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This paper presents a methodology to assess large-scale wind generation projects that considers their effect on network security. The proposed method is based on contingency analysis, including temporal study. Inputs to the simulation are grid model, forecasted load, conventional generation profiles, and wind variability of proposed projects. A time-step simulation is run for the time horizon to produce benefit indices for every location (bus) in the system. The congested transmission elements that require expansion are identified and ranked as part of the simulation. Each wind project in the proposed portfolio can result in benefits or costs for grid security. Policy makers can then use the method to design policies that ensure preservation of long-term system security. Developers could use the tool to identify security effects and assess their wind portfolios. Measuring network security and determining benefits of large-scale wind projects is a complex planning task that involves several aspects: temporal wind variability, spatial distribution of flows, multiple load and generation profiles, and numerous possible contingencies. All these wind project development aspects must be isolated to identify and correctly assign security costs and benefits. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive methodology to determine the locational value of new generation in enhancing system security. The method is based on contingency analysis postprocessing and a novel three-dimensional weighted transmission loading relief (WTLR) calculation. A locational value that can be visualized on a geo-referenced map is assigned to each bus in the system. The spatial representation of the locational value can be overlaid with energy resource maps in order to prioritize siting projects to achieve adequacy and benefit overall system security. [ABSTRACT FROM AUTHOR]

Proposes an algorithm to enhance linear available transfer capability (ATC) calculations in computer networks. Background on linear ATC and line complex flows; Classification of potential errors in determining ATC; Application of the algorithm in a three-bus case and in large systems.

This article is the second part of a two-part article on communication-failure-resilient architecture for distributed operation and control in smart grids with hybrid producer/consumer (prosumer) agents. Part I of this article proposed the distributed architecture and algorithmic development, while this Part II provides the corresponding algorithmic implementation, technical requirements, practical applications, and simulations. We propose a general and scalable framework for implementing resilient distributed frequency regulation (DFR) on large-scale prosumer-based power grids, such as utilities, where each prosumer represents a frequency control area. We first develop a method to obtain quasi-steady state models of prosumers from the dynamic models of generators, loads, and power lines. This model allows demonstrating the dynamic evolution of prosumers under normal conditions and during communication failures. Next, we propose a framework to implement the resilient DFR algorithm on prosumer power grids. We show that under normal conditions prosumers need to solely communicate with their neighbors to obtain optimal control actions. But, during communication failures, prosumers need to extend the communication hops to maintain system-wide stability as well as fair power sharing. The resilient DFR algorithm is demonstrated on two real-world, large-scale power grids and the results show that it can indeed complement and enhance today's Automatic Generation Control systems. [ABSTRACT FROM AUTHOR]

Distributed algorithms have been proposed as options to scale control propositions to the massive number of intelligent energy devices, sub-systems, and distributed energy resources being integrated into the electricity grid. Distributed algorithms rely on the communication network for exchanging information. Failures in the communication network can jeopardize distributed decision-making and in the worst-case scenario can lead to system-level stability problems. This paper proposes a communication-failure-resilient architecture for distributed operation and control in smart grids with hybrid producer/consumer (prosumer) agents. We describe the relations between system-wide performance and communication failures and identify topological conditions on the cyber-physical network, under which prosumers can perform key operating tasks, such as distributed frequency regulation through an imperfect communication network. [ABSTRACT FROM AUTHOR]

The increasing power/load demand is becoming a new concern for the grid operators as it can potentially overload transmission lines. Among advantages of a multi-terminal dc (MTDC) grid, its high controlability makes it a promising asset for ac line overload alleviation. This paper proposes a model predictive control based strategy, which regularly updates the power setpoints of the MTDC converter stations and ac generators to alleviate ac line overloads. To compute and update the power setpoints, necessary measurements are received by the controller within regular time intervals. The proposed controller ensures that subsequent to any ac line overload, changing the power setpoints of the MTDC converter station does not cause any operation violation in the MTDC grid. Furthermore, it ensures that the ac voltage limits and voltage stability criteria are met to avoid voltage instability. Performance and effectiveness of the proposed controller are evaluated by simulation studies on two systems, i.e., the 39-bus New England system integrated with a 5-bus MTDC system and the IEEE 118-bus system connected to a 6-bus MTDC system. Simulation results confirm that the MTDC grid can play a major role in controlling active powers of most of the ac transmission lines. [ABSTRACT FROM AUTHOR]

The smart grid (SG), regarded as the complex cyber-physical ecosystem of infrastructures, orchestrates advanced communication, computation, and control technologies to interact with the physical environment. Due to the high rewards that threats to the grid can realize, adversaries can mount complex cyber-attacks such as advanced persistent threats-based and coordinated attacks to cause operational malfunctions and power outages in the worst scenarios: The latter of which was reflected in the Ukrainian power grid attack. Despite widespread research on smart grid security, the impact of targeted attacks on control and power systems is anecdotal. This article reviews the smart grid security from collaborative factors, emphasizing the situational awareness (SA). Specifically, we propose a threat modeling framework and review the nature of cyber-physical attacks to understand their characteristics and impacts on the smart grid’s control and physical systems. We examine the existing threats detection and defense capabilities, such as intrusion detection systems (IDSs), moving target defense (MTD), and co-simulation techniques, along with discussing the impact of attacks through situational awareness and power system metrics. We discuss the human factor aspects for power system operators in analyzing the impacts of cyber-attacks. Finally, we investigate the research challenges with key research gaps to shed light on future research directions. [ABSTRACT FROM AUTHOR]

To improve the resilience of electric distribution systems, this paper proposes a stochastic multi-period mixed-integer linear programming model that determines where to underground new distribution lines and how to coordinate mobile generators in order to serve critical loads during extreme events. The proposed model represents the service restoration process using the linearized DistFlow approximation of the AC power flow equations as well as binary variables for the undergrounding decisions of the lines, the configurations of switches, and the locations of mobile generators during each time period. The model also enforces a radial configuration of the distribution network and considers the transportation times needed to deploy the mobile generators. It is shown that long-term line undergrounding decisions which are cognizant of short-term mobile generator deployments yield superior results relative to undergrounding decisions made without considering mobile generators. Using an extended version of the IEEE 123-bus test system, numerical simulations show that combining the ability to underground distribution lines with the deployment of mobile generators can significantly improve the resilience of the power supply to critical loads. • Resilience can be improved via mobile generators and underground lines. • Stochastic optimization for siting underground lines and operating mobile generators. • Show benefits from jointly considering undergrounding and mobile generator decisions. [ABSTRACT FROM AUTHOR]