Abstract
This paper presents a mathematical linear expansion model for the probabilistic Multistage Phasor Measurement Unit (PMU) Placement (MPP) in which zero-injection buses (ZIBs), as well as communication channel limitations, are taken into consideration. From the linearization perspective, presenting a model formulizing the probabilistic concept of observability while modelling the ZIB is of great significance, and has been done in this paper for the first time. More importantly, the proposed probabilistic MPP utilizes a technique disregarding the prevalent subsidiary optimizations for each planning stage. Although this technique, in turn, increases the problem complexity with manifold variables, it guarantees the global optimal solution in a wider and thorough search space; while in the prevalent methods, some parts of the search space might be missed. Furthermore, the proposed model indicates more realistic aspects of the MPP where system operators are allowed to follow their intention about the importance of buses such as strategic ones based on monitoring the priority principles. In addition, the model is capable of considering the network topology changes due to long-term expansions over the planning horizon. Finally, in order to demonstrate the effectiveness of the proposed formulation, the model is conducted on the IEEE 57-bus standard test system and the large scale 2383-bus Polish power system. © 2018 by the authors.

Abstract
The issue of environmental emissions has forced the power systems to use cleaner energy sources such as renewable and hydroelectric technologies. However, during recent decades due to the limitations on the available water in many regions, the optimal water reservoir usage has been highlighted. In this regard, this paper proposes a multi-objective model for short-term hydrothermal scheduling problem in the presence of the pumped-storage technology. It is noted that the framework well models the cascaded configuration of hydro reservoirs. Besides, in order to more accurately model the mentioned problem, a Mixed-Integer Non-Linear Programming (MINLP) optimization framework is presented. In this respect, the valve-loading effects occurred in thermal power generation technologies have been taken into account which turns the existing convex optimization problem into a non-convex one. In order to solve the mentioned problem, the Normal Boundary Intersection (NBI) method has been used while the VIKOR decision maker is employed to choose the most compromise solution amongst the Pareto optimal solutions obtained by NBI method. Finally, the efficiency of the proposed model has been verified through implementing four case studies and comparing the obtained results with those obtained by different methods. © 2017 Elsevier Ltd

Abstract
This paper presents recent research conducted at the JRC Smart Grid Interoperability Lab and analyses key parameters that should be taken into consideration for the development of interoperable and sustainable electricity systems. Increasing energy efficiency aims at reducing the overall energy consumption and consequently lower the stress on the environment by using less energy. The first research activity illustrated is on the use of Advanced Metering Infrastructure as a gateway to improve Demand Response/Demand Side Management. The second one focuses on the use of photovoltaic in a low voltage distribution network and studies the effect of penetration in voltage unbalances. The last one addresses the power quality performance of electric vehicle chargers under low temperature conditions and provides hints for improvements. The paper underlines several factors that could affect the efficiency of systems towards making improvements that increase the stability of the relevant operations.

Abstract
Exposing electric vehicles (EV) to extreme temperatures limits its performance and charging. For the foreseen adoption of EVs, it is not only important to study the technology behind it, but also the environment it will be inserted into. In Europe, temperatures ranging from -30°C to +40°C are frequently observed and the impacts on batteries are well-known. However, the impact on the grid due to the performance of fast-chargers, under such conditions, also requires analysis, as it impacts both on the infrastructure's dimensioning and design. In this study, six different fast-chargers were analysed while charging a full battery EV, under four temperature levels (-25 °C, -15 °C, +20 °C, and +40 °C). The current total harmonic distortion, power factor, standby power, and unbalance were registered. Results show that the current total harmonic distortion (THDI) tended to increase at lower temperatures. The standby consumption showed no trend, with results ranging from 210 VA to 1650 VA. Three out of six chargers lost interoperability at -25 °C. Such non-linear loads, present high harmonic distortion, and, hence, low power factor. The temperature at which the vehicle's battery charges is crucial to the current it withdraws, thereby, influencing the charger's performance.

Abstract
Multi-type fast charging stations are being deployed over Europe as electric vehicle adoption becomes more popular. The growth of an electrical charging infrastructure in different countries poses different challenges related to its installation. One of these challenges is related to weather conditions that are extremely heterogeneous due to different latitudes, in which fast charging stations are located and whose impact on the charging performance is often neglected or unknown. The present study focused on the evaluation of the electric vehicle (EV) charging process with fast charging devices (up to 50 kW) at ambient (25°C) and at extreme temperatures (-25°C, -15°C, +40°C). A sample of seven fast chargers and two electric vehicles (CCS (combined charging system) and CHAdeMO (CHArge de Move)) available on the commercial market was considered in the study. Three phase voltages and currents at the wall socket, where the charger was connected, as well as voltage and current at the plug connection between the charger and vehicle have been recorded. According to SAE (Society of Automotive Engineers) J2894/1, the power conversion efficiency during the charging process has been calculated as the ratio between the instantaneous DC power delivered to the vehicle and the instantaneous AC power supplied from the grid in order to test the performance of the charger. The inverse of the efficiency of the charging process, i.e., a kind of energy return ratio (ERR), has been calculated as the ratio between the AC energy supplied by the grid to the electric vehicle supply equipment (EVSE) and the energy delivered to the vehicle's battery. The evaluation has shown a varied scenario, confirming the efficiency values declared by the manufacturers at ambient temperature and reporting lower energy efficiencies at extreme temperatures, due to lower requested and, thus, delivered power levels. The lowest and highest power conversion efficiencies of 39% and 93% were observed at -25°C and ambient temperature (+25°C), respectively.

Abstract
As photovoltaic (PV) penetration increases in low-voltage distribution networks, voltage variation may become a problem. This is particularly important in residential single-phase systems, due to voltage unbalances created by the inflow of points in the network. The existing literature frequently refers to three-phase systems focusing on losses and voltage variations. Many studies tend to use case studies whose conclusions are difficult to replicate and generalise. As levels of residential PV rise, single-phase PV power injection levels, before voltage unbalances reach standard limits, become important to be investigated. In this study, an urban European reference network is considered, and using a real-time digital simulator, different levels of PV penetration are simulated. PV systems are connected to the same phase (unbalanced case), and are also evenly phase-distributed (balanced case). Considering a 2-3% unbalance limit, approximately 3.5-4.6 kW could be injected in every bus in an unbalanced scenario. With a balanced PV distribution, the power injected could reach 10-13 kW per bus. Buses closer to the power transformer allow higher power connections, due to cable distances and inferior voltage drops. Feeder length, loads considered during simulation, and cable shunt capacitance reactance influence the results the most.