Abstract
In response to challenges from the COVID-19 pandemic and climate change to achieve the goal of ensuring sustainable economic growth, offshore wind power development not only provides a clean and sustainable source of energy but also provides opportunities for economic growth and job creation. Offshore wind energy projects have been promptly suggested in Vietnam due to policy advancement, with the country's excellent wind resources. The success of an offshore wind energy project is decided mainly by choosing the best location for offshore wind power station (OWPS) construction, which is a complex multicriteria decision-making (MCDM) problem with the coexistence of conflicting factors. There is a problem with incomplete decision information use and information loss during the decision-making process, and it is easy to overlook the interaction difficulty in a fuzzy environment. To address the complex nature of the prioritization problem posed, this study proposes a hybrid MCDM framework combining the spherical fuzzy analytical hierarchy process (SF-AHP) and weighted aggregated sum product assessment (WASPAS). SF-AHP is used in the first stage to determine the significance levels of OWPS evaluation criteria. WASPAS is then utilized to rank locations of OWPS. A comprehensive set of evaluation criteria developed based on the concept of sustainable development has been recognized by reviewing the literature review and interviewing experts to practice the two-stage MCDM model. A real case study for Vietnam is conducted to test the effectiveness of the proposed method. The best location schemes have been determined by using the decision framework. The results of the sensitivity analysis and a comparison analysis demonstrate that the decision framework is practical and robust. The proposed methodology can be used to attain a decision-making process at the regional level for offshore wind farm planning and coastal development, and the study results encourage the establishment of renewable energy development policies.
Highlights
Among various renewable energy sources, offshore wind is key to the transition to a zero-carbon energy supply in the context of the whole world facing the global fight against climate change and promoting a post-COVID-19 green recovery
A panel of 15 experts with at least ten years of professional experience in energy-related fields was invited to determine potential alternatives and essential criteria for the evaluation to increase the objectivity of the results as much as possible
This paper deployed the spherical fuzzy analytical hierarchy process (SF-analytic hierarchy process (AHP)) weights to combine with the weighted aggregated sum product assessment (WASPAS) model for ranking the potential wind plants, which are Ba Ria—Vung Tau (OWPS-01), Ben Tre (OWPS-02), Binh Dinh (OWPS-03), Binh Thuan (OWPS-04), Ca Mau (OWPS-05), Ninh Thuan (OWPS06), and Soc Trang (OWPS-07)
Summary
Among various renewable energy sources, offshore wind is key to the transition to a zero-carbon energy supply in the context of the whole world facing the global fight against climate change and promoting a post-COVID-19 green recovery. Site selection for an offshore wind power station (OWPS) constitutes a critical phase toward a wind power project It is a multicriteria decision-making (MCDM) problem regarding many conflicting criteria, including wind resources, construction, environmental impacts, marine spatial planning, power grid access lines, economy, and society[10]. Garg and K umar[13] developed the TOPSIS method based on novel exponential distance measures with set pair analysis theory for the intervalvalued intuitionistic fuzzy set to cope with real-world problems Among these methods, WASPAS is a relatively novel and straightforward MCDM method that has been broadly applied in several practical problems[14–17]. This paper aims to develop an MCDM-based framework for the best site selection of OWPSs. the spherical fuzzy sets and analytical hierarchy process (SF-AHP) are integrated into the first stage to determine the significance levels of OWPS evaluation criteria, and the weighted aggregated sum product assessment (WASPAS) is utilized to rank locations of OWPS. A real case study for Vietnam is carried out to validate the proposed method
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