Cleaner Energy Systems最新文献_第7页

A SWOT Analysis Approach for the Development of Photovoltaic (PV) Energy in Northern Nigeria 尼日利亚北部光伏能源开发的 SWOT 分析方法

Cleaner Energy Systems Pub Date : 2024-07-24 DOI: 10.1016/j.cles.2024.100128

Anas A. Bisu , Tariq G. Ahmed , Umar S. Ahmad , Abubakar D. Maiwada

{"title":"A SWOT Analysis Approach for the Development of Photovoltaic (PV) Energy in Northern Nigeria","authors":"Anas A. Bisu , Tariq G. Ahmed , Umar S. Ahmad , Abubakar D. Maiwada","doi":"10.1016/j.cles.2024.100128","DOIUrl":"10.1016/j.cles.2024.100128","url":null,"abstract":"<div><p>This research employs a comprehensive Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis to investigate the advancement of photovoltaic (PV) energy in Northern Nigeria. The study delves into the intricacies of introducing PV systems within the context of economic challenges, including issues such as currency volatility and inflation, which amplify costs and impede capital investments. Environmental factors, such as dust and sandstorms, are identified as obstacles diminishing the efficiency of solar panels. Additionally, security concerns in remote areas elevate operational costs and influence investment decisions. This paper proposes effective mitigation strategies, encompassing widespread public awareness campaigns to augment market engagement, the establishment of mini-grid systems for enhanced energy distribution, customised on-the-job training programs to foster local expertise in PV technology, and the utilisation of micro-grid systems as experimental grounds for regulatory and policy testing. By synthesising these components, the study offers a comprehensive overview of the prerequisites essential for the successful proliferation of PV energy in Northern Nigeria. Emphasis is placed on the potential for solar energy to significantly contribute to the region's sustainable development and achieve energy independence when the identified strength, and opportunities are exploited. The key strength identified are the average Global horizontal irradiance (GHI) of 5.436 kWh/m<sup>2</sup>, Direct Normal Irradiance (DNI) of 1534–1680 kWh/m<sup>2</sup>, Levelised Cost of Electricity (LCoE) of $ 0.1, and an opportunity to fully utilise the over $ 7.88 million grant authorised by the African Development Bank (AfDB) from the Sustainable Energy Fund for Africa.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100128"},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000220/pdfft?md5=5ad76d8050fa4517244a11767e5a1f55&pid=1-s2.0-S2772783124000220-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141961799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing energy expenditure in agricultural autonomous ground vehicles through a GPU-accelerated particle swarm optimization-artificial neural network framework 通过 GPU 加速的粒子群优化-人工神经网络框架优化农业自主地面车辆的能源消耗

Cleaner Energy Systems Pub Date : 2024-07-24 DOI: 10.1016/j.cles.2024.100130

Ambuj, Rajendra Machavaram

{"title":"Optimizing energy expenditure in agricultural autonomous ground vehicles through a GPU-accelerated particle swarm optimization-artificial neural network framework","authors":"Ambuj, Rajendra Machavaram","doi":"10.1016/j.cles.2024.100130","DOIUrl":"10.1016/j.cles.2024.100130","url":null,"abstract":"<div><p>The accurate energy consumption prediction in Agricultural Ground Vehicles (AGVs) holds immense potential for optimizing operational efficiency and minimizing environmental impact. However, existing optimization methods for such prediction tasks often suffer from high computational demands, hindering their practical implementation. This paper introduces a ground-breaking approach that overcomes this limitation by leveraging the potent computational power of Graphics Processing Units (GPUs) to accelerate the optimization process dramatically. We propose a novel adaptation of the Particle Swarm Optimization (PSO) algorithm, specifically tailored to the intricate multi-objective challenges of AGV energy prediction. This framework harnesses the strengths of a multi-objective approach, enabling the simultaneous optimization of prediction accuracy and model complexity. To further enhance efficiency, we seamlessly integrate GPU parallelization techniques, significantly expediting both the optimization process and the training of Artificial Neural Networks (ANNs) employed for prediction. Preliminary results demonstrate a remarkable improvement in the accuracy of AGV energy consumption predictions, directly attributed to the synergistic effect of optimizing the ANN architecture and parameters through our proposed PSO framework. This tailored PSO adaptation distinguishes itself by its ability to tackle the complex multi-objective nature of AGV energy prediction with enhanced efficiency and precision. It thus emerges as a compelling and novel solution within the realm of Machine Learning and heuristic methods for agricultural robotics, paving the way for sustainable and optimal AGV operations.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"9 ","pages":"Article 100130"},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000244/pdfft?md5=95d29beea2a66736f8e26b5d92c843c0&pid=1-s2.0-S2772783124000244-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141852367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Techno-economic analysis and dynamic power simulation of a hybrid solar-wind-battery system for power supply in rural areas in Pakistan 用于巴基斯坦农村地区供电的太阳能-风能-电池混合系统的技术经济分析和动态功率模拟

Cleaner Energy Systems Pub Date : 2024-06-11 DOI: 10.1016/j.cles.2024.100127

Rafiq Ahmad , Hooman Farzaneh

{"title":"Techno-economic analysis and dynamic power simulation of a hybrid solar-wind-battery system for power supply in rural areas in Pakistan","authors":"Rafiq Ahmad , Hooman Farzaneh","doi":"10.1016/j.cles.2024.100127","DOIUrl":"10.1016/j.cles.2024.100127","url":null,"abstract":"<div><p>This study presents the optimal design and operation of a proposed hybrid renewable energy system (HRES) for the electrification of a residential building in rural areas in Pakistan. The main contributions of this study are twofold. Firstly, it develops a size optimization model based on the particle swarm optimization (PSO) technique to determine the optimal configuration for two hybrid renewable energy systems (HRES), including both grid-tied and off-grid modes, integrating wind and photovoltaic (PV) systems with battery storage. The optimal configuration is determined by minimizing the levelized cost of electricity, using local meteorological and electricity load data, along with technical specifications of the main HRES components. Secondly, dynamic simulations of two HRES configurations are conducted, using MATLAB Simulink, ensuring the optimal energy balance between multiple energy sources and the load at each operation hour. To meet an annual electrical demand of 131.035 MWh, the grid-tied HRES yields 146.081 MWh annually, with solar contributing 68.85 MWh and wind 77.272 MWh. Conversely, the off-grid system generates 133.533 MWh annually, with solar and wind output power at 43.932 MWh and 89.601 MWh, respectively. The grid-tied system achieves an LCOE of approximately 0.29 $/kWh, with optimal wind turbine and PV capacities of 11 kW and 29 kW, respectively. While in off-grid configuration, the off-grid scenario exhibits an LCOE of 0.91 $/kWh, with optimal capacities of 10 kW for wind turbine, 20 kW for PV, and 2437.5 AH for batteries. The findings provide insights relevant to diverse locations, emphasizing the importance of local meteorological and geographical data. Multiple case studies ensure the robustness and applicability of the proposed system under varying conditions.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100127"},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000219/pdfft?md5=e59e664382a1c7350082b74cc2fb9e65&pid=1-s2.0-S2772783124000219-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141392712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Can Sri Lanka be a net-zero nation by 2050?—Current renewable energy profile, opportunities, challenges, and recommendations 斯里兰卡能否在 2050 年前实现净零排放？- 可再生能源现状、机遇、挑战和建议

Cleaner Energy Systems Pub Date : 2024-06-03 DOI: 10.1016/j.cles.2024.100126

Isuru Koswatte , Janith Iddawala , Rekha Kulasekara , Praveen Ranaweera , Chamila H. Dasanayaka , Chamil Abeykoon

{"title":"Can Sri Lanka be a net-zero nation by 2050?—Current renewable energy profile, opportunities, challenges, and recommendations","authors":"Isuru Koswatte , Janith Iddawala , Rekha Kulasekara , Praveen Ranaweera , Chamila H. Dasanayaka , Chamil Abeykoon","doi":"10.1016/j.cles.2024.100126","DOIUrl":"10.1016/j.cles.2024.100126","url":null,"abstract":"<div><p>Sri Lanka as a country has tremendous potential for harnessing energy from renewable sources such as solar, wind, and hydro. However, as of 2018, only 39 % of Sri Lanka's energy generation capacity was harnessed through renewable energy sources. The continuous increase in electrical energy demand and the drastic increase in vehicle population over the past few years have resulted in much of its annual income being spent on purchasing fossil fuels from foreign countries. This has placed the country's future at risk due to the predicted shortage of fossil fuel reserves and in release of an unexpected level of harmful emissions to the environment. In the meantime, Sri Lanka also has an ambitious plan of achieving Net Zero by 2050. The study conducted a systematic review followed by a time series analysis to first identify the present state of the renewable energy progress of the country and through the time series analysis recognize any discrepancies in these efforts. The initial findings revealed the lack of coordination amongst relevant institutions and contrasting government policies such as the increase in investment for non-renewable energy resources as well as backing away from providing initial investment needed to boost the usage of renewable sources for businesses and smaller entities. The study further identified sectors such as transportation and non-renewable power generation activities as the two main barriers deterring the country from having a feasible plan for its efforts for net zero by 2050. From a non-governmental perspective, the study also recognized the knowledge gap and lack of awareness in the wider population of the long-term benefits of switching to renewable sources.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100126"},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000207/pdfft?md5=8b3024fab8dde436f2be5629ad0ea610&pid=1-s2.0-S2772783124000207-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141276350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of environmental dust accumulation on the performance and economics of solar energy systems: A comprehensive review 环境灰尘积累对太阳能系统性能和经济性的影响：综述

Cleaner Energy Systems Pub Date : 2024-05-20 DOI: 10.1016/j.cles.2024.100125

Abdullah Al-Sharafi , Ahmad Bilal Ahmadullah , Ghassan Hassan , Hussain Al-Qahtani , Abba Abdulhamid Abubakar , Bekir Sami Yilbas

{"title":"Influence of environmental dust accumulation on the performance and economics of solar energy systems: A comprehensive review","authors":"Abdullah Al-Sharafi , Ahmad Bilal Ahmadullah , Ghassan Hassan , Hussain Al-Qahtani , Abba Abdulhamid Abubakar , Bekir Sami Yilbas","doi":"10.1016/j.cles.2024.100125","DOIUrl":"10.1016/j.cles.2024.100125","url":null,"abstract":"<div><p>The growing energy demand in contemporary societies, coupled with the environmental detriments of conventional energy sources, necessitates a shift towards sustainable alternatives such as solar energy. However, the efficiency of solar energy systems is contingent upon various factors including surface orientation, tilt angle, geographic location, climatic conditions, solar irradiation, humidity, and temperature. Nevertheless, dust deposition on the active surfaces of solar energy systems remains the primary factor that highly impacts the system's energy yield, profitability, and efficiency. This paper provides a comprehensive review of the impact of environmental dust accumulation on the performance of solar energy systems that comprise photovoltaic, flat plate collectors, concentrating solar collectors, or solar chimneys. The objectives of this paper extend to consider economic consequences and the cleaning cost due to dust accumulation on the active surfaces of solar energy systems. The annual revenue loss due to dust accumulation was estimated at up to 35 % for 20 % of solar radiation reduction due to dust accumulation and the cleaning costs ranged from 0.016 to 0.9 $/m<sup>2</sup> worldwide, depending on system type, location, and cleaning technique. The present study offers distinctive perspectives on the topic and provide valuable information to policymakers, researchers, end-users, and stakeholders in the solar energy industry.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100125"},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000190/pdfft?md5=d3014e927afe332727f431dc2bfee5d5&pid=1-s2.0-S2772783124000190-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141130404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reducing energy consumption in a factory and providing an upgraded energy system to improve energy performance 降低工厂能耗，提供升级版能源系统，提高能源绩效

Cleaner Energy Systems Pub Date : 2024-05-04 DOI: 10.1016/j.cles.2024.100124

Armin Tayefeh, Alireza Aslani, Rahim Zahedi, Hossein Yousefi

{"title":"Reducing energy consumption in a factory and providing an upgraded energy system to improve energy performance","authors":"Armin Tayefeh, Alireza Aslani, Rahim Zahedi, Hossein Yousefi","doi":"10.1016/j.cles.2024.100124","DOIUrl":"https://doi.org/10.1016/j.cles.2024.100124","url":null,"abstract":"<div><p>The industrial sector is a major energy consumer worldwide. Much of this consumption is due to air conditioning systems. In regions with extreme temperature conditions, the electricity consumption of these air conditioning systems increases significantly. This study was carried out with the objective of calculating the total energy consumption of the factory and identifying methods to decrease it. Furthermore, an enhanced energy system is suggested to lower energy consumption. This study was carried out with the objective of calculating the total energy consumption of the factory and identifying methods to decrease it. Furthermore, an enhanced energy system is suggested to lower energy consumption. It is also evident that the cooling load decreases by 21,661 kWh when thermal insulation is applied to the walls. Utilizing double-glazed windows for the skylight roof can lead to a reduction in the cooling load by 822 kWh. Additionally, the use of Light-Emitting Diode (LED) bulb lamps in the factory can further decrease the cooling load by up to 14,717 kWh.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100124"},"PeriodicalIF":0.0,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000189/pdfft?md5=d3eb238ce55f4bf09490f5f561fe5213&pid=1-s2.0-S2772783124000189-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140880493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and eco-technoeconomic analysis of a natural gas cogeneration energy management center (EMC) with short-term thermal storage 带短期蓄热的天然气热电联产能源管理中心（EMC）的设计与生态技术经济分析

Cleaner Energy Systems Pub Date : 2024-04-20 DOI: 10.1016/j.cles.2024.100118

Nina Monteiro , Thomas A. Adams II , James Cotton

{"title":"Design and eco-technoeconomic analysis of a natural gas cogeneration energy management center (EMC) with short-term thermal storage","authors":"Nina Monteiro , Thomas A. Adams II , James Cotton","doi":"10.1016/j.cles.2024.100118","DOIUrl":"https://doi.org/10.1016/j.cles.2024.100118","url":null,"abstract":"<div><p>This work proposes a non-islanded cogeneration energy management center (EMC) that can be used to displace grid-level natural gas turbine systems and natural gas combustion systems for heat. The design of the proposed EMC included a weighted multi-objective optimization aimed at minimizing: i) natural gas consumption; ii) capital costs; iii) utility costs; and iv) unmet thermal demand. The decision variables consisted of the existence and capacity of the equipment comprising the EMC, including: i) a natural gas boiler; ii) an internal combustion engine that generates heat and electricity; and iii) a hot water thermal storage system. Four resulting candidates EMC designs were then compared with the status-quo (SQ) in an eco-technoeconomic analysis; The SQ draws electricity from the grid and heating for dwellings come from natural gas boilers. Emissions at grid level change which alternative is favored. The findings showed that, for a system that serves 4–5 dense urban city blocks over a 20-year lifetime, the SQ system had cumulative levelized costs of 9.6 million USD for the final consumer, while the levelized costs of the EMC designs ranged from 12.9 to 15.1 million USD. In terms of emissions, the SQ emitted 959 tonnes of CO<sub>2eq</sub> per year, while the EMC system produced around 500 tonnes of CO<sub>2eq</sub> per year depending on the year, yielding a CCA varying between 364 and 653 USD/tonneCO<sub>2eq</sub></p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100118"},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000128/pdfft?md5=df090e47f2669be2afb8d5229e3dbf76&pid=1-s2.0-S2772783124000128-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140650437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Systematic literature review of urban charging infrastructure planning over time 关于城市充电基础设施规划的系统文献回顾

Cleaner Energy Systems Pub Date : 2024-04-19 DOI: 10.1016/j.cles.2024.100123

Niklas Hildebrand, Sebastian Kummer

{"title":"Systematic literature review of urban charging infrastructure planning over time","authors":"Niklas Hildebrand, Sebastian Kummer","doi":"10.1016/j.cles.2024.100123","DOIUrl":"https://doi.org/10.1016/j.cles.2024.100123","url":null,"abstract":"<div><p>The transition from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs) is imperative to achieve the goal of reducing transport-related greenhouse gas emissions by 90 % in 2050. As urbanization intensifies, vehicle miles in urban environments increase and cities already consume 75 % of global energy, there is a pressing need for efficient charging infrastructure (CI) placement tailored to urban environments. Accordingly, this paper conducts a systematic literature review to outline prevailing research and derive requirements for a future CI model adaptable to urban environments. Analysis of <em>N</em> = 57 studies underscores the necessity for agent-based demand models to capture the intricate behaviors of EV drivers, which are currently underrepresented due to their data-heavy nature (<em>n</em> = 28 flow-based; <em>n</em> = 18 node-based). Furthermore, with a projected surge of 800 % in CI installations in Europe by 2030, strategic placement according to demand and urban-specific requirements is paramount. Still, multi-periodicity considerations are largely absent in current literature (<em>n</em> = 50). Geometric segmentation is presented as a solution to mitigate partial coverage issues. Ultimately, agent-based models, coupled with geometric segmentation, emerge as pivotal requirements for future CI models in urban environments, facilitating the transition to EVs, aligning with emission reduction targets, ensuring resource efficiency, and fostering urban sustainability.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100123"},"PeriodicalIF":0.0,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000177/pdfft?md5=f564588b9a3edaa49a60d35557bf467e&pid=1-s2.0-S2772783124000177-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140639315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy-saving effect assessment of various factors in container plant factories: A data-driven random forest approach 集装箱工厂各种因素的节能效果评估：数据驱动的随机森林方法

Cleaner Energy Systems Pub Date : 2024-04-17 DOI: 10.1016/j.cles.2024.100122

Kunlang Bu , Zhitong Yu , Dayi Lai , Hua Bao

{"title":"Energy-saving effect assessment of various factors in container plant factories: A data-driven random forest approach","authors":"Kunlang Bu , Zhitong Yu , Dayi Lai , Hua Bao","doi":"10.1016/j.cles.2024.100122","DOIUrl":"https://doi.org/10.1016/j.cles.2024.100122","url":null,"abstract":"<div><p>Plant factory is one of the controlled environment agriculture forms with huge potential to alleviate food crisis, but the high energy cost restricts its widespread adoption. Numerous researches have explored various factors for energy-saving in plant factories in their settings, but there is a lack of analysis of the importance of these factors in energy saving. In this work, the energy-saving effect assessment of various factors in the container plant factory is investigated. Four cities (Harbin, Taiyuan, Shanghai, and Guangzhou), three plant densities (cultivation area: floor area=100 %, 150 %, and 200 %), and two temperature/humidity setpoints (20/22 ℃, 60/70 %, and 16/22 ℃, 50/95 %) are selected as operating conditions to cover different weather conditions and plant heat loads. The energy-saving effect of each factor is calculated using a random forest algorithm based on large amounts of energy simulation data. We identify that envelope overall heat transfer coefficient (<em>U</em>), air conditioner coefficient of performance (COP), and light efficacy (Efficacy) are three factors that have the largest impact on energy-saving in plant factories, in which light efficacy is the most important factor. Simultaneous optimization of these three factors could possibly reduce electricity consumption by ∼50 % compared to the base case. Finally, employing weight-light intensity correlation, the minimum specific energy consumption is approximately 4.76 kWh/kg lettuce fresh weight. This study utilizes advanced machine learning methods to sort out important factors and shows that significant energy reduction may be achieved by optimizing dominant factors, which gives a general guidance for future designers to build energy-efficient plant factories.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100122"},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000165/pdfft?md5=a812a8511d6452c35a1004475ac526fc&pid=1-s2.0-S2772783124000165-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140632636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart car parks with EV charging for academic campus 为校园提供电动汽车充电的智能停车场

Cleaner Energy Systems Pub Date : 2024-04-16 DOI: 10.1016/j.cles.2024.100121

Shafiqur Rehman , Abdul Baseer Mohammed , Luai M. Alhems , Fahad A. Alsulaiman

{"title":"Smart car parks with EV charging for academic campus","authors":"Shafiqur Rehman , Abdul Baseer Mohammed , Luai M. Alhems , Fahad A. Alsulaiman","doi":"10.1016/j.cles.2024.100121","DOIUrl":"https://doi.org/10.1016/j.cles.2024.100121","url":null,"abstract":"<div><p>Energy is directly related to the economy and its demand would increase with development in the industrial, residential, transportation, and commercial sectors. It is projected that by 2050, the global energy demand will experience a two-fold increase. Currently, almost 85 % of the consumed energy globally is generated by burning non-renewable sources like oil, coal, and gas. Open car parking areas at universities, shopping malls, hospitals, etc. are unexploited areas that have enormous potential to generate renewable energy without disturbing the flora and fauna of the region. This study analyses the techno-economic feasibility of generating grid-connected energy using solar photovoltaic, PV panels on the parking lots of academic institutions and utilizes a part of it for charging the parked EVs . The best system is found to produce energy at a cost of 0.0529 USD/kWh, almost 54 % less compared to the grid. In the proposed design, 69 % of the total energy is produced by solar PV and almost 52.5 % is sold to the grid. The capacity factor of the PV system, at this location, is 19.8 %. The annual utility bill saving is around US $ 798,100. The internal rate of return and simple payback period are 7.35 % and 10.9 years. The proposed system architecture also caters to an EV charging capacity of 195 MWh, about 1.5 % of the total energy consumption, and a charging load of 578 kWh/day. This proposed PV energy system, for the parking areas, can be adopted in any other region with similar climatic conditions.</p></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"8 ","pages":"Article 100121"},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772783124000153/pdfft?md5=f07484282bfc2b2a0f52f0c58929abd8&pid=1-s2.0-S2772783124000153-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140620921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0