Shore side electricity subsidy policy efficiency optimization: From the game theory perspective

Wang, Yubing; Guo, Siqing; Dai, Lei; Zhang, Zhipeng; Hu, Hao

doi:10.1016/j.ocecoaman.2022.106324

Cited by 25 publications

(12 citation statements)

References 28 publications

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“…Several government subsidy plans aiming to maximize emissions reduction at ports were independently developed by Wu and Wang (2020), Wang et al (2021b) and Wang et al (2022) . These plans were optimized to ensure the optimal utilization of government subsidies.…”

Section: Economic Incentive Of Shore Powermentioning

confidence: 99%

A life cycle cost analysis of different shore power incentive policies on both shore and ship sides based on system dynamics and a Chinese port case

Gu,

2024

Environ Sci Pollut Res

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Shore power (SP) is widely recognized as an efficient strategy for reducing air pollution in port areas. Unfortunately, the adoption of SP has been relatively low, resulting in limited emission reductions and financial losses. To address these challenges, this paper focuses on enhancing the utilization rate of SP. We propose a system dynamics model that assesses the impact of various incentive policies on the economic and environmental benefits of SP. The model considers the life cycle cost and comprises four subsystems. By conducting a case study on Nansha Port, we find that price subsidies are more effective than construction subsidies in overcoming economic barriers. Furthermore, we observe that the overall economic benefits only increase when the electricity price decreases. This is because lowering the electricity price enhances the profitability of ships without negatively affecting port revenue.Additionally, it is the proportion of the electricity price and service price that determines the overall economic benefits, rather than the SP price itself. Hence, it is recommended to provide preferential subsidies for the electricity price.

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Section: Economic Incentive Of Shore Powermentioning

confidence: 99%

A life cycle cost analysis of different shore power incentive policies on both shore and ship sides based on system dynamics and a Chinese port case

Gu,

2024

Environ Sci Pollut Res

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“…Recent years have witnessed the emergence of several green port transformation technologies including electric ships, clean energy, shore power, and ship exhaust treatment technologies. Yet, there is sufficient scope for advancements in technology, policy, market, and management to further mitigate environmental impacts (Wang et al, 2022). The additional costs associated with clean energy technologies can dampen the enthusiasm of shipping enterprises to engage in inland waterway environmental management.…”

Section: Emission Characteristics For Different Ship Attributesmentioning

confidence: 99%

“…Given the subsidy limit, the government should optimize the SSE subsidy structure for ports and ships (Wu and Wang, 2020;Xu and Di, 2021), elevate the subsidy on the sales price of electricity in ports, ascertain the subsidy ratio between equipment installation and operation (Wang et al, 2022), fully leverage national financial support, and enhance the relevant penalty mechanism and regulatory framework. With a guarantee of revenue, in order to obtain government subsidies rather than fines, ports may be inclined to offer certain subsidies for the emission reduction costs of shipping enterprises to encourage SSE usage (Meng et al, 2022).…”

Section: Emission Characteristics For Different Ship Attributesmentioning

confidence: 99%

Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development

Xie,

Li,

Yang

et al. 2023

Front. Mar. Sci.

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The escalating greenhouse gas (GHG) emissions from maritime trade present a serious environmental and biological threat. With increasing emission reduction initiatives, such as the European Union’s incorporation of the maritime sector into the emissions trading system, both challenges and opportunities emerge for maritime transport and associated industries. To address these concerns, this study presents a model specifically designed for estimating and projecting the spatiotemporal GHG emission inventory of ships, particularly when dealing with incomplete automatic identification system datasets. In the computational aspect of the model, various data processing techniques are employed to rectify inaccuracies arising from incomplete or erroneous AIS data, including big data cleaning, ship trajectory aggregation, multi-source spatiotemporal data fusion and missing data complementation. Utilizing a bottom-up ship dynamic approach, the model generates a high-resolution GHG emission inventory. This inventory contains key attributes such as the types of ships emitting GHGs, the locations of these emissions, the time periods during which emissions occur, and emissions. For predictive analytics, the model utilizes temporal fusion transformers equipped with the attention mechanism to accurately forecast the critical emission parameters, including emission locations, time frames, and quantities. Focusing on the sea area around Tianjin port—a region characterized by high shipping activity—this study achieves fine-grained emission source tracking via detailed emission inventory calculations. Moreover, the prediction model achieves a promising loss function of approximately 0.15 under the optimal parameter configuration, obtaining a better result than recurrent neural network (RNN) and long short-term memory network (LSTM) in the comparative experiments. The proposed method allows for a comprehensive understanding of emission patterns across diverse vessel types under various operational conditions. Coupled with the prediction results, the study offers valuable theoretical and data-driven support for formulating emission reduction strategies and optimizing resource allocation, thereby contributing to sustainable maritime transformation.

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“…A range of green energy alternatives to traditional fuels have been explored and summarized, including bioenergy, liquefied natural gas, tidal energy, wind energy, and shore power (SP) (Wan et al, 2018). Moreover, researchers have begun to examine the carbon reduction dynamics of ships from various perspectives, such as policy, economy, and environment (Chen et al, 2021b;Xu et al, 2021;Zhao et al, 2021;Zhong et al, 2021;Meng et al, 2022;Wang et al, 2022). Rehmatulla and Smith (2015) proposed that reducing greenhouse gas emissions from the shipping industry by approximately 30-80% of current levels is feasible, contemplating potential hindrances that may obstruct the shipping industry from implementing such levels of decarbonization.…”

Section: Introductionmentioning

confidence: 99%

Research on the carbon emissions traceability inventory and multi-horizon prediction of ship carbon emissions: a case study of Tianjin Port

Xie

Yang

et al. 2023

Front. Mar. Sci.

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IntroductionIn recent years, the adverse effects of escalating maritime trade and international shipping– particularly in regard to increased greenhouse gas emissions and their impact on human health– have come to the fore. These issues have thus instigated a surge in pressure to enhance the regulation of shipborne carbon emissions.MethodsThe study utilized the automatic identification system (AIS) data, Lloyd’s register data, and pollutant emission parameters to calculate the carbon emissions from the main engine, auxiliary engine, and boiler of vessels under varying sailing conditions, utilizing the dynamic method of ships. In relation to geographic information and ship trajectory, a comprehensive inventory of ship carbon emissions was developed, revealing pronounced spatiotemporal characteristics. To assure the accuracy of the substantial AIS dataset, procedures including data cleaning, trajectory integration, data fusion, and completion were executed. Such processes are indispensable, given the potential for transmission and storage errors associated with AIS data. To forecast CO2 emissions over diverse time intervals, a temporal fusion transformer model equipped with attention mechanisms was employed.ResultThe paper furnishes a case study on Tianjin Port, wherein a high-resolution carbon emissions inventory was devised based on AIS data acquired from vessels. This inventory was subsequently employed to generate multi-feature predictions of future carbon emissions. Given the optimal parameter configuration, the proposed method attained P50 and P90 values of 0.244 and 0.118 respectively, thereby demonstrating its efficacy.DiscussionRecognizing the sources of ship carbon emissions in this region and forecasting such emissions in the future substantiates that this method accurately portrays the laws of ship carbon emissions. Our study provides a scientific basis for decision-making in port and pollution management, enabling the creation of targeted emission reduction policies for ships.

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Shore side electricity subsidy policy efficiency optimization: From the game theory perspective

Cited by 25 publications

References 28 publications

A life cycle cost analysis of different shore power incentive policies on both shore and ship sides based on system dynamics and a Chinese port case

A life cycle cost analysis of different shore power incentive policies on both shore and ship sides based on system dynamics and a Chinese port case

Maritime greenhouse gas emission estimation and forecasting through AIS data analytics: a case study of Tianjin port in the context of sustainable development

Research on the carbon emissions traceability inventory and multi-horizon prediction of ship carbon emissions: a case study of Tianjin Port

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