Dynamic Restoration of Active Distribution Networks by Coordinated Repair Crew Dispatch and Cold Load Pickup

This article presents a dynamic restoration strategy for active distribution networks (ADNs) by coordinating repair crew dispatch and frequency-constrained cold load pickup. To incorporate the stochastic repair time, the repair crew dispatch is formulated as “event-driven” with the implementation of model predictive control (MPC). The stochastic repair time is estimated, convexified, and updated dynamically with each MPC execution. The finish of a repair task triggers the subsequent cold load pickup model, where the frequency dynamics are computed and linearly constrained with the help of a uniform frequency response model for low-inertia systems. Next, a co-optimization framework of the two models is developed to coordinate the repair crew dispatch and cold load pickup under a unified time scale. Numerical results on a modified IEEE 33-node test feeder and a real-world 136-node distribution system have verified the effectiveness of the proposed model.©2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Classifying resilience approaches for protecting smart grids against cyber threats

Smart grids (SG) draw the attention of cyber attackers due to their vulnerabilities, which are caused by the usage of heterogeneous communication technologies and their distributed nature. While preventing or detecting cyber attacks is a well-studied field of research, making SG more resilient against such threats is a challenging task. This paper provides a classification of the proposed cyber resilience methods against cyber attacks for SG. This classification includes a set of studies that propose cyber-resilient approaches to protect SG and related cyber-physical systems against unforeseen anomalies or deliberate attacks. Each study is briefly analyzed and is associated with the proper cyber resilience technique which is given by the National Institute of Standards and Technology in the Special Publication 800-160. These techniques are also linked to the different states of the typical resilience curve. Consequently, this paper highlights the most critical challenges for achieving cyber resilience, reveals significant cyber resilience aspects that have not been sufficiently considered yet and, finally, proposes scientific areas that should be further researched in order to enhance the cyber resilience of SG.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funding for open access charge: Universidad de Málaga / CBUA

Multi-Area Frequency Restoration Reserve Sizing

Frequency Restoration Reserves are traditionally sized using deterministic methods. The constant growth in non-dispatchable renewable energy, however, is increasing the importance of probabilistic methods for reserve sizing. In addition, as the geographical scope of reserve sizing expands, overall power imbalance stochasticity is reduced. In this article, we propose a probabilistic method for shared cross-border frequency restoration reserve commitment and sizing, based on the concept of system generation margin and employing mathematical optimization. The aim is to reduce overall reserve volumes and costs. The cross-border interconnection capacities among countries are taken into account, and the shared uncertainty across interconnections is addressed via a novel robust approach. The method is tested on the cross-border system of south-east Europe that includes 9 countries. 5 different operational scenarios are used and a detailed calculation of the uncertainty distributions in each country is employed. Results show that cross-border shared sizing can significantly reduce overall reserve volumes and costs in a secure way.©2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

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

Modelling of micro-sources for security studies

International audienceThe interconnection of small, modular generation and storage technologies at the MV and LV distribution level have the potential to significantly impact power system performance. In this paper models of the main micro-generation sources are described. In particular, the models of Microturbines, Fuel Cells, Photovoltaic Systems and Wind Turbines, are described. In addition basic models of their power electronic interfaces are given. The integration of the above models in a steady state and dynamic simulation tool, which is developed in the framework of the EU funded MICROGRIDS project, will provide a simulation test platform, which will be necessary to define and evaluate the developed operational and control strategies

MORE CARE Overview

International audienceThis paper provides an overview of MORE CARE, a European R&D project financed within the 5th Framework Energy Programme. This project has as main objective the development of an advanced control software system, aiming to optimize the overall performance of isolated and weakly interconnected systems in liberalized market environments by increasing the share of wind energy and other renewable forms, including advanced on-line security functions. The main features of the control system comprise advanced software modules for load and wind power forecasting, unit commitment and economic dispatch of the conventional and renewable units and on-line security assessment capabilities integrated in a friendly Man-Machine environment. Pilot installations of advanced control functions are foreseen on the islands of Crete, Ireland and Madeira

Anemos : development of a next generation wind power forecasting system for the large-scale integration of onshore & offshore wind farms

International audienceThis paper presents the objectives and the research work carried out in the frame of the ANEMOS project on short-term wind power forecasting. The aim of the project is to develop accurate models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting, exploiting both statistical and physical modeling approaches. The project focus on prediction horizons up to 48 hours ahead and investigates predictability of wind for higher horizons up to 7 days ahead useful i.e. for maintenance scheduling. Emphasis is given on the integration of highresolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information by satellite-radar images. An integrated software platform, ‘ANEMOS', is developed to host the various models. This system will be installed by several utilities for on-line operation at onshore and offshore wind farms for prediction at a local, regional and national scale. The applications include different terrain types and wind climates, on- and offshore cases, and interconnected or island grids. The on-line operation by the utilities will allow validation of the models and an analysis of the value of wind prediction for a competitive integration of wind energy in the developing liberalized electricity markets in the EU

Next Generation Short-Term Forecasting of Wind Power – Overview of the ANEMOS Project.

International audienceThe aim of the European Project ANEMOS is to develop accurate and robust models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced statistical, physical and combined modelling approaches were developed for this purpose. Priority was given to methods for on-line uncertainty and prediction risk assessment. An integrated software platform, 'ANEMOS', was developed to host the various models. This system is installed by several end-users for on-line operation and evaluation at a local, regional and national scale. Finally, the project demonstrates the value of wind forecasts for the power system management and market integration of wind power. Keywords: Wind power, short-term forecasting, numerical weather predictions, on-line software, tools for wind integration