Uncertainty Quantification And Economic Dispatch Models For The Power Grid

The modern power grid is constrained by several challenges, such as increased penetration of Distributed Energy Resources (DER), rising demand for Electric Vehicle (EV) integration, and the need to schedule resources in real-time accurately. To address the above challenges, this dissertation offers solutions through data-driven forecasting models, topology-aware economic dispatch models, and efficient optional power flow calculations for large scale grids. Particularly, in chapter 2, a novel microgrid decomposition scheme is proposed to divide the large scale power grids into smaller microgrids. Here, a two-stage Nearest-Generator Girvan-Newman (NGGN) algorithm, a graphicalclustering-based approach, followed by a distributed economic dispatch model, is deployed to yield a 12.64% cost savings. In chapter 3, a deep-learning-based scheduling scheme is intended for the EVs in a household community that uses forecasted demand, consumer preferences and Time-of-use (TOU) pricing scheme to reduce electricity costs for the consumers and peak shaving for the utilities. In chapter 4, a hybrid machine learning model using GLM with other methods was designed to forecast wind generation data. Finally, in chapter 5, multiple formulations for Alternating Current Optimal Power Flow (ACOPF) were designed for large scale grids in a high-performance computing environment. The ACOPF formulations, namely, power balance polar, power balance Cartesian, and current balance Cartesian, are tested on bus systems ranging from a 9-bus to 25,000. The current balance Cartesian formulation had an average of 23% faster computational time than two other formulations on a 25,000 bus system

Where diversity comes from and why it matters?

In this essay, I describe some of the benefits of cognitive diversity in a complex world as well as the origins of that diversity. The essay has two main parts sandwiched between a brief description of what I mean by diversity and complexity, as well as a brief discussion of whether social systems produce sufficient diversity. In the first part, I describe models that provide insight into why we see the levels of diversity that we do. These models rest on social psychological foundations but borrow ideas from economics as well as population genetics. In the second part, I describe the functional benefits of diversity. I show how diverse predictive models can make a collection of people better able to make accurate predictions, how diverse perspectives and heuristics can enable groups of problem solvers to find innovative new solutions to problems, and how diverse behaviors and representations of the world can make a society more robust. Copyright © 2014 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107520/1/ejsp2016.pd

Cuban energy system development – Technological challenges and possibilities

This eBook is a unique scientific journey to the changing frontiers of energy transition in Cuba focusing on technological challenges of the Cuban energy transition. The focus of this milestone publication is on technological aspects of energy transition in Cuba. Green energy transition with renewable energy sources requires the ability to identify opportunities across industries and services and apply the right technologies and tools to achieve more sustainable energy production systems. The eBook is covering a large diversity of Caribbean country´s experiences of new green technological solutions and applications. It includes various technology assessments of energy systems and technological foresight analyses with a special focus on Cuba

Data Mining in Smart Grids

Effective smart grid operation requires rapid decisions in a data-rich, but information-limited, environment. In this context, grid sensor data-streaming cannot provide the system operators with the necessary information to act on in the time frames necessary to minimize the impact of the disturbances. Even if there are fast models that can convert the data into information, the smart grid operator must deal with the challenge of not having a full understanding of the context of the information, and, therefore, the information content cannot be used with any high degree of confidence. To address this issue, data mining has been recognized as the most promising enabling technology for improving decision-making processes, providing the right information at the right moment to the right decision-maker. This Special Issue is focused on emerging methodologies for data mining in smart grids. In this area, it addresses many relevant topics, ranging from methods for uncertainty management, to advanced dispatching. This Special Issue not only focuses on methodological breakthroughs and roadmaps in implementing the methodology, but also presents the much-needed sharing of the best practices. Topics include, but are not limited to, the following: Fuzziness in smart grids computing Emerging techniques for renewable energy forecasting Robust and proactive solution of optimal smart grids operation Fuzzy-based smart grids monitoring and control frameworks Granular computing for uncertainty management in smart grids Self-organizing and decentralized paradigms for information processin

Valuing adaptation under rapid change

AbstractThe methods used to plan adaptation to climate change have been heavily influenced by scientific narratives of gradual change and economic narratives of marginal adjustments to that change. An investigation of the theoretical aspects of how the climate changes suggests that scientific narratives of climate change are socially constructed, biasing scientific narratives to descriptions of gradual as opposed rapid, non-linear change. Evidence of widespread step changes in recent climate records and in model projections of future climate is being overlooked because of this. Step-wise climate change has the potential to produce rapid increases in extreme events that can cross institutional, geographical and sectoral domains.Likewise, orthodox economics is not well suited to the deep uncertainty faced under climate change, requiring a multi-faceted approach to adaptation. The presence of tangible and intangible values range across five adaptation clusters: goods; services; capital assets and infrastructure; social assets and infrastructure; and natural assets and infrastructure. Standard economic methods have difficulty in giving adequate weight to the different types of values across these clusters. They also do not account well for the inter-connectedness of impacts and subsequent responses between agents in the economy. As a result, many highly-valued aspects of human and environmental capital are being overlooked.Recent extreme events are already pressuring areas of public policy, and national strategies for emergency response and disaster risk reduction are being developed as a consequence. However, the potential for an escalation of total damage costs due to rapid change requires a coordinated approach at the institutional level, involving all levels of government, the private sector and civil society.One of the largest risks of maladaptation is the potential for un-owned risks, as risks propagate across domains and responsibility for their management is poorly allocated between public and private interests, and between the roles of the individual and civil society. Economic strategies developed by the disaster community for disaster response and risk reduction provide a base to work from, but many gaps remain.We have developed a framework for valuing adaptation that has the following aspects: the valuation of impacts thus estimating values at risk, the evaluation of different adaptation options and strategies based on cost, and the valuation of benefits expressed as a combination of the benefits of avoided damages and a range of institutional values such as equity, justice, sustainability and profit.The choice of economic methods and tools used to assess adaptation depends largely on the ability to constrain uncertainty around problems (predictive uncertainty) and solutions (outcome uncertainty). Orthodox methods can be used where both are constrained, portfolio methodologies where problems are constrained and robust methodologies where solutions are constrained. Where both are unconstrained, process-based methods utilising innovation methods and adaptive management are most suitable. All methods should involve stakeholders where possible.Innovative processes methods that enable transformation will be required in some circumstances, to allow institutions, sectors and communities to prepare for anticipated major change.Please cite this report as: Jones, RN, Young, CK, Handmer, J, Keating, A, Mekala, GD, Sheehan, P 2013 Valuing adaptation under rapid change, National Climate Change Adaptation Research Facility, Gold Coast, pp. 192.The methods used to plan adaptation to climate change have been heavily influenced by scientific narratives of gradual change and economic narratives of marginal adjustments to that change. An investigation of the theoretical aspects of how the climate changes suggests that scientific narratives of climate change are socially constructed, biasing scientific narratives to descriptions of gradual as opposed rapid, non-linear change. Evidence of widespread step changes in recent climate records and in model projections of future climate is being overlooked because of this. Step-wise climate change has the potential to produce rapid increases in extreme events that can cross institutional, geographical and sectoral domains.Likewise, orthodox economics is not well suited to the deep uncertainty faced under climate change, requiring a multi-faceted approach to adaptation. The presence of tangible and intangible values range across five adaptation clusters: goods; services; capital assets and infrastructure; social assets and infrastructure; and natural assets and infrastructure. Standard economic methods have difficulty in giving adequate weight to the different types of values across these clusters. They also do not account well for the inter-connectedness of impacts and subsequent responses between agents in the economy. As a result, many highly-valued aspects of human and environmental capital are being overlooked.Recent extreme events are already pressuring areas of public policy, and national strategies for emergency response and disaster risk reduction are being developed as a consequence. However, the potential for an escalation of total damage costs due to rapid change requires a coordinated approach at the institutional level, involving all levels of government, the private sector and civil society.One of the largest risks of maladaptation is the potential for un-owned risks, as risks propagate across domains and responsibility for their management is poorly allocated between public and private interests, and between the roles of the individual and civil society. Economic strategies developed by the disaster community for disaster response and risk reduction provide a base to work from, but many gaps remain.We have developed a framework for valuing adaptation that has the following aspects: the valuation of impacts thus estimating values at risk, the evaluation of different adaptation options and strategies based on cost, and the valuation of benefits expressed as a combination of the benefits of avoided damages and a range of institutional values such as equity, justice, sustainability and profit.The choice of economic methods and tools used to assess adaptation depends largely on the ability to constrain uncertainty around problems (predictive uncertainty) and solutions (outcome uncertainty). Orthodox methods can be used where both are constrained, portfolio methodologies where problems are constrained and robust methodologies where solutions are constrained. Where both are unconstrained, process-based methods utilising innovation methods and adaptive management are most suitable. All methods should involve stakeholders where possible.Innovative processes methods that enable transformation will be required in some circumstances, to allow institutions, sectors and communities to prepare for anticipated major change

Smart Energy Management for Smart Grids

This book is a contribution from the authors, to share solutions for a better and sustainable power grid. Renewable energy, smart grid security and smart energy management are the main topics discussed in this book