globalchange  > 气候变化事实与影响
DOI: 10.3390/su11082218
WOS记录号: WOS:000467752200031
论文题名:
Smart Integration Based on Hybrid Particle Swarm Optimization Technique for Carbon Dioxide Emission Reduction in Eco-Ports
作者: Balbaa, Alsnosy1; Swief, R. A.2; El-Amary, Noha H.1
通讯作者: El-Amary, Noha H.
刊名: SUSTAINABILITY
ISSN: 2071-1050
出版年: 2019
卷: 11, 期:8
语种: 英语
英文关键词: Eco-ports smart commitment ; environmental sustainability ; Egyptian seaports ; green ports ; Hybrid Particle Swarm Optimization Technique (HPSOT) ; optimization techniques ; Photovoltaic (PV) power generation ; renewable electrical energy resources
WOS关键词: UNIT COMMITMENT
WOS学科分类: Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向: Science & Technology - Other Topics ; Environmental Sciences & Ecology
英文摘要:

The increasing daily rate of environmental pollution, due to electrical power generation from fossil fuel sources in different societies, urges the researchers to study alternative solutions. These solutions can be summarized into either finding other clean, renewable sources or managing the available sources optimally. This research represents smart electrical interconnection management between some of the Egyptian seaports for optimal operation, with a clean sustainable environment as the target. The optimum ports' commitment operation works through certain technical constraints to attain optimal economic and environmental factors. One of the main objectives of this study is the reduction of carbon dioxide (CO2) emission, which is released from the electrical power generation that covers the seaports demands. It is progressed through the green port smart commitment, by incorporating unpolluted and renewable energy resources. This study depends on the redesign of some Egyptian seaports to be green ports with eco-friendly electrical construction. According to the new electrical design, two out of the six studied seaports can be considered as renewable energy generation units consisting of Photovoltaic (PV) electrical generation resources. The new design of the seaports electrical network can be considered as a hybrid network, collecting both fossil fuel electrical power generation and PV sources. To gain benefits from the diversity in geographical behaviors, ports on the red sea and Mediterranean sea are integrated into the network cloud. Connecting ports on red and Mediterranean seas construct a network cloud, which supports the operation of the whole network under different conditions. Hybrid (weighted-discrete) Particle Swarm Optimization Technique (HPSOT) is an effective optimization technique which is applied to provide the optimum interconnection management between the eco-ports. It is developed based on some technical constraints which are the availability of the network buses interconnection, the voltage and frequency levels, and deviations due to the smart unit interconnection and the re-direction of the power flow. The HPSOT is targeted to minimize the economical cost and the harmful environmental impact of the seaport electrical network, while covering the overall network load. The HPSOT is programmed utilizing the Matlab program. It is tested on the six Egyptian seaports network that consists of El Dekheila, Alexandria, and Damietta on the Mediteranean and Port Said, Suez, and Sokhna port on the Suez canal and Red sea. It verifies its accurateness and efficiency in decreasing the combined cost function involving costs of CO2 emission. CO2 emission is reduced to 6% of its previous value for the same consumed electrical energy, that means it has a positive impact on retarding the greenhouse effect and climate change.


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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/134029
Appears in Collections:气候变化事实与影响

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作者单位: 1.AASTMT, Cairo 2033, Egypt
2.Ain Shams Univ, Fac Engn, Cairo 11517, Egypt

Recommended Citation:
Balbaa, Alsnosy,Swief, R. A.,El-Amary, Noha H.. Smart Integration Based on Hybrid Particle Swarm Optimization Technique for Carbon Dioxide Emission Reduction in Eco-Ports[J]. SUSTAINABILITY,2019-01-01,11(8)
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