Overvoltages in low voltage (LV) feeders with high penetration of photovoltaics (PV) are usually prevented by limiting the feeder's PV capacity to very conservative values, even if the critical periods rarely occur. This paper discusses the use of droop-based active power curtailment techniques for overvoltage prevention in radial LV feeders as a means for increasing the installed PV capacity and energy yield. Two schemes are proposed and tested in a typical 240-V/75-kVA Canadian suburban distribution feeder with 12 houses with roof-top PV systems. In the first scheme, all PV inverters have the same droop coefficients. In the second, the droop coefficients are different so as to share the total active power curtailed among all PV inverters/houses. Simulation results demonstrate the effectiveness of the proposed schemes and that the option of sharing the power curtailment among all customers comes at the cost of an overall higher amount of power curtailed.

This document is a summary of a report prepared by the IEEE PES Task Force (TF) on Microgrid Stability Definitions, Analysis, and Modeling \cite{task}, which defines concepts and identifies relevant issues related to stability in microgrids. In this paper, definitions and classification of microgrid stability are presented and discussed, considering pertinent microgrid features such as voltage-frequency dependency, unbalancing, low inertia, and generation intermittency. A few examples are also presented, highlighting some of the stability classes defined in the paper. Further examples, along with discussions on microgrid components modeling and stability analysis tools can be found in the TF report.

The modern power system is progressing from a synchronous machine-based system towards an inverter-dominated system, with large-scale penetration of renewable energy sources (RESs) like wind and photovoltaics. RES units today represent a major share of the generation, and the traditional approach of integrating them as grid following units can lead to frequency instability. Many researchers have pointed towards using inverters with virtual inertia control algorithms so that they appear as synchronous generators to the grid, maintaining and enhancing system stability. This paper presents a literature review of the current state-of-the-art of virtual inertia implementation techniques, and explores potential research directions and challenges. The major virtual inertia topologies are compared and classified. Through literature review and simulations of some selected topologies it has been shown that similar inertial response can be achieved by relating the parameters of these topologies through time constants and inertia constants, although the exact frequency dynamics may vary slightly. The suitability of a topology depends on system control architecture and desired level of detail in replication of the dynamics of synchronous generators. A discussion on the challenges and research directions points out several research needs, especially for systems level integration of virtual inertia systems.

The objective of this paper is to provide an assessment on voltage profiles in residential neighborhoods in the presence of photovoltaic (PV) systems. The network was modeled in PSCAD using common feeder characteristics that Canadian system planners use in suburban residential regions. A simulation study was performed to investigate potential voltage rise issues in the network up to 11.25% total PV penetration in the feeder and LV transformer capacity penetration up to 75%. Results indicate that the PV penetration level should not adversely impact the voltage on the grid when the distributed PV resources do not exceed 2.5 kW per household on average on a typical distribution grid. Moreover, the role of feeder impedance, feeder length, and the transformer short circuit resistance in the determination of the voltage rise is quantified.

Big data has potential to unlock novel groundbreaking opportunities in power grid that enhances a multitude of technical, social, and economic gains. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data. In particular, computational complexity, data security, and operational integration of big data into power system planning and operational frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. In this context, suitable big data analytics combined with visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state‐of‐the‐art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into power system planning and operational frameworks. Detailed information for utilities looking to apply big data analytics and insights on how utilities can enhance revenue streams and bring disruptive innovation are discussed. General guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.