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The important factors, which should be considered in the design of a hybrid system of photovoltaic and wind energy are discussed in this study. The current load demand for electricity, as well as the load profile of solar radiation and wind power of the specified region chosen in Iran, is the basis of design and optimization in this study. Hybrid optimization model for electric renewable (HOMER) software was used to simulate and optimize hybrid energy system technically and economically.

HOMER software was used to simulate and optimize hybrid energy system technically and economically.

The maximum radiation intensity for the study area is 7.95 kwh/m²/day for July and the maximum wind speed for the study area is 11.02 m/s for January.

This research is the result of the original studies.

Under the pressure of environment degradation and energy consumption rises, solar photovoltaic power generation (SPPG) has been seen as a strategic emerging industry in China. However, the SPPG projects have many uncertain factors in the process of the life cycle. The purpose of this paper is to evaluate the investment risk comprehensively.

Specifically, this paper firstly identified the risk factors and consequences of SPPG project investment and constructed the investment risk factor evaluation index system. Secondly, the factor analysis method was used to reveal the key investment risk factors and risk consequences. Then, the research hypotheses and conceptual model were proposed, and the empirical analysis was conducted based on the structural equation model (SEM).

The results showed that the six key risk factors (political, economic, technological, management, market and natural) have a significant impact on the risks during the whole period. The influence degree of risk factors in the operational period is such that market factor > political factor > economic factor > management factor > natural factor > technical factor. In addition, the risk of constructional period has a significant impact during the risk of operational period. Except for natural factors, all risk factors are correlated among the mutual influence relationship of risk factors. Finally, this paper puts forward management implications based on the above conclusions: effectively identify investment risk factors and comprehensively improve risk management ability; (refine the risk factors of SPPG project investment and develop targeted risk prevention and control strategies; define risk management objectives and make relevant strategic plans.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further.

It can also help stakeholders propose risk prevention strategies throughout the entire process, to promote the sustainable development of SPPG projects.

This study focuses on the investment risk of SPPG projects, by building an evaluation index system to identify key risk factors, and then establishes a SEM covering constructional period risks and operational period risks to better explore SPPG project risks, in an effort to reveal the mutual influence relationship and influence path of investment risk factors of the projects.

This paper aims to achieve accurate maximum power from solar photovoltaic (PV), its five parameters need to be estimated. This study proposes a novel optimization technique for parameter estimation of solar PV.

To extract optimal parameters of solar PV new optimization technique based on the Jellyfish search optimizer (JSO). The objective function is defined based on two unknown variables and the proposed technique is used to estimate the two unknown variables and the rest three unknown variables are estimated analytically.

In this paper, JSO is used to estimate the parameters of a single diode PV model. In this study, eight different PV panels are considered. In addition, various performance indices, such as PV characteristics, such as power-voltage and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE) are determined using the proposed algorithm and existing algorithms. The results for different solar panels have been obtained under varying environmental conditions such as changing temperature and constant irradiance or changing irradiance and constant temperature.

The proposed technique is new and provides better results with minimum RE, RMSE, NMAE, MAE and converges fast, as depicted by the fitness graph presented in this paper.

Over the past decade, the United Arab Emirates (UAE) introduced several green regulatory guidelines, federal decrees, and a considerable number of environmentally friendly initiatives. Hence, the purpose of this paper is to investigate the top green materials and systems used currently in the UAE construction industry as per the new laws dictate as well as see if professionals are switching over to incorporate more green materials, systems, and/or designs.

The work involved reviewing internationally popular green materials and systems for construction, developing a questionnaire based on the literature review, surveying professionals in the seven UAE emirates, and ranking the findings based on the relative importance index.

Findings found the top used green materials and system in the UAE’s construction industry. As well as identified that there is a communication gap between the design and implementation phases that is possibly hindering the use of more green materials and systems.

This study sets a baseline to measure the UAE’s progress over the coming years in terms of integrating more green construction materials, systems, methodologies, and trends.

The purpose of this study was to design a renovation plan for a university campus building (Department of Electrical and Computer Engineering) with the aim to achieve nearly zero energy performance, ensuring a low specific demand (lower than 44 kWh/m²) and a high level of on-site renewable generation (equivalent to more than 20 per cent of the energy demand).

The baseline demand was characterized based on energy audits, on smart metering data and on the existing building management system data, showing a recent reduction of the electricity demand owing to some implemented measures. The renovation plan was then designed with two main measures, the total replacement of the actual lighting by LEDs and the installation of a photovoltaic system (PV) with 78.8 kWp coupled with an energy storage system with 100 kWh of lithium-ion batteries.

The designed renovation achieved energy savings of 20 per cent, with 27.5 per cent of the consumed energy supplied by the PV system. This will ensure a reduction of the specific energy of the building to only 30 kWh/m², with 42.4 per cent savings on the net-energy demand.

The designed renovation proves that it is possible to achieve nearly zero energy goals with cost-effective solutions, presenting the lighting renovation and the solar PV generation system a payback of 2.3 and 6.9 years, respectively.

This study innovated by defining ambitious goals to achieve nearly zero energy levels and presenting a design based on a comprehensive lighting retrofit and PV generation, whereas other studies are mostly based on envelope refurbishment and behaviour changes.

The purpose of the proposed hybrid method aims to increase population efficiency, and a local search is used to further improve the value of the global best solution. An experimental observation suggests that the model’s statistical outcomes are more aligned with the real-time experimental findings.

A novel metaheuristic efficient hybrid algorithm, i.e. hybrid particle swarm optimization rat search algorithm, is introduced and applied for parameter extraction of hybrid energy system. This proposed hybrid method rules out the chances of local minima, hence enhancing the precision of the parametric estimation. The parameter extraction and error is calculated for the solar photovoltaic (PV)–fuel cell system using the proposed algorithm.

Nonparametric statistical tests are also conducted to indicate the findings of the outcome parameters using various metaheuristic algorithms. The proposed algorithm is better than the rest of the compared algorithms in the study.

The authors proposed a novel algorithm, and this proposed algorithm is implemented on hybrid solar PV and fuel cell-based system for parameter extraction. The nonparametric test results clearly suggest that the proposed algorithm is far more effective for parameter estimation of the test system.

This article reflects an analysis of the energy issues tackled in national foresight studies to date. The energy sector has not been explicitly mentioned in some of the studies but it is integrated in other sectors. What follows is a summary of the issues on which the different foresight studies are focused. The summary includes the most important topics affecting energy‐related issues for the panel of experts of each country. The article shows, first, a group of general considerations specific for each country. It then shows the types of technologies which have been considered in each foresight study. Finally, before drawing conclusions, it provides a technology table from which it is possible to see which energy technologies have been considered as important in each country.

Priorities of decarbonizing the mining sector together with an availability of cost-effective technological solutions lead renewable energy (RE) to become an attractive energy source for the mining industry. Several pilot projects are run as hybrid systems, providing additional capacity to traditional energy systems. The purpose of this paper is to develop a mathematical model as a decision-making tool. The decision refers to a replacement of the fossil fuel system contains by the hybrid system in the sense of no return.

Four systems are considered. System one contains only a diesel plant. System two consists of a hybrid energy system with a photovoltaic (PV) part and a genset as back-up. System three includes a conventional natural gas combined cycle (CGCC) plant. Finally, system four covers a hybrid energy system with a PV part and CGCC turbine. The mathematical model is based upon the well-known concept of levelized cost of electricity.

The scenarios account for the degradation rate of PV modules, the PV yields of mines in different locations and the greenhouse gas emissions impact. The results show the break-even times of each scenario and the years of no return for the four systems in each scenario.

The solution of the model is performed for two case-studies. Case study 1 compares the diesel and hybrid PV-diesel systems. Case study 2 compares the CGCC and hybrid PV-natural gas systems.

This model can be generalized to all mining settings, with specific practical implications for off-grid mines.

The results of this paper bring a valuable contribution to carbon dioxide emissions reduction.

The paper aims to enhance the attention of decision-makers on fossil fuel and RE technologies increase the attractiveness of RE in powering mining operations.

The paper aims to present a grid-connected multi-inverter for solar photovoltaic (PV) systems to enhance reliability indices after selected the placement and level of PV solar.

In this study, the associated probability is calculated based on the solar power generation capacity levels and outages conditions. Then, based on this probability, dependability indices like average energy not supplied (AENS), expected energy not supplied and loss of load expectations (LOLE) are computed, also, another indices have been computed such as (customer average interruption duration index (CAIDI), system average interruption frequency index (SAIFI) and system average interruption duration index (SAIDI)) addressing by affected customers with distribution networks reliability assessment, including PV. On the basis of their dependability indices and active power flow, several PV solar modules installed in several places are analyzed. A mechanism for assessing the performance of the grid's integration of renewable energy sources is also under investigation.

The findings of this study based on data extracted form a PV power plant connected to the power network system in Diyala, Iraq 132 kV, attempts to identify the system's weakest points in order to improve the system's overall dependability. In addition, enhanced reliability indices are given for measuring solar PV systems performance connected to the grid and reviewed for the benefit of the customers.

The main contributions of this study are two methods for determining the reliability of PV generators taking into consideration the system component failure rates and the power electronic component defect rates in a PV system which depend on the power input and the power loss using electrical transient analysis program (ETAP) program.

The purpose of this paper is to propose a conceptual framework for handling end of life (henceforth EoL) scenarios of solar photovoltaic (solar PV) panels, which includes different options available to businesses and end-users, as well as promoting the collaboration between government and all relevant stakeholders.

This paper adopts purposeful sampling, secondary data and content analysis to develop an appropriate conceptual framework that helps to create awareness of the appropriate options for dealing with the EoL cases of solar PV panels.

From the data analysis, it is revealed that reuse, repair and recycling of solar PV panels can ensure value creation, public-private partnership and a solution for education in sustainability, and thus, prolonging the useful life cycle of the products.

This paper limits the analysis on developing economies and the use of selected literature based on the recycling of solar PV panels.

This paper is an initial attempt to create an awareness by identifying, analyzing and educating the stakeholders to handle appropriately any EoL scenario of solar PV panels.