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As global energy demand continues to grow, the demand for renewable energy continues to rise. To meet this demand, many countries have begun to actively promote the development of offshore wind power projects. Since siting is the key to the success of offshore wind power projects, this paper aims to develop a mixed decision-making framework to address the siting of offshore wind power station (OWPS). Firstly, establish a relatively comprehensive OWPS evaluation attribute system. Secondly, the pythagorean hesitation fuzzy set (PHFS) was used to describe the evaluation information in the OWPS site selection process. It can ensure the hesitancy and fuzziness of evaluation information, and is not constrained by the sum of membership and non membership being less than 1. Thirdly, the improved SWARA method is used to calculate the weight of attributes. Finally, an extended MULTIMOORA (Multi-Objective Optimization on the basis of a Ratio Analysis plus the Full Multiplicative form) method is proposed to rank the siting alternatives for OWPS. The proposed method is applied to the study of OWPS site selection in Shandong Province, China. Through calculation, the comprehensive ranking values are G 1 = 14, G 2 = 7, G 3 = 4, G 4 = 8 and G 5 = 13. Therefore, A 3 is the best alternative. Through sensitivity analysis and comparative analysis, it was verified that the proposed model has good reliability and stability. • A new multi-attribute decision-making model is proposed. • The attribute system for site selection evaluation of OWPS is established. • Expression of evaluation information by pythagorean hesitation fuzzy set. • Pythagorean hesitation fuzzy set and SWARA are combined to calculate attribute weight. • An improved MULTIMOORA method is proposed. [ABSTRACT FROM AUTHOR]

Abstract: China has set ambitious goals to increase the use of renewable energy. Developing renewables in rural areas is also one of the most important energy strategies. This paper examines rural social acceptance of renewable energy deployment taking Shandong as a case study via a field questionnaire survey. Theory of planned behavior is adopted to establish an analytical framework, and a logit model is used to examine possible determinants of local social acceptance. The results show that rural residents are generally supportive renewable energy development given its positive impacts on environment. A stated willingness to pay more for renewable electricity is taken as a variable representing an individual’s behavioral intention. The probability of occurrence of positive intention is found to increase with household income, individual knowledge level and belief about costs of renewable energy use but decrease with individual age. Residents with higher level of income are more likely to be willing to pay more for green electricity, so are the younger people. Enhancive knowledge and understanding about renewable energy (for instance, the cost) would be conducive to win public acceptance of renewable energy deployment. [Copyright &y& Elsevier]