Increased deployment of variable renewable energy (VRE) has posed significant challenges to ensure reliable power system operations. As VRE penetration increases beyond 80%, the power system will require long duration energy storage and flexibility. Detailed uncertainty analysis, identifying challenges, and opportunities to provide sufficient flexibility will help to achieve smooth operations of power system networks during the scenario of high share of VRE sources. Hence, this paper presents a comprehensive overview of the power system flexibility (PSF). The intention of this review is to provide a wide spectrum of power system flexibility, PSF drivers, PSF resources, PSF provisions, methods used for assessment of flexibility and flexibility planning to the researchers, academicians, power system planners, and engineers working on the integration of VRE into the utility grid to achieve high share of these sources. More than 100 research papers on the basic concepts of PSF, drivers of the PSF, resources of PSF, requirement of the PSF, metrics used for assessment of the flexibility, methods and approaches used for measurement of flexibility level in network of the power system, and methods used for the PSF planning and flexibility provisions have been thoroughly reviewed and classified for quick reference considering different dimensions.

Bulk integration of Distributed Energy Resources (DERs) into the power grids reduces the system’s inherent inertial response.The reduced inertial response causes a high Rate-of-Change-of-Frequency (RoCoF) and poses formidable operational challenges for the grid frequency stability. Interconnections around the world comprehend the role and value of the Synthetic Inertia Control (SIC), which is considered as a subset of the Fast Frequency Response (FFR) and as one of the potential solutions to arrest high RoCoF in low-inertia power systems. This paper proposes an intelligent SIC model with an adaptive Fuzzy Logic Controller for a low-inertia microgrid. The proposed Fuzzy-SIC (FSIC) design optimizes the DER output to fulfill the FFR requirements of the system for various operating conditions. The particle swarm optimization algorithm is applied to tune the SIC unit parameters along with the secondary Proportional-Integral-Derivative control. The proposed approach is examined in a control area with distinct degrees of DERs and load. Case studies and numerical results demonstrate about 87% improvement in RoCoF and frequency nadir in comparison to the system without a synthetic inertia emulation. Furthermore, the robustness of the proposed approach is evaluated using various case studies and a time-domain analysis is conducted to demonstrate the impact of incremental SIC parameters on the system parameters.

High penetration of renewable energy sources (RES) particularly wind and solar in the electric power system would reduce environmental pollution and cope with energy demand in a sustainable manner. In addition to this, electric vehicles (EV) are integrated into the power system as alternate solution to fossil fuel based vehicles. Integration of both RES and EV create range of economic and technical challenges for the system operators (SO) due to their stochastic nature. In this context, this paper aims to investigate the impact of high RES and EV penetration on generation scheduling and overall cost. Exposition of two-stage model is proposed in which the first stage is aggregator model for EV scheduling based on expected price of the day-ahead electricity market and the second stage is market model for optimal generation scheduling considering RES and EVs. Proposed model is implemented on IEEE 24 bus system. Obtained results show the significant impact of high penetration of RES and EV on generation scheduling and total system cost reduction.