Event Sponsorship & Exhibitor Opportunities 
Islanding Detection of Grid-Forming Inverters: Mechanism, Methods, and Challenges
Over the past decades, because of boosted energy demands and the serious concerns of climate change, inverter-based resources (IBRs) have been widely deployed to integrate renewable energy into power systems for the goal of carbon neutrality. Thanks to the full controllability of power electronic devices, IBRs have the capability to implement reliable and flexible power regulation, which makes them technically feasible for enhancing the resilience and energy efficiency of power systems.
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Intra-Hour Photovoltaic Generation Forecasting Based on Multi-Source Data and Deep Learning Methods
Global issues pertaining to climate change have necessitated the rapid deployment of new energy sources, such as photovoltaic (PV) generation. In smart grids, accurate forecasting is essential to ensure the reliability and economy of the power system. However, PV generation is severely affected by meteorological factors, which hinders accurate forecasting. Various types of data, such as local measurement data, numerical weather prediction, and satellite images, can reflect meteorological dynamics over different time scales. This paper proposes a novel data-driven forecasting framework based on deep learning, which integrates an advanced U-net and an encoder-decoder architecture to cooperatively process multi-source (time series recording and satellite image) data.
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Flexibility in Sustainable Electricity Systems: Multivector and Multisector Nexus Perspectives
As environmental concerns increase, researchers, policy makers, and the public in general are becoming more interested in options to make energy more sustainable while at the same time ensuring that energy systems are affordable, reliable, and resilient. This dynamic is bringing about challenges across the world, as established energy systems (such as those in cities) must be enhanced to integrate large volumes of renewable energy sources (RES), while new or evolving systems (for instance, in developing economies) must be planned to manage the increasingly extreme conditions associated with climate change.
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The Fragile Grid: The Physics and Economics of Security Services in Low-Carbon Power Systems
Worldwide, there are unstoppable forces toward low-carbon power systems that can support the fight against climate change and help solve the security of supply issues in many countries. Low-carbon grids are likely to be characterized by substantial renewable energy sources, both centralized and distributed, combined with intelligent and dynamic demand-side technology and multisector electrification (including heating, transport, and future fuels). In this context, successfully resolving the “affordability-sustainability-reliability” energy trilemma is crucial for paving the way to low-carbon energy futures.
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Latin American Energy Markets: Investment Opportunities in Nonconventional Renewables
Latin America is very rich from the point of view of its varied energy resources, with an abundance of hydroelectric generation and large reserves of fossil fuels. At present, although there is a general awareness of climate change issues associated with fossil fuel use, the facts show that economic needs over the short and medium terms are the engine of technology change.
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Supporting Energy Transition in Transmission Systems: An Operator’s Experience Using Electromagnetic Transient Simulation
The electric power industry is faced with the challenges of mitigating climate change, maintaining low electricity prices, and satisfying high reliability requirements for power supply. The increased application of power electronics devices is the inevitable result of the changes being experienced by the system. Careful analysis is required to install and operate power electronics devices. This article describes the use of electromagnetic transient (EMT) simulation on the French transmission grid to meet these new challenges in the context of energy transition.
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A Numerical Approach for Hybrid Simulation of Power System Dynamics Considering Extreme Icing Events
The global climate change leads to more extreme meteorological conditions such as icing weather, which have caused great losses to power systems. Comprehensive simulation tools are required to enhance the capability of power system risk assessment under extreme weather conditions. A hybrid numerical simulation scheme integrating icing weather events with power system dynamics is proposed to extend power system numerical simulation. A technique is developed to efficiently simulate the interaction of slow dynamics of weather events and fast dynamics of power systems. An extended package for PSS/E enabling hybrid simulation of icing event and power system disturbance is developed, based on which a hybrid simulation platform is established.
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Planning With Multiple Transmission and Storage Investment Options Under Uncertainty: A Nested Decomposition Approach
Achieving the ambitious climate change mitigation objectives set by governments worldwide is bound to lead to unprecedented amounts of network investment to accommodate low-carbon sources of energy. Beyond investing in conventional transmission lines, new technologies, such as energy storage, can improve operational flexibility and assist with the cost-effective integration of renewables. Given the long lifetime of these network assets and their substantial capital cost, it is imperative to decide on their deployment on a long-term cost-benefit basis. In this paper, we propose a novel, efficient, and highly generalizable framework for solving large-scale planning problems under uncertainty by using a temporal decomposition scheme based on the principles of Nested Benders.
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A Probabilistic Transmission Planning Framework for Reducing Network Vulnerability to Extreme Events
The restructuring of electric power industry has brought in plenty of challenges for transmission expansion planning (TEP), mainly due to uncertainties. The commonly used probabilistic TEP approach requires the network to meet an acceptable risk criterion. However, a series of blackouts in recent years caused by extreme weather-related events have raised the concerns about network vulnerability through calculating the expected risk value. In this paper, we have proposed the concept that TEP should be economically adjusted in order to make network less vulnerable to extreme events (EEs) caused by climate change, e.g., floods or ice storms.
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Robust Resiliency-Oriented Operation of Active Distribution Networks Considering Windstorms
Recent climate changes have created intense natural disasters, such as windstorms, which can cause significant damages to power grids. System resilience is defined as the ability of the system to withstand such high-impact low-probability events. This paper proposes a robust resilient operational schedule for active distribution networks against windstorms. In order to capture dynamic behaviors of these disasters, zonal disaster-specific uncertainty sets associated with the windstorm are proposed.
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