In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates.

Applications of fuzzy logic in renewable energy systems – A review

Technologies and decision support systems to aid solid-waste management: a systematic review.

Comprehensive evaluation and scenario simulation for the water resources carrying capacity in Xi'an city, China.

Developing framework for reducing purchasing risks associated with suppliers.Combination of grey system theory and uncertainty theory is used.It neither requires any probability distribution nor fuzzy membership function.It selects the most appropriate suppliers and allocates optimal purchase quantity. Supplier selection in supply chain is critical strategic decision for organization's success and has attracted much attention of both academic researchers and practitioners. Supplier selection problem consists of stochastic and recognitive uncertainties. However, the requirement of large sample size and strong subject knowledge to build suitable fuzzy membership function restrict the applicability of probability and fuzzy theories in supplier selection problem. In response, this study proposed a new tool for supplier selection. In this paper, we applied the combination of grey system theory and uncertainty theory which neither requires any probability distribution nor fuzzy membership function. The objective of this paper is to develop framework for reducing the purchasing risks associated with suppliers. The proposed supplier selection method not only selects the most appropriate supplier(s) but also allocate optimal purchase quantity under stochastic and recognitive uncertainties. An example is shown to highlight the procedure of the proposed model at the end of this paper.

Group multi-criteria supplier selection using combined grey systems theory and uncertainty theory

A system of systems approach to energy sustainability assessment: Are all renewables really green?

Identification of optimal strategies for improving eco-resilience to floods in ecologically vulnerable regions of a wetland

In this study, a large-scale integrated modeling system (IMS) was developed for supporting climate-change impact analysis and adaptation planning under multi-level uncertainties. A number of methodologies were seamlessly incorporated within IMS, including fuzzy-interval inference method (FIIM), inexact energy model (IEM), and uncertainty analysis. The system could (i) encompass multiple technologies, energy resources, and sub-sectors, and climate change impact analysis into a general modeling framework, (ii) address interactions of climate change impacts on multiple energy sub-sectors and resources within an EMS, (iii) identify optimal adaptation strategies of an EMS to climate change impact through a two-step procedure, (iv) deal with multiple levels of uncertain information associated with processes of climate change impact analysis and adaptation planning, and (v) seamlessly combine climate change impact analysis results with inexact adaptation planning. It could provide decision makers a comprehensive view on the EMS as well as the corresponding adaptation schemes under climate change, greatly improving the robustness and completeness of the decision-making processes. The generated solutions can provide desired energy resource/service allocation with a minimized system cost, a maximized system reliability and a maximized energy security under varied climate change impact levels, as well as multiple levels of uncertainties. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the Province of Manitoba, Canada.

An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part II. Case study

Waste management with recourse: an inexact dynamic programming model containing fuzzy boundary intervals in objectives and constraints.

This paper presents the development and the first application of an inexact quadratic programming (IQP) approach for sustainable water supply under multiple uncertainties. The developed IQP improves conventional nonlinear programming by tackling multiple uncertainties within an individual parameter; IQP is also superior to existing inexact methods due to its reflection of economies of scale and reduction of computational requirements. An interactive solution algorithm with high computational efficiency was also proposed. The application of IQP to long-term planning of a multi-source multi-sector water supply system demonstrated its applicability. The close reflection of system complexities, such as multiple uncertainties, scale economies and dynamic parameters, could enhance the robustness of the optimization process as well as the acceptability of obtained results. Corresponding to varied system conditions and decision priorities, the interval solutions from IQP could help generate a series of long-term water supply strategies under a number of economic, environmental, ecological, and water-security targets.

Q. Tan

Papers

Identification of optimal strategies for improving eco-resilience to floods in ecologically vulnerable regions of a wetland

An integrated approach for climate-change impact analysis and adaptation planning under multi-level uncertainties. Part II. Case study

Waste management with recourse: an inexact dynamic programming model containing fuzzy boundary intervals in objectives and constraints.

An inexact programming approach for supporting ecologically sustainable water supply with the consideration of uncertain water demand by ecosystems