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Co-optimization to Integrate Power System Reliability Decisions with Resiliency Decisions.
Abstract not provided.
Co-optimization to Integrate Power System Reliability Decisions with Resiliency Decisions.
Abstract not provided.
Co-optimization to Integrate Power System Reliability Decisions with Resiliency Decisions.
Abstract not provided.
Co-optimization to Integrate Power System Reliability Decisions with Resiliency Decisions.
Abstract not provided.
Co-optimization to Integrate Power System Reliability Decisions with Resiliency Decisions.
Abstract not provided.
Quantum Distribution System Reliability Assessment
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Machine Learning-Based Composite Power System Reliability Assessment
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New Report Highlights LAMP's Role as a Robust and Reliable System for Wave Energy Converter Testing
Harnessing the power of waves requires more than just putting devices in the ocean - it takes tools that can refine and accelerate innovation before the first deployment. That's where NLR's largeamplitude motion platform, or LAMP, comes in. LAMP is a six-degree-of-freedom motion system designed to replicate the response of a wave energy converter (WEC) device in realistic ocean conditions. By letting researchers evaluate WEC performance in a safe, controlled lab environment before moving offshore, LAMP helps accelerate innovation while reducing risk. An NLR report, titled Initial Characterization of the NLR LargeAmplitude Motion Platform (https://www.nrel.gov/docs/fy26osti/93733.pdf), provides a deeper understanding of LAMP's capabilities and also lays the groundwork for future advancements in WEC testing methodologies. Researchers studied LAMP's amplitude and frequency limits across different payloads and collected data from 16 test profiles. Testing demonstrated that platform accuracy remained consistent across all payloads evaluated; researchers expect similar accuracy up to LAMP's 10,000-kilogram capacity limit. The measured position limits for single degrees of freedom experienced by WECs, including surge, sway, heave, roll, pitch, and yaw, also exceeded the original manufacturer specifications, providing new insight into the true boundaries of the system.
A Systematic Approach to Applying Lean Techniques to Optimize an Office Process at the Y-12 National Security Complex
This capstone offers the introduction of Lean concepts to an office activity to demonstrate the versatility of Lean. Traditionally Lean has been associated with process improvements as applied to an industrial atmosphere. However, this paper will demonstrate that implementing Lean concepts within an office activity can result in significant process improvements. Lean first emerged with the conception of the Toyota Production System. This innovative concept was designed to improve productivity in the automotive industry by eliminating waste and variation. Lean has also been applied to office environments, however the limited literature reveals most Lean techniques within an office are restricted to one or two techniques. Our capstone confronts these restrictions by introducing a systematic approach that utilizes multiple Lean concepts. The approach incorporates: system analysis, system reliability, system requirements, and system feasibility. The methodical Lean outline provides tools for a successful outcome, which ensures the process is thoroughly dissected and can be achieved for any process in any work environment.
Wholesale electricity market design with increasing levels of renewable generation: Revenue sufficiency and long-term reliability
This paper discusses challenges that relate to assessing and properly incentivizing the resources necessary to ensure a reliable electricity system with growing penetrations of variable generation (VG). The output of VG (primarily wind and solar generation) varies over time and cannot be predicted precisely. Therefore, the energy from VG is not always guaranteed to be available at times when it is most needed. This means that its contribution towards resource adequacy can be significantly less than the contribution from traditional resources. Variable renewable resources also have near-zero variable costs, and with production-based subsidies they may even have negative offer costs. Because variable costs drive the spot price of energy, this can lead to reduced prices, sales, and therefore revenue for all resources within the energy market. The characteristics of VG can also result in increased price volatility as well as the need for more flexibility in the resource fleet in order to maintain system reliability. Furthermore, we explore both traditional and evolving electricity market designs in the United States that aim to ensure resource adequacy and sufficient revenues to recover costs when those resources are needed for long-term reliability. We also investigate how reliability needs may be evolving and discuss how VG may affect future electricity market designs.
Development and testing of a performance evaluation methodology to assess the reliability of occupancy sensor systems in residential buildings
With the emergence of advanced occupancy sensor technologies to better detect occupancy in buildings, a universal methodology and metrics are required to evaluate and report sensor systems’ reliability and compare the performance across multiple sensor systems. Herein this research presents a methodology to assess the reliability of occupancy sensor systems in residential buildings in a controlled laboratory environment, including both “typical” and “failure” testing scenarios. The developed methodology was then implemented to evaluate a novel occupancy detection sensor system’s reliability. “Typical” testing evaluates the overall accuracy of the sensor system, which suggest how reliable the occupancy sensor system is over time. Results show that on average, the precision and recall are 0.75 and 0.70, indicating similar numbers of false positives and false negatives across the dataset. The overall accuracy of the tested sensor system was 62.4% to 76.4%. Failure testing results indicate whether there are influential variables impacting the sensor performance. For the tested sensor system, the number of occupants, presence of large objects, presence of interior light sources, and number of doors are not influential, while lighting level, location of occupants, additional door in the entry/exit area, and having the TV on are variables determined to impact the sensor system performance.
Distribution System Pricing with Distributed Energy Resources
Technological changes in the electric utility industry bring tremendous opportunities and significant challenges. Customers are installing clean sources of on-site generation such as rooftop solar photovoltaic (PV) systems. At the same time, smart appliances and control systems that can communicate with the grid are entering the retail market. Among the opportunities these changes create are a cleaner and more diverse power system, the ability to improve system reliability and system resilience, and the potential for lower total costs. Challenges include integrating these new resources in a way that maintains system reliability, provides an equitable sharing of system costs, and avoids unbalanced impacts on different groups of customers, including those who install distributed energy resources (DERs) and low-income households who may be the least able to afford the transition.
An Approach to Automate tools for the Risk Assessment of Digital Instrumentation and Control Systems
Reliable digital instrumentation and control systems (DI&C) are integral for sustaining the continued operation of nuclear power plants. These systems ensure that nuclear reactors operate safely, efficiently, and within regulatory requirements. Yet, the cost of designing and licensing new nuclear DI&C can be prohibitively expensive. Under the U.S. Department of Energy Light Water Reactor Sustainability Program, Idaho National Laboratory has developed a framework for supporting the risk-informed design of DI&C systems by offering methods to support the identification, quantification, and evaluation of risks for various DI&C design architectures. The framework indicates potential software failure modes and provides pathways for quantifying the potential for these software failures, including common cause failures. Using the framework’s systematic approach, challenges for assessing risks within new and existing nuclear DI&C systems can be reduced. Nevertheless, the current framework can be further improved using the convenience of automation. This paper introduces the development of Software for the Hazard Identification and Evaluation of Digital Systems (SHIELDS). SHIELDS is an engineering software package that enables the identification, elimination, and mitigation of potential risks and reduces the burden of deploying reliable DI&C systems. This work introduces plans and techniques to digitize and improve the manual risk assessment modules of the framework. These improvements will save time and increase the repeatability and usability of the framework, making it more accessible to a wider range of users. Ultimately, this introduces SHIELDS and how its modules support efficient development of safe and reliable DI&C systems.
Recent advances and challenges in optimization models for expansion planning of power systems and reliability optimization
Optimization models for expansion planning of power systems aim to determine capacities, investment timing, and location of power systems to satisfy the power demands while minimizing the total cost. The models have become complex in recent years to reflect both regulations on conventional energy sources and the increasing penetration of renewable energy sources (RES). This paper reviews the basic concepts and optimization models for expansion planning of power systems. We first explain the definition and features of generation expansion planning (GEP), transmission expansion planning (TEP), and generation and transmission expansion planning (GTEP). To address the computational challenges of large-scale expansion planning problems, we review several simplifications including temporal and spatial aggregation, and decomposition methods. This paper also addresses power system reliability defined as the probability of satisfying the load demand while withstanding failures of components. Finally, the goal of this paper is to provide a research overview, discuss trends in expansion planning of power systems, and suggest directions for future research.
Modular & Scalable Small-Scale Mass-on-Spring Wave Energy Convertor (MOSWEC) PowerBuoy System for Reliable Powering of Autonomous Ocean Monitoring System
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Multi-Stage and Multi-Timescale Robust Co-Optimization Planning for Reliable and Sustainable Power Systems. Final Report
In this project, Clarkson University, in collaboration with Southern Methodist University and University of Pittsburgh, conducted the research to model, design, and implement a sophisticated generation and transmission co-optimization planning decision tool, called Multi-stage and Multi-timescale robust Co-Optimization Planning (MMCOP). The MMCOP decision tool intends to facilitate generation and transmission co-optimization planning of emerging power systems, while mitigating risks and uncertainties in both short-term operation dynamics and long-term policy and technology changes. Long-term power system planning aims at optimizing asset utilization by investing in a proper mix of various generation technologies and transmission lines to supply the future load growth. In particular, the Clean Power Plan (CPP), which is designed to combat climate change and reduce carbon emissions by setting a national limit on carbon pollution from power plants, may dramatically change the landscape of the power industry by further promoting clean energy and phasing out emissions-intensive generation technologies. In addition, novel non-wire alternatives (e.g., demand response (DR), distributed generation (DG), energy efficiency (EE), and smart grid technologies) and the computational complexity for large-scale systems significantly complicate the system planning procedure even further. However, existing conventional planning approaches neglect short-term variability and uncertainty of renewable energy, hourly chronological operation details, and physical nonlinear characteristics of the alternating current transmission network. As a result, existing conventional planning approaches may not work properly, and power systems reliability could be in jeopardy. In observing the limitations of existing conventional planning approaches and addressing new challenges of emerging power systems, the main scope of this project to develop co-optimization planning models within a multi-stage and multi-timescale framework. In particular, random contingencies, key uncertainty factors, and AC power flows are included to derive expansion plans while considering both long-term reliability and short-term flexibility.
Integrating Transactive Energy into Reliability Evaluation for a Self-healing Distribution System with Microgrid
Non-utility owned distributed energy resources (DERs) are mostly untapped currently, but they can provide many grid services such as voltage regulation and service restoration, if properly controlled, and can improve the distribution systems reliability when coordinated with utility-owned assets such as self-healing control and microgrids. This paper integrates transactive energy control into the distribution system reliability evaluation to quantitatively assess the impact of non-utility owned DERs on reliability improvement. Here, a transactive reactive power control strategy is designed to incentivize the DERs to provide reactive power support for improving voltage profiles thus enabling additional customer load restoration during an outage. Also, an operational sequence to coordinate the non-utility owned DERs with the utility owned self-healing control and utility owned microgrids is designed and integrated into the service restoration process with the operational constraints guaranteed by checking the three-phase unbalanced power flow for post-fault network reconfiguration. The reliability indices are then calculated through a Monte Carlo simulation. The transactive reactive power control strategy is tested on a four-feeder distribution system operated by Duke Energy in the U.S. Results demonstrate that the non-utility owned DERs with the transactive control improve the reliability of both the system and critical loads by more than 30%.