Description : Everyone makes decisions, but not everyone is a decision analyst. A decision analyst uses quantitative models and computational methods to formulate decision algorithms, assess decision performance, identify and evaluate options, determine trade-offs and risks, evaluate strategies for investigation, and so on. Info-Gap Decision Theory is written for decision analysts. The term "decision analyst" covers an extremely broad range of practitioners. Virtually all engineers involved in design (of buildings, machines, processes, etc.) or analysis (of safety, reliability, feasibility, etc.) are decision analysts, usually without calling themselves by this name. In addition to engineers, decision analysts work in planning offices for public agencies, in project management consultancies, they are engaged in manufacturing process planning and control, in financial planning and economic analysis, in decision support for medical or technological diagnosis, and so on and on. Decision analysts provide quantitative support for the decision-making process in all areas where systematic decisions are made. This second edition entails changes of several sorts. First, info-gap theory has found application in several new areas - especially biological conservation, economic policy formulation, preparedness against terrorism, and medical decision-making. Pertinent new examples have been included. Second, the combination of info-gap analysis with probabilistic decision algorithms has found wide application. Consequently "hybrid" models of uncertainty, which were treated exclusively in a separate chapter in the previous edition, now appear throughout the book as well as in a separate chapter. Finally, info-gap explanations of robust-satisficing behavior, and especially the Ellsberg and Allais "paradoxes", are discussed in a new chapter together with a theorem indicating when robust-satisficing will have greater probability of success than direct optimizing with uncertain models. New theory developed systematically Many examples from diverse disciplines Realistic representation of severe uncertainty Multi-faceted approach to risk Quantitative model-based decision theory
Description : Highlights: Risk-constrained scheduling of the apartment smart building (ASB) is considered. IGDT is proposed for risk-constrained energy management of apartment smart building. Robust scheduling of ASB is obtained from robustness function of IGDT. Opportunistic scheduling of ASB is obtained from opportunity function of IGDT. Solar thermal storage is used to reduce operation cost of apartment smart building. Abstract: In domestic sector, robust scheduling of energy usage under various uncertainties is an important factor for any smart home energy management systems (EMS). In this paper, information gap decision theory (IGDT) is proposed for robust scheduling of apartment smart building (ASB) in the presence of price uncertainty and solar thermal storage system (STS). The proposed sample ASB contains combined heat and power (CHP) generator, boiler, battery storage system (BSS), STS system and smart appliances. IGDT approach doesn't depend on the size of the model. So, the EMS of ASB which is known as small scale loads can use IGDT to make more informed decisions against the price uncertainty. IGDT contains two functions namely robustness and opportunity functions. Risk-averse perspective of optimal scheduling of ASB is modeled by robustness function and opportunity function is used to model risk-taker perspective of optimal scheduling of ASB. Also, to assess the effect of STS system on proposed problem, two case studies are studied, and significant results were obtained, which indicate the validity of proposed model.
Description : Abstract: This paper proposes a novel approach for long-term planning of wind energy considering its inherent uncertainty. The uncertainty of wind energy is handled via information gap decision theory (IGDT) method. Additionally, due to the importance of security considerations, loading margin is employed as an index of voltage stability to guarantee the security of power system. The operational constraints (such as power flow equations) in initial operation point considered along with those at the voltage collapse point, simultaneously. Accordingly, the IGDT-based voltage stability constrained wind energy-planning model is proposed that can be used for ensuring the safe operation of power networks. The main feature of this model is to handle the uncertainty of wind energy in the long-term wind energy planning via IGDT technique, by considering voltage stability constraints. In order to evaluate the capability of the IGDT technique for uncertainty handling of wind energy, the obtained results are compared with Monte Carlo simulations. To demonstrate the effectiveness of proposed model, it is applied to the New-England 39-bus test system. The obtained results validated the applicability of the proposed model for optimal wind energy planning. The proposed methodology could help wind farm investors to make optimal large-scale wind energy investment decisions. Highlights: A long-term horizon considered for wind energy planning. Wind energy planning investigated from perspective of wind farm investors. The uncertainty of wind energy is handled via information gap decision theory method. Voltage stability constraints considered in a risk averse strategy. Loading margin is employed as an index of voltage stability.
Description : This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.
Description : Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 42. Chapters: Median, Outlier, Info-gap decision theory, M-estimator, Robust regression, Least absolute deviations, RANSAC, Non-parametric statistics, Median absolute deviation, Hodges-Lehmann estimator, Robust measures of scale, Dixon's Q test, Huber loss function, Robust confidence intervals, Redescending M-estimator, Least trimmed squares, Winsorising, Trimean, Winsorized mean, L-estimator. Excerpt: Info-gap decision theory is a non-probabilistic decision theory that seeks to optimize robustness to failure - or opportuneness for windfall - under severe uncertainty, in particular applying sensitivity analysis of the stability radius type to perturbations in the value of a given estimate of the parameter of interest. It has some connections with Wald's maximin model; some authors distinguish them, others consider them instances of the same principle. It has been developed since the 1980s by Yakov Ben-Haim, and has found many applications and described as a theory for decision-making under "severe uncertainty." It has been criticized as unsuited for this purpose, and alternatives proposed, including such classical approaches as robust optimization. Info-gap is a decision theory: it seeks to assist in decision-making under uncertainty. It does this by using 3 models, each of which builds on the last. One begins with a model for the situation, where some parameter or parameters are unknown. One then takes an estimate for the parameter, which is assumed to be substantially wrong, and one analyzes how sensitive the outcomes under the model are to the error in this estimate. Uncertainty modelStarting from the estimate, an uncertainty model measures how distant other values of the parameter are from the estimate: as uncertainty increases, the set of possible values increase - if one is this uncertain in the estimate, what other paramet...
Description : This book is a product of applying info-gap decision theory to policy formulation and evaluation in monetary economics and related domains. Info-gap theory has been applied to planning and decision problems in many areas, including engineering, biological conservation, project management, economics, medicine, homeland security, and more.
Description : This book identifies the challenges faced by large electricity consumers when they use several sources to procure their energy. The huge penetration of distributed energy resources and the intermittent nature of renewables can put the operations of the large electricity consumer at risk. The book discusses the different types of energy sources including the pool market, bilateral contracts, electrical vehicles, energy storage systems, and demand response programs in detail and presents solutions for robust and risk based scheduling. The author provides models for determining and considering uncertainties and optimal bidding strategies. The book is useful to engineers and students involved in the integration of various energy types as well as those working in state and federal governmental organizations who regulate different aspects of electricity market operation and planning. Presents solutions for robust and risk based scheduling; Discusses the operation and planning of energy storage systems; Presents the most-up-to-date technological approaches to energy integration.
Description : This book presents the outcomes of a workshop around the emerging area of the economics of plant health. The workshop was organized in Wageningen in July 2005 under the auspices of Frontis – Wageningen International Nucleus for Strategic Expertise. Plant health nowadays plays an increasing role in national and international policy making. This explains the interest of the Netherlands Ministry of Agriculture, Nature and Food Quality in this workshop. The increasing importance of plant health in international policy making also follows from the recent establishment of a scientific panel on plant health by the European Food Safety Authority. This panel has to advise the EU on policy issues in the area of plant health. Plant health issues have numerous economic dimensions. Measures to control quarantine diseases and invasive species are usually costly, whereas the potential benefits, e. g. , avoided losses, are often difficult to quantify. Quantifying the costs and benefits requires close collaboration between economists and epidemiologists. New GIS tools can play an important role in visualizing and modelling the combined economic and epidemiological consequences of control measures. Quarantine organisms and invasive species also frequently have impacts that go beyond agriculture. Impacts on landscapes and the environment call for the application of new approaches to measuring the economic impacts on society. This book presents a number of new approaches to economic modelling of plant health; it is primarily intended for policy makers and scientists working in the area of plant health.
Description : This book highlights the cutting-edge research on energy management within smart grids with significant deployment of Plug-in Electric Vehicles (PEV). These vehicles not only can be a significant electrical power consumer during Grid to Vehicle (G2V) charging mode, they can also be smartly utilized as a controlled source of electrical power when they are used in Vehicle to Grid (V2G) operating mode. Electricity Price, Time of Use Tariffs, Quality of Service, Social Welfare as well as electrical parameters of the network are all different criteria considered by the researchers when developing energy management techniques for PEVs. Risk averse stochastic energy hub management, maximizing profits in ancillary service markets, power market bidding strategies for fleets of PEVs, energy management of PEVs in the presence of renewable energy in distribution lines or microgrids and loss minimization in distribution networks based on smart coordination approaches using real time energy prices are some of the attractive and novel topics explored in this book. It will be an excellent reference for graduate students, researchers and industry professionals who are interested in getting a snapshot view of today’s latest research on applying various smart energy management strategies for smart grids with high penetration of PEVs.
Description : Uncertainties play a dominant role in the design and optimization of structures and infrastructures. In optimum design of structural systems due to variations of the material, manufacturing variations, variations of the external loads and modelling uncertainty, the parameters of a structure, a structural system and its environment are not given, fixed coefficients, but random variables with a certain probability distribution. The increasing necessity to solve complex problems in Structural Optimization, Structural Reliability and Probabilistic Mechanics, requires the development of new ideas, innovative methods and numerical tools for providing accurate numerical solutions in affordable computing times. This book presents the latest findings on structural optimization considering uncertainties. It contains selected contributions dealing with the use of probabilistic methods for the optimal design of different types of structures and various considerations of uncertainties. The first part is focused on reliability-based design optimization and the second part on robust design optimization. Comprising twenty-one, self-contained chapters by prominent authors in the field, it forms a complete collection of state-of-the-art theoretical advances and applications in the fields of structural optimization, structural reliability, and probabilistic computational mechanics. It is recommended to researchers, engineers, and students in civil, mechanical, naval and aerospace engineering and to professionals working on complicated costs-effective design problems.