoid possible unsecure situations. Based on High Performance Computing (IIPC), the iTesla platform was tested in the French network for a specific security problem: overload of transmission circuits. The results obtained show that forecast uncertainty representation is of the utmost importance, since from apparently secure forecast network states, it is possible to obtain unsecure situations that need to be tackled in advance by the system operator.

Abstract
Using Voltage Source Converter (VSC) based High Voltage Direct Current (HVDC) technologies, in a Multi-terminal dc (MTDC) system, has been envisaged as an attractive solution for connecting the large offshore wind farms that have been planned to meet the EU renewable energy targets. The control and operation of VSC-HVDC technologies comprise a number of challenging tasks, aiming to assure an effective integration of MTDC systems in ac transmission systems. Stability studies play a key role within this framework. Among them, small signal stability analysis is required. Therefore, in this paper, modal analysis is performed for assessing small signal stability, in terms of the electromechanical modes of oscillation, considering the combined AC-MTDC system. Also, this paper evaluates the interest of installing classical Power Systems Stabilizer (PSS) in the onshore VSC stations for providing additional damping to the electromechanical modes of oscillation. Simultaneous tuning is performed for adjusting the parameters of these PSS based controllers. For this purpose, an optimization based approach exploiting Evolutionary Particle Swarm Optimization (EPSO) is proposed. Modal analysis and time domain simulations are performed to evaluate the effectiveness of the proposed solutions.

Abstract
Accounting for the increasing uncertainties related to forecast of renewables is becoming an essential requirement while assessing the security of future power system scenarios. The FP7 EU project iTesla tackles these needs and reaches several major objectives, including the development of a security platform architecture. In particular, the platform implements a complex stochastic dependence model to simulate a reasonable cloud of plausible "future" states - due to renewable forecast - around the expected state, and evaluates the security on relevant states sampling the cloud of uncertainty. The paper focuses on the proposed model of the uncertainty and its exploitation in power system security assessment process.

Abstract
This paper addresses the dynamic stability analysis of an islanded power system regarding the installation of a reversible hydro power plant for increasing renewable energy integration. Being a high-head facility, the hydro power plant consists of separated pumps and turbines (Pelton type). In order to properly support the identification of hydro pumps connection requirements and the technology to be used, different options were taken into consideration, namely: fixed speed pumps coupled to induction machines directly connected to the grid and adjustable speed pumps supplied by a drive system. Extensive numerical simulations of the power system's dynamic behaviour response allowed the evaluation of the hydro power plant's role for the purpose of grid stability conditions. These simulations showed that the high head hydro power installation provides a marginal contribution to system frequency regulation when explored in turbine operation mode, leading to a reversible power station with a single penstock. Moreover, due to the significant additional system load introduced by the hydro pumping units, the obtained results clearly indicate that supplementary regulation flexibility is required to attend the need of assuring the stable operation of the system in case of critical disturbances such as grid faults. The study case demonstrates that, although the foreseen operation of a reversible hydro power plant creates new security challenges to overcome in an autonomous power system, robust technical solutions can be identified without increasing, from the local system operator's perspective, the operation complexity of the power system.

Abstract
Accounting for the increasing uncertainties related to forecast of renewables is becoming an essential requirement while assessing the security of future power system scenarios. Project iTesla in the Seventh Framework Program (FP7) of the European Union (EU) tackles these needs and reaches several major objectives, including the development of a security platform architecture. In particular, the platform implements a stochastic dependence model to simulate a reasonable cloud of plausible 'future' states - due to renewable forecast - around the expected state, and evaluates the security on relevant states after sampling the cloud of uncertainty. The paper focuses on the proposed model for the uncertainty and its exploitation in power system security assessment process and it reports the relevant validation results. Copyright © 2019 Inderscience Enterprises Ltd.