Day-ahead and Intraday Dispatch of an Integrated Biomass-Concentrated Solar System: A Multi-Objective Risk-Controlling Approach

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Offtake Strategy Design for Wind Energy Projects under Uncertainty

Energy use from wind, solar, and other renewable sources is a public policy at the federal and state levels to address environment, energy, and sustainability concerns. As the cost of renewable energy is still relatively high compared to fossil fuels, it remains a critical challenge to make renewable energy cost competitive, without relying on public subsidies. During recent years, much advance has been made in our understanding of technology innovations and cost structure optimization of renewable energy. A knowledge gap exists on the other side of the equation - revenue generation. Considering the complexity and stochastic nature of renewable energy projects, there is great potential to optimize the revenue generation mechanisms in a systematic fashion for improved profitability and growth. This dissertation examines two primary revenue generation mechanisms, or offtake strategies, used in wind energy development projects in the U.S. While a short-term offtake strategy allows project developers to benefit from price volatility in the wholesale spot market for profit maximization, a long-term offtake strategy minimizes the market risk exposure through a long-term Power Purchase Agreement (PPA). With Conditional Value-at-Risk (CVaR) introduced as a risk measure, this dissertation first develops two stochastic programming models for optimizing offtake designs under short and long-term strategies respectively. Furthermore, this study also proposes a hybrid offtake strategy that combines both short and long-term strategies. The two-level stochastic model demonstrates the merit of the hybrid strategy, i.e. obtaining the maximized profit while maintaining the flexibility of balancing and hedging against market and resource risks efficiently. The Cape Wind project in Massachusetts has been used as an example to demonstrate the model validity and potential applications in optimizing its revenue streams. The analysis shows valuable implications on the optimal design of renewable energy project development in regard to offtake arrangements

A review of co-optimization approaches for operational and planning problems in the energy sector

This paper contributes to a comprehensive perspective on the application of co-optimization in the energy sector – tracking the frontiers and trends in the field and identifying possible research gaps – based on a systematic literature review of 211 related studies. The use of co-optimization is addressed from a variety of perspectives by splitting the studies into ten key categories. Research has consistently shown that co-optimization approaches can be technically challenging and it is usually a data-intensive procedure. Overall, a set of techniques such as relaxation, decomposition and linear approaches have been proposed for reducing the inherent nonlinear model's complexities. The need to coordinate the necessary data from multiples actors might increase the complexity of the problem since security and confidentiality issues would also be put on the table. The evidence from our review seems to suggest a pertinent role for addressing real-case systems in future models instead of using theoretical test cases as considered by most studies. The identified challenges for future co-optimization models include (i) dealing with the treatment of uncertainties and (ii) take into account the trade-offs among modelling fidelity, spatial granularity and geographical coverage. Although there is also a growing body of literature that recognizes the importance of co-optimization focused on integrating supply and demand-side options, there has been little work in the development of co-optimization models for long-term decision-making, intending to recognize the impact of short-term variability of both demand and RES supply and well suited to systems with a high share of RES and under different demand flexibility conditions. The research results represent a further step towards the importance of developing more comprehensive approaches for integrating short-term constraints in future co-optimized planning models. The findings provide a solid evidence base for the multi-dimensionality of the co-optimization problems and contriThis work is supported by the National Council for Scientific and Technological Development (CNPq), Brazil. This work has been supported by FCT – Fundaça˜o para a Ciˆencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Sustainable Assessment in Supply Chain and Infrastructure Management

In the competitive business environment or public domain, the sustainability assessment in supply chain and infrastructure management are important for any organization. Organizations are currently striving to improve their sustainable strategies through preparedness, response, and recovery because of increasing competitiveness, community, and regulatory pressure. Thus, it is necessary to develop a meaningful and more focused understanding of sustainability in supply chain management and infrastructure management practices. In the context of a supply chain, sustainability implies that companies identify, assess, and manage impacts and risks in all the echelons of the supply chain, considering downstream and upstream activities. Similarly, the sustainable infrastructure management indicates the ability of infrastructure to meet the requirements of the present without sacrificing the ability of future generations to address their needs. The complexities regarding sustainable supply chain and infrastructure management have driven managers and professionals to seek different solutions. This Special Issue aims to provide readers with the most recent research results on the aforementioned subjects. In addition, it offers some solutions and also raises some questions for further research and development toward sustainable supply chain and infrastructure management

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes