Selection of optimal access point for offshore wind farm based on multi-objective decision making

Bian, Zhipeng; Xu, Zheng; Dong, Huanfeng; Xu, Qian

doi:10.1016/j.ijepes.2018.05.025

Cited by 14 publications

(6 citation statements)

References 15 publications

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“…The weight coefficients are calculated by an objective method based on entropy weight theory (Bian et al, 2018). The sample data are the 128 existing ski areas established before 2012.…”

Section: Methodsmentioning

confidence: 99%

Suitability Analysis of Ski Areas in China: An Integrated Study Based on Natural and Socioeconomic Conditions

Che¹,

Xiao²,

Wang³

et al. 2019

Preprint

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Abstract. The successful bidding of the 2022 Winter Olympics (Beijing 2022, officially known as the XXIV Olympic Winter Games) has greatly stimulated Chinese enthusiasm to participate in winter sports. Consequently, the Chinese ski industry is rapidly booming driven by enormous market demand and government support. However, investing in ski area at an unreasonable location will cause problems both from economic perspective (in terms of operation and management) as well as geographical concerns (such as environmental degradation). To evaluate the suitability of a ski area based on scientific metrics has since become a prerequisite to the sustainable development of ski industry. In this study, we evaluate the locational suitability of ski areas in China by integrating their natural and socioeconomic conditions using linear weighted method based on geographic information systems (GIS) spatial analysis combined with remote sensing, online and field survey data. Key indexes for evaluating the natural suitability include snow cover, air temperature, topographic conditions, groundwater, and vegetation, whereas socioeconomic suitability is evaluated based on economic conditions, accessibility of transportation, distance to tourist attractions, and distance to cities. As such, an integrated metrics considering both natural and socioeconomic suitability is defined to be a threshold and used to identify the suitability of a candidate region for ski area development. The results show that 92 % of existing ski areas are located in areas with an integrated index greater than 0.5. In contrary, a ski area is considered to be a dismal prospect when the locational integrated index is less than 0.5. Finally, corresponding development strategies for decision-makers are proposed based on the multi-criteria metrics, which will be extended to incorporate potential influences from future climate change and socioeconomic development.

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“…The weight coefficients are calculated by an objective method based on entropy weight theory (Bian et al, 2018). The sample data are the 128 existing ski areas established before 2012.…”

Section: Methodsmentioning

confidence: 99%

Suitability Analysis of Ski Areas in China: An Integrated Study Based on Natural and Socioeconomic Conditions

Che¹,

Xiao²,

Wang³

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…The nature of the compensation systems to be used offshore has also been accepted to be mostly based on static-compensation (STATCOM) systems with some variance in the control methodologies [3][4][5], while references vary in the location (either 50% on each of the two remote-ends of the cable system, or 100% onshore). Other reviews [6] address the advantages and methods for using the HVDC-VSC (voltage-sourced converter-based HVDC) converters, paired with a multi-objective optimization algorithm, to significantly improve the operation of AC offshore networks.…”

Section: Literature Reviewmentioning

confidence: 99%

Power-from-Shore Optioneering for Integration of Offshore Renewable Energy in Oil and Gas Production

Antunes,

Castro,

Santos

et al. 2023

Energies

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Despite the widespread usage of high-voltage alternating current (HVAC) for the connection of offshore wind farms (OWF), its use to power-from-shore (PFS) offshore oil and gas (O&G) production sites is often not feasible. Its limitations for long-distance subsea transmission are usually found at 50–70 km from shore and might be even shorter when compared commercially to a direct-current (DC) alternative or conventional generation. Therefore, this research paper aims to address the standardization of offshore transmission with a particular focus on the high-voltage direct current (HVDC) alternative. While the distance is typically not a limiting factor when using DC, and the voltages used are rather standard, the concept of power envelopes can be quite useful in addressing the high variability of offshore site power requirements and setting a design baseline that would lead to improved lead time. In this article, a full back and front-end genetic optioneering model purposely built from the ground up in Python language is used to #1 define up to three DC power envelopes that would cater to most of the candidate’s requirements and #2 provide the lowest cost variance. The results will demonstrate that this can be achieved at a minor overall cost expense.

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“…Therefore, the method evaluates the contribution of every time‐domain index to the clustering results. The entropy is used to ascertain the disorder degree and information utility in a system [26]. The weight of the index is determined by the amount of information on the basis of the entropy‐weighting method, which is calculated using (8) and (9).…”

Section: Integrated Clustering Algorithm Based On the Divide‐and‐conqmentioning

confidence: 99%

Electricity consumption behaviour analysis based on adaptive weighted‐feature K‐means‐AP clustering

Cai

et al. 2019

IET Generation, Transmission & Distribution

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Selection of optimal access point for offshore wind farm based on multi-objective decision making

Cited by 14 publications

References 15 publications

Suitability Analysis of Ski Areas in China: An Integrated Study Based on Natural and Socioeconomic Conditions

Suitability Analysis of Ski Areas in China: An Integrated Study Based on Natural and Socioeconomic Conditions

Power-from-Shore Optioneering for Integration of Offshore Renewable Energy in Oil and Gas Production

Electricity consumption behaviour analysis based on adaptive weighted‐feature K‐means‐AP clustering

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