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The goal of increasing fuel efficiency and decreasing greenhouse gas (GHG) emissions has increased interest in the application of renewable energy sources and the usage of new technologies in the maritime industry. In order to implement the most suitable source, factors such as voyage duration, storage availability, and the condition of existing vessels as well as those that are still under construction should be taken into account. Propeller optimization is proposed as a long-term solution. This paper investigates the environmental aspects of propeller optimization, focusing on its potential to reduce ship vibrations fuel consumption, and, therefore, the ship's carbon footprint. The case study presents propeller optimization on a Ro-Ro passenger ship. The data collected during sea trials before and after propeller optimization will be compared. Expected fuel oil consumption will be correlated to the CO2 emission reduction. Besides propeller optimization, the paper performs a SWOT (strengths, weaknesses, opportunities, threats) analysis comparing it with solar and wind power applications on ships. [ABSTRACT FROM AUTHOR]

The ageing of coal-fired power stations in South Africa has led to regular power outages. Therefore, the country will need to urgently increase its electricity capacity to meet further energy demand from growing urbanization and population growth. This challenge has increased interest in alternative energy sources, such as renewable energy (RE). South Africa is gradually implementing appropriate renewable energy practices, reducing carbon emissions, cleansing the air, and assuring a more sustainable future. This paper summarizes the availability, current state, and future potential of renewable energy choices in South Africa. This paper also evaluates specific policy measures and government actions aimed at eliminating barriers and increasing renewable energy deployment in the future. It also considers the South African network's specialized techno-economic analysis. The findings show that South Africa is still heavily reliant on coal, with 78% of the current installed capacity coming from coal power in 2022, compared to 9.3% for solar and wind energy. [ABSTRACT FROM AUTHOR]

This paper addresses the optimal sizing of Hybrid Renewable Energy Systems (HRESs), encompassing wind, solar, and battery systems, with the aim of delivering reliable performance at a reasonable cost. The focus is on mitigating unscheduled outages on the national grid in Iraq. The proposed On–off-grid HRES method is implemented using MATLAB and relies on an iterative technique to achieve multi-objectives, balancing reliability and economic constraints. The optimal HRES configuration is determined by evaluating various scenarios related to energy flow management, electricity prices, and land cover effects. Consumer requirements regarding cost and reliability are factored into a 2D optimization process. A battery model is developed to capture the dynamic exchange of energy among different renewable sources, battery storage, and energy demands. A detailed case study across fifteen locations in Iraq, including water, desert, and urban areas, revealed that local wind speed significantly affects the feasibility and efficiency of the HRES. Locations with higher wind speeds, such as the Haditha lake region (payback period: 7.8 years), benefit more than urban areas (Haditha city: payback period: 12.4 years). This study also found that not utilizing the battery, particularly during periods of high electricity prices (e.g., 2015), significantly impacts the HRES performance. In the Haditha water area, for instance, this technique reduced the payback period from 20.1 to 7.8 years by reducing the frequency of charging and discharging cycles and subsequently mitigating the need for battery replacement. [ABSTRACT FROM AUTHOR]

The integration of renewable energy systems in buildings leads to a reduction in energy bills for end users and a reduction in the carbon footprint of such buildings, usually referred to as prosumers. In addition, the installation of charging points for the electric vehicles of people working or living in these buildings can further improve the energy efficiency of the whole system if innovative technologies, such as vehicle-to-building (V2B) technologies, are implemented. The aim of this paper is to present an Energy Management System (EMS) based on mathematical programming that has been developed to optimally manage a prosumer building equipped with photovoltaics, a micro wind turbine and several charging points for electric vehicles. Capabilities curves of renewable power plant inverters are modelled within the EMS, as well as the possibility to apply power curtailment and V2B. The use of V2B technology reduces the amount of electricity purchased from the public grid, while the use of smart inverters for the power plants allows zero reactive power to be drawn from the grid. Levelized cost of electricity (LCOE) is used to quantify curtailment costs, while penalties on reactive power absorption from the distribution network are evaluated in accordance with the current regulatory framework. Specifically, the model is applied to a prosumer building owned by the postal service in a large city in Italy. The paper reports the main results of the study and proposes a sensitivity analysis on the number of charging stations and vehicles, as well as on the consideration of different typical days characterized by different load and generation profiles. This paper also investigates how errors in forecasting energy production from renewable sources impact the optimal operation of the whole system. [ABSTRACT FROM AUTHOR]

Solar power systems, such as photovoltaic (PV) systems, have become a necessary feature of zero-energy buildings because efficient building design and construction materials alone are not sufficient to meet the building's energy consumption needs. However, solar power generation is subject to fluctuations based on weather conditions, and these fluctuations are higher than other renewable energy sources. This phenomenon has emphasized the importance of predicting solar power generation through weather forecasting. In this paper, an Automatic Machine Learning (AML)-based method is proposed to create multiple prediction models based on solar power generation and weather data. Then, the best model to predict daily solar power generation is selected from these models. The solar power generation data used in this study was obtained from an actual solar system installed in a zero-energy building, while the weather data was obtained from open data provided by the Korea Meteorological Administration. In addition, To verify the validity of the proposed method, an ideal data model with high accuracy but difficult to apply to the actual system and a comparison model with a relatively low accuracy but suitable for application to the actual system were created. The performance was compared with the model created by the proposed method. Based on the validation process, the proposed approach shows 5–10% higher prediction accuracies compared to the comparison model. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

In the context of an insulated area with a subtropical climate, such as La Réunion island, it is crucial to reduce the energy consumption of buildings and develop local renewable energy sources to achieve energy autonomy. Direct current (DC) nanogrids could facilitate this by reducing the energy conversion steps, especially for solar energy. This article presents the deployment and efficiency evaluation of a 48 VDC low-voltage direct current (LVDC) nanogrid, from conception to real-world installation within a company. The nanogrid consists of a photovoltaic power plant, a lithium–iron–phosphate (LFP) battery, and DC end-use equipment, such as LED lighting and DC fans, for two individual offices. For identical test conditions, which are at an equivalent cabling distance and with the same final power demand, the total power consumed by the installation is measured for several stages from 50 to 400 W, according to a 100% DC configuration or a conventional DC/AC/DC PV configuration incorporating an inverter and AC/DC converter. The methodology used enables a critical view to be taken of the installation, assessing both its efficiency and its limitations. Energy savings of between 23% and 40% are measured in DC for a power limit identified at 150 W for a distance of 25 m. These results show that it is possible to supply 48 VDC in an innovative way to terminal equipment consuming no more than 100 W, such as lighting and air fans, using the IEEE 802.3 bt power over ethernet (PoE) protocol, while at the same time saving energy. The nanogrid hardware and software infrastructure, the methodology employed for efficiency quantification, and the measurement results are described in the paper. [ABSTRACT FROM AUTHOR]

Energy crises and the growth of the energy demand have increased the interest in utilizing unconventional power sources. Thus, renewable energy sources have become a topic of interest to mitigate rising energy concerns and cope with increased electricity demand. With remarkable merits including cleanness and abundance, photovoltaic (PV) solar energy systems are a key to solving these issues. The employed inverters should effectively utilize the maximum available power from the PV solar system and transfer this power to the utility grid without posing any further limitations. However, the unequal power generation of different PV systems caused by partial shading (PS) and other PV panel degradation factors leads to a reduction in generation capacity. One of the relatively new solutions to mitigate the mismatch concerns between the PV modules and sub-modules is to extract the maximum power of each sub-module individually. The main objective of this paper is to present a comprehensive review of such PV grid-connected inverters topologies associated with sub-module connection and control. It will classify the PV grid-tied inverters in accordance with the level where the maximum power point tracking (MPPT) system is implemented. A special focus has been placed on sub-module microinverters (MI) in terms of circuit topologies, conversion efficiency, and controller design. This paper provides a comprehensive analysis of employing the distributed MPPT (DMPPT) approach to maximize the power generation of PV systems by mitigating the mismatch issues inside the PV module. The circuit topology, PV system configuration, and MPPT algorithms used for applying DMPPT solutions in PV SMs are discussed in detail in this study. [ABSTRACT FROM AUTHOR]

This paper provides a review of the implementation of different materials and how they have impacted the efficiency of solar cells. This work elaborates on all solar generation methods that have been developed in the past and covers disparate technologies that are being implemented in different generations. A review of the characterization and factors involved in these processes are also discussed briefly. Furthermore, the economic, environmental, and technical perspectives related to solar cells have also been expounded. This paper also provides some insights into potential research directions that can be pursued in the field of solar energy. Energy demands are increasing all over the world, and substantial amounts of fossil fuels are currently exhausted all over the world in order to meet those needs, which in turn contaminates our environment; moreover, non-renewable sources of energy are diminishing at higher rates as well. Solar energy is of prime importance in all renewable energy sources as the Sun shines at the Earth for 8 to 10 h on average. Thus, heat can be harnessed to generate electricity, but solar cells are not substantially efficient because the materials used in them are quite costly and waste a considerable amount of energy, mostly as heat, which subsequently reduces the efficiency of the cell and increases the overall price as well. These challenges can be dealt with by designing more efficient, economical systems of storage and manufacturing PV cells with high efficacy. Scientists and engineers are more inclined toward advanced technologies and material manipulation to enhance the efficiency of solar energy and reduce its cost. In this regard, substantial research is being carried out, especially on the structure of materials and advanced materials like nanomaterials and quantum dots. Due to their distinct electromechanical and material properties, carbon-based nanomaterials like carbon nanotubes, graphene, fullerene, and nanohybrids are being employed as the electrodes, transport layers, active layers, or intermediate (interfacial) layers of solar cells in this regard. [ABSTRACT FROM AUTHOR]

The increasing demand for energy and electricity and the depletion of fossil fuels are global problems. In recent years, dye-sensitized solar cell (DSSC) technologies have gained notoriety for their application in solar energy. DSSCs are considered a promising alternative renewable energy source to both inorganic and organic photovoltaic (PV) cells. Many types of dyes are being investigated to enhance the light-harvesting properties of DSSCs, but the actual realization of these absorbers in cell structure requires optimum parameters. The main aim of this study was to simulate proposed zinc phthalocyanine (ZnPC)-based structures to validate their design, assess their performance for commercial implementation, and optimize the cell parameters for optimum efficiency. To that end, Scaps-1D was employed to evaluate the performance of DSSCs to determine their optimum parameters. We found that ZnPC and isopropoxy ZnPC molecules outperform others molecules because of better optoelectronic properties. Several other parametric effects, such as photoactive layer thicknesses, doping densities, trap densities, and charge carrier mobilities, were also evaluated to observe their impact on device performance. The results show that moderate thickness, low defect density, moderate doping, and charge carrier mobility are favorable for better device performance due to low recombination losses, electrical losses, and better transport of charge carriers. The utmost power conversion efficiency values found for ZnPC- and ZnPC: PC70BM-based DSSCs after optimization were 9.50% and 9.81%. This paper also suggests a practical method for efficiently using DSSC cells by modifying factors that are significantly reliant on DSSC performance and output. [ABSTRACT FROM AUTHOR]

The adoption of renewable energies such as solar power, heat pumps, and wind power is on the rise, and individuals have started generating energy using their own solar panels. In recent years, many blockchain-based energy trading schemes have been proposed. However, existing schemes cannot fully address privacy issues and dependency on energy brokers during energy trading. In this paper, we propose a privacy-preserving authentication scheme for blockchain-based energy traders. An energy user encrypts a request message through lightweight attribute-based encryption, and only energy sellers who have proper attribute keys can decrypt and conduct further processes with the energy user. We analyze the proposed scheme using both informal and formal methods, such as the BAN logic, AVISPA simulation tool, and RoR model. Furthermore, we compare the computational and communication costs of our scheme with related schemes and show that the proposed scheme has competitive performance. [ABSTRACT FROM AUTHOR]

To cope with the increasing energy demand, power systems, especially distribution networks, face many challenges. Recently, these networks have become complex and large, and their stability and reliability are not easy to be handled. The integration of renewable energy resources and at the same time limiting their accompanied high fault currents is one of the approvable suggestions. Many solutions have appeared to restrict the fault currents, but fault current limiters (FCLs) arise as an efficient and promising solution to whether to interrupt or limit the fault currents to allowable limits. This paper presents a literature review of the integration of renewable energy resources as distributed generation units (DGs) and FCLs in distribution networks. The DGs can be categorized based on their size and ability to deliver active or reactive power in addition to their fuel. All of solar, wind, water, biomass, geothermal, and fuel cell are utilized as the main engine for these units. Additionally, a survey about FCLs is provided, including their diverse types and applications in either medium- or low-voltage networks. FCLs are divided into reactor, pyrotechnic, non-superconducting (solid state), and the last-developed ones, superconducting FCLs. In addition, the implemented optimization techniques are summarized to correctly employ both FCLs and DGs. These techniques vary between classical and modern, whereas more methods are developed to suit the renewable energy intermittence and uncertainty and the power system operators' aspirations. Moreover, in this paper, the optimal allocation of diverse types of DGs correlated with FCLs is presented and applied to the real Egyptian distribution network of the East Delta Network (EDN). The results show the avails obtained where the power losses are significantly reduced, with respect to the total load, from 3.59% in the initial case to 0.296%. In addition, the fault current returns to its initial value, removing the percentage of increase of 20.93%. [ABSTRACT FROM AUTHOR]

To meet the expanding energy demand, all available energy sources must be utilized. Renewable energies are both eternal and natural, but their major downside is their inconsistency. Due to the rising costs of fossil fuels and the CO2 they emit, hybrid renewable energy (HRE) sources have gained popularity as an alternative in remote and rural areas. To address this issue, a hybrid renewable energy system (HRES) can be developed by combining several energy sources. In order to build modern electrical grids that have advantages for the economy, environment, and society, the hybrid system is preferable. A summary of various optimization methods (modeling techniques) of an HRES is presented in this paper. This study offers an in-depth analysis of the best sizing, control methodologies, and energy management strategies, along with the incorporation of various renewable energy sources to form a hybrid system. Modern hybrid renewable energy system utilities rely more on an optimal design to reduce the cost function. Reviews of several mathematical models put out by various academicians are presented in this work. These models were created based on reliability analyses incorporating design factors, objective functions, and economics. The reader will get familiar with numerous system modelling optimization strategies after reading this study, and they will be able to compare different models based on their cost functions. Numerous modeling approaches and software simulation tools have been created to aid stakeholders in the planning, research, and development of HRES. The optimal use of renewable energy potential and the meticulous creation of applicable designs are closely tied to the full analysis of these undoubtedly complicated systems. In this field, as well, several optimization restrictions and objectives have been applied. Overall, the optimization, sizing, and control of HRES are covered in this paper with the energy management strategies. [ABSTRACT FROM AUTHOR]

This research paper examines the adoption of solar energy in residential buildings throughout Saudi Arabia, with a specific emphasis on Makkah. Despite the immense global demand for energy and growing environmental concerns, the adoption of solar energy in Saudi housing remains relatively low. While previous studies have examined the potential, feasibility, and policy support for solar energy, this research uniquely approaches the issue from the perspective of customers on a national scale. The study aims to identify the factors that influence customers' intentions to use solar energy in Saudi Arabia, contributing to the development of a sustainable circular supply chain for renewable energy. To achieve this, the research integrates the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). An online questionnaire was distributed, garnering responses from a total of 250 participants. A regression analysis was employed to analyze the data and examine the relationships between the proposed hypotheses. The study's findings reveal that four critical factors wield significant influence over consumer behavior and their decisions regarding the adoption of solar PV technology. These factors are: Social Influence (SI), Performance Expectancy (PE), Effort Expectancy (EE), and Facilitating Conditions (FC). [ABSTRACT FROM AUTHOR]

The exponential growth of population and industries has brought about an increase in energy consumption, causing severe climatic and environmental problems. Therefore, the move towards green renewable energy is being ever more intensified. This study aims at estimating the rooftop solar power production for Tehran, the capital city of Iran, using a Geospatial Information System (GIS) to assess the big data of city building parcels. Tehran is faced with severe air pollution due to its excessive fossil fuel usage, and its electricity demand is increasing. As a result, this paper attempts to provide the quantified solar power potential of city roof tops for policymakers and authorities in order to facilitate decision-making in relation to integrating renewable energies into the power production infrastructure. The results shows that approximately 3000 GWh (more than 14% of the total electric energy consumption) of solar power can be produced by the rooftop PV installations in Tehran. The potential nominal power of rooftop PV installations is estimated to be more than 2000 MW, which is four times the current installed PV capacity of the whole country. The findings of the study suggest that there is great potential hidden on the rooftops of the city, which can be utilized to assist the power systems of the city in the longer run for a more sustainable future. [ABSTRACT FROM AUTHOR]

A Chinese solar greenhouse (CSG) is an agricultural facility type with Chinese characteristics. It can effectively utilize solar energy during low-temperature seasons in alpine regions. The low construction and operation costs make it a main facility for agricultural production in the northern regions of China. It plays an extremely important role in "Chinese vegetable basket projects". Energy is one of the important issues faced by CSGs. The better climate resources in the northern regions of China make it possible to apply solar energy as a green and sustainable energy source in the production of CSGs. Faced with the increasingly serious environmental problems of the new century, the Chinese government has made a decision and put it into practice to improve the rate and efficiency of solar energy utilization in agricultural facilities. In this paper, we summarize the research on the application of photovoltaic power generation and solar thermal technology in CSGs. The application of these advanced solar technologies has made great progress. With the further improvement of economic benefits and the establishment of relevant support policies and incentive mechanisms, the combination of CSG and solar energy technology will have certain application prospects and satisfy China's requirements for long-term sustainable development. [ABSTRACT FROM AUTHOR]

The increased use of fossil fuels in transportation is considered a major cause of environmental pollution and climate change on a global scale. In international shipping, regulations and strict measures have been introduced by the International Maritime Organization to achieve the goal of a 40% reduction in greenhouse gas (GHG) emissions by 2030, with the envisage to reach net-zero GHG emissions close to 2050. Renewable energy sources, such as solar photovoltaic (PV) systems, can be implemented on new-build or existing marine vessels as an effective alternative source for auxiliary power generation, reducing the dependency on fossil fuels and contributing to decarbonization. In the present paper, a sustainable retrofit design using PV panels on an existing Ro-Ro vessel is analyzed for its feasibility. The proposed system is used for energy production during ship cargo operations and takes advantage of the large space area on the upper deck and its continuous exposure to sunlight during its voyage. To investigate the effectiveness of the PV system as an alternative to fossil fuel consumption, an environmental and economic evaluation is performed. According to the results obtained, the solar PV system can provide approximately 88% of the required energy annually for lighting during ship cargo operations, with the corresponding fuel savings and emission reductions, making the investment economically feasible, with a high potential to contribute to environmental sustainability. [ABSTRACT FROM AUTHOR]

Energy-efficient buildings are a new demand in the current era. In this paper, we present a novel metamaterial design aimed at achieving efficient solar energy absorption through a periodic MMA structure composed of a W-GaAs-W. The proposed structure can be implemented as the window coating and in turn it can absorb the incident solar energy and, then, this energy can be used to fulfill the energy demand of the building. Our results reveal significant improvements, achieving an average absorptance of 96.94% in the spectral range. Furthermore, we explore the influence of the angle of incidence on the absorber's response, demonstrating its angle-insensitive behavior with high absorption levels (above 90%) for incidence angles up to 60° for TE polarization and 40° for TM polarization. The proposed structure presents a significant advancement in metamaterial-based solar energy absorption. By exploring the effects of structural parameters and incident angles, we have demonstrated the optimized version of our proposed absorber. The potential applications of this metamaterial absorber in self-sufficient futuristic building technologies and self-sustaining systems offer new opportunities for harnessing solar energy and are a valuable contribution to future developments in the fields of metamaterials and renewable energy. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS. [ABSTRACT FROM AUTHOR]

With the increasing need for cooling and the concerns for pollution due to fossil fuel-based energy use, renewable energy is considered an add-on to cooling technologies. The climatic condition in the Middle East, analyzed in this paper, provides the potential to integrate solar energy with the cooling system. Due to the availability of various solar energy and cooling technologies, multiple configurations of solar-cooling systems can be considered to satisfy the cooling demand. The research presented in this paper aims to assess and compare these configurations by considering the energy prices and the installation area. The proposed model is formulated in Mixed-Integer Linear Programming and optimizes the holistic system design and operation. The economic, renewable energy use, and environmental performances of the optimal solution for each configuration are analyzed and compared to the base grid-DCS configuration. Results show that the electricity tariff and the available installation area impact the economic competitiveness of the solar energy integration. When electricity tariff is subsided (low), the conventional grid-based DCS is the most competitive. The PV-DCS configuration is economically competitive among the solar assisted cooling systems, and it can contribute to reducing the environmental impact by 58.3%. The PVT-DCS configuration has the lowest operation cost and the highest environmental performance by decreasing the global warming potential by 89.5%. The T-DCS configuration becomes economically competitive only at high electricity tariffs. [ABSTRACT FROM AUTHOR]

Agrivoltaics and aquavoltaics combine renewable energy production with agriculture and aquaculture. Agrivoltaics involves placing solar panels on farmland, while aquavoltaics integrates photovoltaic systems with water bodies and aquaculture. This paper examines the benefits and challenges of agrivoltaics and aquavoltaics, focusing on their potential for Croatian agriculture and freshwater aquaculture. Benefits include dual land use, which allows farmers to produce clean energy while maintaining agricultural practices. They diversify renewable energy sources and reduce dependence on fossil fuels and greenhouse gas emissions. Solar panels in agrivoltaics provide shade, protect crops, reduce water needs, and increase yields. Challenges include high initial costs and limited accessibility, especially for small farmers. Integration with existing systems requires careful planning, considering irrigation, soil moisture, and crop or fish production. Maintenance and cleaning present additional challenges due to dust, debris, and algae. Policy and regulatory frameworks must support implementation, including incentives, grid integration, land use regulations, and conservation. The location, resources, and crops grown in Croatia present an opportunity for agrivoltaics and aquavoltaics, considering cultivation methods, species, and regulatory requirements. [ABSTRACT FROM AUTHOR]

In this twenty-first century, energy shortages have become a global issue as energy demand is growing at an astounding rate while the energy supply from fossil fuels is depleting. Thus, the urge to develop sustainable renewable energy to replace fossil fuels is significant to prevent energy shortages. Solar energy is the most promising, accessible, renewable, clean, and sustainable substitute for fossil fuels. Third-generation (3G) emerging solar cell technologies have been popular in the research field as there are many possibilities to be explored. Among the 3G solar cell technologies, perovskite solar cells (PSCs) are the most rapidly developing technology, making them suitable for generating electricity efficiently with low production costs. However, the toxicity of Pb in organic–inorganic metal halide PSCs has inherent shortcomings, which will lead to environmental contamination and public health problems. Therefore, developing a lead-free perovskite solar cell is necessary to ensure human health and a pollution-free environment. This review paper summarized numerous types of Sn-based perovskites with important achievements in experimental-based studies to date. [ABSTRACT FROM AUTHOR]

Integrating renewable energy sources (RESs) into modern electric power systems offers various techno-economic benefits. However, the inconsistent power profile of RES influences the power flow of the entire distribution network, so it is crucial to optimize the power flow in order to achieve stable and reliable operation. Therefore, this paper proposes a newly developed circle search algorithm (CSA) for the optimal solution of the probabilistic optimal power flow (OPF). Our research began with the development and evaluation of the proposed CSA. Firstly, we solved the OPF problem to achieve minimum generation fuel costs; this used the classical OPF. Then, the newly developed CSA method was used to deal with the probabilistic power flow problem effectively. The impact of the intermittency of solar and wind energy sources on the total generation costs was investigated. Variations in the system's demands are also considered in the probabilistic OPF problem scenarios. The proposed method was verified by applying it to the IEEE 57-bus and the 118-bus test systems. This study's main contributions are to test the newly developed CSA on the OPF problem to consider stochastic models of the RESs, providing probabilistic modes to represent the RESs. The robustness and efficiency of the proposed CSA in solving the probabilistic OPF problem are evaluated by comparing it with other methods, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and the hybrid machine learning and transient search algorithm (ML-TSO) under the same parameters. The comparative results showed that the proposed CSA is robust and applicable; as evidence, an observable decrease was obtained in the costs of the conventional generators' operation, due to the penetration of renewable energy sources into the studied networks. [ABSTRACT FROM AUTHOR]

Renewable energy resources have gained considerable attention in recent years due to their efficiency and economic benefits. Their proportion of total energy use continues to grow over time. Photovoltaic (PV) cell and wind energy generation are the least-expensive new energy sources in most countries. Renewable energy technologies significantly contribute to climate mitigation and provide economic benefits. Apart from these advantages, renewable energy sources, particularly solar energy, have drawbacks, for instance restricted energy supply, reliance on weather conditions, and being affected by several kinds of faults, which cause a high power loss. Usually, the local PV plants are small in size, and it is easy to trace any fault and defect; however, there are many PV cells in the grid-connected PV system where it is difficult to find a fault. Keeping in view the aforedescribed facts, this paper presents an intelligent model to detect faults in the PV panels. The proposed model utilizes the Convolutional Neural Network (CNN), which is trained on historic data. The dataset was preprocessed before being fed to the CNN. The dataset contained different parameters, such as current, voltage, temperature, and irradiance, for five different classes. The simulation results showed that the proposed CNN model achieved a training accuracy of 97.64% and a testing accuracy of 95.20%, which are much better than the previous research performed on this dataset. [ABSTRACT FROM AUTHOR]

As non-renewable energy sources are in the verge of exhaustion, the entire world turns towards renewable sources to fill its energy demand. In the near future, solar energy will be a major contributor of renewable energy, but the integration of unreliable solar energy sources directly into the grid makes the existing system complex. To reduce the complexity, a microgrid system is a better solution. Solar energy forecasting models improve the reliability of the solar plant in microgrid operations. Uncertainty in solar energy prediction is the challenge in generating reliable energy. Employing, understanding, training, and evaluating several forecasting models with available meteorological data will ensure the selection of an appropriate forecast model for any particular location. New strategies and approaches emerge day by day to increase the model accuracy, with an ultimate objective of minimizing uncertainty in forecasting. Conventional methods include a lot of differential mathematical calculations. Large data availability at solar stations make use of various Artificial Intelligence (AI) techniques for computing, forecasting, and predicting solar radiation energy. The recent evolution of ensemble and hybrid models predicts solar radiation accurately compared to all the models. This paper reviews various models in solar irradiance and power estimation which are tabulated by classification types mentioned. [ABSTRACT FROM AUTHOR]

South Africa is one of the most carbon-intensive economies in the world, but it is presently experiencing an energy crisis, as its utility company cannot meet the country's energy demands. The use of renewable energy sources and retiring of coal-fired power stations are two important ways of alleviating this problem, as well as decarbonizing the grid. Repurposing retiring coal-fired power stations for renewable energy generation (RCP-RES) while maintaining energy sustainability and reliability has rarely been researched. This paper proposes macro- and microelements for repurposing retiring coal-fired power stations for renewable energy generation in Camden with the aim of improving power generation through a low-carbon system. In this model, concentrated solar power (CSP) and solar photovoltaics (SPV), in combination with storage technologies (STs), were employed for RCP-RES, owing to their excellent levels of availability in the retiring fleet regions. The simulation results show that the power densities of CSP and SPV are significantly lower compared with retiring a coal-fired power plant (CFPP). Both are only able to generate 8.4% and 3.84% rated capacity of the retired CFPP, respectively. From an economic perspective, the levelized cost of electricity (LCOE) analysis indicates that CSP is significantly cheaper than coal technology, and even cheaper when considering SPV with a storage system. [ABSTRACT FROM AUTHOR]

Renewable energy resource utilisation is becoming more prevalent in society and can be a sustainable method to meet rising energy demand and consumption. The International Renewable Energy Agency reports that presently, approximately 33% of total electricity output around the world is from renewable energy sources. However, in Nigeria, the World Bank reported this figure as 18.2% in 2015. It is important to understand how Nigeria can raise this average as the world moves towards less use of fossil fuels. Therefore, the aim of this work was to provide a review of the established literature, which can then be used to support the development of renewable energy systems in Nigeria. The methodology employed for the study of the literature involved a systematic review method, including identification, screening, eligibility and inclusion criterium steps. Understanding the national energy landscape is essential to support potential projects, and consequently, energy supply, demand and consumption in Nigeria are observed. The review examined renewable energy sources in Nigeria with a focus on solar and biomass/bioenergy. The levelised cost of electricity from renewable technologies was analysed, and the paper identified and evaluated past projects centered on solar and biomass, presenting three main case studies. The results indicate that solar and biomass have the most potential for energy generation in Nigeria, with 4–6.5 kWh/m2 of solar irradiation available per day and approximately 2.3 × 109 GJ bioenergy potential per year. However, solar PV is currently of most interest in Nigeria due to the lower cost of on-grid solar PV electricity, which can comfortably compete with fossil fuels. Nevertheless, costs still need to be lowered to compete fully. Finally, the findings also indicate that there is an omission in the literature surrounding the existing renewable projects and technologies in Nigeria. [ABSTRACT FROM AUTHOR]

Using renewable energy sources instead of fossil fuels is one of the best solutions to overcome greenhouse gas (GHG) emissions. However, in designing clean power generation microgrids, the economic aspects of using renewable energy technologies should be considered. Furthermore, due to the unpredictable nature of renewable energy sources, the reliability of renewable energy microgrids should also be evaluated. Optimized hybrid microgrids based on wind and solar energy can provide cost-effective power generation systems with high reliability. These microgrids can meet the power demands of the consuming units, especially in remote areas. Various techniques have been used to optimize the size of power generation systems based on renewable energy to improve efficiency, maintain reliability, improve the power grid's resilience, and reduce system costs. Each of these techniques has shown its advantages and disadvantages in optimizing the size of hybrid renewable energy systems. To increase the share of renewable energies in electricity supply in the future and develop these new technologies further, this paper reviews the latest and most efficient techniques used to optimize green microgrids from an economical and reliable perspective to achieve a clean, economical, and highly reliable microgrid. [ABSTRACT FROM AUTHOR]

Renewable energy sources and sustainability have been attracting increased focus and development worldwide. Qatar is no exception, as it has ambitious plans to deploy renewable energy sources on a mass scale. Qatar may also investigate initiating and permitting the deployment of rooftop photovoltaic (PV) systems for residential households. Therefore, a research gap has been introduced regarding the system design, grid compatibility, economic viability, and energy consumption produced from household rooftop PV systems. Additionally, the lack of supporting policies and a feed-in tariff creates further research and development topics. Therefore, using collected data regarding household power consumption and rooftop PV generation, the purposes of this research study are as follows: (1) determining the economic aspects and practicality of using energy storage systems for self-consumption values; and (2) evaluating the economic viability of rooftop PV systems under different policies and electricity rate schemes. The insights of the results of this study can serve as a stepping stone for decisions and policymakers regarding the application of rooftop PV systems in Qatar. This study utilizes empirical evidence and an economic model to evaluate rooftop PV systems in Qatar and can also be applicable in the middle east region. A few studies in the region produce complementary results, which further supports our findings; however, what makes this paper unique is the use of different economic tools and real collected data while investigating multiple economic and energy policy scenarios. [ABSTRACT FROM AUTHOR]

The introduction of solar photovoltaic (PV) systems would provide electricity accessibility to rural areas that are far from or have no access to the grid system. Various countries are planning to reduce their emissions from fossil fuel, due to its negative effects, by substituting with renewable energy resources. The use of solar PV systems is expanding globally because of growing energy demands and depleting fossil fuel reserves. Grid integration of the solar system is expected to increase further in the near future. However, the power output of solar PV systems is inherently intermittent, and depends on the irradiance and the temperature operation of the solar cell, resulting in a wide range of defects. Hence, it is vital to extract peak power from the solar panel in all conditions to provide constant power to the load. This paper presents a tracking control method of the peak output power of a solar PV system connected to a DC-DC boost converter using an improved incremental conductance and integral regulator (IC + IR). The research was carried out because the solar PV output is dependent on environmental parameters, such as solar insolation and temperature. Therefore, it is pertinent to forecast the peak power point in outdoor conditions and to operate at that point, so that solar PV can produce the highest output each time it is used. A peak power point strategy that maximizes the output of a solar PV array is proposed. This method establishes the maximum output operation point under the effects of the solar insolation and the module temperature. An automatic converter restoration scheme with block/de-block signal control is proposed to protect the converters from the higher phase current, total capacitor voltage deviation, grid disturbance, and fault current. The proposed scheme also tracks the peak power point (PPP) of the solar array with stable output voltage under varying operating conditions. It reduces the error signal and ripples at the PPP during instantaneous and incremental conductance to zero. In addition, it controls the solar PV system under constantly changing climatic conditions, and thus improves the system efficiency. [ABSTRACT FROM AUTHOR]

The penetration rates of intermittent renewable energies such as wind and solar energy have been increasing in power grids, often leading to a massive peak-to-valley difference in the net load demand, known as a "duck curve". The power demand and supply should remain balanced in real-time, however, traditional power plants generally cannot output a large range of variable loads to balance the demand and supply, resulting in the overgeneration of solar and wind energy in the grid. Meanwhile, the power generation hours of the plant are forced to be curtailed, leading to a decrease in energy efficiency. Building demand response (DR) is considered as a promising technology for the collaborative control of energy supply and demand. Conventionally, building control approaches usually consider the minimization of total energy consumption as the optimization objective function; relatively few control methods have considered the balance of energy supply and demand under high renewable energy penetration. Thus, this paper proposes an innovative DR control approach that considers the energy flexibility of buildings. First, based on an energy flexibility quantification framework, the energy flexibility capacity of a typical office building is quantified; second, according to energy flexibility and a predictive net load demand curve of the grid, two DR control strategies are designed: rule-based and prediction-based DR control strategies. These two proposed control strategies are validated based on scenarios of heating, ventilation, and air conditioning (HVAC) systems with and without an energy storage tank. The results show that 24–55% of the building's total load can be shifted from the peak load time to the valley load time, and that the duration is over 2 h, owing to the utilization of energy flexibility and the implementation of the proposed DR controls. The findings of this work are beneficial for smoothing the net load demand curve of a grid and improving the ability of a grid to adopt renewable energies. [ABSTRACT FROM AUTHOR]

Despite the increasing utilization of renewable energy resources, such as solar and wind energy, most residential buildings still rely on conventional energy supply by public utility services. Such utility services often use time-of-use energy pricing, which compels residential consumers to reduce their energy usage. This paper presents a wireless home energy management (HEM) system that enables the automatic control of home appliances to reduce energy consumption to assist such energy users. The system consists of multiple smart sockets that measure the energy that is consumed by the connected appliances and are capable of implementing on/off commands. The system includes other support components for supplying data to a central controller, which utilizes a rule-based HEM algorithm. The control rules were designed, such that the lifestyle of the user would be preserved while the energy consumption and daily energy cost were reduced. The experimental results showed that the central controller could effectively receive data and control multiple devices. The system was also found to afford significant reductions of 23.5 kWh and $2.898 in the total daily energy consumption and bill of the considered household setup, respectively. The proposed HEM system promises to be particularly useful for households with a high daily energy consumption. [ABSTRACT FROM AUTHOR]

By considering the weight penalty of batteries on payload and total vehicle weight, this paper shows that almost all forms of land-based transport may be served by battery electric vehicles (BEV) with acceptable cost and driving range. Only long-distance road freight is unsuitable for battery electrification. The paper models the future Indian electricity grid supplied entirely by low-carbon forms of generation to quantify the additional solar PV power required to supply energy for transport. Hydrogen produced by water electrolysis for use as a fuel for road freight provides an inter-seasonal energy store that accommodates variations in renewable energy supply. The advantages and disadvantages are considered of midday electric vehicle charging vs. overnight charging considering the temporal variations in supply of renewable energy and demand for transport services. There appears to be little to choose between these two options in terms of total system costs. The result is an energy scenario for decarbonized surface transport in India, based on renewable energy, that is possible, realistically achievable, and affordable in a time frame of year 2050. [ABSTRACT FROM AUTHOR]

Nowadays, due to climate change and disappearance of fossil fuels, hybrid electric UAVs using renewable energy sources are being developed. In addition, although research on UAVs with a large wingspan and high weight is common due to their long endurance, research on mini UAVs has remained limited. This study aims to increase the energy capacity of solar-powered mini UAVs and thus extend their endurance by developing a fixed-wing hybrid UAV that can fly with solar energy as much as possible, especially during the cruise phase. In this study, a solar-powered mini VTOL (vertical take-off and landing) UAV with a wingspan of 1.8 m and weight of 3.3 kg is developed and a model of the system consisting of solar cells, a battery, a super capacitor, and a DC/DC converter is created in MATLAB/Simulink software (R2023b). Additionally, state machine control (SMC), a rule-based (RB) energy management strategy (EMS), has been applied to this model. While the power obtained from the sun is divided among the other energy components, the durability of the UAV is increased, and the excess energy is stored as altitude energy to be used when necessary. As a result, in this study, an energy management algorithm including altitude energy has been successfully applied to a solar-powered UAV, achieving an 11.11% energy saving. [ABSTRACT FROM AUTHOR]

Increased world energy demand necessitates looking for appropriate alternatives to oil and fossil fuel. Countries encourage institutions and households to create their own photovoltaic (PV) systems to reduce spending money in electricity sectors and address environmental issues. Due to high solar radiation in the Kingdom of Saudi Arabia (KSA), the government urges people and institutions to establish PV systems as the best promising renewable energy resource in the country. This paper presents an optimal and complete design of a 300 kW PV system installed in a limited rooftop area to feed the needs of the Ministry of Electricity building, which has a high energy consumption. The design has been suggested for two scenarios in terms of adjusting the orientation angles. The available rooftop area allowed to be used is insufficient if a tilt angle of 22o is used, suggested by the designer, so the tilt angle has been adjusted from 22o to 15o to accommodate the available area and meet the required demand with a minimum shading effect. The authors of this paper propose a modified scenario "third scenario" which accommodates the available area and provides more energy than the installed "second scenario". The proposed panel distribution and the estimated energy for all scenarios are presented in the paper. The possibility of changing tilt angles and the extent of energy production variations are also discussed. Finally, a comparative study between measured and simulated energy is included. The results show that August has the lowest percentage error, with a value of 2.7%, while the highest percentage error was noticed in November. [ABSTRACT FROM AUTHOR]

The increase in demand for electricity due to industrial development and the growing use of electronic equipment has led to the need for new alternative energy sources, such as photovoltaic solar energy conversion. In this context, organic photovoltaic (OPV) stands out as an efficient way of generating energy indoors. An electrical power supply system (EPS) was developed to power a commercial electronic lock, using OPV as the energy source. The system was designed with a charging control to match the panel voltage to a supercapacitor charge accumulator and a boost converter. Tests on the bench and in a real scenario demonstrated the viability and effectiveness of the system, showing that it is capable of operating self-sufficiently with a minimum daily illuminance of 250 lux for 12 h. The results indicate that the system can be applied to various loads with low energy consumption, promoting energy efficiency in different contexts. [ABSTRACT FROM AUTHOR]

Despite the global importance of solar energy, its variability requires energy storage to balance production during peak and off-peak periods. Moreover, the transport sector is undergoing a global transition from internal combustion engines to electric vehicles. Since vehicles are idle 95% of the time, electric vehicle batteries, when connected to a grid, can effectively regulate intermittent photovoltaics using vehicle-to-grid technology. This conceptual study investigates the feasibility of a nationwide energy infrastructure that relies solely on solar energy, replacing other electricity sources, such as solid fuels, petroleum products, and natural gas, and utilizes electric vehicles as the sole battery energy storage system. This study aims to demonstrate the significant potential and benefits of such collaboration. The theoretical study combines historical data, assumptions, and conditions to build a simulation model that is modelled similarly as in previous conceptual studies of nationwide energy systems based solely on photovoltaics and electric vehicles, referenced in this article. In Slovenia, the total surface size suitable for the installation of photovoltaic systems is estimated to be 280 km2. The calculations show that a surface size of 217 km2 for photovoltaic systems can produce enough energy to cover Slovenia's entire energy demand, Slovenia's final energy consumption. However, simulations comparing photovoltaic production, total energy consumption (electricity, solid fuels, etc.), and the capacity of electric vehicle batteries show that a surface size of more than 500 km2 with photovoltaic systems and a 200% share of electric vehicles in the Slovenian vehicle fleet in 2022 will provide satisfactory results. Therefore, for a country like Slovenia, in addition to a solar power plant with a surface size of 280 km2, additional renewable energy sources are needed to cover the total energy demand, as well as additional battery energy storage systems in addition to electric vehicles. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) systems are widely adopted for renewable energy generation, but their performance is influenced by complex interactions between longer-term trends and seasonal variations. This study aims to remove these factors and provide valuable insights for optimising PV system operation. We employ comprehensive datasets of measured PV system performance over five years, focusing on identifying the distinct contributions of longer-term trends and seasonal effects. To achieve this, we develop a novel analytical framework that combines time series and statistical analytical techniques. By applying this framework to the extensive performance data, we successfully break down the overall PV system output into its constituent components, allowing us to find out the impact of the system degradation, maintenance, and weather variations from the inherent seasonal patterns. Our results reveal significant trends in PV system performance, indicating the need for proactive maintenance strategies to mitigate degradation effects. Moreover, we quantify the impact of changing weather patterns and provide recommendations for optimising the system's efficiency based on seasonally varying conditions. Hence, this study not only advances our understanding of the intricate variations within PV system performance but also provides practical guidance for enhancing the sustainability and effectiveness of solar energy utilisation in both residential and commercial settings. [ABSTRACT FROM AUTHOR]

Buildings account for a significant proportion of total energy consumption. The integration of renewable energy sources is essential to reducing energy demand and achieve sustainable building design. The use of solar energy has great potential for promoting energy efficiency and reducing the environmental impact of energy consumption in buildings. This study examines the applications of photovoltaic and solar thermal technologies in the field of architecture, demonstrating the huge potential of solar energy in building applications. To ensure a fresh and thorough review, we examine literature that encompasses the advancements made in the utilization of solar energy in buildings over the past decade. The key factors to consider in this study are reliability, performance, cost and aesthetics in real applications of photovoltaic and solar thermal technologies in the field of architecture, which have a significant impact on people's acceptance of solar energy technology. Recent developments in feasible and effective optimization solutions for solar energy technologies are summarized. Accurate and convenient simulation techniques are also summarized for reference. The results show that the rapid progress of BIPV systems is fueled by advancements in three crucial areas: enhancing solar cell and module efficiency, reducing manufacturing costs and achieving a competitive levelized cost of electricity. The results can provide researchers with a reference for understanding recent technological developments in the integration of solar energy into buildings. [ABSTRACT FROM AUTHOR]

This study investigates the use of a foldable solar panel system equipped with a dynamic tracking algorithm for agrivoltaics system (AVS) applications. It aims to simultaneously meet the requirements for renewable energy and sustainable agriculture. The design focuses on improving solar energy capture while facilitating crop growth through adjustable shading. The results show that foldable panels, controlled by the tracking algorithm, significantly outperform fixed panels in energy efficiency, achieving up to a 15% gain in power generation and uniform power generation throughout the day. Despite the presence of shadows of adjacent panels in the early morning and late evening, the system's effectiveness in creating microclimates for diverse crops demonstrates its substantial value. The foldable design not only protects crops from adverse climate conditions across different seasons but also generates energy efficiently. This demonstrates a step forward in sustainable land use and food security. [ABSTRACT FROM AUTHOR]

In today's world, renewable energy sources are increasingly integrated with nonrenewable energy sources into electric grids and pose new challenges because of their intermittent and variable nature. Energy prediction using soft-computing techniques plays a vital role in addressing these challenges. As electricity consumption is closely linked to other energy sources such as natural gas and oil, forecasting electricity consumption is essential for making national energy policies. In this paper, we utilize various data mining techniques, including preprocessing historical load data and the load time series's characteristics. We analyzed the power consumption trends from renewable energy sources and nonrenewable energy sources and combined them. A novel machine learning-based hybrid approach, combining multilayer perceptron (MLP), support vector regression (SVR), and CatBoost, is proposed in this paper for power forecasting. A thorough comparison is made, taking into account the results obtained using other prediction methods. [ABSTRACT FROM AUTHOR]

Worldwide, governmental organizations are restructuring energy policies, making them cleaner, encouraging transformation and energy transition by integrating renewable sources, engaging in environmental preservation, and, notably, meeting the growing demand for sustainable energy models, such as solar and wind energy. In the electricity sector, reducing carbon emissions is crucial to facilitating the integration of microgrids (MGs) with renewable sources and Battery Energy Storage Systems (BESSs). This work constitutes a systematic review that thoroughly analyzes the sizing of MGs with BESSs. The unpredictability and variability of renewable sources justify the complexity of this analysis and the loads connected to the system. Additionally, the sizing of a BESS depends primarily on the application, battery technology, and the system's energy demand. This review mapped and identified existing computational and optimization methodologies for structured sizing in technical indicators of an MG with a BESS based on articles published between 2017 and 2021. A protocol was defined in which articles were filtered in multiple stages, undergoing strategic refinements to arrive at the final articles to address the Research Questions (RQs). The final number of articles was 44, and within these, technical indicators related to the RQs were addressed, covering the most relevant works and comparing them technically, including how each explains the objective and result of their work. The rejected articles did not meet the criteria established by the defined protocol, such as exclusion criteria, quality criteria, and RQs. In conclusion, studies employing the integration of machine learning coupled with optimization techniques exhibit a significant contribution to results, as historical data can aid machine learning for data prediction. [ABSTRACT FROM AUTHOR]

Fossil fuel consumption has progressively increased alongside global population growth, representing the predominant energy consumption pattern for humanity. Unfortunately, this persistent reliance on fossil fuels has resulted in a substantial surge in pollution emissions, exerting a detrimental influence on the delicate ecological balance. Therefore, it is imperative to find new renewable energy sources to replace fossil fuels. Solar energy is a clean energy source and has become the most preferred option for human day-to-day needs. Since the construction of the world's first floating photovoltaic power station, humanity has been continuously advancing the technology of power generation by floating photovoltaics. This review comprehensively elucidates the progression of offshore photovoltaic technology and illustrates the composition of the floating photovoltaic system. Each section meticulously contrasts the advantages and drawbacks of various photovoltaic systems. In addition, an in-depth analysis of the offshore photovoltaic application potentials is conducted based on fundamental theories, thereby offering valuable insights for future research. Finally, an encompassing summary of the potential challenges associated with deep-sea floating photovoltaic systems is presented. [ABSTRACT FROM AUTHOR]

Turkey is among the countries largely dependent on energy import. This dependency has increased interest in new and alternative energy sources. Installation of rooftop solar photovoltaic systems (RSPSs) in Turkey is increasing continuously regarding geographical and meteorological conditions. This paper presents an insight into the potential situation for Turkey and a simulation study for the RSPS designing and calculation for the faculty building at Marmara University in Istanbul. This simulation study demonstrates that 84.75-kWp grid-connected RSPS can produce remarkable power. The system is performed in detail with the PV*SOL software (Premium 2017 R8-Test Version, Valentin Software GmbH, Berlin, Germany). Detailed financial and performance analysis of the grid-connected RSPS for faculty building with various parameters is also carried out in this study. According to the simulation results, the system supplies 13.2% of the faculty buildings' annual electrical energy consumption. The annual savings value of faculty buildings' electrical consumption is approximately 90,298 kWh energy which costs roughly $7296. A photovoltaic (PV) system installation for the faculty building, which has considerable potential for solar energy and sunshine duration, is indispensable for clean energy requirements and was supported by the simulation results. This paper can be considered to be a basic feasibility study prior to moving on to the implementation project. [ABSTRACT FROM AUTHOR]

The majority of photovoltaic (PV) systems in the Netherlands are small scale, and installed on residential and commercial rooftops, where different objects in many cases may lead to the presence of shading and inevitable energy loss. Nevertheless, the energy loss due to expected shadow must be distinguished from the energy loss due to other malfunctions. In this study an algorithmic tool is presented that automates the process of analyzing monitoring data of partially shaded PV systems. The algorithm compares long-term and high-resolution yield data of a partially shaded PV system with the yield data of an unshaded PV system, as reference PV system, and automatically detects the energy loss due to the expected shadow, caused by any surrounding obstacles, and distinguishes it from any additional energy loss due to other malfunctions. This study focuses on PV systems with module-level power electronics (MLPE) since these are mostly used on PV systems on rooftops. Three different cases of shaded MLPE PV systems are presented to illustrate the versatility of the methodology. Furthermore, suggestions for further research are discussed at the end of the paper. [ABSTRACT FROM AUTHOR]

Chile has set itself to achieve Greenhouse Gas emission neutrality, with at least 70% of electricity coming from renewable energy sources by 2050. To this end, institutional and regulatory frameworks have been improved, resulting in significant progress in medium and large-scale projects. However, solar energy production at residential level and its surplus injection to all distribution networks has been very limited. This paper analyzes the evolution of the regulatory energy policies in Chile in order to contrast it with an economic evaluation of residential projects. The analysis focuses on the city of Arica, one of the highest potential regions in terms of solar energy within the country. There, a particularly low penetration of residential solar energy usage has been observed. Based on the current situation, projections are made for Arica in 2050, through the identification of barriers and opportunities on a residential scale development. According to some recommendations, there is the need to design policies that take into account the particular characteristics of each region within the country. [ABSTRACT FROM AUTHOR]

The protection of the natural environment and countering global warming are crucial worldwide issues. The residential sector has a significant impact on overall energy consumption and associated greenhouse gas emissions. Therefore, it is extremely important to focus on all of the activities that can result in more energy efficient and sustainable city scale areas, preventing global warming. The highest improvement in the energy efficiency of existing buildings is possible by combining their deep refurbishment and the use of renewable energy sources (RES), where solar energy appears to be the best for application in buildings. Modernizations that provide full electrification seem to be a trend towards providing modern, energy efficient and environmentally friendly, smart buildings. Moreover, switching from an analysis at the single building level to the district scale allows us to develop more sustainable neighborhoods, following the urban energy modelling (UEM) paradigm. Then, it is possible to use the energy cluster (EC) concept, focusing on energy-, environmental- and economic-related aspects of an examined region. In this paper, an actual Polish suburban district is examined using the home-developed TEAC software. The software is briefly described and compared with other computer codes applied for UEM. In this study, the examined suburban area is modernized, assuming buildings' deep retrofitting, the application of RES and energy storage systems, as well as usage of smart metering techniques. The proposed modernizations assumed full electrification of the cluster. Moreover, the examined scenarios show potential electricity savings up to approximately 60%, as well as GHG emission reduction by 90% on average. It is demonstrated that the proposed approach is a valid method to estimate various energy- and environment-related issues of modernization for actual residential clusters. [ABSTRACT FROM AUTHOR]

The increase in global energy demand has led to increased research in harvesting solar energy. Solar energy is widely used in homes, electric vehicles and is a great solution to power remote areas. DC–DC converters are essential in extracting power from solar panels. One of the main problems in designing converters for solar energy applications is boosting the low output voltage of the solar panel to meaningful levels. While there are several topologies to achieve high gain, some of the problems faced by them are the extreme duty ratio, complex design and discontinuous input current. This paper presents a novel topology that uses an interleaved input, a voltage lift capacitor and a hybrid switched capacitor network to achieve high gain without an extreme duty ratio or bulky magnetics. The proposed converter is controlled using a microcontroller which regulates the output voltage. The voltage lift capacitor and the switched capacitor network enhances the voltage gain over a conventional boost converter without an extreme duty ratio. The analysis and design of the proposed converter are presented and verified with a 100 W prototype. The results show that the converter provides a gain of 10, at a duty ratio of 30%, while delivering the designed output power with considerably high efficiency. [ABSTRACT FROM AUTHOR]

With the rapidly evolving mobile technologies, the number of cellular base stations (BSs) has significantly increased to meet the explosive demand for mobile services and applications. In turn, this has significantly increased the capital and operational expenses, due to the increased electricity prices and energy consumption. To generate electricity, power plants mainly rely on fossil fuels, which are non-renewable energy resources. As a result, CO 2 emissions also increase, which adversely affect health and environment. For wireless access technologies and cellular networks, BSs are the largest power consumer, and the network energy consumption is mainly dominated by the network infrastructure, which makes the telecommunications sector liable for energy consumption as well as CO 2 emissions around the globe. Alternatively, solar energy is considered as an eco-friendly and economically attractive solution, due to its cost-effectiveness and sustainability. In this paper, the potentials of photovoltaic (PV) solar power to energize cellular BSs in Kuwait are studied, with the focus on the design, implementation, and analysis of off-grid solar PV systems. Specifically, system components, such as the number of PV panels, batteries, and converters needed for the design are determined and evaluated via HOMER software, with the focus on minimizing the net present cost (NPC). A comparison between various PV, diesel generator (DG), and battery bank (BB) system configurations is also performed. Moreover, a comparison of system deployment area will be presented for different PV panels that have different output power and panel sizes, in addition to utilizing a solar tracking system. It is revealed that utilizing a hybrid system configuration (i.e., PV-DG-BB) decreases fuel consumption per year by almost 95% in comparison to the conventional DG-only based electric systems. Not only that, but utilizing a pure off-grid solar PV system (i.e., PV-BB) can significantly reduce the total NPC while completely eliminating CO 2 emissions; however, at the expense of more land. [ABSTRACT FROM AUTHOR]

The EU power sector is under increasing pressure due to rising electricity demand and the need to meet decarbonisation targets. Member states have been active in investing in renewables and building capacity to increase their share of renewables in electricity generation. However, it is important to examine what progress each member state has made in the deployment of renewable energy for electricity generation and what factors influence gross electricity generation from renewable energy. In this study, logarithmic mean Divisia index (LMDI) analysis was used to examine the changes in EU-27 countries' gross electricity generation from renewable energy sources (RES), wind, and solar PV from 2012 to 2021. The results show that the RES deployment per capita effect and the RES share effect were the main positive factors for the total gross electricity generation from RES in the EU. In contrast, the RES capacity productivity effect and the energy intensity effect had negative contributions. Population growth had a positive influence but was less significant than the other factors. The deployment of RES per capita effect was the main factor in the overall growth of gross electricity generation from RES in Northern Europe, Central Western Europe, and Central Eastern Europe, according to comparisons between the regional groups. RES share effect was the main driver in Southern Europe. The decrease in RES capacity productivity was the second most important factor influencing the variation in the amount of energy generated by RES in Northern Europe and Central Western Europe. The results could be used to develop more effective and tailored renewable energy policies that take into account the existing main drivers of RES, wind, and solar energy in each of the EU-27 member states. [ABSTRACT FROM AUTHOR]