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The purpose of this study is optimization of existing PV system and by making the optimization to reach the heights energy performance from the system.

The methodology used in this work is analytical as well as software using PV*SOL premium software. Both methods are used to achieve a more realistic analysis of the results achieved at the end of the work.

After analyzing the optimization of the PV system in terms of certain atmospheric conditions, it is clear that the optimization of the system is necessary. Through the optimization of the systems, a better performance of the system is achieved, as well as in the case in question, it affects the increase of the energy generated annually up to 500 kWh.

This work is the original work of the author, which represents a part of the topic of the doctorate.

This paper aims to develop a selective energy optimisation of the photovoltaic–thermal (PV/T) system performance. The PV cell inside the PV/T system could be periodically manipulated to produce domestic hot water without applying an external power supply.

A numerical simulation model of the proposed PV/T model was developed in MATLAB/Simulink to analyse the selective energy optimisation of the model. The extrinsic cell resistance (R_se) is adjusted to control the ratio of thermal to the electrical energy, generated from the PV cell inside the PV/T system. Therefore, the internal heat of the PV cell inside the PV/T system is periodically used as a thermal element to produce electrical power and hot water.

The optimisation of PV/T energy shows that the electrical power efficiency can increase by 11.6% when R_se was 0 Ω, and the 200 L water tank temperature increased by 22ºC when R_se was 50 Ω.

This study showed that the use of the PV cell could be extended to domestic hot water and space heating, and not only for electricity.

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.

The main purpose of this controller is to carryout irrigation by the farmers with renewable energy resources.

The proposed design includes the Deep learning based intelligent stand-alone energy management system used for irrigation purpose. The deep algorithm applied here is Radial basis function neural network which tracks the maximum power, maintains the battery as well as load system.

The Radial Basis Function Neural Network algorithm is used for carrying out the training process. In comparison with other conventional algorithms, this algorithm outperforms by higher efficiency and lower tracking time without oscillation.

It is little complex to implement the hardware setup of neural network in terms of training process but the work is under progress.

The practical hardware implementation is under progress.

If controller are implemented in a real-time environment, definitely it helps the human-less farming and irrigation process.

If this system is implemented in real-time environment, every farmer gets benefitted.

This study aims to provide and illustrate the application of a framework for conducting techno-economic analyses (TEA) of early-stage designs for net-zero water and energy, single-family homes that meet affordable housing criteria in diverse locations.

The framework is developed and applied in a case example of a TEA of four designs for achieving net zero-water and energy in an affordable home in Saint Lucie County, Florida.

Homes built and sold at current market prices, using combinations of well versus rainwater harvesting (RWH) systems and grid-tied versus hybrid solar photovoltaic (PV) systems, can meet affordable housing criteria for moderate-income families, when 30-year fixed-rate mortgages are at 2%–3%. As rates rise to 6%, unless battery costs drop by 40% and 60%, respectively, homes using hybrid solar PV systems combined with well versus RWH systems cease to meet affordable housing criteria. For studied water and electricity usage and 6% interest rates, only well and grid-tied solar PV systems provide water and electricity at costs below current public supply prices.

This article provides a highly adaptable framework for conducting TEAs in diverse locations for designs of individual net-zero water and energy affordable homes and whole subdivisions of such homes. The framework includes a new technique for sizing storage tanks for residential RWH systems and provides a foundation for future research at the intersection of affordable housing development and residential net-zero water and energy systems design.

This paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.

The WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.

The coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.

To improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

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 study is to examine the effects of using discrete and continuous porous layers on the convective heat transfer improvement for multiple slot jet impingement onto a flat surface under magnetic field.

In the domains which are separated by the porous layers, uniform magnetic field with different strengths is used and as the solution technique finite element method is used. The numerical study is conducted considering different values of parameters: Reynolds number (250–1000), strength of magnetic field in different domains (Hartmann number between 0 and 20), permeability of discrete or continuous layers (Darcy number between 105 and 102) and number of layers in discrete case (2–10). Artificial neural network is used for performance estimation of systems equipped with different types of porous layers.

It is observed that significant differences occur in the local Nu between the discrete and continuous layer case, especially at lower Re, while peak Nu value is 77% higher in discrete layer configurations as compared to continuous one at Re = 250. Upper domain magnetic field results in average Nu enhancement, while the trend is opposite for the lower domain magnetic field strength. The increment amount becomes 10%, while the reduction amount is obtained as 38% at the highest magnetic field strengths. The permeability of layers in both cases and number of layers in discrete porous layer case provide effective solution for the cooling performance control. A modeling approach based on artificial neural networks provides fast thermal performance estimations of multiple impinging jets equipped with discrete and continuous porous layers.

Outcomes of the study are useful in development and optimization of new cooling systems in many thermal engineering systems encountered in photovoltaic panels, micro-electro-mechanical systems, metal processing and many others.

The organization of services can affect the adoption of sustainable practices within the relationship between a buyer (e.g. a shipper) and a supplier (e.g. a logistics service provider–LSP). The purpose of this paper is to analyse, within this relationship, the mechanisms affecting collaboration between shippers and LSPs towards adopting green logistics practices to reduce the negative environmental effects of logistics processes. The authors take the perspective of small and medium enterprises (SMEs), which represent – although less investigated than large enterprises – a relevant field of investigation given their impact on the environmental sustainability of logistics processes.

The authors conducted a multiple case-study investigation on a set of dyads involving shippers and LSPs. The authors explored the antecedents shaping the approach to sustainability in logistics and, adopting the absorptive capacity (AC) theory, the learning and knowledge transfer processes leading to the adoption of green practices.

Collaboration between shippers and LSPs for better sustainability in logistics seems not to work when relationships are limited to simple annual (or pluriannual) contracts, and when shippers do not show ambition to improve the level of sustainability of their logistics processes (regardless of whether they show an interest in general sustainability matters). On the other hand, successful cases show higher commitment in the dyadic relationship with respect to improving logistics sustainability, good levels of communication and a more structured process of knowledge sharing, enabled by IT integration, shared performance monitoring, and creation of inter-organizational teams.

While most of the existing research focuses on the perspective of shippers or LSPs, this work is original since it explores collaborative mechanisms within a buyer-supplier relationship simultaneously taking the perspective of both parties, according to the lens of the AC. It identifies directions for improving collaboration within the shipper-LSP relationship in the context of SMEs to foster the adoption of collaborative green logistics practices to impact sustainability positively.

This paper aims to analyze energy and exergy analysis of solar-based intercooled and reheated gas turbine (GT) trigeneration cycle using parabolic trough solar collectors (PTC) with the use of MATLAB 2018.

In the first section of this paper, the solar-based GT is validated with the reference paper. According to the reference paper, the solar field is comprising 30 modules in series and 35 modules in parallel series, where a total of 1,050 modules of PTC are taken into consideration. In the second part of this paper, the hybridization of the solar, GT trigeneration cycle is analyzed and optimized. In the last section of this paper, the hybridization of solar, intercooled and reheated GT trigeneration systems is examined and compared.

The results examined the first section, the power produced by the cycle will be 37.34 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and the efficiencies of energy and exergy will be 38.34% and 39.76%, respectively. The results examined in the second section, the power produced by the cycle will be 38.4 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and accordingly the efficiency of energy and exergy is found to be 40.011% and 41.763%. Where in the last section, the power produced by the cycle will be 41.43 MW at 0.5270 kg/s mass flow rate of the natural gas consumption and the energy and exergy efficiencies will be 39.76% and 40.924%, respectively.

The author confirms that this study is original and has neither been published elsewhere nor it is currently under consideration for publication elsewhere.