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19 pages, 4781 KiB

Open AccessArticle

The Impact of Ambient Weather Conditions and Energy Usage Patterns on the Performance of a Domestic Off-Grid Photovoltaic System

by Iviwe Mcingani, Edson L. Meyer and Ochuko K. Overen

Energies 2024, 17(19), 5013; https://doi.org/10.3390/en17195013 - 9 Oct 2024

Cited by 1 | Viewed by 923

Abstract

Solar photovoltaic (PV) systems are growing rapidly as a renewable energy source. Evaluating the performance of a PV system based on local weather conditions is crucial for its adoption and deployment. However, the current IEC 61724 standard, used for assessing PV system performance, [...] Read more.

Solar photovoltaic (PV) systems are growing rapidly as a renewable energy source. Evaluating the performance of a PV system based on local weather conditions is crucial for its adoption and deployment. However, the current IEC 61724 standard, used for assessing PV system performance, is limited to grid-connected systems. This standard may not accurately reflect the performance of off-grid PV systems. This study aims to evaluate how ambient weather conditions and energy usage patterns affect the performance of an off-grid PV system. This study uses a 3.8 kWp building-integrated photovoltaic (BIPV) system located at SolarWatt Park, University of Fort Hare, Alice, as a case study. Meteorological and electrical data from August and November are analyzed to assess the winter and summer performance of the BIPV system using the IEC 61724 standard. The BIPV system generated 376.29 kWh in winter and 366.38 kWh in summer, with a total energy consumption of 209.50 kWh in winter and 236.65 kWh in summer. Solar irradiation during winter was 130.18 kWh/m², while it was 210.24 kWh/m² during summer. The average daily performance ratio (PR) was 44.01% in winter and 28.94% in summer. The observed decrease in PR during the summer month was attributed to the higher levels of solar irradiance experienced during this time, which outweighs the increased AC energy output. The low-performance ratio does not indicate technical issues but rather a mismatch between the load demand and PV generation. The results of this study highlight the need for a separate method to assess the performance of off-grid PV systems. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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28 pages, 16028 KiB

Open AccessEditor’s ChoiceArticle

Open-Source Internet of Things-Based Supervisory Control and Data Acquisition System for Photovoltaic Monitoring and Control Using HTTP and TCP/IP Protocols

by Wajahat Khalid, Mohsin Jamil, Ashraf Ali Khan and Qasim Awais

Energies 2024, 17(16), 4083; https://doi.org/10.3390/en17164083 - 16 Aug 2024

Cited by 1 | Viewed by 4314

Abstract

This study presents a cost-effective IoT-based Supervisory Control and Data Acquisition system for the real-time monitoring and control of photovoltaic systems in a rural Pakistani community. The system utilizes the Blynk platform with Arduino Nano, GSM SIM800L, and ESP-32 microcontrollers. The key components [...] Read more.

This study presents a cost-effective IoT-based Supervisory Control and Data Acquisition system for the real-time monitoring and control of photovoltaic systems in a rural Pakistani community. The system utilizes the Blynk platform with Arduino Nano, GSM SIM800L, and ESP-32 microcontrollers. The key components include a ZMPT101B voltage sensor, ACS712 current sensors, and a Maximum Power Point Tracking module for optimizing power output. The system operates over both Global System for Mobile Communications and Wi-Fi networks, employing universal asynchronous receiver–transmitter serial communication and using the transmission control protocol/Internet protocol and hypertext transfer protocol for data exchange. Testing showed that the system consumes only 3.462 W of power, making it highly efficient. With an implementation cost of CAD 35.52, it offers an affordable solution for rural areas. The system achieved an average data transmission latency of less than 2 s over Wi-Fi and less than 5 s over GSM, ensuring timely data updates and control. The Blynk 2.0 app provides data retention capabilities, allowing users to access historical data for performance analysis and optimization. This open-source SCADA system demonstrates significant potential for improving efficiency and user engagement in renewable energy management, offering a scalable solution for global applications. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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27 pages, 6282 KiB

Open AccessFeature PaperArticle

Solar Energy Received on Flat-Plate Collectors Fixed on 2-Axis Trackers: Effect of Ground Albedo and Clouds

by Harry D. Kambezidis, Kosmas A. Kavadias and Ashraf M. Farahat

Energies 2024, 17(15), 3721; https://doi.org/10.3390/en17153721 - 28 Jul 2024

Viewed by 717

Abstract

This study investigates the performance of isotropic and anisotropic diffuse models to estimate the total solar energy received on flat-plate collectors fixed on dual-axis trackers. These estimations are applied at twelve sites selected in both hemispheres with different terrain and environmental conditions. The [...] Read more.

This study investigates the performance of isotropic and anisotropic diffuse models to estimate the total solar energy received on flat-plate collectors fixed on dual-axis trackers. These estimations are applied at twelve sites selected in both hemispheres with different terrain and environmental conditions. The diffuse (or transposition) models used in this study are the isotropic Liu-Jordan (L&J), Koronakis (KOR), Badescu (BAD), and Tian (TIA), and the anisotropic Hay (HAY), Reindl (REI), Klucher (KLU), Skartveit and Olseth (S&O), and Steven and Unsworth (S&U). These models were chosen because of their simplicity in the calculations and minimum number of input values. The results show that a single transposition model is not efficient for all sites; therefore, the most appropriate models are selected for each site under all, clear, intermediate, and overcast conditions in skies. On the other hand, an increase in the ground albedo in the vicinity of the solar installation can increase the annual inclined solar availability on a two-axis tracker by at least 9% on average. Further, a linear dependence of the annual inclined solar energy on the variation of the ground albedo was found. Also, a linear relationship exists between the annual diffuse-fraction and cloud-modification factor values at the 12 sites. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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17 pages, 523 KiB

Open AccessArticle

Global Energy Transition and the Efficiency of the Largest Oil and Gas Companies

by Sami Jarboui and Hind Alofaysan

Energies 2024, 17(10), 2271; https://doi.org/10.3390/en17102271 - 8 May 2024

Cited by 2 | Viewed by 1194

Abstract

The challenges posed by climate change and global warming loom large, necessitating a critical initial step towards the long-term growth and the enhancement of both environmental and operational efficiency. Within the energy sector, renewable energy sources are gaining increasing prominence. Consequently, traditional oil [...] Read more.

The challenges posed by climate change and global warming loom large, necessitating a critical initial step towards the long-term growth and the enhancement of both environmental and operational efficiency. Within the energy sector, renewable energy sources are gaining increasing prominence. Consequently, traditional oil and gas companies (OGC) are undergoing a gradual transformation into comprehensive energy corporations, aligning themselves with energy transition policies. This paper examines two types of efficiency measures—operational and environmental—for the 20 largest OGC during the period of 2010–2019. Secondly, this research aims to explore the effect of the global energy transition on both environmental and operational efficiency. Based on three estimation methods, two estimation steps are used in this research. In the first step, the True Fixed Effect (TFE) model and the Battese and coelli (1995) SFA model are applied to evaluate, measure and compare the environmental and operational efficiency scores. In the second step, the TFE model and GMM approach for the dynamic panel data model are used to explore, evaluate and verify the effect of global energy transition on the environmental and operational efficiency of the largest 20 OGC in the world. The results reveal that the average operational efficiency of major OGC measured using the BC.95 model and TFE model is 66% and 85%, respectively, and the overall average level of environmental efficiency for OGC over a 10-year period is 31% (based to B.C.95 model) and 13% (based to TFE model). Our findings reveal that biofuels, solar and hydropower contribute to promote the operational and environmental efficiency of the largest 20 OGC. However, the analysis suggests that while the global energy transition significantly influences and bolsters environmental efficiency, its effect on operational efficiency among these major OGC remains less pronounced and insufficient. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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13 pages, 2944 KiB

Open AccessCommunication

Comparative Analysis of Methods for Predicting Brine Temperature in Vertical Ground Heat Exchanger—A Case Study

by Joanna Piotrowska-Woroniak, Krzysztof Nęcka, Tomasz Szul and Stanisław Lis

Energies 2024, 17(6), 1465; https://doi.org/10.3390/en17061465 - 19 Mar 2024

Viewed by 1020

Abstract

This research was carried out to compare selected forecasting methods, such as the following: Artificial Neural Networks (ANNs), Classification and Regression Trees (CARTs), Chi-squared Automatic Interaction Detector (CHAID), Fuzzy Logic Toolbox (FUZZY), Multivariant Adaptive Regression Splines (MARSs), Regression Trees (RTs), Rough Set Theory [...] Read more.

This research was carried out to compare selected forecasting methods, such as the following: Artificial Neural Networks (ANNs), Classification and Regression Trees (CARTs), Chi-squared Automatic Interaction Detector (CHAID), Fuzzy Logic Toolbox (FUZZY), Multivariant Adaptive Regression Splines (MARSs), Regression Trees (RTs), Rough Set Theory (RST), and Support Regression Trees (SRTs), in the context of determining the temperature of brine from vertical ground heat exchangers used by a heat pump heating system. The subject of the analysis was a public building located in Poland, in a temperate continental climate zone. The results of this study indicate that the models based on Rough Set Theory (RST) and Artificial Neural Networks (ANNs) achieved the highest accuracy in predicting brine temperature, with the choice of the preferred method depending on the input variables used for modeling. Using three independent variables (mean outdoor air temperature, month of the heating season, mean solar irradiance), Rough Set Theory (RST) was one of the best models, for which the evaluation rates were as follows: CV RMSE 21.6%, MAE 0.3 °C, MAPE 14.3%, MBE 3.1%, and R² 0.96. By including an additional variable (brine flow rate), Artificial Neural Networks (ANNs) achieved the most accurate predictions. They had the following evaluation rates: CV RMSE 4.6%, MAE 0.05 °C, MAPE 1.7%, MBE 0.4%, and R² 0.99. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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19 pages, 9047 KiB

Open AccessArticle

Optimal Generation Dispatch in Electrical Microgrids Based on Inertia Markets as a Solution to Frequency Stability

by Luis Cruz, Alexander Águila Téllez and Leony Ortiz

Energies 2023, 16(22), 7500; https://doi.org/10.3390/en16227500 - 9 Nov 2023

Viewed by 1152

Abstract

This paper addresses a crucial omission in the traditional approach to solving the classic economic dispatch problem within microgrids featuring renewable energy sources—the often-neglected frequency disturbances arising from reductions in system inertia. To remedy this, we present an innovative economic dispatch model empowered [...] Read more.

This paper addresses a crucial omission in the traditional approach to solving the classic economic dispatch problem within microgrids featuring renewable energy sources—the often-neglected frequency disturbances arising from reductions in system inertia. To remedy this, we present an innovative economic dispatch model empowered by nonlinear optimization (NLP), incorporating stringent minimum inertia constraints essential for ensuring system stability over a 24-h horizon. Our approach involves a comprehensive exploration of the intricate relationship between system inertia and frequency stability, culminating in the seamless integration of these inertia constraints into the economic dispatch model. To validate the practicality of our model, we present two distinct scenarios: a base case representing conventional dispatch methodologies and an alternative case that considers the imposition of inertia restrictions. These scenarios are rigorously tested and implemented using the CICGRE TF C6.04 test system. Employing the powerful GAMS platform alongside the NPL model, we successfully solved the dispatch problem. Our results underscore the significance of maintaining system inertia within the 1.54-s threshold proposed by our model, showcasing a tangible reduction in generation costs as a direct outcome of this enhanced approach to economic dispatch. This research advances the understanding of microgrid management and offers a practical solution to enhance system stability and economic efficiency in renewable-energy-powered microgrids. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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Review

Jump to: Research

19 pages, 1952 KiB

Open AccessReview

Applications of Machine Learning Technologies for Feedstock Yield Estimation of Ethanol Production

by Hyeongjun Lim and Sojung Kim

Energies 2024, 17(20), 5191; https://doi.org/10.3390/en17205191 - 18 Oct 2024

Viewed by 549

Abstract

Biofuel has received worldwide attention as one of the most promising renewable energy sources. Particularly, in many countries such as the U.S. and Brazil, first-generation ethanol from corn and sugar cane has been used as automobile fuel after blending with gasoline. Nevertheless, in [...] Read more.

Biofuel has received worldwide attention as one of the most promising renewable energy sources. Particularly, in many countries such as the U.S. and Brazil, first-generation ethanol from corn and sugar cane has been used as automobile fuel after blending with gasoline. Nevertheless, in order to continuously increase the use of biofuels, efforts are needed to reduce the cost of biofuel production and increase its profitability. This can be achieved by increasing the efficiency of a sequential biofuel production process consisting of multiple operations such as feedstock supply, pretreatment, fermentation, distillation, and biofuel transportation. This study aims at investigating methodologies for predicting feedstock yields, which is the earliest step for stable and sustainable biofuel production. Particularly, this study reviews feedstock yield estimation approaches using machine learning technologies that focus on gradually improving estimation accuracy by using big data and computer algorithms from traditional statistical approaches. Given that it is becoming increasingly difficult to stably produce biofuel feedstocks as climate change worsens, research on developing predictive modeling for raw material supply using the latest ML techniques is very important. As a result, this study will help researchers and engineers predict feedstock yields using various machine learning techniques, and contribute to efficient and stable biofuel production and supply chain design based on accurate predictions of feedstocks. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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27 pages, 1933 KiB

Open AccessEditor’s ChoiceReview

Solar Radiation Forecasting: A Systematic Meta-Review of Current Methods and Emerging Trends

by Ewa Chodakowska, Joanicjusz Nazarko, Łukasz Nazarko and Hesham S. Rabayah

Energies 2024, 17(13), 3156; https://doi.org/10.3390/en17133156 - 26 Jun 2024

Cited by 4 | Viewed by 2639

Abstract

Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of this source of energy. The need to optimise energy systems, ensure power continuity, [...] Read more.

Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of this source of energy. The need to optimise energy systems, ensure power continuity, and balance energy supply and demand is driving the continuous development of forecasting methods and approaches based on meteorological data or photovoltaic plant characteristics. This article presents the results of a meta-review of the solar forecasting literature, including the current state of knowledge and methodological discussion. It presents a comprehensive set of forecasting methods, evaluates current classifications, and proposes a new synthetic typology. The article emphasises the increasing role of artificial intelligence (AI) and machine learning (ML) techniques in improving forecast accuracy, alongside traditional statistical and physical models. It explores the challenges of hybrid and ensemble models, which combine multiple forecasting approaches to enhance performance. The paper addresses emerging trends in solar forecasting research, such as the integration of big data and advanced computational tools. Additionally, from a methodological perspective, the article outlines a rigorous approach to the meta-review research procedure, addresses the scientific challenges associated with conducting bibliometric research, and highlights best practices and principles. The article’s relevance consists of providing up-to-date knowledge on solar forecasting, along with insights on emerging trends, future research directions, and anticipating implications for theory and practice. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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41 pages, 6824 KiB

Open AccessEditor’s ChoiceReview

Green Hydrogen Energy Systems: A Review on Their Contribution to a Renewable Energy System

by Julián Gómez and Rui Castro

Energies 2024, 17(13), 3110; https://doi.org/10.3390/en17133110 - 24 Jun 2024

Cited by 1 | Viewed by 2838

Abstract

Accelerating the transition to a cleaner global energy system is essential for tackling the climate crisis, and green hydrogen energy systems hold significant promise for integrating renewable energy sources. This paper offers a thorough evaluation of green hydrogen’s potential as a groundbreaking alternative [...] Read more.

Accelerating the transition to a cleaner global energy system is essential for tackling the climate crisis, and green hydrogen energy systems hold significant promise for integrating renewable energy sources. This paper offers a thorough evaluation of green hydrogen’s potential as a groundbreaking alternative to achieve near-zero greenhouse gas (GHG) emissions within a renewable energy framework. The paper explores current technological options and assesses the industry’s present status alongside future challenges. It also includes an economic analysis to gauge the feasibility of integrating green hydrogen, providing a critical review of the current and future expectations for the levelized cost of hydrogen (LCOH). Depending on the geographic location and the technology employed, the LCOH for green hydrogen can range from as low as EUR 1.12/kg to as high as EUR 16.06/kg. Nonetheless, the findings suggest that green hydrogen could play a crucial role in reducing GHG emissions, particularly in hard-to-decarbonize sectors. A target LCOH of approximately EUR 1/kg by 2050 seems attainable, in some geographies. However, there are still significant hurdles to overcome before green hydrogen can become a cost-competitive alternative. Key challenges include the need for further technological advancements and the establishment of hydrogen policies to achieve cost reductions in electrolyzers, which are vital for green hydrogen production. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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33 pages, 6478 KiB

Open AccessReview

Simulation and Modelling as Catalysts for Renewable Energy: A Bibliometric Analysis of Global Research Trends

by Ionuț Nica, Irina Georgescu and Nora Chiriță

Energies 2024, 17(13), 3090; https://doi.org/10.3390/en17133090 - 22 Jun 2024

Cited by 1 | Viewed by 1143

Abstract

This study investigates the application of advanced simulation and modeling technologies to optimize the performance and reliability of renewable energy systems. Given the urgent need to combat climate change and reduce greenhouse gas emissions, integrating renewable energy sources into existing infrastructure is essential. [...] Read more.

This study investigates the application of advanced simulation and modeling technologies to optimize the performance and reliability of renewable energy systems. Given the urgent need to combat climate change and reduce greenhouse gas emissions, integrating renewable energy sources into existing infrastructure is essential. Using bibliometric methods, our research spans from 1979 to 2023, identifying key publications, institutions, and trends. The analysis revealed a significant annual growth rate of 16.78% in interest in simulation and modeling, with a notable surge in published articles, reaching 921 in 2023. This indicates heightened research activity and interest. Our findings highlight that optimization, policy frameworks, and energy management are central themes. Leading journals like Energies, Energy, and Applied Energy play significant roles in disseminating research. Key findings also emphasize the importance of international collaboration, with countries like China, the USA, and European nations playing significant roles. The three-field plot analysis demonstrated interconnections between keywords, revealing that terms like “renewable energy sources”, “optimization”, and “simulation” are central to the research discourse. Core funding agencies, such as the National Natural Science Foundation of China (NSFC) and the European Union, heavily support this research. This study underscores the importance of policies and sustainability indicators in promoting renewable energy technologies. These insights emphasize the need for ongoing innovation and interdisciplinary collaboration to achieve a sustainable energy future. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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18 pages, 8068 KiB

Open AccessReview

Overview of Health and Safety Risks in the Process of Production and Storage of Forest Biomass for Energy Purposes—A Review

by Miloš Gejdoš and Martin Lieskovský

Energies 2024, 17(5), 1064; https://doi.org/10.3390/en17051064 - 23 Feb 2024

Cited by 1 | Viewed by 1151

Abstract

With increasing demands on the quality and quantity of produced biomass, as the main element of the knowledge-based economy, people and the issue of safety and health protection at work are coming to the fore. The aim of the work is the synthesis [...] Read more.

With increasing demands on the quality and quantity of produced biomass, as the main element of the knowledge-based economy, people and the issue of safety and health protection at work are coming to the fore. The aim of the work is the synthesis and overview of the results of the analysis of the health and safety risks of the production of forest biomass in various production phases, starting with its cultivation, through the harvesting production and transport process, up to the issue of its safe storage until it is used for the production of primary energy. Based on the analyzed overview of the existing risks in the production and storage of biomass, it can be concluded that the largest number of works is dedicated to the technological process of storage and consumption of the produced forms of biomass. Of the risks in this phase, the largest number of works is devoted to the risks of the production of spores of phytopathogens and fungi threatening human health. Further research should be primarily oriented toward creating models and modeling the processes of the emergence of these risk factors and the dynamics of their growth. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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34 pages, 9460 KiB

Open AccessReview

Innovative Industrial Solutions for Improving the Technical/Economic Competitiveness of Concentrated Solar Power

by Valeria Palladino, Marialaura Di Somma, Carmine Cancro, Walter Gaggioli, Maurizio De Lucia, Marco D’Auria, Michela Lanchi, Fulvio Bassetti, Carla Bevilacqua, Stefano Cardamone, Francesca Nana, Fabio Maria Montagnino and Giorgio Graditi

Energies 2024, 17(2), 360; https://doi.org/10.3390/en17020360 - 10 Jan 2024

Cited by 5 | Viewed by 2180

Abstract

The modernization, efficiency, and decarbonization of the energy supply systems are among the new challenges to be faced in the coming decades to achieve the targets and objectives dictated by European strategic policies. Despite the countless benefits related to renewable energy sources (RES) [...] Read more.

The modernization, efficiency, and decarbonization of the energy supply systems are among the new challenges to be faced in the coming decades to achieve the targets and objectives dictated by European strategic policies. Despite the countless benefits related to renewable energy sources (RES) integration, this brings key challenges to the power system, such as the risk of imbalance between energy generation and demand, sudden changes in flows in transmission lines with a need for expensive and time-consuming upgrades, and the withdrawal of conventional generation systems with consequent demands for new solutions and innovation to support grid services. A potential solution to limit the huge intermittence and fluctuation in power generation from RES is Concentrated Solar Power (CSP) technology integrated with thermal energy storage. The aim of this paper is to discuss the potential benefits related to the use of CSP technology by presenting innovative industrial solutions developed in the Italian SOLARGRID Project, namely the hybridization of CSP–PV systems and the solar thermo-electric system developed by MAGALDI, the parabolic trough collector of Eni, and the new linear Fresnel reflector configuration of IDEA S.r.l. These plant and component solutions are developed for improving the technical performance of CSP technology and reducing the levelized cost of electricity, thereby fostering an effective and massive deployment and encouraging the creation of new business models. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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13 pages, 2876 KiB

Open AccessReview

Simulation Modeling in Supply Chain Management Research of Ethanol: A Review

by Sojung Kim, Yeona Choi and Sumin Kim

Energies 2023, 16(21), 7429; https://doi.org/10.3390/en16217429 - 3 Nov 2023

Cited by 6 | Viewed by 1184

Abstract

Ethanol, a common renewable energy resource, can reduce greenhouse gas (GHG) emissions to resolve the problem of global warming worldwide. Various feedstocks such as corn, sugarcane, maize stover, and wheat straw can be utilized for ethanol production. They determine production operations and relevant [...] Read more.

Ethanol, a common renewable energy resource, can reduce greenhouse gas (GHG) emissions to resolve the problem of global warming worldwide. Various feedstocks such as corn, sugarcane, maize stover, and wheat straw can be utilized for ethanol production. They determine production operations and relevant costs. Although there are monetary incentives and government policies in different countries to increase ethanal use, it is still challenging to make its sales price competitive due to the inefficient supply chain of ethanol. Unlike fossil fuels such as coal, oil, and natural gas using a well-designed supply chain in the long history of mankind, additional efforts are needed to organize and stabilize the supply chain of ethanol efficiently. The goal of this study is to investigate how simulation modeling techniques can be applied to various supply chain management issues of ethanol. Particularly, application cases of three major simulation paradigms such as discrete-event simulation, system dynamics, and agent-based simulation are investigated by conducting a scientific literature review. The findings of this study will contribute to the expansion of simulation use in the field of biofuel supply chain management. Full article

(This article belongs to the Special Issue Simulation Modelling and Analysis of a Renewable Energy System, Volume II)

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