• Energy Research

Offshore wind energy takes up an important place in Ireland’s renewable generation portfolio thanks to its abundant offshore wind resource. Optimal offshore site selection and developing site-specific energy policy instruments are of key importance to the success of offshore wind energy investments. In this respect, this study aims at developing a multi-criteria decision-making (MCDM) model considering technical, economic, environmental and social criteria to assess Ireland’s most promising offshore wind sites in terms of their sustainable development. An interval type-2 fuzzy sets based MCDM model is developed that integrates the score function with positive and negative solutions to achieve better results. Moreover, advanced energy economic metrics such as levelized cost of electricity with higher resolution are integrated into the decision-making process to make more precise decisions. Case studies are conducted for the five of the offshore sites in development pipeline. Results are compared to those of other state-of-the-art MCDM methods. It is found that Arklow Bank-2 is the most favorable site while Sceirde is the least site. The ranking of other sites is found to be Oriel>Dublin Array>Codling Park. It is shown that the proposed approach is superior in terms of stability and implementation as compared to its counterparts.

Les défis techniques, logistiques et écologiques associés au développement de l'éolien offshore nécessitent une analyse approfondie de la sélection des sites. Les paramètres techniques tels que les ressources éoliennes, les préoccupations logistiques telles que la distance à la côte et les considérations écologiques telles que les pêches doivent tous être évalués et pondérés, dans de nombreux cas avec des données incomplètes ou incertaines. Prendre une décision aussi critique avec de graves conséquences économiques et écologiques potentielles nécessite une approche décisionnelle solide pour guider en fin de compte le processus de sélection du site. Cet article propose un modèle de prise de décision multicritère (MCDM) à base floue de numéro neutrosophique de type 2 (T2NN) pour la sélection de sites de parcs éoliens offshore (OWF). Cette approche combine les avantages des ensembles de nombres neutrosophiques, qui peuvent utiliser des informations incertaines et incomplètes, avec une comparaison multi-attributive de la zone d'approximation des frontières qui offre une flexibilité de formulation et un calcul facile. En outre, cette étude développe et intègre un modèle techno-économique pour les OWF dans la prise de décision. Une étude de cas est réalisée pour évaluer et classer cinq sites OWF proposés au large des côtes du New Jersey. Pour valider le modèle proposé, une comparaison avec trois modèles T2NN alternatifs à base floue est effectuée. Il est démontré que le modèle mis en œuvre donne le même ordre de classement que les approches alternatives. L'analyse de sensibilité révèle que la modification des pondérations des critères n'affecte pas l'ordre de classement. Los desafíos técnicos, logísticos y ecológicos asociados con el desarrollo eólico marino requieren un extenso análisis de selección de sitios. Los parámetros técnicos, como los recursos eólicos, las preocupaciones logísticas, como la distancia a la costa, y las consideraciones ecológicas, como las pesquerías, deben evaluarse y ponderarse, en muchos casos con datos incompletos o inciertos. Tomar una decisión tan crítica con graves consecuencias económicas y ecológicas potenciales requiere un fuerte enfoque de toma de decisiones para guiar en última instancia el proceso de selección del sitio. Este documento propone un modelo de toma de decisiones multicriterio (MCDM) de base difusa de número neutrosófico tipo 2 (T2NN) para la selección de sitios de parques eólicos marinos (OWF). Este enfoque combina las ventajas de los conjuntos de números neutrosóficos, que pueden utilizar información incierta e incompleta, con una comparación de área de aproximación de frontera multiatributiva que proporciona flexibilidad de formulación y cálculo fácil. Además, este estudio desarrolla e integra un modelo tecnoeconómico para los OWF en la toma de decisiones. Se realiza un estudio de caso para evaluar y clasificar cinco sitios propuestos de OWF frente a la costa de Nueva Jersey. Para validar el modelo propuesto, se realiza una comparación con tres modelos alternativos basados en T2NN fuzzy. Se demuestra que el modelo implementado produce el mismo orden de clasificación que los enfoques alternativos. El análisis de sensibilidad revela que cambiar las ponderaciones de los criterios no afecta el orden de clasificación. The technical, logistical, and ecological challenges associated with offshore wind development necessitate an extensive site selection analysis. Technical parameters such as wind resource, logistical concerns such as distance to shore, and ecological considerations such as fisheries all must be evaluated and weighted, in many cases with incomplete or uncertain data. Making such a critical decision with severe potential economic and ecologic consequences requires a strong decision-making approach to ultimately guide the site selection process. This paper proposes a type-2 neutrosophic number (T2NN) fuzzy based multi-criteria decision-making (MCDM) model for offshore wind farm (OWF) site selection. This approach combines the advantages of neutrosophic numbers sets, which can utilize uncertain and incomplete information, with a multi-attributive border approximation area comparison that provides formulation flexibility and easy calculation. Further, this study develops and integrates a techno-economic model for OWFs in the decision-making. A case study is performed to evaluate and rank five proposed OWF sites off the coast of New Jersey. To validate the proposed model, a comparison against three alternative T2NN fuzzy based models is performed. It is demonstrated that the implemented model yields the same ranking order as the alternative approaches. Sensitivity analysis reveals that changing criteria weightings does not affect the ranking order. تتطلب التحديات التقنية واللوجستية والبيئية المرتبطة بتطوير الرياح البحرية إجراء تحليل شامل لاختيار الموقع. يجب تقييم وترجيح المعايير الفنية مثل موارد الرياح والمخاوف اللوجستية مثل المسافة إلى الشاطئ والاعتبارات البيئية مثل مصايد الأسماك، وفي كثير من الحالات مع بيانات غير كاملة أو غير مؤكدة. يتطلب اتخاذ مثل هذا القرار الحاسم مع عواقب اقتصادية وبيئية محتملة شديدة اتباع نهج قوي في صنع القرار لتوجيه عملية اختيار الموقع في نهاية المطاف. تقترح هذه الورقة نموذج صنع القرار متعدد المعايير (MCDM) المبني على عدد نيوتروسوفيك من النوع 2 (T2NN) لاختيار موقع مزرعة الرياح البحرية (OWF). يجمع هذا النهج بين مزايا مجموعات الأرقام النيوتروسوفية، والتي يمكن أن تستخدم معلومات غير مؤكدة وغير كاملة، مع مقارنة منطقة تقريبية متعددة الحدود توفر مرونة في الصياغة وسهولة الحساب. علاوة على ذلك، تطور هذه الدراسة وتدمج نموذجًا تقنيًا واقتصاديًا لصناديق العمل في عملية صنع القرار. يتم إجراء دراسة حالة لتقييم وترتيب خمسة مواقع مقترحة خارج سواحل نيو جيرسي. للتحقق من صحة النموذج المقترح، يتم إجراء مقارنة مع ثلاثة نماذج بديلة مبنية على T2NN غامضة. ثبت أن النموذج المنفذ يعطي نفس ترتيب الترتيب مثل النهج البديلة. يكشف تحليل الحساسية أن تغيير أوزان المعايير لا يؤثر على ترتيب الترتيب.

The recent drastic natural degradation and climate change urge the authorities to transform their traditional policies to take climate action in urban mobility planning. However, the interests of the stakeholders may differ so that the development and the implementation of the required action become challenging. In this study, we trace how an optimal action plan should take the societal dynamics into account and how the taken actions can reshape the societal dynamics. To illustrate and analyze the complex forces that drive the decision-making process in urban mobility planning, we develop a case scenario in which bunches three small-scale urban mobility planning alternatives that are highly proposed in the literature and practiced in cities. Alternatives are assessed under twelve criteria reflecting economic, environmental, technical, and political dimensions of the decision problem. In solving the problem, we propose an improvement of the Weighted Aggregated Sum Product Assessment (WASPAS) approach by applying Einstein norms in a fuzzy environment over triangular fuzzy numbers to evaluate and rank the prioritization of climate change mitigation strategies. The proposed method comprises two stages. In the first stage, the weight coefficients of the criteria are calculated. In the second stage, the fuzzy Einstein WASPAS approach is applied to select the most suitable alternative among the three alternatives. Testing and validation of the model are done through a comparison with existing decision making methods in the literature. The results show that the best plan should be inclusive and equitable as well as economically efficient. Although the economic dimension is highly important in the decision-making process. Choosing the most suitable urban mobility planning option requires the consideration of other societal dynamics, too.

Using electricity to fuel buses has always been known as a green option for the public bus operations considering the recent regulations on environmental and climate concerns. Emission-free public transportation modes such as electric buses improve local air quality and reduce noise pollution and also contribute to achieving sustainability goals by developing a sustainable transportation system. Many projects have been carried out using different charging strategies for electric buses around the world. However, selecting the most appropriate charging strategy for the electric buses in the public transportation is a challenging and multidimensional decision-making problem for transportation management sector. Therefore, this article proposes a decision support model based on the interval-valued neutrosophic set which uses Shannon's entropy and mixed aggregation by comprehensive normalization technique to choose the most appropriate charging type for urban electric buses among alternatives such as opportunity, depot, inductive, and no shift. This article presents a real-life case study in Turkey to illustrate the applicability and advantages of the proposed model. Extensive sensitivity analysis and comparative analysis tests are conducted to show the robustness of the proposed methodology. The results show that depot charging is the most suitable charging strategy for Istanbul's bus operator system.

Alors que les températures médianes mondiales continuent d'augmenter, la demande de systèmes de refroidissement actifs (CA) augmente. Ces systèmes sont particulièrement répandus dans les pays développés pour maintenir le confort par temps chaud. Diverses technologies de climatisation sont disponibles, et l'évaluation de leurs performances dans des paramètres multi-perspectives est nécessaire pour déterminer la meilleure option pour l'utilisation prévue. Cela nécessite une plateforme d'évaluation pour l'évaluation. Cet article présente un nouveau modèle de prise de décision multicritères (MCDM) basé sur une nouvelle comparaison linguistique intégrée de la zone d'approximation de la frontière multi-attributive floue de Pythagore à 2 tuple (2 TLP-FWZIC) et modifiée de la zone d'approximation de la frontière floue de Pythagore à 2 tuple (2TLPF-MABAC). Le premier est utilisé pour déterminer l'importance des critères d'évaluation, tandis que le second est utilisé pour sélectionner les climatiseurs optimaux à l'aide des pondérations obtenues. Les résultats de la pondération de premier niveau révèlent que les critères de performance ont été principalement privilégiés pour l'évaluation, la « performance énergétique » acquérant le poids le plus significatif (0,2487) parmi tous les critères de performance. En termes de résultats de sélection des climatiseurs, parmi les 20 systèmes testés et évalués, les « climatiseurs à base d'électricité de forage géothermique » ont obtenu la valeur de score la plus élevée (0,1296), tandis que les « climatiseurs à base d'électricité emballés dans des fenêtres » ont obtenu le score le plus bas (-0,0515). La robustesse des résultats a été confirmée par une analyse de sensibilité. A medida que las temperaturas medias globales continúan aumentando, la demanda de sistemas de refrigeración activos (AC) está aumentando. Estos sistemas son particularmente frecuentes en los países desarrollados para mantener la comodidad durante el clima cálido. Hay varias tecnologías de ACs disponibles, y es necesario evaluar su rendimiento en entornos de múltiples perspectivas para determinar la mejor opción para el uso previsto. Esto requiere una plataforma de evaluación para la evaluación. Este documento presenta un novedoso modelo de toma de decisiones multicriterio (MCDM) basado en una nueva comparación lingüística integrada de área de aproximación de frontera multiatributiva difusa pitagórica de 2 tuplas (2 TLP-FWZIC) y de área de aproximación de frontera difusa multiatributiva pitagórica de 2 tuplas (2TLPF-MABAC). El primero se utiliza para determinar la importancia de los criterios de evaluación, mientras que el segundo se emplea para seleccionar los AC óptimos utilizando los pesos obtenidos. Los resultados de ponderación de primer nivel revelan que los criterios de rendimiento se favorecieron predominantemente para la evaluación, y el "rendimiento energético" adquirió el peso más significativo (0,2487) entre todos los criterios de rendimiento. En términos de resultados de selección de AC, entre los 20 sistemas probados y evaluados, los 'AC basados en electricidad de pozos geotérmicos' obtuvieron el valor de puntuación más alto (0.1296), mientras que los 'AC basados en electricidad empaquetados en ventanas' tuvieron la puntuación más baja (-0.0515). La solidez de los resultados se confirmó a través del análisis de sensibilidad. As global median temperatures continue to rise, the demand for active cooling systems (ACs) is increasing. These systems are particularly prevalent in developed countries for maintaining comfort during hot weather. Various ACs technologies are available, and assessing their performance in multi-perspective settings is necessary to determine the best option for intended usage. This requires an evaluation platform for assessment. This paper presents a novel multi-criteria decision-making (MCDM) model based on a new integrated 2-tuple linguistic Pythagorean fuzzy-weighted zero-inconsistency (2 TLP-FWZIC) and modified 2-tuple linguistic Pythagorean fuzzy multi-attributive border approximation area comparison (2TLPF-MABAC). The former is used to determine the importance of assessment criteria, while the latter is employed for selecting the optimal ACs using the obtained weights. The first-level weighting results reveal that performance criteria were predominantly favored for assessment, with 'energy performance' acquiring the most significant weight (0.2487) among all performance criteria. In terms of ACs selection results, among the 20 tested and assessed systems, the 'geothermal borehole electricity-based ACs' obtained the highest score value (0.1296), while the 'window packaged electricity-based ACs' had the lowest score (-0.0515). The robustness of the results was confirmed through sensitivity analysis. مع استمرار ارتفاع متوسط درجات الحرارة العالمية، يزداد الطلب على أنظمة التبريد النشطة (ACs). تنتشر هذه الأنظمة بشكل خاص في البلدان المتقدمة للحفاظ على الراحة أثناء الطقس الحار. تتوفر تقنيات مكيفات الهواء المختلفة، وتقييم أدائها في إعدادات متعددة وجهات النظر ضروري لتحديد أفضل خيار للاستخدام المقصود. وهذا يتطلب منصة تقييم للتقييم. تقدم هذه الورقة نموذجًا جديدًا لصنع القرار متعدد المعايير (MCDM) استنادًا إلى نموذج لغوي جديد متكامل مكون من مجموعتين فيثاغورس لغويًا ضبابيًا منعدم الاتساق (2 TLP - FWZIC) ومقارنة تقريبية لغوية متعددة الصفات لغوية معدلة من مجموعتين فيثاغورس (2TLPF - MABAC). يستخدم الأول لتحديد أهمية معايير التقييم، بينما يستخدم الأخير لاختيار التكييفات المثلى باستخدام الأوزان التي تم الحصول عليها. تكشف نتائج الترجيح من المستوى الأول أن معايير الأداء كانت مفضلة في الغالب للتقييم، حيث اكتسب "أداء الطاقة" الوزن الأكثر أهمية (0.2487) بين جميع معايير الأداء. من حيث نتائج اختيار مكيفات الهواء، من بين 20 نظامًا تم اختبارها وتقييمها، حصلت "مكيفات الهواء القائمة على الكهرباء الحرارية الأرضية" على أعلى قيمة للدرجات (0.1296)، في حين حصلت "مكيفات الهواء القائمة على الكهرباء المعبأة في النوافذ" على أدنى درجة (-0.0515). تم تأكيد قوة النتائج من خلال تحليل الحساسية.

Expert systems with applications 221, 119724 (2023). doi:10.1016/j.eswa.2023.119724 Published by Elsevier Science, Amsterdam [u.a.]

This paper proposes a novel ship energy systems (SESs) benchmarking model for performance measurement of sustainable transportation based on the extension of q-rung orthopair fuzzy rough sets (q-ROFRS) and multicriteria decision-making (MCDM) methods. The underlying research methodology consists of two main stages: (i) Formulation of the SES decision matrix between SESs and the sustainability, (ii) Development of a q-ROFRS and fuzzy-weighted zero-inconsistency (q-ROFRS–FWZIC) model to determine the weights of each criterion. The integrated model of the q-ROFRS and fuzzy decision by the opinion score method (q-ROFRS-FDOSM) is offered as a tool for benchmarking the SESs. Sixty-two SESs are evaluated and benchmarked according to the three layers of criteria concerning the five design alternatives. The analysis of the proposed q-ROFRS–FWZIC methodology revealed that decision support methods (C2) is the most important criterion with a weight of 0.4174, followed by gas emissions (C1.1.2) and economic criterion (C1.1.1) with weights of 0.1661 and 0.1498, respectively; and energy efficiency design index (C1.2.1) is the least important. Furthermore, the results from q-ROFRS-FDOSM reveal that SES62 is the most suitable SES followed by SES60, whereas SES37 is the least suitable. Finally, the robustness of the proposed method is assessed by conducting a sensitivity analysis.

As the transition to electric mobility accelerates, charging infrastructure is rapidly expanding. Publicly accessible chargers, also known as electric vehicle supply equipment (EVSE), are critical not only for further promoting the transition but also for mitigating charger access anxiety among electric vehicle (EV) users. It is essential to install the proper EVSE configuration that meets the EV user's various considerations. This study presents a multi-criteria decision-making (MCDM) framework for determining the best performing public EVSE type from multiple EV user perspectives. The proposed approach combines a new MCDM model with an optimal public charging station model. While the optimal model outputs are used to evaluate the quantitative criteria, the MCDM model assesses EV users' evaluations of the qualitative criteria using nonlinear Bonferroni functions extended by rough Dombi norms. The proposed MCDM has standardization parameters with a flexible rough boundary interval, allowing for flexible and rational decision-making. The model is tested using real public EVSE charging data and EV users' evaluations from the field. All public EVSE alternatives are studied. Among the five EVSE options, DCFC EVSE is found to be the best performing, whereas three-phase AC L2 is the least performing option. In terms of EV user preferences, the required charging time is found to have the highest degree of importance, while V2G capability is the least important. The comparative analysis with state-of-the-art MCDM methods validates the proposed model results. Finally, sensitivity analysis verified the ranking order.