Search Results (46)

With the large-scale global deployment of photovoltaics (PV), traditional monitoring technologies face challenges such as wiring difficulties, high energy consumption, and high maintenance costs in remote or complex terrains, which limit long-term environmental sensing. Therefore, energy-harvesting systems are crucial for the intelligent operation of photovoltaic systems; however, their deployment depends on the accurate mapping of wind energy fields and solar irradiance fields. This study proposes a multi-scale simulation method based on computational fluid dynamics (CFD) to optimize the placement of energy-harvesting systems in photovoltaic power plants. By integrating wind and irradiance distribution analysis, the spatial characteristics of airflow and solar radiation are mapped to identify high-efficiency zones for energy harvesting. The results indicate that the top of the photovoltaic panel exhibits a higher wind speed and reflected irradiance, providing the optimal location for an energy-harvesting system. The proposed layout strategy improves overall energy capture efficiency, enhances sensor deployment effectiveness, and supports intelligent, maintenance-free monitoring systems. This research not only provides theoretical guidance for the design of energy-harvesting systems in PV stations but also offers a scalable method applicable to various geographic scenarios, contributing to the advancement of smart and self-powered energy systems. Full article

Solar photovoltaic (SPV) arrays play a pivotal role in advancing clean and sustainable energy systems, with a worldwide total installed capacity of 1.6 terawatts and annual investments reaching USD 480 billion in 2023. However, climate disaster effects, particularly extremely hot weather events, can compromise the performance and resilience of SPV panels through thermal deterioration and degradation, which may lead to lessened operational life and potential failure. These heatwave-related consequences highlight the need for timely inspection and precise anomaly diagnosis of SPV panels to ensure optimal energy production. This case study focuses on intelligent remote inspection by employing aerial radiometric infrared thermography within a predictive maintenance framework to enhance diagnostic monitoring and early scrutiny capabilities for SPV power plant sites. The proposed methodology leverages pre-trained deep learning (DL) algorithms, enabling a deep transfer learning approach, to test the effectiveness of multiclass classification (or diagnosis) of various thermal anomalies of the SPV panel. This case study adopted a highly imbalanced 6-class thermographic radiometric dataset (floating-point temperature numerical values in degrees Celsius) for training and validating the pre-trained DL predictive classification models and comparing them with a customized convolutional neural network (CNN) ensembled model. The performance metrics demonstrate that among selected pre-trained DL models, the MobileNetV2 exhibits the highest F1 score (0.998) and accuracy (0.998), followed by InceptionV3 and VGG16, which recorded an F1 score of 0.997 and an accuracy of 0.998 in performing the smart inspection of 6-class thermal anomalies, whereas the customized CNN ensembled model achieved both a perfect F1 score (1.000) and accuracy (1.000). Furthermore, to create trust in the intelligent inspection system, we investigated the pre-trained DL predictive classification models using perceptive explainability to display the most discriminative data features, and mathematical-structure-based interpretability to portray multiclass feature clustering. Full article

Energy is one of the essential human needs that plays a crucial role in achieving sustainable development. Indonesia is among the countries that are highly focused on developing renewable energy to reduce greenhouse gas emissions and achieve net-zero emissions. In addition, the government has launched various policies and programs to promote the use of renewable energy, such as increased investment in biomass, geothermal, and solar power generation. Wind energy stands out as a sufficient, widely available, and an environmentally friendly alternative in renewable energy. In 2021, the Indonesian Energy Outlook highlights that Indonesia has an energy potential of 154.9 gigawatts (GWs). It is associated with minimal emissions of greenhouse gases during its operation and does not demand vast tracts of land. However, the actual installed capacity of wind power plants is at a modest 157.41 megawatts (MWs). Meanwhile, the targeted capacity is 255 MWs for 2025. One significant factor contributing to this lower-than-expected capacity is a lack of in-depth research into the potential of wind energy. Consequently, the primary aim of this paper is to conduct a thorough examination of the wind energy potential in Indonesia. This includes an analysis of the current state of both existing and upcoming power plants, as well as a review of recent studies conducted by Indonesian researchers on wind turbines. Furthermore, this paper explores the government program to encourage the sustainable development of wind power plants. It also explains various aspects including the untapped wind energy potential, the interference in developing wind power plants, and the strategy to harness the full potential of abundant renewable resources in Indonesia. Through an in-depth investigation of the potential of wind energy, this review aims to provide a more comprehensive understanding of the current conditions and prospects of wind power plants in Indonesia as well as contribute to a more accurate mapping of wind energy potential and more targeted development, specifically in remote areas, outer islands, and borders. The results obtained are expected to support Indonesia’s energy transition toward more environmentally friendly and sustainable renewable energy sources, thereby reducing dependence on fossil fuels. Full article

Solar energy plays a crucial role in mitigating greenhouse gas emissions in the context of global climate change. However, its deployment for green electricity generation can significantly influence regional climate and vegetation dynamics. While prior studies have examined the impacts of solar power plants on vegetation, the accuracy of these assessments has often been constrained by the availability of publicly accessible multispectral, high-resolution remotely sensed imagery. Given the abundant solar energy resources and the ecological significance of the Tibetan Plateau, a thorough evaluation of the vegetation effects associated with solar power installations is warranted. In this study, we utilize sub-meter resolution imagery from the GF-2 satellite to reconstruct the fractional vegetation cover (FVC) at the Gonghe solar thermal power plant through image classification, in situ sampling, and sliding window techniques. We then quantify the plant’s impact on FVC by comparing data from the pre-installation and post-installation periods. Our findings indicate that the Gonghe solar thermal power plant is associated with a 0.02 increase in FVC compared to a surrounding control region (p < 0.05), representing a 12.5% increase relative to the pre-installation period. Notably, the enhancement in FVC is more pronounced in the outer ring areas than near the central tower. The observed enhancement in vegetation growth at the Gonghe plant suggests potential ecological and carbon storage benefits resulting from solar power plant establishment on the Tibetan Plateau. These findings underscore the necessity of evaluating the climate and ecological impacts of renewable energy facilities during the planning and design phases to ensure a harmonious balance between clean energy development and local ecological integrity. Full article

Wind–solar power generating and hybrid battery-supercapacitor energy storage complex is used for autonomous power supply of consumers in remote areas. This work uses passivity-based control (PBC) for this complex in accordance with the accepted energy management strategy (EMS). Structural and parametric synthesis of the overall PBC system was carried out, which was accompanied by a significant amount of research. In order to simplify this synthesis, a structural decomposition of the overall dynamic system of the object presented in the form of a port-Hamiltonian system, which was described by a system of differential equations of the seventh order, into three subsystems was applied. These subsystems are a wind turbine, a PV plant, and a hybrid battery-supercapacitor system. For each of the subsystems, it is quite simple to synthesize the control influence formers according to the interconnections and damping assignment (IDA) method of PBC, which locally performs the tasks set by the EMS. The results obtained by computer simulation of the overall and decomposed systems demonstrate the effectiveness of this approach in simplifying synthesis and debugging procedures of complex multi-physical systems. Full article

Growing environmental concerns have driven the installation of renewable systems. Meanwhile, the continuous decline in the levelized cost of energy (LCOE), alongside the decreasing cost of photovoltaics (PVs), is compelling the power sector to accurately forecast the performance of energy plants to maximize plant profitability. This paper presents a comprehensive analysis and optimization of a hybrid power generation system for a remote community in the Middle East and North Africa (MENA) region, with a 10 MW peak power demand. The goal is to achieve 90 percent of annual load coverage from renewable energy. This study introduces a novel comparison between three different configurations: (i) concentrated solar power (parabolic troughs + thermal energy storage + steam Rankine cycle); (ii) fully electric (PVs + wind + batteries); and (iii) an energy mix that combines both solutions. The research demonstrates that the hybrid mix achieves the lowest levelized cost of energy (LCOE) at 0.1364 USD/kWh through the use of advanced transient simulation and load-following control strategies. The single-technology solutions were found to be oversized, resulting in higher costs and overproduction. This paper also explores a reduction in the economic scenario and provides insights into cost-effective renewable systems for isolated communities. The new minimum cost of 0.1153 USD/kWh underscores the importance of integrating CSP and PV technologies to meet the very stringent conditions of high renewable penetration and improved grid stability. Full article

When operating solar–wind power plants (SWPPs) located in populated areas, cases of premature failure of expensive batteries and other power equipment often occur. The purpose of this study is to develop a wireless data acquisition system (DAS) for the operation of an SWPP with a feedback function to prevent material damage from the failure of power equipment and to increase the efficiency of natural energy use. The principles of constructing a DAS, free from some of the disadvantages of analogues, are described in this paper. Intelligent wireless current and voltage sensors and a device for receiving and recording data with an additional feedback function have been developed, providing real-time feedback when the measured parameters go outside the norm. Measurement data are displayed on the laptop screen and alphanumeric display and stored on the hard drive along with timestamps and current event messages. An example of using a reverse communication channel to implement the functions of backup battery protection and to switch SWPP loads is described. The principles and methods proposed in this article are suitable for constructing systems for remote measurements of any physical quantities; therefore, the scope of application of the described system can be significantly expanded. Full article

Solar photovoltaic (SPV) arrays are crucial components of clean and sustainable energy infrastructure. However, SPV panels are susceptible to thermal degradation defects that can impact their performance, thereby necessitating timely and accurate fault detection to maintain optimal energy generation. The considered case study focuses on an intelligent fault detection and diagnosis (IFDD) system for the analysis of radiometric infrared thermography (IRT) of SPV arrays in a predictive maintenance setting, enabling remote inspection and diagnostic monitoring of the SPV power plant sites. The proposed IFDD system employs a custom-developed deep learning approach which relies on convolutional neural networks for effective multiclass classification of defect types. The diagnosis of SPV panels is a challenging task for issues such as IRT data scarcity, defect-patterns’ complexity, and low thermal image acquisition quality due to noise and calibration issues. Hence, this research carefully prepares a customized high-quality but severely imbalanced six-class thermographic radiometric dataset of SPV panels. With respect to previous approaches, numerical temperature values in floating-point are used to train and validate the predictive models. The trained models display high accuracy for efficient thermal anomaly diagnosis. Finally, to create a trust in the IFDD system, the process underlying the classification model is investigated with perceptive explainability, for portraying the most discriminant image features, and mathematical-structure-based interpretability, to achieve multiclass feature clustering. Full article

The energy sector is the main source of greenhouse gases, so it has the highest potential for improvement. The improvements can be achieved by generating energy from renewable sources. It is necessary to combine production from renewable sources with storage systems. Thermal energy storage using concentrated solar power systems is a promising technology for dispatchable renewable energy that can guarantee a stable energy supply even in remote areas without contributing to greenhouse gas emissions during operation. However, it must be emphasised that greenhouse gases and other impacts can occur during the production process of concentrating solar system components. This paper analyses the receiver design to produce thermal energy for the existing CSP dish plant at the Energy Center of the Politecnico di Torino. The plant is designed to produce electrical energy in the spring and summer periods. In addition to this energy production, the CSP can be adopted to produce thermal energy, through hot water, during the less favourable periods of the year in terms of global solar radiation. The surface heat flux is calculated in the first part of the analysis to obtain the maximum internal temperature in the receiver, which is 873.7 °C. This value is a constraint for the choice of material for the solar receiver. A life cycle assessment is performed to compare the emissions generated during the production of the main components of the CSP system with the emissions generated by the methane-fuelled water heater to produce the same amount of thermal energy. It can be concluded that the production of the main components of the CSP system results in lower greenhouse gas emissions than the operational phase of a conventional system. Given the assumptions made, the utilization of methane leads to the emission of approximately 12,240 kg of CO₂, whereas the production of the CSP system results in emissions totalling 5332.8 kg of CO₂ equivalent Full article

In recent years, with the continuous growth in China’s economy, the continuous advancement of urbanization and industrialization, the contradiction between rapid economic development and the continuous reduction in traditional fossil energy reserves such as coal, oil, and natural gas, the continuous aggravation of environmental pollution has become increasingly prominent. In this era, clean energy power generation technologies such as hydropower, wind power, and solar power generation, which have the advantages of renewability, environmental protection, and economy, have developed rapidly. However, wind and photovoltaic power plants are often located in remote areas, which means significant losses in the transmission process. High-voltage direct current (HVDC) transmission technology becomes the best choice to solve this problem. The HVDC transmission system based on a grid commutator is widely used in China’s AC-DC hybrid power grid. When an AC fault occurs on the inverter side, the line-commutated converter high-voltage direct current (LCC-HVDC) system is more prone to continuous commutation failure, which brings serious harm to system operation. To better suppress the problem of continuous commutation failure on the contravariant side, this paper analyzes the mechanism of continuous commutation failure from multiple angles. The DC current command sensitivity of a voltage-dependent current order limiter (VDCOL) in the LCC-HVDC system is low, which will lead to different degrees of continuous commutation failure. In addition, the rapid rise in DC current and the drop in commutation voltage during the fault will cause the turn-off angle to drop, and the probability of continuous commutation failure of the system will increase significantly. Based on the above theoretical analysis, a new control strategy combining the dynamic compensation of the turn-off angle of a virtual inductor and the suppression of continuous commutation failure by dynamic nonlinear VDCOL is proposed. A dynamic nonlinear VDCOL control strategy is proposed for the low sensitivity of current command adjustment under conventional VDCOL control. Secondly, two concepts of virtual inductance and DC current change rate are introduced, and a control strategy based on virtual inductance is proposed to comprehensively ensure that the switching angle has sufficient commutation margin during fault recovery. Finally, based on the CIGRE standard test model in PSCAD/EMTDC, the accuracy of the correlation mechanism analysis and the effectiveness of the suppression method are verified. Full article

With a deficit of about 20 BCM in 2022, Egypt faces a severe water shortage due to rapid population growth (109.3 million in 2022). Egypt launched a program to utilize non-conventional water sources, like treated wastewater, agriculture drainage water, and desalination. Egypt is expanding its non-conventional water resources, boosting desalination capacity from 86,000 m³/day in 2015 to 680,000 m³/day in 2022, with plans to reach 1,250,000 m³/day by 2025. Despite the improvements in desalination technologies and cost, its high energy use and environmental impacts are still limiting its use. Egypt’s desalination relies on grid electricity, but renewable energy is crucial for remote areas where no electricity grid exists. Scaling up renewable energy in desalination faces challenges like land availability and high costs. GIS was used for optimal site selection for a brackish groundwater solar desalination plant in the Western North Nile Delta. Factors like solar radiation, groundwater quality, aquifer potentiality, geology, and seawater intrusion were carefully assessed. An evaluation of a sustainable 1000 m³/day solar-powered RO desalination pilot plant’s economic and technical viability is provided, along with its performance assessment. Limitations, challenges, and potential improvements are discussed. The study finds that RO–PV desalination for brackish groundwater is technically mature, with competitive Capex costs (USD 760-USD 850/m³) and low Opex (USD 0.55–USD 0.63/m³). Solar desalination for brackish groundwater with salinity less than 23,000 ppm can reduce energy consumption to 3.6–4.2 kWhr/m³. Water storage and hybrid systems with solar and conventional energy are suggested to enhance efficiency. This implies a growing market for small- to medium-scale RO solar-powered desalination in remote areas in the near future. Full article

Operations and maintenance (O&M) of floating offshore wind turbines (FOWTs) require regular inspection activities to predict, detect, and troubleshoot faults at high altitudes and in harsh environments such as strong winds, waves, and tides. Their costs typically account for more than 30% of the lifetime cost due to high labor costs and long downtime. Different inspection methods, including manual inspection, permanent sensors, climbing robots, remotely operated vehicles (ROVs), and unmanned aerial vehicles (UAVs), can be employed to fulfill O&M missions. The UAVs, as an enabling technology, can deal with time and space constraints easily and complete tasks in a cost-effective and efficient manner, which have been widely used in different industries in recent years. This study provides valuable insights into the existing applications of UAVs in FOWT inspection, highlighting their potential to reduce the inspection cost and thereby reduce the cost of energy production. The article introduces the rationale for applying UAVs to FOWT inspection and examines the current technical status, research gaps, and future directions in this field by conducting a comprehensive literature review over the past 10 years. This paper will also include a review of UAVs’ applications in other infrastructure inspections, such as onshore wind turbines, bridges, power lines, solar power plants, and offshore oil and gas fields, since FOWTs are still in the early stages of development. Finally, the trends of UAV technology and its application in FOWTs inspection are discussed, leading to our future research direction. Full article

Autonomous power systems serving remote areas with weather stations with small settlements are characterized by a fairly high cost of generating electricity and the purchase and delivery of fuel. In addition, diesel power plants require regular maintenance, have a relatively short service life during continuous operation and produce a large amount of emissions into the environment. This article discusses various methods of placing solar panels in the space for the autonomous power supply of weather station equipment. The principles of these methods are described and their advantages and disadvantages are outlined. The optimal algorithms of functioning for photomodules are described and their comparison regarding the main, significant parameters is carried out. The choice of the most effective algorithm for use at a weather station is made. The effective positioning of solar panels is also calculated, and positioning conditions are determined depending on the territorial location and various environmental conditions. Simulation of the power supply system of a weather station consisting of solar panels, batteries and inverters is performed. As a result, a practical example of the application of the method of selecting the optimal composition of equipment for a hybrid power system of a weather station territorially located in Siberia with different configurations of equipment is considered. In numerical terms, it was possible to reduce the cost of power equipment operation by more than 60% with a fairly low payback period of 5.5 years and an increased reliability of the power system, which is very important for autonomous power systems of northern weather stations. Full article

This study analyses the expansion of solar energy in Iran, considering political, economic, social, and technological factors. Due to the prolonged sanctions on Iran, the development of clean energy power plants has been either halted or significantly reduced. Hence, this study aims to identify barriers to the expansion of solar energy power plants and simulate solar power plants using PVsyst (Photovoltaic system) software. The study is unique in its approach of combining technical analysis with social sciences to facilitate the implementation of solar energy expansion in remote areas. This study focuses on two specific areas with high solar radiation, namely Darab and Meybod, which are located in Fars and Yazd provinces, respectively. Solar energy can be generated in these two areas due to their unique location with high levels of solar irritation. To achieve this goal, the technical analyses focuson simulating the performance of a 9 kWp (kilowatt ‘peak’ power output of a system) grid-connected polysilicon(poly-Si) photovoltaic plant for Darab and a 9.90 kWp plant for Meybod. The simulation is carried out to obtain maximum electricity production and evaluate parameters such as incident radiation, performance ratio, energy into the grid, energy output at the array, and losses. The produced energy for Darab was 20.40 MWh/year, with specific production of 2061 kWh/kWp/year, and the performance ratio (PR) was 81.26%. For Meybod, production was 20.70 MWh/year, with specific production of 2091 kWh/kWp/year, and the performance ratio (PR) was 80.88%. Through the PEST analysis, it is evident that strategic planning and appropriate actions are crucial at the provincial, national, and local levels for energy systems’ development. This indicates that both governments and citizens should play an active role in supporting the expansion of energy systems by planning and creating awareness among the public to embrace and adopt energy systems. Full article

Hydropower plants cover almost 70% of the Colombian electrical demand, were built several decades ago, and present low levels of digitisation compared to other modern power-generation technologies, e.g., wind turbines, solar PV plants, and recently buil hydroelectric plants t. Renovating power plant equipment and investing in modernisation and digitisation can significantly increase the plant flexibility. Those actions will increase a plant’s operational safety and contribute to the solution of environmental and social problems. This work presents the actions followed to extend the lifetime of a 1000 MW hydropower plant operating for more than 40 years. Activities included a residual life status evaluation of generators and component upgrades, among others. The rehabilitation and digitalisation of the generation units allow their integration and remote monitoring so that diagnostic actions can be carried out during a continuous and economically sustainable operation. These activities complement the plan implemented by the company during the last decade to ensure the plant’s operation for another 50 years and its respective integration with nonconventional generation systems at the national level. Besides the generator’s life extension, the main result of rewinding is an increase in the Minimum Breakdown Voltage by almost 140% (from 38.4 kV to 95.6 kV) with respect to the current operation state, ensuring its operation for the following years. Full article