Microgrids for power system resilience enhancement

Power system resilience is defined as the ability of power grids to anticipate, withstand, adapt and recover from high-impact low-probability (HILP) events. There are both long-term and short-term measures that system operators can employ for resilience reinforcement. Longer-term measures include infrastructure hardening and resilient planning, while short-term operational measures are applied in the pre-event, during-event and post-event phases. Microgrids (MGs) can effectively enhance resilience for both transmission and distribution systems, due to their ability to operate in a controlled, coordinated way, when connected to the main power grid and in islanded mode. In this paper, MG-based strategies for resilience enhancement are presented, including MG-based resilient planning and MG-based operational measures, consisting of preventive MG scheduling and emergency measures and MG-based system restoration. Classification of literature is made by considering whether the transmission system, distribution system or individual MG resilience is targeted. The way uncertainties are handled by various methods is also outlined. Finally, challenges and future research requirements for improving MG-based power system resilience are highlighted

TSO-DSO-Customer coordination for purchasing flexibility system services: Challenges and lessons learned from a demonstration in Sweden

This paper presents a real-word implementation of a TSO-DSO-customer coordination framework for the use of flexibility to support system operation. First, we describe the general requirements for TSO-DSO-customer coordination, including potential coordination schemes, actors and roles and the required architecture. Then, we particularise those general requirements for a real-world demonstration in Sweden, aiming to avoid congestions in the grid during the high-demand winter season. In the light of current congestion management rules and existing markets in Sweden, we describe an integration path to newly defined flexibility markets in support of new tools that we developed for this application. The results show that the use of flexibility can reduce the congestion costs while enhancing the secure operation of the system. Additionally, we discuss challenges and lessons learned from the demonstration, including the importance of the engagement between stakeholders, the role of availability remuneration, and the paramount importance of defining appropriate technical requirements and market timings.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement nº 824414

Spatial Risk Analysis of Power Systems Resilience During Extreme Events

The increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real-time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on probabilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience-based decisions for risk mitigation. The IEEE 24-bus Reliability Test System has been used to demonstrate the effectiveness of the proposed online risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method

Microgrids against wildfires : distributed energy resources enhance system resilience

In recent years, countries around the world have been severely affected by catastrophic wildfires with significant environmental, economic, and human losses. Critical infrastructures, including power systems, have been severely damaged, compromising the quality of life and the continuous and reliable provision of essential services, including the electricity supply

A Novel Two-Stage Multi-Layer Constrained Spectral Clustering Strategy for Intentional Islanding of Power Grids

Intentional islanding can be considered as the last action to prevent power grids from severe blackouts. In this strategy, the endangered network is deliberately decomposed into self-sustained islands to improve the power grid resilience, reliability, and security. In this way, this paper develops a novel optimal intentional islanding solution to deal with deliberate physical attacks on the power system. The proposed solution employs a modified multi-layer constrained clustering method based on multi-layer graphs via subspace analysis on Grassmann manifolds clustering. The main objectives are to minimize the active and reactive powers disruptions crossways for decomposed islands, as well as grouping the generators with high-frequency change similarity so that stable operation of each self-supplied grid is ensured. This technique guarantees that each island is only comprised of generators that are synchronized with each other. The proposed multi-layer technique increases the stability of the island by implementing different criteria such as frequency, active power, and reactive power. To better display the improvement, the method is compared with the single layer constrained clustering that can only handle one criterion at a time. The proposed intentional islanding technique is applied to IEEE-9 bus, IEEE-39 bus, and IEEE-118 bus as small, medium, and large-scale networks, respectively