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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Stochastic Unit Commitment in Isolated Systems With Renewable Penetration Under CVaR Assessment
Isolated regions and islands are facing imported fossil-fuel dependency, higher electricity prices, and vulnerability to climate change. At the same time, they are increasing their renewable penetration and, therefore, risk for electric utilities. Integrating stochastic energy resources in noninterconnected systems may take advantage of an intelligent and optimized risk-averse unit commitment (UC) model. This paper presents a two-stage stochastic UC model with high renewable penetration including reserve requirements for the efficient management of uncertainty.
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Resilience Assessment of Distribution Systems Integrated With Distributed Energy Resources
The resilience of electric systems is receiving growing attention due to their increased vulnerability to infrastructure damages and widespread outages from frequent extreme climactic conditions attributed to global warming effects. Resilience evaluation methods should recognize the uncertainties and correlations in the performance variations of different types of energy resources, load characteristics, extreme events and their impacts on the grid elements.
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On the Path to Decarbonization: Electrification and Renewables in California and the Northeast United States
Climate change threatens our quality of life and the habitability of planet Earth for many species. The Intergovernmental Panel on Climate Change estimates that, to reduce the risk that global temperature increases more than 2 °C above preindustrial levels, greenhouse gas (GHG) emissions in developed countries must fall by approximately 80% below 1990 levels by 2050. A number of states and regions in the United States have committed to reducing long-term GHG emissions by this level, including California, New York, and New England.
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Stochastic Generation Capacity Expansion Planning Reducing Greenhouse Gas Emissions
With increasing concerns about greenhouse gas emissions, a least-cost generation capacity expansion model to control carbon dioxide (CO 2) emissions is proposed in this paper. The mathematical model employs a decomposed two-stage stochastic integer program. Realizations of uncertain load and wind are represented by independent and identically distributed (i.i.d.) random samples generated via the Gaussian copula method. Two policies that affect CO 2 emissions directly and indirectly, carbon tax and renewable portfolio standard (RPS), are investigated to assess how much CO 2 emissions are expected to be reduced through those policies.
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