Search results

Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs. Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper aims to propose a novel tracker while using MPPT to boost the PV system's actual efficiency accounting for the involved costs.

The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

To the best of the authors’ knowledge, this work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

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 allows more accurate estimation of the economy in investing in PV electrification for buildings, especially for Gulf Cooperation Council Countries (GCCC) where they have nearly similar climate and building structure. The actual solar electricity yield from this building is used to make empirical modelling.

The accurate automated daily-recorded solar electricity from 8.64 kW solar PV on a rooftop of Sadeem Building at Awali, Bahrain, was modelled to polynomial equations of order of 6. The effect of the tilt (β) and azimuth (Ψ) angle of PV panels for smart and sustainable buildings is studied.

The correlation of each set of polynomial equation (R²) is listed and had reached a highest value of 0.9792 (for order of 6) with lowest value of 0.1853 (for order of 1). The model may be also applied to the GCCC. The results show that each kW of PV will have a solar electricity yield, on average, of 4.1 kWh. It also shows that the tilt angle has little influence on the solar electricity yield (less than 10%) when the tilt angle changed from 26° to 0° or from 26° to 50°. The influence of the azimuth angle is found to be more than 50% in changing Ψ from 90° to 180°.

The model may not be restricted to Bahrain but applies – to a certain extent – to GCCC (six countries) and to other countries having buildings with similar roof design and at latitude close to the latitude of Bahrain.

The model enables developers and investors to estimate, with high accuracy, the solar electricity provided from a building if PV panels are to be installed on its rooftop (or facade) at different tilt (β) and azimuth (Ψ) angle for smart and sustainable buildings.

Empirically finding out how much each kW of solar PV integrated to the building will produce solar energy electricity (in kWh), that is, 1 kW of PV yield, on average, 4.1 kWh.

Establishing empirical models to evaluate the outcome of each installed kW of PV panels. Each 1 kW installation of PV panels is 4.0 kWh/day, on average. This is less than what commercial companies claim for this region, that is, 1 kW produces 5.5 kWh/ day – which affects the estimated economic outcome of PV projects.

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.

The Kingdom of Saudi Arabia (KSA) is facing a rapid growth in energy demand mainly because of factors like burgeoning population, economic growth, modernization and infrastructure development. It is estimated that between 2000 and 2017 the power consumption has increased from 120 to 315 TWh. The building sector has an important role in this respect as it accounts for around 80 percent of the total electricity consumption. The situation is imposing significant energy, environmental and economic challenges for the country. To tackle these problems and curtail its dependence on oil-based energy infrastructure, KSA is aiming to develop 9.5 GW of renewable energy projects by 2030. The campus of the King Fahd University of Petroleum and Minerals (KFUPM) has been considered as a case study. In the wake of recently announced net-metering policy, the purpose of this paper is to investigate the prospects of rooftop application of PV in buildings. ArcGIS and PVsyst software have been used to determine the rooftop area and undertake PV system modeling respectively. Performance of PV system has been investigated for both horizontal and tilted installations. The study also investigates the economic feasibility of the PV application with the help of various economic parameters such as benefit cost ratio, simple payback period (SPP) and equity payback periods. An environmental analysis has also been carried out with the help of RETScreen software to determine the savings in greenhouse gas emissions as a result of PV system.

This study examines the buildings of the university campus for utilizable rooftop areas for PV application. Various types of structural, architectural and utilities-related features affecting the use of building roofs for PV have been investigated to determine the corrected area. To optimize the performance of the PV system as well as space utilization, modeling has been carried out for both horizontal and tilted applications of panels. Detailed economic and environmental assessments of the rooftop PV systems have also been investigated in detail. Modern software tools such as PVsyst, ArcGIS and RETScreen have also been used for system design calculations.

Saudi Arabia is embarking on a massive solar energy program as it plans to have over 200 GW of installed capacity by 2030. With solar energy being the most abundant of the available renewable resource for the country, PV is going to be one of the main technologies in achieving the set targets. The country has, however, unlike global trends, traditionally overlooked the small-scale and building-related application of solar PV, focusing mainly on larger projects. This study explores the prospects of utilization of solar PV on building roofs. Building rooftops are constrained in terms of PV application owing to wide ranging obstacles that can be classified into five types – structural, services, accessibility, maintenance and others. The total building rooftop area in the study zone, calculated through ArcGIS has been found to be 857,408 m² of which 352,244 m² is being used as car parking and hence is not available for PV application. The available roof area, 505,165 m² is further hampered by construction and utilities related features including staircases, HVAC systems, skylights, water tanks and satellite dish antennas. Taking into account the relevant obstructive features, the net rooftop area covered by PV panels has been found to be in the range 25–41 percent depending upon the building typology, with residential buildings offering the least. To optimize both the system efficiency and space utilization, PV modeling has been carried out with the help of PVsyst software for both the tilted and horizontal installations. In terms of output, PV panels with tilt angle of 24° have been found to be 9 percent more efficient compared to the horizontally installed ones. Modeling results provide a net annual output 37,750 and 46,050 MWh from 21.44 and 28.51 MW of tilted and horizontal application of PV panels, sufficient to respectively meet 16 and 20 percent of the total campus electricity requirements. Findings of the economic analysis reveal the average SPP for horizontal and tilted applications of the PV to be 9.2 and 8.4 years, respectively. The benefit cost ratio for different types of buildings for horizontal and tilted application has been found to be ranging between 0.89 and 2.08 and 0.83 and 2.15, respectively. As electricity tariff in Saudi Arabia has been increased this year by as much as 45 percent and there are plans to remove $54bn of subsidy by 2020, the cost effectiveness of PV systems will be greatly helped. Application of PV in buildings can significantly improve their environmental performance as the findings of this study reveal that the annual greenhouse gas emission in the KFUPM campus can be reduced by as much as 40,199 tons carbon dioxide equivalent.

The PV application on building roof especially from economic perspective is an area which has not been addressed thus far. Khan et al. (2017) studied the power generation potential for PV application on residential buildings in KSA. Asif (2016) also investigated power output potential of PV system in different types of buildings. Dehwas et al. (2018) adopted a detailed approach to determine utilizability of PV on residential building roofs. None of these studies have covered the economics of PV systems. This study attempts to address the gap and contribute to the scholarship on the subject. It targets to determine the power output from different types of building in an urban environment by taking into account building roof conditions. It also provides detailed economic assessment of PV systems. Subsequent environmental savings are also calculated.

Solar photovoltaic (PV) is commonly used as a renewable energy source to provide electrical power to customers. This research establishes a method for testing the performance reliability of large grid-connected PV power systems. Solar PV can turn unrestricted amounts of sunlight into energy without releasing carbon dioxide or other contaminants into the atmosphere. Because of these advantages, large-scale solar PV generation has been increasingly incorporated into power grids to meet energy demand. The capability of the installation and the position of the PV are the most important considerations for a utility company when installing solar PV generation in their system. Because of the unpredictability of sunlight, the amount of solar penetration in a device is generally restricted by reliability constraints. PV power systems are made up of five PV modules, with three of them needing to be operational at the same time. In other words, three out of five. Then there is a charge controller and a battery bank with three batteries, two of which must be consecutively be in operation. i.e. two out of three. Inverter and two distributors, all of which were involved at the same time. i.e. two out of two. In order to evaluate real-world grid-connected PV networks, state enumeration is used. To measure the reliability of PV systems, a collection of reliability indices has been created. Furthermore, detailed sensitivity tests are carried out to examine the effect of various factors on the efficiency of PV power systems. Every module's test results on a realistic 10-kW PV system. To see how the model works in practice, many scenarios are considered. Tables and graphs are used to show the findings.

The system of first-order differential equations is formulated and solved using Laplace transforms using regenerative point techniques. Several scenarios were examined to determine the impact of the model under consideration. The calculations were done with Maple 13 software.

The authors get availability, reliability, mean time to failure (MTTF), MTTF sensitivity and gain feature in this research. To measure the reliability of PV systems, a collection of reliability indices has been created. Furthermore, detailed sensitivity tests are carried out to examine the effect of various factors on the efficiency of PV power systems.

This is the authors' original copy of the paper. Because of the importance of the study, the references are well-cited. Nothing from any previously published articles or textbooks has been withdrawn.

Renewable energy sources such as solar photovoltaic (PV) and wind are ubiquitous because of their lower environmental impact. Output from solar PV and wind turbines is unstable; hence, this article aims to propose an effective controller to extract maximum available power.

By focusing on the varying nature of solar irradiance and wind speed, the paper presents the maximum power point tracking (MPPT) technique for renewable energy sources, and power regulation is made by the novel inverter design. Moreover, a DC–DC boost converter is adopted with solar PV, and a doubly fed induction generator is connected with the wind turbine. The proposed MPPT technique is used with the help of a rain optimization algorithm (ROA) based on bi-directional long short-term memory (Bi-LSTM) (ROA_Bi-LSTM). In addition, the sinusoidal pulse width modulation inverter is used for DC–AC power conversion.

The proposed MPPT technique has jointly tracked the maximum power from solar PV and wind under varying climatic conditions. The power flow to the transmission line is stabilized to protect the load devices from unregulated frequency and voltage deviations. The power to the smart grid is regulated by three-level sinusoidal pulse width modulation inverter.

The methodology and concept of the paper are taken by the author on their own. They have not taken a duplicate copy of any other research article.

This paper aims to explore the process of implementing solar photovoltaic (PV) systems in construction to contribute to the understanding of systemic innovation in construction.

The exploratory research presented is based on qualitative data collected in workshops and interviews with 76 construction- and solar-industry actors experienced in solar PV projects. Actor-specific barriers were identified and analysed using an abductive approach.

In light of established definitions of systemic innovation, the process of implementing solar PV systems in construction involves challenges regarding technical and material issues, competencies, and informal and formal institutions. The specificities of this case highlight the necessity of paying attention to details in the process and to develop knowledge of systemic innovation in construction since the industry’s involvement in addressing societal challenges related to the energy transition will require implementing such innovations much more in the future.

New knowledge of solar PV systems as an innovation in professional construction is collected, enabling the adaptation of management strategies for its implementation. This knowledge can also be applied generally to other challenges encountered in highly systemic innovation implementation. Solar industry actors can gain an understanding of solar-specific challenges for the construction industry, challenges for which they must adapt their activities.

The exploration of actor-specific experiences of solar PV projects has resulted in a novel understanding of this specific innovation and its implementation. The findings illustrate a case of a high level of systemic innovation and the need to use a finer-grained scale for classification when studying innovation in construction.

The purpose of this paper is to focus on life cycle cost analysis (LCCA) of 1 MW roof-top Solar Photovoltaic (PV) panels installed in warm and humid climatic region in Southern India. The effect of actual power generated from solar PV panels on financial indicators is evaluated.

LCCA is done using the actual power generated from solar PV panels for one year. The net present value (NPV), internal rate of return (IRR), simple payback period (SPP) and discounted payback period (DPP) are determined for a base case scenario. The effect of service life and the differences between the ideal power expected and the actual power generated is evaluated.

A base case scenario is evaluated using the actual power generation data, 25-year service life and 6 percent discount rate. The NPV, IRR, SPP and DPP are found to be INR 13m, 8 percent, 10.9 years and 18.8 years respectively. It is found that the actual power generated is about one-third less than the ideal power estimated by consultants prior to project bidding. The payback period increases by 70–120 percent when the actual power generated from solar PV panels is considered.

The return on investment calculated based on ideal power generation data without considering the operation and maintenance related aspects may lead to incorrect financial assessment. Hence, strategies toward solar power generation should also focus on the actual system performance during operation.

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.