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The purpose of this paper is to design and implement a directly cooled photovoltaic thermal (PV/T) hybrid system.

The research design subjects, instruments and methods that were used to collect data are as detailed in the paper. Two polycrystalline photovoltaic (PV) modules were used in this study.

The directly water-cooled PV module (PV/T) was found to operate better as compared to a naturally cooled module for the first three months. The PV/T initially operated at a higher electrical efficiency for 87 per cent of the day. The monthly energy-saving efficiency of the PV/T was found to be approximately 61 per cent, while the solar utilisation of the naturally cooled PV module M1 was found to be 8.79 per cent and that of M2 was 47.93 per cent.

The major limitation was the continued drop in efficiency after the first three months of the PV/T placed outdoors. The fall in the efficiency was attributed to water ingress.

Direct water cooling of PV modules is possible, only that a better sealing is needed to prevent water ingress.

PV air cooling has been researched on. Use of water as a cooling medium has been carried out using serpentine pipes or riser tube, and no direct water cooling on the back of the module has been researched on.

The purpose of this paper is to propose a fixed PV energy system design and a sun tracking PV energy system design to meet the primitive energy demands of a typical house in Sakarya, Turkey with energy payback times (EPBT) and greenhouse payback times (GPBT) calculations.

The designs were developed based on the total solar radiation received on the surface of the PV modules. The EPBT and the GPBT of the designs were investigated by utilizing the current embodied energy data of the literature and annual energy output of the proposed systems. The monthly mean total solar radiation, the yearly total solar radiation and the annual energy output of the systems were calculated according to the results of previous studies of authors on 80-W prototypes of a fixed PV energy system tilted at the yearly optimum tilt angle of Sakarya and a two-axis sun tracking PV energy system.

The annual energy outputs of the fixed system and the tracking system were established to be 10.092 and 10.311 MJ, respectively. EPBT of the systems were estimated 15.347 years for the fixed system and 11.932 years for the tracking systems which were less than the lifespan of PV modules. The greenhouse gas emitted to produce and install the systems were estimated to be 6,899.342 kg for the fixed system and 5,040.097 kg for the tracking system. GPBT of the systems were calculated to be 5.203 and 2.658 years, respectively.

PV energy is clean without greenhouse gas emission during the operation. However, significant emissions occur in the life cycle of PV modules until the installation is completed. Therefore reducing the number of PV modules make great differences in the GPBT of PV energy systems. In this paper, comparisons between the GPBT results of the optimally tilted fixed system and tracking system were performed to discuss the best option by means of environmental concerns.

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 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 chapter contributes to the Public Value (PV) literature in relation to accounting by providing evidence on its content's operationalization through performance measurement. In particular, it establishes the link with Sustainable Development Goals (SDGs), which may work as guiding principles of a public organization’s action. Accordingly, organizations embedding SDGs include them in their strategic decisions and disclose them through performance measurement and narratives.

The SDGs' presence is explored in the PV of a sample of Italian health institutes through documentary analysis of their performance plans. The aim is to verify if and how SDGs are pursued and whether the COVID-19 pandemic has affected PV content.

Besides Goal No. 3 (Health), the PV content of the investigated institutes contains various SDGs. Before the pandemic, their PV was aligned with SDGs mainly related to prosperity, economic growth and social inclusion. In the following period, the number of SDGs increased, introducing planet and environmental protection dimensions. No one explicitly mentions pursuing SDGs, revealing a non-institutionalized sensitivity of managers towards SDGs. The analysis distinguishes between ‘core’ SDGs, revealed mostly by traditional performance measures disclosing the achievement of institutes' mission, and ‘complementary’ SDGs, expressed mostly through narratives. This can derive from performance measurement, which employs the language of performativity, while the contribution to society is relegated in the narratives, making them less incisive.

This chapter seeks to place the Paris agreement on anthropogenic greenhouse gases (COP21) in a wider picture on how the global solar photovoltaic (PV) market has been created and shaped over decades. The chapter discusses the role of solar PV actors, as well as other actors in the market-shaping process. The aim is to show how the COP21 can be interpreted in a wider historical perspective.

The chapter builds on expert interviews conducted after the COP21, as well as secondary data on historical studies on evolution of solar energy markets in various countries.

Although scientists and entrepreneurs have been important in creating and shaping the global solar PV market, it is noted that other actors have also had an influence on the market development. Particularly, politicians are seen as playing a crucial role through legislation and funding. Unfortunately for the solar PV market, support has fluctuated over time. The COP21 provides a clear pathway for positive support, and it is expected to bind governments for pro-solar politics even during low prices of fossil fuels and economic downturn.

The chapter provides an overview of what has happened in the history of global solar PV market. It gives reasoning as to why the COP21 is important in securing support for the solar PV market. Thus, it can provide reasoning as to why the COP21 can make a difference.

This is the first academic study that portrays the COP21 against historical evolution of the global solar PV market.

This paper aims to Solar photovoltaic (PV) power can significantly impact the power system because of its intermittent nature. Hence, an accurate solar PV power forecasting model is required for appropriate power system planning.

In this paper, a long short-term memory (LSTM)-based double deep Q-learning (DDQL) neural network (NN) is proposed for forecasting solar PV power indirectly over the long-term horizon. The past solar irradiance, temperature and wind speed are used for forecasting the solar PV power for a place using the proposed forecasting model.

The LSTM-based DDQL NN reduces over- and underestimation and avoids gradient vanishing. Thus, the proposed model improves the forecasting accuracy of solar PV power using deep learning techniques (DLTs). In addition, the proposed model requires less training time and forecasts solar PV power with improved stability.

The proposed model is trained and validated for several places with different climatic patterns and seasons. The proposed model is also tested for a place with a temperate climatic pattern by constructing an experimental solar PV system. The training, validation and testing results have confirmed the practicality of the proposed solar PV power forecasting model using LSTM-based DDQL NN.

This study aims to develop customer trust through information quality, customer awareness, and perceived value. This study is motivated by the hustle and bustle occurred as the result of the socialization of MyPertamina, a digital payment service for subsidized fuel customers in 11 areas of 4 provinces in Indonesia. The hustle and bustle can be viewed as customer distrust of MyPertamina. However, customer trust is a business success key. Is MyPertamina a solution or problem maker for customers to buy subsidized fuel?

The design of this study is survey. Primary data are collected through questionnaires sent to subsidized fuel customers in the socialization areas of MyPertamina. The data are processed using SPSS and Amos programs.

PV, IQ and CA, respectively, can develop CT on MyPertamina. Although the PV cannot strengthen the effect of CA on CT, the construct can strengthen the effect of IQ on CT.

Indonesian Government via Pertamina, a state-owned enterprise, must develop CT through IQ, CA and PV to succeed the application of MyPertamina.

This study develops IQ, CA and PV based on technology acceptance model and theory of reasoned action to develop CT on MyPertamina.

This study aims to provide an in-depth understanding of investors’ cognition and decision-making process with regard to internet financial products. The objective is to effectively guide users’ rational investments.

First, based on grounded theory, this study develops a tool for measuring users’ perceived value (PV) of internet financial products via in-depth interviews. Then, after comprehensively considering users’ environmental, individual and psychological characteristics, this study proposes a theoretical model of internet financial product investment decisions based on the PV of users. Finally, an empirical study is conducted on 693 valid sample data from e-commerce and online banking financial platforms.

The empirical results suggest that network externalities influence users’ financial behavior by herding (HE) (imitating others and discounting their own information) and PV. PV and HE are key factors in users’ investment decisions with regard to internet financial products. Moreover, users’ self-efficacy (SE) and platform type play moderate roles in the influence mechanism.

The research conclusions provide valuable references for designing financial products and establishing regulatory rules, which will help the internet financial industry to grow soundly and innovatively.

This study uncovers the mediating effect of HE and PV between network externalities and users’ investment intentions in the context of internet financial products. In addition, the moderating effect of users’ SE and platform types is revealed.

A key feature of human rights in health is access to safe, effective and affordable medicines. Pharmacovigilance is advocated for monitoring intended/unintended effects of medicines to assure their safety. The purpose of this paper is to synthesize knowledge about supply chain impediments to safe medicines in developing nations and contribute to future development of research in this field.

This paper conducts a structured literature review based on Preferred Reporting Items for the Systematic Reviews and Meta-Analyses guidelines. It aims at profiling supply chain impediments to safe medicines in developing nations by reviewing 46 recent pharmacovigilance-specific papers published between 2005 and 2020.

Analysis of reviewed articles identified criticality of supply chain impediments that affect constituents across pharmaceutical in developing nations, which still struggle to maintain robust national pharmacovigilance systems due to lack of awareness, policy and practices.

Research results can be applied by pharmaceutical industry decision-makers and drug safety professionals in developing nations. Because the review is qualitative in nature, its implication ought to be tested after actual implementation.

This review can help identify underinvestigated impediments and methods to aid in developing new pharmacovigilance knowledge areas in developing nation context.

The review uncovers gaps in global health equity dialogue in developing nations. It also recognizes that macrolevel supply chain impediments exist due to unfair disease burden and health inequities in developing nations.

The paper examines supply chain impediments to safe medicines in developing nations with insights for future pharmacovigilance research. Identifying and classifying supply chain impediments through this review is the first step toward creating effective interventions for these impediments to safe medicines.