Deployment Of Photovoltaic Systems Research Articles

Unveiling mega-prosumers for sustainable electricity generation in a developing country with techno-economic and emission analysis

In response to the urgent climate crisis, there is a growing emphasis on reducing carbon emissions and decreasing reliance on fossil fuels. This research aims to explore the possibility of enhancing renewable energy production in Bangladesh by installing photovoltaic (PV) systems on the rooftops of 30 universities to fulfill the sustainable development goal-7 (SDG-7). Helioscope is used for planning the deployment of PV systems while DIgSILENT PowerFactory is utilized for analyzing their impact on the grid. Site selection and data collection are conducted considering energy consumption and solar potential at different universities in Bangladesh. The results indicate that 29.5 MW (approximately) of power could be generated from approximately 84,295 solar panels rated at 350 W, producing about 43 GWh of electricity annually. Technical assessments on grid stability demonstrate that PV integration significantly reduces grid dependency and enhances voltage security. Economic analyses reveal that the proposed PV project is cost-effective compared to existing power plants, considering all relevant expenses. Furthermore, there is a reduction in CO2 emissions due to this project of 890.72 tons, per year, which translates to an emission factor of approximately 0.608 kg of CO2-eq/kWh. In particular, this study endorses the use of rooftop solar PV systems for universities in Bangladesh as mega-prosumers to promote sustainability and increase energy consumption, demonstrating their technical, economic, and environmental feasibility.

The Role of Education and Science-Driven Tools in Scaling Up Photovoltaic Deployment

Accelerating the deployment of Photovoltaic (PV) systems is a key contributing factor in achieving climate neutrality. Even though solar power is one of the cheapest energy sources and its deployment is growing rapidly around the world, an even faster growth is required to achieve existing climate goals. Besides the role that finance and permitting can play as enablers or barriers to this, the key elements to enable fast PV deployment are the use of education, and science and data-driven tools to empower citizens, installers, and investors to make their decisions based on robust scientific evidence. This perspective article aims to summarize the key concepts presented and discussed during the side event at COP27 on PV resources towards climate neutrality. The article will accomplish this by highlighting two key aspects: (1) the advantages of using solar-related education and data-driven tools, and (2) showcasing the significance of education, improved data and tools, community involvement, and PV mapping in expediting the deployment of PV systems.

Simulation of a floating solar farm in waves with a novel sun-tracking system

The awareness of the energy and climate crisis has accelerated the development of renewable energy sources. Photovoltaic (PV) solar power plants harvest clean solar energy and convert it to electricity, which will be one of the most promising alternatives to the power industry in the context of a low-carbon society. Due to its low power density, the traditional deployment of PV systems on land or inland rivers requires much space. Therefore, industries are increasingly interested in expanding offshore Floating PhotoVoltaics (FPV) to oceans, where FPV has less influence on the marine environment and does not occupy precious space for land resources and human activities. This study performs a hydrodynamics-based structural response analysis for a novel FPV system in OpenFOAM. The wave-proof FPV platform is newly designed for this work, which integrated breakwater technologies to sustain the system’s survivability in harsh ocean-wave environments. Firstly, the rational mooring types for FPVs installed close to the island are studied considering seabed effects. Subsequently, extensive parametric studies have been conducted to determine a rational design strategy for the mitigation of wave impact. Several potential effects of the proposed platforms on the hydrodynamics in a coastal sea are evaluated for the first time.

Barrier identification and prioritisation for the deployment of solar photovoltaic systems in dairy farming in India using the ISM–MICMAC approach

ABSTRACT Dairy farming needs a strong foundation of energy security in rural India for its sustainability. Solar Photovoltaic (PV) systems in dairy farming act as a catalyst to ensure Green Energy Measures (GEMs) and to achieve the various missions of the Indian Government. The deployment of solar PV systems to fulfil energy needs in Indian dairy farming has several issues and barriers. In this investigation, various foremost barriers creating hindrances in deployment of PV systems in Indian dairy farms have been identified. Contextual relationships between identified barriers have been established by Interpretive Structural Modelling (ISM) and classified using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC). It is used to determine the ranks and types of hindrances and to develop a structural model. The strongest driving force barriers are high initial capital cost, storage devices barrier, policy and regulatory issues, less education and weak affordability in rural and long payback periods. The strongest dependent force barriers include societal acceptance, fewer concerns about ecological and environmental issues, and a lack of entrepreneurs and innovations in the rural sector. Finally, the future roadmap to address the obstacles in exploitation of PV systems in context of dairy sector has been described.

Energy performance evaluation for a floating photovoltaic system located on the reservoir of a hydro power plant under the mediterranean climate conditions during a sunny day and a cloudy-one

• The world’s biggest Floating Photovoltaic unit of its kind is considered. • Floating membrane is used as the floating technology. • Values of final yield, performance ratio, and system efficiency are estimated. • Performance data during a clear day and a cloudy one are compared. Deployment of photovoltaic systems on water bodies unlocks enormous areas in populated regions. Also, their utilization will create the possibility to increase the share of photovoltaics systems related to the energy transition. There is little information regarding the available data for floating photovoltaic systems (FPVS). The positive effect of water on cooling the photovoltaic modules should be considered, also. This study is performed by utilizing experimental data from a field test located in a region having Mediterranean Climate Conditions. It is a newly installed FPVS with an installed capacity of 0.5 MW p DC. The unit is the world’s biggest of its configuration referred to the installed capacity and its diameter. Results include the energy yield, final yield, performance ratio, capacity factor, and system efficiency. They refer to a daily period during sunny and cloudy days and offer a clear view regarding the system operation. For the considered sunny and cloudy days, it is noticed that the daily final yields are 7.289 kWh/(kW p ·day) and 3.572 kWh/(kW p ·day), respectively. The daily performance ratio is 86.9% (sunny day) and 89.8% (cloudy day). Also, the daily system efficiency in the selected days are 17.4% and 17.9%, respectively.

Modeling and Implementation of Photovoltaic Modules for a DC-DC Boost Converter

A photovoltaic (PV) system is a renewable energy system intended to convert sunlight into the usable electricity. Due to the rapid world infrastructure development, the demand for electricity is increasing drastically. One of the promising energy resources is the PV. The required energy demand can be provided by the increase of PV system deployment. Thus, as part of the design, development and implementation of a new PV system, a system design simulation is essential. This is to ensure that the designed system works properly according to design specifications. For this reason, a PV mathematical model is necessary in the development process of the PV system especially in the MATLAB/Simulink software environment. With the developed PV model, the PV system design and simulation is made handy, thus escalates the future energy demand. This work describes the development of the PV mathematical model in the MATLAB/Simulink software environment based on the PV related equations. The equations are formed by the consideration of the equivalent circuit of PV cell. The developed PV model characteristics such as the Power-Voltage (P-V) and Current-Voltage (I-V) curves are obtained as the simulation output in MATLAB/Simulink. The obtained characteristics are compared to the actual PV model A 100W RNG-50D Renogy, as to verify the effectiveness and closeness of the developed PV model to the real PV module. In addition, in the simulation, a dc-dc boost converter is also designed and integrated with the PV model as to verify the PV module and capability as a PV power source. The simulation results with the dc-dc boost converter DC-DC integration have shown that the developed PV model is very effective to be used for the PV system simulation.

Medium voltage consumers’ cost evaluation connected to a micro-grid PV system

The increase in the deployment of photovoltaic systems has brought a change to the national grid and directly influences the energy charges applied by the utilities. Different types of tariffs are applied to consumers for electrical energy. These tariffs differ according to the level of voltages that are supplied to the customers. The low voltage applies to household customers and some small businesses, while the medium voltage grid supplies the industries using voltages higher than that of low voltages. In South Africa, the medium voltage grid-tied solar photovoltaic customers can operate a network that generates up to 100MW of power from their solar systems without a licence. However, the tariffs that apply to such customers are the same as those who do not have solar systems since operating without a licence does not permit feeding power back to the grid. Many industries use medium voltages, and it is crucial to evaluate the cost-effective tariffs for medium voltages with a solar system. This paper uses consumption data to verify the type of tariffs that result in lower energy charges. It was found that the large power user tariffs result in higher energy charges than the time of use tariffs during holidays and weekends and vice versa during weekdays. However, the paper concludes that the time of use tariffs can lower energy costs if applied in a grid-tied solar system with battery storage, provided that the batteries supply power during peak hours.

Estimation of future changes in photovoltaic potential in Australia due to climate change

Solar photovoltaic (PV) energy is one of the fastest growing renewable energy sources globally. However, the dependency of PV generation on climatological factors such as the intensity of radiation, temperature, wind speed, cloud cover, etc can impact future power generation capacity. Considering the future large-scale deployment of PV systems, accurate climate information is essential for PV site selection, stable grid regulation, planning and energy output projections. In this study, the long-term changes in the future PV potential are estimated over Australia using regional climate projections for the near-future (2020–2039) and far-future (2060–2079) periods under a high emission scenario that projects 3.4 °C warming by 2100. The effects of projected changes in shortwave downwelling radiation, temperature and wind speed on the future performance of PV systems over Australia is also examined. Results indicate decline in the future PV potential over most of the continent due to reduced insolation and increased temperature. Northern coastal Australia experiences negligible increase in PV potential during the far future period due to increase in radiation and wind speed in that region. On further investigation, we find that the cell temperatures are projected to increase in the future under a high emission scenario (2.5 °C by 2079), resulting in increased degradation and risks of failure. The elevated cell temperatures significantly contribute to cell efficiency losses, that are expected to increase in the future (6–13 d yr−1 for multi-crystalline silicon cells) mostly around Western and central Australia indicating further reductions in PV power generation. Therefore, long-term PV power projections can help understand the variations in future power generation and identify regions where PV systems will be highly susceptible to losses in Australia.

Degradation analysis of installed solar photovoltaic (PV) modules under outdoor conditions in Ghana

Photovoltaic (PV) module degradation rate depends on technology, manufacturer and environmental conditions. This makes it challenging to transfer the results of degradation analysis from one country to another. Thus, the increase in deployment of PV systems in Ghana makes degradation analysis a necessity. This study quantified the degradation rates and predicted the lifetime of 16 PV systems of different module technologies and age groups installed in different locations under outdoor conditions in Ghana to provide a better understanding of the long-term behavior of installed PV systems in Ghana. It presented the frequency distribution of output power degradation of different PV module technologies, estimated their power degradation rates, and predicted and compared the lifetime of these technologies. The country was grouped into three strata and 104 PV modules of different technologies which were older than 5 years were selected from 16 PV systems in these strata, depending on availability and accessibility. The electrical parameters of the PV modules were measured by current–voltage (IV) tracing. The results revealed that crystalline silicon modules degraded less than amorphous silicon. The median and mean power degradation rates of, monocrystalline silicon were 1.23%/year and 1.37%/year respectively, polycrystalline silicon were 1.35%/year and 1.44%/year respectively and, amorphous silicon were 1.65%/year and 1.67%/year respectively. Overall, the median and mean predicted lifetime of the PV systems (crystalline and amorphous silicon) were 14 year and 16 years respectively but the median lifetime of both monocrystalline and polycrystalline modules was 16 years while that of amorphous was 13 years. It was predicted that 50% of PV modules studied would fail before 15 years, indicating that most of the PV modules in Ghana are unlikely to operate for the 25 years warranty, signifying less power output and shorter lifetime of the modules which could discourage the widespread implementation of PV systems in Ghana.

Spatiotemporal Graph Neural Network for Performance Prediction of Photovoltaic Power Systems

In recent years, a large number of photovoltaic (PV) systems have been added to the electrical grid as well as installed as off-grid systems. The trend suggests that the deployment of PV systems will continue to rise in the future. Thus, accurate forecasting of PV performance is critical for the reliability of PV systems. Due to the complex non-linear variability in power output of the PV systems, forecasting PV power is a non-trivial task. This variability affects the stability and planning of a power system network, and accurate forecasting of the performance of the PV system can reduce the uncertainty caused during PV operation. In this work, we leverage spatial and temporal coherence among the power plants for PV power forecasting. Our approach is motivated by the observation that power plants in a region undergo similar environmental exposure. Thus, one power plant’s performance can help improve the forecast of other power plants' power values in the region. We utilize the relationship between PV plants to build a spatiotemporal graph neural network (st-GNN) and train machine learning models to forecast the PV power. The computational experiments on large-scale data from a network of 316 systems show that spatiotemporal forecasting of PV power performs significantly better than a model that only applies temporal convolution to isolated systems or nodes. Furthermore, the longer the future forecast time, the difference between the spatiotemporal forecasting and the isolated system forecast when only temporal convolution is applied increases further.

Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities

The demand for renewable energy generation, especially photovoltaic (PV) power generation, has been growing over the past few years. However, the amount of generated energy by PV systems is highly dependent on weather conditions. Therefore, accurate forecasting of generated PV power is of importance for large-scale deployment of PV systems. Recently, machine learning (ML) methods have been widely used for PV power generation forecasting. A variety of these techniques, including artificial neural networks (ANNs), ridge regression, K-nearest neighbour (kNN) regression, decision trees, support vector regressions (SVRs) have been applied for this purpose and achieved good performance. In this paper, we briefly review the most recent ML techniques for PV energy generation forecasting and propose a new regression technique to automatically predict a PV system’s output based on historical input parameters. More specifically, the proposed loss function is a combination of three well-known loss functions: Correntropy, Absolute and Square Loss which encourages robustness and generalization jointly. We then integrate the proposed objective function into a Deep Learning model to predict a PV system’s output. By doing so, both the coefficients of loss functions and weight parameters of the ANN are learned jointly via back propagation. We investigate the effectiveness of the proposed method through comprehensive experiments on real data recorded by a real PV system. The experimental results confirm that our method outperforms the state-of-the-art ML methods for PV energy generation forecasting.

Shading on Photovoltaic Collectors on Rooftops

Rooftop photovoltaic (PV) systems in urban environments play an important role in solar electric energy generation. Shading on PV collectors, by self-shading, walls and fences on rooftops, affect negatively the output energy of the PV systems. Increasing the distance between the collector rows, and between the walls and fences near to the collectors, may minimize the shading losses. Practically, this option is usually limited, especially on rooftops. Rooftops may be of different types: horizontal, inclined, and saw-tooth, and may have obscuring structures like walls and fences. The distance between the shading objects and the PV collector rows determine the loss of energy due to shading. The study provides the PV system designer with mathematical expressions for distances from obscuring objects for the deployment of PV systems on rooftops. The optimal inclination and azimuths angles of a PV system on a triangular sloped rooftop are also illustrated.

Interview

Shamsodin Taheri Shamsodin Taheri, from the University of Quebec Outaouais, Canada, talks to us about his group's submission “Analysis of electrical behaviour of PV arrays covered with nonuniform snow” page 192. I am an Associate Professor of Electrical Engineering in the Department of Computer Science and Engineering at the Université du Québec en Outaouais (UQO). The expertise of my research group in the field of power energy has advanced our understanding of the performance of photovoltaic (PV) sources in cold-climate conditions. This research was inspired by the issues that PV plants in Canada experience during cold months. In recent years, we have collaborated with several industry partners, who own utility-scale PV plants, to evaluate the performance of their facilities. This ongoing research helps mitigate the technical challenges facing the integration of renewable energy sources into power grids in cold regions. PV systems have found different applications in cold areas for a long time, such as remote research facilities in the South and North Poles and space travelling. The majority of PV energy plants are presently installed in geographical cold locations with a considerable amount of snowfall every year. Furthermore, the solar energy industry is expanding competitively in cold climate regions. For example, in Canada, the installed capacity of solar PV grew from 95 MW to more than 2500 MW during 2009–2016. PV panel efficiency is not only influenced by PV technology, but environmental conditions can also influence their energy production. Accumulation of snow/ice decreases solar radiation reaching the PV panels, which results in a significant loss of power generation. Non-uniform snow accretion on PV panels often occurs due to ambient conditions such as wind, temperature variation, partial snow shedding and ground interference. This leads to power loss that is dependent on the configuration of the PV system. Owing to the increasing deployment of PV systems, there is a significant interest in optimal utilisation of PV potential in cold climate regions. A fundamental need for knowledge of the impact of nonuniform snow accretion on PV systems is therefore essential. This research has shown that the snow-covered PV panels can still produce a significant amount of energy depending on the pattern and depth of the snow accumulation. The portion of this energy that could be collected is decided by configuration of the PV array as well as the maximum power point tracking (MPPT) technique. Investigations concerning the effect of bypass diodes have shown that the PV string without bypass diodes generally experiences more power loss. In addition, the vertical and horizontal PV array layouts were tested to determine power loss due to nonuniform snow accretion. The horizontal PV array layout would be more effective in snowy climates. This work is helpful for PV system performance assessment, MPPT development and testing, power generation prediction, and proper arrangement of panels in cold regions. The accumulation of snow on PV modules weakens the intensity of incoming solar radiation and hence limits their ability to generate electricity during cold months. However, the true extent of such impact on the energy production of PV modules cannot be specified in a straightforward way, since it is not proportional to the snow-covered area. In some instances, snow covering only one cell can reduce the efficiency of a whole module by a noticeable amount. Snow is a complex phenomenon, and a quantitative characterisation of radiation transmittance through snow coverage requires knowledge of the physical properties of snow. In fact, the interaction of sunlight with snow to determine the influence of snow coverage on the PV modules is a challenge. This leads to changing the electrical characteristics of the PV array and producing multiple, local peaks on PV characteristics. Accurate modelling of the electric behaviour of PV modules and systems is a key element in improving system operation and efficiency. Hence, proper modelling approaches of the operation of PV generators under varying environmental conditions that improve their performance control and assist the design of PV converters and their MPPT controller have been achieved. Moreover, an appropriate tool has been proposed to determine the efficiency of PV farms under cold conditions. Furthermore, a high performance MPPT technique has been proposed to harvest the maximum energy of a PV array with multipeak characteristic under partial shading condition. Major progress must be made on the proper design and arrangement of PV arrays and power electronic interfaces, minimising the effects of snow on large-scale PV farms and the increasing the use of bifacial PV modules as a candidate for cold regions over the next ten years.

Global Climate Data Processing and Mapping of Degradation Mechanisms and Degradation Rates of PV Modules

Photovoltaic (PV) systems are the cheapest source of electricity in sunny locations and nearly all European countries. However, the fast deployment of PV systems around the world is bringing uncertainty to the PV community in terms of the reliability and long-term performance of PV modules under different climatic stresses, such as irradiation, temperature changes, and humidity. Methodologies and models to estimate the annual degradation rates of PV modules have been studied in the past, yet, an evaluation of the issue at global scale has not been addressed so far. Hereby, we process the ERA5 climate re-analysis dataset to extract and model the climatic stresses necessary for the calculation of degradation rates. These stresses are then applied to evaluate three degradation mechanisms (hydrolysis-degradation, thermomechanical-degradation, and photo- degradation) and the total degradation rate of PV modules due to the combination of temperature, humidity, and ultraviolet irradiation. Further on, spatial distribution of the degradation rates worldwide is computed and discussed proving direct correlation with the Köppen-Geiger-Photovoltaic climate zones, showing that the typical value considered for the degradation rate on PV design and manufacturer warranties (i.e., 0.5%/a) can vary ± 0.3%/a in the temperate zones of Europe and rise up to 1.5%/a globally. The mapping of degradation mechanisms and total degradation rates is provided for a monocrystalline silicon PV module. Additionally, we analyze the temporal evolution of degradation rates, where a global degradation rate is introduced and its dependence on global ambient temperature demonstrated. Finally, the categorization of degradation rates is made for Europe and worldwide to facilitate the understanding of the climatic stresses.

Potential for Rooftop-Mounted PV Power Generation to Meet Domestic Electrical Demand in Saudi Arabia: Case Study of a Villa in Jeddah

The Kingdom of Saudi Arabia (KSA) has a large solar and wind energy resource. Through its Vision 2030 to exploit such resources, KSA is planning to install 9.5 GW of renewable energy power generation systems by 2030, through a mix of solar and wind energy. The government is planning to invest 109 billion US$ over the next 20 years for solar energy. The focus will be on solar photovoltaic (PV) and concentrated solar technologies at a national level. So far, the electricity demand in KSA is almost entirely dependent on fossil fuels for generating power. This paper addresses the potential to utilize the solar radiation resource at a different scale and reduce the power demand from the grid, bringing collateral benefits for householders and the government alike. The work presents the results from monitoring the electricity consumption of two typical domestic buildings (villas) in Jeddah, KSA. The electricity consumption observations were associated with indoor environmental conditions to study how and when cooling demand affects final demand. The study investigated options to serve the observed demand profile of the villas with simulated power generation from arrays of PV panels installed on two buildings’ roofs. Finally, a model of dynamic solar radiation simulation was developed to assess the hourly electricity generation, and a cost-benefit analysis was conducted for different capacity PV systems scenarios. The results indicate that locally used rooftop PV output could reduce the household electrical demand from the grid by around 80% at the housing level and in combination with building refurbishment solutions, could result in additional energy savings. The economic analysis discusses the implications of a proposed feed-in tariff with the associated payback periods and ROI, as well as proposals for PV system deployment at a large scale on the roof of buildings in KSA.

Reactive power management to enhance solar energy penetration in small grids: technical and framework approaches

In the last few years, rising environmental concerns and especially, cost reductions that photovoltaic technology has experienced, have led to an unprecedented increase in the deployment of photovoltaic systems all over the world. Although nowadays most of the installed photovoltaic capacity is due to utility-scale plants, medium-and small-scale plants connected to distribution systems are becoming increasingly more frequent. Distribution networks were originally designed assuming a centralized operation, and the growing penetration of distributed generators is arising both technical and regulatory issues. In this work, we summarize different approaches from the technical and framework point of view. Key words.

Data-Driven Probabilistic Power Flow Analysis for a Distribution System With Renewable Energy Sources Using Monte Carlo Simulation

This paper investigates the effect of uncertainty in the allocation of photovoltaic (PV) generation, solar irradiance, and its impact on the power flow in a distribution network. The solar irradiance available in the National Renewable Energy Laboratory Resource Data Center is clustered into two states: high and low irradiance defined by a threshold. The uncertainty is modeled based on Non-Gaussian distribution, obtained using kernel density estimation. This estimation aids in achieving the probability density function and cumulative distribution functions of the solar irradiance. Moreover, the load demand, wind speed, and generator location are modeled according to Gaussian, Weibull, and discrete uniform distribution functions, respectively. As a part of probabilistic power flow, the backward/forward sweep method is used to solve each scenario of the Monte Carlo simulation. The proposed framework is applied to the 33-node test system considering three different test cases. The first case considers deployment of PV systems in three microgrids of the electric grid, and the other two test cases analyze different levels of penetration of randomly allocated PV and wind power systems. At the end, the results indicate potential reverse power flow through certain branches of the grid, and the renewables have a major impact on the system.

Hierarchical Look-Ahead Conservation Voltage Reduction Framework Considering Distributed Energy Resources and Demand Reduction

This paper proposes a hierarchical look-ahead framework to conduct conservation voltage reduction (CVR) when distributed energy resources such as solar photovoltaic (PV) systems and energy storage systems (ESSs), and demand response programs are integrated into distribution systems. With the increasing deployment of PV systems in distribution systems, their frequently varying power output due to cloud movements could have a detrimental impact on the consumer’s voltage quality, consequently leading to degraded CVR performance. A two-level CVR framework for the coordination of an on-load tap changer (OLTC), capacitor banks (CBs), and the smart inverters of PV systems/ESSs is presented, in which these elements operate to reduce the voltage profile along the distribution feeder at different temporal scales. At the global level, the operations of the OLTC and the CBs are scheduled every hour to achieve the best CVR performance in an optimization problem using mixed-integer linear programming. When voltage violations occur rapidly, the smart inverters of PV systems and ESSs help to maintain a lower voltage profile every second based on the proposed piecewise droop control functions at the local level. A simulation study is carried out in an IEEE 33-bus distribution system with an OLTC, CBs, PV systems, and ESSs, and our results demonstrate the advantages of the proposed approach in terms of voltage level and energy savings. Furthermore, the impact of demand reduction on the proposed approach is quantified, and we verify that a higher demand reduction yields more energy savings in the proposed framework.

Highlight of Grid-connected PV systems in administrative buildings in Egypt

Solar energy applications are becoming increasingly common in Egypt. The abundant sunshine in Egypt, as well as the increasing competitiveness of solar energy systems including- but not limited to photovoltaic (PV), – predicts that these technologies could be weighed to be raised in Egypt. PV systems are installed on roof tiles or other parts of building structures to supplement grid utility, reduce electric bills, and provide emergency back–up energy. Moreover, they simultaneously reduce significant amounts of CO 2 emissions. It is foreseen, a number of residential and public buildings in Egypt are using solar power to cut electric utility bills significantly. The approximately payback period to recover the investment costs for PV systems is up to about 5 years. In addition, it is more economical to use PV system than grid utility systems. The two components that determine the total initial price of a grid- connected PV system are the modules and the balance of systems (BOS). The BOS includes different components such as mounting frames, inverters and site- specific installation hardware. The Government of Egypt (GOE) has endorsed the deployment of PV systems through three approaches. It started with a prime minister decree to install PV projects on one-thousand of the governmental buildings. This was followed by as an initiative called "Shamsk ya Masr", and finally the Feed-in Tariff (FiT) projects. Following the prime minster decree the Egyptian Electricity Holding Company (EEHC) and its affiliated companies took the lead to install PV systems at the top roof of their administrative buildings and interconnect these systems to the electricity network where the suitable locations have been selected for mounting them. About 90 PV systems have been already mounted with about a capacity of 9 MW. On the other hand, "Shamsk ya Masr" has considered energy efficiency (EE) so as to complement the PV systems, which will be installed on administrative buildings. Cost- effective EE measures should be implemented prior to or at the same time as implemented PV program. The amount of electricity that a PV system produces depends on the system type, orientation and the available solar resource. In 2014, the GOE issued the Feed-in Tariff program to further promote RE technologies in general and PV in particular. Egyptian Electric Utility and Consumer Protection Regulatory Authority (Egypt ERA) has set the regulations, promotion and awareness for PVs. This approach has been applied for administrative buildings as well. The paper highlights the impact of the previously mentioned mechanisms in deploying PV technologies through small scale projects. It also represents a cost- benefit analysis for the installed systems taking into account the measured value for PV parameters (kWh/kWp, PSH) and daily load profiles of the selected administrative buildings.

A novel climate classification criterion based on the performance of solar photovoltaic technologies

The response of solar photovoltaic (PV) technologies with respect to environmental parameters is governed by the physical and chemical properties of the PV material. The PV modules are being tested under standard test conditions (STC), however, these conditions are hardly available in real operating conditions, of the locations where the PV modules are supposed to be operational. Therefore, the performance of PV power plant varies with the environmental conditions of the location and technology of the PV module. In this paper, seven climatic zones have been proposed for India, based on the annual daytime irradiance and ambient temperature specifically for the deployment of PV system. A novel methodology has been proposed in order to identify the most efficient PV technology for a particular climatic zone. The parametric study of efficiency for four different technologies i.e. multi- crystalline silicon (m-Si), amorphous silicon (a-Si), cadmium telluride (CdTe), and hetero junction intrinsic thin film (HIT), has also been evaluated with respect to the irradiance and ambient temperature based on the indoor measurements. The m-Si PV technology is found to be most efficient in all the irradiance range, while CdTe technology has the lowest impact of temperature with high efficiency at lower irradiance range.