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Article

A Simulation Modeling Approach for the Techno-Economic Analysis of the Integration of Electric Vehicle Charging Stations and Hybrid Renewable Energy Systems in Tourism Districts

1
Electrical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt
2
Mechanical and Industrial Engineering Department, College of Engineering, Sultan Qaboos University, Al-Khoud, Muscat 123, Oman
3
Mechanical Engineering Department, Faculty of Engineering, Fayoum University, Fayoum 63514, Egypt
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2024, 14(11), 4525; https://doi.org/10.3390/app14114525
Submission received: 3 May 2024 / Revised: 22 May 2024 / Accepted: 23 May 2024 / Published: 25 May 2024
(This article belongs to the Special Issue Renewable Energy Systems 2024)

Abstract

:
Electric vehicles (EVs) play a crucial role in tertiary sectors due to their eco-friendliness and sustainability when powered by clean energy. Integrating EV charging stations with renewable energy systems is essential to alleviate energy issues and grid pressure. Exploring this integration’s feasibility is imperative for sustainable transportation. This study aims to provide a clear approach and methodology for examining the potential of integrating renewable energy technologies with EV charging stations at the district level. Additionally, the study investigates the energy, economic, and environmental benefits of an integrated system comprising photovoltaic/wind turbines (PV/WTs) connected to the electricity grid to meet the energy demand of a tertiary district consisting of five hotels in Egypt. Through the development of a simulation model, the paper verifies whether the proposed energy system can meet the district’s energy demand. In addition, the simulation model has been employed to conduct a sensitivity analysis for investigating the impact of different charging rates on economic feasibility. The results indicate that a hybrid renewable energy system (HRES) integrated with an EV charging station can effectively relieve pressure on the electricity grid and provide electricity at competitive prices compared to the national grid. Moreover, the proposed energy system significantly reduces environmental emissions by up to 510 tons of CO2 per year and has the potential to decrease fossil fuel usage by 248 tons per year. Sensitivity analysis highlights the significant impact of charging prices on project profitability.

1. Introduction

The transportation sector accounts for approximately 25% of the world’s total energy consumption [1]. It is a significant contributor to global CO2 emissions, with three-quarters of these emissions attributed to road transport [2]. The rising demand for urban mobility has led to increased energy consumption and greenhouse gas emissions from transportation, emphasizing the urgent need for sustainable mobility solutions to address pollution, congestion, and environmental degradation in urban areas [3]. In response to these challenges, governments and experts are actively promoting the development and adoption of electric vehicles (EVs) in the transportation sector [4].
Sustainable tourism is essential in the global economy, as it harmonizes environmental, social, and economic perspectives to achieve lasting benefits for destinations and the global community [5]. Increasing traveler preferences for eco-friendly and culturally responsible experiences are driving the demand for sustainable tourism. This trend not only protects natural ecosystems and cultural heritage, but also creates economic opportunities for local communities. By promoting job creation, community engagement, and biodiversity conservation, sustainable tourism enhances the overall resilience and attractiveness of destinations.
Interest in EVs has garnered widespread support from responsible governments, automobile companies, and startups [6]. These environmentally friendly vehicles show promising results in reducing carbon dioxide emissions, eliminating carbon emissions from transportation, and addressing and mitigating climate change. This is because they provide solutions to the negative and harmful effects of traditional vehicles and are gaining global acceptance due to their ability to reduce local and global air pollution and greenhouse gas (GHG) emissions [7]. The growing interest in EVs is driving dynamic growth in the EV market, leading to increased acquisition in the automotive industry. EVs contribute positively and effectively to green and sustainable tourism by promoting clean air, reducing environmental pollution, and providing a quieter environment and enjoyment for tourists [8]. However, if the electricity used to charge these vehicles is not sourced from clean, renewable energy, energy challenges will persist. Therefore, it is important to explore the integration of electric vehicle charging stations with renewable energy systems. Additionally, the use of electric vehicles in tourism could play a crucial role in the integration of renewable energy into the transportation sector.
The decarbonization of the tourism sector involves strategically integrating hybrid renewable energy systems [9] and promoting the widespread adoption of EVs [10]. Utilizing various renewable energy resources to provide energy for hotels, resorts, and tourist facilities can effectively reduce carbon emissions. Establishing a network of electric charging stations in popular tourist destinations may encourage the use of EVs, offering travelers a viable and environmentally friendly transportation option. Therefore, the synergy between hybrid renewable energy solutions and EVs in the tourism sector not only mitigates the negative environmental impacts of tourism, but also provides compelling solutions for sustainable practices across other industries, promoting a greener and more responsible approach to global travel.
While significant research has been conducted on establishing and operating charging stations for EVs using renewable energy, the majority of these studies have focused on areas outside the tourism sector. Ihm et al. [11] proposed an optimal energy system to generate electrical power for an EV charging station from renewable energy at a specific location in Korea. Al Hammadi et al. [12] examined different hybrid renewable energy systems for charging EVs in the city of Abu Dhabi, the United Arab Emirates. Wang et al. [13] designed an integrated electric charging station capable of serving electric and hybrid new energy vehicles. In [14], researchers investigated the technical and economic evaluations of a self-powered EV charging station based on renewable energy sources to determine the optimal system for charging EVs in four different cities in Qatar. In a previous paper, the authors [15] proposed the establishment of a grid-connected hybrid renewable energy power plant, consisting of photovoltaic, wind, and battery systems, to generate electricity for supermarkets in three different Moroccan cities.
Turkdogan S. [16] implemented a hybrid renewable energy system to meet the energy needs of a single-family residential home, examining utility and transportation requirements in Turkey. Bilal et al. [17] conducted research on the technical and economic feasibility of grid-connected renewable energy systems to establish environmentally sustainable EV charging stations in three distinct regions across India. Khan et al. [18] explored the economic feasibility of an integrated PV charging station in a residential building located in Malaysia. The research in [19] presented a technical, economic, and environmental evaluation of EV charging stations powered by intermittent hybrid renewable energy generation systems in three cities in Ethiopia.
Karmaker et al. [20] conducted a study to establish an EV charging station powered by a hybrid renewable energy system using solar energy and biogas to alleviate pressure on the national grid. Additionally, study [21] compared the technical and economic effectiveness of centralized DC fast-charging systems with decentralized AC charging systems using a grid-connected power system with PV systems in Egypt. Enany et al. [22] focused their study on the optimal design and operation of fast EV charging stations using renewable energy along transportation roads in Egypt.
Despite the significant impact of electric vehicles powered by renewable energy on the tourism sector, there is a severe lack of studies addressing this topic. This research contributes to the existing literature by being the first to examine renewable energy applications integrated with electric charging stations to serve a sector comprising five hotels in Egypt. Additionally, this study provides a comprehensive approach for researchers to conduct similar studies in various countries around the world. For example, but not limited to, this study is useful for analyzing renewable energy system-based EV charging stations, such as PV systems that supply electrical charging stations, as referenced [23] to determine the extent of their technical and economic feasibility.

1.1. Motivation

Decarbonizing tertiary sectors, like the tourism sector, is a goal that all countries aspire to achieve due to its prominent role in fostering a green and sustainable economy. Previous studies have demonstrated that the feasibility of an EV charging system powered by renewable energy depends largely on the meteorological and topological characteristics of the region. The literature review mentioned in the introduction reveals that there are limited studies that have conducted detailed research on the potential of EV charging stations based on renewable energy for powering district loads. However, very few studies have explored the technical and economic feasibility of EV charging systems running on renewable energy in the tourism sector. Motivated by this gap, this research aims to thoroughly study the design, analysis, and optimization of a tertiary district powered by a renewable energy system coupled with an EV charging station in a developing country (Egypt). Moreover, this work can pave the way for a green and sustainable tourism district with EV charging stations.

1.2. Objectives

This research aims to evaluate primary energy conservation and the reduction in greenhouse gas (GHG) emissions at the district level. Additionally, a sensitivity analysis is performed to study the impact of charging prices on system profitability.
This study contributes to the existing body of literature in the following ways:
  • Designing a hybrid renewable energy system (HRES) coupled with an EV charging station with a grid connection to meet the daily energy requirements in a tertiary district.
  • Analyzing the feasibility of the proposed system under typical conditions for developing countries, such as Egypt.
  • Evaluating the levelized cost of energy (LCOE) and utility bill savings of the system.
  • Assessing primary energy and GHG emission savings.
  • Conducting a sensitivity analysis of the effect of charging prices on system profitability. This is particularly important because there is no set price for charging electric vehicles, which can help decision makers and governments determine the appropriate pricing strategy.
  • Propose a simulation modeling approach that can be employed to optimally design hybrid renewable energy systems coupled with EV charging station for tourism applications.

2. Materials and Methods

This work simulates different energy system configurations integrated with EV charging stations to electrify a tertiary sector in Egypt. The energy systems were designed and simulated using HOMER Grid 1.11 software, a powerful tool for designing and analyzing microgrid systems that include electric vehicle (EV) charging stations [24,25]. HOMER Grid is more suitable for examining the optimal design of renewable energy distribution systems connected to the grid and integrated with EV charging stations. It is also more suitable for technical and economic evaluations, as well as conducting sensitivity studies for such systems. The proposed system is a centralized distributed hybrid renewable energy system located in an area close to the loads of the five hotels, as these hotels are located close to each other. The architecture of the proposed system can be observed in Figure 1. The diagram illustrates that the solar panel array and wind turbine generate electricity to power the hotel buildings (tertiary district) and electric vehicle charging stations. Excess electricity can be exported back to the utility grid under a power purchase agreement (PPA) of 0.02 USD/kWh, while the building can also import electricity from the grid when needed under the feed-in tariff scheme of 0.07 USD/kWh. The steps involved in modeling and simulation using HOMER Grid software can be explained as follows: The user starts by defining the load profiles for both the primary load and EV charging stations, then defines the renewable energy sources. Subsequently, the user selects the appropriate components of the system, taking into account the technical and financial data, and establishes system constraints. The software then performs simulations to evaluate system performance and calculate costs related to different configurations of components. The simulation results can be employed to refine the design of the microgrid system and make well-informed decisions regarding the selection of components.

2.1. Primary Load

Fayoum, Egypt, renowned for its history and tourism, experiences electricity demand spikes during peak tourist seasons. The government ensures a reliable electricity supply and promotes sustainability in the tourism sector, reflecting the need for sustainable energy solutions to preserve Fayoum’s charm amid growing tourism. In particular, tourist hotels mainly depend on the utility grid to satisfy their electric energy demand, which primarily relies on fossil fuels for generation. In this study, the electric energy output will be compared to the electric load of five selected hotels. Figure 2 illustrates the typical daily electric power loads in kW for selected hotels during the summer and winter seasons. It can be observed that the lowest peak demand occurs in winter (115 kW), while the highest occurs in summer (400 kW). The hotel district’s combined annual electricity primary demand is 1.7 GWh per year, with an expected average daily energy consumption of 4.6 MWh/day.

2.2. EV Charging Load

The EV charging load represents the electrical energy needed to charge a specific number of EVs that serve visitors in the five hotels for tourist tours in this region. This load was estimated based on the expected daily travel distance of the vehicles, in addition to the distance the vehicles can travel when the battery is fully charged. The total number of electric vehicles (EVs) entering the charging station during the day is estimated at 30. It is assumed that this station consists of ten chargers to accommodate the charging needs of the 30 EVs during the day. The number of EVs is estimated based on the number of tourists per day visiting tourist sites in Fayoum, which was collected from the selected hotels according to the historical data on tourist visits. It is considered that all the EVs are of the same type, namely the Nissan Leaf [18]. The technical data for the EVs are provided in Table 1 [18]. The daily energy required to charge an electric car was estimated as follows [18]:
E d a i l y   =   B c a × D R
where:
  • B c a is the capacity of the EV battery in kWh, which is estimated to be 40 kWh [18].
  • D is the daily commute distance in km, which is estimated to be 50 km.
  • R is the range of EV in km, which refers to the distance it can travel on a single charge before requiring recharging. The range of the EV Nissan leaf is estimated at 311 km [18].
HOMER Grid facilitates the definition of the load profile for EV charging stations, allowing users to specify power requirements and charging duration. Users can input technical details, such as the number of EVs, maximum charge power, charger output power, the quantity of charging stations, and charging price. As Egypt currently has a limited number of EVs and EVCS, the selling price of EV charging has not been officially declared. Given that the unit cost of purchasing power from the grid in Egypt is 0.07 USD/kWh, the assumed EV charging selling price is also 0.07 USD/kWh.

2.3. Renewable Energy Potentials

Egypt boasts an excellent photovoltaic daily power potential ranging from 5.0 to more than 5.6 kWh/kWp (Figure 3). The wind atlas of Egypt indicates that the country enjoys high wind energy potential, with wind speeds ranging approximately between 3.5 and 9.0 m/s in some areas (Figure 4). The tourism district considered in this study is located in a very promising area for exploiting PV and wind power systems, with a latitude of 25°27′ N and a longitude of 30°34′ E in Fayoum, Egypt. Solar irradiation and wind speed measurements for one year at 15 m above the surface of the Earth for the location of the selected load were sourced from the measurement station installed at Fayoum town. Figure 5 shows the average monthly global horizontal sun irradiance at the power plant’s location, consistently exceeding 5.0 kWh/m2/day in almost all months of the year. Figure 6 shows that the atmospheric clearness index of Fayoum town has a value greater than 50% in all months of the year. The average monthly wind speed ranges between 3.21 m/s and 5.9 m/s at a 15 m hub height (Figure 7).

2.4. Design of Proposed Energy System

The paper considers grid-connected hybrid renewable energy systems (HRESs) comprising PV panels and wind turbines (WTs). Figure 8 illustrates the layout of the suggested hybrid model integrated with the primary load and EV charging station. The technical and economic data of the system components are described in detail in Table 2 and are based on types available in the local market with high efficiency and reasonable prices [9].

3. Results and Discussion

3.1. Energy Potential of the Optimal System Configuration

This paper proposes a centralized distributed grid-connected HRES to power a group of five hotels located in the same area. The total electrical load is estimated at 1.7 GWh/yr. The system boundary condition is set to a 1.0 MW PV system and five wind turbines based on the available space for establishing the HRES. The simulation results show that the optimal HRES comprises 420 kW of PV and five wind turbines with a specified rating of 20 kW, both integrated with the utility grid. Table 3 presents the performance results of the PV and wind turbines. It can be observed from this table that the PV system operates for 4384 h per year, indicating approximately 12 h of sunshine per day. The results also show that the wind turbines operate for 7762 h per year, highlighting the attractiveness of this region for solar and wind energy applications. The comprehensive performance data for the optimal system configurations are presented in Figure 9. The optimal HRES is capable of generating 1.2 GWh/yr of electric energy through PV and wind turbines, achieving a total renewable energy fraction of 58%. The amount of energy purchased is estimated to be 844 MWh/yr, accounting for 42% of the required electric energy. The amount of energy sold is estimated to be 291 MWh/yr.

3.2. EV Charging Station

The simulation results reveal that the proposed optimal system configuration allows for the charging of 10,072 sessions per year and an average of 27.6 sessions per day for EVs, with only 2.4 missed sessions per day. Table 4 presents the results for the EV charging stations. The energy required for charging EVs is estimated at 65,343 kWh/yr, with the amount of energy needed to charge one EV calculated as 6.49 kWh. The charging time required for EVs to be fully charged is estimated at seven hours. The number of chargers within the EV charging stations of the proposed system is estimated to be ten.

3.3. Cost Analysis

The cost analysis of the HRESs has been evaluated based on all expenses associated with installing, operating, and maintaining such systems and compared to the benefits they provide. Table 5 suggests that the proposed HRES integrated with an EV charging station is economically beneficial. The HRES appears to generate electricity at a lower cost than the current grid system and has a lower overall net present cost. Additionally, the system is expected to provide substantial electricity bill savings over time. The financial performance indicators of the proposed HRES are as follows:
  • The levelized cost of energy (LCOE) of the HRES is a crucial metric used to evaluate the long-term economic viability of such a system. It represents the average cost of electricity generated by the HRES over its operational lifespan, considering factors such as initial capital investment, operating and maintenance expenses, fuel costs, and system lifetime. The estimated LCOE of the proposed HRES was USD 0.042/kWh, which is lower than the electricity price of USD 0.07/kWh in Egypt. This provides insights into the competitiveness of HRES in the energy market.
  • The net present cost (NPC) of the proposed system is estimated at USD 3.0 million. This refers to the total cost of integrating the HRES, which is lower than the overall cost of the current grid system, estimated at USD 4.4 million.
  • Utility bill savings are estimated at USD 67.2 k/yr, representing the annual savings on electricity bills per year.
  • The net present utility bill savings are estimated at USD 2.54 million. This value likely represents the total discounted value of electricity bill savings over the lifetime of the HRES.
  • The table reveals that the projected payback period for the proposed system is approximately 11.8 years. This signifies that it will take roughly 11.8 years for the total savings or profits generated by the system to offset the initial investment required for installation and operation. Following the completion of the payback period, the system is anticipated to yield net positive returns or savings.

3.4. Environmental Analysis

In this section, we discuss the environmental implications of Egypt’s reliance on fossil fuel electricity generation and the potential benefits of implementing the proposed renewable energy system. Fossil fuel electricity generation in Egypt has significant environmental consequences, particularly in terms of greenhouse gas emissions (GHGs). The current CO2 emission factor (EF) for Egypt’s power system is reported as 431 g CO2/kWh emitted.
The results highlight the potential reduction, or mitigation, in GHG emissions that could result from implementing the proposed energy system. By transitioning to renewable energy sources, like solar and wind power, the system could substantially decrease CO2 emissions. Specifically, the estimated reduction in environmental emissions could reach up to 510 tons of CO2 per year. Additionally, the results emphasize the potential impact on fossil fuel consumption. It is indicated that adopting the proposed renewable energy system could lead to a decrease in fossil fuel usage by 248 tons of oil equivalent (toe) per year. This reduction in fossil fuel consumption is significant for reducing reliance on non-renewable energy sources and mitigating associated environmental impacts, such as air pollution and carbon emissions.

3.5. Sensitivity Analysis

The charging price of electric vehicles has significant implications for revenue generation and the economic viability of EV-related investments. Balancing affordability for consumers with the need for sustainable revenue streams is crucial for the long-term success of EV adoption and charging infrastructure deployment. However, as Egypt is still in the early stages of EV adoption, the EV charging price has not yet been determined. Therefore, it is crucial to study the sensitivity of the EV charging price to the total net present value (NPV) of the project. In this study, a sensitivity analysis of the charging price of electric vehicles (EVs) on the NPV is conducted to assess the impact of varying charging prices on the financial viability of the project. By examining the influence of charging prices on NPV, stakeholders can make more informed decisions about the economic feasibility and sustainability of the EV charging project. Figure 10 illustrates the results of the sensitivity analysis of the charging price against the NPV. In this study, we examine the change in charging price for prices equal to and greater than the electricity price in Egypt. The range of charging prices is from USD 0.07 to USD 1.5 per kWh. The results indicate that increasing charging prices leads to an increase in project profitability. After the charging price reaches USD 1.5 per kWh, the NPV becomes a positive value. This suggests that the charging price has a significant impact on the economic feasibility of the project.

4. Conclusions

This research aims to explore the performance of electric charging stations powered by renewable energy to serve an energy-consuming district, with the goal of decarbonizing this district in a promising area of Egypt. A simulation modeling approach was adopted to assess the performance of the proposed system. The research has yielded positive results from technical, economic, and environmental perspectives. The proposed hybrid energy system has the potential to save utility bills by USD 67,000 per year, with renewable energy contributing 58% and the power grid 42%. The levelized cost of electricity (LCOE) for the proposed hybrid power system, at USD 0.042 per kWh, is highly competitive with Egypt’s conventional electricity price of USD 0.07 per kWh. The results indicate that implementing the proposed energy system for electricity production could reduce environmental emissions by up to 510 tons of CO2 per year and decrease fossil fuel usage by 248 tons of oil equivalent per year. The study underscores the significant impact of charging prices on the economic viability of the project. Future research directions could investigate further the economic aspects of EV charging stations, considering factors such as pricing models, consumer behavior, and potential incentives or subsidies that may affect the financial viability of these projects. Additionally, given the evolving global renewable energy policy landscape and efforts to combat climate change, future research can explore the regulatory and policy implications of implementing hybrid renewable energy systems with EV charging infrastructure. Understanding how supportive policies or regulatory frameworks can facilitate widespread adoption of such projects will be critical to their long-term success.
Finally, although the topic of this study is focused on tourist areas, it can serve as a guide for researchers in this field and is applicable in various sectors, including tourism, the building sector, and those examining the integration of renewable energy stations with electrical charging stations. The results of this study rely on certain characteristics specific to its application site, such as electricity prices, renewable energy resources, solar radiation, and wind speed. Therefore, it can be beneficial for implementation in different locations worldwide, provided that these location-specific factors are taken into account. Moreover, the paper has introduced the simulation modeling approach that can be employed to optimally design hybrid renewable energy systems integrated with EV charging stations for tourism and other applications.

Author Contributions

Conceptualization, A.S. and S.A.; methodology, A.S. and S.A.; software, S.A.; validation, A.S. and S.A.; formal analysis, A.S. and S.A.; investigation, A.S. and S.A.; resources, A.S.; data curation, S.A.; writing—original draft preparation, S.A.; writing—review and editing, A.S. and S.A.; visualization, A.S. and S.A.; supervision, A.S. and S.A.; project administration, A.S. and S.A.; funding acquisition, A.S. and S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Lindstad, E.; Ask, T.Ø.; Cariou, P.; Eskeland, G.S.; Rialland, A. Wise use of renewable energy in transport. Transp. Res. Part D Transp. Environ. 2023, 119, 103713. [Google Scholar] [CrossRef]
  2. Lashari, Z.A.; Ko, J.; Jang, J. Consumers’ Intention to Purchase Electric Vehicles: Influences of User Attitude and Perception. Sustainability 2021, 13, 6778. [Google Scholar] [CrossRef]
  3. Miah, M.S.; Lipu, M.S.H.; Meraj, S.T.; Hasan, K.; Ansari, S.; Jamal, T.; Masrur, H.; Elavarasan, R.M.; Hussain, A. Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends. Sustainability 2021, 13, 12800. [Google Scholar] [CrossRef]
  4. Wu, X.; Chen, J.; Hu, C. Dynamic programming-based energy management system for range-extended electric bus. Math. Probl. Eng. 2015, 2015, 624649. [Google Scholar] [CrossRef]
  5. Peeters, P.; Çakmak, E.; Guiver, J. Current issues in tourism: Mitigating climate change in sustainable tourism research. Tour. Manag. 2024, 100, 104820. [Google Scholar] [CrossRef]
  6. Liu, J.; Zhuge, C.; Tang, J.H.C.G.; Meng, M.; Zhang, J. A spatial agent-based joint model of electric vehicle and vehicle-to-grid adoption: A case of Beijing. Appl. Energy 2022, 310, 118581. [Google Scholar] [CrossRef]
  7. Brdulak, A.; Chaberek, G.; Jagodziński, J. BASS Model Analysis in ‘Crossing the Chasm’ in E-Cars Innovation Diffusion Scenarios. Energies 2021, 14, 3216. [Google Scholar] [CrossRef]
  8. Nikiforiadis, A.; Ayfantopoulou, G.; Basbas, S.; Stefanidou, M. Examining tourists’ intention to use electric vehicle-sharing services. Transp. Res. Interdiscip. Perspect. 2022, 14, 100610. [Google Scholar] [CrossRef]
  9. Abdelhady, S. Techno-economic study and the optimal hybrid renewable energy system design for a hotel building with net zero energy and net zero carbon emissions. Energy Convers. Manag. 2023, 289, 117195. [Google Scholar] [CrossRef]
  10. Reddy, V.J.; Hariram, N.P.; Maity, R.; Ghazali, M.F.; Kumarasamy, S. Sustainable Vehicles for Decarbonizing the Transport Sector: A Comparison of Biofuel, Electric, Fuel Cell and Solar-Powered Vehicles. World Electr. Veh. J. 2024, 15, 93. [Google Scholar] [CrossRef]
  11. Ihm, J.; Amghar, B.; Chun, S.; Park, H. Optimum Design of an Electric Vehicle Charging Station Using a Renewable Power Generation System in South Korea. Sustainability 2023, 15, 9931. [Google Scholar] [CrossRef]
  12. AlHammadi, A.; Al-Saif, N.; Al-Sumaiti, A.S.; Marzband, M.; Alsumaiti, T.; Heydarian-Forushani, E. Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates. Energies 2022, 15, 6621. [Google Scholar] [CrossRef]
  13. Wang, M.; Dong, X.; Zhai, Y. Optimal configuration of the integrated charging station for PV and hydrogen storage. Energies 2021, 14, 7087. [Google Scholar] [CrossRef]
  14. Al Wahedi, A.; Bicer, Y. Techno-economic optimization of novel stand-alone renewables-based electric vehicle charging stations in Qatar. Energy 2022, 243, 123008. [Google Scholar] [CrossRef]
  15. Allouhi, A.; Rehman, S. Grid-connected hybrid renewable energy systems for supermarkets with electric vehicle charging platforms: Optimization and sensitivity analyses. Energy Rep. 2023, 9, 3305–3318. [Google Scholar] [CrossRef]
  16. Turkdogan, S. Design and optimization of a solely renewable based hybrid energy system for residential electrical load and fuel cell electric vehicle. Eng. Sci. Technol. Int. J. 2021, 24, 397–404. [Google Scholar] [CrossRef]
  17. Bilal, M.; Ahmad, F.; Rizwan, M. Techno-economic assessment of grid and renewable powered electric vehicle charging stations in India using a modified metaheuristic technique. Energy Convers. Manag. 2023, 284, 116995. [Google Scholar] [CrossRef]
  18. Khan, S.; Sudhakar, K.; Yusof, M.H.B. Building integrated photovoltaics powered electric vehicle charging with energy storage for residential building: Design, simulation, and assessment. J. Energy Storage 2023, 63, 107050. [Google Scholar] [CrossRef]
  19. Muna, Y.B.; Kuo, C.C. Feasibility and Techno-Economic Analysis of Electric Vehicle Charging of PV/Wind/Diesel/Battery Hybrid Energy System with Different Battery Technology. Energies 2022, 15, 4364. [Google Scholar] [CrossRef]
  20. Karmaker, A.K.; Ahmed, M.R.; Hossain, M.A.; Sikder, M.M. Feasibility assessment & design of hybrid renewable energy based electric vehicle charging station in Bangladesh. Sustain. Cities Soc. 2018, 39, 189–202. [Google Scholar] [CrossRef]
  21. Hassan, N.M.; Abdellatif, S.O. Assessing Centralized and Decentralized EV Charging Schemes using PV-Grid Connected System, Case Study in Egypt. In Proceedings of the 2021 International Conference on Microelectronics (ICM), Cairo, Egypt, 19–22 December 2021; pp. 232–235. [Google Scholar] [CrossRef]
  22. Enany, M.A.; Farahat, M.A.; Otay, M.I. Optimal Design and Operation of Fast Charging Station for Electric Vehicle Via Renewable Energy in Wadi El-Natrun-El Alamein Road, Egypt. Int. J. Sustain. Energy Environ. Res. 2021, 10, 38–46. [Google Scholar] [CrossRef]
  23. Tostado-Véliz, M.; Kamel, S.; Hasanien, H.M.; Arévalo, P.; Turky, R.A.; Jurado, F. A stochastic-interval model for optimal scheduling of PV-assisted multi-mode charging stations. Energy 2022, 253, 124219. [Google Scholar] [CrossRef]
  24. Ghatak, A.; Alfred, R.B.; Singh, R.R. Optimization for Electric Vehicle Charging Station using Homer Grid. In Proceedings of the 2021 Innovations in Power and Advanced Computing Technologies (i-PACT), Kuala Lumpur, Malaysia, 27–29 November 2021. [Google Scholar] [CrossRef]
  25. Shafiq, A.; Iqbal, S.; Ali, S.D.; Rehman, A.U.; Ali, M.; Iqbal, R.T.; Usman, M. Economic and environmental analysis for different scenarios of grid-connected Solar PV-based EV charging Station facility using Homer Grid. In Proceedings of the ICETECC 2022—International Conference on Emerging Technologies in Electronics, Computing and Communication, Jamshoro, Pakistan, 7–9 December 2022. [Google Scholar] [CrossRef]
  26. Global Solar Atlas. Available online: https://globalsolaratlas.info/download/egypt (accessed on 13 December 2023).
  27. Global Wind Atlas. Available online: https://globalwindatlas.info/en/area/Egypt (accessed on 13 December 2023).
Figure 1. Proposed system architecture of HRES integrated EV charging station.
Figure 1. Proposed system architecture of HRES integrated EV charging station.
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Figure 2. Seasonal (winter (A) and summer (B)) daily electric load curves in kW for the primary electricity load.
Figure 2. Seasonal (winter (A) and summer (B)) daily electric load curves in kW for the primary electricity load.
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Figure 3. Map of photovoltaic power potential in Egypt [26]. The map is sourced from Global Solar Atlas (https://globalsolaratlas.info/download/egypt) accessed on 22 May 2024.
Figure 3. Map of photovoltaic power potential in Egypt [26]. The map is sourced from Global Solar Atlas (https://globalsolaratlas.info/download/egypt) accessed on 22 May 2024.
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Figure 4. Map of wind speed at 10 m above surface level in Egypt [27]. The map is sourced from Global Wind Atlas (https://globalwindatlas.info/en/area/Egypt) accessed on 22 May 2024.
Figure 4. Map of wind speed at 10 m above surface level in Egypt [27]. The map is sourced from Global Wind Atlas (https://globalwindatlas.info/en/area/Egypt) accessed on 22 May 2024.
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Figure 5. The average monthly global horizontal sun irradiance in kWh/m2/day in Fayoum town.
Figure 5. The average monthly global horizontal sun irradiance in kWh/m2/day in Fayoum town.
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Figure 6. The clearness index of the proposed HRES location (Fayoum town).
Figure 6. The clearness index of the proposed HRES location (Fayoum town).
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Figure 7. Monthly average wind speed in Fayoum town at a 15 m hub height.
Figure 7. Monthly average wind speed in Fayoum town at a 15 m hub height.
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Figure 8. Schematic diagram of the proposed energy system.
Figure 8. Schematic diagram of the proposed energy system.
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Figure 9. The comprehensive performance data for the optimal system configurations.
Figure 9. The comprehensive performance data for the optimal system configurations.
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Figure 10. The results of the sensitivity analysis of the charging price against NPV.
Figure 10. The results of the sensitivity analysis of the charging price against NPV.
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Table 1. Technical data of EV charging station.
Table 1. Technical data of EV charging station.
No of EV Population 30
Max charge power per EV (kW)6.6
Required charge energy per EV (kWh)6.5
Charger output power (kW)10
No. of charger 10
Scaled avg sessions/day 30
Time connected hours7
Charging price (USD/kWh)0.07
Table 2. The technical and economic data of the system components.
Table 2. The technical and economic data of the system components.
PV
PV moduleSuntech 325
Panel type Flat plate
Maximum power325 W
Cell efficiency15%
Temperature coefficient−0.4%/K
Degrading factor85%
Orientation angel30°
Lifetime25 years
Capital expenditure950 USD/kW
Replacement cost100% of capital cost
O&M cost23 USD/year
Wind Turbine
Wind turbine modelEocycle EO20
Axis eype Horizontal axis
Rated power20 kW
Rotor diameter length15.8 m
Hub height 36 m
Wind speed (Cut-in)2.7 m/s
Wind speed (Cut-out)20 m/s
Lifetime25 years
Capital expenditureUSD 29,400
Replacement cost50% of capital cost
O&M cost880 USD/year
Table 3. The electricity generation summary of PV and wind turbines.
Table 3. The electricity generation summary of PV and wind turbines.
QuantityPVWind TurbinesUnits
Minimum output00kW
Maximum output394100kW
Penetration 44.229.6%
Hours of operation43847762Hours/yr
Capacity factor20.256.4%
Total production737494MWh/yr
LCOE0.030.02USD/kWh
Table 4. EV charging station results.
Table 4. EV charging station results.
Charging StationSessions per YearAnnual Energy Served (kWh)Energy per Session (kWh)Sessions per Day
Deferrable EV charger10,07265,3436.4927.6
Table 5. The economic results of the proposed system configurations.
Table 5. The economic results of the proposed system configurations.
System ArchitecturePV/Wind/Grid
LCOE (USD/kWh)0.042
NPC of HRES (MUSD)3.0
NPC of the base system (MUSD) 4.4
Utility bill savings (kUSD/yr)67.2
Net present utility bill savings (MUSD)2.54
Payback time11.8 years
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Abdelhady, S.; Shaban, A. A Simulation Modeling Approach for the Techno-Economic Analysis of the Integration of Electric Vehicle Charging Stations and Hybrid Renewable Energy Systems in Tourism Districts. Appl. Sci. 2024, 14, 4525. https://doi.org/10.3390/app14114525

AMA Style

Abdelhady S, Shaban A. A Simulation Modeling Approach for the Techno-Economic Analysis of the Integration of Electric Vehicle Charging Stations and Hybrid Renewable Energy Systems in Tourism Districts. Applied Sciences. 2024; 14(11):4525. https://doi.org/10.3390/app14114525

Chicago/Turabian Style

Abdelhady, Suzan, and Ahmed Shaban. 2024. "A Simulation Modeling Approach for the Techno-Economic Analysis of the Integration of Electric Vehicle Charging Stations and Hybrid Renewable Energy Systems in Tourism Districts" Applied Sciences 14, no. 11: 4525. https://doi.org/10.3390/app14114525

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