Having a sustainable, clean, efficient and economic environment is one of the main requirements of humanity. The seaport is such an environment, which needs care to be maintained as a sustainable green environment. This research provides a model for attaining a sustainable green port with the utilization of two mutual sequential renewable energies, which are Biomass and photovoltaic (PV) energy. This research plans to cover the whole electrical power generation of the seaport model after ten years using biomass and PV energy. Further, the research suggests the selling of extra electrical energy to the Egyptian Unified Electrical Power Network and the nearby loads. The project is held in two main stages. The first stage is the intermediate stage in which both green energy and the conventional electrical energy from the power grid will supply the port. In the second (final) stage, the green renewable energy will cover the consumption of the targeted seaport and sell the excess to the unified grid or the nearby costumers. The combination of biomass and PV electrical power generation can lead to an integrated efficient green energy port model. The research model will be applied to Damietta seaport, which is located 10 km to the west of the Nile River (Damietta Branch). It is assumed that by 2021 more than 50% of Damietta seaport electrical energy will be supplied by both biomass electrical generated energy and PV power generation. By 2026, green energy generation will have covered all the port requirements for electrical energy, and the extra power will have been diverted to the Egyptian unified electrical power network.

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.

This paper studies the effect on the rate of growth of carbon dioxide emission in seaports' atmosphere of replacing a part of the fossil fuel electrical power generation by clean renewable electrical energies, through two different scheduling strategies. The increased rate of harmful greenhouse gas emissions due to conventional electrical power generation severely affects the whole global atmosphere. Carbon dioxide and other greenhouse gases emissions are responsible for a significant share of global warming. Developing countries participate in this environmental distortion to a great percentage. Two different suggested strategies for renewable electrical energy scheduling are discussed in this paper, to attain a sustainable green port by the utilization of two mutual sequential clean renewable energies, which are biomass and photovoltaic (PV) energy. The first strategy, which is called the eco-availability mode, is a simple method. It is based on operating the renewable electrical energy sources during the available time of operation, taking into consideration the simple and basic technical issues only, without considering the sophisticated technical and economical models. The available operation time is determined by the environmental condition. This strategy is addressed to result on the maximum available Biomass and PV energy generation based on the least environmental and technical conditions (panel efficiency, minimum average daily sunshine hours per month, minimum average solar insolation per month). The second strategy, which is called the Intelligent Scheduling (IS) mode, relies on an intelligent Reconfigured Whale Optimization Technique (RWOT) based-model. In this strategy, some additional technical and economical issues are considered. The studied renewable electrical energy generation system is considered in two scenarios, which are with and without storage units. The objective (cost) function of the scheduling optimization problem, for both scenarios, are developed. Also, the boundary conditions and problem constraints are concluded. The RWOT algorithm is an updated Whale Optimization Algorithm (WOA). It is developed to accelerate the rate of reaching the optimal solution for the IS problem. The two strategies simulation and implementation are illustrated and applied to the seaport of Damietta, which is an Egyptian port, located 10 km to the west of the Nile River (Damietta Branch). The scheduling of PV and biomass energy generation during the different year months is examined for both strategies. The impact of renewable electrical energies generation scheduling on carbon dioxide emission and consequently global warming is discussed. The saving in carbon dioxide emission is calculated and the efficient results of the suggested models are clarified. The carbon dioxide emission is reduced to around its fifth value, during renewable energy operation. This work focuses on decreasing the rate of growth of carbon dioxide emission coming from fossil fuel electrical power generation in Egypt, targ...

Climate change is an established and growing priority environmental issue. This paper investigates the importance of climate change in ports through a research-based survey on data collected from participants at the Greenport Congress in Valencia in 2018. The data for this paper were obtained from the responses of 55 port professionals and environmental specialists that replied to a questionnaire survey during the Congress. Questionnaires were analyzed to identify the opinions and experience of delegates. A collaborative approach involving the free exchange of knowledge and experience between port professionals, industry practitioners and academia is the model most likely to deliver practicable options to the mutual advantage of operators, local communities, regulatory authorities and the environment. Based on the results of this survey, Climate Change occupies the 6th position among top 10 environmental port priorities and Carbon Footprint the 8th position. This reflects the importance of these two issues in the whole set of environmental priorities. Data collection has been identified as the main challenge ports encounter to implement a carbon management program. The need for a common port-sector Carbon Footprint scheme, which would benefit individual port authorities and the port-sector as a whole, was highlighted by the participants.

This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel Artificial Immunity sensorless Eco-Maximum Power Point Tracking (AI EMPPT) and the asymptotic non-linear control techniques. The main target of the AI EMPPT is to reduce the carbon dioxide emission by generating the maximum possible power from the renewable electrical energy resource, which is wind electrical power generation to replace the fossil-fuel conventional generation. To build the AI EMPPT, an Artificial Immunity System Estimator (AISE) based on artificial immunity technique and a Model Reference Adaptive System (MRAS) are used to estimate the DFIG rotor speed. Then, the AI EMPPT is applied to provide the reference electromagnetic torque signal. Subsequently, the reference electromagnetic torque interacts with the estimated generator speed, determined by the wind mechanical power, to supply the wind electrical power. The second cluster is the asymptotic non-linear control technique which proposes the reference signal tracking of the rotor direct and quadratic current, respectively. Thus, assigning specific zeros through feedback ensures the reproduction of an output that converges asymptotically to a required reference rotor current. For online operation, the Artificial Immunity Technique (AIT) is utilized to deal with the generated control reference signal. A proposal hardware implementation on Field Programmed Gate Array (FPGA) is also presented. The introduced approach was applied to a wind turbine generator driving a 3.7 kW load. MATLAB program was used to simulate and test the performance of the proposed control methods. The results to show the effectiveness of the proposed technique. The reduction in CO 2 emission was calculated.