Feasibility study of integrating the renewable energy system for increased electricity access: A case study of Choba community in Nigeria

Ezekwem, Chidozie; Muthusamy, Suresh

doi:10.1016/j.sciaf.2023.e01781

Cited by 7 publications

(2 citation statements)

References 48 publications

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“…Several studies have explored the potential benefits and challenges associated with integrating renewable energy sources, such as photovoltaic (PV) and wind energy, in port operations (Tawfik et al, 2023). For instance, (Ezekwem & Muthusamy, 2023;Parhamfar et al, 2023) investigated the feasibility of integrating PV systems in a major port and highlighted the potential for reducing carbon emissions and electricity costs. Similarly, (Cascajo, 2019;Engelmann & Robinson, 2019;Willmott et al, 2022) explored the integration of wind energy systems in ports, emphasizing the importance of site selection, wind resource assessment, and grid integration strategies.…”

Section: Introductionmentioning

confidence: 99%

Introducing Optimal Energy Hub Approach in Smart Green Ports based on Machine Learning Methodology

Tawfik,

Shehata,

Hassan

et al. 2024

Preprint

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The integration of renewable energy systems in port facilities is essential for achieving sustainable and environmentally friendly operations. This paper presents the implementation of an Optimal Energy Hub approach in smart green ports, with a focus on the case study of Egypt and the Middle East Oil Transmission & Pipelines Company (MIDTAP) company. The study explores the integration of photovoltaic (PV) and wind energy systems within the port's operations. Machine learning methodologies are utilized to optimize energy management and decision-making processes in the port. The proposed approach leverages historical data, weather forecasts, and real-time energy demand to predict and optimize the utilization of PV and wind energy resources. By utilizing machine learning techniques, the energy hub can efficiently balance energy supply and demand, ensuring optimal utilization of renewable sources while minimizing reliance on conventional energy sources. Furthermore, this paper discusses a scenario of increasing load and renewable energy generation in the port facility. A comprehensive energy flow-based mixed integer linear programming (MILP)-based optimization framework implemented in MATLAB is presented. This framework aims to minimize electricity consumption costs while providing considerable flexibility and adaptability to accommodate the changing energy landscape. The results of the study provide valuable insights into the implementation of sustainable energy solutions in smart green ports, specifically in the context of Egypt and the MIDTAP company. The integration of PV and wind energy systems, along with the proposed MILP-based optimization framework, offers a practical and efficient approach to minimize electricity consumption costs and reduce the carbon footprint of port operations. The findings demonstrate the flexibility and adaptability of the Optimal Energy Hub approach in accommodating increasing loads and renewable energy generation. The research findings encourage the adoption of similar energy hub approaches in other port facilities, contributing to the global transition towards greener and more sustainable practices. The utilization of machine learning methodologies and MILP-based optimization frameworks in smart green ports can facilitate cost-effective and environmentally friendly energy management, promoting a more sustainable future for port operations. Several scenarios were used to show how the proposed notion was perceived. The primary objective is to maximize the use of renewable energy sources while reducing expenses and emissions. The MIDTAP Company evaluated the effects of adding more renewable energy systems in smart green ports through a study involving six scenarios. Additionally, MIDTAP Company conducted research with six scenarios to assess the impact of increasing the number of renewable energy systems in smart green ports. In these scenarios, the renewable energy systems (PV + Wind) are increased by 10%, 20%, 30%, and 40%, while the load is increased by 25% and 50%. The primary objective of these scenarios is to maximize the use of renewable energy sources while reducing expenses and emissions, and the results provide valuable insights into the potential benefits and challenges of scaling up renewable energy systems in smart green ports. The significance of grid connectivity and sustainable energy solutions for smart green ports was also emphasized by the study. The findings show how economical and sustainable energy solutions may be achieved in smart green ports through the application of machine learning and optimization based on MILP. The selection of a 40% increase in renewable energy systems (PV + Wind) in the sixth scenario, which aims to explore the potential for further scaling up renewable energy infrastructure within the MIDTAP port, is based on the available area in MIDTAP. Considering the spatial limitations and resource availability of the port, careful assessment and planning are crucial to determine the optimal capacity for renewable energy systems. By selecting a 40% increase, the study takes into account the available area within MIDTAP and the potential for accommodating additional renewable energy installations. This approach ensures that the scenario aligns with the port's physical constraints while still pushing the boundaries of renewable energy integration. Evaluating this scenario provides insights into the feasibility and benefits of leveraging a larger share of renewable energy sources within the port, ultimately contributing to its sustainable and environmentally friendly operations.

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Section: Introductionmentioning

confidence: 99%

Introducing Optimal Energy Hub Approach in Smart Green Ports based on Machine Learning Methodology

Tawfik,

Shehata,

Hassan

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The principal cause of the increased technical problems is the result of inadequate financial investment over the years in system improvement projects. This has generated unintended extensions of the distribution lines, the overloading of system components, such as transformers and conductors and a deficiency in reactive power support (Ezekwem et al, 2023). Low metering efficiency, power theft and theft are primarily to blame for commercial losses.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Geospatial Technology for Enhanced Utility Management: A Case Study in Electrical Distribution Power Systems

Adekunle,

Alausa,

Adaradoun

et al. 2023

For. Geo.

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Over the years, electricity has developed into a crucial commodity for any nation. The need to evaluate the rate of electricity consumption in regard to utility management and the spatial distribution of major devices to facilitate appropriate planning within the estate is the motivation for this research. This study used geospatial technology to evaluate the electricity distribution to support planning and management in Omole Estate (Phase One) and environs within the city of Lagos, Nigeria. The focus was on determining the land use in study area, geolocations of the transformers, along with the cost of energy consumed per household. Spatial data for the research area was collected through a Hand-held GPS. Google Earth images were downloaded to supplement the data, and a comprehensive analysis of administered and recovered questionnaires was conducted to enrich the dataset. ArcGIS 10.6.1 software was employed to create the database and depict the area, whilst modifying all of the details required within. The result confirms that 72% of the respondents use electricity for domestic use, 18% for commercial use while 10% utilise it for domestic and commercial use. A significant portion of homes (33%) still use outdated postpaid meters and 35% of respondents do not know how much power they use at home each month or the cost per unit of that electricity. Regarding the respondents, 67% have a prepaid card/electrical meter installed (per kilowatt). Concerning cost, 10% of the respondents spends between N1000-N5000 for their monthly electricity consumption, 27% of the respondents between N5,000 and N10,000, 38% between N10,000 and N17,000, 24% between N17,000 and N25,000 and 2% above N25,000 per month on electricity. These findings will assist effective power distribution within the estate and provide guidance on charge rates for commercial power users which is approximately 28% overall.

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A perspective on solar railway potential for the UK

Braima,

Butt,

Maraqa

et al. 2024

Env Prog and Sustain Energy

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In the face of climate change challenges, energy demand is still increasing, and renewable energy is becoming increasingly necessary as a sustainable resource. Solar energy stands out as a promising renewable resource, yet its widespread adoption faces challenges, notably the substantial land requirements for photovoltaic (PV) panels. This conflict intensifies as land could be more efficiently utilized for agriculture and development. Conversely, railway infrastructure occupies expansive tracts of land, presenting an opportunity to integrate PV panels without disrupting rail operations. However, a comprehensive assessment of the solar potential along railway tracks on a national scale is lacking for different countries and the UK is one of them. This study addresses this gap by evaluating the feasibility of installing PV panels on railway tracks throughout the UK to generate electricity. Utilizing mathematical models tailored to five distinct solar panel technologies, the study incorporates various factors, including solar radiation levels across different months. Assumptions were made where necessary, with values for certain variables averaged to facilitate calculations. The findings reveal that solar energy harnessed from railways could satisfy up to 8% of the UK's total electricity demand, with a minimum contribution of 0.3%. This study provides valuable insights from a UK‐centric perspective and offers a replicable framework for similar assessments in other countries with extensive railway networks, such as China and India. By leveraging existing infrastructure for renewable energy generation, such initiatives could contribute significantly to global sustainability efforts.

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Feasibility study of integrating the renewable energy system for increased electricity access: A case study of Choba community in Nigeria

Cited by 7 publications

References 48 publications

Introducing Optimal Energy Hub Approach in Smart Green Ports based on Machine Learning Methodology

Introducing Optimal Energy Hub Approach in Smart Green Ports based on Machine Learning Methodology

Leveraging Geospatial Technology for Enhanced Utility Management: A Case Study in Electrical Distribution Power Systems

A perspective on solar railway potential for the UK

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