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This purpose of this paper is to address the research problem of optimizing photovoltaic (PV) panel placement on building facades to maximize solar energy generation.

The study examines the significance of various design configurations and their implications for PV system performance. The research involves analysis of relevant literature and energy simulations. An exemplary case study is conducted in a hot climate zone to quantify the impacts of PV panel placement on energy generation. Various application scenarios are developed, resulting in 28 scenarios for PV on building facades. Energy simulations using Grasshopper Rhino software and Ladybug plugin components are performed.

The paper identifies key factors influencing PV panel placement and energy generation through qualitative analysis. It introduces an appropriateness matrix as a decision-making framework to evaluate placement options. The study identifies design configurations and external features impacting PV location selection and performs a qualitative classification to determine their impact on energy generation.

The results and decision-making framework enable informed choices based on solar radiation levels, shading conditions, and building requirements. Optimizing PV panel placement enhances solar energy harvesting in buildings, benefiting architects and engineers.

The novel contributions of this paper include practical insights and guidance for strategically placing PV panels on building facades.

This paper aims to develop a causal feedback structure that explains the dynamics of entrepreneurship development in Iran’s photovoltaic (PV) technological innovation system (TIS) to design effective policy interventions for fostering PV innovation.

This study adopts the system dynamics approach to develop the causal structure model. The methodology follows a systematic method to elicit the causal structure from qualitative data gathered by interviewing several stakeholders with extensive knowledge about different aspects of Iran’s PV TIS.

Lack of technological knowledge and financial resources within Iranian PV panel-producing firms are the main barriers to entrepreneurship development in Iran’s PV TIS. This study proposes two policy enforcement mechanisms to tackle these problems. The proposed feedback mechanisms contribute to the domestic PV market size and knowledge transfer from public research organizations to the PV industry.

The proposed policy mechanisms aid Iranian policymakers in designing effective policy interventions stimulating innovation in Iran’s PV industry.

The main contributions of this study include conceptualizing the causal structure capturing entrepreneurship dynamics in emerging PV TIS and proposing policy mechanisms fostering entrepreneurship and innovation in PV sectors.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

This study aims to focus on the transition of Kosovo’s energy generation sector from fossil fuels (94%), to renewable sources. The installation of 10 kW photovoltaic (PV) panels in individual houses will mitigate CO₂ emissions from electrical energy generation and contribute meeting the sustainable development goals (SDGs; 7, 11 and 13) set by United Nations General Assembly. This study case is based on the installation of PV panels on the roofs, and where possible on the facades of the private residential buildings in seven, the most populated towns of Kosovo (Prishtina, Prizren, Mitrovica, Peja, Gjakova, Ferizaj and Gjilan).

This study used the data, in regard to direct normal irradiation, altitude, coordinates, PV system configurations, specific PV power output and optimum tilt of PV panels specific for the selected locations,retrieved from Global Solar Atlas, which is a web-based-tool, as provided by “Solargis,”a company that provides online and commercial solar data resources, selected by The World Bank and the International Finance Corporation. The second software was RETScreen Expert, which is more sophisticated and allows input of more variables with regard to the proposed 10 kW PV system. With the use of RETScreen Expert software, the financial viability of the project, the equity payback period, and the reduction in greenhouse gas (GHG) emissions compared to the base case were assessed. Based on the gained data, the feasibility and outcome of the study case were assessed in terms of power generation, cost and comparison with the present PV installed capacities in Kosovo.

Small-scale solar energy generated from individual buildings can make great impact of country’s policies toward lowering CO₂ emission as one most influential greenhouse gas in rising average global temperature, improving air quality in towns by lowering emission of harmful gases and particulate matter (PM). As the study foresees installation of 10 kW of PV in residential houses, the calculated yearly energy generation would be around 15 MWh, which is twice of the average of real consumption of a household in Kosovo. This calculated energy generation from private houses is equal in capacity with generation of present PV parks that are connected on grid as reported from Transmission, System and Market Operator of the Republic of Kosovo. This proves that, if implemented, the study outcome would make Kosovo to meet the goal for a carbon free energy and meeting targets of at least three out of 17 SDG set by UNSC.

This paper’s model provides a ground for a transition of national energy sector from 90% fossils dependence to renewable energy sources (RES). Despite of some barriers such as cost of initial investment, energy storage, lack of government’s incentives and legislative base for households to become prosumer or at best energy self-sufficient buildings, this solution will make Kosovo harness its unused RES and meet targets of Paris Climate Agreement for net zero CO₂ emissions from energy production by 2050 and SDG targets.

Switching to green energy is a crucial step in achieving carbon neutrality. This study aims to explore what motivates people to use green energy and how much more people are willing to pay for green energy.

Grounded on the value–attitude–intention hierarchy, this study proposes that environmental consciousness as a human value influences attitudes including attitude toward environmental issues and attitude toward ecosocial benefits while attitudes, information and knowledge about green energy and quality and price of green energy influence people’s intention to use green energy. Data were collected from 342 Chinese adults.

Results showed that environmental consciousness significantly and positively influenced attitudes while attitude toward environmental issues had the greatest effect on people’s intention to use green energy, followed by quality and price of green energy. About 44% respondents were willing to pay 2.5% to <5% more money for green energy.

This study extended the use of value–attitude–intention hierarchy to investigate what motivates people to use green energy. Specifically, this study demonstrated that quality and price, and knowledge and information also significantly shaped people’s intention to use green energy significantly.

The primary aim of this study is to provide actionable guidance for augmenting profitability in photovoltaic power plant investments within Iran’s solar energy sector. By emphasizing prudent capital management and strategic investment decisions, our research seeks to assist emerging businesses in attaining sustained success in this domain.

This study presents a comprehensive approach to refined decision-making in Iran’s solar energy sector. Our methodology integrates the best-worst method, ArcGIS software for site selection, and the TOPSIS method for decision-making, aiming to enhance precision and reliability.

Our research has identified ten promising regions suitable for photovoltaic power plant installations in Iran. Leveraging the TOPSIS method, we have made optimal selections among these alternatives. Furthermore, our exhaustive cost analysis, incorporating factors like land prices, system maintenance, revenue estimation, and various financial scenarios, has yielded insights into project cost-effectiveness.

By filling a notable gap in the literature regarding optimal site selection and investment strategies for photovoltaic power plants in Iran, our research contributes to the sustainable development of solar energy infrastructure. Through a thorough literature review and the development of a novel methodology, we offer valuable guidance for businesses and investors seeking success in Iran’s solar energy sector. Our study represents a significant advancement by introducing a novel methodology that integrates the best-worst method, ArcGIS software, and the TOPSIS method for site selection and investment analysis. These findings furnish valuable guidance for businesses seeking success in the solar energy sector, thereby contributing to the sustainable development of renewable energy infrastructure in Iran and beyond.

The deployment of solar photovoltaic (PV) in higher education institutions is beneficial and critical for attaining sustainable campus goals. However, various barriers hamper the adoption of the technology, and unless these challenges are identified, formulating tailor made solutions to boost deployment will be challenging. Thus, this study aimed to identify the barriers to the deployment of PV in the public university sector in South Africa.

A critical review of the literature was conducted to identify the factors that negatively impact PV deployment. By screening the barriers identified from the literature using a conceptual framework, the barriers that were considered relevant to deployment within a university context were selected. Thereafter, the selected barriers and additional barriers recommended by panellists were verified through a three-round Delphi survey. The factors were either accepted or rejected as barriers in the sector based on the factors' mean score and interquartile range values.

The study observed that 12 barriers hamper PV deployment in the public university sector. The findings indicated that the top five barriers were the lack of incentives, lack of green building targets, lack of financial resources, high initial cost, and lack of clear policy direction. However, the study found that deployment was not hindered because there was resistance to change or uncertainty of recouping investment costs. The deployment was also not hindered because there was a lack of demand from electricity end-users or a lack of suitable installation space.

Given the lack of empirical studies on the subject in the region, the present study contributes to the body of knowledge by identifying the significant barriers that impede PV deployment in the public university sector. Furthermore, insight is provided on measures that relevant stakeholders can take to motivate and support universities to deploy the technology further.

This study aims to offer a hybrid stand-alone system for electric vehicle (EV) charging stations (CS), an emerging power scheme due to the availability of renewable and environment-friendly energy sources. This paper presents the analysis of a photovoltaic (PV) with an adaptive neuro-fuzzy inference system (ANFIS) algorithm, solid oxide fuel cell (SOFC) and a battery storage scheme incorporated for EV CS in a stand-alone mode. In previous studies, either the hydrogen fuel of SOFC or the irradiance is controlled using artificial neural network. These parameters are not controlled simultaneously using an ANFIS-based approach. The ANFIS-based stand-alone hybrid system controlling both the fuel flow of SOFC and the irradiance of PV is discussed in this paper.

The ANFIS algorithm provides an efficient estimation of maximum power (MP) to the nonlinear voltage–current characteristics of a PV, integrated with a direct current–direct current (DC–DC) converter to boost output voltage up to 400 V. The issue of fuel starvation in SOFC due to load transients is also mitigated using an ANFIS-based fuel flow regulator, which robustly provides fuel, i.e. hydrogen per necessity. Furthermore, to ensure uninterrupted power to the CS, PV is integrated with a SOFC array, and a battery storage bank is used as a backup in the current scenario. A power management system efficiently shares power among the aforesaid sources.

A comprehensive simulation test bed for a stand-alone power system (PV cells and SOFC) is developed in MATLAB/Simulink. The adaptability and robustness of the proposed control paradigm are investigated through simulation results in a stand-alone hybrid power system test bed.

The simulation results confirm the effectiveness of the ANFIS algorithm in a stand-alone hybrid power system scheme.

This study evaluates the aesthetic perception of photovoltaic (PV) systems situated at various locations on an apartment building facade, comparing them with the original facade. It also aims to understand how aesthetic dimensions influence the perception of PV installations in diverse building locations. Moreover, it aims to create a framework that will guide for installing PV installations considering both their functionality and aesthetics.

The study uses a mixed-method approach, including qualitative and quantitative approaches. It includes a literature review and a questionnaire. 418 participants evaluated different PV-embedded facades using a Likert scale across various aesthetic variables.

The findings indicate that aesthetic perceptions of PV vary by the location of installation. It also shows that all aesthetic dimensions affect PV installation aesthetics, with location-specific preferences. For original elevation, compatibility and simplicity are given precedence over blending and coherence for windows, creativity and harmony for facades, functionality and harmony for balconies, and innovation potential and simplicity for roofs.

This study focuses on a single building type; further investigation is required to examine other building types. It also examined one PV technology with common visual properties, but future studies can examine others. Additional research is needed to compare the participating groups and the effect of their sociodemographic factors, using on-site surveys and interviews.

Few studies have investigated how PV systems affect apartment building users' architectural aesthetic perception. The results of this study make a valuable contribution to the field of sustainable architecture by providing practical guidance for architects, engineers, stakeholders, and researchers who are interested in integrating aesthetic, user-centric considerations into renewable energy solutions.

Recent advancements in technology have led to the exploration of solar-based thermal radiation and nanotechnology in the field of fluid dynamics. Solar energy is captured through sunlight absorption, acting as the primary source of heat. Various solar technologies, such as solar water heating and photovoltaic cells, rely on solar energy for heat generation. This study focuses on investigating heat transfer mechanisms by utilizing a hybrid nanofluid within a parabolic trough solar collector (PTSC) to advance research in solar ship technology. The model incorporates multiple effects that are detailed in the formulation.

The mathematical model is transformed using suitable similarity transformations into a system of higher-order nonlinear differential equations. The model was solved by implementing a numerical procedure based on the Wavelets and Chebyshev wavelet method for simulating the outcome.

The velocity profile is reduced by Deborah's number and velocity slip parameter. The Ag-EG nanoparticles mixture demonstrates less smooth fluid flow compared to the significantly smoother fluid flow of the Ag-Fe3O4/EG hybrid nanofluids (HNFs). Additionally, the Ag-Ethylene Glycol nanofluids (NFs) exhibit higher radiative performance compared to the Ag-Fe3O4/Ethylene Glycol hybrid nanofluids (HNFs).

Additionally, the Oldroyd-B hybrid nanofluid demonstrates improved thermal conductivity compared to traditional fluids, making it suitable for use in cooling systems and energy applications in the maritime industry.

The originality of the study lies in the exploration of the thermal transport enhancement in sun-powered energy ships through the incorporation of silver-magnetite hybrid nanoparticles within the heat transfer fluid circulating in parabolic trough solar collectors. This particular aspect has not been thoroughly researched previously. The findings have been validated and provide a highly positive comparison with the research papers.