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The world faces mounting challenges related to food, energy, and water security. Modeling approaches have emerged in the last decade to address this problem with mixed outcomes across a range of boundaries, including local, regional, national, and by research agendas. This paper delves into a comprehensive meta-analysis of the literature to identify the prevalence and strengths of these emergent approaches on the agendas they were applied to, the boundary levels, nexus dimensions, and the perspectives of the social and political dynamics. The research highlights the critical gaps that remain in the intersection of the different nexus agendas. A crucial observation was the scarcity of food, energy, and water models that incorporate technology adoption and economic implementation of nexus projects. On the core dimensions of the nexus, there is an important opportunity to include ecosystems, soil health, human health, and waste as key nexus dimensions. Although it is difficult to include social and political dynamics in nexus studies, this research identified proxies including (1) stakeholder interactions; (2) the intersection of access, security, and education; and (3) trade patterns and measures of prosperity. 

Failure identification and prediction in a power system are essential components that are prerequisites for optimizing the maintenance of the system. The incidences of power system failures have increased dramatically in recent times due to the uncertainties inherent in the advent of both man-made and natural disasters. This problem is further exacerbated due to the increasing demand for higher operational efficiency in power systems. Currently, there is a paucity of studies that predict and identify failure in a distribution power system. In this paper, we propose an integrated methodology for selecting the optimal maintenance plan based on predicting and identifying failure modes with the aid of Hidden Markov Models (HMM) and a probabilistic decision-making tool. While the model parameters of previous studies were determined utilizing observable prior knowledge, the use of HMM offers a different approach especially in the absence of such observable prior distributions. Thus, we determine the status of health of a power system by using an HMM to capture the relationship between unobservable degradation state and observed parameters. The preliminary outcome is instructive for the management of power systems especially in response to fortifying the system against aging and degradation. 

There is no doubt that there is an increase in the penetration of electrical energy into the operation of high-speed railway systems (HSR). This is even more pronounced with the increasing trends in smart electric multiple units (EMU). The operational speed serves as a metric for punctuality and safety, as well as a critical element to maintain the balance between energy supply and consumption. The speed-based regenerative energy from EMU’s braking mode could be utilized in the restoration of system operation in the aftermath of a failure. This paper optimizes the system resiliency with respect to the operational speed for the purpose of restoration by minimizing the total cost of implementing recovery measures. By simultaneously valuating the dual-impact of any given fault on the speed deterioration level from the railway operation systems (ROS) side and the power supply and demand unbalance level from the railway power systems (RPS) side, this process develops an adaptive two-dimension risk assessment scheme for prioritizing the handling of different operational zones that are cascaded in the system. With the aid of an integrated speed-based resilience cost model, we determine the optimal resilience time, speed modification plan, and energy allocation strategy. The outcome from implementing this routine in a real-world HSR offers a pioneering decision-making strategy and perspective on optimizing the resilience of an integrated system. 

The nexus of food, energy, and water systems offers a meaningful lens to evaluate hydroelectric dam removal decisions. Maintaining adequate power supplies and flourishing fish populations hangs on the balance of managing the tradeoffs of water resource management. Aside from energy adequacy, substituting hydropower with other renewable energy sources impacts the overall energy dispatch behavior of the grid, including emissions of existing fossil fuels. This study extends earlier work in the literature to evaluate the adequacy impact to the power supply by removing four Lower Snake River dams in the Columbia River Basin in favor of supporting migratory salmon populations. The authors explore the climate performance, i.e., fossil fuel dispatch changes, of simulated renewable substitution portfolios to supplement performance metrics alongside adequacy and initial investment metrics. The study finds that including the climate metric greatly influences the favorability of some alternative portfolios that would otherwise be overlooked, with some portfolios improving climate mitigation efforts by reducing emissions over the baseline scenario. The contribution is in advancing a straightforward and supplementary climate performance method that can accompany any energy portfolio analysis. 

Purpose of Review This paper focuses on the advances in the resilience of electricity systems and energy markets. The objective is to identify how the progress on system resilience may influence market rules while uncovering the gaps in the literature. Recent Findings This review distills three findings. First, significant advances have been achieved both in the design and configuration of power systems for resilience. Second, topological and architectural advances appear isolated from market operations. Third, there is room to integrate self-healing resilience into power systems and bridge the bifurcation between increasing network resilience and having the market adequately value resilience. Summary Evidently, the incidences of disruptions to electricity networks are on the rise, making a change from having a merely reliable electricity network to one that is resilient and adaptive a necessity. This review showcases the qualitative value inherent in processes to enhance adaptive resilience while promoting the requisite signals for power market integration. 

This paper examines the use of quantitative research agendas on systems modeling to study anticipatory cognition and cultural competency. This combination results in an integrative science approach to explore the intersectionality of metacognition, academic self-efficacy, stereotype threat, scholarly reasoning and identity among minority black diaspora graduate students. Extant literature focuses on social support models, but the novelty of the approach in this paper examines metacognition in action within a culturally-aware context. Data were collected as semi-structured narrative inquiry to capture metacognition during learning using narrative identity construction as a tool. There was a total of five students in the study including three females and two male participants in their first year of the graduate studies. However, the analysis focused on three of the participants who provided data consistently for eleven months -- two males and one female. The participants provided data including responses to Likert scale questions, and weekly video narratives in response to three sets of questions each week in an n-of-1 big data approach. This approach has the empirical benefit of allowing more inclusive and personalized analyses to draw conclusions. By observing the requirements of an approved IRB protocol, the analysis based on the transcripts of the video recordings, and the examination of change within each individual over time was confidential and conducted with de-identified data. Video recordings are coded and analyzed using HyperRESEARCH TM version 3.7.5. The result calibrates students’ comprehension, integration, and application of impactful, data-driven research skills. The metacognitive development portion examines the influence and dynamics of anticipatory cognition, stereotype threat, identity, and academic self-efficacy as the students’ progress through the process of quantitative skills mastery. This paper reports on the highlights of the distilled data on: (i) anticipatory cognition -- construct to describe use of prospective memory to simulate future associations and expected outcomes; (ii) academic self-efficacy -- captures the perceived level of confidence in the participants to engage successfully in specific cognitive acts associated with academic mastery; (iii) stereotype threat -- captures the anxiety associated with the salience of status as a member of a group that is stereotyped as underperforming in a specific area; (iv) identity or categorization of the self as a scholar and engineer. Other themes emerging include perseverance or determination, isolation, extant knowledge, future anticipation, and problem solution focus. 

This paper presents a survey of the literature on the strategies to enhance the resilience of power systems while shedding lights on the research gaps. Using a deductive methodology on the literature covering the resilience of power systems, we reviewed more than two hundred peer-reviewed articles spanning the 2010–2019 decade. We find that there is vacuum on the level of integration that considers the interdependence of local or decentralized decision making in an adaptive power system. This gap is widened by the absence of policies to enhance resilience in power networks. While there is significant coverage and convergence of research on algorithms for solving the multi-objective problem in optimization routines, there are still uncharted territories on how to incorporate system degradation while designing these self-restoration systems. We posit that a shift to a smarter, cleaner and more resilient power network requires sustained investments rather than disaster-induced responses. 

The widespread presence of contingent generation, when coupled with the resulting volatility of the chronological net-load (i.e., the difference between stochastic generation and uncertain load) in today's modern electricity markets, engender the significant operational risks of an uncertain sufficiency of flexible energy capacity. In this article, we address several operational flexibility concerns that originate from the increase in generation variability captured within a security-constrained unit commitment (SCUC) formulation in smart grids. To quantitatively assess the power grid operational flexibility capacity, we first introduce two reference operation strategies based on a two-stage robust SCUC, one through a fixed and the other via an adjustable uncertainty set, for which the state-of-the-art techniques may not be always feasible, efficient, and practical. To address these concerns and to account for the effects of the uncertainty cost resulting from dispatch limitations of flexible resources, a new framework centered on the adjustable penetration of stochastic generation is proposed. Our hypothesis is that if the SCUC is scheduled with an appropriate dispatch level of stochastic generation, the system uncertainty cost will decrease, and subsequently, the system's ability to accommodate additional uncertainty will improve. Numerical simulations on a modified IEEE 73-bus test system verify the efficiency of the suggested assessment techniques. 

The growth of renewable energy technologies creates significant challenges for the stability of the system because of their intermittency. Nonetheless, we can value these technologies with storage systems. We model the supply by a renewable technology, wind, into a storage facility using the leaky bucket mechanism. The bucket is synonymous with storage while the leakage is equivalent to meeting load. Modelica is used to capture: (i) the time-dependence of the state of the bucket based on a physical model of storage; (ii) the stochastic representation of wind energy using wind speed data that is fed into a physical model of a wind technology; and (iii) the load, modeled as a resistor-inductor circuit. The strength of Modelica in using non-causal equations for basic sub-systems that are linked together is harnessed through its libraries. We find that there is a diminishing return to storage. Beyond a certain level of storage, the integration of a reliable baseload power supply is required to diminish the risk due to reduced reliability. The need for storage systems as a hedge against intermittency is dependent on the interplay between the supply volatilities and the stochastic load to guarantee an acceptable level of quality of service and reliability.