Abstract
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.
Highlights
Egypt has joined the 20 20 20 agreement that, by the year 2020, 20% of its generation will be replaced by renewable energy, towards decarbonizing the electrical power sector
To reduce emissions from electricity sector, the efficiency of the power plants should be increased, the fossil fuels electrical power sources are recommended to be replaced by renewable and clean electrical power resources, and/or Carbon Capture Sequestration and Storage (CCSS) should be utilized
The Hybrid Particle Swarm Optimization Technique (HPSOT) consists of discrete Particle Swarm Optimization (PSO) for assigning both supplier and consumer ports, and the direction of the power flow, while weighted PSO is for determining the transmitted power between the two ports
Summary
Egypt has joined the 20 20 20 agreement that, by the year 2020, 20% of its generation will be replaced by renewable energy, towards decarbonizing the electrical power sector. The 20 20 20 goals are 20% increase in energy efficiency, 20% reduction of CO2 emissions, and 20% renewables by 2020. It depends on the reconfiguration of the electricity grid into a “smart grid” [1]. The transportation sector is one of the main sectors affecting eco-environment behavior. The vehicle routing problems are studied, considering environmental costs, which are composed of noise, pollution, and fuel consumption [2,3]. Reducing the companies costs and greenhouse gas emissions through horizontal transportation collaboration are described in [4]
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