Energy management problems associated with rapid institutional, political, technical, ecological, social and economic development have been of critical concern to both national and local governments worldwide for many decades; thus, addressing such issues is a global priority.

This handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions. Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.

Fuzzy logic has vast applications in power and electrical engineering. This collection is the first book to cover research advancements in the application of fuzzy logic in the planning and operation of smart grids. A global group of researchers and scholars present innovative approaches to fuzzy-based smart grid planning and operation, cover theoretical concepts and experimental results of the application of fuzzy-based techniques, and define and apply these techniques to deal with smart grid issues. Applications of Fuzzy Logic in Planning and Operation of Smart Grids is an ideal resource for researchers on the theory and application of fuzzy logic, practicing engineers working in electrical power engineering and power system planning, and post-graduates and students in advanced graduate-level courses.

Sustainable Procurement is an emerging concept in supply chain and operations management. Manufacturing industries have made improvements in moving from cost-based to quality-based, and customer-focused supply chain management strategies. This is becoming an integrated component in the supply chain system, with players becoming aware of the regulations and needs of the customer. It is imperative for production firms to look at the procurement activity as one of the strategic enablers for sustaining the business in the competitive global environment. This book will provide industries with an understanding of the concepts related to sustainable procurement policies and its implementation. Provides decision and theory development models in sustainable procurement supply chains Includes contributions in all three major analytics: descriptive, predictive, and perspectives in the context of sustainable procurement supply chain Discusses new business models with suppliers and opportunities for co-branding Covers how to develop new tools to measure and allocate the gains from sustainable practices among stakeholders Analyses the science of translating data into meaningful and actionable insights

This book presents various multi-criteria analysis methods for sustainability-oriented analysis and decision-making for energy systems, under various different conditions and scenarios. It presents methodologies to answer the questions relating to which of the options are the most sustainable among the alternatives, and how multi-criteria decision analysis methods can be used to select the most sustainable energy systems. A systematic innovative methodological framework is presented, which enables the most appropriate energy system to be selected under different conditions including: Scientific decision support tools for sustainable energy system selection; Fuzzy, grey, and rough sets based multi-criteria decision analysis; Decision-making models under uncertainties; and The combination of life cycle thinking and multi-criteria decision analysis This book is of interest to researchers, engineers, decision makers, and postgraduate students within the field of energy systems, sustainability, and multi-criteria decision analysis.

With immense consumption of resources, increased global warming, and environmental pollution, the energy sector has inevitably embraced sustainability. Countries are releasing plans and programs to shift their fossil fuel-dependent energy sectors into clean energy sectors, and projections show that renewable energy will be a significant part of nations’ energy mixes in the near future. Optimization and decision-making techniques have been commonly used in the energy sector as problems encountered in this sector are complex and therefore need comprehensive techniques to solve them. With the uncertainty and high-cost issues of renewable resources, the complexity increases in the sector and requires optimization and decision-making techniques. Optimization and Decision-Making in the Renewable Energy Industry analyzes renewable energy sources using current mathematical methods and techniques and provides advanced knowledge on key opportunities and challenges. The book discusses current and trending mathematical methods, tests their validity and verification, and considers their practical application in the field. Covering topics such as urban sustainability and renewable energy systems, this reference work is ideal for practitioners, academicians, industry professionals, researchers, scholars, instructors, and students.

Rapid increases in energy demand and international drive to reduce carbon emissions from fossil fuels have led many oil-rich countries to diversify their energy portfolio and resources. Libya is one of these countries, and it has recently become interested in utilizing its renewable-energy resources in order to reduce financial and energy dependency on oil reserves. This paper introduces an original multicriteria decision-making Pairwise-CODAS model in which the modification of the CODAS method was made using Linguistic Neutrosophic Numbers (LNN).